xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

1c15b634ddb263d20add136ebc95c1405585f3a8

14,133

py

Python

stumpy/mpdist.py

mexxexx/stumpy

dcfa14b98aee375da4239363c1d2a6520fb54e80

[ "BSD-3-Clause" ]

null

stumpy/mpdist.py

mexxexx/stumpy

dcfa14b98aee375da4239363c1d2a6520fb54e80

[ "BSD-3-Clause" ]

null

stumpy/mpdist.py

mexxexx/stumpy

dcfa14b98aee375da4239363c1d2a6520fb54e80

[ "BSD-3-Clause" ]

null

# STUMPY # Copyright 2019 TD Ameritrade. Released under the terms of the 3-Clause BSD license. # STUMPY is a trademark of TD Ameritrade IP Company, Inc. All rights reserved. import numpy as np import math from . import stump, stumped, core from .core import _mass_distance_matrix from .aampdist import aampdist, aampdisted def _compute_P_ABBA( T_A, T_B, m, P_ABBA, dask_client=None, device_id=None, mp_func=stump ): """ A convenience function for computing the (unsorted) concatenated matrix profiles from an AB-join and BA-join for the two time series, `T_A` and `T_B`. This result can then be used to compute the matrix profile distance (MPdist) measure. The MPdist distance measure considers two time series to be similar if they share many subsequences, regardless of the order of matching subsequences. MPdist concatenates and sorts the output of an AB-join and a BA-join and returns the value of the `k`th smallest number as the reported distance. Note that MPdist is a measure and not a metric. Therefore, it does not obey the triangular inequality but the method is highly scalable. Parameters ---------- T_A : ndarray The first time series or sequence for which to compute the matrix profile T_B : ndarray The second time series or sequence for which to compute the matrix profile m : int Window size P_ABBA : ndarray The output array to write the concatenated AB-join and BA-join results to dask_client : client, default None A Dask Distributed client that is connected to a Dask scheduler and Dask workers. Setting up a Dask distributed cluster is beyond the scope of this library. Please refer to the Dask Distributed documentation. device_id : int or list, default None The (GPU) device number to use. The default value is `0`. A list of valid device ids (int) may also be provided for parallel GPU-STUMP computation. A list of all valid device ids can be obtained by executing `[device.id for device in numba.cuda.list_devices()]`. mp_func : object, default stump Specify a custom matrix profile function to use for computing matrix profiles Returns ------- None Notes ----- `DOI: 10.1109/ICDM.2018.00119 \ <https://www.cs.ucr.edu/~eamonn/MPdist_Expanded.pdf>`__ See Section III """ n_A = T_A.shape[0] partial_mp_func = core._get_partial_mp_func( mp_func, dask_client=dask_client, device_id=device_id ) P_ABBA[: n_A - m + 1] = partial_mp_func(T_A, m, T_B, ignore_trivial=False)[:, 0] P_ABBA[n_A - m + 1 :] = partial_mp_func(T_B, m, T_A, ignore_trivial=False)[:, 0] def _select_P_ABBA_value(P_ABBA, k, custom_func=None): """ A convenience function for returning the `k`th smallest value from the `P_ABBA` array or use a custom function to specify what `P_ABBA` value to return. The MPdist distance measure considers two time series to be similar if they share many subsequences, regardless of the order of matching subsequences. MPdist concatenates and sorts the output of an AB-join and a BA-join and returns the value of the `k`th smallest number as the reported distance. Note that MPdist is a measure and not a metric. Therefore, it does not obey the triangular inequality but the method is highly scalable. Parameters ---------- P_ABBA : ndarray A pre-sorted array resulting from the concatenation of the outputs from an AB-joinand BA-join for two time series, `T_A` and `T_B` k : int Specify the `k`th value in the concatenated matrix profiles to return. This parameter is ignored when `k_func` is not None. custom_func : object, default None A custom user defined function for selecting the desired value from the sorted `P_ABBA` array. This function may need to leverage `functools.partial` and should take `P_ABBA` as its only input parameter and return a single `MPdist` value. The `percentage` and `k` parameters are ignored when `custom_func` is not None. Returns ------- MPdist : float The matrix profile distance """ k = min(int(k), P_ABBA.shape[0] - 1) if custom_func is not None: MPdist = custom_func(P_ABBA) else: MPdist = P_ABBA[k] if ~np.isfinite(MPdist): k = max(0, np.count_nonzero(np.isfinite(P_ABBA[:k])) - 1) MPdist = P_ABBA[k] return MPdist def _mpdist( T_A, T_B, m, percentage=0.05, k=None, dask_client=None, device_id=None, mp_func=stump, custom_func=None, ): """ A convenience function for computing the matrix profile distance (MPdist) measure between any two time series. The MPdist distance measure considers two time series to be similar if they share many subsequences, regardless of the order of matching subsequences. MPdist concatenates and sorts the output of an AB-join and a BA-join and returns the value of the `k`th smallest number as the reported distance. Note that MPdist is a measure and not a metric. Therefore, it does not obey the triangular inequality but the method is highly scalable. Parameters ---------- T_A : ndarray The first time series or sequence for which to compute the matrix profile T_B : ndarray The second time series or sequence for which to compute the matrix profile m : int Window size percentage : float, 0.05 The percentage of distances that will be used to report `mpdist`. The value is between 0.0 and 1.0. This parameter is ignored when `k` is not `None` or when `k_func` is not None. k : int, default None Specify the `k`th value in the concatenated matrix profiles to return. When `k` is not `None`, then the `percentage` parameter is ignored. This parameter is ignored when `k_func` is not None. dask_client : client, default None A Dask Distributed client that is connected to a Dask scheduler and Dask workers. Setting up a Dask distributed cluster is beyond the scope of this library. Please refer to the Dask Distributed documentation. device_id : int or list, default None The (GPU) device number to use. The default value is `0`. A list of valid device ids (int) may also be provided for parallel GPU-STUMP computation. A list of all valid device ids can be obtained by executing `[device.id for device in numba.cuda.list_devices()]`. mp_func : object, default stump Specify a custom matrix profile function to use for computing matrix profiles custom_func : object, default None A custom user defined function for selecting the desired value from the sorted `P_ABBA` array. This function may need to leverage `functools.partial` and should take `P_ABBA` as its only input parameter and return a single `MPdist` value. The `percentage` and `k` parameters are ignored when `custom_func` is not None. Returns ------- MPdist : float The matrix profile distance Notes ----- `DOI: 10.1109/ICDM.2018.00119 \ <https://www.cs.ucr.edu/~eamonn/MPdist_Expanded.pdf>`__ See Section III """ n_A = T_A.shape[0] n_B = T_B.shape[0] P_ABBA = np.empty(n_A - m + 1 + n_B - m + 1, dtype=np.float64) _compute_P_ABBA(T_A, T_B, m, P_ABBA, dask_client, device_id, mp_func) P_ABBA.sort() if k is not None: k = min(int(k), P_ABBA.shape[0] - 1) else: percentage = min(percentage, 1.0) percentage = max(percentage, 0.0) k = min(math.ceil(percentage * (n_A + n_B)), n_A - m + 1 + n_B - m + 1 - 1) MPdist = _select_P_ABBA_value(P_ABBA, k, custom_func) return MPdist def _mpdist_vect( Q, T, m, distance_matrix_func=_mass_distance_matrix, percentage=0.05, k=None, custom_func=None, ): """ Compute the matrix profile distance measure vector between `Q` and each subsequence, `T[i : i + len(Q)]`, within `T`. Parameters ---------- Q : ndarray Query array T : ndarray Time series or sequence m : int Window size distance_matrix_func : object, default _mass_distance_matrix The function to use to compute the distance matrix between `Q` and `T` percentage : float, 0.05 The percentage of distances that will be used to report `mpdist`. The value is between 0.0 and 1.0. This parameter is ignored when `k` is not `None` or when `k_func` is not None. k : int, default None Specify the `k`th value in the concatenated matrix profiles to return. When `k` is not `None`, then the `percentage` parameter is ignored. This parameter is ignored when `k_func` is not None. custom_func : object, default None A custom user defined function for selecting the desired value from the sorted `P_ABBA` array. This function may need to leverage `functools.partial` and should take `P_ABBA` as its only input parameter and return a single `MPdist` value. The `percentage` and `k` parameters are ignored when `custom_func` is not None. """ j = Q.shape[0] - m + 1 # `k` is reserved for `P_ABBA` selection l = T.shape[0] - m + 1 MPdist_vect = np.empty(T.shape[0] - Q.shape[0] + 1) distance_matrix = np.full((j, l), np.inf) P_ABBA = np.empty(2 * j) if k is None: percentage = min(percentage, 1.0) percentage = max(percentage, 0.0) k = min(math.ceil(percentage * (2 * Q.shape[0])), 2 * j - 1) k = min(int(k), P_ABBA.shape[0] - 1) distance_matrix_func(Q, T, m, distance_matrix) rolling_row_min = core.rolling_nanmin(distance_matrix, j) col_min = np.nanmin(distance_matrix, axis=0) for i in range(MPdist_vect.shape[0]): P_ABBA[:j] = rolling_row_min[:, i] P_ABBA[j:] = col_min[i : i + j] P_ABBA.sort() MPdist_vect[i] = _select_P_ABBA_value(P_ABBA, k, custom_func) return MPdist_vect @core.non_normalized(aampdist) def mpdist(T_A, T_B, m, percentage=0.05, k=None, normalize=True): """ Compute the z-normalized matrix profile distance (MPdist) measure between any two time series The MPdist distance measure considers two time series to be similar if they share many subsequences, regardless of the order of matching subsequences. MPdist concatenates and sorts the output of an AB-join and a BA-join and returns the value of the `k`th smallest number as the reported distance. Note that MPdist is a measure and not a metric. Therefore, it does not obey the triangular inequality but the method is highly scalable. Parameters ---------- T_A : ndarray The first time series or sequence for which to compute the matrix profile T_B : ndarray The second time series or sequence for which to compute the matrix profile m : int Window size percentage : float, default 0.05 The percentage of distances that will be used to report `mpdist`. The value is between 0.0 and 1.0. normalize : bool, default True When set to `True`, this z-normalizes subsequences prior to computing distances. Otherwise, this function gets re-routed to its complementary non-normalized equivalent set in the `@core.non_normalized` function decorator. Returns ------- MPdist : float The matrix profile distance Notes ----- `DOI: 10.1109/ICDM.2018.00119 \ <https://www.cs.ucr.edu/~eamonn/MPdist_Expanded.pdf>`__ See Section III """ return _mpdist(T_A, T_B, m, percentage, k, mp_func=stump) @core.non_normalized(aampdisted) def mpdisted(dask_client, T_A, T_B, m, percentage=0.05, k=None, normalize=True): """ Compute the z-normalized matrix profile distance (MPdist) measure between any two time series with a distributed dask cluster The MPdist distance measure considers two time series to be similar if they share many subsequences, regardless of the order of matching subsequences. MPdist concatenates and sorts the output of an AB-join and a BA-join and returns the value of the `k`th smallest number as the reported distance. Note that MPdist is a measure and not a metric. Therefore, it does not obey the triangular inequality but the method is highly scalable. Parameters ---------- dask_client : client A Dask Distributed client that is connected to a Dask scheduler and Dask workers. Setting up a Dask distributed cluster is beyond the scope of this library. Please refer to the Dask Distributed documentation. T_A : ndarray The first time series or sequence for which to compute the matrix profile T_B : ndarray The second time series or sequence for which to compute the matrix profile m : int Window size percentage : float, default 0.05 The percentage of distances that will be used to report `mpdist`. The value is between 0.0 and 1.0. This parameter is ignored when `k` is not `None`. k : int Specify the `k`th value in the concatenated matrix profiles to return. When `k` is not `None`, then the `percentage` parameter is ignored. normalize : bool, default True When set to `True`, this z-normalizes subsequences prior to computing distances. Otherwise, this function gets re-routed to its complementary non-normalized equivalent set in the `@core.non_normalized` function decorator. Returns ------- MPdist : float The matrix profile distance Notes ----- `DOI: 10.1109/ICDM.2018.00119 \ <https://www.cs.ucr.edu/~eamonn/MPdist_Expanded.pdf>`__ See Section III """ return _mpdist(T_A, T_B, m, percentage, k, dask_client=dask_client, mp_func=stumped)

35.870558

88

0.675157

2,160

14,133

4.323611

0.124537

0.019274

0.015419

0.024628

0.82632

0.806403

0.797409

0.790556

0.784559

0.767855

0

0.01429

0.252317

14,133

393

89

35.961832

0.869499

0.725607

0

0.341463

0

1

0.073171

false

0

0.060976

0

0.195122

0

null

0

1

0

null

0

6

1c35aa1277ffe802f90bac0cd78c1c4a49041400

69,352

py

Python

hack/test_errata.py

Davoska/cincinnati-graph-data

3bc79fdcefa72f570e0757c0bfd46d4302543264

[ "Apache-2.0" ]

null

hack/test_errata.py

Davoska/cincinnati-graph-data

3bc79fdcefa72f570e0757c0bfd46d4302543264

[ "Apache-2.0" ]

null

hack/test_errata.py

Davoska/cincinnati-graph-data

3bc79fdcefa72f570e0757c0bfd46d4302543264

[ "Apache-2.0" ]

null

import copy import datetime import os import tempfile import unittest import urllib from unittest.mock import MagicMock from unittest.mock import patch import errata class GithubUserMock(): def __init__(self, login): self.login = login class GithubLabelMock(): def __init__(self, name): self.name = name class GithubPRMock: def __init__(self, user, title, labels=[], number=0, body="", url="", html_url=""): self.user = user self.title = title self.labels = labels self.number = number self.body = body self.url = url self.html_url = html_url self.create_issue_comment = MagicMock() def __eq__(self, other): if not isinstance(other, GithubPRMock): return False return self.user == other.user \ and self.title == other.title \ and self.labels == other.labels \ and self.number == other.number \ and self.body == other.body \ and self.url == other.url \ and self.html_url == other.html_url class ExtractErrataNumberFromBodyTest(unittest.TestCase): def test_url_starting_with_valid_errata_marker(self): """ Test errata number extraction from valid URLs. URLs starting with corresponding ERRATA_MARKER in errata.py. """ param_list = [ ('https://errata.devel.redhat.com/advisory/12345', 12345), ('https://errata.devel.redhat.com/advisory/67890', 67890), ('https://errata.devel.redhat.com/advisory/13579', 13579), ('https://errata.devel.redhat.com/advisory/24680', 24680), ('https://errata.devel.redhat.com/advisory/', None), ('https://errata.devel.redhat.com/advisory/invalid', None) ] for (url, expected) in param_list: with self.subTest(url=url): self.assertEqual(errata.extract_errata_number_from_body(url), expected) def test_invalid_url(self): """ Test errata number extraction from invalid URLs. """ param_list = [ 'http://errata.devel.redhat.com/advisory/12345', 'https://errrata.devel.redhat.com/advisory/12345', 'https://errata.dvel.reddhat.com/advisori/12345', 'https://errata.devel.redhat.com/12345', 'https://errata.devel.com/advisory/12345', 'https://errata.redhat.com/advisory/12345', 'https://devel.redhat.com/advisory/12345', 'https://redhat.com/advisory/12345', 'https://errata.com/advisory/12345' ] for url in param_list: with self.subTest(url=url): self.assertEqual(errata.extract_errata_number_from_body(url), None) def test_missing_url(self): """ Test errata number extraction from missing URLs. """ param_list = [ 'errata', '12345', 'errata is 12345' ] for body in param_list: with self.subTest(body=body): self.assertEqual(errata.extract_errata_number_from_body(body), None) def test_url_is_not_on_the_first_line(self): """ Test errata number extraction from valid URLs which are not located on the first line. """ param_list = [ '\nhttps://errata.devel.redhat.com/advisory/12345', '\n\nhttps://errata.devel.redhat.com/advisory/12345' ] for body in param_list: with self.subTest(body=body): self.assertEqual(errata.extract_errata_number_from_body(body), None) class SaveAndLoadTest(unittest.TestCase): def test_load_nonexisting_file(self): """ Test loading a nonexisting file. """ with tempfile.TemporaryDirectory() as tempdir: cachepath = os.path.join(tempdir, "cache.json") self.assertCountEqual(errata.load(cachepath), {}) def test_save_and_load_as_a_pair(self): """ Test using errata.save and errata.load as a pair to confirm their functionality. """ param_list = [ (), ({"foo": "bar"}), ({"value": "1234"}), ({"company": "Red Hat"}), ({"foo": "bar"}, {"value": "1234"}, {"errata": "1234"}), ({"value": "1234"}, {"foo": "bar"}, {"errata": "1234"}) ] for cache in param_list: with self.subTest(): with tempfile.TemporaryDirectory() as tempdir: cachepath = os.path.join(tempdir, "cache.json") errata.save(cachepath, cache) self.assertCountEqual(errata.load(cachepath), cache) class PollTest(unittest.TestCase): def setUp(self): self.raw_messages = [ ( True, { "additional_unnecessary_info": "shouldn't be processed", "msg": { "errata_id": 11, "product": "RHOSE", "to": "SHIPPED_LIVE", } } ), ( True, { "additional_unnecessary_info": "shouldn't be processed", "msg": { "errata_id": 12, "product": "RHOSE", "to": "SHIPPED_LIVE", } } ), ( False, { "additional_unnecessary_info": "shouldn't be processed", "msg": { "errata_id": 21, "product": "RHOSE", "to": "QE", } } ), ( False, { "additional_unnecessary_info": "shouldn't be processed", "msg": { "errata_id": 22, "product": "RHEL", "to": "SHIPPED_LIVE", } } ), ( False, { "additional_unnecessary_info": "shouldn't be processed", "msg": { "errata_id": 23, "product": "RHEL", "to": "QE", } } ), ( False, { "additional_unnecessary_info": "shouldn't be processed", "msg": { "errata_id": 24, "product": "SHIPPED_LIVE", "to": "RHOSE", } } ) ] self.valid_messages = [x[1] for x in self.raw_messages if x[0]] self.invalid_messages = [x[1] for x in self.raw_messages if not x[0]] @patch("json.load") @patch("urllib.request.urlopen") def test_params_of_urlopen_call(self, urlopen_mock, json_load_mock): """ Test parameters used in the data_grepper's url which is used for getting raw messages. """ urlopen_mock.return_value = MagicMock() json_load_mock.return_value = { "raw_messages": [], "pages": 1 } polled_messages = [] for message in errata.poll(period=datetime.timedelta(seconds=3600)): polled_messages.append(message) # Get params of the url used in urlopen in errata.poll parsed_url = urllib.parse.urlparse(urlopen_mock.call_args[0][0]) params = urllib.parse.parse_qs(parsed_url.query) # Assert if parameters complies with datagrepper reference self.assertGreater(int(params["page"][0]), 0) # Page must be greater than 0 self.assertLessEqual(int(params["rows_per_page"][0]), 100) # Must be less than or equal to 100 self.assertEqual(params["category"][0], "errata") # Should only look for errata category self.assertEqual(params["contains"][0], "RHOSE") # Only messages containing RHOSE @patch("json.load") @patch("urllib.request.urlopen") def test_number_of_returned_pages_is_zero(self, urlopen_mock, json_load_mock): """ Test poll's functionality if returned data contains number of pages equal to zero. """ urlopen_mock.return_value = MagicMock() json_load_mock.return_value = { "raw_messages": [], "pages": 0 } polled_messages = [] for message in errata.poll(period=datetime.timedelta(seconds=3600)): polled_messages.append(message) self.assertEqual(polled_messages, []) @patch("json.load") @patch("urllib.request.urlopen") def test_no_raw_messages(self, urlopen_mock, json_load_mock): """ Test polling messages if data doesn't contain any raw messages. """ urlopen_mock.return_value = MagicMock() json_load_mock.return_value = { "raw_messages": [], "pages": 1 } polled_messages = [] for message in errata.poll(period=datetime.timedelta(seconds=3600)): polled_messages.append(message) self.assertEqual(polled_messages, []) @patch("json.load") @patch("time.sleep") @patch("urllib.request.urlopen") def test_unresponsive_url_becomes_responsive(self, urlopen_mock, sleep_mock, json_load_mock): """ Test polling messages if request.urlopen throws exception on a first try. """ urlopen_mock.side_effect = [ Exception("Unresponsive, request.urlopen has failed"), MagicMock() ] json_load_mock.return_value = { "raw_messages": self.valid_messages, "pages": 1 } polled_messages = [] for message in errata.poll(period=datetime.timedelta(seconds=3600)): polled_messages.append(message) sleep_mock.assert_called_once() # URL wasn't responsive only once, so time.sleep should have been called only once expected_msgs = [x['msg'] for x in self.valid_messages] self.assertEqual(polled_messages, expected_msgs) @patch("json.load") @patch("urllib.request.urlopen") def test_multiple_messages(self, urlopen_mock, json_load_mock): """ Test polling messages from raw messages that include wanted and unwanted messages. """ urlopen_mock.return_value = MagicMock() messages = self.valid_messages + self.invalid_messages json_load_mock.return_value = { "raw_messages": messages, "pages": 1 } polled_messages = [] for message in errata.poll(period=datetime.timedelta(seconds=3600)): polled_messages.append(message) expected_msgs = [x['msg'] for x in self.valid_messages] self.assertEqual(polled_messages, expected_msgs) class SynopsisMatchTest(unittest.TestCase): def test_match(self): """ Ensure we match only the synopses that we want to match. """ for synopsis, expected in [ ( 'Moderate: OpenShift Container Platform 4.7.13 bug fix and security update', { 'impact': 'Moderate', 'version': '4.7.13', 'major': '4', 'minor': '7', 'patch': '13', 'prerelease': None, 'build': None, 'type': 'bug fix and security update', }, ), ( 'Moderate: OpenShift Container Platform 4.7.5 security and bug fix update', { 'impact': 'Moderate', 'version': '4.7.5', 'major': '4', 'minor': '7', 'patch': '5', 'prerelease': None, 'build': None, 'type': 'security and bug fix update', }, ), ( 'OpenShift Container Platform 4.6 GA Images', { 'impact': None, 'version': '4.6', 'major': '4', 'minor': '6', 'patch': None, 'prerelease': None, 'build': None, 'type': 'GA Images', }, ), ( 'OpenShift Container Platform 4.5.11 optional CSI driver Operators bug fix update', None, ), ( 'Moderate: OpenShift Container Platform 4.5.20 bug fix and golang security update', { 'impact': 'Moderate', 'version': '4.5.20', 'major': '4', 'minor': '5', 'patch': '20', 'prerelease': None, 'build': None, 'type': 'bug fix and golang security update', }, ), ( 'Low: OpenShift Container Platform 4.3.40 security and bug fix update', { 'impact': 'Low', 'version': '4.3.40', 'major': '4', 'minor': '3', 'patch': '40', 'prerelease': None, 'build': None, 'type': 'security and bug fix update', }, ), ]: with self.subTest(synopsis=synopsis): actual = errata._SYNOPSIS_REGEXP.match(synopsis) if actual: self.assertEqual(actual.groupdict(), expected) else: self.assertEqual(actual, expected) class AdvisoryPhrasingsTest(unittest.TestCase): def test_phrasings(self): """ Ensure we can construct synonym phrasins. """ for advisory, expected in [ ( 'RHBA-123', ['RHBA-123', 'RHSA-123'], ), ( 'RHSA-123', ['RHBA-123', 'RHSA-123'], ), ( 'https://example.com/RHBA-123', ['https://example.com/RHBA-123', 'https://example.com/RHSA-123'], ), ( 'https://example.com/RHBA-123/abc', ['https://example.com/RHBA-123/abc', 'https://example.com/RHSA-123/abc'], ), ]: with self.subTest(advisory=advisory): actual = list(errata.advisory_phrasings(advisory=advisory)) self.assertEqual(actual, expected) class NotifyTest(unittest.TestCase): def setUp(self): self.messages_including_approved_pr = [ ( { "errata_id": 11, "fulladvisory": "RHSA-2020:0000-00", "product": "RHOSE", "to": "SHIPPED_LIVE", "synopsis": "OpenShift Container Platform 4.6 GA Images", "when": "2021-01-01 12:00:00 UTC", "uri": "Public_Errata_URI_11", "approved_pr": "PR_HTML_URL_11" }, '<!subteam^STE7S7ZU2>: ' 'RHSA-2020:0000-00 shipped ' '2021-01-01 12:00:00 UTC: ' 'OpenShift Container Platform 4.6 GA Images ' 'Public_Errata_URI_11' '\nPR PR_HTML_URL_11 has been approved' ), ( { "errata_id": 12, "fulladvisory": "RHSA-2020:2000-20", "product": "RHOSE", "to": "SHIPPED_LIVE", "synopsis": "Moderate: OpenShift Container Platform 4.5.20 bug fix and golang security update", "when": "2021-01-02 13:00:00 UTC", "uri": "Public_Errata_URI_12", "approved_pr": "PR_HTML_URL_12" }, '<!subteam^STE7S7ZU2>: ' 'RHSA-2020:2000-20 shipped ' '2021-01-02 13:00:00 UTC: ' 'Moderate: OpenShift Container Platform 4.5.20 bug fix and golang security update ' 'Public_Errata_URI_12' '\nPR PR_HTML_URL_12 has been approved' ) ] self.messages_not_including_approved_pr = [ ( { "errata_id": 21, "fulladvisory": "RHSA-2020:0000-00", "product": "RHOSE", "to": "SHIPPED_LIVE", "synopsis": "OpenShift Container Platform 4.6 GA Images", "when": "2021-01-01 12:00:00 UTC", "uri": "Public_Errata_URI_21", }, '<!subteam^STE7S7ZU2>: ' 'RHSA-2020:0000-00 shipped ' '2021-01-01 12:00:00 UTC: ' 'OpenShift Container Platform 4.6 GA Images ' 'Public_Errata_URI_21' ), ( { "errata_id": 22, "fulladvisory": "RHSA-2020:2000-20", "product": "RHOSE", "to": "SHIPPED_LIVE", "synopsis": "Moderate: OpenShift Container Platform 4.5.20 bug fix and golang security update", "when": "2021-01-02 13:00:00 UTC", "uri": "Public_Errata_URI_22", }, '<!subteam^STE7S7ZU2>: ' 'RHSA-2020:2000-20 shipped ' '2021-01-02 13:00:00 UTC: ' 'Moderate: OpenShift Container Platform 4.5.20 bug fix and golang security update ' 'Public_Errata_URI_22' ) ] self.messages = \ self.messages_including_approved_pr + \ self.messages_not_including_approved_pr @patch("builtins.print") @patch("urllib.request.urlopen") def test_no_webhook(self, urlopen_mock, print_mock): """ Test functionality of notify if parameter webhook is set to its default value. """ for message in self.messages: with self.subTest(message=message): errata.notify(message[0]) expected_message = message[0] self.assertEqual(print_mock.call_args, unittest.mock.call(expected_message)) @patch("urllib.request.urlopen") def test_format_of_message_not_including_approved_pr(self, urlopen_mock): """ Test format of data passed as argument to request.urlopen in errata.get_open_prs_to_fast. This tests encoded format of the message in data as well. Only testing messages including approved_pr key. """ for (message, expected_message_in_data_to_be_uploaded) in self.messages_not_including_approved_pr: with self.subTest(message=message): expected_data_to_be_uploaded = urllib.parse.urlencode({ 'payload': { 'text': expected_message_in_data_to_be_uploaded } }).encode('utf-8') errata.notify(message, MagicMock()) uploaded_data = urlopen_mock.call_args[1]['data'] self.assertEqual(uploaded_data, expected_data_to_be_uploaded) @patch("urllib.request.urlopen") def test_format_of_message_including_approved_pr(self, urlopen_mock): """ Test format of data passed as argument to request.urlopen in errata.get_open_prs_to_fast. This tests encoded format of the message in data as well. Only testing messages that do not include approved_pr key. """ for (message, expected_message_in_data_to_be_uploaded) in self.messages_including_approved_pr: with self.subTest(message=message): expected_data_to_be_uploaded = urllib.parse.urlencode({ 'payload': { 'text': expected_message_in_data_to_be_uploaded } }).encode('utf-8') errata.notify(message, MagicMock()) uploaded_data = urlopen_mock.call_args[1]['data'] self.assertEqual(uploaded_data, expected_data_to_be_uploaded) class GetOpenPRsToFastTest(unittest.TestCase): def setUp(self): self.repo = MagicMock() self.labels_multiple_including_lgtm = [ [ GithubLabelMock('lgtm') ], [ GithubLabelMock('bug'), GithubLabelMock('duplicate'), GithubLabelMock('lgtm'), GithubLabelMock('documentation'), GithubLabelMock('invalid') ], [ GithubLabelMock('wontfix'), GithubLabelMock('lgtm'), GithubLabelMock('question'), GithubLabelMock('invalid') ], [ GithubLabelMock('help wanted'), GithubLabelMock('lgtm'), GithubLabelMock('good first issue'), GithubLabelMock('bug') ] ] self.labels_multiple_not_including_lgtm = [ [ ], [ GithubLabelMock('wontfix'), GithubLabelMock('bug'), GithubLabelMock('question'), GithubLabelMock('invalid') ], [ GithubLabelMock('help wanted'), GithubLabelMock('invalid'), GithubLabelMock('good first issue'), GithubLabelMock('duplicate') ], [ GithubLabelMock('bug'), GithubLabelMock('duplicate'), GithubLabelMock('invalid'), GithubLabelMock('documentation'), GithubLabelMock('enhancement') ] ] self.prs_correct_and_expected_to_be_yielded = [ GithubPRMock(GithubUserMock("openshift-bot"), "Enable 3.0.0 in fast channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.1.2 in fast channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.2.3 in fast channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.6.0 in fast channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", self.labels_multiple_not_including_lgtm[0]), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", self.labels_multiple_not_including_lgtm[1]), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", self.labels_multiple_not_including_lgtm[2]), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", self.labels_multiple_not_including_lgtm[3]), ] self.prs_including_the_lgtm_label = [ GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", self.labels_multiple_including_lgtm[0]), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", self.labels_multiple_including_lgtm[1]), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", self.labels_multiple_including_lgtm[2]), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", self.labels_multiple_including_lgtm[3]) ] self.prs_author_is_not_openshift_bot = [ GithubPRMock(GithubUserMock("user1234"), "Enable 4.0.0 in fast channel(s)"), GithubPRMock(GithubUserMock("bot-openshift"), "Enable 4.0.0 in fast channel(s)"), GithubPRMock(GithubUserMock("Openshift-Bot"), "Enable 4.0.0 in fast channel(s)"), GithubPRMock(GithubUserMock("GitHubUser1234"), "Enable 4.0.0 in fast channel(s)") ] self.prs_title_not_starting_with_Enable = [ GithubPRMock(GithubUserMock("openshift-bot"), ""), GithubPRMock(GithubUserMock("openshift-bot"), "Fix component"), GithubPRMock(GithubUserMock("openshift-bot"), "Add features in fast channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "enable 4.0.0 in fast channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Disable 4.0.0 in fast channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Enablee 4.0.0 in fast channel(s)") ] self.prs_do_not_target_fast = [ GithubPRMock(GithubUserMock("openshift-bot"), "Enable "), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in FAST channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in faast channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in stable channel(s)"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in candidate channel(s)") ] def test_prs_including_the_lgtm_label(self): """ Test retrieving PRs which include the LGTM label. These PRs should be skipped. """ self.repo.get_pulls = MagicMock(return_value=self.prs_including_the_lgtm_label) open_prs_to_fast = [] for pr in errata.get_open_prs_to_fast(self.repo): open_prs_to_fast.append(pr) expected_prs = [] self.assertEqual(open_prs_to_fast, expected_prs) def test_prs_author_is_not_openshift_bot(self): """ Test getting PRs whose author is not openshift-bot. These PRs should be skipped. """ self.repo.get_pulls = MagicMock(return_value=self.prs_author_is_not_openshift_bot) open_prs_to_fast = [] for pr in errata.get_open_prs_to_fast(self.repo): open_prs_to_fast.append(pr) expected_prs = [] self.assertEqual(open_prs_to_fast, expected_prs) def test_unknown_prs_should_be_skipped(self): """ Test getting unknown PRs. These PRs should be skipped. """ self.repo.get_pulls = MagicMock(return_value=self.prs_title_not_starting_with_Enable) open_prs_to_fast = [] for pr in errata.get_open_prs_to_fast(self.repo): open_prs_to_fast.append(pr) expected_prs = [] self.assertEqual(open_prs_to_fast, expected_prs) def test_ignore_prs_which_dont_target_fast(self): """ Test getting PRs which don't target fast. These PRs should be skipped. """ self.repo.get_pulls = MagicMock(return_value=self.prs_do_not_target_fast) open_prs_to_fast = [] for pr in errata.get_open_prs_to_fast(self.repo): open_prs_to_fast.append(pr) expected_prs = [] self.assertEqual(open_prs_to_fast, expected_prs) def test_correct_prs_should_be_yielded(self): """ Test getting PRs which are correct and should be yielded back. """ self.repo.get_pulls = MagicMock(return_value=self.prs_correct_and_expected_to_be_yielded) open_prs_to_fast = [] for pr in errata.get_open_prs_to_fast(self.repo): open_prs_to_fast.append(pr) expected_prs = self.prs_correct_and_expected_to_be_yielded self.assertEqual(open_prs_to_fast, expected_prs) def test_get_pulls_query_params(self): """ Test query params used for getting the initial PRs from the repository. """ self.repo.get_pulls = MagicMock(return_value=[]) open_prs_to_fast = [] for pr in errata.get_open_prs_to_fast(self.repo): open_prs_to_fast.append(pr) expected_params = { 'state': 'open', 'base': 'master', 'sort': 'created', } self.assertEqual(self.repo.get_pulls.call_args, (unittest.mock.call(**expected_params))) class LgtmFastPrForErrata(unittest.TestCase): def setUp(self): self.repo = MagicMock() self.github_object_mock = MagicMock() self.github_object_mock.get_repo.return_value = self.repo self.prs_with_html_url_of_expected_pr = [ ( [ GithubPRMock(GithubUserMock("openshift-bot"), "Enable 3.0.0 in fast channel(s)", [], 1, "https://errata.devel.redhat.com/advisory/1111", "PR_URL1", "PR_HTML_URL1"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", [], 2, "https://errata.devel.redhat.com/advisory/1234", "PR_URL2", "PR_HTML_URL2"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.1.2 in fast channel(s)", [], 3, "https://errata.devel.redhat.com/advisory/5678", "PR_URL3", "PR_HTML_URL3"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.2.3 in fast channel(s)", [], 4, "https://errata.devel.redhat.com/advisory/1357", "PR_URL4", "PR_HTML_URL4") ], { "errata_id": 1357 }, "PR_HTML_URL4" # HTML url of a PR which body has the wanted errata id. ), ( [ GithubPRMock(GithubUserMock("openshift-bot"), "Enable 3.0.0 in fast channel(s)", [], 12345, "https://errata.devel.redhat.com/advisory/41", "PR_URL12345", "PR_HTML_URL12345"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", [], 12354, "https://errata.devel.redhat.com/advisory/42", "PR_URL12354", "PR_HTML_URL12354"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.1.2 in fast channel(s)", [], 12340, "https://errata.devel.redhat.com/advisory/43", "PR_URL12340", "PR_HTML_URL12340"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.2.3 in fast channel(s)", [], 43215, "https://errata.devel.redhat.com/advisory/44", "PR_URL43215", "PR_HTML_URL43215") ], { "errata_id": 41 }, "PR_HTML_URL12345" ), ( [ GithubPRMock(GithubUserMock("openshift-bot"), "Enable 3.0.0 in fast channel(s)", [], 1111, "https://errata.devel.redhat.com/advisory/51", "PR_URL1111", "PR_HTML_URL1111"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", [], 2222, "https://errata.devel.redhat.com/advisory/62", "PR_URL2222", "PR_HTML_URL2222"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.1.2 in fast channel(s)", [], 3333, "https://errata.devel.redhat.com/advisory/73", "PR_URL3333", "PR_HTML_URL3333"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.2.3 in fast channel(s)", [], 4444, "https://errata.devel.redhat.com/advisory/84", "PR_URL4444", "PR_HTML_URL4444") ], { "errata_id": 73 }, "PR_HTML_URL3333" ) ] self.prs_with_index_of_expected_pr = [ ( [ GithubPRMock(GithubUserMock("openshift-bot"), "Enable 3.0.0 in fast channel(s)", [], 1, "https://errata.devel.redhat.com/advisory/1111", "PR_URL1", "PR_HTML_URL1"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", [], 2, "https://errata.devel.redhat.com/advisory/1234", "PR_URL2", "PR_HTML_URL2"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.1.2 in fast channel(s)", [], 3, "https://errata.devel.redhat.com/advisory/5678", "PR_URL3", "PR_HTML_URL3"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.2.3 in fast channel(s)", [], 4, "https://errata.devel.redhat.com/advisory/1357", "PR_URL4", "PR_HTML_URL4") ], { "errata_id": 1357 }, 3 # Index of the PR which has the wanted errata id. ), ( [ GithubPRMock(GithubUserMock("openshift-bot"), "Enable 3.0.0 in fast channel(s)", [], 12345, "https://errata.devel.redhat.com/advisory/41", "PR_URL12345", "PR_HTML_URL12345"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", [], 12354, "https://errata.devel.redhat.com/advisory/42", "PR_URL12354", "PR_HTML_URL12354"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.1.2 in fast channel(s)", [], 12340, "https://errata.devel.redhat.com/advisory/43", "PR_URL12340", "PR_HTML_URL12340"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.2.3 in fast channel(s)", [], 43215, "https://errata.devel.redhat.com/advisory/44", "PR_URL43215", "PR_HTML_URL43215") ], { "errata_id": 41 }, 0 ), ( [ GithubPRMock(GithubUserMock("openshift-bot"), "Enable 3.0.0 in fast channel(s)", [], 1111, "https://errata.devel.redhat.com/advisory/51", "PR_URL1111", "PR_HTML_URL1111"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", [], 2222, "https://errata.devel.redhat.com/advisory/62", "PR_URL2222", "PR_HTML_URL2222"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.1.2 in fast channel(s)", [], 3333, "https://errata.devel.redhat.com/advisory/73", "PR_URL3333", "PR_HTML_URL3333"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.2.3 in fast channel(s)", [], 4444, "https://errata.devel.redhat.com/advisory/84", "PR_URL4444", "PR_HTML_URL4444") ], { "errata_id": 73 }, 2 ) ] self.prs_with_invalid_errata_url = [ ( [ GithubPRMock(GithubUserMock("openshift-bot"), "Enable 3.0.0 in fast channel(s)", [], 1, "", "PR_URL1", "PR_HTML_URL1"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.0.0 in fast channel(s)", [], 2, "https://errata", "PR_URL2", "PR_HTML_URL2"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.1.2 in fast channel(s)", [], 3, "https://redhat.com/advisory/84", "PR_URL3", "PR_HTML_URL3"), GithubPRMock(GithubUserMock("openshift-bot"), "Enable 4.2.3 in fast channel(s)", [], 4, "https://errata.devel.redhat.com", "PR_URL4", "PR_HTML_URL4") ], { "errata_id": 21 } ) ] @patch("github.Github") def test_return_value_is_correct_for_specific_pr(self, Github_mock): """ Test retrieving the HTML url of a PR which is related to a specific errata id. """ githubrepo = MagicMock() githubtoken = MagicMock() Github_mock.return_value = self.github_object_mock param_list = self.prs_with_html_url_of_expected_pr for (prs, message, expected_pr_html_url) in param_list: with self.subTest(prs_body=[x.body for x in prs], message=message): self.repo.get_pulls = MagicMock(return_value=prs) pr_html_url = errata.lgtm_fast_pr_for_errata(githubrepo, githubtoken, message) self.assertEqual(pr_html_url, expected_pr_html_url) @patch("github.Github") def test_only_create_issue_on_the_expected_pr(self, Github_mock): """ Test creating an issue comment only on the PR which is related to the specific errata id. """ githubrepo = MagicMock() githubtoken = MagicMock() Github_mock.return_value = self.github_object_mock param_list = self.prs_with_index_of_expected_pr for (prs, message, expected_index_of_pr_to_create_issue) in param_list: self.repo.get_pulls = MagicMock(return_value=prs) errata.lgtm_fast_pr_for_errata(githubrepo, githubtoken, message) for index, pr in enumerate(prs): with self.subTest(prs_body=[x.body for x in prs], message=message): if index == expected_index_of_pr_to_create_issue: pr.create_issue_comment.assert_called_once() else: pr.create_issue_comment.assert_not_called() @patch("github.Github") def test_issue_comment_format(self, Github_mock): """ Test the format of the created issue comment on the PR which is related to the specific errata id. """ githubrepo = MagicMock() githubtoken = MagicMock() Github_mock.return_value = self.github_object_mock param_list = self.prs_with_index_of_expected_pr for (prs, message, expected_index_of_pr_to_create_issue) in param_list: with self.subTest(prs_body=[x.body for x in prs], message=message): self.repo.get_pulls = MagicMock(return_value=prs) errata.lgtm_fast_pr_for_errata(githubrepo, githubtoken, message) issue_comment = prs[expected_index_of_pr_to_create_issue].create_issue_comment.call_args expected_issue_comment = "Autoapproving PR to fast after the errata has shipped\n/lgtm" self.assertEqual(issue_comment, (unittest.mock.call(expected_issue_comment))) @patch("github.Github") def test_prs_include_invalid_errata_url(self, Github_mock): """ Test PRs which body include invalid errata url. These prs should be skipped. """ githubrepo = MagicMock() githubtoken = MagicMock() Github_mock.return_value = self.github_object_mock param_list = self.prs_with_invalid_errata_url for (prs, message) in param_list: with self.subTest(body=[x.body for x in prs]): self.repo.get_pulls = MagicMock(return_value=prs) pr_html_url = errata.lgtm_fast_pr_for_errata(githubrepo, githubtoken, message) self.assertEqual(pr_html_url, None) class PublicErrataUriTest(unittest.TestCase): def setUp(self): self.nodes_valid = [ ( { # nodes received via urlopen "nodes": [ { "version": "4.0.0", "metadata": { "url": "https://access.redhat.com/errata/RHBA-2020:0000" } } ] }, ( # Parameteres for calling errata.public_errata_uri "4.0.0", "RHBA-2020:0000", "candidate-4.0.0", ), # Expected uri of the wanted node "https://access.redhat.com/errata/RHBA-2020:0000", ), ( { "nodes": [ { "version": "4.1.0", "metadata": { "url": "https://access.redhat.com/errata/RHBA-2020:1000" } } ] }, ( "4.1.0", "RHBA-2020:1000", "candidate-4.1.0", ), "https://access.redhat.com/errata/RHBA-2020:1000", ), ( { "nodes": [ { "version": "4.2.0", "metadata": { "url": "https://access.redhat.com/errata/RHBA-2020:2000" } } ] }, ( "4.2.0", "RHBA-2020:2000", "candidate-4.2.0", ), "https://access.redhat.com/errata/RHBA-2020:2000", ), ] @patch("json.load") @patch("urllib.request.urlopen") def test_should_return_uri_of_same_version(self, urlopen_mock, json_load_mock): """ Test if URL of the node with the same version as the parameter is returned. """ for (data, params, expected_errata_uri) in self.nodes_valid: version = params[0] channel = params[2] json_load_mock.return_value = data with self.subTest(version=version): errata_uri = errata.public_errata_uri(version=version, advisory="", channel=channel) self.assertEqual(errata_uri, expected_errata_uri) @patch("json.load") @patch("urllib.request.urlopen") def test_should_return_uri_of_the_same_advisory(self, urlopen_mock, json_load_mock): """ Test if URL of the node with the same advisory as the parameter is returned. """ for (data, params, expected_errata_uri) in self.nodes_valid: advisory = params[1] channel = params[2] json_load_mock.return_value = data with self.subTest(advisory=advisory): errata_uri = errata.public_errata_uri(version="", advisory=advisory, channel=channel) self.assertEqual(errata_uri, expected_errata_uri) @patch("json.load") @patch("urllib.request.urlopen") def test_zero_nodes_received(self, urlopen_mock, json_load_mock): """ Test if None is returned when zero nodes are received. """ json_load_mock.return_value = { "nodes": [] } for (_, params, _) in self.nodes_valid: version = params[0] advisory = params[1] channel = params[2] with self.subTest(version=version, advisory=advisory): errata_uri = errata.public_errata_uri(version=version, advisory=advisory, channel=channel) self.assertEqual(errata_uri, None) @patch("json.load") @patch("urllib.request.urlopen") def test_zero_nodes_match(self, urlopen_mock, json_load_mock): """ Test if None is returned when zero nodes match wanted version or advisory. """ for (data, params, _) in self.nodes_valid: version = params[0] advisory = params[1] channel = params[2] json_load_mock.return_value = data with self.subTest(version=version, advisory=advisory): errata_uri = errata.public_errata_uri(version="", advisory="", channel=channel) self.assertEqual(errata_uri, None) @patch("time.sleep") @patch("json.load") @patch("urllib.request.urlopen") def test_unresponsive_url_becomes_responsive(self, urlopen_mock, json_load_mock, sleep_mock): """ Test requesting messages if request.urlopen throws exception on a first try. """ for (data, params, expected_errata_uri) in self.nodes_valid: version = params[0] advisory = params[1] channel = params[2] json_load_mock.return_value = data urlopen_mock.side_effect = [ Exception("Unresponsive, request.urlopen has failed"), MagicMock() ] sleep_mock.reset_mock() with self.subTest(): errata_uri = errata.public_errata_uri(version=version, advisory=advisory, channel=channel) sleep_mock.assert_called_once() self.assertEqual(errata_uri, expected_errata_uri) class ProcessMessageTest(unittest.TestCase): def setUp(self): self.valid_params = [ ( "https://access.redhat.com/errata/RHBA-2020:0000", { "synopsis": "Moderate: OpenShift Container Platform 4.0.0 bug fix and golang security update", "fulladvisory": "RHBA-2020:0000-01", "when": "2021-01-01 00:00:00 UTC", } ), ( "https://access.redhat.com/errata/RHBA-2021:0749", { "synopsis": "OpenShift Container Platform 4.7.2 bug fix update", "fulladvisory": "RHBA-2021:0749-06", "when": "2021-03-16 08:42:16 UTC", } ) ] @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_raise_exception_when_new_invalid_synopsis_is_received( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test processing an invalid synopsis which is not in the excluded cache. Should raise the ValueError exception. """ public_errata_uri_mock.return_value = "https://access.redhat.com/errata/RHBA-2020:0000" invalid_synopsis = "Invalid Synopsis 0.0.0" message = { "synopsis": invalid_synopsis, "fulladvisory": "RHBA-2020:0000-01", "when": "2021-01-01 00:00:00 UTC", } cache = {} excluded_cache = {} with self.assertRaises(ValueError): errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_content_of_cache_when_invalid_synopsis_is_received( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test content of the cache should remain unchanged when invalid synopsis is received. """ public_errata_uri_mock.return_value = "https://access.redhat.com/errata/RHBA-2020:0000" invalid_synopsis = "Invalid Synopsis 0.0.0" cache = { "RHBA-2020:0000-01": { "synopsis": "Moderate: OpenShift Container Platform 4.0.0 bug fix and golang security update", "uri": "https://access.redhat.com/errata/RHBA-2020:0000", "when": "2021-01-01 00:00:00 UTC", } } cache_copy = copy.deepcopy(cache) message = { "synopsis": invalid_synopsis, "fulladvisory": "RHBA-2020:0000-01", "when": "2021-01-01 00:00:00 UTC", } excluded_cache = {} with self.assertRaises(ValueError): errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) self.assertDictEqual(cache, cache_copy) @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_add_new_invalid_synopsis_to_the_excluded_cache( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test processing invalid synopsis which is not in the excluded cache. Should add the synopsis and the fulladvisory to the excluded cache. """ public_errata_uri_mock.return_value = "https://access.redhat.com/errata/RHBA-2020:0000" invalid_synopsis = "Invalid Synopsis 0.0.0" message = { "synopsis": invalid_synopsis, "fulladvisory": "RHBA-2020:0000-01", "when": "2021-01-01 00:00:00 UTC", } cache = {} excluded_cache = {} with self.assertRaises(ValueError): errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) self.assertDictEqual( excluded_cache, { invalid_synopsis: "RHBA-2020:0000-01", } ) @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_not_lgtm_fast_pr_when_new_invalid_synopsis_is_received( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test if there isn't an attempt to lgtm fast pr when a new invalid synopsis is received. The new invalid synopsis wasn't saved in the excluded cache. """ public_errata_uri_mock.return_value = "https://access.redhat.com/errata/RHBA-2020:0000" invalid_synopsis = "Invalid Synopsis 0.0.0" message = { "synopsis": invalid_synopsis, "fulladvisory": "RHBA-2020:0000-01", "when": "2021-01-01 00:00:00 UTC", } cache = {} excluded_cache = {} with self.assertRaises(ValueError): errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) lgtm_fast_pr_for_errata_mock.assert_not_called() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_not_notify_when_new_invalid_synopsis_is_received( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test if there isn't an attempt to notify when a new invalid synopsis is received. The new invalid synopsis wasn't saved in the excluded cache. """ public_errata_uri_mock.return_value = "https://access.redhat.com/errata/RHBA-2020:0000" invalid_synopsis = "Invalid Synopsis 0.0.0" message = { "synopsis": invalid_synopsis, "fulladvisory": "RHBA-2020:0000-01", "when": "2021-01-01 00:00:00 UTC", } cache = {} excluded_cache = {} with self.assertRaises(ValueError): errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) notify_mock.assert_not_called() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_content_of_excluded_cache_when_reprocessing_invalid_synopsis( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test processing invalid synopsis which is already in the excluded cache. Should not change the content of the excluded cache. """ public_errata_uri_mock.return_value = "https://access.redhat.com/errata/RHBA-2020:0000" invalid_synopsis = "Invalid Synopsis 0.0.0" invalid_synopsis_2 = "Invalid 1.0.0" excluded_cache = { invalid_synopsis: "RHBA-2020:0000-01", invalid_synopsis_2: "RHBA-2020:1111-01" } excluded_cache_copy = copy.deepcopy(excluded_cache) message = { "synopsis": invalid_synopsis, "fulladvisory": "RHBA-2020:0000-01", "when": "2021-01-01 00:00:00 UTC", } cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) self.assertDictEqual(excluded_cache, excluded_cache_copy) @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_not_lgtm_fast_pr_when_reprocessing_invalid_synopsis( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test if there isn't an attempt to lgtm fast pr when an already processed invalid synopsis is received. Invalid synopsis is saved in the excluded cache. """ public_errata_uri_mock.return_value = "https://access.redhat.com/errata/RHBA-2020:0000" invalid_synopsis = "Invalid Synopsis 0.0.0" message = { "synopsis": invalid_synopsis, "fulladvisory": "RHBA-2020:0000-01", "when": "2021-01-01 00:00:00 UTC", } cache = {} excluded_cache = { invalid_synopsis: "RHBA-2020:0000-01" } errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) lgtm_fast_pr_for_errata_mock.assert_not_called() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_not_notify_when_reprocessing_invalid_synopsis( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test if there isn't an attempt to notify when an already processed invalid synopsis is received. Invalid synopsis is saved in the excluded cache. """ public_errata_uri_mock.return_value = "https://access.redhat.com/errata/RHBA-2020:0000" invalid_synopsis = "Invalid Synopsis 0.0.0" message = { "synopsis": invalid_synopsis, "fulladvisory": "RHBA-2020:0000-01", "when": "2021-01-01 00:00:00 UTC", } cache = {} excluded_cache = { invalid_synopsis: "RHBA-2020:0000-01", } errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) notify_mock.assert_not_called() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_add_new_valid_synopsis_to_the_cache( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test processing valid synopsis which is not in the cache. Should add the synopsis's data to the cache. """ for (public_errata_uri, message) in self.valid_params: with self.subTest(message=message, errata_uri=public_errata_uri): public_errata_uri_mock.return_value = public_errata_uri message_copy = copy.deepcopy(message) cache = {} excluded_cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) self.assertDictEqual( cache, { message_copy['fulladvisory']: { "when": message_copy['when'], "synopsis": message_copy['synopsis'], "uri": public_errata_uri, } } ) @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_notify_when_new_valid_synopsis_is_received( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test if there is an attempt to notify when a new valid synopsis is received. """ for (public_errata_uri, message) in self.valid_params: with self.subTest(message=message, errata_uri=public_errata_uri): public_errata_uri_mock.return_value = public_errata_uri notify_mock.reset_mock() cache = {} excluded_cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) notify_mock.assert_called_once() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_lgtm_fast_pr_when_new_valid_synopsis_is_received( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test if there is an attempt to lgtm fast pr when a new valid synopsis is received. """ for (public_errata_uri, message) in self.valid_params: with self.subTest(message=message, errata_uri=public_errata_uri): public_errata_uri_mock.return_value = public_errata_uri lgtm_fast_pr_for_errata_mock.reset_mock() cache = {} excluded_cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) lgtm_fast_pr_for_errata_mock.assert_called_once() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_content_of_cache_when_reprocessing_valid_synopsis( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test processing valid synopsis which is already in the cache. Should not change the content of the cache. """ for (public_errata_uri, message) in self.valid_params: with self.subTest(message=message, errata_uri=public_errata_uri): public_errata_uri_mock.return_value = public_errata_uri cache = {} cache[message['fulladvisory']] = { 'when': message['when'], 'synopsis': message['synopsis'], 'uri': public_errata_uri, } cache_copy = copy.deepcopy(cache) excluded_cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) self.assertDictEqual(cache, cache_copy) @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_not_notify_when_reprocessing_valid_synopsis( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test if there isn't an attempt to notify when reprocessing a valid synopsis. The valid synopsis is already saved in the cache. """ for (public_errata_uri, message) in self.valid_params: with self.subTest(message=message, errata_uri=public_errata_uri): public_errata_uri_mock.return_value = public_errata_uri notify_mock.reset_mock() cache = {} cache[message['fulladvisory']] = { 'when': message['when'], 'synopsis': message['synopsis'], 'uri': public_errata_uri, } excluded_cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) notify_mock.assert_not_called() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_not_lgtm_fast_pr_when_reprocessing_valid_synopsis( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test if there isn't an attempt to lgtm fast PR when reprocessing a valid synopsis. The valid synopsis is already saved in the cache. """ for (public_errata_uri, message) in self.valid_params: with self.subTest(message=message, errata_uri=public_errata_uri): public_errata_uri_mock.return_value = public_errata_uri lgtm_fast_pr_for_errata_mock.reset_mock() cache = {} cache[message['fulladvisory']] = { 'when': message['when'], 'synopsis': message['synopsis'], 'uri': public_errata_uri, } excluded_cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) lgtm_fast_pr_for_errata_mock.assert_not_called() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_not_notify_for_valid_synopsis_does_not_have_public_errata( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test processing a new valid synopsis which does not have a public errata uri. Test if there isn't attempt to notify. """ for (public_errata_uri, message) in self.valid_params: with self.subTest(message=message, errata_uri=public_errata_uri): public_errata_uri_mock.return_value = None notify_mock.reset_mock() cache = {} excluded_cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) notify_mock.assert_not_called() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_not_lgtm_fast_pr_for_valid_synopsis_does_not_have_public_errata( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test processing a new valid synopsis which does not have a public errata uri. Test if there isn't attempt to lgtm fast pr for a message's synopsis. """ for (public_errata_uri, message) in self.valid_params: with self.subTest(message=message, errata_uri=public_errata_uri): public_errata_uri_mock.return_value = None lgtm_fast_pr_for_errata_mock.reset_mock() cache = {} excluded_cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) lgtm_fast_pr_for_errata_mock.assert_not_called() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_not_notify_when_public_errata_does_not_match_synopsis( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test processing a new valid synopsis which does not have a matching public errata uri. Test if there isn't attempt to notify when the public errata uri does not match message's advisory. """ for (public_errata_uri, message) in self.valid_params: with self.subTest(message=message, errata_uri=public_errata_uri): public_errata_uri_mock.return_value = 'non_matching_errata_uri' lgtm_fast_pr_for_errata_mock.reset_mock() notify_mock.reset_mock() cache = {} excluded_cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) notify_mock.assert_not_called() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_should_not_lgtm_fast_pr_when_public_errata_does_not_match_synopsis( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Test processing a new valid synopsis which does not have a matching public errata uri. Test if there isn't attempt to lgtm fast pr for a message's synopsis when the public errata uri does not match message's advisory. """ for (public_errata_uri, message) in self.valid_params: with self.subTest(message=message, errata_uri=public_errata_uri): public_errata_uri_mock.return_value = 'non_matching_errata_uri' lgtm_fast_pr_for_errata_mock.reset_mock() notify_mock.reset_mock() cache = {} excluded_cache = {} errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) lgtm_fast_pr_for_errata_mock.assert_not_called() @patch("errata.lgtm_fast_pr_for_errata") @patch("errata.public_errata_uri") @patch("errata.notify") def test_processing_valid_message_multiple_times( self, notify_mock, public_errata_uri_mock, lgtm_fast_pr_for_errata_mock ): """ Processing multiple valid messages. Should attempt to notify and to lgtm the fast pr once for the same message. """ for (public_errata_uri, message) in self.valid_params: public_errata_uri_mock.return_value = public_errata_uri lgtm_fast_pr_for_errata_mock.reset_mock() notify_mock.reset_mock() message_copy = copy.deepcopy(message) cache = {} excluded_cache = {} for _ in range(10): message = copy.deepcopy(message_copy) errata.process_message( message=message, cache=cache, excluded_cache=excluded_cache, webhook=None, githubrepo=None, githubtoken=None, ) with self.subTest(message=message, errata_uri=public_errata_uri): lgtm_fast_pr_for_errata_mock.assert_called_once() with self.subTest(message=message, errata_uri=public_errata_uri): notify_mock.assert_called_once() if __name__ == '__main__': unittest.main()

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1c46e8ebc705732b535b16f3a42154c4df52a3d9

82

py

Python

tests/conftest.py

mishc9/flake_rba

eda1e80436f401871dba61a4c769204c2cbcfc65

[ "MIT" ]

null

tests/conftest.py

mishc9/flake_rba

eda1e80436f401871dba61a4c769204c2cbcfc65

[ "MIT" ]

null

tests/conftest.py

mishc9/flake_rba

eda1e80436f401871dba61a4c769204c2cbcfc65

[ "MIT" ]

null

import pytest @pytest.fixture def fixture_template(): return "Hello World!"

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31,832

py

Python

Chatbot_DockerVersion/webapp/requirements/mindmeld/tests/test_markup.py

ptrckhmmr/ChatBotforCulturalInstitutions

c3da1a6d142e306c2e3183ba5609553e15a0e124

[ "Apache-2.0" ]

1

2020-12-24T13:28:35.000Z

Chatbot_DockerVersion/webapp/requirements/mindmeld/tests/test_markup.py

ptrckhmmr/ChatBotforCulturalInstitutions

c3da1a6d142e306c2e3183ba5609553e15a0e124

[ "Apache-2.0" ]

null

Chatbot_DockerVersion/webapp/requirements/mindmeld/tests/test_markup.py

ptrckhmmr/ChatBotforCulturalInstitutions

c3da1a6d142e306c2e3183ba5609553e15a0e124

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ test_markup ---------------------------------- Tests for `markup` module. """ import pytest from mindmeld import markup from mindmeld.core import Entity, NestedEntity, ProcessedQuery, QueryEntity, Span MARKED_UP_STRS = [ 'show me houses under {[600,000|sys_number] dollars|price}', 'show me houses under {[$600,000|sys_number]|price}', 'show me houses under {[1.5|sys_number] million dollars|price}', 'play {s.o.b.|track}', "what's on at {[8 p.m.|sys_time]|range}?", 'is {s.o.b.|show} gonna be on at {[8 p.m.|sys_time]|range}?', 'this is a {role model|type|role}', 'this query has no entities' ] MARKED_DOWN_STRS = [ 'show me houses under 600,000 dollars', 'show me houses under $600,000', 'show me houses under 1.5 million dollars', 'play s.o.b.', "what's on at 8 p.m.?", 'is s.o.b. gonna be on at 8 p.m.?', 'this is a role model', 'this query has no entities' ] @pytest.mark.mark_down def test_mark_down(): """Tests the mark down function""" text = 'is {s.o.b.|show} gonna be {{on at 8 p.m.|sys_time}|range}?' marked_down = markup.mark_down(text) assert marked_down == 'is s.o.b. gonna be on at 8 p.m.?' @pytest.mark.load def test_load_basic_query(query_factory): """Tests loading a basic query with no entities""" markup_text = 'This is a test query string' processed_query = markup.load_query(markup_text, query_factory) assert processed_query assert processed_query.query @pytest.mark.load def test_load_entity(query_factory): """Tests loading a basic query with an entity""" markup_text = 'When does the {Elm Street|store_name} store close?' processed_query = markup.load_query(markup_text, query_factory) assert len(processed_query.entities) == 1 entity = processed_query.entities[0] assert entity.span.start == 14 assert entity.span.end == 23 assert entity.normalized_text == 'elm street' assert entity.entity.type == 'store_name' assert entity.entity.text == 'Elm Street' @pytest.mark.load @pytest.mark.system def test_load_system(query_factory): """Tests loading a query with a system entity""" text = 'show me houses under {600,000 dollars|sys_amount-of-money}' processed_query = markup.load_query(text, query_factory) assert processed_query assert len(processed_query.entities) == 1 entity = processed_query.entities[0] assert entity.text == '600,000 dollars' assert entity.entity.type == 'sys_amount-of-money' assert entity.span.start == 21 assert not isinstance(entity.entity.value, str) assert entity.entity.value == {'unit': '$', 'value': 600000} @pytest.mark.dump @pytest.mark.system @pytest.mark.role def test_load_system_role(query_factory): """Tests loading a basic query with an entity with a role""" text = ('What stores are open between {3|sys_time|open_hours} and ' '{5|sys_time|close_hours}') processed_query = markup.load_query(text, query_factory) assert len(processed_query.entities) == 2 entity = processed_query.entities[0] assert entity.span.start == 29 assert entity.span.end == 29 assert entity.normalized_text == '3' assert entity.entity.type == 'sys_time' assert entity.entity.text == '3' assert entity.entity.role == 'open_hours' entity = processed_query.entities[1] assert entity.span.start == 35 assert entity.span.end == 35 assert entity.normalized_text == '5' assert entity.entity.type == 'sys_time' assert entity.entity.text == '5' assert entity.entity.role == 'close_hours' @pytest.mark.load @pytest.mark.system @pytest.mark.nested def test_load_nested(query_factory): """Tests loading a query with a nested system entity""" text = 'show me houses under {{600,000|sys_number} dollars|price}' processed_query = markup.load_query(text, query_factory) assert processed_query assert len(processed_query.entities) == 1 entity = processed_query.entities[0] assert entity.text == '600,000 dollars' assert entity.entity.type == 'price' assert entity.span == Span(21, 35) assert not isinstance(entity.entity.value, str) assert 'children' in entity.entity.value assert len(entity.entity.value['children']) == 1 nested = entity.entity.value['children'][0] assert nested.text == '600,000' assert nested.span == Span(0, 6) assert nested.entity.type == 'sys_number' assert nested.entity.value == {'value': 600000} @pytest.mark.load @pytest.mark.system @pytest.mark.nested def test_load_nested_2(query_factory): """Tests loading a query with a nested system entity""" text = 'show me houses under {${600,000|sys_number}|price}' processed_query = markup.load_query(text, query_factory) assert processed_query assert len(processed_query.entities) == 1 entity = processed_query.entities[0] assert entity.text == '$600,000' assert entity.entity.type == 'price' assert entity.span == Span(21, 28) assert not isinstance(entity.entity.value, str) assert 'children' in entity.entity.value assert len(entity.entity.value['children']) == 1 nested = entity.entity.value['children'][0] assert nested.text == '600,000' assert nested.entity.value == {'value': 600000} assert nested.span == Span(1, 7) @pytest.mark.load @pytest.mark.system @pytest.mark.nested def test_load_nested_3(query_factory): """Tests loading a query with a nested system entity""" text = 'show me houses under {{1.5 million|sys_number} dollars|price}' processed_query = markup.load_query(text, query_factory) assert processed_query @pytest.mark.load @pytest.mark.system @pytest.mark.nested def test_load_nested_4(query_factory): """Tests dumping a query with multiple nested system entities""" text = 'show me houses {between {600,000|sys_number} and {1,000,000|sys_number} dollars|price}' processed_query = markup.load_query(text, query_factory) assert processed_query assert len(processed_query.entities) == 1 entity = processed_query.entities[0] assert entity.text == 'between 600,000 and 1,000,000 dollars' assert entity.entity.type == 'price' assert entity.span == Span(15, 51) assert not isinstance(entity.entity.value, str) assert 'children' in entity.entity.value assert len(entity.entity.value['children']) == 2 lower, upper = entity.entity.value['children'] assert lower.text == '600,000' assert lower.entity.value == {'value': 600000} assert lower.span == Span(8, 14) assert upper.text == '1,000,000' assert upper.entity.value == {'value': 1000000} assert upper.span == Span(20, 28) @pytest.mark.load @pytest.mark.special def test_load_special_chars(query_factory): """Tests loading a query with special characters""" text = 'play {s.o.b.|track}' processed_query = markup.load_query(text, query_factory) entities = processed_query.entities assert len(entities) entity = entities[0] assert entity.text == 's.o.b.' assert entity.normalized_text == 's o b' assert entity.span.start == 5 assert entity.span.end == 10 @pytest.mark.load @pytest.mark.special def test_load_special_chars_2(query_factory): """Tests loading a query with special characters""" text = "what's on at {{8 p.m.|sys_time}|range}?" processed_query = markup.load_query(text, query_factory) entities = processed_query.entities assert len(entities) == 1 entity = entities[0] assert entity.text == '8 p.m.' assert entity.normalized_text == '8 p m' assert entity.span == Span(13, 18) assert entity.entity.type == 'range' nested = entity.entity.value['children'][0] assert nested.text == '8 p.m.' assert nested.span == Span(0, 5) assert nested.entity.type == 'sys_time' assert nested.entity.value['value'] @pytest.mark.load @pytest.mark.special def test_load_special_chars_3(query_factory): """Tests loading a query with special characters""" text = 'is {s.o.b.|show} gonna be {{on at 8 p.m.|sys_time}|range}?' processed_query = markup.load_query(text, query_factory) entities = processed_query.entities expected_entity = QueryEntity.from_query(processed_query.query, Span(3, 8), entity_type='show') assert entities[0] == expected_entity assert entities[1].entity.type == 'range' assert entities[1].span == Span(19, 30) assert 'children' in entities[1].entity.value assert entities[1].entity.value['children'][0].entity.type == 'sys_time' @pytest.mark.load @pytest.mark.special def test_load_special_chars_4(query_factory): """Tests loading a query with special characters""" text = 'is {s.o.b.|show} ,, gonna be on at {{8 p.m.|sys_time}|range}?' processed_query = markup.load_query(text, query_factory) entities = processed_query.entities expected_entity = QueryEntity.from_query(processed_query.query, Span(3, 8), entity_type='show') assert entities[0] == expected_entity assert entities[1].entity.type == 'range' assert entities[1].span == Span(28, 33) assert 'children' in entities[1].entity.value assert entities[1].entity.value['children'][0].entity.type == 'sys_time' @pytest.mark.load @pytest.mark.special def test_load_special_chars_5(query_factory): """Tests loading a query with special characters""" text = 'what christmas movies are , showing at {{8pm|sys_time}|range}' processed_query = markup.load_query(text, query_factory) assert len(processed_query.entities) == 1 entity = processed_query.entities[0] assert entity.span == Span(42, 44) assert entity.normalized_text == '8pm' @pytest.mark.load @pytest.mark.special def test_load_special_chars_6(query_factory): """Tests loading a query with special characters""" text = "what's on {after {8 p.m.|sys_time}|range}?" processed_query = markup.load_query(text, query_factory) entities = processed_query.entities assert len(entities) == 1 assert entities[0].text == 'after 8 p.m.' assert entities[0].normalized_text == 'after 8 p m' assert entities[0].span == Span(10, 21) @pytest.mark.load @pytest.mark.group def test_load_group(query_factory): """Tests loading a query with an entity group""" text = "a [{large|size} {latte|product} with {nonfat milk|option}|product] please" processed_query = markup.load_query(text, query_factory) entities = processed_query.entities assert len(entities) == 3 assert entities[0].text == 'large' assert entities[0].entity.type == 'size' assert entities[0].span == Span(2, 6) assert entities[0].parent == entities[1] assert entities[1].text == 'latte' assert entities[1].entity.type == 'product' assert entities[1].span == Span(8, 12) assert entities[1].children == (entities[0], entities[2]) assert entities[2].text == 'nonfat milk' assert entities[2].entity.type == 'option' assert entities[2].span == Span(19, 29) assert entities[2].parent == entities[1] @pytest.mark.load @pytest.mark.group def test_load_group_nested(query_factory): """Tests loading a query with a nested entity group""" text = ('Order [{one|quantity} {large|size} {Tesora|product} with [{medium|size} ' '{cream|option}|option] and [{medium|size} {sugar|option}|option]|product]') processed_query = markup.load_query(text, query_factory) entities = processed_query.entities assert len(entities) == 7 assert entities[0].text == 'one' assert entities[0].entity.type == 'quantity' assert entities[0].span == Span(6, 8) assert entities[0].parent == entities[2] assert entities[1].text == 'large' assert entities[1].entity.type == 'size' assert entities[1].span == Span(10, 14) assert entities[1].parent == entities[2] assert entities[2].text == 'Tesora' assert entities[2].entity.type == 'product' assert entities[2].span == Span(16, 21) assert entities[2].children == (entities[0], entities[1], entities[4], entities[6]) assert entities[3].text == 'medium' assert entities[3].entity.type == 'size' assert entities[3].span == Span(28, 33) assert entities[3].parent == entities[4] assert entities[4].text == 'cream' assert entities[4].entity.type == 'option' assert entities[4].span == Span(35, 39) assert entities[4].parent == entities[2] assert entities[4].children == (entities[3],) assert entities[5].text == 'medium' assert entities[5].entity.type == 'size' assert entities[5].span == Span(45, 50) assert entities[5].parent == entities[6] assert entities[6].text == 'sugar' assert entities[6].entity.type == 'option' assert entities[6].span == Span(52, 56) assert entities[6].parent == entities[2] assert entities[6].children == (entities[5],) @pytest.mark.load @pytest.mark.group def test_load_groups(query_factory): """Tests loading a query with multiple top level entity groups""" text = ('Order [{one|quantity} {large|size} {Tesora|product} with ' '[{medium|size} {cream|option}|option]|product] from ' '[{Philz|store} in {Downtown Sunnyvale|location}|store]') processed_query = markup.load_query(text, query_factory) entities = processed_query.entities assert len(entities) == 7 assert entities[0].text == 'one' assert entities[0].entity.type == 'quantity' assert entities[0].span == Span(6, 8) assert entities[0].parent == entities[2] assert entities[1].text == 'large' assert entities[1].entity.type == 'size' assert entities[1].span == Span(10, 14) assert entities[1].parent == entities[2] assert entities[2].text == 'Tesora' assert entities[2].entity.type == 'product' assert entities[2].span == Span(16, 21) assert entities[2].children == (entities[0], entities[1], entities[4]) assert entities[3].text == 'medium' assert entities[3].entity.type == 'size' assert entities[3].span == Span(28, 33) assert entities[3].parent == entities[4] assert entities[4].text == 'cream' assert entities[4].entity.type == 'option' assert entities[4].span == Span(35, 39) assert entities[4].parent == entities[2] assert entities[4].children == (entities[3],) assert entities[5].text == 'Philz' assert entities[5].entity.type == 'store' assert entities[5].span == Span(46, 50) assert entities[5].children == (entities[6],) assert entities[6].text == 'Downtown Sunnyvale' assert entities[6].entity.type == 'location' assert entities[6].span == Span(55, 72) assert entities[6].parent == entities[5] @pytest.mark.dump def test_dump_basic(query_factory): """Tests dumping a basic query""" query_text = 'A basic query' query = query_factory.create_query(query_text) processed_query = ProcessedQuery(query) assert markup.dump_query(processed_query) == query_text @pytest.mark.dump def test_dump_entity(query_factory): """Tests dumping a basic query with an entity""" query_text = 'When does the Elm Street store close?' query = query_factory.create_query(query_text) entities = [QueryEntity.from_query(query, Span(14, 23), entity_type='store_name')] processed_query = ProcessedQuery(query, entities=entities) markup_text = 'When does the {Elm Street|store_name} store close?' assert markup.dump_query(processed_query) == markup_text assert markup.dump_query(processed_query, no_entity=True) == query_text @pytest.mark.dump def test_dump_role(query_factory): """Tests dumping a basic query with an entity with a role""" query_text = 'What stores are open between 3 and 5' query = query_factory.create_query(query_text) entities = [ QueryEntity.from_query(query, Span(29, 29), entity_type='sys_time', role='open_hours'), QueryEntity.from_query(query, Span(35, 35), entity_type='sys_time', role='close_hours') ] processed_query = ProcessedQuery(query, entities=entities) markup_text = ('What stores are open between {3|sys_time|open_hours} and ' '{5|sys_time|close_hours}') entity_text = 'What stores are open between {3|sys_time} and {5|sys_time}' assert markup.dump_query(processed_query) == markup_text assert markup.dump_query(processed_query, no_role=True) == entity_text assert markup.dump_query(processed_query, no_role=True, no_entity=True) == query_text @pytest.mark.dump def test_dump_entities(query_factory): """Tests dumping a basic query with two entities""" query_text = 'When does the Elm Street store close on Monday?' query = query_factory.create_query(query_text) entities = [QueryEntity.from_query(query, Span(14, 23), entity_type='store_name'), QueryEntity.from_query(query, Span(40, 45), entity_type='sys_time')] processed_query = ProcessedQuery(query, entities=entities) markup_text = 'When does the {Elm Street|store_name} store close on {Monday|sys_time}?' assert markup.dump_query(processed_query) == markup_text assert markup.dump_query(processed_query, no_entity=True) == query_text @pytest.mark.dump @pytest.mark.nested def test_dump_nested(query_factory): """Tests dumping a query with a nested system entity""" query_text = 'show me houses under 600,000 dollars' query = query_factory.create_query(query_text) nested = NestedEntity.from_query(query, Span(0, 6), parent_offset=21, entity_type='sys_number') raw_entity = Entity('600,000 dollars', 'price', value={'children': [nested]}) entities = [QueryEntity.from_query(query, Span(21, 35), entity=raw_entity)] processed_query = ProcessedQuery(query, entities=entities) markup_text = 'show me houses under {{600,000|sys_number} dollars|price}' assert markup.dump_query(processed_query) == markup_text assert markup.dump_query(processed_query, no_group=True) == markup_text assert markup.dump_query(processed_query, no_entity=True) == query_text @pytest.mark.dump @pytest.mark.nested def test_dump_multi_nested(query_factory): """Tests dumping a query with multiple nested system entities""" query_text = 'show me houses between 600,000 and 1,000,000 dollars' query = query_factory.create_query(query_text) lower = NestedEntity.from_query(query, Span(8, 14), parent_offset=15, entity_type='sys_number') upper = NestedEntity.from_query(query, Span(20, 28), parent_offset=15, entity_type='sys_number') raw_entity = Entity('between 600,000 dollars and 1,000,000', 'price', value={'children': [lower, upper]}) entities = [QueryEntity.from_query(query, Span(15, 51), entity=raw_entity)] processed_query = ProcessedQuery(query, entities=entities) markup_text = ('show me houses {between {600,000|sys_number} and ' '{1,000,000|sys_number} dollars|price}') assert markup.dump_query(processed_query) == markup_text assert markup.dump_query(processed_query, no_group=True) == markup_text assert markup.dump_query(processed_query, no_entity=True) == query_text @pytest.mark.dump @pytest.mark.group def test_dump_group(query_factory): """Tests dumping a query with an entity group""" query_text = 'a large latte with nonfat milk please' query = query_factory.create_query(query_text) size = QueryEntity.from_query(query, Span(2, 6), entity_type='size') option = QueryEntity.from_query(query, Span(19, 29), entity_type='option') product = QueryEntity.from_query(query, Span(8, 12), entity_type='product', children=(size, option)) processed_query = ProcessedQuery(query, entities=[size, product, option]) markup_text = "a [{large|size} {latte|product} with {nonfat milk|option}|product] please" entity_text = "a {large|size} {latte|product} with {nonfat milk|option} please" group_text = "a [large latte with nonfat milk|product] please" assert markup.dump_query(processed_query) == markup_text assert markup.dump_query(processed_query, no_group=True) == entity_text assert markup.dump_query(processed_query, no_entity=True) == group_text assert markup.dump_query(processed_query, no_group=True, no_entity=True) == query_text @pytest.mark.dump @pytest.mark.group def test_dump_group_with_role(query_factory): """Tests dumping a query with an entity group with role type""" query_text = 'a large latte with nonfat milk please' query = query_factory.create_query(query_text) size = QueryEntity.from_query(query, Span(2, 6), entity_type='size') option = QueryEntity.from_query(query, Span(19, 29), entity_type='option', role='beverage') product = QueryEntity.from_query(query, Span(8, 12), entity_type='dish-type', role='beverage', children=(size, option)) processed_query = ProcessedQuery(query, entities=[size, product, option]) markup_text = "a [{large|size} {latte|dish-type|beverage} with " \ "{nonfat milk|option|beverage}|dish-type] please" entity_text = "a {large|size} {latte|dish-type|beverage} with " \ "{nonfat milk|option|beverage} please" group_text = "a [large latte with nonfat milk|dish-type] please" assert markup.dump_query(processed_query) == markup_text assert markup.dump_query(processed_query, no_group=True) == entity_text assert markup.dump_query(processed_query, no_entity=True, no_role=True) == group_text assert markup.dump_query(processed_query, no_group=True, no_entity=True, no_role=True) == query_text @pytest.mark.dump @pytest.mark.group def test_dump_group_nested(query_factory): """Tests dumping a query with nested entity groups""" query_text = 'Order one large Tesora with medium cream and medium sugar' query = query_factory.create_query(query_text) entities = [ QueryEntity.from_query(query, Span(6, 8), entity_type='quantity'), QueryEntity.from_query(query, Span(10, 14), entity_type='size'), QueryEntity.from_query(query, Span(16, 21), entity_type='product'), QueryEntity.from_query(query, Span(28, 33), entity_type='size'), QueryEntity.from_query(query, Span(35, 39), entity_type='option'), QueryEntity.from_query(query, Span(45, 50), entity_type='size'), QueryEntity.from_query(query, Span(52, 56), entity_type='option') ] entities[4] = entities[4].with_children((entities[3],)) entities[6] = entities[6].with_children((entities[5],)) entities[2] = entities[2].with_children((entities[0], entities[1], entities[4], entities[6])) processed_query = ProcessedQuery(query, entities=entities) markup_text = ('Order [{one|quantity} {large|size} {Tesora|product} with [{medium|size} ' '{cream|option}|option] and [{medium|size} {sugar|option}|option]|product]') entity_text = ('Order {one|quantity} {large|size} {Tesora|product} with {medium|size} ' '{cream|option} and {medium|size} {sugar|option}') group_text = ('Order [one large Tesora with [medium ' 'cream|option] and [medium sugar|option]|product]') assert markup.dump_query(processed_query) == markup_text assert markup.dump_query(processed_query, no_group=True) == entity_text assert markup.dump_query(processed_query, no_entity=True) == group_text assert markup.dump_query(processed_query, no_group=True, no_entity=True) == query_text @pytest.mark.dump @pytest.mark.group def test_dump_group_nested_2(query_factory): """Tests dumping a query with nested entity groups""" query_text = 'Can I get one curry sauce with my rice ball with house salad' query = query_factory.create_query(query_text) entities = [ QueryEntity.from_query(query, Span(10, 12), entity_type='sys_number', role='quantity'), QueryEntity.from_query(query, Span(14, 24), entity_type='option'), QueryEntity.from_query(query, Span(34, 59), entity_type='dish') ] entities[1] = entities[1].with_children((entities[0],)) entities[2] = entities[2].with_children((entities[1],)) processed_query = ProcessedQuery(query, entities=entities) markup_text = ('Can I get [[{one|sys_number|quantity} {curry sauce|option}|option] ' 'with my {rice ball with house salad|dish}|dish]') entity_text = ('Can I get {one|sys_number|quantity} {curry sauce|option} ' 'with my {rice ball with house salad|dish}') role_text = ('Can I get {one|quantity} curry sauce ' 'with my rice ball with house salad') group_text = ('Can I get [[one curry sauce|option] ' 'with my rice ball with house salad|dish]') assert markup.dump_query(processed_query) == markup_text assert markup.dump_query(processed_query, no_group=True) == entity_text assert markup.dump_query(processed_query, no_group=True, no_entity=True) == role_text assert markup.dump_query(processed_query, no_entity=True, no_role=True) == group_text assert markup.dump_query(processed_query, no_group=True, no_entity=True, no_role=True) == query_text @pytest.mark.dump @pytest.mark.group def test_dump_groups(query_factory): """Tests dumping a query with multiple top level entity groups""" query_text = 'Order one large Tesora with medium cream from Philz in Downtown Sunnyvale' query = query_factory.create_query(query_text) entities = [ QueryEntity.from_query(query, Span(6, 8), entity_type='quantity'), QueryEntity.from_query(query, Span(10, 14), entity_type='size'), QueryEntity.from_query(query, Span(16, 21), entity_type='product'), QueryEntity.from_query(query, Span(28, 33), entity_type='size'), QueryEntity.from_query(query, Span(35, 39), entity_type='option'), QueryEntity.from_query(query, Span(46, 50), entity_type='store'), QueryEntity.from_query(query, Span(55, 72), entity_type='location') ] entities[4] = entities[4].with_children((entities[3],)) entities[2] = entities[2].with_children((entities[0], entities[1], entities[4])) entities[5] = entities[5].with_children((entities[6],)) processed_query = ProcessedQuery(query, entities=entities) markup_text = ('Order [{one|quantity} {large|size} {Tesora|product} with ' '[{medium|size} {cream|option}|option]|product] from ' '[{Philz|store} in {Downtown Sunnyvale|location}|store]') assert markup.dump_query(processed_query) == markup_text @pytest.mark.load @pytest.mark.dump @pytest.mark.group def test_load_dump_groups(query_factory): """Tests that load_query and dump_query are reversible""" text = ('Order [{one|quantity} {large|size} {Tesora|product} with ' '[{medium|size} {cream|option}|option]|product] from ' '[{Philz|store} in {Downtown Sunnyvale|location}|store]') processed_query = markup.load_query(text, query_factory) markup_text = markup.dump_query(processed_query) assert text == markup_text @pytest.mark.load @pytest.mark.dump @pytest.mark.group def test_load_dump_groups_roles(query_factory): """Tests that load_query and dump_query are reversible""" text = ('Order [{one|sys_number|quantity} {large|size} {Tesora|product|dish} with ' '[{medium|size} {cream|option|addin}|option]|product]') processed_query = markup.load_query(text, query_factory) markup_text = markup.dump_query(processed_query) assert text == markup_text @pytest.mark.load @pytest.mark.dump def test_load_dump_2(query_factory): """Tests that load_query and dump_query are reversible""" text = ("i'm extra hungry get me a {chicken leg|dish}, [{1|quantity} " "{kheema nan|dish}|dish] [{2|quantity} regular {nans|dish}|dish] " "[{one|quantity} {chicken karahi|dish}|dish], [{1|quantity} " "{saag paneer|dish}|dish] and [{1|quantity} {chicken biryani|dish}|dish]") processed_query = markup.load_query(text, query_factory) markup_text = markup.dump_query(processed_query) assert text == markup_text def test_bootstrap_query_with_entities(query_factory): query_text = 'Can I get one curry sauce with my rice ball with house salad' query = query_factory.create_query(query_text) entities = [ QueryEntity.from_query(query, Span(10, 12), entity_type='sys_number', role='quantity'), QueryEntity.from_query(query, Span(14, 24), entity_type='option'), QueryEntity.from_query(query, Span(34, 59), entity_type='dish') ] entities[1] = entities[1].with_children((entities[0],)) entities[2] = entities[2].with_children((entities[1],)) confidence = { 'domains': { 'food': 0.95, 'music': 0.05 }, 'intents': { 'get_comestibles': 0.99, 'reorder': 0.01 }, 'entities': [ {'sys_number': 0.9}, {'option': 0.99}, {'dish': 0.65} ], 'roles': [ {'quantity': 0.8, 'quality': 0.2}, None, None ] } processed_query = ProcessedQuery( query, domain='food', intent='get_comestibles', entities=entities, confidence=confidence ) bootstrap_data = markup.bootstrap_query_row(processed_query, show_confidence=True) expected_data = { 'query': ('Can I get [[{one|sys_number|quantity} {curry sauce|option}|option] ' 'with my {rice ball with house salad|dish}|dish]'), 'domain': 'food', 'domain_conf': 0.95, 'intent': 'get_comestibles', 'intent_conf': 0.99, 'entity_conf': 0.65, 'role_conf': 0.8 } assert bootstrap_data == expected_data def test_bootstrap_query_no_entity(query_factory): """"Tests bootstrap output for a query without entities""" query_text = 'cancel the timer' query = query_factory.create_query(query_text) confidence = { 'domains': { 'times_and_dates': 0.95, 'espionage': 0.05 }, 'intents': { 'stop_timer': 0.9, 'start_timer': 0.07, 'cut_blue_wire': 0.03 }, 'entities': [], 'roles': [] } processed_query = ProcessedQuery( query, domain='times_and_dates', intent='stop_timer', entities=[], confidence=confidence ) bootstrap_data = markup.bootstrap_query_row(processed_query, show_confidence=True) expected_data = { 'query': 'cancel the timer', 'domain': 'times_and_dates', 'domain_conf': 0.95, 'intent': 'stop_timer', 'intent_conf': 0.9, 'entity_conf': 1.0, 'role_conf': 1.0 } assert bootstrap_data == expected_data

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1c5bf5712c64da44df655f05b3579218e605402a

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py

Python

project/poisson1d.py

amit17133129/pyMG-2016

b82a60811bb0a8b91d8793c47177a240221f9176

[ "BSD-2-Clause" ]

2

2016-04-04T15:20:50.000Z

2020-08-01T19:28:55.000Z

project/poisson1d.py

amit17133129/pyMG-2016

b82a60811bb0a8b91d8793c47177a240221f9176

[ "BSD-2-Clause" ]

1

2020-10-02T05:44:45.000Z

project/poisson1d.py

amit17133129/pyMG-2016

b82a60811bb0a8b91d8793c47177a240221f9176

[ "BSD-2-Clause" ]

11

2016-03-26T18:37:06.000Z

2020-10-01T19:44:55.000Z

# coding=utf-8 import numpy as np import scipy.sparse as sp from pymg.problem_base import ProblemBase class Poisson1D(ProblemBase): """Implementation of the 1D Poission problem. Here we define the 1D Poisson problem :math:`-\Delta u = 0` with Dirichlet-Zero boundary conditions. This is the homogeneous problem, derive from this class if you want to play around with different RHS. Attributes: dx (float): mesh size """ def __init__(self, ndofs, *args, **kwargs): """Initialization routine for the Poisson1D problem Args: ndofs (int): number of degrees of freedom (see :attr:`pymg.problem_base.ProblemBase.ndofs`) *args: Variable length argument list **kwargs: Arbitrary keyword arguments """ self.dx = 1.0 / (ndofs + 1) # compute system matrix A, scale by 1/dx^2 A = 1.0 / (self.dx ** 2) * self.__get_system_matrix(ndofs) rhs = self.__get_rhs(ndofs) super(Poisson1D, self).__init__(ndofs, A, rhs, *args, **kwargs) @staticmethod def __get_system_matrix(ndofs): """Helper routine to get the system matrix discretizing :math:`-Delta` with second order FD Args: ndofs (int): number of inner grid points (no boundaries!) Returns: scipy.sparse.csc_matrix: sparse system matrix A of size :attr:`ndofs` x :attr:`ndofs` """ data = np.array([[2] * ndofs, [-1] * ndofs, [-1] * ndofs]) diags = np.array([0, -1, 1]) return sp.spdiags(data, diags, ndofs, ndofs, format='csc') @staticmethod def __get_rhs(ndofs): """Helper routine to set the right-hand side Args: ndofs (int): number of inner grid points (no boundaries!) Returns: numpy.ndarray: the right-hand side vector of size :attr:`ndofs` """ return np.zeros(ndofs) @property def u_exact(self): """Routine to compute the exact solution Returns: numpy.ndarray: exact solution array of size :attr:`ndofs` """ return np.zeros(self.ndofs) @property def domain(self): return np.array([(i + 1) * self.dx for i in range(self.ndofs)]) @ProblemBase.ndofs.setter def ndofs(self, val): ProblemBase.ndofs.fset(self, val) self.dx = 1.0 / (val + 1) # compute system matrix A, scale by 1/dx^2 self.A = 1.0 / (self.dx ** 2) * self.__get_system_matrix(val) self.rhs = self.__get_rhs(self._ndofs) class Poisson1DPeriodic(ProblemBase): """Implementation of the 1D Poission problem. Here we define the 1D Poisson problem :math:`-\Delta u = 0` with Dirichlet-Zero boundary conditions. This is the homogeneous problem, derive from this class if you want to play around with different RHS. Attributes: dx (float): mesh size """ def __init__(self, ndofs, sigma, *args, **kwargs): """Initialization routine for the Poisson1D problem Args: ndofs (int): number of degrees of freedom (see :attr:`pymg.problem_base.ProblemBase.ndofs`) *args: Variable length argument list **kwargs: Arbitrary keyword arguments """ self.dx = 1.0 / ndofs self.sigma = sigma # compute system matrix A, scale by 1/dx^2 A = self.__get_system_matrix(ndofs) A[0, -1] = A[0, 1] A[-1, 0] = A[1, 0] A = -sigma * 1.0 / (self.dx ** 2) * A rhs = self.__get_rhs(ndofs) super(Poisson1DPeriodic, self).__init__(ndofs, A, rhs, *args, **kwargs) @staticmethod def __get_system_matrix(ndofs): """Helper routine to get the system matrix discretizing :math:`-Delta` with second order FD Args: ndofs (int): number of inner grid points (no boundaries!) Returns: scipy.sparse.csc_matrix: sparse system matrix A of size :attr:`ndofs` x :attr:`ndofs` """ data = np.array([[2] * ndofs, [-1] * ndofs, [-1] * ndofs]) diags = np.array([0, -1, 1]) return sp.spdiags(data, diags, ndofs, ndofs, format='csc') @staticmethod def __get_rhs(ndofs): """Helper routine to set the right-hand side Args: ndofs (int): number of inner grid points (no boundaries!) Returns: numpy.ndarray: the right-hand side vector of size :attr:`ndofs` """ return np.zeros(ndofs) @property def u_exact(self): """Routine to compute the exact solution Returns: numpy.ndarray: exact solution array of size :attr:`ndofs` """ return np.zeros(self.ndofs) @property def domain(self): return np.array([(i) * self.dx for i in range(self.ndofs)]) @ProblemBase.ndofs.setter def ndofs(self, val): ProblemBase.ndofs.fset(self, val) self.dx = 1.0 / val # compute system matrix A, scale by 1/dx^2 self.A = -self.sigma * 1.0 / (self.dx ** 2) * self.__get_system_matrix(val) self.A[0, -1] = self.A[0, 1] self.A[-1, 0] = self.A[1, 0] self.rhs = self.__get_rhs(self._ndofs)

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py

Python

code/code_annotation/code_retrieval/__init__.py

sunlab-osu/CoaCor

e5df8fd38830590b9f132dd68bc26c630e41e509

[ "Apache-2.0" ]

30

2019-03-08T05:11:32.000Z

2021-12-09T12:11:29.000Z

code/code_annotation/code_retrieval/__init__.py

sunlab-osu/CoaCor

e5df8fd38830590b9f132dd68bc26c630e41e509

[ "Apache-2.0" ]

1

2020-04-18T14:46:48.000Z

2020-06-17T20:08:37.000Z

code/code_annotation/code_retrieval/__init__.py

sunlab-osu/CoaCor

e5df8fd38830590b9f132dd68bc26c630e41e509

[ "Apache-2.0" ]

4

2019-07-02T05:25:11.000Z

2021-05-27T12:52:21.000Z

from CodeRetrievalCritic import *

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py

Python

src/bookmarks_converter/__init__.py

radam9/bookmarks_parser

fc508908fe4b5551d517e7da7120bcc2480200f7

[ "MIT" ]

8

2021-02-19T09:28:31.000Z

2022-02-16T02:33:26.000Z

src/bookmarks_converter/__init__.py

radam9/bookmarks_parser

fc508908fe4b5551d517e7da7120bcc2480200f7

[ "MIT" ]

50

2021-02-06T14:16:38.000Z

2022-03-01T17:55:05.000Z

src/bookmarks_converter/__init__.py

radam9/bookmarks_parser

fc508908fe4b5551d517e7da7120bcc2480200f7

[ "MIT" ]

1

2021-09-15T16:45:08.000Z

from .core import BookmarksConverter

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98c0697b8141518e4ac7ec1fde16be14dd07dd8a

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py

Python

{{cookiecutter.project_slug}}/tests/test_import.py

tobiasraabe/cookiecutter-pytask

425bbb8480e5eaae560dbb5e0cb36685e8fb4e30

[ "MIT" ]

null

{{cookiecutter.project_slug}}/tests/test_import.py

tobiasraabe/cookiecutter-pytask

425bbb8480e5eaae560dbb5e0cb36685e8fb4e30

[ "MIT" ]

9

2022-01-24T08:04:54.000Z

2022-03-21T20:28:30.000Z

{{cookiecutter.project_slug}}/tests/test_import.py

pytask-dev/cookiecutter-pytask

425bbb8480e5eaae560dbb5e0cb36685e8fb4e30

[ "MIT" ]

null

from __future__ import annotations import {{ cookiecutter.project_slug }} def test_import(): assert hasattr({{ cookiecutter.project_slug }}, "__version__")

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6

98e79458318bbe0f9ee035eed54230f1e3ce48fc

40

py

Python

cpp/__init__.py

hwangyale/AlphaGomoku

7c85a71c710fa8d114b3591e4fd27c8649caccbb

[ "MIT" ]

3

2018-10-30T07:07:40.000Z

2019-11-22T12:32:32.000Z

cpp/__init__.py

hwangyale/AlphaGomoku

7c85a71c710fa8d114b3591e4fd27c8649caccbb

[ "MIT" ]

null

cpp/__init__.py

hwangyale/AlphaGomoku

7c85a71c710fa8d114b3591e4fd27c8649caccbb

[ "MIT" ]

null

from .cpp_board_wrapper import CPPBoard

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1

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1

0

1

0

6

98f31f6e4b926fc88efb628054fde7c5ea8454a5

2,343

py

Python

ad_api/sp_products/negative_product_targeting.py

854350999/python-amazon-advertising-api

ec52f72dab85ad67e271bfd6248071f00e9c7292

[ "MIT" ]

null

ad_api/sp_products/negative_product_targeting.py

854350999/python-amazon-advertising-api

ec52f72dab85ad67e271bfd6248071f00e9c7292

[ "MIT" ]

null

ad_api/sp_products/negative_product_targeting.py

854350999/python-amazon-advertising-api

ec52f72dab85ad67e271bfd6248071f00e9c7292

[ "MIT" ]

null

from ..client import Client class NegativeProductTargeting(Client): def create_negative_targets(self, data): self.uri_path = "/v2/sp/negativeTargets" self.method = "post" self.data = data return self.execute() def update_negative_targets(self, data): self.uri_path = "/v2/sp/negativeTargets" self.method = "put" self.data = data return self.execute() def get_negative_targets(self, start_index: int = 0, count: int = None, state_filter: str = None, campaign_id_filter: str = None, ad_group_id_filter: str = None, target_id_filter: str = None): self.uri_path = "/v2/sp/negativeTargets" self.params = { "startIndex": start_index, "count": count, "stateFilter": state_filter, "campaignIdFilter": campaign_id_filter, "adGroupIdFilter": ad_group_id_filter, "targetIdFilter": target_id_filter } self.method = "get" return self.execute() def get_negative_targets_by_id(self, target_id): self.uri_path = "/v2/sp/negativeTargets/{}".format(target_id) self.method = "get" return self.execute() def delete_negative_targets_by_id(self, target_id): self.uri_path = "/v2/sp/negativeTargets/{}".format(target_id) self.method = "delete" return self.execute() def get_negative_targets_extended(self, start_index: int = 0, count: int = None, state_filter: str = None, campaign_id_filter: str = None, ad_group_id_filter: str = None, target_id_filter: str = None): self.uri_path = "/v2/sp/negativeTargets/extended" self.method = "get" self.params = { "startIndex": start_index, "count": count, "stateFilter": state_filter, "campaignIdFilter": campaign_id_filter, "adGroupIdFilter": ad_group_id_filter, "targetIdFilter": target_id_filter } return self.execute() def get_negative_targets_extended_by_id(self, target_id): self.uri_path = "/v2/sp/negativeTargets/extended/{}".format(target_id) self.method = "get" return self.execute()

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null

0

1

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null

0

6

c7ab45bfa2bcd34f9e8d66769433a3036296ad1e

213

py

Python

common.py

sujeevraja/utility-scripts

464fedb2b2430567f1d9162834bf64bac14ddc3d

[ "MIT" ]

null

common.py

sujeevraja/utility-scripts

464fedb2b2430567f1d9162834bf64bac14ddc3d

[ "MIT" ]

null

common.py

sujeevraja/utility-scripts

464fedb2b2430567f1d9162834bf64bac14ddc3d

[ "MIT" ]

null

class ScriptException(Exception): """Custom exception class with message for this module.""" def __init__(self, value): self.value = value def __repr__(self): return repr(self.value)

23.666667

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0.234742

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null

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1

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1

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6

c7dfe2cc00ddc5c870039ca299d4ad3811035262

34

py

Python

CLR-master/__init__.py

dr-yali/Bone-MRI

54c50b2da26190575ad0913f715bc15a7dbd857f

[ "MIT" ]

1,201

2017-03-23T07:19:33.000Z

2022-03-29T08:59:07.000Z

CLR/__init__.py

prateekvyas1996/Facies-Prediction-From-well-log-using-deep-learning

68645ce1b40f9263f3ac5c7758ba4923377cb3d0

[ "MIT" ]

18

2017-03-25T00:08:36.000Z

2021-05-03T07:12:05.000Z

CLR/__init__.py

prateekvyas1996/Facies-Prediction-From-well-log-using-deep-learning

68645ce1b40f9263f3ac5c7758ba4923377cb3d0

[ "MIT" ]

293

2017-03-24T04:37:06.000Z

2022-02-16T18:33:54.000Z

from .clr_callback import CyclicLR

34

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5

34

5.8

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1

0

6

c7e50d652b755eb3d65c592e97fcf494e22a2b51

15,566

py

Python

tests/processors/graphic_matching_test.py

elifesciences/sciencebeam-parser

66964f283612b8d6fa8a23ad8790292c1ec07651

[ "MIT" ]

13

2021-08-04T12:11:17.000Z

2022-03-28T20:41:20.000Z

tests/processors/graphic_matching_test.py

elifesciences/sciencebeam-parser

66964f283612b8d6fa8a23ad8790292c1ec07651

[ "MIT" ]

33

2021-08-05T08:37:59.000Z

2022-03-29T18:42:09.000Z

tests/processors/graphic_matching_test.py

elifesciences/sciencebeam-parser

66964f283612b8d6fa8a23ad8790292c1ec07651

[ "MIT" ]

1

2022-01-05T14:53:06.000Z

import logging from pathlib import Path from typing import Sequence, Tuple from unittest.mock import MagicMock import pytest import PIL.Image from sciencebeam_parser.document.layout_document import ( LayoutBlock, LayoutGraphic, LayoutPageCoordinates, LayoutToken ) from sciencebeam_parser.document.semantic_document import ( SemanticContentWrapper, SemanticFigure, SemanticGraphic, SemanticLabel, SemanticMixedContentWrapper ) from sciencebeam_parser.processors.graphic_matching import ( BoundingBoxDistanceGraphicMatcher, GraphicRelatedBlockTextGraphicMatcher, OpticalCharacterRecognitionGraphicMatcher, get_bounding_box_list_distance ) LOGGER = logging.getLogger(__name__) COORDINATES_1 = LayoutPageCoordinates( x=10, y=100, width=200, height=100, page_number=1 ) GRAPHIC_ABOVE_FIGURE_COORDINATES_1 = LayoutPageCoordinates( x=10, y=100, width=200, height=100, page_number=1 ) FIGURE_BELOW_GRAPHIC_COORDINATES_1 = LayoutPageCoordinates( x=10, y=GRAPHIC_ABOVE_FIGURE_COORDINATES_1.y + GRAPHIC_ABOVE_FIGURE_COORDINATES_1.height + 10, width=200, height=20, page_number=1 ) FAR_AWAY_COORDINATES_1 = LayoutPageCoordinates( x=10, y=10, width=200, height=20, page_number=10 ) FAR_AWAY_COORDINATES_2 = LayoutPageCoordinates( x=10, y=10, width=200, height=20, page_number=11 ) @pytest.fixture(name='ocr_model_mock') def _ocr_model_mock() -> MagicMock: return MagicMock(name='ocr_model') def _get_semantic_content_for_page_coordinates( coordinates: LayoutPageCoordinates ) -> SemanticContentWrapper: return SemanticFigure( layout_block=LayoutBlock.for_tokens([ LayoutToken( text='dummy', coordinates=coordinates ) ]) ) def _get_bounding_box_list_distance_sort_key( bounding_box_list_1: Sequence[LayoutPageCoordinates], bounding_box_list_2: Sequence[LayoutPageCoordinates] ) -> Tuple[float, ...]: return get_bounding_box_list_distance( bounding_box_list_1, bounding_box_list_2 ) class TestGetBoundingBoxListDistance: def test_should_return_distance_between_vertical_adjacent_bounding_boxes(self): bounding_box_distance = get_bounding_box_list_distance( [COORDINATES_1], [COORDINATES_1.move_by(dy=COORDINATES_1.height)] ) assert bounding_box_distance.page_number_diff == 0 assert bounding_box_distance.delta_x == 0 assert bounding_box_distance.delta_y == 0 assert bounding_box_distance.euclidean_distance == 0 def test_should_return_distance_between_horizontal_adjacent_bounding_boxes(self): bounding_box_distance = get_bounding_box_list_distance( [COORDINATES_1], [COORDINATES_1.move_by(dx=COORDINATES_1.width)] ) assert bounding_box_distance.page_number_diff == 0 assert bounding_box_distance.delta_x == 0 assert bounding_box_distance.delta_y == 0 assert bounding_box_distance.euclidean_distance == 0 def test_should_return_delta_x_for_bounding_box_left_right(self): bounding_box_distance = get_bounding_box_list_distance( [COORDINATES_1], [COORDINATES_1.move_by(dx=COORDINATES_1.width + 10)] ) assert bounding_box_distance.page_number_diff == 0 assert bounding_box_distance.delta_x == 10 assert bounding_box_distance.delta_y == 0 assert bounding_box_distance.euclidean_distance == 10 def test_should_return_delta_x_for_bounding_box_right_left(self): bounding_box_distance = get_bounding_box_list_distance( [COORDINATES_1.move_by(dx=COORDINATES_1.width + 10)], [COORDINATES_1] ) assert bounding_box_distance.page_number_diff == 0 assert bounding_box_distance.delta_x == 10 assert bounding_box_distance.delta_y == 0 assert bounding_box_distance.euclidean_distance == 10 def test_should_return_delta_y_for_bounding_box_above_below(self): bounding_box_distance = get_bounding_box_list_distance( [COORDINATES_1], [COORDINATES_1.move_by(dy=COORDINATES_1.height + 10)] ) assert bounding_box_distance.page_number_diff == 0 assert bounding_box_distance.delta_x == 0 assert bounding_box_distance.delta_y == 10 assert bounding_box_distance.euclidean_distance == 10 def test_should_return_delta_y_for_bounding_box_below_above(self): bounding_box_distance = get_bounding_box_list_distance( [COORDINATES_1.move_by(dy=COORDINATES_1.height + 10)], [COORDINATES_1] ) assert bounding_box_distance.page_number_diff == 0 assert bounding_box_distance.delta_x == 0 assert bounding_box_distance.delta_y == 10 assert bounding_box_distance.euclidean_distance == 10 class TestBoundingBoxDistanceGraphicMatcher: def test_should_return_empty_list_with_empty_list_of_graphics(self): result = BoundingBoxDistanceGraphicMatcher().get_graphic_matches( semantic_graphic_list=[], candidate_semantic_content_list=[SemanticMixedContentWrapper()] ) assert not result def test_should_match_graphic_above_semantic_content(self): semantic_graphic_1 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=GRAPHIC_ABOVE_FIGURE_COORDINATES_1 )) candidate_semantic_content_1 = _get_semantic_content_for_page_coordinates( coordinates=FIGURE_BELOW_GRAPHIC_COORDINATES_1 ) result = BoundingBoxDistanceGraphicMatcher().get_graphic_matches( semantic_graphic_list=[semantic_graphic_1], candidate_semantic_content_list=[ _get_semantic_content_for_page_coordinates( coordinates=FAR_AWAY_COORDINATES_1 ), candidate_semantic_content_1, _get_semantic_content_for_page_coordinates( coordinates=FAR_AWAY_COORDINATES_2 ) ] ) LOGGER.debug('result: %r', result) assert len(result) == 1 first_match = result.graphic_matches[0] assert first_match.semantic_graphic == semantic_graphic_1 assert first_match.candidate_semantic_content == candidate_semantic_content_1 def test_should_not_match_further_away_graphic_to_same_semantic_content(self): semantic_graphic_1 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=GRAPHIC_ABOVE_FIGURE_COORDINATES_1 )) candidate_semantic_content_1 = _get_semantic_content_for_page_coordinates( coordinates=FIGURE_BELOW_GRAPHIC_COORDINATES_1 ) further_away_graphic_1 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=FIGURE_BELOW_GRAPHIC_COORDINATES_1.move_by(dy=500) )) further_away_graphic_2 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=FIGURE_BELOW_GRAPHIC_COORDINATES_1.move_by(dy=1000) )) result = BoundingBoxDistanceGraphicMatcher().get_graphic_matches( semantic_graphic_list=[ further_away_graphic_1, semantic_graphic_1, further_away_graphic_2 ], candidate_semantic_content_list=[ candidate_semantic_content_1 ] ) LOGGER.debug('result: %r', result) assert len(result) == 1 first_match = result.graphic_matches[0] assert first_match.semantic_graphic == semantic_graphic_1 assert first_match.candidate_semantic_content == candidate_semantic_content_1 def test_should_not_match_empty_graphic(self): empty_semantic_graphic_1 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=COORDINATES_1._replace( width=0, height=0 ) )) candidate_semantic_content_1 = _get_semantic_content_for_page_coordinates( coordinates=COORDINATES_1 ) result = BoundingBoxDistanceGraphicMatcher().get_graphic_matches( semantic_graphic_list=[empty_semantic_graphic_1], candidate_semantic_content_list=[ candidate_semantic_content_1 ] ) LOGGER.debug('result: %r', result) assert not result def test_should_not_match_graphic_on_another_page(self): semantic_graphic_1 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=COORDINATES_1._replace( page_number=COORDINATES_1.page_number + 1 ) )) candidate_semantic_content_1 = _get_semantic_content_for_page_coordinates( coordinates=COORDINATES_1 ) result = BoundingBoxDistanceGraphicMatcher().get_graphic_matches( semantic_graphic_list=[semantic_graphic_1], candidate_semantic_content_list=[ candidate_semantic_content_1 ] ) LOGGER.debug('result: %r', result) assert not result.graphic_matches assert result.unmatched_graphics == [semantic_graphic_1] @pytest.mark.parametrize( "graphic_type,should_match", [("svg", False), ("bitmap", True)] ) def test_should_match_graphic_of_specific( self, graphic_type: str, should_match: bool ): semantic_graphic_1 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=GRAPHIC_ABOVE_FIGURE_COORDINATES_1, graphic_type=graphic_type )) candidate_semantic_content_1 = _get_semantic_content_for_page_coordinates( coordinates=FIGURE_BELOW_GRAPHIC_COORDINATES_1 ) result = BoundingBoxDistanceGraphicMatcher().get_graphic_matches( semantic_graphic_list=[semantic_graphic_1], candidate_semantic_content_list=[ candidate_semantic_content_1 ] ) LOGGER.debug('result: %r', result) if should_match: assert len(result) == 1 first_match = result.graphic_matches[0] assert first_match.semantic_graphic == semantic_graphic_1 else: assert not result.graphic_matches assert result.unmatched_graphics == [semantic_graphic_1] class TestGraphicRelatedBlockTextGraphicMatcher: @pytest.mark.parametrize( "related_text,figure_label,should_match", [ ("Figure 1", "Figure 1", True), ("Figure 1", "Figure 2", False), ("Fig 1", "Figure 1", True), ("F 1", "Figure 1", False), ("Fug 1", "Figure 1", False), ("Other\nFigure 1\nMore", "Figure 1", True) ] ) def test_should_match_based_on_figure_label( self, related_text: str, figure_label: str, should_match: bool ): semantic_graphic_1 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=FAR_AWAY_COORDINATES_1, related_block=LayoutBlock.for_text(related_text) )) candidate_semantic_content_1 = SemanticFigure([ SemanticLabel(layout_block=LayoutBlock.for_text(figure_label)) ]) result = GraphicRelatedBlockTextGraphicMatcher().get_graphic_matches( semantic_graphic_list=[semantic_graphic_1], candidate_semantic_content_list=[ candidate_semantic_content_1 ] ) LOGGER.debug('result: %r', result) if should_match: assert len(result) == 1 first_match = result.graphic_matches[0] assert first_match.semantic_graphic == semantic_graphic_1 else: assert not result.graphic_matches assert result.unmatched_graphics == [semantic_graphic_1] def test_should_ignore_layout_graphic_without_related_block( self ): semantic_graphic_1 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=FAR_AWAY_COORDINATES_1, related_block=None )) candidate_semantic_content_1 = SemanticFigure([ SemanticLabel(layout_block=LayoutBlock.for_text('Figure 1')) ]) result = GraphicRelatedBlockTextGraphicMatcher().get_graphic_matches( semantic_graphic_list=[semantic_graphic_1], candidate_semantic_content_list=[ candidate_semantic_content_1 ] ) LOGGER.debug('result: %r', result) assert not result.graphic_matches assert result.unmatched_graphics == [semantic_graphic_1] class TestOpticalCharacterRecognitionGraphicMatcher: @pytest.mark.parametrize( "ocr_text,figure_label,should_match", [ ("Figure 1", "Figure 1", True), ("Figure 1", "Figure 2", False), ("Fig 1", "Figure 1", True), ("F 1", "Figure 1", False), ("Fug 1", "Figure 1", False), ("Other\nFigure 1\nMore", "Figure 1", True) ] ) def test_should_match_based_on_figure_label( self, ocr_model_mock: MagicMock, ocr_text: str, figure_label: str, should_match: bool, tmp_path: Path ): local_graphic_path = tmp_path / 'image.png' PIL.Image.new('RGB', (10, 10), (0, 1, 2)).save(local_graphic_path) ocr_model_mock.predict_single.return_value.get_text.return_value = ocr_text semantic_graphic_1 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=FAR_AWAY_COORDINATES_1, local_file_path=str(local_graphic_path) )) candidate_semantic_content_1 = SemanticFigure([ SemanticLabel(layout_block=LayoutBlock.for_text(figure_label)) ]) result = OpticalCharacterRecognitionGraphicMatcher( ocr_model=ocr_model_mock ).get_graphic_matches( semantic_graphic_list=[semantic_graphic_1], candidate_semantic_content_list=[ candidate_semantic_content_1 ] ) LOGGER.debug('result: %r', result) if should_match: assert len(result) == 1 first_match = result.graphic_matches[0] assert first_match.semantic_graphic == semantic_graphic_1 else: assert not result.graphic_matches assert result.unmatched_graphics == [semantic_graphic_1] def test_should_ignore_layout_graphic_without_local_path( self, ocr_model_mock: MagicMock ): ocr_model_mock.predict_single.return_value.get_text.side_effect = RuntimeError semantic_graphic_1 = SemanticGraphic(layout_graphic=LayoutGraphic( coordinates=FAR_AWAY_COORDINATES_1, local_file_path=None )) candidate_semantic_content_1 = SemanticFigure([ SemanticLabel(layout_block=LayoutBlock.for_text('Figure 1')) ]) result = OpticalCharacterRecognitionGraphicMatcher( ocr_model=ocr_model_mock ).get_graphic_matches( semantic_graphic_list=[semantic_graphic_1], candidate_semantic_content_list=[ candidate_semantic_content_1 ] ) LOGGER.debug('result: %r', result) assert not result.graphic_matches assert result.unmatched_graphics == [semantic_graphic_1]

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6

1bddb289ff53be3d31895fea85fc09af69ce8295

6,883

py

Python

pay-api/tests/unit/api/test_account.py

nitheesh-aot/sbc-pay

dcb9c1bd3d2954f11c8d643aa6618d8470e3b0f7

[ "Apache-2.0" ]

null

pay-api/tests/unit/api/test_account.py

nitheesh-aot/sbc-pay

dcb9c1bd3d2954f11c8d643aa6618d8470e3b0f7

[ "Apache-2.0" ]

null

pay-api/tests/unit/api/test_account.py

nitheesh-aot/sbc-pay

dcb9c1bd3d2954f11c8d643aa6618d8470e3b0f7

[ "Apache-2.0" ]

null

# Copyright © 2019 Province of British Columbia # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests to assure the accounts end-point. Test-Suite to ensure that the /accounts endpoint is working as expected. """ import json from pay_api.models.credit_payment_account import CreditPaymentAccount from pay_api.models.payment import Payment from pay_api.models.payment_account import PaymentAccount from pay_api.schemas import utils as schema_utils from tests.utilities.base_test import ( get_claims, get_payment_request, token_header) def test_account_purchase_history(session, client, jwt, app): """Assert that the endpoint returns 200.""" token = jwt.create_jwt(get_claims(), token_header) headers = {'Authorization': f'Bearer {token}', 'content-type': 'application/json'} rv = client.post(f'/api/v1/payment-requests', data=json.dumps(get_payment_request()), headers=headers) payment: Payment = Payment.find_by_id(rv.json.get('id')) credit_account: CreditPaymentAccount = CreditPaymentAccount.find_by_id(payment.invoices[0].credit_account_id) pay_account: PaymentAccount = PaymentAccount.find_by_id(credit_account.account_id) rv = client.post(f'/api/v1/accounts/{pay_account.auth_account_id}/payments/queries', data=json.dumps({}), headers=headers) assert rv.status_code == 200 def test_account_purchase_history_pagination(session, client, jwt, app): """Assert that the endpoint returns 200.""" token = jwt.create_jwt(get_claims(), token_header) headers = {'Authorization': f'Bearer {token}', 'content-type': 'application/json'} for i in range(10): rv = client.post(f'/api/v1/payment-requests', data=json.dumps(get_payment_request()), headers=headers) payment: Payment = Payment.find_by_id(rv.json.get('id')) credit_account: CreditPaymentAccount = CreditPaymentAccount.find_by_id(payment.invoices[0].credit_account_id) pay_account: PaymentAccount = PaymentAccount.find_by_id(credit_account.account_id) rv = client.post(f'/api/v1/accounts/{pay_account.auth_account_id}/payments/queries?page=1&limit=5', data=json.dumps({}), headers=headers) assert rv.status_code == 200 assert rv.json.get('total') == 10 assert len(rv.json.get('items')) == 5 def test_account_purchase_history_invalid_request(session, client, jwt, app): """Assert that the endpoint returns 400.""" token = jwt.create_jwt(get_claims(), token_header) headers = {'Authorization': f'Bearer {token}', 'content-type': 'application/json'} rv = client.post(f'/api/v1/payment-requests', data=json.dumps(get_payment_request()), headers=headers) payment: Payment = Payment.find_by_id(rv.json.get('id')) credit_account: CreditPaymentAccount = CreditPaymentAccount.find_by_id(payment.invoices[0].credit_account_id) pay_account: PaymentAccount = PaymentAccount.find_by_id(credit_account.account_id) search_filter = { 'businessIdentifier': 1111 } rv = client.post(f'/api/v1/accounts/{pay_account.auth_account_id}/payments/queries?page=1&limit=5', data=json.dumps(search_filter), headers=headers) assert rv.status_code == 400 assert schema_utils.validate(rv.json, 'problem')[0] def test_account_purchase_history_export_as_csv(session, client, jwt, app): """Assert that the endpoint returns 200.""" token = jwt.create_jwt(get_claims(), token_header) headers = { 'Authorization': f'Bearer {token}', 'content-type': 'application/json' } rv = client.post(f'/api/v1/payment-requests', data=json.dumps(get_payment_request()), headers=headers) payment: Payment = Payment.find_by_id(rv.json.get('id')) credit_account: CreditPaymentAccount = CreditPaymentAccount.find_by_id(payment.invoices[0].credit_account_id) pay_account: PaymentAccount = PaymentAccount.find_by_id(credit_account.account_id) headers = { 'Authorization': f'Bearer {token}', 'content-type': 'application/json', 'Accept': 'text/csv' } rv = client.post(f'/api/v1/accounts/{pay_account.auth_account_id}/payments/reports', data=json.dumps({}), headers=headers) assert rv.status_code == 201 def test_account_purchase_history_export_as_pdf(session, client, jwt, app): """Assert that the endpoint returns 200.""" token = jwt.create_jwt(get_claims(), token_header) headers = { 'Authorization': f'Bearer {token}', 'content-type': 'application/json' } rv = client.post(f'/api/v1/payment-requests', data=json.dumps(get_payment_request()), headers=headers) payment: Payment = Payment.find_by_id(rv.json.get('id')) credit_account: CreditPaymentAccount = CreditPaymentAccount.find_by_id(payment.invoices[0].credit_account_id) pay_account: PaymentAccount = PaymentAccount.find_by_id(credit_account.account_id) headers = { 'Authorization': f'Bearer {token}', 'content-type': 'application/json', 'Accept': 'application/pdf' } rv = client.post(f'/api/v1/accounts/{pay_account.auth_account_id}/payments/reports', data=json.dumps({}), headers=headers) assert rv.status_code == 201 def test_account_purchase_history_export_invalid_request(session, client, jwt, app): """Assert that the endpoint returns 200.""" token = jwt.create_jwt(get_claims(), token_header) headers = { 'Authorization': f'Bearer {token}', 'content-type': 'application/json' } rv = client.post(f'/api/v1/payment-requests', data=json.dumps(get_payment_request()), headers=headers) payment: Payment = Payment.find_by_id(rv.json.get('id')) credit_account: CreditPaymentAccount = CreditPaymentAccount.find_by_id(payment.invoices[0].credit_account_id) pay_account: PaymentAccount = PaymentAccount.find_by_id(credit_account.account_id) headers = { 'Authorization': f'Bearer {token}', 'content-type': 'application/json', 'Accept': 'application/pdf' } rv = client.post(f'/api/v1/accounts/{pay_account.auth_account_id}/payments/reports', data=json.dumps({ 'businessIdentifier': 1111 }), headers=headers) assert rv.status_code == 400

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6

1bdef0e5df0c225eb2775cb6ea55f9021c9fb5fa

576

py

Python

sdk/python/pulumi_aws/s3/__init__.py

texdc/pulumi-aws

93a7a28ab7db6b1cd7e6686c0b68aa4c89490d4f

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_aws/s3/__init__.py

texdc/pulumi-aws

93a7a28ab7db6b1cd7e6686c0b68aa4c89490d4f

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_aws/s3/__init__.py

texdc/pulumi-aws

93a7a28ab7db6b1cd7e6686c0b68aa4c89490d4f

[ "ECL-2.0", "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** # Export this package's modules as members: from .account_public_access_block import * from .bucket import * from .inventory import * from .bucket_metric import * from .bucket_notification import * from .bucket_object import * from .bucket_policy import * from .bucket_public_access_block import * from .get_bucket import * from .get_bucket_object import * from .get_bucket_objects import *

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0

1

0

6

402e44e902fa8cead89eae17a87c8aa8f9902299

21,328

py

Python

src/genie/libs/parser/iosxe/tests/test_show_mld.py

nujo/genieparser

083b01efc46afc32abe1a1858729578beab50cd3

[ "Apache-2.0" ]

2

2021-01-27T03:37:39.000Z

2021-01-27T03:40:50.000Z

src/genie/libs/parser/iosxe/tests/test_show_mld.py

nujo/genieparser

083b01efc46afc32abe1a1858729578beab50cd3

[ "Apache-2.0" ]

1

2020-08-01T00:23:31.000Z

2020-08-01T00:40:05.000Z

src/genie/libs/parser/iosxe/tests/test_show_mld.py

nujo/genieparser

083b01efc46afc32abe1a1858729578beab50cd3

[ "Apache-2.0" ]

null

# Python import unittest from unittest.mock import Mock # ATS from pyats.topology import Device # Metaparset from genie.metaparser.util.exceptions import SchemaEmptyParserError, \ SchemaMissingKeyError # Parser from genie.libs.parser.iosxe.show_mld import ShowIpv6MldInterface, \ ShowIpv6MldGroupsDetail, \ ShowIpv6MldSsmMap # ================================================== # Unit test for 'show ipv6 mld interface' # Unit test for 'show ipv6 mld vrf <WORD> interface' # ================================================== class test_show_ipv6_mld_interface(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = { "vrf": { "default": { "interface": { "Tunnel0": { "oper_status": "up", "interface_adress": "FE80::21E:BDFF:FEBA:D000/10", "enable": False, "interface_status": "up" }, "VoIP-Null0": { "oper_status": "up", "interface_adress": "::/0", "enable": False, "interface_status": "up" }, "LIIN0": { "oper_status": "up", "interface_adress": "::/0", "enable": False, "interface_status": "up" }, "GigabitEthernet1": { "oper_status": "up", "querier_timeout": 740, "active_groups": 0, "group_policy": "test", "query_interval": 366, "version": 2, "query_this_system": True, "querier": "FE80::5054:FF:FE7C:DC70", "interface_status": "up", "last_member_query_interval": 1, "counters": { "leaves": 2, "joins": 11 }, "max_groups": 6400, "query_max_response_time": 16, "enable": True, "interface_adress": "FE80::5054:FF:FE7C:DC70/10" }, "GigabitEthernet3": { "oper_status": "down", "interface_adress": "::/0", "enable": False, "interface_status": "administratively down" }, "Null0": { "oper_status": "up", "interface_adress": "FE80::1/10", "enable": False, "interface_status": "up" } }, "max_groups": 64000, "active_groups": 0 } } } golden_output = {'execute.return_value': '''\ Global State Limit : 0 active out of 64000 max GigabitEthernet1 is up, line protocol is up Internet address is FE80::5054:FF:FE7C:DC70/10 MLD is enabled on interface Current MLD version is 2 MLD query interval is 366 seconds MLD querier timeout is 740 seconds MLD max query response time is 16 seconds Last member query response interval is 1 seconds Inbound MLD access group is: test Interface State Limit : 0 active out of 6400 max MLD activity: 11 joins, 2 leaves MLD querying router is FE80::5054:FF:FE7C:DC70 (this system) GigabitEthernet3 is administratively down, line protocol is down Internet address is ::/0 MLD is disabled on interface Null0 is up, line protocol is up Internet address is FE80::1/10 MLD is disabled on interface VoIP-Null0 is up, line protocol is up Internet address is ::/0 MLD is disabled on interface LIIN0 is up, line protocol is up Internet address is ::/0 MLD is disabled on interface Tunnel0 is up, line protocol is up Internet address is FE80::21E:BDFF:FEBA:D000/10 MLD is disabled on interface '''} golden_parsed_output_1 = { "vrf": { "VRF1": { "interface": { "GigabitEthernet2": { "query_max_response_time": 16, "enable": True, "query_interval": 366, "querier": "FE80::5054:FF:FEDD:BB49", "interface_status": "up", "query_this_system": True, "version": 2, "interface_adress": "FE80::5054:FF:FEDD:BB49/10", "active_groups": 0, "querier_timeout": 740, "last_member_query_interval": 1, "counters": { "joins": 9, "leaves": 0 }, "oper_status": "up", "max_groups": 6400 }, "Tunnel1": { "interface_status": "up", "interface_adress": "FE80::21E:BDFF:FEBA:D000/10", "oper_status": "up", "enable": False } }, "max_groups": 64000, "active_groups": 0 } } } golden_output_1 = {'execute.return_value': '''\ Global State Limit : 0 active out of 64000 max GigabitEthernet2 is up, line protocol is up Internet address is FE80::5054:FF:FEDD:BB49/10 MLD is enabled on interface Current MLD version is 2 MLD query interval is 366 seconds MLD querier timeout is 740 seconds MLD max query response time is 16 seconds Last member query response interval is 1 seconds Interface State Limit : 0 active out of 6400 max MLD activity: 9 joins, 0 leaves MLD querying router is FE80::5054:FF:FEDD:BB49 (this system) Tunnel1 is up, line protocol is up Internet address is FE80::21E:BDFF:FEBA:D000/10 MLD is disabled on interface '''} def test_empty(self): self.device = Mock(**self.empty_output) obj = ShowIpv6MldInterface(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse() def test_golden_default_vrf(self): self.device = Mock(**self.golden_output) obj = ShowIpv6MldInterface(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output,self.golden_parsed_output) def test_golden_non_default_vrf(self): self.device = Mock(**self.golden_output_1) obj = ShowIpv6MldInterface(device=self.device) parsed_output = obj.parse(vrf='VRF1') self.assertEqual(parsed_output,self.golden_parsed_output_1) # ===================================================== # Unit test for 'show ipv6 mld groups detail' # Unit test for 'show ipv6 mld vrf <WORD> groups detail' # ===================================================== class test_show_ipv6_mld_groups_detail(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = { "vrf": { "default": { "interface": { "GigabitEthernet1": { "group": { "FF15:1::1": { "up_time": "08:14:15", "source": { "2001:DB8:2:2::2": { "forward": True, "up_time": "08:13:22", "flags": "Remote Local 2D", "expire": "00:06:42" } }, "filter_mode": "include", "host_mode": "include", "last_reporter": "FE80::5054:FF:FE7C:DC70" }, "FF25:2::1": { "up_time": "08:14:01", "filter_mode": "exclude", "last_reporter": "FE80::5054:FF:FE7C:DC70", "host_mode": "exclude", "expire": "never" }, "FF35:1::1": { "up_time": "00:42:41", "source": { "2001:DB8:3:3::3": { "forward": True, "up_time": "00:42:41", "flags": "Remote Local E", "expire": "00:06:42" } }, "filter_mode": "include", "host_mode": "include", "last_reporter": "FE80::5054:FF:FE7C:DC70" }, "FF45:1::1": { "up_time": "00:42:32", "filter_mode": "exclude", "last_reporter": "FE80::5054:FF:FE7C:DC70", "host_mode": "exclude", "expire": "never" } }, "join_group": { "FF15:1::1 2001:DB8:2:2::2": { "group": "FF15:1::1", "source": "2001:DB8:2:2::2" }, }, "static_group": { "FF35:1::1 2001:DB8:3:3::3": { "group": "FF35:1::1", "source": "2001:DB8:3:3::3" } } } } } } } golden_output = {'execute.return_value': '''\ Interface: GigabitEthernet1 Group: FF15:1::1 Uptime: 08:14:15 Router mode: INCLUDE Host mode: INCLUDE Last reporter: FE80::5054:FF:FE7C:DC70 Group source list: Source Address Uptime Expires Fwd Flags 2001:DB8:2:2::2 08:13:22 00:06:42 Yes Remote Local 2D Interface: GigabitEthernet1 Group: FF25:2::1 Uptime: 08:14:01 Router mode: EXCLUDE (Expires: never) Host mode: EXCLUDE Last reporter: FE80::5054:FF:FE7C:DC70 Source list is empty Interface: GigabitEthernet1 Group: FF35:1::1 Uptime: 00:42:41 Router mode: INCLUDE Host mode: INCLUDE Last reporter: FE80::5054:FF:FE7C:DC70 Group source list: Source Address Uptime Expires Fwd Flags 2001:DB8:3:3::3 00:42:41 00:06:42 Yes Remote Local E Interface: GigabitEthernet1 Group: FF45:1::1 Uptime: 00:42:32 Router mode: EXCLUDE (Expires: never) Host mode: EXCLUDE Last reporter: FE80::5054:FF:FE7C:DC70 Source list is empty '''} golden_parsed_output_1 = { "vrf": { "VRF1": { "interface": { "GigabitEthernet2": { "group": { "FF15:1::1": { "up_time": "08:14:20", "source": { "2001:DB8:2:2::2": { "forward": True, "up_time": "08:13:56", "flags": "Remote Local 2D", "expire": "00:12:23" } }, "filter_mode": "include", "host_mode": "include", "last_reporter": "FE80::5054:FF:FEDD:BB49" }, "FF25:2::1": { "up_time": "08:14:18", "filter_mode": "exclude", "last_reporter": "FE80::5054:FF:FEDD:BB49", "host_mode": "exclude", "expire": "never" }, "FF35:1::1": { "up_time": "00:42:30", "source": { "2001:DB8:3:3::3": { "forward": True, "up_time": "00:42:30", "flags": "Remote Local E", "expire": "00:12:23" } }, "filter_mode": "include", "host_mode": "include", "last_reporter": "FE80::5054:FF:FEDD:BB49" }, "FF45:1::1": { "up_time": "00:42:30", "filter_mode": "exclude", "last_reporter": "FE80::5054:FF:FEDD:BB49", "host_mode": "exclude", "expire": "never" } }, "join_group": { "FF15:1::1 2001:DB8:2:2::2": { "group": "FF15:1::1", "source": "2001:DB8:2:2::2" } }, "static_group": { "FF35:1::1 2001:DB8:3:3::3": { "group": "FF35:1::1", "source": "2001:DB8:3:3::3" } } } } } } } golden_output_1 = {'execute.return_value': '''\ Interface: GigabitEthernet2 Group: FF15:1::1 Uptime: 08:14:20 Router mode: INCLUDE Host mode: INCLUDE Last reporter: FE80::5054:FF:FEDD:BB49 Group source list: Source Address Uptime Expires Fwd Flags 2001:DB8:2:2::2 08:13:56 00:12:23 Yes Remote Local 2D Interface: GigabitEthernet2 Group: FF25:2::1 Uptime: 08:14:18 Router mode: EXCLUDE (Expires: never) Host mode: EXCLUDE Last reporter: FE80::5054:FF:FEDD:BB49 Source list is empty Interface: GigabitEthernet2 Group: FF35:1::1 Uptime: 00:42:30 Router mode: INCLUDE Host mode: INCLUDE Last reporter: FE80::5054:FF:FEDD:BB49 Group source list: Source Address Uptime Expires Fwd Flags 2001:DB8:3:3::3 00:42:30 00:12:23 Yes Remote Local E Interface: GigabitEthernet2 Group: FF45:1::1 Uptime: 00:42:30 Router mode: EXCLUDE (Expires: never) Host mode: EXCLUDE Last reporter: FE80::5054:FF:FEDD:BB49 Source list is empty '''} def test_empty(self): self.device = Mock(**self.empty_output) obj = ShowIpv6MldGroupsDetail(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse() def test_golden_default_vrf(self): self.device = Mock(**self.golden_output) obj = ShowIpv6MldGroupsDetail(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output,self.golden_parsed_output) def test_golden_non_default_vrf(self): self.device = Mock(**self.golden_output_1) obj = ShowIpv6MldGroupsDetail(device=self.device) parsed_output = obj.parse(vrf='VRF1') self.assertEqual(parsed_output,self.golden_parsed_output_1) # =========================================================== # Unit test for 'show ipv6 mld ssm-mapping <WROD>' # Unit test for 'show ipv6 mld vrf <WORD> ssm-mapping <WORD>' # ============================================================ class test_show_ipv6_mld_ssm_mapping(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = { "vrf": { "default": { "ssm_map": { "2001:DB8:1:1::1 FF35:1::1": { "source_addr": "2001:DB8:1:1::1", "group_address": "FF35:1::1", "database": "static", "group_mode_ssm": False } } } } } golden_output = {'execute.return_value': '''\ Group address : FF35:1::1 Group mode ssm : FALSE Database : STATIC Source list : 2001:DB8:1:1::1 '''} golden_parsed_output_1 = { "vrf": { "VRF1": { "ssm_map": { "2001:DB8:1:1::1 FF35:1::1": { "source_addr": "2001:DB8:1:1::1", "group_address": "FF35:1::1", "database": "static", "group_mode_ssm": False }, "2001:DB8::3 FF35:1::1": { "source_addr": "2001:DB8::3", "group_address": "FF35:1::1", "database": "static", "group_mode_ssm": False } } } } } golden_output_1 = {'execute.return_value': '''\ Group address : FF35:1::1 Group mode ssm : FALSE Database : STATIC Source list : 2001:DB8:1:1::1 2001:DB8::3 '''} def test_empty(self): self.device = Mock(**self.empty_output) obj = ShowIpv6MldSsmMap(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse(group='ff35:1::1') def test_golden_default_vrf(self): self.device = Mock(**self.golden_output) obj = ShowIpv6MldSsmMap(device=self.device) parsed_output = obj.parse(group='ff35:1::1') self.assertEqual(parsed_output,self.golden_parsed_output) def test_golden_non_default_vrf(self): self.device = Mock(**self.golden_output_1) obj = ShowIpv6MldSsmMap(device=self.device) parsed_output = obj.parse(vrf='VRF1', group='ff35:1::1') self.assertEqual(parsed_output,self.golden_parsed_output_1) if __name__ == '__main__': unittest.main()

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88

0.386534

1,759

21,328

4.554861

0.105173

0.010734

0.029955

0.03994

0.866076

0.833375

0.757239

0.714678

0.662506

0.632302

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0.504126

21,328

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42.40159

0.667455

0.030851

0

0.699779

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0.00883

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0.019868

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null

0

1

0

1

0

1

0

null

0

6

4034928e25b018ee24acfa6ff967519b3bcf52ce

3,045

py

Python

test/test_conditionals.py

jackdavidweber/cjs_capstone

8929e4939f5b7b172c595dbb49b1d2ccc7805b8a

[ "MIT" ]

2

2020-07-13T18:58:57.000Z

2020-07-20T23:30:21.000Z

test/test_conditionals.py

jackdavidweber/cjs_capstone

8929e4939f5b7b172c595dbb49b1d2ccc7805b8a

[ "MIT" ]

20

2020-06-18T20:49:20.000Z

2020-08-04T16:15:46.000Z

test/test_conditionals.py

jackdavidweber/cjs_capstone

8929e4939f5b7b172c595dbb49b1d2ccc7805b8a

[ "MIT" ]

null

import unittest2 import matrix from Unittest import Unittest class TestConditionals(unittest2.TestCase): def test_if(self): js_code = Unittest('if (1) {\n\tconsole.log("This is true")\n}', 'js') py_code = Unittest('if (1):\n\tprint("This is true")', 'py') bash_code = Unittest('if [[ 1 ]]; then\n\techo "This is true"\nfi', 'bash', is_input=False) java_code = Unittest( 'if (1) {\n\tSystem.out.println("This is true");\n}', 'java') matrix.matrix(self, [py_code, js_code, java_code, bash_code]) def test_else(self): js_code = Unittest( 'if (1) {\n\tconsole.log("1 is true")\n} else {\n\tconsole.log("1 is NOT true")\n}', 'js') py_code = Unittest( 'if (1):\n\tprint("1 is true")\nelse:\n\tprint("1 is NOT true")', 'py') bash_code = Unittest( 'if [[ 1 ]]; then\n\techo "1 is true"\nelse\n\techo "1 is NOT true"\nfi', 'bash', is_input=False) java_code = Unittest( 'if (1) {\n\tSystem.out.println("1 is true");\n} else {\n\tSystem.out.println("1 is NOT true");\n}', 'java') matrix.matrix(self, [py_code, js_code, java_code, bash_code]) def test_elif(self): js_code = Unittest( 'if (1) {\n\tconsole.log("1 is true")\n} else if (2) {\n\tconsole.log("2 is true")\n\tconsole.log("second line")\n}', 'js') py_code = Unittest( 'if (1):\n\tprint("1 is true")\nelif (2):\n\tprint("2 is true")\n\tprint("second line")', 'py') bash_code = Unittest( 'if [[ 1 ]]; then\n\techo "1 is true"\nelif [[ 2 ]]; then\n\techo "2 is true"\n\techo "second line"\nfi', 'bash', is_input=False) java_code = Unittest( 'if (1) {\n\tSystem.out.println("1 is true");\n} else if (2) {\n\tSystem.out.println("2 is true");\n\tSystem.out.println("second line");\n}', 'java') matrix.matrix(self, [py_code, js_code, java_code, bash_code]) def test_elif_else(self): js_code = Unittest( 'if (1) {\n\tconsole.log("1 is true")\n} else if (2) {\n\tconsole.log("2 is true")\n} else {\n\tconsole.log("nothing is true")\n}', 'js') py_code = Unittest( 'if (1):\n\tprint("1 is true")\nelif (2):\n\tprint("2 is true")\nelse:\n\tprint("nothing is true")', 'py') bash_code = Unittest( 'if [[ 1 ]]; then\n\techo "1 is true"\nelif [[ 2 ]]; then\n\techo "2 is true"\nelse\n\techo "nothing is true"\nfi', 'bash', is_input=False) java_code = Unittest( 'if (1) {\n\tSystem.out.println("1 is true");\n} else if (2) {\n\tSystem.out.println("2 is true");\n} else {\n\tSystem.out.println("nothing is true");\n}', 'java') matrix.matrix(self, [py_code, js_code, java_code, bash_code]) if __name__ == '__main__': unittest2.main()

44.130435

167

0.533333

447

3,045

3.52349

0.098434

0.106667

0.142222

0.152381

0.834921

0.8

0.798095

0.780317

0.754921

0.733968

0

0.023309

0.281445

3,045

68

168

44.779412

0.696527

0

0.566667

0

0.2

0.480131

0.134319

0

1

0.066667

false

0

0.05

0

0.133333

0

null

0

1

0

null

0

6

404e5830e4578ca4f6e6632a4880c94c2c42ba62

85

py

Python

spikeextractors/extractors/kilosortextractors/__init__.py

zekearneodo/spikeextractors

d30aa85e69d0331fffdb58a03a2bb628f93b405e

[ "MIT" ]

145

2018-12-06T23:12:54.000Z

2022-02-10T22:57:35.000Z

spikeextractors/extractors/kilosortextractors/__init__.py

zekearneodo/spikeextractors

d30aa85e69d0331fffdb58a03a2bb628f93b405e

[ "MIT" ]

396

2018-11-26T11:46:30.000Z

2022-01-04T07:27:47.000Z

spikeextractors/extractors/kilosortextractors/__init__.py

zekearneodo/spikeextractors

d30aa85e69d0331fffdb58a03a2bb628f93b405e

[ "MIT" ]

67

2018-11-19T12:38:01.000Z

2021-09-25T03:18:22.000Z

from .kilosortextractors import KiloSortSortingExtractor, KiloSortRecordingExtractor

42.5

84

0.917647

5

85

15.6

1

0

0.058824

85

1

85

0.975

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

null

0

1

0

1

0

1

0

6

4087c7c36a8169662cbe27cfbc842c59b72bc32f

50,379

py

Python

spiketoolkit/validation/quality_metrics.py

Shawn-Guo-CN/spiketoolkit

11e60f3cd80c135c62e27538a4e141115a7e27ad

[ "MIT" ]

null

spiketoolkit/validation/quality_metrics.py

Shawn-Guo-CN/spiketoolkit

11e60f3cd80c135c62e27538a4e141115a7e27ad

[ "MIT" ]

null

spiketoolkit/validation/quality_metrics.py

Shawn-Guo-CN/spiketoolkit

11e60f3cd80c135c62e27538a4e141115a7e27ad

[ "MIT" ]

null

import spiketoolkit as st def compute_num_spikes(sorting, sampling_frequency=None, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True): ''' Computes and returns the spike times in seconds and also returns the cluster_ids needed for quality metrics. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. sampling_frequency: The sampling frequency of the result. If None, will check to see if sampling frequency is in sorting extractor unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch epoch_names: list A list of strings for the names of the given epochs save_as_property: bool If True, the metric is saved as sorting property Returns ---------- num_spikes_epochs: list The spike counts of the sorted units in the given epochs. ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=sampling_frequency, unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) num_spikes_epochs = metric_calculator.compute_num_spikes() if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'num_spikes', num_spikes_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return num_spikes_epochs def compute_firing_rates(sorting, sampling_frequency=None, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True): ''' Computes and returns the spike times in seconds and also returns the cluster_ids needed for quality metrics. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. sampling_frequency: The sampling frequency of the result. If None, will check to see if sampling frequency is in sorting extractor unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch epoch_names: list A list of strings for the names of the given epochs save_as_property: bool If True, the metric is saved as sorting property Returns ---------- firing_rates_epochs: list The firing rates of the sorted units in the given epochs. ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=sampling_frequency, unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) firings_rates_epochs = metric_calculator.compute_firing_rates() if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'firing_rate', firings_rates_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return firings_rates_epochs def compute_presence_ratios(sorting, sampling_frequency=None, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True): ''' Computes and returns the presence ratios. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. sampling_frequency: The sampling frequency of the result. If None, will check to see if sampling frequency is in sorting extractor unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch epoch_names: list A list of strings for the names of the given epochs save_as_property: bool If True, the metric is saved as sorting property Returns ---------- presence_ratios_epochs: list The presence ratios violations of the sorted units in the given epochs. ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=sampling_frequency, unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) presence_ratios_epochs = metric_calculator.compute_presence_ratios() if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'presence_ratio', presence_ratios_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return presence_ratios_epochs def compute_isi_violations(sorting, sampling_frequency=None, isi_threshold=0.0015, min_isi=0.000166, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True): ''' Computes and returns the ISI violations for the given parameters. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. sampling_frequency: The sampling frequency of the result. If None, will check to see if sampling frequency is in sorting extractor isi_threshold: float The isi threshold for calculating isi violations min_isi: float The minimum expected isi value unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch epoch_names: list A list of strings for the names of the given epochs save_as_property: bool If True, the metric is saved as sorting property Returns ---------- isi_violations_epochs: list The isi violations of the sorted units in the given epochs. ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=sampling_frequency, unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) isi_violations_epochs = metric_calculator.compute_isi_violations(isi_threshold=isi_threshold, min_isi=min_isi) if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'isi_violation', isi_violations_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return isi_violations_epochs def compute_amplitude_cutoffs(sorting, recording, amp_method='absolute', amp_peak='both', amp_frames_before=3, amp_frames_after=3, apply_filter=True, freq_min=300, freq_max=6000, save_features_props=False, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True, seed=0): ''' Computes and returns the amplitude cutoffs for the sorted dataset. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. recording: RecordingExtractor The given recording extractor from which to extract amplitudes amp_method: str If 'absolute' (default), amplitudes are absolute amplitudes in uV are returned. If 'relative', amplitudes are returned as ratios between waveform amplitudes and template amplitudes. amp_peak: str If maximum channel has to be found among negative peaks ('neg'), positive ('pos') or both ('both' - default) amp_frames_before: int Frames before peak to compute amplitude. amp_frames_after: int Frames after peak to compute amplitude. apply_filter: bool If True, recording is bandpass-filtered. freq_min: float High-pass frequency for optional filter (default 300 Hz). freq_max: float Low-pass frequency for optional filter (default 6000 Hz). save_features_props: bool If true, it will save amplitudes in the sorting extractor. unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch epoch_names: list A list of strings for the names of the given epochs. seed: int Random seed for reproducibility save_as_property: bool If True, the metric is saved as sorting property Returns ---------- amplitude_cutoffs_epochs: list The amplitude cutoffs of the sorted units in the given epochs. ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=recording.get_sampling_frequency(), unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) metric_calculator.compute_amplitudes(recording=recording, amp_method=amp_method, amp_peak=amp_peak, amp_frames_before=amp_frames_before, amp_frames_after=amp_frames_after, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max, save_features_props=save_features_props, seed=seed) amplitude_cutoffs_epochs = metric_calculator.compute_amplitude_cutoffs() if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'amplitude_cutoff', amplitude_cutoffs_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return amplitude_cutoffs_epochs def compute_snrs(sorting, recording, snr_mode='mad', snr_noise_duration=10.0, max_spikes_per_unit_for_snr=1000, recompute_info=True, apply_filter=True, freq_min=300, freq_max=6000, save_features_props=False, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True, seed=0): ''' Computes and stores snrs for the sorted units. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. recording: RecordingExtractor The given recording extractor from which to extract amplitudes. snr_mode: str Mode to compute noise SNR ('mad' | 'std' - default 'mad') snr_noise_duration: float Number of seconds to compute noise level from (default 10.0) max_spikes_per_unit_for_snr: int Maximum number of spikes to compute templates from (default 1000) unit_ids: list List of unit ids to compute metric for. If not specified, all units are used recompute_info: bool If True, waveforms are recomputed apply_filter: bool If True, recording is bandpass-filtered. freq_min: float High-pass frequency for optional filter (default 300 Hz). freq_max: float Low-pass frequency for optional filter (default 6000 Hz). save_features_props: bool If True, waveforms and templates are saved as properties and features of the sorting extractor epoch_tuples: list A list of tuples with a start and end time for each epoch. epoch_names: list A list of strings for the names of the given epochs. save_as_property: bool If True, the metric is saved as sorting property seed: int Random seed for reproducibility. Returns ---------- snrs_epochs: list The snrs of the sorted units in the given epochs. ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=recording.get_sampling_frequency(), unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) metric_calculator.set_recording(recording, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max) snrs_epochs = metric_calculator.compute_snrs(snr_mode=snr_mode, snr_noise_duration=snr_noise_duration, max_spikes_per_unit_for_snr=max_spikes_per_unit_for_snr, recompute_info=recompute_info, save_features_props=save_features_props, seed=seed) if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'snr', snrs_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return snrs_epochs def compute_drift_metrics(sorting, recording, drift_metrics_interval_s=51, drift_metrics_min_spikes_per_interval=10, n_comp=3, ms_before=1., ms_after=2., dtype=None, max_spikes_per_unit=300, recompute_info=True, max_spikes_for_pca=1e5, apply_filter=True, freq_min=300, freq_max=6000, save_features_props=False, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True, seed=0): ''' Computes and returns the drift metrics for the sorted dataset. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. recording: RecordingExtractor The given recording extractor from which to extract amplitudes. drift_metrics_interval_s: float Time period for evaluating drift. drift_metrics_min_spikes_per_interval: int Minimum number of spikes for evaluating drift metrics per interval. n_comp: int n_compFeatures in template-gui format ms_before: float Time period in ms to cut waveforms before the spike events ms_after: float Time period in ms to cut waveforms after the spike events dtype: dtype The numpy dtype of the waveforms max_spikes_per_unit: int The maximum number of spikes to extract (default is np.inf) recompute_info: bool If True, will always re-extract waveforms. max_spikes_for_pca: int The maximum number of spikes to use to compute PCA (default is np.inf) apply_filter: bool If True, recording is bandpass-filtered. freq_min: float High-pass frequency for optional filter (default 300 Hz). freq_max: float Low-pass frequency for optional filter (default 6000 Hz). save_features_props: bool If True, save all features and properties in the sorting extractor. unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch. epoch_names: list A list of strings for the names of the given epochs. save_as_property: bool If True, the metric is saved as sorting property seed: int Random seed for reproducibility Returns ---------- max_drifts_epochs: list The max drift of the given units over the specified epochs cumulative_drifts_epochs: list The cumulative drifts of the given units over the specified epochs ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=recording.get_sampling_frequency(), unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) metric_calculator.compute_pca_scores(recording=recording, n_comp=n_comp, ms_before=ms_before, ms_after=ms_after, dtype=dtype, max_spikes_per_unit=max_spikes_per_unit, recompute_info=recompute_info, max_spikes_for_pca=max_spikes_for_pca, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max, save_features_props=save_features_props, seed=seed) max_drifts_epochs, cumulative_drifts_epochs = metric_calculator.compute_drift_metrics( drift_metrics_interval_s=drift_metrics_interval_s, drift_metrics_min_spikes_per_interval=drift_metrics_min_spikes_per_interval) if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'max_drift', max_drifts_epochs[i_u]) sorting.set_unit_property(u, 'cumulative_drift', cumulative_drifts_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return max_drifts_epochs, cumulative_drifts_epochs def compute_silhouette_scores(sorting, recording, max_spikes_for_silhouette=10000, n_comp=3, ms_before=1., ms_after=2., dtype=None, max_spikes_per_unit=300, recompute_info=True, max_spikes_for_pca=1e5, apply_filter=True, freq_min=300, freq_max=6000, save_features_props=False, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True, seed=0): ''' Computes and returns the silhouette scores in the sorted dataset. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. recording: RecordingExtractor The given recording extractor from which to extract amplitudes. max_spikes_for_silhouette: int Max spikes to be used for silhouette metric n_comp: int n_compFeatures in template-gui format ms_before: float Time period in ms to cut waveforms before the spike events ms_after: float Time period in ms to cut waveforms after the spike events dtype: dtype The numpy dtype of the waveforms max_spikes_per_unit: int The maximum number of spikes to extract (default is np.inf) recompute_info: bool If True, will always re-extract waveforms. max_spikes_for_pca: int The maximum number of spikes to use to compute PCA (default is np.inf) apply_filter: bool If True, recording is bandpass-filtered. freq_min: float High-pass frequency for optional filter (default 300 Hz). freq_max: float Low-pass frequency for optional filter (default 6000 Hz). save_features_props: bool If True, save all features and properties in the sorting extractor. unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch. epoch_names: list A list of strings for the names of the given epochs. save_as_property: bool If True, the metric is saved as sorting property seed: int Random seed for reproducibility Returns ---------- silhouette_scores_epochs: list The silhouette scores of the given units for the specified epochs. ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=recording.get_sampling_frequency(), unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) metric_calculator.compute_pca_scores(recording=recording, n_comp=n_comp, ms_before=ms_before, ms_after=ms_after, dtype=dtype, max_spikes_per_unit=max_spikes_per_unit, recompute_info=recompute_info, max_spikes_for_pca=max_spikes_for_pca, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max, save_features_props=save_features_props, seed=seed) silhouette_scores_epochs = metric_calculator.compute_silhouette_scores( max_spikes_for_silhouette=max_spikes_for_silhouette, seed=seed) if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'silhouette_score', silhouette_scores_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return silhouette_scores_epochs def compute_isolation_distances(sorting, recording, num_channels_to_compare=13, max_spikes_per_cluster=500, n_comp=3, ms_before=1., ms_after=2., dtype=None, max_spikes_per_unit=300, recompute_info=True, max_spikes_for_pca=1e5, apply_filter=True, freq_min=300, freq_max=6000, save_features_props=False, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True, seed=0): ''' Computes and returns the mahalanobis metric, isolation distance, for the sorted dataset. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. recording: RecordingExtractor The given recording extractor from which to extract amplitudes. num_channels_to_compare: int The number of channels to be used for the PC extraction and comparison max_spikes_per_cluster: int Max spikes to be used from each unit n_comp: int n_compFeatures in template-gui format ms_before: float Time period in ms to cut waveforms before the spike events ms_after: float Time period in ms to cut waveforms after the spike events dtype: dtype The numpy dtype of the waveforms max_spikes_per_unit: int The maximum number of spikes to extract (default is np.inf) recompute_info: bool If True, will always re-extract waveforms. max_spikes_for_pca: int The maximum number of spikes to use to compute PCA (default is np.inf) apply_filter: bool If True, recording is bandpass-filtered. freq_min: float High-pass frequency for optional filter (default 300 Hz). freq_max: float Low-pass frequency for optional filter (default 6000 Hz). save_features_props: bool If True, save all features and properties in the sorting extractor. unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch. epoch_names: list A list of strings for the names of the given epochs. save_as_property: bool If True, the metric is saved as sorting property seed: int Random seed for reproducibility Returns ---------- isolation_distances_epochs: list Returns the isolation distances of each specified unit for the given epochs. ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=recording.get_sampling_frequency(), unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) metric_calculator.compute_pca_scores(recording=recording, n_comp=n_comp, ms_before=ms_before, ms_after=ms_after, dtype=dtype, max_spikes_per_unit=max_spikes_per_unit, recompute_info=recompute_info, max_spikes_for_pca=max_spikes_for_pca, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max, save_features_props=save_features_props, seed=seed) isolation_distances_epochs = metric_calculator.compute_isolation_distances( num_channels_to_compare=num_channels_to_compare, max_spikes_per_cluster=max_spikes_per_cluster, seed=seed) if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'isolation_distance', isolation_distances_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return isolation_distances_epochs def compute_l_ratios(sorting, recording, num_channels_to_compare=13, max_spikes_per_cluster=500, n_comp=3, ms_before=1., ms_after=2., dtype=None, max_spikes_per_unit=300, recompute_info=True, max_spikes_for_pca=1e5, apply_filter=True, freq_min=300, freq_max=6000, save_features_props=False, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True, seed=0): ''' Computes and returns the mahalanobis metric, l-ratio, for the sorted dataset. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. recording: RecordingExtractor The given recording extractor from which to extract amplitudes. num_channels_to_compare: int The number of channels to be used for the PC extraction and comparison max_spikes_per_cluster: int Max spikes to be used from each unit n_comp: int n_compFeatures in template-gui format ms_before: float Time period in ms to cut waveforms before the spike events ms_after: float Time period in ms to cut waveforms after the spike events dtype: dtype The numpy dtype of the waveforms max_spikes_per_unit: int The maximum number of spikes to extract (default is np.inf) recompute_info: bool If True, will always re-extract waveforms. max_spikes_for_pca: int The maximum number of spikes to use to compute PCA (default is np.inf) apply_filter: bool If True, recording is bandpass-filtered. freq_min: float High-pass frequency for optional filter (default 300 Hz). freq_max: float Low-pass frequency for optional filter (default 6000 Hz). save_features_props: bool If True, save all features and properties in the sorting extractor. unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch. epoch_names: list A list of strings for the names of the given epochs. save_as_property: bool If True, the metric is saved as sorting property seed: int Random seed for reproducibility Returns ---------- l_ratios_epochs: list Returns the L ratios of each specified unit for the given epochs ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=recording.get_sampling_frequency(), unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) metric_calculator.compute_pca_scores(recording=recording, n_comp=n_comp, ms_before=ms_before, ms_after=ms_after, dtype=dtype, max_spikes_per_unit=max_spikes_per_unit, recompute_info=recompute_info, max_spikes_for_pca=max_spikes_for_pca, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max, save_features_props=save_features_props, seed=seed) l_ratios_epochs = metric_calculator.compute_l_ratios(num_channels_to_compare=num_channels_to_compare, max_spikes_per_cluster=max_spikes_per_cluster, seed=seed) if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'l_ratio', l_ratios_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return l_ratios_epochs def compute_d_primes(sorting, recording, num_channels_to_compare=13, max_spikes_per_cluster=500, n_comp=3, ms_before=1., ms_after=2., dtype=None, max_spikes_per_unit=300, recompute_info=True, max_spikes_for_pca=1e5, apply_filter=True, freq_min=300, freq_max=6000, save_features_props=False, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True, seed=0): ''' Computes and returns the lda-based metric, d-prime, for the sorted dataset. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. recording: RecordingExtractor The given recording extractor from which to extract amplitudes. num_channels_to_compare: int The number of channels to be used for the PC extraction and comparison max_spikes_per_cluster: int Max spikes to be used from each unit n_comp: int n_compFeatures in template-gui format ms_before: float Time period in ms to cut waveforms before the spike events ms_after: float Time period in ms to cut waveforms after the spike events dtype: dtype The numpy dtype of the waveforms max_spikes_per_unit: int The maximum number of spikes to extract (default is np.inf) recompute_info: bool If True, will always re-extract waveforms. max_spikes_for_pca: int The maximum number of spikes to use to compute PCA (default is np.inf) apply_filter: bool If True, recording is bandpass-filtered. freq_min: float High-pass frequency for optional filter (default 300 Hz). freq_max: float Low-pass frequency for optional filter (default 6000 Hz). save_features_props: bool If True, save all features and properties in the sorting extractor. unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch. epoch_names: list A list of strings for the names of the given epochs. save_as_property: bool If True, the metric is saved as sorting property seed: int Random seed for reproducibility Returns ---------- d_primes_epochs: list Returns the d primes of each specified unit for the given epochs. ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=recording.get_sampling_frequency(), unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) metric_calculator.compute_pca_scores(recording=recording, n_comp=n_comp, ms_before=ms_before, ms_after=ms_after, dtype=dtype, max_spikes_per_unit=max_spikes_per_unit, recompute_info=recompute_info, max_spikes_for_pca=max_spikes_for_pca, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max, save_features_props=save_features_props, seed=seed) d_primes_epochs = metric_calculator.compute_d_primes(num_channels_to_compare=num_channels_to_compare, max_spikes_per_cluster=max_spikes_per_cluster, seed=seed) if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'd_prime', d_primes_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return d_primes_epochs def compute_nn_metrics(sorting, recording, num_channels_to_compare=13, max_spikes_per_cluster=500, max_spikes_for_nn=10000, n_neighbors=4, n_comp=3, ms_before=1., ms_after=2., dtype=None, max_spikes_per_unit=300, recompute_info=True, max_spikes_for_pca=1e5, apply_filter=True, freq_min=300, freq_max=6000, save_features_props=False, unit_ids=None, epoch_tuples=None, epoch_names=None, save_as_property=True, seed=0): ''' Computes and returns the nearest neighbor metrics for the sorted dataset. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. recording: RecordingExtractor The given recording extractor from which to extract amplitudes. num_channels_to_compare: int The number of channels to be used for the PC extraction and comparison. max_spikes_per_cluster: int Max spikes to be used from each unit. max_spikes_for_nn: int Max spikes to be used for nearest-neighbors calculation. n_neighbors: int Number of neighbors to compare. n_comp: int n_compFeatures in template-gui format ms_before: float Time period in ms to cut waveforms before the spike events ms_after: float Time period in ms to cut waveforms after the spike events dtype: dtype The numpy dtype of the waveforms max_spikes_per_unit: int The maximum number of spikes to extract (default is np.inf) recompute_info: bool If True, will always re-extract waveforms. max_spikes_for_pca: int The maximum number of spikes to use to compute PCA (default is np.inf) apply_filter: bool If True, recording is bandpass-filtered. freq_min: float High-pass frequency for optional filter (default 300 Hz). freq_max: float Low-pass frequency for optional filter (default 6000 Hz). save_features_props: bool If True, save all features and properties in the sorting extractor. unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch. epoch_names: list A list of strings for the names of the given epochs. save_as_property: bool If True, the metric is saved as sorting property seed: int Random seed for reproducibility Returns ---------- nn_hit_rates_epochs: np.array The nearest neighbor hit rates for each specified unit. nn_miss_rates_epochs: np.array The nearest neighbor miss rates for each specified unit. ''' if unit_ids is None: unit_ids = sorting.get_unit_ids() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=recording.get_sampling_frequency(), unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) metric_calculator.compute_pca_scores(recording=recording, n_comp=n_comp, ms_before=ms_before, ms_after=ms_after, dtype=dtype, max_spikes_per_unit=max_spikes_per_unit, recompute_info=recompute_info, max_spikes_for_pca=max_spikes_for_pca, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max, save_features_props=save_features_props, seed=seed) nn_hit_rates_epochs, nn_miss_rates_epochs = metric_calculator.compute_nn_metrics( num_channels_to_compare=num_channels_to_compare, max_spikes_per_cluster=max_spikes_per_cluster, max_spikes_for_nn=max_spikes_for_nn, n_neighbors=n_neighbors, seed=seed) if save_as_property: if epoch_tuples is None: for i_u, u in enumerate(unit_ids): sorting.set_unit_property(u, 'nn_hit_rates', nn_hit_rates_epochs[i_u]) sorting.set_unit_property(u, 'nn_miss_rates', nn_miss_rates_epochs[i_u]) else: raise NotImplementedError("Quality metrics cannot be saved as properties if 'epochs_tuples' are given.") return nn_hit_rates_epochs, nn_miss_rates_epochs def compute_metrics(sorting, recording=None, sampling_frequency=None, isi_threshold=0.0015, min_isi=0.000166, snr_mode='mad', snr_noise_duration=10.0, max_spikes_per_unit_for_snr=1000, drift_metrics_interval_s=51, drift_metrics_min_spikes_per_interval=10, max_spikes_for_silhouette=10000, num_channels_to_compare=13, max_spikes_per_cluster=500, max_spikes_for_nn=10000, n_neighbors=4, n_comp=3, ms_before=1., ms_after=2., dtype=None, max_spikes_per_unit=300, amp_method='absolute', amp_peak='both', amp_frames_before=3, amp_frames_after=3, recompute_info=True, max_spikes_for_pca=1e5, apply_filter=True, freq_min=300, freq_max=6000, save_features_props=False, metric_names=None, unit_ids=None, epoch_tuples=None, epoch_names=None, return_dataframe=False, seed=0): ''' Computes and returns all specified metrics for the sorted dataset. Parameters ---------- sorting: SortingExtractor The sorting result to be evaluated. sampling_frequency: The sampling frequency of the result. If None, will check to see if sampling frequency is in sorting extractor. recording: RecordingExtractor The given recording extractor from which to extract amplitudes. If None, certain metrics cannot be computed. isi_threshold: float The isi threshold for calculating isi violations. min_isi: float The minimum expected isi value. snr_mode: str Mode to compute noise SNR ('mad' | 'std' - default 'mad') snr_noise_duration: float Number of seconds to compute noise level from (default 10.0) max_spikes_per_unit_for_snr: int Maximum number of spikes to compute templates from (default 1000) drift_metrics_interval_s: float Time period for evaluating drift. drift_metrics_min_spikes_per_interval: int Minimum number of spikes for evaluating drift metrics per interval. max_spikes_for_silhouette: int Max spikes to be used for silhouette metric num_channels_to_compare: int The number of channels to be used for the PC extraction and comparison. max_spikes_per_cluster: int Max spikes to be used from each unit to compute metrics. max_spikes_for_nn: int Max spikes to be used for nearest-neighbors calculation. n_neighbors: int Number of neighbors to compare for nearest-neighbors calculation. max_spikes_per_unit: int The maximum number of spikes to extract (default is np.inf) amp_method: str If 'absolute' (default), amplitudes are absolute amplitudes in uV are returned. If 'relative', amplitudes are returned as ratios between waveform amplitudes and template amplitudes. amp_peak: str If maximum channel has to be found among negative peaks ('neg'), positive ('pos') or both ('both' - default) amp_frames_before: int Frames before peak to compute amplitude amp_frames_after: float Frames after peak to compute amplitude recompute_info: bool If True, will always re-extract waveforms. max_spikes_for_pca: int The maximum number of spikes to use to compute PCA (default is np.inf) apply_filter: bool If True, recording is bandpass-filtered. freq_min: float High-pass frequency for optional filter (default 300 Hz). freq_max: float Low-pass frequency for optional filter (default 6000 Hz). save_features_props: bool If True, save all features and properties in the sorting extractor. n_comp: int n_compFeatures in template-gui format ms_before: float Time period in ms to cut waveforms before the spike events ms_after: float Time period in ms to cut waveforms after the spike events dtype: dtype The numpy dtype of the waveforms metrics_names: list The list of metric names to be computed. Available metrics are: 'firing_rate', 'num_spikes', 'isi_viol', 'presence_ratio', 'amplitude_cutoff', 'max_drift', 'cumulative_drift', 'silhouette_score', 'isolation_distance', 'l_ratio', 'd_prime', 'nn_hit_rate', 'nn_miss_rate', 'snr'. If None, all metrics are computed. unit_ids: list List of unit ids to compute metric for. If not specified, all units are used epoch_tuples: list A list of tuples with a start and end time for each epoch. epoch_names: list A list of strings for the names of the given epochs. return_dataframe: bool If True, this function will return a dataframe of the metrics. seed: int Random seed for reproducibility Returns ---------- metrics_epochs : list List of metrics data. The list consists of lists of metric data for each given epoch. OR metrics_df: pandas.DataFrame A pandas dataframe of the cached metrics ''' metrics_epochs = [] all_metrics_list = ['firing_rate', 'num_spikes', 'isi_viol', 'presence_ratio', 'amplitude_cutoff', 'max_drift', 'cumulative_drift', 'silhouette_score', 'isolation_distance', 'l_ratio', 'd_prime', 'nn_hit_rate', 'nn_miss_rate', 'snr'] if metric_names is None: metric_names = all_metrics_list else: bad_metrics = [] for m in metric_names: if m not in all_metrics_list: bad_metrics.append(m) if len(bad_metrics) > 0: raise ValueError("Wrong metrics name: " + str(bad_metrics)) if recording is not None: sampling_frequency = recording.get_sampling_frequency() metric_calculator = st.validation.MetricCalculator(sorting, sampling_frequency=sampling_frequency, unit_ids=unit_ids, epoch_tuples=epoch_tuples, epoch_names=epoch_names) if 'max_drift' in metric_names or 'cumulative_drift' in metric_names or 'silhouette_score' in metric_names \ or 'isolation_distance' in metric_names or 'l_ratio' in metric_names or 'd_prime' in metric_names \ or 'nn_hit_rate' in metric_names or 'nn_miss_rate' in metric_names: if recording is None: raise ValueError("The recording cannot be None when computing max_drift, cumulative_drift, " "silhouette_score isolation_distance, l_ratio, d_prime, nn_hit_rate, amplitude_cutoff, " "or nn_miss_rate.") else: metric_calculator.compute_all_metric_data(recording=recording, n_comp=n_comp, ms_before=ms_before, ms_after=ms_after, dtype=dtype, max_spikes_per_unit=max_spikes_per_unit, amp_method=amp_method, amp_peak=amp_peak, amp_frames_before=amp_frames_before, amp_frames_after=amp_frames_after, recompute_info=recompute_info, max_spikes_for_pca=max_spikes_for_pca, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max, save_features_props=save_features_props, seed=seed) elif 'amplitude_cutoff' in metric_names: if recording is None: raise ValueError("The recording cannot be None when computing amplitude cutoffs.") else: metric_calculator.compute_amplitudes(recording=recording, amp_method=amp_method, amp_peak=amp_peak, amp_frames_before=amp_frames_before, amp_frames_after=amp_frames_after, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max, save_features_props=save_features_props, seed=seed) elif 'snr' in metric_names: if recording is None: raise ValueError("The recording cannot be None when computing snr.") else: metric_calculator.set_recording(recording, apply_filter=apply_filter, freq_min=freq_min, freq_max=freq_max) if 'num_spikes' in metric_names: num_spikes_epochs = metric_calculator.compute_num_spikes() metrics_epochs.append(num_spikes_epochs) if 'firing_rate' in metric_names: firing_rates_epochs = metric_calculator.compute_firing_rates() metrics_epochs.append(firing_rates_epochs) if 'presence_ratio' in metric_names: presence_ratios_epochs = metric_calculator.compute_presence_ratios() metrics_epochs.append(presence_ratios_epochs) if 'isi_viol' in metric_names: isi_violations_epochs = metric_calculator.compute_isi_violations(isi_threshold=isi_threshold, min_isi=min_isi) metrics_epochs.append(isi_violations_epochs) if 'amplitude_cutoff' in metric_names: amplitude_cutoffs_epochs = metric_calculator.compute_amplitude_cutoffs() metrics_epochs.append(amplitude_cutoffs_epochs) if 'snr' in metric_names: snrs_epochs = metric_calculator.compute_snrs(snr_mode=snr_mode, snr_noise_duration=snr_noise_duration, max_spikes_per_unit_for_snr=max_spikes_per_unit_for_snr) metrics_epochs.append(snrs_epochs) if 'max_drift' in metric_names or 'cumulative_drift' in metric_names: max_drifts_epochs, cumulative_drifts_epochs = metric_calculator.compute_drift_metrics( drift_metrics_interval_s=drift_metrics_interval_s, drift_metrics_min_spikes_per_interval=drift_metrics_min_spikes_per_interval) if 'max_drift' in metric_names: metrics_epochs.append(max_drifts_epochs) if 'cumulative_drift' in metric_names: metrics_epochs.append(cumulative_drifts_epochs) if 'silhouette_score' in metric_names: silhouette_scores_epochs = metric_calculator.compute_silhouette_scores( max_spikes_for_silhouette=max_spikes_for_silhouette, seed=seed) metrics_epochs.append(silhouette_scores_epochs) if 'isolation_distance' in metric_names: isolation_distances_epochs = metric_calculator.compute_isolation_distances( num_channels_to_compare=num_channels_to_compare, max_spikes_per_cluster=max_spikes_per_cluster, seed=seed) metrics_epochs.append(isolation_distances_epochs) if 'l_ratio' in metric_names: l_ratios_epochs = metric_calculator.compute_l_ratios(num_channels_to_compare=num_channels_to_compare, max_spikes_per_cluster=max_spikes_per_cluster, seed=seed) metrics_epochs.append(l_ratios_epochs) if 'd_prime' in metric_names: d_primes_epochs = metric_calculator.compute_d_primes(num_channels_to_compare=num_channels_to_compare, max_spikes_per_cluster=max_spikes_per_cluster, seed=seed) metrics_epochs.append(d_primes_epochs) if 'nn_hit_rate' in metric_names or 'nn_miss_rate' in metric_names: nn_hit_rates_epochs, nn_miss_rates_epochs = metric_calculator.compute_nn_metrics( num_channels_to_compare=num_channels_to_compare, max_spikes_per_cluster=max_spikes_per_cluster, max_spikes_for_nn=max_spikes_for_nn, n_neighbors=n_neighbors, seed=seed) if 'nn_hit_rate' in metric_names: metrics_epochs.append(nn_hit_rates_epochs) if 'nn_miss_rate' in metric_names: metrics_epochs.append(nn_miss_rates_epochs) if return_dataframe: metrics_df = metric_calculator.get_metrics_df() return metrics_df else: return metrics_epochs

48.302013

129

0.658905

6,537

50,379

4.804803

0.039774

0.032952

0.023687

0.018339

0.904518

0.89121

0.884937

0.875864

0.86367

0.856729

0

0.008437

0.287124

50,379

1,042

130

48.348369

0.866125

0.407829

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1

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false

0

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0

0.074074

0

null

0

1

0

null

0

6

40a01a454c06c426f8e730660c8186f0008bbe29

27,389

py

Python

events/ped_events.py

mtasa-typescript/mtasa-wiki-dump

edea1746850fb6c99d6155d1d7891e2cceb33a5c

[ "MIT" ]

null

events/ped_events.py

mtasa-typescript/mtasa-wiki-dump

edea1746850fb6c99d6155d1d7891e2cceb33a5c

[ "MIT" ]

1

2021-02-24T21:50:18.000Z

events/ped_events.py

mtasa-typescript/mtasa-wiki-dump

edea1746850fb6c99d6155d1d7891e2cceb33a5c

[ "MIT" ]

null

# Autogenerated file. ANY CHANGES WILL BE OVERWRITTEN from to_python.core.types import FunctionType, \ FunctionArgument, \ FunctionArgumentValues, \ FunctionReturnTypes, \ FunctionSignature, \ FunctionDoc, \ EventData, \ CompoundEventData DUMP_PARTIAL = [ CompoundEventData( server=[ ], client=[ EventData( name='onClientPedDamage', docs=FunctionDoc( description='This event is triggered whenever a ped is damaged.' , arguments={ "attacker": """: A player element representing the attacker or vehicle element (when a ped falls of a bike). """, "weapon": """: An integer representing the Weapons|weapon ID the attacker used """, "bodypart": """: An integer representing the bodypart the ped was damaged """, "loss": """: A float representing the percentage of health the ped lost. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='attacker', argument_type=FunctionType( names=['element'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='weapon', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='bodypart', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='loss', argument_type=FunctionType( names=['float'], is_optional=True, ), default_value=None, ) ] ], variable_length=False, ), ) ], ), CompoundEventData( server=[ ], client=[ EventData( name='onClientPedHeliKilled', docs=FunctionDoc( description='This event is fired when a ped is killed due to the effect of a helicopter blades.' , arguments={ "killer": """the vehicle (heli) responsible for causing the death. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='killer', argument_type=FunctionType( names=['vehicle'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], ), CompoundEventData( server=[ ], client=[ EventData( name='onClientPedHitByWaterCannon', docs=FunctionDoc( description='This event is fired when a ped is hit by a water cannon.' , arguments={ "pedHit": """the ped which got shot by the water cannon """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='pedHit', argument_type=FunctionType( names=['ped'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], ), CompoundEventData( server=[ ], client=[ EventData( name='onClientPedStep', docs=FunctionDoc( description='This event is called when a peds foot has come on to the ground after jumping or taking a full step.' , arguments={ "leftFoot": """: a bool representing if it was the left foot that moved. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='leftFoot', argument_type=FunctionType( names=['bool'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], ), CompoundEventData( server=[ ], client=[ EventData( name='onClientPedVehicleEnter', docs=FunctionDoc( description='' , arguments={ "theVehicle": """The vehicle that the ped entered. """, "seat": """The seat that the ped now is on. Drivers seat = 0, higher numbers are passenger seats. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theVehicle', argument_type=FunctionType( names=['vehicle'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='seat', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], ), CompoundEventData( server=[ ], client=[ EventData( name='onClientPedVehicleExit', docs=FunctionDoc( description='' , arguments={ "theVehicle": """The vehicle that the ped exited. """, "seat": """The number of the seat that the ped was sitting on. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theVehicle', argument_type=FunctionType( names=['vehicle'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='seat', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], ), CompoundEventData( server=[ ], client=[ EventData( name='onClientPedWasted', docs=FunctionDoc( description='This event is triggered whenever a ped dies.' , arguments={ "killer": """: A player element representing the killer. """, "weapon": """: An int|integer representing the Weapons|killer weapon or the Damage Types|damage types. """, "bodypart": """: An int|integer representing the bodypart the player was damaged. """, "loss": """: A float representing the percentage of health the ped lost in the final hit. Note: Only for client-side created peds. '''OR''' """, "stealth": """: A boolean representing whether or not this was a stealth kill. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='killer', argument_type=FunctionType( names=['element'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='weapon', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='bodypart', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='loss', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ), FunctionArgument( name='stealth', argument_type=FunctionType( names=['bool'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], ), CompoundEventData( server=[ ], client=[ EventData( name='onClientPedWeaponFire', docs=FunctionDoc( description='This event is called when ped shoots a weapon. This does not trigger for projectiles based, or melee weapons.' , arguments={ "weapon": """: an int representing weapons|weapon used for making a shot. """, "ammo": """: an int ammount of ammo left for this weapon type. """, "ammoInClip": """: an int ammount of ammo left for this weapon type in clip. """, "hitX": """, hitY, hitZ: float world coordinates representing a hit point. """, "hitElement": """: an element which was hit by a shot. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='weapon', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='ammo', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='ammoInClip', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='hitX', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='hitY', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='hitZ', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='hitElement', argument_type=FunctionType( names=['element'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], ), CompoundEventData( server=[ EventData( name='onPedDamage', docs=FunctionDoc( description='This event is triggered when a ped is damaged. For player damage, use onPlayerDamage instead.' , arguments={ "loss": """: an int representing the percentage of health the ped lost. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='loss', argument_type=FunctionType( names=['float'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], client=[ ], ), CompoundEventData( server=[ EventData( name='onPedVehicleEnter', docs=FunctionDoc( description='' , arguments={ "theVehicle": """: A vehicle element representing the vehicle that was entered. """, "seat": """: An int representing the seat in which the ped is entering. """, "jacked": """: A player or ped element representing who has been jacked. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theVehicle', argument_type=FunctionType( names=['vehicle'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='seat', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='jacked', argument_type=FunctionType( names=['ped'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], client=[ ], ), CompoundEventData( server=[ EventData( name='onPedVehicleExit', docs=FunctionDoc( description='' , arguments={ "theVehicle": """: A vehicle element representing the vehicle in which the ped exited from. """, "seat": """: An int representing the seat in which the ped was before exiting. """, "jacker": """: A player or ped element representing who jacked the driver. """, "forcedByScript": """A boolean representing whether the exit was forced using removePedFromVehicle or by the ped. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='theVehicle', argument_type=FunctionType( names=['vehicle'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='seat', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='jacker', argument_type=FunctionType( names=['ped'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='forcedByScript', argument_type=FunctionType( names=['bool'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], client=[ ], ), CompoundEventData( server=[ EventData( name='onPedWasted', docs=FunctionDoc( description='This event is triggered when a ped is killed or dies. It is not triggered for players.' , arguments={ "totalAmmo": """: an int representing the total ammo the victim had when he died. """, "killer": """: an element representing the player or vehicle who was the killer. If there was no killer this is false. """, "killerWeapon": """: an int representing the Weapons|killer weapon or the Damage Types|damage types. """, "bodypart": """: an int representing the bodypart ID the victim was hit on when he died. """, "stealth": """: a boolean representing whether or not this was a stealth kill. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='totalAmmo', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='killer', argument_type=FunctionType( names=['element'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='killerWeapon', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='bodypart', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='stealth', argument_type=FunctionType( names=['bool'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], client=[ ], ), CompoundEventData( server=[ EventData( name='onPedWeaponSwitch', docs=FunctionDoc( description='This event is triggered when a ped switches weapons.' , arguments={ "previousWeaponID": """: an int representing the weapon that was switched from. """, "currentWeaponID": """: an int representing the weapon that was switched to. """ }, result='' , ), arguments=FunctionArgumentValues( arguments=[ [ FunctionArgument( name='previousWeaponID', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ], [ FunctionArgument( name='currentWeaponID', argument_type=FunctionType( names=['int'], is_optional=False, ), default_value=None, ) ] ], variable_length=False, ), ) ], client=[ ], ) ]

39.071327

150

0.312461

1,339

27,389

6.294996

0.150112

0.090165

0.108198

0.130739

0.761656

0.735081

0.706134

0.698066

0.674813

0

0.000096

0.618606

27,389

700

151

39.127143

0.806816

0.001862

0

0.708029

1

0.005839

0.145778

0.00417

0

1

0

false

0.00146

0

0.00146

0

null

0

1

0

1

0

1

0

1

0

null

0

6

9054ff3253327eff6e4f7afe4df3cc12d5f1ddc5

533

py

Python

imgaug/augmenters/__init__.py

hungrayho/yolo3

f3759bf10ab8bed4a5133989cda8f8d59b20aa16

[ "MIT" ]

null

imgaug/augmenters/__init__.py

hungrayho/yolo3

f3759bf10ab8bed4a5133989cda8f8d59b20aa16

[ "MIT" ]

null

imgaug/augmenters/__init__.py

hungrayho/yolo3

f3759bf10ab8bed4a5133989cda8f8d59b20aa16

[ "MIT" ]

null

from __future__ import absolute_import from imgaug.augmenters.arithmetic import * from imgaug.augmenters.blend import * from imgaug.augmenters.blur import * from imgaug.augmenters.color import * from imgaug.augmenters.contrast import * from imgaug.augmenters.convolutional import * from imgaug.augmenters.flip import * from imgaug.augmenters.geometric import * from imgaug.augmenters.meta import * from imgaug.augmenters.segmentation import * from imgaug.augmenters.size import * from imgaug.augmenters.weather import *

38.071429

46

0.810507

65

533

6.569231

0.276923

0.28103

0.449649

0.730679

0

0.121951

533

13

47

41

0.912393

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

1

0

6

9085c0a4366098004c978d03a3c382a4605bcbb3

5,160

py

Python

TestHtmlWrapper.py

ytyaru/Python.pylangstudy.HtmlWrapper.201705220846

e18a488577c4ed1af690fa629d988ef867c1834d

[ "CC0-1.0" ]

null

TestHtmlWrapper.py

ytyaru/Python.pylangstudy.HtmlWrapper.201705220846

e18a488577c4ed1af690fa629d988ef867c1834d

[ "CC0-1.0" ]

null

TestHtmlWrapper.py

ytyaru/Python.pylangstudy.HtmlWrapper.201705220846

e18a488577c4ed1af690fa629d988ef867c1834d

[ "CC0-1.0" ]

null

import unittest import os.path import HtmlWrapper class TestHtmlWrapper(unittest.TestCase): # def __init__(self): # pass def test_CreateElement_html(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html') self.assertEqual(html, '<html></html>') def test_Wrap_html(self): w = HtmlWrapper.HtmlWrapper() html = w.Wrap(w.CreateElement('html'), w.CreateElement('body')) self.assertEqual(html, '<html><body></body></html>') def test_Wrap_nest3(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html') body = w.CreateElement('body') ul = w.CreateElement('ul') lis = '' for count in range(1, 4): lis += w.CreateElement('li', text_node_value='項目{0}'.format(count)) ul = w.Wrap(ul, lis) body = w.Wrap(body, ul) html = w.Wrap(html, body) self.assertEqual(html, '<html><body><ul><li>項目1</li><li>項目2</li><li>項目3</li></ul></body></html>') def test_CreateElement_Attributes(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', lang='ja') self.assertEqual(html, '<html lang="ja"></html>') def test_CreateElement_Attributes_dict(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', **{'lang': 'ja'}) self.assertEqual(html, '<html lang="ja"></html>') def test_CreateElement_Attributes_id_(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', id_='id1') self.assertEqual(html, '<html id="id1"></html>') def test_CreateElement_Attributes_class_(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', class_='cls1 cls2') self.assertEqual(html, '<html class="cls1 cls2"></html>') def test_CreateElement_Attributes_id_class_(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', id_='id1', class_='cls1 cls2') self.assertIn(html, ['<html id="id1" class="cls1 cls2"></html>', '<html class="cls1 cls2" id="id1"></html>']) def test_CreateElement_Attributes_id(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', **{'id': 'id1'}) self.assertEqual(html, '<html id="id1"></html>') def test_CreateElement_Attributes_class(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', **{'class': 'cls1 cls2'}) self.assertEqual(html, '<html class="cls1 cls2"></html>') def test_CreateElement_Attributes_id_class(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', **{'id': 'id1', 'class': 'cls1 cls2'}) self.assertIn(html, ['<html id="id1" class="cls1 cls2"></html>', '<html class="cls1 cls2" id="id1"></html>']) def test_CreateElement_Attributes_id_id(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', id_='id1', **{'id': 'id2'}) self.assertEqual(html, '<html id="id1"></html>') def test_CreateElement_Attributes_class_class(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', class_='cls1 cls2', **{'class': 'cls3 cls4'}) self.assertEqual(html, '<html class="cls1 cls2"></html>') def test_CreateElement_Attributes_id_id_class_class(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', id_='id1', class_='cls1 cls2', **{'id': 'id2', 'class': 'cls3 cls4'}) self.assertIn(html, ['<html id="id1" class="cls1 cls2"></html>', '<html class="cls1 cls2" id="id1"></html>']) def test_CreateElement_Attributes_dict(self): w = HtmlWrapper.HtmlWrapper() html = w.CreateElement('html', **{'id': 'id1', 'class': 'cls1 cls2', 'lang': 'ja'}) self.assertIn(html, [ '<html id="id1" class="cls1 cls2" lang="ja"></html>', '<html id="id1" lang="ja" class="cls1 cls2"></html>', '<html lang="ja" id="id1" class="cls1 cls2"></html>', '<html lang="ja" class="cls1 cls2" id="id1"></html>', '<html class="cls1 cls2" lang="ja" id="id1"></html>', '<html class="cls1 cls2" id="id1" lang="ja"></html>' ]) def test_CreateElement_None(self): w = HtmlWrapper.HtmlWrapper() element_name = None with self.assertRaises(Exception) as e: html = w.CreateElement(element_name) self.assertEqual(e.msg, '要素名を指定してください。: element_name = {0}'.format(element_name)) def test_CreateElement_blank(self): w = HtmlWrapper.HtmlWrapper() element_name = '' with self.assertRaises(Exception) as e: html = w.CreateElement(element_name) self.assertEqual(e.msg, '要素名を指定してください。: element_name = {0}'.format(element_name)) def test_CreateElement_space(self): w = HtmlWrapper.HtmlWrapper() element_name = ' ' with self.assertRaises(Exception) as e: html = w.CreateElement(element_name) self.assertEqual(e.msg, '要素名を指定してください。: element_name = {0}'.format(element_name))

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0

1

0

1

0

null

0

6

908ac9bab86cd055cff258beb8bef1a4ea213786

250

py

Python

decorator_2.py

jepster/python_advanced_techniques

f4b0e0dda7b66be55f650f9f902e735d3f5a9f64

[ "MIT" ]

null

decorator_2.py

jepster/python_advanced_techniques

f4b0e0dda7b66be55f650f9f902e735d3f5a9f64

[ "MIT" ]

null

decorator_2.py

jepster/python_advanced_techniques

f4b0e0dda7b66be55f650f9f902e735d3f5a9f64

[ "MIT" ]

null

def make_divisibility_test(n): def divisible_by_n(m): return m % n == 0 return divisible_by_n div_by_3 = make_divisibility_test(3) tuple(filter(div_by_3, range(10))) # => (0, 3, 6, 9) print(make_divisibility_test(5)(10)) # => True

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6

90f9d1b8609fcd41593763343270ab9e8e8f2f86

150

py

Python

capcom/__init__.py

rcthomas/capcom

e72c41da046e05d8450dfa7297cb5dee5a206daa

[ "BSD-3-Clause" ]

1

2015-07-24T21:32:22.000Z

capcom/__init__.py

rcthomas/capcom

e72c41da046e05d8450dfa7297cb5dee5a206daa

[ "BSD-3-Clause" ]

null

capcom/__init__.py

rcthomas/capcom

e72c41da046e05d8450dfa7297cb5dee5a206daa

[ "BSD-3-Clause" ]

null

from census import * from dbi import * from parser import * from scraper import * from selector import *

25

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6

290cd744c3bed450a7f51b9e08827eacc782b0b8

169

py

Python

active_semi_clustering/exceptions.py

heriosousa/active-semi-supervised-clustering

8ed97c7f3bdd76cf6c03e0ca6ef56bcf27b2d399

[ "MIT" ]

67

2018-11-09T06:59:31.000Z

2021-11-04T06:54:36.000Z

active_semi_clustering/exceptions.py

heriosousa/active-semi-supervised-clustering

8ed97c7f3bdd76cf6c03e0ca6ef56bcf27b2d399

[ "MIT" ]

5

2020-03-24T18:10:32.000Z

2021-06-02T01:08:20.000Z

active_semi_clustering/exceptions.py

heriosousa/active-semi-supervised-clustering

8ed97c7f3bdd76cf6c03e0ca6ef56bcf27b2d399

[ "MIT" ]

29

2018-10-16T15:36:28.000Z

2021-11-20T10:09:41.000Z

class ClusteringNotFoundException(Exception): pass class EmptyClustersException(Exception): pass class InconsistentConstraintsException(Exception): pass

15.363636

50

0.798817

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169

11.25

0.5

0.288889

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169

10

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null

1

0

null

0

1

0

6

291d7795a276f54915ea30b9e2a876b3400978a4

45

py

Python

src/satextractor/tiler/__init__.py

oxfordeo/sat-extractor

1d6841751e8b2ce65a02f5d3d608f181a31ab917

[ "BSD-2-Clause" ]

29

2021-11-02T16:07:04.000Z

2022-03-14T00:16:27.000Z

src/satextractor/tiler/__init__.py

oxfordeo/sat-extractor

1d6841751e8b2ce65a02f5d3d608f181a31ab917

[ "BSD-2-Clause" ]

16

2021-11-01T16:23:01.000Z

2022-03-24T11:44:13.000Z

src/satextractor/tiler/__init__.py

oxfordeo/sat-extractor

1d6841751e8b2ce65a02f5d3d608f181a31ab917

[ "BSD-2-Clause" ]

6

2021-11-09T01:10:30.000Z

2022-03-14T18:04:32.000Z

from .tiler import split_region_in_utm_tiles

22.5

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1

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1

0

1

0

6

29385fc52e1ebe822e998c4e12734fb1b6d0a3d0

4,292

py

Python

torchqf/stochastic/brownian.py

simaki/torchqf

e4dfd154c62ccd858847048f77d8c2f82924ae80

[ "BSD-3-Clause" ]

7

2021-05-18T17:03:10.000Z

2021-12-01T07:58:41.000Z

torchqf/stochastic/brownian.py

vishalbelsare/torchqf

e4dfd154c62ccd858847048f77d8c2f82924ae80

[ "BSD-3-Clause" ]

27

2021-05-18T03:54:17.000Z

2022-01-31T15:16:16.000Z

torchqf/stochastic/brownian.py

vishalbelsare/torchqf

e4dfd154c62ccd858847048f77d8c2f82924ae80

[ "BSD-3-Clause" ]

3

2021-07-13T12:56:12.000Z

2021-12-26T23:00:06.000Z

import torch from torch import Tensor from ..tensor import steps def generate_brownian( size, time, drift: float = 0.0, volatility: float = 0.2, init_value: float = 0.0, dtype=None, device=None, ) -> Tensor: """Generates and returns time-series that follows Brownian motion. Args: size (torch.Size): The shape of the output tensor. The last dimension means the number of time steps. time (float | Tensor): The total time length (`float`) or time steps (`Tensor`). drift (float, default 0.0): The drift of the process. volatility (float, default 0.2): The volatility of the process. init_value (float, default 0.0) Initial value of the process. dtype (`torch.dtype`, optional): The desired data type of returned tensor. Default: if None, uses a global default (see `torch.set_default_tensor_type()`). device (`torch.device`, optional): The desired device of returned tensor. Default: if None, uses the current device for the default tensor type (see `torch.set_default_tensor_type()`). `device` will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. Returns: Tensor: The time-series. Size: - time: :math:`(T,)` :math:`T` means the number of time steps. - output: :math:`(*, T)` The shape specified by `size`. Examples: >>> from torchqf.stochastic import generate_brownian >>> _ = torch.manual_seed(42) >>> generate_brownian((2, 5), time=0.1) tensor([[ 0.0095, 0.0132, 0.0198, 0.0263, -0.0054], [-0.0053, 0.0572, 0.0391, 0.0522, 0.0598]]) """ assert dtype is None, "not supported" assert device is None, "not supported" n_steps = size[-1] if not isinstance(time, torch.Tensor): time = steps(time, n_steps) # shape : (T,) dt = torch.empty_like(time) dt[0] = time[0] - 0.0 dt[1:] = time[1:] - time[:-1] drift_term = drift * time random_term = (volatility * torch.randn(size) * dt.sqrt()).cumsum(-1) return init_value + drift_term + random_term def generate_geometric_brownian( size, time, drift: float = 0.0, volatility: float = 0.2, init_value: float = 1.0, dtype=None, device=None, ) -> Tensor: """Generates and returns time-series that follows geometric Brownian motion. Args: size (tuple[int]): The shape of the output tensor. The last dimension means the number of time steps. time (float | Tensor): The total time length (`float`) or time steps (`Tensor`). drift (float, default 0.0): The drift of the process. volatility (float, default 0.2): The volatility of the process. init_value (float, default 0.0): Initial value of the process. dtype (`torch.dtype`, optional): The desired data type of returned tensor. Default: if None, uses a global default (see `torch.set_default_tensor_type()`). device (`torch.device`, optional): The desired device of returned tensor. Default: if None, uses the current device for the default tensor type (see `torch.set_default_tensor_type()`). `device` will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. Returns: ------- Tensor: The time-series. Size: - time: :math:`(T,)` :math:`T` means the number of time steps. - output: :math:`(*, T)` The shape specified by `size`. Examples: >>> from torchqf.stochastic import generate_geometric_brownian >>> _ = torch.manual_seed(42) >>> generate_geometric_brownian((2, 5), time=0.1) tensor([[1.0092, 1.0124, 1.0188, 1.0250, 0.9926], [0.9943, 1.0580, 1.0387, 1.0519, 1.0595]]) """ assert dtype is None, "not supported" assert device is None, "not supported" brown = generate_brownian( size, time=time, drift=drift - volatility ** 2 / 2, volatility=volatility, dtype=dtype, device=device, ) return init_value * torch.exp(brown)

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0.162791

0

null

0

1

0

1

0

null

0

6

294c59832bba932ffc6997cadfe29c3060020bf2

71

py

Python

problem3_6starter_origin.py

BjornChrisnach/Coursera_Python_concise_intro

12c3c022b89dc8bba0fe02000728a69d7e4fd0ef

[ "MIT" ]

null

problem3_6starter_origin.py

BjornChrisnach/Coursera_Python_concise_intro

12c3c022b89dc8bba0fe02000728a69d7e4fd0ef

[ "MIT" ]

null

problem3_6starter_origin.py

BjornChrisnach/Coursera_Python_concise_intro

12c3c022b89dc8bba0fe02000728a69d7e4fd0ef

[ "MIT" ]

null

# -problem3_6.py *- coding: utf-8 -*- import sys # add your code here

14.2

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0.647887

12

71

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1

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0.197183

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0

1

0

1

0

6

4621d7096646ebfc22985e637e3ed0aa96d4a8f8

39

py

Python

sleepmind/models/__init__.py

IamGianluca/sleepmind

7132feb08086e57219ff9859545eafa6842b5c96

[ "MIT" ]

1

2018-12-06T21:19:50.000Z

sleepmind/models/__init__.py

IamGianluca/sleepmind

7132feb08086e57219ff9859545eafa6842b5c96

[ "MIT" ]

2

2018-11-24T17:20:33.000Z

2021-06-01T22:28:31.000Z

sleepmind/models/__init__.py

IamGianluca/sleepmind

7132feb08086e57219ff9859545eafa6842b5c96

[ "MIT" ]

1

2019-03-05T19:57:18.000Z

from .xgboost import XGBoostClassifier

19.5

38

0.871795

4

39

8.5

1

0

0.102564

39

1

39

0.971429

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1

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0

null

0

1

0

1

0

1

0

6

462ad89e5a98b2236f40eda1d78eb54c68ad2774

116

py

Python

Lib/fontTools/ttLib/tables/T_S_I_J_.py

anntzer/fonttools

726cd67549956b985bbbe83e26fb0af9da59ddf7

[ "MIT", "BSD-3-Clause" ]

2

2021-04-07T16:47:04.000Z

2022-01-15T04:01:01.000Z

Lib/fontTools/ttLib/tables/T_S_I_J_.py

anntzer/fonttools

726cd67549956b985bbbe83e26fb0af9da59ddf7

[ "MIT", "BSD-3-Clause" ]

74

2020-01-30T07:27:54.000Z

2021-08-03T05:47:17.000Z

Lib/fontTools/ttLib/tables/T_S_I_J_.py

anntzer/fonttools

726cd67549956b985bbbe83e26fb0af9da59ddf7

[ "MIT", "BSD-3-Clause" ]

1

2020-01-22T20:06:09.000Z

from fontTools.misc.py23 import * from .T_S_I_V_ import table_T_S_I_V_ class table_T_S_I_J_(table_T_S_I_V_): pass

19.333333

37

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0.103896

0.155844

0.233766

0

0.019417

0.112069

116

5

38

23.2

0.728155

0

1

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true

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null

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1

0

null

0

1

0

1

0

6

465e79d220f84e2d98aaec826747b644e378b931

157

py

Python

molecule/official_packages/tests/test_software.py

mesaguy/ansible-hashicorp

1e2a0fb5fa11061968de2a574853b1a6b4cee80d

[ "MIT" ]

2

2021-04-23T12:32:28.000Z

2021-12-23T20:00:10.000Z

molecule/official_packages/tests/test_software.py

mesaguy/ansible-hashicorp

1e2a0fb5fa11061968de2a574853b1a6b4cee80d

[ "MIT" ]

null

molecule/official_packages/tests/test_software.py

mesaguy/ansible-hashicorp

1e2a0fb5fa11061968de2a574853b1a6b4cee80d

[ "MIT" ]

null

def test_installed(host, hashicorp_official_package_names): for name in hashicorp_official_package_names: assert host.package(name).is_installed

39.25

59

0.808917

21

157

5.666667

0.619048

0.285714

0.403361

0.487395

0

0.133758

157

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52.333333

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false

0

0.333333

0

1

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null

1

0

1

0

null

0

1

0

6

466b740ac6f5504a3e0bd592a76eb7ea9cb7f560

52

py

Python

server/app.py

henri-hulski/morepath_cerebral_todomvc

568ac277c1844c4cf28bbacf484940f779fc7407

[ "BSD-3-Clause" ]

314

2015-01-01T01:42:52.000Z

2022-01-07T21:46:15.000Z

server/app.py

henri-hulski/morepath_cerebral_todomvc

568ac277c1844c4cf28bbacf484940f779fc7407

[ "BSD-3-Clause" ]

369

2015-01-02T19:10:40.000Z

2021-07-03T04:37:27.000Z

server/app.py

henri-hulski/morepath_cerebral_todomvc

568ac277c1844c4cf28bbacf484940f779fc7407

[ "BSD-3-Clause" ]

37

2015-01-11T09:22:02.000Z

2021-07-02T20:48:20.000Z

import morepath class App(morepath.App): pass

8.666667

24

0.711538

7

52

5.285714

0.714286

0

0.211538

52

5

25

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0

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true

0.333333

0

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null

0

1

0

null

0

1

0

1

0

6

46996a6bda526fcafacf4d33206d23606c9e01fa

8,127

py

Python

ExampleCases/OpFAST_FLORIS_WF3x1/plotyaw.py

tonino102008/openfast

cfb401af163f4e0b6bb8588c23374e1534ad8d87

[ "Apache-2.0" ]

null

ExampleCases/OpFAST_FLORIS_WF3x1/plotyaw.py

tonino102008/openfast

cfb401af163f4e0b6bb8588c23374e1534ad8d87

[ "Apache-2.0" ]

null

ExampleCases/OpFAST_FLORIS_WF3x1/plotyaw.py

tonino102008/openfast

cfb401af163f4e0b6bb8588c23374e1534ad8d87

[ "Apache-2.0" ]

1

2021-02-05T17:50:01.000Z

import matplotlib.pyplot as plt import numpy import pandas as pd import control.matlab as cnt import cp import scipy.optimize as optim dfdata = pd.read_csv('t1.T1.out', sep='\t', header=None, skiprows=10) datadata = dfdata.values dfdata2 = pd.read_csv('t2.T2.out', sep='\t', header=None, skiprows=10) datadata2 = dfdata2.values dfdata3 = pd.read_csv('t3.T3.out', sep='\t', header=None, skiprows=10) datadata3 = dfdata3.values iT = 0 nT = 3 nend = 30000 df = pd.read_csv('EPOWER.txt', header=None) data = df.values[iT::nT,:] df6 = pd.read_csv('ECROSS.txt', header=None) data6 = df6.values[iT::nT,:] df8 = pd.read_csv('EWIND.txt', header=None) data8 = df8.values[iT::nT,:] fig, axes = plt.subplots(2,sharex = True) axes[0].plot(datadata[:,0], datadata[:,21], 'r') axes[0].set_title("T1 Yaw Angle w.r.t. Wind Direction", fontsize = 20) axes[0].set_ylabel("T1 Yaw Angle (deg)", fontsize = 20) axes[0].set_xlabel("Simulated Time (s)", fontsize = 20) axes[0].tick_params(axis="x", labelsize=20) axes[0].tick_params(axis="y", labelsize=20) axes[1].plot(datadata2[:,0], datadata2[:,21], 'r') axes[1].set_title("T2 Yaw Angle w.r.t. Wind Direction", fontsize = 20) axes[1].set_ylabel("T2 Yaw Angle (deg)", fontsize = 20) axes[1].set_xlabel("Simulated Time (s)", fontsize = 20) axes[1].tick_params(axis="x", labelsize=20) axes[1].tick_params(axis="y", labelsize=20) plt.show() plt.plot(datadata[:,0], datadata[:,1], 'b') plt.title("T1 Wind Speed \n X-axis of Reference Farm Layout", fontsize = 20) plt.ylabel("Wind Speed (m/s)", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() plt.plot(datadata[:,0], datadata[:,21], 'r') plt.title("T1 Yaw Angle w.r.t. Wind Direction", fontsize = 20) plt.ylabel("Yaw Angle", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() plt.plot(datadata2[:,0], datadata2[:,1], 'b') plt.title("T2 Wind Speed \n X-axis of Reference Farm Layout", fontsize = 20) plt.ylabel("Wind Speed (m/s)", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() plt.plot(datadata2[:,0], datadata2[:,21], 'r') plt.title("T2 Yaw Angle w.r.t. Wind Direction", fontsize = 20) plt.ylabel("Yaw Angle", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() plt.plot(datadata3[:,0], datadata3[:,1], 'b') plt.title("T3 Wind Speed \n X-axis of Reference Farm Layout", fontsize = 20) plt.ylabel("Wind Speed (m/s)", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() plt.plot(datadata3[:,0], datadata3[:,21], 'r') plt.title("T3 Yaw Angle w.r.t. Wind Direction", fontsize = 20) plt.ylabel("Yaw Angle", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() plt.plot(datadata[:,0], datadata[:,23], 'b', datadata2[:,0], datadata2[:,23], 'r', datadata3[:,0], datadata3[:,23], 'g') plt.title("Ct") plt.show() nn = min([len(data6[:,0]), len(data8[:,0]), len(datadata[:,0])]) Wind_mag = numpy.power(numpy.power(datadata[:nn:,1], 2) + numpy.power(datadata[:nn:,2], 2), 0.5) plt.plot(data6[:nn:,2], numpy.arctan2(data6[:nn:,0], data8[:nn:,0])*180/numpy.pi, 'b', data6[:nn:,2], numpy.arctan2(data6[:nn:,1], data8[:nn:,0])*180/numpy.pi, 'y', datadata[:nn:,0], numpy.arctan2(datadata[:nn:,2] - numpy.multiply(Wind_mag, numpy.sin(datadata[:nn:,21] * numpy.pi/180.0)), datadata[:,1])*180/numpy.pi,'r', datadata[:nn:,0], numpy.arctan2(datadata[:nn:,2], datadata[:nn:,1])*180.0/numpy.pi, 'g') plt.title("CROSS WIND ESTIMATE YAW ERROR", fontsize = 20) plt.xlabel("SIMULATED TIME (s)", fontsize = 20) plt.ylabel("WIND RELATIVE YAW ERROR (deg)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.ylim(-35,35) plt.show() fig, axes = plt.subplots(2,sharex = True) axes[0].plot(datadata[:,0], datadata[:,1], 'b') axes[0].set_title("Wind X", fontsize = 20) axes[0].set_ylabel("Wind X (m/s)", fontsize = 20) axes[0].set_xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) axes[1].plot(datadata[:,0], datadata[:,2], 'r') axes[1].set_title("Wind Y", fontsize = 20) axes[1].set_ylabel("Wind X (m/s)", fontsize = 20) axes[1].set_xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() plt.plot(datadata[:,0], datadata[:,1], 'b', datadata2[:,0], datadata2[:,1], 'r' ,datadata3[:,0], datadata3[:,1], 'g') plt.title("Wind U", fontsize = 20) plt.ylabel("Wind U (m/s)", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() plt.plot(datadata2[:,0], datadata2[:,1], 'b') plt.title("Wind U", fontsize = 20) plt.ylabel("Wind U (m/s)", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() plt.plot(datadata3[:,0], datadata3[:,1], 'b') plt.title("Wind U", fontsize = 20) plt.ylabel("Wind U (m/s)", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() fig, axes = plt.subplots(2,sharex = True) axes[0].plot(datadata2[:,0], datadata2[:,1], 'b') axes[0].set_title("Wind X", fontsize = 20) axes[0].set_ylabel("Wind X (m/s)", fontsize = 20) axes[0].set_xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) axes[1].plot(datadata2[:,0], datadata2[:,2], 'r') axes[1].set_title("Wind Y", fontsize = 20) axes[1].set_ylabel("Wind X (m/s)", fontsize = 20) axes[1].set_xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() fig, axes = plt.subplots(2,sharex = True) axes[0].plot(datadata3[:,0], datadata3[:,1], 'b') axes[0].set_title("Wind X", fontsize = 20) axes[0].set_ylabel("Wind X (m/s)", fontsize = 20) axes[0].set_xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) axes[1].plot(datadata3[:,0], datadata3[:,2], 'r') axes[1].set_title("Wind Y", fontsize = 20) axes[1].set_ylabel("Wind X (m/s)", fontsize = 20) axes[1].set_xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() fig, axes = plt.subplots(2,sharex = True) axes[0].plot(datadata[:,0], datadata[:,21], 'b') axes[0].set_title("Yaw Position") axes[1].plot(datadata[:,0], datadata[:,22]*numpy.pi/180.0, 'r') axes[1].set_title("Yaw Speed") plt.show() fig, axes = plt.subplots(2,sharex = True) axes[0].plot(datadata2[:,0], datadata2[:,21], 'b') axes[0].set_title("Yaw Position") axes[1].plot(datadata2[:,0], datadata2[:,22]*numpy.pi/180.0, 'r') axes[1].set_title("Yaw Speed") plt.show() fig, axes = plt.subplots(2,sharex = True) axes[0].plot(datadata3[:,0], datadata3[:,21], 'b') axes[0].set_title("Yaw Position") axes[1].plot(datadata3[:,0], datadata3[:,22]*numpy.pi/180.0, 'r') axes[1].set_title("Yaw Speed") plt.show() plt.plot(datadata[:,0], datadata[:,52], 'b', datadata2[:,0], datadata2[:,52],'r', datadata3[:,0], datadata3[:,52], 'g') plt.title("POWER", fontsize = 20) plt.ylabel("POWER (kW)", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show() nn = min([len(datadata[:,0]), len(datadata2[:,0]), len(datadata3[:,0])]) plt.plot(datadata[:nn:,0], datadata[:nn:,52]+datadata2[:nn:,52]+datadata3[:nn:,52],'g') plt.title("POWER TOTAL", fontsize = 20) plt.ylabel("POWER TOTAL (kW)", fontsize = 20) plt.xlabel("Simulated Time (s)", fontsize = 20) plt.xticks(fontsize=20, rotation=0) plt.yticks(fontsize=20, rotation=0) plt.show()

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null

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null

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6

d3bc046401a00e84d30558571e42547a86086b34

43

py

Python

hyde/__init__.py

MoonCrystalPower/Dr.Hyde

e324f60899fad0d96aa35a6e669c9aa7dff6ca58

[ "MIT" ]

null

hyde/__init__.py

MoonCrystalPower/Dr.Hyde

e324f60899fad0d96aa35a6e669c9aa7dff6ca58

[ "MIT" ]

null

hyde/__init__.py

MoonCrystalPower/Dr.Hyde

e324f60899fad0d96aa35a6e669c9aa7dff6ca58

[ "MIT" ]

null

from .app import * from .commands import *

14.333333

23

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1

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1

0

1

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6

d3e7b88a903e8f5daf0380d2a77023f1e7db7c58

4,287

py

Python

savanamedapi/test/test_api.py

erego/savanamedapi

bcf79fd92c20a2a9abc3cc41d121844a67ec78d3

[ "MIT" ]

null

savanamedapi/test/test_api.py

erego/savanamedapi

bcf79fd92c20a2a9abc3cc41d121844a67ec78d3

[ "MIT" ]

null

savanamedapi/test/test_api.py

erego/savanamedapi

bcf79fd92c20a2a9abc3cc41d121844a67ec78d3

[ "MIT" ]

null

from unittest import TestCase import json from savanamedapi import app class TestApi(TestCase): def setUp(self): self.test_client = app.test_client(self) def test_list_api_cancer(self): param_to_sent = {"search": "cancer"} resp = self.test_client.post("/savanamed/api/get_terms", data=json.dumps(param_to_sent)) data = json.loads(resp.data.decode()) self.assertEqual(len(data["terms"]), 0) resp = self.test_client.get("/savanamed/api/get_terms", query_string=param_to_sent) data = json.loads(resp.data.decode()) self.assertEqual(len(data["terms"]), 0) def test_list_api_embarazo(self): param_to_sent = {"search": "embarazo"} resp = self.test_client.post("/savanamed/api/get_terms", data=json.dumps(param_to_sent)) data = json.loads(resp.data.decode()) self.assertEqual(len(data["terms"]), 1) self.assertEqual(data['terms'][0]['name'], 'embarazo') self.assertEqual(data['terms'][0]['id'], 4) resp = self.test_client.get("/savanamed/api/get_terms", query_string=param_to_sent) data = json.loads(resp.data.decode()) self.assertEqual(len(data["terms"]), 1) self.assertEqual(data['terms'][0]['name'], 'embarazo') self.assertEqual(data['terms'][0]['id'], 4) def test_list_api_cirugia(self): param_to_sent = {"search": "cirugia"} resp = self.test_client.post("/savanamed/api/get_terms", data=json.dumps(param_to_sent)) data = json.loads(resp.data.decode()) self.assertEqual(len(data["terms"]), 2) self.assertEqual(data['terms'][0]['name'], 'cirugia') self.assertEqual(data['terms'][0]['id'], 2) self.assertEqual(data['terms'][1]['name'], 'cirugia cardiaca') self.assertEqual(data['terms'][1]['id'], 3) resp = self.test_client.get("/savanamed/api/get_terms", query_string=param_to_sent) data = json.loads(resp.data.decode()) self.assertEqual(len(data["terms"]), 2) self.assertEqual(data['terms'][0]['name'], 'cirugia') self.assertEqual(data['terms'][0]['id'], 2) self.assertEqual(data['terms'][1]['name'], 'cirugia cardiaca') self.assertEqual(data['terms'][1]['id'], 3) def test_list_api_param_wrong(self): param_to_sent = {"searching": "cancer"} resp = self.test_client.post("/savanamed/api/get_terms", data=json.dumps(param_to_sent)) data = json.loads(resp.data.decode()) self.assertEqual(data["message"], "Search key not found") def test_detail_api(self): param_to_sent = {"id": 1} resp = self.test_client.post("/savanamed/api/get_details", data=json.dumps(param_to_sent)) data = json.loads(resp.data.decode()) self.assertEqual(data['detail_term'][0]['name'], 'ictus') self.assertEqual(len(data['detail_term'][0]['descriptions']), 2) resp = self.test_client.get("/savanamed/api/get_details", query_string=param_to_sent) data = json.loads(resp.data.decode()) self.assertEqual(data['detail_term'][0]['name'], 'ictus') self.assertEqual(len(data['detail_term'][0]['descriptions']), 2) def test_detail_api_param_wrong(self): param_to_sent = {"ident": 1} resp = self.test_client.post("/savanamed/api/get_details", data=json.dumps(param_to_sent)) data = json.loads(resp.data.decode()) self.assertEqual(data["message"], "Id key not found in parameters") def test_detail_api_id_not_found(self): param_to_sent = {"id": 7} resp = self.test_client.post("/savanamed/api/get_details", data=json.dumps(param_to_sent)) data = json.loads(resp.data.decode()) self.assertEqual(len(data['detail_term']), 0) def test_endpoint_not_exist(self): param_to_sent = {"id": 1} resp = self.test_client.post("/savanamed/api/get_descriptions", data=json.dumps(param_to_sent)) data = json.loads(resp.data.decode()) self.assertEqual(resp.status_code, 404) self.assertEqual(data['message'], "The requested URL was not found on the server. If you entered the URL " "manually please check your spelling and try again.")

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null

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6

d3fdde1c55ff9d1a94ef0962125ea91849e5ec28

78

py

Python

pyspecnest/tests/__init__.py

vlas-sokolov/pyspecnest

b8bd7044380da3cca7d2a5323c141d4b1ca93cd1

[ "MIT" ]

1

2019-01-16T16:19:12.000Z

pyspecnest/tests/__init__.py

vlas-sokolov/pyspecnest

b8bd7044380da3cca7d2a5323c141d4b1ca93cd1

[ "MIT" ]

4

2019-09-17T22:24:55.000Z

2020-04-15T15:08:04.000Z

pyspecnest/tests/__init__.py

vlas-sokolov/pyspecnest

b8bd7044380da3cca7d2a5323c141d4b1ca93cd1

[ "MIT" ]

3

2019-09-18T08:17:59.000Z

2021-02-28T19:50:36.000Z

from . import blackbox from . import spec_model_tests from . import run_tests

19.5

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6

312a8ed82b9f7859937aa3f9bd211b42ec91523e

69

py

Python

qunetsim/objects/packets/__init__.py

pritamsinha2304/QuNetSim

65a7486d532816724b5c98cfdcc0910404bfe0e2

[ "MIT" ]

61

2020-02-15T00:59:20.000Z

2022-03-08T10:29:23.000Z

qunetsim/objects/packets/__init__.py

pritamsinha2304/QuNetSim

65a7486d532816724b5c98cfdcc0910404bfe0e2

[ "MIT" ]

50

2020-01-28T12:18:50.000Z

2021-12-16T21:38:19.000Z

qunetsim/objects/packets/__init__.py

pritamsinha2304/QuNetSim

65a7486d532816724b5c98cfdcc0910404bfe0e2

[ "MIT" ]

27

2020-01-21T12:59:28.000Z

2022-02-21T14:23:00.000Z

from .packet import Packet from .routing_packet import RoutingPacket

23

41

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9

69

6.444444

0.555556

0.413793

0

0.115942

69

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34.5

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null

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1

0

1

0

1

0

6

317a9aaa2a03b0da292b0b17543c96705af24412

42

py

Python

services/music/test/__init__.py

Ovakefali13/buerro

1476f6e708f95a09a2d73f67ae8aa2cb3bb836af

[ "MIT" ]

2

2020-03-26T19:20:31.000Z

2020-03-30T13:09:07.000Z

services/music/test/__init__.py

Ovakefali13/buerro

1476f6e708f95a09a2d73f67ae8aa2cb3bb836af

[ "MIT" ]

51

2020-03-05T09:04:21.000Z

2021-12-13T20:34:22.000Z

services/music/test/__init__.py

Ovakefali13/buerro

1476f6e708f95a09a2d73f67ae8aa2cb3bb836af

[ "MIT" ]

null

from .test_service import MusicMockRemote

21

41

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5

42

7.2

1

0

0.095238

42

1

42

0.947368

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null

0

1

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null

0

1

0

1

0

1

0

6

31938a4df6acf3ead90937873988916863b194fd

37

py

Python

src/parsers/__init__.py

iweans/translrt

e96d2cf0e7f0f378b8078a8e2942669ad924af8f

[ "MIT" ]

1

2020-02-25T01:58:34.000Z

src/parsers/__init__.py

iweans/translrt

e96d2cf0e7f0f378b8078a8e2942669ad924af8f

[ "MIT" ]

null

src/parsers/__init__.py

iweans/translrt

e96d2cf0e7f0f378b8078a8e2942669ad924af8f

[ "MIT" ]

null

from .markdown import MarkdownParser

18.5

36

0.864865

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1

37

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1

0

null

0

1

0

1

0

1

0

6

31af52404eb6d6c3cdc11e912028134a7ca5f718

169

py

Python

pyinstalive/__main__.py

pjw91/PyInstaLive

433bf862e2d38f9131772905ceab17343053dc3b

[ "MIT" ]

234

2020-04-08T09:47:42.000Z

2022-03-29T19:12:52.000Z

pyinstalive/__main__.py

pjw91/PyInstaLive

433bf862e2d38f9131772905ceab17343053dc3b

[ "MIT" ]

80

2017-10-08T08:53:09.000Z

2020-03-27T16:54:55.000Z

pyinstalive/__main__.py

pjw91/PyInstaLive

433bf862e2d38f9131772905ceab17343053dc3b

[ "MIT" ]

80

2020-04-08T10:42:25.000Z

2022-03-23T03:54:14.000Z

try: # Python 2 from startup import run except ImportError: # Python 3 from .startup import run def main(): run() if __name__ == '__main__': run()

13

31

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0.278107

169

12

32

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null

1

0

null

0

1

0

1

0

6

31d8a53ae57d8ee48ceb57a8eb7d1d88b90cfc2e

97

py

Python

aegis/data/parser.py

Yijie-Wu/Aegis

f8082b66d55be135a5e2bec7ac15f860f99f7df7

[ "MIT" ]

null

aegis/data/parser.py

Yijie-Wu/Aegis

f8082b66d55be135a5e2bec7ac15f860f99f7df7

[ "MIT" ]

null

aegis/data/parser.py

Yijie-Wu/Aegis

f8082b66d55be135a5e2bec7ac15f860f99f7df7

[ "MIT" ]

null

# -*- encoding:utf-8 -*- """ Author: Yijie.Wu Email: [email protected] Date: 2020/5/14 13:43 """

13.857143

24

0.618557

16

97

3.75

1

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97

6

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0

null

0

null

0

null

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null

1

null

true

0

null

1

0

null

0

1

0

1

0

1

0

null

0

1

0

6

31df6fb33a5dd05fc0d6331443a27721848ec336

20

py

Python

tiotools/__init__.py

twinleaf/tio-python

ce272d0bf3f60d7b97e41b3b7742a094a8db3f26

[ "MIT" ]

9

2017-12-21T16:21:49.000Z

2021-12-02T20:48:03.000Z

tiotools/__init__.py

twinleaf/tio-python

ce272d0bf3f60d7b97e41b3b7742a094a8db3f26

[ "MIT" ]

5

2018-12-14T22:06:08.000Z

2021-09-30T17:33:53.000Z

tiotools/__init__.py

twinleaf/tio-python

ce272d0bf3f60d7b97e41b3b7742a094a8db3f26

[ "MIT" ]

4

2017-12-27T12:46:34.000Z

2020-06-05T17:14:34.000Z

from .itio import *

10

19

0.7

3

20

4.666667

1

0

0.2

20

1

20

0.875

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

9ef267e9db214e8479d8d79aa0625132da08722e

70

py

Python

WeatherPy/api_keys.py

tkabdelaziz/python-api-challenge

f69b70bc59a17e49130a655738d7c675c63b29b4

[ "ADSL" ]

null

WeatherPy/api_keys.py

tkabdelaziz/python-api-challenge

f69b70bc59a17e49130a655738d7c675c63b29b4

[ "ADSL" ]

null

WeatherPy/api_keys.py

tkabdelaziz/python-api-challenge

f69b70bc59a17e49130a655738d7c675c63b29b4

[ "ADSL" ]

null

# OpenWeatherMap API Key api_key = "e6fdf32acc353fd819e7190e6f44d47d"

23.333333

44

0.842857

6

70

9.666667

0.666667

0.206897

0

0.285714

0.1

70

2

45

35

0.634921

0.314286

0

0.695652

0

1

0

false

0

1

0

null

1

0

1

0

1

0

1

null

0

6

73333abc61baea0ed961b2ad582ade9139ffab4a

45

py

Python

image_classification/token_labeling/tlt/models/__init__.py

AK391/UniFormer

22c6b3b98b68236dda6a8fa7152a32af1af62a20

[ "MIT" ]

367

2022-01-14T03:32:25.000Z

2022-03-31T04:48:20.000Z

image_classification/token_labeling/tlt/models/__init__.py

hadlang/UniFormer

e8024703bffb89cb7c7d09e0d774a0d2a9f96c25

[ "MIT" ]

27

2022-01-27T07:12:49.000Z

2022-03-31T04:31:13.000Z

image_classification/token_labeling/tlt/models/__init__.py

hadlang/UniFormer

e8024703bffb89cb7c7d09e0d774a0d2a9f96c25

[ "MIT" ]

53

2022-01-18T11:21:43.000Z

2022-03-31T06:42:41.000Z

from .lvvit import * from .uniformer import *

22.5

24

0.755556

6

45

5.666667

0.666667

0

0.155556

45

2

24

22.5

0.894737

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

73505118824c9e00c59e8a0d453bcc5313ec713c

38

py

Python

examples/ehdemov3/living_room_rgb/user_boot.py

ulno/iot-devkit

6e90c1c207f23c4b5bf374f58d3701550e6c70ca

[ "MIT" ]

null

examples/ehdemov3/living_room_rgb/user_boot.py

ulno/iot-devkit

6e90c1c207f23c4b5bf374f58d3701550e6c70ca

[ "MIT" ]

null

examples/ehdemov3/living_room_rgb/user_boot.py

ulno/iot-devkit

6e90c1c207f23c4b5bf374f58d3701550e6c70ca

[ "MIT" ]

1

2020-07-23T03:03:38.000Z

import rgb_handler rgb_handler.run()

9.5

18

0.815789

6

38

4.833333

0.666667

0.689655

0

0.105263

38

3

19

12.666667

0.852941

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

b40131cc0f7760cd11fcf2ba0595a918a3c845c6

25

py

Python

mercs/core/__init__.py

systemallica/mercs

39e999620ab989abb29310488dcd30354d029490

[ "MIT" ]

11

2020-01-28T16:15:53.000Z

2021-05-20T08:05:42.000Z

mercs/core/__init__.py

systemallica/mercs

39e999620ab989abb29310488dcd30354d029490

[ "MIT" ]

null

mercs/core/__init__.py

systemallica/mercs

39e999620ab989abb29310488dcd30354d029490

[ "MIT" ]

4

2020-02-06T09:02:28.000Z

2022-02-14T09:42:04.000Z

from .Mercs import Mercs

12.5

24

0.8

4

25

5

0.75

0

0.16

25

1

25

0.952381

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

b40a09413f8b62366473c29f262ace0bbb8cfb88

31,345

py

Python

tests/python_venv/test_env_pyenv.py

jmknoble/python-venv

698aff4341c358b0e1469c845398f275a3df1cb8

[ "MIT" ]

1

2021-06-04T15:24:45.000Z

tests/python_venv/test_env_pyenv.py

jmknoble/python-venv

698aff4341c358b0e1469c845398f275a3df1cb8

[ "MIT" ]

6

2021-06-04T15:06:31.000Z

2021-09-24T06:04:45.000Z

tests/python_venv/test_env_pyenv.py

jmknoble/python-venv

698aff4341c358b0e1469c845398f275a3df1cb8

[ "MIT" ]

null

"""Provide unit tests for `~python_venv.env`:py:mod:.""" import os import os.path import random import subprocess import unittest import parameterized # https://pypi.org/project/parameterized/ from python_venv import const, env from python_venv import exceptions as exc from python_venv import reqs from tests.python_venv import contextmgr as ctx from tests.python_venv import flags ######################################## @unittest.skipUnless(flags.should_run_pyenv_tests(), flags.SKIP_PYENV_MESSAGE) class TestEnv_200_PyenvEnvironment(unittest.TestCase): def setUp(self): self.saved_requirements = reqs.REQUIREMENTS def tearDown(self): reqs.REQUIREMENTS = self.saved_requirements def test_PV_ENV_PYNV_000_instantiate_empty(self): with self.assertRaises(TypeError) as raised: env.PyenvEnvironment() msg = raised.exception.args[0] self.assertTrue( msg.startswith("__init__() missing 1 required positional argument") ) @parameterized.parameterized.expand( [ ("dry_run", {"dry_run": True}, "dry_run", True), ("force", {"force": True}, "force", True), ( "message_prefix", {"message_prefix": "dummy_message_prefix"}, "message_prefix", "dummy_message_prefix", ), ("python", {"python": "dummy_python"}, "python", "dummy_python"), ("basename", {"basename": "dummy_basename"}, "_basename", "dummy_basename"), ("env_name", {"env_name": "dummy_env_name"}, "_env_name", "dummy_env_name"), ( "env_prefix", {"env_prefix": "dummy_env_prefix"}, "_env_prefix", "dummy_env_prefix", ), ] ) def test_PV_ENV_PYNV_002_instantiate_kwargs(self, name, kwargs, attr, value): x = env.PyenvEnvironment("dummy_req_scheme", **kwargs) self.assertEqual(getattr(x, attr), value) def test_PV_ENV_PYNV_010_requirements(self): dummy_requirements = {"dummy_req_source": ["dummy_requirement"]} reqs.REQUIREMENTS = {"dummy_req_scheme": [dummy_requirements]} x = env.PyenvEnvironment("dummy_req_scheme") self.assertListEqual(x.requirements.requirements, [dummy_requirements]) def test_PV_ENV_PYNV_020_package_name(self): x = env.PyenvEnvironment("dummy_req_scheme") self.assertEqual(x.package_name, "python_venv") @parameterized.parameterized.expand( [ ("default", None, "python-venv"), ("specified", "dummy-package", "dummy-package"), ] ) def test_PV_ENV_PYNV_030_basename(self, name, basename, expected): kwargs = {} if basename is None else {"basename": basename} x = env.PyenvEnvironment("dummy_req_scheme", **kwargs) self.assertEqual(x.basename, expected) @parameterized.parameterized.expand( [ ("default", reqs.REQ_SCHEME_PLAIN, {}, "python-venv"), ("default_dev", reqs.REQ_SCHEME_DEV, {}, "python-venv-dev"), ("default_devplus", reqs.REQ_SCHEME_DEVPLUS, {}, "python-venv-dev"), ( "default_prefix", reqs.REQ_SCHEME_PLAIN, {"env_prefix": "dummy-prefix-"}, "dummy-prefix-python-venv", ), ( "basename", reqs.REQ_SCHEME_PLAIN, {"basename": "dummy-package"}, "dummy-package", ), ( "basename_dev", reqs.REQ_SCHEME_DEV, {"basename": "dummy-package"}, "dummy-package-dev", ), ( "basename_devplus", reqs.REQ_SCHEME_DEVPLUS, {"basename": "dummy-package"}, "dummy-package-dev", ), ( "basename_prefix", reqs.REQ_SCHEME_PLAIN, {"basename": "dummy-package", "env_prefix": "dummy-prefix-"}, "dummy-prefix-dummy-package", ), ("specified", "dummy_req_scheme", {"env_name": "dummy-env"}, "dummy-env"), ( "specified_prefix", "dummy_req_scheme", {"env_name": "dummy-env", "env_prefix": "dummy-prefix-"}, "dummy-env", ), ] ) def test_PV_ENV_PYNV_040_env_name(self, name, req_scheme, kwargs, expected): x = env.PyenvEnvironment(req_scheme, **kwargs) self.assertEqual(x.env_name, expected) @parameterized.parameterized.expand( [ ("default", "dummy-basename", None, None, "<ENV_DIR>"), ("specified", None, "dummy-env", None, "<ENV_DIR>"), ("with_prefix", "dummy-basename", None, "dummy-prefix", "<ENV_DIR>"), ( "specified_with_prefix", "dummy-basename", "dummy-env", "dummy-prefix", "<ENV_DIR>", ), ] ) def test_PV_ENV_PYNV_050_env_dir_dry_run( self, name, basename, env_name, env_prefix, expected ): kwargs = {} if basename is not None: kwargs["basename"] = basename if env_name is not None: kwargs["env_name"] = env_name if env_prefix is not None: kwargs["env_prefix"] = env_prefix x = env.PyenvEnvironment(reqs.REQ_SCHEME_PLAIN, dry_run=True, **kwargs) self.assertEqual(x.env_dir, expected) @parameterized.parameterized.expand( [ ( "default", "dummy-basename", None, None, os.path.join(os.getcwd(), "<ENV_DIR>"), ), ( "specified", None, "dummy-env", None, os.path.join(os.getcwd(), "<ENV_DIR>"), ), ( "with_prefix", "dummy-basename", None, "dummy-prefix", os.path.join(os.getcwd(), "<ENV_DIR>"), ), ( "specified_with_prefix", "dummy-basename", "dummy-env", "dummy-prefix", os.path.join(os.getcwd(), "<ENV_DIR>"), ), ] ) def test_PV_ENV_PYNV_051_abs_env_dir_dry_run( self, name, basename, env_name, env_prefix, expected ): kwargs = {} if basename is not None: kwargs["basename"] = basename if env_name is not None: kwargs["env_name"] = env_name if env_prefix is not None: kwargs["env_prefix"] = env_prefix x = env.PyenvEnvironment(reqs.REQ_SCHEME_PLAIN, dry_run=True, **kwargs) self.assertEqual(x.abs_env_dir, expected) @parameterized.parameterized.expand( [ ("specified", "dummy-env", "dummy-env"), ] ) def test_PV_ENV_PYNV_060_env_description(self, name, env_name, expected): kwargs = {} if env_name is None else {"env_name": env_name} x = env.PyenvEnvironment("dummy_req_scheme", **kwargs) x.env_description self.assertTrue(x.env_description.endswith(expected)) @parameterized.parameterized.expand( [ ("dry_run_text", {}, "[DRY-RUN]"), ("create_msg", {}, "Creating pyenv environment dummy-package"), ("create_venv", {}, "+ pyenv virtualenv"), ("install_msg", {}, "Installing dummy_req_scheme requirements"), ( "pip_install", {}, "+ <ENV_DIR>/bin/python3 -m pip install -r dummy_requirements.txt", ), ("success", {}, "==> Done."), ] ) def test_PV_ENV_PYNV_100_create_dry_run(self, name, kwargs, expected_text): dummy_requirements = {const.FROM_FILES: ["dummy_requirements.txt"]} reqs.REQUIREMENTS = {"dummy_req_scheme": [dummy_requirements]} x = env.PyenvEnvironment( "dummy_req_scheme", dry_run=True, basename="dummy-package", ignore_preflight_checks=True, **kwargs, ) with ctx.capture(x.create) as ( status, _stdout, stderr, ): self.assertTrue(expected_text in stderr) @parameterized.parameterized.expand( [ ("dry_run_text", "[DRY-RUN]"), ("remove_msg", "Removing pyenv environment dummy-package"), ] ) def test_PV_ENV_PYNV_200_remove_dry_run(self, name, expected_text): x = env.PyenvEnvironment( reqs.REQ_SCHEME_PLAIN, dry_run=True, basename="dummy-package" ) with ctx.capture(x.remove) as (status, _stdout, stderr): self.assertTrue(expected_text in stderr) @parameterized.parameterized.expand( [ ("dry_run_text", "[DRY-RUN]"), ("replace_msg", "Replacing pyenv environment dummy-package"), ("remove_msg", "Removing pyenv environment dummy-package"), ("create_msg", "Creating pyenv environment dummy-package"), ("success", "==> Done."), ] ) def test_PV_ENV_PYNV_300_replace_dry_run(self, name, expected_text): dummy_requirements = {const.FROM_FILES: ["dummy_requirements.txt"]} reqs.REQUIREMENTS = {"dummy_req_scheme": [dummy_requirements]} x = env.PyenvEnvironment( "dummy_req_scheme", dry_run=True, basename="dummy-package", ignore_preflight_checks=True, ) with ctx.capture(x.replace) as (status, _stdout, stderr): self.assertTrue(expected_text in stderr) ######################################## @unittest.skipUnless(flags.should_run_pyenv_tests(), flags.SKIP_PYENV_MESSAGE) class TestEnv_210_PyenvCreate(unittest.TestCase): def setUp(self): self.env_name = None try: self.choices except AttributeError: self.choices = ( [chr(x) for x in range(ord("0"), ord("9") + 1)] + [chr(x) for x in range(ord("A"), ord("Z") + 1)] + [chr(x) for x in range(ord("a"), ord("z") + 1)] ) # Random prefix for environments is required # since pyenv virtualenv doesn't give us a choice # to place an environment somewhere specific. self.env_prefix = "".join(random.choice(self.choices) for x in range(10)) + "-" def tearDown(self): if self.env_name is not None: # remove pyenv virtual environment subprocess.call( ["pyenv", "virtualenv-delete", "-f", self.env_name], stderr=subprocess.DEVNULL, ) self.env_name = None @parameterized.parameterized.expand( [ ("plain_dry_run", reqs.REQ_SCHEME_PLAIN, True, None, None, []), ("plain", reqs.REQ_SCHEME_PLAIN, False, None, None, []), ( "plain_dry_run_env_name", reqs.REQ_SCHEME_PLAIN, True, None, "dummy-env", [], ), ("plain_env_name", reqs.REQ_SCHEME_PLAIN, False, None, "dummy-env", []), ("dev_dry_run", reqs.REQ_SCHEME_DEV, True, None, None, []), ("dev", reqs.REQ_SCHEME_DEV, False, None, None, []), ("devplus_dry_run", reqs.REQ_SCHEME_DEVPLUS, True, None, None, []), ("devplus", reqs.REQ_SCHEME_DEVPLUS, False, None, None, []), ("frozen_dry_run", reqs.REQ_SCHEME_FROZEN, True, None, None, []), ("frozen", reqs.REQ_SCHEME_FROZEN, False, None, None, []), ("source_dry_run", reqs.REQ_SCHEME_SOURCE, True, None, None, []), ("source", reqs.REQ_SCHEME_SOURCE, False, None, None, []), ("wheel_dry_run", reqs.REQ_SCHEME_WHEEL, True, None, None, []), ("wheel", reqs.REQ_SCHEME_WHEEL, False, None, None, []), ("package_dry_run", reqs.REQ_SCHEME_PACKAGE, True, "argcomplete", None, []), ("package", reqs.REQ_SCHEME_PACKAGE, False, "argcomplete", None, []), ("pip_dry_run", reqs.REQ_SCHEME_PIP, True, None, None, ["argcomplete"]), ("pip", reqs.REQ_SCHEME_PIP, False, None, None, ["argcomplete"]), ] ) def test_PV_ENV_PYNV_110_create( self, name, req_scheme, dry_run, basename, env_name, pip_args ): env_prefix = self.env_prefix if env_name: env_name = env_prefix + env_name dirs = [] filespecs = { "requirements.txt": "argcomplete", "requirements_dev.txt": "argcomplete", "requirements_frozen.txt": "argcomplete == 1.12.3", os.path.join("dev", "requirements_build.txt"): "", os.path.join("dev", "requirements_dev.txt"): "", os.path.join("dev", "requirements_test.txt"): "parameterized", } with ctx.project("dummy_package", dirs=dirs, filespecs=filespecs): x = env.PyenvEnvironment( req_scheme, pip_args=pip_args, basename=basename, env_name=env_name, env_prefix=env_prefix, dry_run=dry_run, force=True, ) self.env_name = x.env_name if not flags.should_suppress_output(): x.create() else: original_stderr = None with ctx.capture_to_file(x.create) as ( _status, _stdout, stderr, ): original_stderr = stderr testable_stderr = original_stderr.lower() if "error" in testable_stderr: print(original_stderr, file=stderr) self.assertNotIn("error", testable_stderr) @parameterized.parameterized.expand( [ ("plain_dry_run", reqs.REQ_SCHEME_PLAIN, True, None, None), ("plain", reqs.REQ_SCHEME_PLAIN, False, None, None), ("dev_dry_run", reqs.REQ_SCHEME_DEV, True, None, None), ("dev", reqs.REQ_SCHEME_DEV, False, None, None), ("devplus_dry_run", reqs.REQ_SCHEME_DEVPLUS, True, None, None), ("devplus", reqs.REQ_SCHEME_DEVPLUS, False, None, None), ("frozen_dry_run", reqs.REQ_SCHEME_FROZEN, True, None, None), ("frozen", reqs.REQ_SCHEME_FROZEN, False, None, None), ] ) def test_PV_ENV_PYNV_120_create_missing_reqs( self, name, req_scheme, dry_run, basename, env_name ): env_prefix = self.env_prefix if env_name: env_name = env_prefix + env_name dirs = [] with ctx.project("dummy_package", dirs=dirs): x = env.PyenvEnvironment( req_scheme, basename=basename, env_name=env_name, env_prefix=env_prefix, dry_run=dry_run, force=True, ) self.env_name = x.env_name with self.assertRaises(exc.MissingRequirementsError): if not flags.should_suppress_output(): x.create() else: with ctx.capture_to_file(x.create) as ( _status, _stdout, _stderr, ): pass @parameterized.parameterized.expand( [ ("plain_dry_run", reqs.REQ_SCHEME_PLAIN, True, None, True), ("plain", reqs.REQ_SCHEME_PLAIN, False, None, True), ( "plain_dry_run_env_name", reqs.REQ_SCHEME_PLAIN, True, "dummy-env", True, ), ("plain_env_name", reqs.REQ_SCHEME_PLAIN, False, "dummy-env", True), ] ) def test_PV_ENV_PYNV_130_create_duplicate( self, name, req_scheme, dry_run, env_name, should_raise ): env_prefix = self.env_prefix if env_name: env_name = env_prefix + env_name dirs = [] filespecs = { "requirements.txt": "argcomplete", "requirements_dev.txt": "argcomplete", "requirements_frozen.txt": "argcomplete == 1.12.3", os.path.join("dev", "requirements_build.txt"): "", os.path.join("dev", "requirements_dev.txt"): "", os.path.join("dev", "requirements_test.txt"): "parameterized", } with ctx.project("dummy_package", dirs=dirs, filespecs=filespecs): x = env.PyenvEnvironment( req_scheme, env_name=env_name, env_prefix=env_prefix, dry_run=False, force=True, ) self.env_name = x.env_name if not flags.should_suppress_output(): x.create() else: with ctx.capture_to_file(x.create) as (_status, _stdout, _stderr): pass x = env.PyenvEnvironment( req_scheme, env_name=env_name, env_prefix=env_prefix, dry_run=dry_run, force=True, ) if should_raise: with self.assertRaises(exc.EnvExistsError): if not flags.should_suppress_output(): x.create() else: with ctx.capture_to_file(x.create) as ( _status, _stdout, _stderr, ): pass else: if not flags.should_suppress_output(): x.create() else: original_stderr = None with ctx.capture_to_file(x.create) as (_status, _stdout, stderr): original_stderr = stderr testable_stderr = original_stderr.lower() if "error" in testable_stderr: print(original_stderr, file=stderr) self.assertNotIn("error", testable_stderr) ######################################## @unittest.skipUnless(flags.should_run_pyenv_tests(), flags.SKIP_PYENV_MESSAGE) class TestEnv_220_PyenvRemove(unittest.TestCase): def setUp(self): self.env_name = None try: self.choices except AttributeError: self.choices = ( [chr(x) for x in range(ord("0"), ord("9") + 1)] + [chr(x) for x in range(ord("A"), ord("Z") + 1)] + [chr(x) for x in range(ord("a"), ord("z") + 1)] ) # Random prefix for environments is required # since pyenv virtualenv doesn't give us a choice # to place an environment somewhere specific. self.env_prefix = "".join(random.choice(self.choices) for x in range(10)) + "-" def tearDown(self): if self.env_name is not None: # remove pyenv virtual environment subprocess.call( ["pyenv", "virtualenv-delete", "-f", self.env_name], stderr=subprocess.DEVNULL, ) self.env_name = None @parameterized.parameterized.expand( [ ("plain_dry_run", reqs.REQ_SCHEME_PLAIN, True, None, None, []), ("plain", reqs.REQ_SCHEME_PLAIN, False, None, None, []), ( "plain_dry_run_env_name", reqs.REQ_SCHEME_PLAIN, True, None, "dummy-env", [], ), ("plain_env_name", reqs.REQ_SCHEME_PLAIN, False, None, "dummy-env", []), ("dev_dry_run", reqs.REQ_SCHEME_DEV, True, None, None, []), ("dev", reqs.REQ_SCHEME_DEV, False, None, None, []), ("devplus_dry_run", reqs.REQ_SCHEME_DEVPLUS, True, None, None, []), ("devplus", reqs.REQ_SCHEME_DEVPLUS, False, None, None, []), ("frozen_dry_run", reqs.REQ_SCHEME_FROZEN, True, None, None, []), ("frozen", reqs.REQ_SCHEME_FROZEN, False, None, None, []), ("source_dry_run", reqs.REQ_SCHEME_SOURCE, True, None, None, []), ("source", reqs.REQ_SCHEME_SOURCE, False, None, None, []), ("wheel_dry_run", reqs.REQ_SCHEME_WHEEL, True, None, None, []), ("wheel", reqs.REQ_SCHEME_WHEEL, False, None, None, []), ("package_dry_run", reqs.REQ_SCHEME_PACKAGE, True, "argcomplete", None, []), ("package", reqs.REQ_SCHEME_PACKAGE, False, "argcomplete", None, []), ("pip_dry_run", reqs.REQ_SCHEME_PIP, True, None, None, ["argcomplete"]), ("pip", reqs.REQ_SCHEME_PIP, False, None, None, ["argcomplete"]), ] ) def test_PV_ENV_PYNV_210_remove( self, name, req_scheme, dry_run, basename, env_name, pip_args ): env_prefix = self.env_prefix if env_name: env_name = env_prefix + env_name dirs = [] filespecs = { "requirements.txt": "argcomplete", "requirements_dev.txt": "argcomplete", "requirements_frozen.txt": "argcomplete == 1.12.3", os.path.join("dev", "requirements_build.txt"): "", os.path.join("dev", "requirements_dev.txt"): "", os.path.join("dev", "requirements_test.txt"): "parameterized", } with ctx.project("dummy_package", dirs=dirs, filespecs=filespecs): x = env.PyenvEnvironment( req_scheme, pip_args=pip_args, basename=basename, env_name=env_name, env_prefix=env_prefix, dry_run=dry_run, force=True, ) y = env.PyenvEnvironment( req_scheme, pip_args=pip_args, basename=basename, env_name=env_name, env_prefix=env_prefix, dry_run=False, force=True, ) self.env_name = y.env_name if not flags.should_suppress_output(): x.remove() # remove non-existent y.create() x.remove() # remove existing else: original_stderrs = [] with ctx.capture_to_file(x.remove) as (_status, _stdout, stderr): original_stderrs.append(stderr) with ctx.capture_to_file(y.create) as (_status, _stdout, stderr): original_stderrs.append(stderr) with ctx.capture_to_file(x.remove) as (_status, _stdout, stderr): original_stderrs.append(stderr) testable_stderrs = [text.lower() for text in original_stderrs] for (i, text) in enumerate(testable_stderrs): if "error" in text: print(original_stderrs[i], file=stderr) self.assertNotIn("error", text) ######################################## @unittest.skipUnless(flags.should_run_pyenv_tests(), flags.SKIP_PYENV_MESSAGE) class TestEnv_230_PyenvReplace(unittest.TestCase): def setUp(self): self.env_name = None try: self.choices except AttributeError: self.choices = ( [chr(x) for x in range(ord("0"), ord("9") + 1)] + [chr(x) for x in range(ord("A"), ord("Z") + 1)] + [chr(x) for x in range(ord("a"), ord("z") + 1)] ) # Random prefix for environments is required # since pyenv virtualenv doesn't give us a choice # to place an environment somewhere specific. self.env_prefix = "".join(random.choice(self.choices) for x in range(10)) + "-" def tearDown(self): if self.env_name is not None: # remove pyenv virtual environment subprocess.call( ["pyenv", "virtualenv-delete", "-f", self.env_name], stderr=subprocess.DEVNULL, ) self.env_name = None @parameterized.parameterized.expand( [ ("plain_dry_run", reqs.REQ_SCHEME_PLAIN, True, None, None, []), ("plain", reqs.REQ_SCHEME_PLAIN, False, None, None, []), ( "plain_dry_run_env_name", reqs.REQ_SCHEME_PLAIN, True, None, "dummy-env", [], ), ("plain_env_name", reqs.REQ_SCHEME_PLAIN, False, None, "dummy-env", []), ("dev_dry_run", reqs.REQ_SCHEME_DEV, True, None, None, []), ("dev", reqs.REQ_SCHEME_DEV, False, None, None, []), ("devplus_dry_run", reqs.REQ_SCHEME_DEVPLUS, True, None, None, []), ("devplus", reqs.REQ_SCHEME_DEVPLUS, False, None, None, []), ("frozen_dry_run", reqs.REQ_SCHEME_FROZEN, True, None, None, []), ("frozen", reqs.REQ_SCHEME_FROZEN, False, None, None, []), ("source_dry_run", reqs.REQ_SCHEME_SOURCE, True, None, None, []), ("source", reqs.REQ_SCHEME_SOURCE, False, None, None, []), ("wheel_dry_run", reqs.REQ_SCHEME_WHEEL, True, None, None, []), ("wheel", reqs.REQ_SCHEME_WHEEL, False, None, None, []), ("package_dry_run", reqs.REQ_SCHEME_PACKAGE, True, "argcomplete", None, []), ("package", reqs.REQ_SCHEME_PACKAGE, False, "argcomplete", None, []), ("pip_dry_run", reqs.REQ_SCHEME_PIP, True, None, None, ["argcomplete"]), ("pip", reqs.REQ_SCHEME_PIP, False, None, None, ["argcomplete"]), ] ) def test_PV_ENV_PYNV_310_replace_nonexistent( self, name, req_scheme, dry_run, basename, env_name, pip_args ): env_prefix = self.env_prefix if env_name: env_name = env_prefix + env_name dirs = [] filespecs = { "requirements.txt": "argcomplete", "requirements_dev.txt": "argcomplete", "requirements_frozen.txt": "argcomplete == 1.12.3", os.path.join("dev", "requirements_build.txt"): "", os.path.join("dev", "requirements_dev.txt"): "", os.path.join("dev", "requirements_test.txt"): "parameterized", } with ctx.project("dummy_package", dirs=dirs, filespecs=filespecs): x = env.PyenvEnvironment( req_scheme, pip_args=pip_args, basename=basename, env_name=env_name, env_prefix=env_prefix, dry_run=dry_run, force=True, ) self.env_name = x.env_name if not flags.should_suppress_output(): x.replace() else: original_stderrs = [] with ctx.capture_to_file(x.replace) as (_status, _stdout, stderr): original_stderrs.append(stderr) testable_stderrs = [text.lower() for text in original_stderrs] for (i, text) in enumerate(testable_stderrs): if "error" in text: print(original_stderrs[i], file=stderr) self.assertNotIn("error", text) @parameterized.parameterized.expand( [ ("plain_dry_run", reqs.REQ_SCHEME_PLAIN, True, None, None, []), ("plain", reqs.REQ_SCHEME_PLAIN, False, None, None, []), ( "plain_dry_run_env_name", reqs.REQ_SCHEME_PLAIN, True, None, "dummy-env", [], ), ("plain_env_name", reqs.REQ_SCHEME_PLAIN, False, None, "dummy-env", []), ("dev_dry_run", reqs.REQ_SCHEME_DEV, True, None, None, []), ("dev", reqs.REQ_SCHEME_DEV, False, None, None, []), ("devplus_dry_run", reqs.REQ_SCHEME_DEVPLUS, True, None, None, []), ("devplus", reqs.REQ_SCHEME_DEVPLUS, False, None, None, []), ("frozen_dry_run", reqs.REQ_SCHEME_FROZEN, True, None, None, []), ("frozen", reqs.REQ_SCHEME_FROZEN, False, None, None, []), ("source_dry_run", reqs.REQ_SCHEME_SOURCE, True, None, None, []), ("source", reqs.REQ_SCHEME_SOURCE, False, None, None, []), ("wheel_dry_run", reqs.REQ_SCHEME_WHEEL, True, None, None, []), ("wheel", reqs.REQ_SCHEME_WHEEL, False, None, None, []), ("package_dry_run", reqs.REQ_SCHEME_PACKAGE, True, "argcomplete", None, []), ("package", reqs.REQ_SCHEME_PACKAGE, False, "argcomplete", None, []), ("pip_dry_run", reqs.REQ_SCHEME_PIP, True, None, None, ["argcomplete"]), ("pip", reqs.REQ_SCHEME_PIP, False, None, None, ["argcomplete"]), ] ) def test_PV_ENV_PYNV_320_replace_existing( self, name, req_scheme, dry_run, basename, env_name, pip_args ): env_prefix = self.env_prefix if env_name: env_name = env_prefix + env_name dirs = [] filespecs = { "requirements.txt": "argcomplete", "requirements_dev.txt": "argcomplete", "requirements_frozen.txt": "argcomplete == 1.12.3", os.path.join("dev", "requirements_build.txt"): "", os.path.join("dev", "requirements_dev.txt"): "", os.path.join("dev", "requirements_test.txt"): "parameterized", } with ctx.project("dummy_package", dirs=dirs, filespecs=filespecs): x = env.PyenvEnvironment( req_scheme, pip_args=pip_args, basename=basename, env_name=env_name, env_prefix=env_prefix, dry_run=dry_run, force=True, ) y = env.PyenvEnvironment( req_scheme, pip_args=pip_args, basename=basename, env_name=env_name, env_prefix=env_prefix, dry_run=False, force=True, ) self.env_name = y.env_name if not flags.should_suppress_output(): y.create() x.replace() else: original_stderrs = [] with ctx.capture_to_file(y.create) as (_status, _stdout, stderr): original_stderrs.append(stderr) with ctx.capture_to_file(x.replace) as (_status, _stdout, stderr): original_stderrs.append(stderr) testable_stderrs = [text.lower() for text in original_stderrs] for (i, text) in enumerate(testable_stderrs): if "error" in text: print(original_stderrs[i], file=stderr) self.assertNotIn("error", text)

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0

1

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null

0

6

b41a0470134fb1e8ea681d8bc3db3889104e143a

12,319

py

Python

tests/test_radials.py

rucool/HFRadarPy

4b81d21da2f7c732e5377689df7bb328bfb37e37

[ "MIT" ]

1

2022-03-15T13:58:00.000Z

tests/test_radials.py

rucool/HFRadarPy

4b81d21da2f7c732e5377689df7bb328bfb37e37

[ "MIT" ]

1

2021-12-03T00:36:41.000Z

tests/test_radials.py

rucool/HFRadarPy

4b81d21da2f7c732e5377689df7bb328bfb37e37

[ "MIT" ]

2

2020-11-17T17:06:34.000Z

2022-03-04T01:26:58.000Z

import unittest from pathlib import Path import numpy as np import xarray as xr from hfradarpy.radials import Radial from hfradarpy.radials import concat as concatenate_radials data_path = (Path(__file__).parent.with_name('examples') / 'data').resolve() output_path = (Path(__file__).parent.with_name('examples') / 'output').resolve() def test_codar_radial_to_tabular_netcdf(): radial_file = data_path / 'radials' / 'ruv' / 'SEAB' / 'RDLi_SEAB_2019_01_01_0000.ruv' nc_file = output_path / 'radials' / 'nc' / 'tabular' / 'SEAB' / 'RDLi_SEAB_2019_01_01_0000.nc' # Converts the underlying .data (natively a pandas DataFrame) # to an xarray object when `create_netcdf` is called. # This automatically 'enhances' the netCDF file # with better variable names and attributes. rad1 = Radial(radial_file) rad1.export(str(nc_file), file_type='netcdf-tabular') # Convert it to an xarray Dataset with no variable # or attribte enhancements xds2 = rad1.to_xarray_tabular(enhance=False) # Convert it to xarray Dataset with increased usability # by changing variables names, adding attributes, # and decoding the CF standards like scale_factor xds3 = rad1.to_xarray_tabular(enhance=True) with xr.open_dataset(nc_file) as xds1: # The two enhanced files should be identical assert xds1.identical(xds3) # Enhanced and non-enhanced files should not # be equal assert not xds1.identical(xds2) def test_codar_radial_to_multidimensional_netcdf(): radial_file = data_path / 'radials' / 'ruv' / 'SEAB' / 'RDLi_SEAB_2019_01_01_0000.ruv' nc_file = output_path / 'radials' / 'nc' / 'multidimensional' / 'SEAB' / 'RDLi_SEAB_2019_01_01_0000.nc' # Converts the underlying .data (natively a pandas DataFrame) # to an xarray object when `create_netcdf` is called. # This automatically 'enhances' the netCDF file # with better variable names and attributes. rad1 = Radial(radial_file) rad1.export(str(nc_file), file_type='netcdf-multidimensional') # Convert it to an xarray Dataset with no variable # or attribte enhancements xds2 = rad1.to_xarray_multidimensional(enhance=False) # Convert it to xarray Dataset with increased usability # by changing variables names, adding attributes, # and decoding the CF standards like scale_factor xds3 = rad1.to_xarray_multidimensional(enhance=True) with xr.open_dataset(nc_file) as xds1: # The two enhanced files should be identical assert xds1.identical(xds3) # Enhanced and non-enhanced files should not # be equal assert not xds1.identical(xds2) def test_wera_radial_to_tabular_netcdf(): radial_file = data_path / 'radials' / 'ruv' / 'WERA' / 'RDL_csw_2019_10_24_162300.ruv' nc_file = output_path / 'radials' / 'nc' / 'tabular' / 'WERA' / 'RDL_csw_2019_10_24_162300.nc' # Converts the underlying .data (natively a pandas DataFrame) # to an xarray object when `create_netcdf` is called. # This automatically 'enhances' the netCDF file # with better variable names and attributes. rad1 = Radial(radial_file) rad1.export(str(nc_file), file_type='netcdf-tabular') # Convert it to an xarray Dataset with no variable # or attribte enhancements xds2 = rad1.to_xarray_tabular(enhance=False) # Convert it to xarray Dataset with increased usability # by changing variables names, adding attributes, # and decoding the CF standards like scale_factor xds3 = rad1.to_xarray_tabular(enhance=True) with xr.open_dataset(nc_file) as xds1: # The two enhanced files should be identical assert xds1.identical(xds3) # Enhanced and non-enhanced files should not # be equal assert not xds1.identical(xds2) def test_wera_radial_to_multidimensional_netcdf(): radial_file = data_path / 'radials' / 'ruv' / 'WERA' / 'RDL_csw_2019_10_24_162300.ruv' nc_file = output_path / 'radials' / 'nc' / 'multidimensional' / 'WERA' / 'RDL_csw_2019_10_24_162300.nc' # Converts the underlying .data (natively a pandas DataFrame) # to an xarray object when `create_netcdf` is called. # This automatically 'enhances' the netCDF file # with better variable names and attributes. rad1 = Radial(radial_file) rad1.export(str(nc_file), file_type='netcdf-multidimensional') # Convert it to an xarray Dataset with no variable # or attribte enhancements xds2 = rad1.to_xarray_multidimensional(enhance=False) # Convert it to xarray Dataset with increased usability # by changing variables names, adding attributes, # and decoding the CF standards like scale_factor xds3 = rad1.to_xarray_multidimensional(enhance=True) with xr.open_dataset(nc_file) as xds1: # The two enhanced files should be identical assert xds1.identical(xds3) # Enhanced and non-enhanced files should not # be equal assert not xds1.identical(xds2) def test_wera_mask(): radial_file = data_path / 'radials' / 'ruv' / 'WERA' / 'RDL_csw_2019_10_24_162300.ruv' rad1 = Radial(radial_file, mask_over_land=False, replace_invalid=False) # Total points before masking assert len(rad1.data) == 6327 rad1.mask_over_land() # Make sure we subset the land points assert len(rad1.data) == 5745 def test_wera_qc(): radial_file = data_path / 'radials' / 'ruv' / 'WERA' / 'RDL_csw_2019_10_24_162300.ruv' rad1 = Radial(radial_file, mask_over_land=False, replace_invalid=False) rad1.initialize_qc() assert len(rad1.data) == 6327 rad1.mask_over_land() rad1.qc_qartod_radial_count() rad1.qc_qartod_valid_location() rad1.qc_qartod_maximum_velocity() rad1.qc_qartod_spatial_median() rad1.qc_qartod_avg_radial_bearing(reference_bearing=180) rad1.qc_qartod_primary_flag() assert len(rad1.data) == 5745 assert 'QC07' in rad1.data assert 'QC08' not in rad1.data # no VFLG column so we can't run it assert 'QC09' in rad1.data assert 'QC10' in rad1.data # assert 'QC11' in rad1.data # temporal gradient test assert 'QC12' in rad1.data assert 'PRIM' in rad1.data def test_wera_raw_to_quality_multidimensional_nc(): radial_file = data_path / 'radials' / 'ruv' / 'WERA' / 'RDL_csw_2019_10_24_162300.ruv' nc_file = output_path / 'radials' / 'qc' / 'nc' / 'multidimensional' / 'WERA' / 'RDL_csw_2019_10_24_162300.nc' rad1 = Radial(radial_file, mask_over_land=False, replace_invalid=False) rad1.initialize_qc() rad1.mask_over_land() rad1.qc_qartod_radial_count() rad1.qc_qartod_valid_location() rad1.qc_qartod_maximum_velocity() rad1.qc_qartod_spatial_median() rad1.export(str(nc_file), file_type='netcdf-multidimensional') xds2 = rad1.to_xarray_multidimensional(enhance=True) with xr.open_dataset(nc_file) as xds1: assert len(xds1.QCTest) == 3 # no VFLG column so one test not run # The two enhanced files should be identical assert xds1.identical(xds2) def test_wera_raw_to_quality_tabular_nc(): radial_file = data_path / 'radials' / 'ruv' / 'WERA' / 'RDL_csw_2019_10_24_162300.ruv' nc_file = output_path / 'radials' / 'qc' / 'nc' / 'tabular' / 'WERA' / 'RDL_csw_2019_10_24_162300.nc' rad1 = Radial(radial_file, mask_over_land=False, replace_invalid=False) rad1.initialize_qc() rad1.mask_over_land() rad1.qc_qartod_radial_count() rad1.qc_qartod_valid_location() rad1.qc_qartod_maximum_velocity() rad1.qc_qartod_spatial_median() rad1.export(str(nc_file), file_type='netcdf-tabular') xds2 = rad1.to_xarray_tabular(enhance=True) with xr.open_dataset(nc_file) as xds1: assert len(xds1.QCTest) == 3 # no VFLG column so one test not run # The two enhanced files should be identical assert xds1.identical(xds2) def test_miami_radial_multidimensional_nc(): radial_file = data_path / 'radials' / 'ruv' / 'WERA' / 'RDL_UMiami_STF_2019_06_01_0000.hfrweralluv1.0' nc_file = output_path / 'radials' / 'nc' / 'multidimensional' / 'WERA' / 'RDL_UMiami_STF_2019_06_01_0000.nc' # Converts the underlying .data (natively a pandas DataFrame) # to an xarray object when `create_netcdf` is called. # This automatically 'enhances' the netCDF file # with better variable names and attributes. rad1 = Radial(radial_file) rad1.export(str(nc_file), file_type='netcdf-multidimensional') # Convert it to an xarray Dataset with no variable # or attribte enhancements xds2 = rad1.to_xarray_multidimensional(enhance=False) # Convert it to xarray Dataset with increased usability # by changing variables names, adding attributes, # and decoding the CF standards like scale_factor xds3 = rad1.to_xarray_multidimensional(enhance=True) with xr.open_dataset(nc_file) as xds1: # The two enhanced files should be identical assert xds1.identical(xds3) # Enhanced and non-enhanced files should not # be equal assert not xds1.identical(xds2) def test_miami_radial_tabular_nc(): radial_file = data_path / 'radials' / 'ruv' / 'WERA' / 'RDL_UMiami_STF_2019_06_01_0000.hfrweralluv1.0' nc_file = output_path / 'radials' / 'nc' / 'tabular' / 'WERA' / 'RDL_UMiami_STF_2019_06_01_0000.nc' # Converts the underlying .data (natively a pandas DataFrame) # to an xarray object when `create_netcdf` is called. # This automatically 'enhances' the netCDF file # with better variable names and attributes. rad1 = Radial(radial_file) rad1.export(str(nc_file), file_type='netcdf-tabular') # Convert it to an xarray Dataset with no variable # or attribte enhancements xds2 = rad1.to_xarray_tabular(enhance=False) # Convert it to xarray Dataset with increased usability # by changing variables names, adding attributes, # and decoding the CF standards like scale_factor xds3 = rad1.to_xarray_tabular(enhance=True) with xr.open_dataset(nc_file) as xds1: # The two enhanced files should be identical assert xds1.identical(xds3) # Enhanced and non-enhanced files should not # be equal assert not xds1.identical(xds2) class TestCombineRadials(unittest.TestCase): def setUp(self): self.file_paths = list( (data_path / 'radials' / 'ruv' / 'SEAB').glob('*.ruv') ) self.radial_files = [ str(r) for r in self.file_paths ] self.radial_objects = [ Radial(str(r)) for r in self.radial_files ] # Select even indexed file_paths and odd indexed radial objects # into one array of mixed content types for concating self.radial_mixed = self.radial_files[::2] + self.radial_objects[1:][::2] def test_concat_radial_objects(self): combined = concatenate_radials(self.radial_objects) assert combined.time.size == len(self.file_paths) # Make sure the dataset was sorted by time assert np.array_equal( combined.time.values, np.sort(combined.time.values) ) def test_concat_radial_files(self): combined = concatenate_radials(self.radial_files) assert combined.time.size == len(self.file_paths) # Make sure the dataset was sorted by time assert np.array_equal( combined.time.values, np.sort(combined.time.values) ) def test_concat_mixed_radials(self): combined = concatenate_radials(self.radial_mixed) assert combined.time.size == len(self.file_paths) # Make sure the dataset was sorted by time assert np.array_equal( combined.time.values, np.sort(combined.time.values) ) def test_concat_mixed_radials_enhance(self): # Select even indexed file_paths and odd indexed radial objects # into one array of mixed content types for concating combined = concatenate_radials(self.radial_mixed, enhance=True) assert combined.time.size == len(self.file_paths) # Make sure the dataset was sorted by time assert np.array_equal( combined.time.values, np.sort(combined.time.values) )

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null

0

1

0

null

0

6

b41a6fb1230ffb4cb7b7dd42943c11f7da6ced76

141

py

Python

scippycrm/organisations/__init__.py

realScipio/scippycrm

f267b82f07e2784e97089b0b9a35024d58fd4a60

[ "MIT" ]

14

2018-07-12T19:08:28.000Z

2021-10-16T23:46:10.000Z

scippycrm/organisations/__init__.py

Zenahr/scippycrm

f267b82f07e2784e97089b0b9a35024d58fd4a60

[ "MIT" ]

1

2020-02-12T00:41:34.000Z

scippycrm/organisations/__init__.py

Zenahr/scippycrm

f267b82f07e2784e97089b0b9a35024d58fd4a60

[ "MIT" ]

5

2020-01-08T18:26:47.000Z

2022-03-10T06:51:07.000Z

from flask import Blueprint organisations_blueprint = Blueprint('organisations', __name__, template_folder='templates') from . import routes

35.25

91

0.829787

15

141

7.4

0.666667

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0

0.092199

141

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92

35.25

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0

1

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false

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0

6

b42c1a79c337482386b3d089c413a5fc4a4a523e

4,092

py

Python

tests/safe/test_config_parser.py

ddiss/rtslib

6fd0bbfc20947143eb2e4c3bfd34c65bf8551468

[ "Apache-2.0" ]

21

2015-04-02T21:44:26.000Z

2020-03-30T12:43:02.000Z

tests/safe/test_config_parser.py

ddiss/rtslib

6fd0bbfc20947143eb2e4c3bfd34c65bf8551468

[ "Apache-2.0" ]

17

2015-06-23T09:04:00.000Z

2020-01-04T19:31:34.000Z

tests/safe/test_config_parser.py

ddiss/rtslib

6fd0bbfc20947143eb2e4c3bfd34c65bf8551468

[ "Apache-2.0" ]

18

2015-06-18T14:29:43.000Z

2021-03-25T19:51:18.000Z

import sys, pprint, logging, unittest, cPickle from rtslib import config_parser # TODO Add PolicyParser tests logging.basicConfig() log = logging.getLogger('TestConfigParser') log.setLevel(logging.INFO) class TestConfigParser(unittest.TestCase): parser = config_parser.ConfigParser() samples_dir = '../data' def test_one_line(self): print log.info(self._testMethodName) config = "%s/config_one_line.lio" % self.samples_dir parse_tree = self.parser.parse_file(config) for statement in parse_tree: log.debug(pprint.pformat(statement)) # with open("%s.ast" % config[:-4], 'w') as f: # cPickle.dump(parse_tree, f) with open("%s.ast" % config[:-4], 'r') as f: expected_tree = cPickle.load(f) self.failUnless(parse_tree == expected_tree) def test_basic(self): print log.info(self._testMethodName) config = "%s/config_basic.lio" % self.samples_dir parse_tree = self.parser.parse_file(config) for statement in parse_tree: log.debug(pprint.pformat(statement)) # with open("%s.ast" % config[:-4], 'w') as f: # cPickle.dump(parse_tree, f) with open("%s.ast" % config[:-4], 'r') as f: expected_tree = cPickle.load(f) self.failUnless(parse_tree == expected_tree) def test_attribute_group(self): print log.info(self._testMethodName) config = "%s/config_attribute_group.lio" % self.samples_dir parse_tree = self.parser.parse_file(config) for statement in parse_tree: log.debug(pprint.pformat(statement)) # with open("%s.ast" % config[:-4], 'w') as f: # cPickle.dump(parse_tree, f) with open("%s.ast" % config[:-4], 'r') as f: expected_tree = cPickle.load(f) self.failUnless(parse_tree == expected_tree) def test_nested_blocks(self): print log.info(self._testMethodName) config = "%s/config_nested_blocks.lio" % self.samples_dir parse_tree = self.parser.parse_file(config) for statement in parse_tree: log.debug(pprint.pformat(statement)) # with open("%s.ast" % config[:-4], 'w') as f: # cPickle.dump(parse_tree, f) with open("%s.ast" % config[:-4], 'r') as f: expected_tree = cPickle.load(f) self.failUnless(parse_tree == expected_tree) def test_comments(self): print log.info(self._testMethodName) config = "%s/config_comments.lio" % self.samples_dir parse_tree = self.parser.parse_file(config) for statement in parse_tree: log.debug(pprint.pformat(statement)) # with open("%s.ast" % config[:-4], 'w') as f: # cPickle.dump(parse_tree, f) with open("%s.ast" % config[:-4], 'r') as f: expected_tree = cPickle.load(f) self.failUnless(parse_tree == expected_tree) def test_strings(self): print log.info(self._testMethodName) config = "%s/config_strings.lio" % self.samples_dir parse_tree = self.parser.parse_file(config) for statement in parse_tree: log.debug(pprint.pformat(statement)) # with open("%s.ast" % config[:-4], 'w') as f: # cPickle.dump(parse_tree, f) with open("%s.ast" % config[:-4], 'r') as f: expected_tree = cPickle.load(f) self.failUnless(parse_tree == expected_tree) def test_complete(self): print log.info(self._testMethodName) config = "%s/config_complete.lio" % self.samples_dir parse_tree = self.parser.parse_file(config) for statement in parse_tree: log.debug(pprint.pformat(statement)) # with open("%s.ast" % config[:-4], 'w') as f: # cPickle.dump(parse_tree, f) with open("%s.ast" % config[:-4], 'r') as f: expected_tree = cPickle.load(f) self.failUnless(parse_tree == expected_tree) if __name__ == '__main__': unittest.main()

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null

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6

b42e18509f9f253682f3bbecf10ca37a07186740

305

py

Python

bdd/scenarios.py

tinytoon1/python

cc320fddea962fec97eb928e2c4ebbd5bad3ed43

[ "Apache-2.0" ]

null

bdd/scenarios.py

tinytoon1/python

cc320fddea962fec97eb928e2c4ebbd5bad3ed43

[ "Apache-2.0" ]

null

bdd/scenarios.py

tinytoon1/python

cc320fddea962fec97eb928e2c4ebbd5bad3ed43

[ "Apache-2.0" ]

null

from pytest_bdd import scenario from .steps import * @scenario('contacts.feature', 'add contact') def test_add_contact(): pass @scenario('contacts.feature', 'delete contact') def test_delete_contact(): pass @scenario('contacts.feature', 'update contact') def test_update_contact(): pass

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6

b43b67cd4b5c3ec1adf9c36f8678e32bf2e82120

1,527

py

Python

DBmanagement_scripts/cleancsv2019.py

cemac/SWIFTDB

5c6bc0ae4ff674c2eede44783ca1738630d97ebb

[ "MIT" ]

2

2020-07-14T14:14:45.000Z

2021-05-13T13:01:51.000Z

DBmanagement_scripts/cleancsv2019.py

cemac-tech/SWIFTDB

5c6bc0ae4ff674c2eede44783ca1738630d97ebb

[ "MIT" ]

18

2019-02-07T10:28:19.000Z

2020-06-18T18:31:41.000Z

DBmanagement_scripts/cleancsv2019.py

cemac-tech/SWIFTDB

5c6bc0ae4ff674c2eede44783ca1738630d97ebb

[ "MIT" ]

1

2019-03-25T14:54:26.000Z

''' A script to take tab deliminated dump Lorraines excel work sheets and tidy them up for postgres storage. **Inprogess** Known issues Encoding with excel, python defaults to utf-8 excel uses something else, current fix is to resave the file in atom! Generalise: Pass in file name and extract header names rather than hard code ''' import pandas as pd import re file_name = 'deliverables.tab' # Read in tab deliminated file df = pd.read_csv(file_name, sep='\t') # percents are Integer df.percent = df.percent.fillna(0).astype(int) # theres some trailing white spaces df.partner = df.partner.str.strip() # Partners need to match existing keys # make everything upper case df.partner = df.partner.apply(lambda x: x.upper()) up = ['UOL', 'UOR', 'GMET', 'NIMET', 'UON'] mixp = ['UoL', 'UoR', 'GMet', 'NiMet', 'UoN'] for i, p in enumerate(up): df.partner = df.partner.replace(p, mixp[i]) df.to_csv(file_name, sep='\t', index=False, header=False) file_name = 'tasks.tab' # Read in tab deliminated file df = pd.read_csv(file_name, sep='\t') # percents are Integer df.percent = df.percent.fillna(0).astype(int) # theres some trailing white spaces df.partner = df.partner.str.strip() # Partners need to match existing keys # make everything upper case df.partner = df.partner.apply(lambda x: x.upper()) up = ['UOL', 'UOR', 'GMET', 'NIMET', 'UON'] mixp = ['UoL', 'UoR', 'GMet', 'NiMet', 'UoN'] for i, p in enumerate(up): df.partner = df.partner.replace(p, mixp[i]) df.to_csv(file_name, sep='\t', index=False, header=False)

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null

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1

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1

0

null

0

6

b44749f0c586def93090ab449574879aea07b2ee

229

py

Python

src/python/WMCore/WMBS/Oracle/Workflow/InsertOutput.py

khurtado/WMCore

f74e252412e49189a92962945a94f93bec81cd1e

[ "Apache-2.0" ]

21

2015-11-19T16:18:45.000Z

2021-12-02T18:20:39.000Z

src/python/WMCore/WMBS/Oracle/Workflow/InsertOutput.py

khurtado/WMCore

f74e252412e49189a92962945a94f93bec81cd1e

[ "Apache-2.0" ]

5,671

2015-01-06T14:38:52.000Z

2022-03-31T22:11:14.000Z

src/python/WMCore/WMBS/Oracle/Workflow/InsertOutput.py

khurtado/WMCore

f74e252412e49189a92962945a94f93bec81cd1e

[ "Apache-2.0" ]

67

2015-01-21T15:55:38.000Z

2022-02-03T19:53:13.000Z

#!/usr/bin/env python """ _InsertOutput_ Oracle implementation of Workflow.InsertOutput """ from WMCore.WMBS.MySQL.Workflow.InsertOutput import InsertOutput as InsertOutputMySQL class InsertOutput(InsertOutputMySQL): pass

19.083333

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null

0

1

0

1

0

6

b461a899f59ec2b1b1ba6985f723c5422f0fe3af

42,731

py

Python

airflow/providers/google/cloud/operators/datafusion.py

npodewitz/airflow

511ea702d5f732582d018dad79754b54d5e53f9d

[ "Apache-2.0" ]

8,092

2016-04-27T20:32:29.000Z

2019-01-05T07:39:33.000Z

airflow/providers/google/cloud/operators/datafusion.py

npodewitz/airflow

511ea702d5f732582d018dad79754b54d5e53f9d

[ "Apache-2.0" ]

2,961

2016-05-05T07:16:16.000Z

2019-01-05T08:47:59.000Z

airflow/providers/google/cloud/operators/datafusion.py

npodewitz/airflow

511ea702d5f732582d018dad79754b54d5e53f9d

[ "Apache-2.0" ]

3,546

2016-05-04T20:33:16.000Z

2019-01-05T05:14:26.000Z

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. """This module contains Google DataFusion operators.""" from time import sleep from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, Union from google.api_core.retry import exponential_sleep_generator from googleapiclient.errors import HttpError from airflow.models import BaseOperator from airflow.providers.google.cloud.hooks.datafusion import SUCCESS_STATES, DataFusionHook, PipelineStates from airflow.providers.google.cloud.links.base import BaseGoogleLink if TYPE_CHECKING: from airflow.utils.context import Context BASE_LINK = "https://console.cloud.google.com/data-fusion" DATAFUSION_INSTANCE_LINK = BASE_LINK + "/locations/{region}/instances/{instance_name}?project={project_id}" DATAFUSION_PIPELINES_LINK = "{uri}/cdap/ns/default/pipelines" DATAFUSION_PIPELINE_LINK = "{uri}/pipelines/ns/default/view/{pipeline_name}" class DataFusionPipelineLinkHelper: """Helper class for Pipeline links""" @staticmethod def get_project_id(instance): instance = instance["name"] project_id = [x for x in instance.split("/") if x.startswith("airflow")][0] return project_id class DataFusionInstanceLink(BaseGoogleLink): """Helper class for constructing Data Fusion Instance link""" name = "Data Fusion Instance" key = "instance_conf" format_str = DATAFUSION_INSTANCE_LINK @staticmethod def persist( context: "Context", task_instance: Union[ "CloudDataFusionRestartInstanceOperator", "CloudDataFusionCreateInstanceOperator", "CloudDataFusionUpdateInstanceOperator", "CloudDataFusionGetInstanceOperator", ], project_id: str, ): task_instance.xcom_push( context=context, key=DataFusionInstanceLink.key, value={ "region": task_instance.location, "instance_name": task_instance.instance_name, "project_id": project_id, }, ) class DataFusionPipelineLink(BaseGoogleLink): """Helper class for constructing Data Fusion Pipeline link""" name = "Data Fusion Pipeline" key = "pipeline_conf" format_str = DATAFUSION_PIPELINE_LINK @staticmethod def persist( context: "Context", task_instance: Union[ "CloudDataFusionCreatePipelineOperator", "CloudDataFusionStartPipelineOperator", "CloudDataFusionStopPipelineOperator", ], uri: str, ): task_instance.xcom_push( context=context, key=DataFusionPipelineLink.key, value={ "uri": uri, "pipeline_name": task_instance.pipeline_name, }, ) class DataFusionPipelinesLink(BaseGoogleLink): """Helper class for constructing list of Data Fusion Pipelines link""" name = "Data Fusion Pipelines" key = "pipelines_conf" format_str = DATAFUSION_PIPELINES_LINK @staticmethod def persist( context: "Context", task_instance: "CloudDataFusionListPipelinesOperator", uri: str, ): task_instance.xcom_push( context=context, key=DataFusionPipelinesLink.key, value={ "uri": uri, }, ) class CloudDataFusionRestartInstanceOperator(BaseOperator): """ Restart a single Data Fusion instance. At the end of an operation instance is fully restarted. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:CloudDataFusionRestartInstanceOperator` :param instance_name: The name of the instance to restart. :param location: The Cloud Data Fusion location in which to handle the request. :param project_id: The ID of the Google Cloud project that the instance belongs to. :param api_version: The version of the api that will be requested for example 'v3'. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields: Sequence[str] = ( "instance_name", "impersonation_chain", ) operator_extra_links = (DataFusionInstanceLink(),) def __init__( self, *, instance_name: str, location: str, project_id: Optional[str] = None, api_version: str = "v1beta1", gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.instance_name = instance_name self.location = location self.project_id = project_id self.api_version = api_version self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context') -> None: hook = DataFusionHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) self.log.info("Restarting Data Fusion instance: %s", self.instance_name) operation = hook.restart_instance( instance_name=self.instance_name, location=self.location, project_id=self.project_id, ) instance = hook.wait_for_operation(operation) self.log.info("Instance %s restarted successfully", self.instance_name) project_id = self.project_id or DataFusionPipelineLinkHelper.get_project_id(instance) DataFusionInstanceLink.persist(context=context, task_instance=self, project_id=project_id) class CloudDataFusionDeleteInstanceOperator(BaseOperator): """ Deletes a single Date Fusion instance. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:CloudDataFusionDeleteInstanceOperator` :param instance_name: The name of the instance to restart. :param location: The Cloud Data Fusion location in which to handle the request. :param project_id: The ID of the Google Cloud project that the instance belongs to. :param api_version: The version of the api that will be requested for example 'v3'. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields: Sequence[str] = ( "instance_name", "impersonation_chain", ) def __init__( self, *, instance_name: str, location: str, project_id: Optional[str] = None, api_version: str = "v1beta1", gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.instance_name = instance_name self.location = location self.project_id = project_id self.api_version = api_version self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context') -> None: hook = DataFusionHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) self.log.info("Deleting Data Fusion instance: %s", self.instance_name) operation = hook.delete_instance( instance_name=self.instance_name, location=self.location, project_id=self.project_id, ) hook.wait_for_operation(operation) self.log.info("Instance %s deleted successfully", self.instance_name) class CloudDataFusionCreateInstanceOperator(BaseOperator): """ Creates a new Data Fusion instance in the specified project and location. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:CloudDataFusionCreateInstanceOperator` :param instance_name: The name of the instance to create. :param instance: An instance of Instance. https://cloud.google.com/data-fusion/docs/reference/rest/v1beta1/projects.locations.instances#Instance :param location: The Cloud Data Fusion location in which to handle the request. :param project_id: The ID of the Google Cloud project that the instance belongs to. :param api_version: The version of the api that will be requested for example 'v3'. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields: Sequence[str] = ( "instance_name", "instance", "impersonation_chain", ) operator_extra_links = (DataFusionInstanceLink(),) def __init__( self, *, instance_name: str, instance: Dict[str, Any], location: str, project_id: Optional[str] = None, api_version: str = "v1beta1", gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.instance_name = instance_name self.instance = instance self.location = location self.project_id = project_id self.api_version = api_version self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context') -> dict: hook = DataFusionHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) self.log.info("Creating Data Fusion instance: %s", self.instance_name) try: operation = hook.create_instance( instance_name=self.instance_name, instance=self.instance, location=self.location, project_id=self.project_id, ) instance = hook.wait_for_operation(operation) self.log.info("Instance %s created successfully", self.instance_name) except HttpError as err: if err.resp.status not in (409, '409'): raise self.log.info("Instance %s already exists", self.instance_name) instance = hook.get_instance( instance_name=self.instance_name, location=self.location, project_id=self.project_id ) # Wait for instance to be ready for time_to_wait in exponential_sleep_generator(initial=10, maximum=120): if instance['state'] != 'CREATING': break sleep(time_to_wait) instance = hook.get_instance( instance_name=self.instance_name, location=self.location, project_id=self.project_id ) project_id = self.project_id or DataFusionPipelineLinkHelper.get_project_id(instance) DataFusionInstanceLink.persist(context=context, task_instance=self, project_id=project_id) return instance class CloudDataFusionUpdateInstanceOperator(BaseOperator): """ Updates a single Data Fusion instance. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:CloudDataFusionUpdateInstanceOperator` :param instance_name: The name of the instance to create. :param instance: An instance of Instance. https://cloud.google.com/data-fusion/docs/reference/rest/v1beta1/projects.locations.instances#Instance :param update_mask: Field mask is used to specify the fields that the update will overwrite in an instance resource. The fields specified in the updateMask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask, all the supported fields (labels and options currently) will be overwritten. A comma-separated list of fully qualified names of fields. Example: "user.displayName,photo". https://developers.google.com/protocol-buffers/docs/reference/google.protobuf?_ga=2.205612571.-968688242.1573564810#google.protobuf.FieldMask :param location: The Cloud Data Fusion location in which to handle the request. :param project_id: The ID of the Google Cloud project that the instance belongs to. :param api_version: The version of the api that will be requested for example 'v3'. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields: Sequence[str] = ( "instance_name", "instance", "impersonation_chain", ) operator_extra_links = (DataFusionInstanceLink(),) def __init__( self, *, instance_name: str, instance: Dict[str, Any], update_mask: str, location: str, project_id: Optional[str] = None, api_version: str = "v1beta1", gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.update_mask = update_mask self.instance_name = instance_name self.instance = instance self.location = location self.project_id = project_id self.api_version = api_version self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context') -> None: hook = DataFusionHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) self.log.info("Updating Data Fusion instance: %s", self.instance_name) operation = hook.patch_instance( instance_name=self.instance_name, instance=self.instance, update_mask=self.update_mask, location=self.location, project_id=self.project_id, ) instance = hook.wait_for_operation(operation) self.log.info("Instance %s updated successfully", self.instance_name) project_id = self.project_id or DataFusionPipelineLinkHelper.get_project_id(instance) DataFusionInstanceLink.persist(context=context, task_instance=self, project_id=project_id) class CloudDataFusionGetInstanceOperator(BaseOperator): """ Gets details of a single Data Fusion instance. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:CloudDataFusionGetInstanceOperator` :param instance_name: The name of the instance. :param location: The Cloud Data Fusion location in which to handle the request. :param project_id: The ID of the Google Cloud project that the instance belongs to. :param api_version: The version of the api that will be requested for example 'v3'. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields: Sequence[str] = ( "instance_name", "impersonation_chain", ) operator_extra_links = (DataFusionInstanceLink(),) def __init__( self, *, instance_name: str, location: str, project_id: Optional[str] = None, api_version: str = "v1beta1", gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.instance_name = instance_name self.location = location self.project_id = project_id self.api_version = api_version self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context') -> dict: hook = DataFusionHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) self.log.info("Retrieving Data Fusion instance: %s", self.instance_name) instance = hook.get_instance( instance_name=self.instance_name, location=self.location, project_id=self.project_id, ) project_id = self.project_id or DataFusionPipelineLinkHelper.get_project_id(instance) DataFusionInstanceLink.persist(context=context, task_instance=self, project_id=project_id) return instance class CloudDataFusionCreatePipelineOperator(BaseOperator): """ Creates a Cloud Data Fusion pipeline. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:CloudDataFusionCreatePipelineOperator` :param pipeline_name: Your pipeline name. :param pipeline: The pipeline definition. For more information check: https://docs.cdap.io/cdap/current/en/developer-manual/pipelines/developing-pipelines.html#pipeline-configuration-file-format :param instance_name: The name of the instance. :param location: The Cloud Data Fusion location in which to handle the request. :param namespace: If your pipeline belongs to a Basic edition instance, the namespace ID is always default. If your pipeline belongs to an Enterprise edition instance, you can create a namespace. :param api_version: The version of the api that will be requested for example 'v3'. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields: Sequence[str] = ( "instance_name", "pipeline_name", "impersonation_chain", ) operator_extra_links = (DataFusionPipelineLink(),) def __init__( self, *, pipeline_name: str, pipeline: Dict[str, Any], instance_name: str, location: str, namespace: str = "default", project_id: Optional[str] = None, api_version: str = "v1beta1", gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.pipeline_name = pipeline_name self.pipeline = pipeline self.namespace = namespace self.instance_name = instance_name self.location = location self.project_id = project_id self.api_version = api_version self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context') -> None: hook = DataFusionHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) self.log.info("Creating Data Fusion pipeline: %s", self.pipeline_name) instance = hook.get_instance( instance_name=self.instance_name, location=self.location, project_id=self.project_id, ) api_url = instance["apiEndpoint"] hook.create_pipeline( pipeline_name=self.pipeline_name, pipeline=self.pipeline, instance_url=api_url, namespace=self.namespace, ) DataFusionPipelineLink.persist(context=context, task_instance=self, uri=instance["serviceEndpoint"]) self.log.info("Pipeline created") class CloudDataFusionDeletePipelineOperator(BaseOperator): """ Deletes a Cloud Data Fusion pipeline. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:CloudDataFusionDeletePipelineOperator` :param pipeline_name: Your pipeline name. :param version_id: Version of pipeline to delete :param instance_name: The name of the instance. :param location: The Cloud Data Fusion location in which to handle the request. :param namespace: If your pipeline belongs to a Basic edition instance, the namespace ID is always default. If your pipeline belongs to an Enterprise edition instance, you can create a namespace. :param api_version: The version of the api that will be requested for example 'v3'. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields: Sequence[str] = ( "instance_name", "version_id", "pipeline_name", "impersonation_chain", ) def __init__( self, *, pipeline_name: str, instance_name: str, location: str, version_id: Optional[str] = None, namespace: str = "default", project_id: Optional[str] = None, api_version: str = "v1beta1", gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.pipeline_name = pipeline_name self.version_id = version_id self.namespace = namespace self.instance_name = instance_name self.location = location self.project_id = project_id self.api_version = api_version self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context') -> None: hook = DataFusionHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) self.log.info("Deleting Data Fusion pipeline: %s", self.pipeline_name) instance = hook.get_instance( instance_name=self.instance_name, location=self.location, project_id=self.project_id, ) api_url = instance["apiEndpoint"] hook.delete_pipeline( pipeline_name=self.pipeline_name, version_id=self.version_id, instance_url=api_url, namespace=self.namespace, ) self.log.info("Pipeline deleted") class CloudDataFusionListPipelinesOperator(BaseOperator): """ Lists Cloud Data Fusion pipelines. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:CloudDataFusionListPipelinesOperator` :param instance_name: The name of the instance. :param location: The Cloud Data Fusion location in which to handle the request. :param artifact_version: Artifact version to filter instances :param artifact_name: Artifact name to filter instances :param namespace: If your pipeline belongs to a Basic edition instance, the namespace ID is always default. If your pipeline belongs to an Enterprise edition instance, you can create a namespace. :param api_version: The version of the api that will be requested for example 'v3'. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields: Sequence[str] = ( "instance_name", "artifact_name", "artifact_version", "impersonation_chain", ) operator_extra_links = (DataFusionPipelinesLink(),) def __init__( self, *, instance_name: str, location: str, artifact_name: Optional[str] = None, artifact_version: Optional[str] = None, namespace: str = "default", project_id: Optional[str] = None, api_version: str = "v1beta1", gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.artifact_version = artifact_version self.artifact_name = artifact_name self.namespace = namespace self.instance_name = instance_name self.location = location self.project_id = project_id self.api_version = api_version self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context') -> dict: hook = DataFusionHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) self.log.info("Listing Data Fusion pipelines") instance = hook.get_instance( instance_name=self.instance_name, location=self.location, project_id=self.project_id, ) api_url = instance["apiEndpoint"] pipelines = hook.list_pipelines( instance_url=api_url, namespace=self.namespace, artifact_version=self.artifact_version, artifact_name=self.artifact_name, ) self.log.info("%s", pipelines) DataFusionPipelinesLink.persist(context=context, task_instance=self, uri=instance["serviceEndpoint"]) return pipelines class CloudDataFusionStartPipelineOperator(BaseOperator): """ Starts a Cloud Data Fusion pipeline. Works for both batch and stream pipelines. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:CloudDataFusionStartPipelineOperator` :param pipeline_name: Your pipeline name. :param instance_name: The name of the instance. :param success_states: If provided the operator will wait for pipeline to be in one of the provided states. :param pipeline_timeout: How long (in seconds) operator should wait for the pipeline to be in one of ``success_states``. Works only if ``success_states`` are provided. :param location: The Cloud Data Fusion location in which to handle the request. :param runtime_args: Optional runtime args to be passed to the pipeline :param namespace: If your pipeline belongs to a Basic edition instance, the namespace ID is always default. If your pipeline belongs to an Enterprise edition instance, you can create a namespace. :param api_version: The version of the api that will be requested for example 'v3'. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). :param asynchronous: Flag to return after submitting the pipeline Id to the Data Fusion API. This is useful for submitting long running pipelines and waiting on them asynchronously using the CloudDataFusionPipelineStateSensor """ template_fields: Sequence[str] = ( "instance_name", "pipeline_name", "runtime_args", "impersonation_chain", ) operator_extra_links = (DataFusionPipelineLink(),) def __init__( self, *, pipeline_name: str, instance_name: str, location: str, runtime_args: Optional[Dict[str, Any]] = None, success_states: Optional[List[str]] = None, namespace: str = "default", pipeline_timeout: int = 5 * 60, project_id: Optional[str] = None, api_version: str = "v1beta1", gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, asynchronous=False, **kwargs, ) -> None: super().__init__(**kwargs) self.pipeline_name = pipeline_name self.runtime_args = runtime_args self.namespace = namespace self.instance_name = instance_name self.location = location self.project_id = project_id self.api_version = api_version self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain self.asynchronous = asynchronous self.pipeline_timeout = pipeline_timeout if success_states: self.success_states = success_states else: self.success_states = SUCCESS_STATES + [PipelineStates.RUNNING] def execute(self, context: 'Context') -> str: hook = DataFusionHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) self.log.info("Starting Data Fusion pipeline: %s", self.pipeline_name) instance = hook.get_instance( instance_name=self.instance_name, location=self.location, project_id=self.project_id, ) api_url = instance["apiEndpoint"] pipeline_id = hook.start_pipeline( pipeline_name=self.pipeline_name, instance_url=api_url, namespace=self.namespace, runtime_args=self.runtime_args, ) self.log.info("Pipeline %s submitted successfully.", pipeline_id) DataFusionPipelineLink.persist(context=context, task_instance=self, uri=instance["serviceEndpoint"]) if not self.asynchronous: self.log.info("Waiting when pipeline %s will be in one of the success states", pipeline_id) hook.wait_for_pipeline_state( success_states=self.success_states, pipeline_id=pipeline_id, pipeline_name=self.pipeline_name, namespace=self.namespace, instance_url=api_url, timeout=self.pipeline_timeout, ) self.log.info("Job %s discover success state.", pipeline_id) return pipeline_id class CloudDataFusionStopPipelineOperator(BaseOperator): """ Stops a Cloud Data Fusion pipeline. Works for both batch and stream pipelines. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:CloudDataFusionStopPipelineOperator` :param pipeline_name: Your pipeline name. :param instance_name: The name of the instance. :param location: The Cloud Data Fusion location in which to handle the request. :param namespace: If your pipeline belongs to a Basic edition instance, the namespace ID is always default. If your pipeline belongs to an Enterprise edition instance, you can create a namespace. :param api_version: The version of the api that will be requested for example 'v3'. :param gcp_conn_id: The connection ID to use when fetching connection info. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields: Sequence[str] = ( "instance_name", "pipeline_name", "impersonation_chain", ) operator_extra_links = (DataFusionPipelineLink(),) def __init__( self, *, pipeline_name: str, instance_name: str, location: str, namespace: str = "default", project_id: Optional[str] = None, api_version: str = "v1beta1", gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.pipeline_name = pipeline_name self.namespace = namespace self.instance_name = instance_name self.location = location self.project_id = project_id self.api_version = api_version self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context') -> None: hook = DataFusionHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) self.log.info("Data Fusion pipeline: %s is going to be stopped", self.pipeline_name) instance = hook.get_instance( instance_name=self.instance_name, location=self.location, project_id=self.project_id, ) api_url = instance["apiEndpoint"] DataFusionPipelineLink.persist(context=context, task_instance=self, uri=instance["serviceEndpoint"]) hook.stop_pipeline( pipeline_name=self.pipeline_name, instance_url=api_url, namespace=self.namespace, ) self.log.info("Pipeline stopped")

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0

1

0

1

0

null

0

6

c35e120d31acd0d1ae05806ded43352553a41220

112

py

Python

user/models.py

ashwin-bitsathy/django---ecommerce

49ebb518ed5831639d560c27f2313f983fe27e86

[ "BSD-3-Clause" ]

null

user/models.py

ashwin-bitsathy/django---ecommerce

49ebb518ed5831639d560c27f2313f983fe27e86

[ "BSD-3-Clause" ]

null

user/models.py

ashwin-bitsathy/django---ecommerce

49ebb518ed5831639d560c27f2313f983fe27e86

[ "BSD-3-Clause" ]

null

from django.db import models from django.utils import timezone from django.contrib.auth.models import User

22.4

44

0.803571

17

112

5.294118

0.588235

0.333333

0

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112

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1

0

null

0

1

0

1

0

1

0

6

c37098b3e27127a9c247f787f7b23e329f49b646

42

py

Python

pello/__init__.py

encukou/Pello

bac192da6288cea103eab05fc2ca0b7f37b78abf

[ "CC0-1.0" ]

null

pello/__init__.py

encukou/Pello

bac192da6288cea103eab05fc2ca0b7f37b78abf

[ "CC0-1.0" ]

3

2020-05-11T11:25:40.000Z

2020-08-05T09:26:01.000Z

pello/__init__.py

hrnciar/pello

d93051c271a2c163f903d7c3676739a0a331549e

[ "MIT" ]

null

from pello.pello_greeting import greeting

21

41

0.880952

6

42

6

0.666667

0

0.095238

42

1

42

0.947368

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1

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1

0

null

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1

0

null

0

1

0

1

0

1

0

6

c37d8a6b933810f9d544027015017376c08c6d6a

97

py

Python

editor/lib/juma/AssetEditor/converters/__init__.py

RazielSun/juma-editor

125720f7386f9f0a4cd3466a45c883d6d6020e33

[ "MIT" ]

null

editor/lib/juma/AssetEditor/converters/__init__.py

RazielSun/juma-editor

125720f7386f9f0a4cd3466a45c883d6d6020e33

[ "MIT" ]

null

editor/lib/juma/AssetEditor/converters/__init__.py

RazielSun/juma-editor

125720f7386f9f0a4cd3466a45c883d6d6020e33

[ "MIT" ]

1

2022-03-31T00:50:23.000Z

from PyAssimpConverter import PyAssimpConverter from AnimationConverter import AnimationConverter

48.5

49

0.927835

8

97

11.25

0.5

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0.072165

97

2

49

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true

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null

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0

1

0

1

0

6

6f044e619fc0b5359a90973e556edad7df74210a

22

py

Python

src/__init__.py

michalsta/mocos_helper

e33f29246c70ce1dbd477eeed2374ba902e46cfe

[ "MIT" ]

89

2020-02-06T09:24:10.000Z

2021-09-11T22:49:34.000Z

src/__init__.py

michalsta/mocos_helper

e33f29246c70ce1dbd477eeed2374ba902e46cfe

[ "MIT" ]

null

src/__init__.py

michalsta/mocos_helper

e33f29246c70ce1dbd477eeed2374ba902e46cfe

[ "MIT" ]

8

2020-04-15T19:07:49.000Z

2020-10-12T10:06:55.000Z

from .random import *

11

21

0.727273

3

22

5.333333

1

0

0.181818

22

1

22

0.888889

0

1

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1

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null

0

1

0

1

0

1

0

6

6f1e64a90a4fa6b96a01f729ac30110014ef1343

2,017

py

Python

test/test_index.py

grijul/arch-security-tracker

132d1088a982d406436a2d1a047e977d0b2f18ed

[ "MIT" ]

80

2017-10-09T13:39:34.000Z

2022-03-30T08:28:25.000Z

test/test_index.py

grijul/arch-security-tracker

132d1088a982d406436a2d1a047e977d0b2f18ed

[ "MIT" ]

103

2017-07-20T23:01:23.000Z

2022-03-29T15:45:44.000Z

test/test_index.py

grijul/arch-security-tracker

132d1088a982d406436a2d1a047e977d0b2f18ed

[ "MIT" ]

28

2017-10-18T17:03:42.000Z

2022-03-18T17:36:48.000Z

from flask import url_for from werkzeug.exceptions import NotFound from .conftest import DEFAULT_GROUP_ID from .conftest import DEFAULT_GROUP_NAME from .conftest import create_group from .conftest import create_package @create_package(name='foo', version='1.2.3-4') @create_group(id=DEFAULT_GROUP_ID, packages=['foo'], affected='1.2.3-3', fixed='1.2.3-4') def test_index(db, client): resp = client.get(url_for('tracker.index'), follow_redirects=True) assert 200 == resp.status_code assert DEFAULT_GROUP_NAME not in resp.data.decode() @create_package(name='foo', version='1.2.3-4') @create_group(id=DEFAULT_GROUP_ID, packages=['foo'], affected='1.2.3-3') def test_index_vulnerable(db, client): resp = client.get(url_for('tracker.index_vulnerable'), follow_redirects=True) assert 200 == resp.status_code assert DEFAULT_GROUP_NAME in resp.data.decode() @create_package(name='foo', version='1.2.3-4') @create_group(id=DEFAULT_GROUP_ID, packages=['foo'], affected='1.2.3-3') def test_index_all(db, client): resp = client.get(url_for('tracker.index_all'), follow_redirects=True) assert 200 == resp.status_code assert DEFAULT_GROUP_NAME in resp.data.decode() @create_package(name='foo', version='1.2.3-4') @create_group(id=DEFAULT_GROUP_ID, packages=['foo'], affected='1.2.3-3') def test_index_json(db, client): resp = client.get(url_for('tracker.index_json', only_vulernable=False, path='all.json'), follow_redirects=True) assert 200 == resp.status_code data = resp.get_json() assert len(data) == 1 assert data[0]['name'] == DEFAULT_GROUP_NAME @create_package(name='foo', version='1.2.3-4') @create_group(id=DEFAULT_GROUP_ID, packages=['foo'], affected='1.2.3-3') def test_index_vulnerable_json(db, client): resp = client.get(url_for('tracker.index_vulnerable_json', path='vulnerable.json'), follow_redirects=True) assert 200 == resp.status_code data = resp.get_json() assert len(data) == 1 assert data[0]['name'] == DEFAULT_GROUP_NAME

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321

2,017

4.389408

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0.1022

0.023421

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null

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null

0

6

6f220c3cf0fed5d4ce8be1d1fdbb0ec07a827600

129

py

Python

homebot/dash/__init__.py

bearylogical/homebot

07e01df8de20764b3850a6181529a109c020f855

[ "MIT" ]

null

homebot/dash/__init__.py

bearylogical/homebot

07e01df8de20764b3850a6181529a109c020f855

[ "MIT" ]

null

homebot/dash/__init__.py

bearylogical/homebot

07e01df8de20764b3850a6181529a109c020f855

[ "MIT" ]

null

from flask import Blueprint dash = Blueprint('dash', __name__, static_folder='static', static_url_path='') from . import views

21.5

78

0.75969

17

129

5.352941

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null

0

1

0

1

0

6

6f24d41f765bfb7415f1e24bec70c028dc933391

2,338

py

Python

tests/test_question_answering.py

easynlp/easynlp

4b3b405a64ca166cc19ee9c43b79a475cf699996

[ "MIT" ]

6

2021-07-09T08:13:44.000Z

2021-11-10T04:09:33.000Z

tests/test_question_answering.py

easynlp/easynlp

4b3b405a64ca166cc19ee9c43b79a475cf699996

[ "MIT" ]

1

2021-07-09T17:18:16.000Z

tests/test_question_answering.py

easynlp/easynlp

4b3b405a64ca166cc19ee9c43b79a475cf699996

[ "MIT" ]

1

2022-02-09T15:37:14.000Z

import easynlp def test_single_question_answering(): data = { "text": [ "What is extractive question answering?", ], "context": [ """Extractive Question Answering is the task of extracting an answer from a text given a question. An example of a question answering dataset is the SQuAD dataset, which is entirely based on that task. If you would like to fine-tune a model on a SQuAD task, you may leverage the examples/pytorch/question-answering/run_squad.py script.""", ], } input_column = "text" context_column = "context" output_column = "answer" output_dataset = easynlp.question_answering( data, input_column, context_column, output_column ) answers = [ "the task of extracting an answer from a text given a question", ] assert len(output_dataset) == 1 assert output_dataset[output_column] == answers def test_question_answering(): data = { "text": [ "What is extractive question answering?", "What is a good example of a question answering dataset?", ], "context": [ """Extractive Question Answering is the task of extracting an answer from a text given a question. An example of a question answering dataset is the SQuAD dataset, which is entirely based on that task. If you would like to fine-tune a model on a SQuAD task, you may leverage the examples/pytorch/question-answering/run_squad.py script.""", """Extractive Question Answering is the task of extracting an answer from a text given a question. An example of a question answering dataset is the SQuAD dataset, which is entirely based on that task. If you would like to fine-tune a model on a SQuAD task, you may leverage the examples/pytorch/question-answering/run_squad.py script.""", ], } input_column = "text" context_column = "context" output_column = "answer" output_dataset = easynlp.question_answering( data, input_column, context_column, output_column ) answers = [ "the task of extracting an answer from a text given a question", "SQuAD dataset", ] assert len(output_dataset) == 2 assert output_dataset[output_column] == answers

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2,338

4.977124

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0.062377

0.933027

0.860801

0.784636

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0.068182

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null

0

1

0

null

0

6

6f2de558f0fb56b6b1140309e954d10f16785d66

97

py

Python

recursion/reverse_string.py

JunzhongLin/leetcode_practice

47b2f5cc3c87de004ae21a94024e751b40b8f559

[ "MIT" ]

null

recursion/reverse_string.py

JunzhongLin/leetcode_practice

47b2f5cc3c87de004ae21a94024e751b40b8f559

[ "MIT" ]

null

recursion/reverse_string.py

JunzhongLin/leetcode_practice

47b2f5cc3c87de004ae21a94024e751b40b8f559

[ "MIT" ]

null

s = 'tomclancy' def print_letter(strings): print(strings[-1]) print_letter(strings[:-1])

19.4

30

0.670103

13

97

4.846154

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0.349206

0.571429

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97

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null

0

1

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1

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6

6f3f84e67888ee647792baa9bd5d3d853847bb79

313

py

Python

utils/__init__.py

edwardyehuang/iSeg

256b0f7fdb6e854fe026fa8df41d9a4a55db34d5

[ "MIT" ]

4

2021-12-13T09:49:26.000Z

2022-02-19T11:16:50.000Z

utils/__init__.py

edwardyehuang/iSeg

256b0f7fdb6e854fe026fa8df41d9a4a55db34d5

[ "MIT" ]

1

2021-07-28T10:40:56.000Z

2021-08-09T07:14:06.000Z

utils/__init__.py

edwardyehuang/iSeg

256b0f7fdb6e854fe026fa8df41d9a4a55db34d5

[ "MIT" ]

null

# ================================================================ # MIT License # Copyright (c) 2021 edwardyehuang (https://github.com/edwardyehuang) # ================================================================ from iseg.utils.sugars import * from iseg.utils.common import resize_image, simple_load_image

39.125

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null

0

1

0

1

0

6

6f6143b3480544510ea0cd43ede8c061b44a5767

1,964

py

Python

axitom/tests/test_rotate_coordinates.py

PolymerGuy/AXITOM

7682be5b21fa933b9bea4082fe9a830076431feb

[ "MIT" ]

4

2019-09-06T16:31:11.000Z

2022-02-04T12:18:47.000Z

axitom/tests/test_rotate_coordinates.py

PolymerGuy/AXITOM

7682be5b21fa933b9bea4082fe9a830076431feb

[ "MIT" ]

1

2019-08-08T12:30:33.000Z

2019-08-08T12:34:55.000Z

axitom/tests/test_rotate_coordinates.py

PolymerGuy/AXITOM

7682be5b21fa933b9bea4082fe9a830076431feb

[ "MIT" ]

7

2019-08-21T20:51:12.000Z

2020-02-04T14:20:42.000Z

from unittest import TestCase import numpy as np from axitom.backprojection import rotate_coordinates class Test_RotateCoordinates(TestCase): def test_rotate_coordinates_90deg(self): tol = 1e-9 n_coordinates = 10 rotation_angle = np.pi/2. xs, ys = np.meshgrid(np.arange(n_coordinates),np.arange(n_coordinates)) xr,yr = rotate_coordinates(xs,ys,rotation_angle) error_xs = np.abs(xr-ys) error_ys = np.abs(yr+xs) if np.max(error_xs) >tol or np.max(error_ys) >tol: print("The maximum error in X after rotation was:",np.max(error_xs) ) print("The maximum error in Y after rotation was:",np.max(error_ys) ) self.fail() def test_rotate_coordinates_0deg(self): tol = 1e-9 n_coordinates = 10 rotation_angle = 0.0 xs, ys = np.meshgrid(np.arange(n_coordinates),np.arange(n_coordinates)) xr,yr = rotate_coordinates(xs,ys,rotation_angle) error_xs = np.abs(xr-xs) error_ys = np.abs(yr-ys) if np.max(error_xs) >tol or np.max(error_ys) >tol: print("The maximum error in X after rotation was:",np.max(error_xs) ) print("The maximum error in Y after rotation was:",np.max(error_ys) ) self.fail() def test_rotate_coordinates_forward_and_reverse(self): tol = 1e-9 n_coordinates = 10 rotation_angle = np.pi/4 xs, ys = np.meshgrid(np.arange(n_coordinates),np.arange(n_coordinates)) xr_forw,yr_forw = rotate_coordinates(xs,ys,rotation_angle) xr,yr = rotate_coordinates(xr_forw,yr_forw,-rotation_angle) error_xs = np.abs(xr-xs) error_ys = np.abs(yr-ys) if np.max(error_xs) >tol or np.max(error_ys) >tol: print("The maximum error in X after rotation was:",np.max(error_xs) ) print("The maximum error in Y after rotation was:",np.max(error_ys) ) self.fail()

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null

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1

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null

0

6

48ad9da2050df47a06c5487872f04c3641ae6370

9,227

py

Python

tests/test_karma_parser.py

leoriviera/apollo

acd10d0e238b34bb61aaefa5d29db181fd171b79

[ "MIT" ]

null

tests/test_karma_parser.py

leoriviera/apollo

acd10d0e238b34bb61aaefa5d29db181fd171b79

[ "MIT" ]

null

tests/test_karma_parser.py

leoriviera/apollo

acd10d0e238b34bb61aaefa5d29db181fd171b79

[ "MIT" ]

null

import os import pytest from alembic import command from alembic.config import Config from sqlalchemy import create_engine from sqlalchemy.orm import Session from karma.parser import RawKarma, parse_message from models import Base @pytest.fixture(scope="module") def database(): # Locate the testing config for Alembic config = Config(os.path.join(os.path.dirname(__file__), "../alembic.tests.ini")) # Set the migration secret key here if not os.environ.get("SECRET_KEY", None): os.environ["SECRET_KEY"] = "test" # Start up the in-memory database instance db_engine = create_engine("sqlite:///:memory:") Base.metadata.create_all(db_engine) db_session = Session(bind=db_engine) # Mark it as up-to-date with migrations command.stamp(config, "head") return db_session def test_empty(database): assert parse_message("", database) is None def test_no_karma(database): assert parse_message("Hello, world!", database) is None def test_no_karma_complex_sentence(database): assert ( parse_message( "Hello, world! This is a test input string with 30+ characters", database ) is None ) def test_empty_with_code_block(database): assert parse_message("```FoobarBaz```", database) is None def test_empty_with_inline_block(database): assert parse_message("`FoobarBaz`", database) is None def test_simple_positive(database): assert parse_message("Foobar++", database) == [ RawKarma(name="Foobar", op="++", reason=None) ] def test_simple_negative(database): assert parse_message("Foobar--", database) == [ RawKarma(name="Foobar", op="--", reason=None) ] def test_simple_neutral_pm(database): assert parse_message("Foobar+-", database) == [ RawKarma(name="Foobar", op="+-", reason=None) ] def test_simple_neutral_mp(database): assert parse_message("Foobar-+", database) == [ RawKarma(name="Foobar", op="-+", reason=None) ] def test_quoted_positive(database): assert parse_message('"Foobar"++', database) == [ RawKarma(name="Foobar", op="++", reason=None) ] def test_quoted_negative(database): assert parse_message('"Foobar"--', database) == [ RawKarma(name="Foobar", op="--", reason=None) ] def test_quoted_neutral_pm(database): assert parse_message('"Foobar"+-', database) == [ RawKarma(name="Foobar", op="+-", reason=None) ] def test_quoted_sentence_neutral_pm(database): assert parse_message('"Foobar Baz"+-', database) == [ RawKarma(name="Foobar Baz", op="+-", reason=None) ] def test_quoted_neutral_mp(database): assert parse_message('"Foobar"-+', database) == [ RawKarma(name="Foobar", op="-+", reason=None) ] def test_simple_positive_with_text_after(database): assert parse_message("Foobar++ since it's pretty cool", database) == [ RawKarma(name="Foobar", op="++", reason=None) ] def test_simple_positive_with_text_before(database): assert parse_message("Since its pretty cool, foobar++", database) == [ RawKarma(name="foobar", op="++", reason=None) ] def test_simple_positive_with_paren_reason(database): assert parse_message("Foobar++ (hella cool)", database) == [ RawKarma(name="Foobar", op="++", reason="hella cool") ] def test_simple_positive_with_quote_reason(database): assert parse_message('Foobar++ "\'hella cool"', database) == [ RawKarma(name="Foobar", op="++", reason="'hella cool") ] def test_simple_positive_with_paren_reason_and_comma(database): assert parse_message("Foobar++ (hella, cool)", database) == [ RawKarma(name="Foobar", op="++", reason="hella, cool") ] def test_simple_positive_with_empty_paren_reason(database): assert parse_message("Foobar++ ()", database) == [ RawKarma(name="Foobar", op="++", reason=None) ] def test_simple_positive_with_compound_reason(database): assert parse_message("Foobar++ because it is (hella cool)", database) == [ RawKarma(name="Foobar", op="++", reason="it is (hella cool)") ] def test_simple_positive_with_compound_reason_comma(database): assert parse_message("Foobar++ because it, is (hella cool)", database) == [ RawKarma(name="Foobar", op="++", reason="it") ] def test_simple_positive_with_reason(database): assert parse_message("Foobar++ because baz", database) == [ RawKarma(name="Foobar", op="++", reason="baz") ] def test_simple_positive_with_reason_quoted(database): assert parse_message('Foobar++ because "baz"', database) == [ RawKarma(name="Foobar", op="++", reason="baz") ] def test_simple_positive_with_reason_quoted_comma(database): assert parse_message('Foobar++ because "baz, blat"', database) == [ RawKarma(name="Foobar", op="++", reason="baz, blat") ] def test_simple_negative_with_reason(database): assert parse_message("Foobar-- because baz", database) == [ RawKarma(name="Foobar", op="--", reason="baz") ] def test_simple_neutral_pm_with_reason(database): assert parse_message("Foobar+- because baz", database) == [ RawKarma(name="Foobar", op="+-", reason="baz") ] def test_simple_neutral_mp_with_reason(database): assert parse_message("Foobar-+ because baz", database) == [ RawKarma(name="Foobar", op="-+", reason="baz") ] def test_quoted_positive_with_reason(database): assert parse_message('"Foobar"++ because baz', database) == [ RawKarma(name="Foobar", op="++", reason="baz") ] def test_quoted_negative_with_reason(database): assert parse_message('"Foobar"-- because baz', database) == [ RawKarma(name="Foobar", op="--", reason="baz") ] def test_quoted_neutral_pm_with_reason(database): assert parse_message('"Foobar"+- because baz', database) == [ RawKarma(name="Foobar", op="+-", reason="baz") ] def test_quoted_neutral_mp_with_reason(database): assert parse_message('"Foobar"-+ because baz', database) == [ RawKarma(name="Foobar", op="-+", reason="baz") ] def test_simple_multiple_karma(database): assert parse_message("Foobar++, Baz-- Blat+-", database) == [ RawKarma(name="Foobar", op="++", reason=None), RawKarma(name="Baz", op="--", reason=None), RawKarma(name="Blat", op="+-", reason=None), ] def test_simple_multiple_karma_with_reasons_and_quotes(database): assert parse_message('Foobar++ because baz blat, "Hello world"--', database) == [ RawKarma(name="Foobar", op="++", reason="baz blat"), RawKarma(name="Hello world", op="--", reason=None), ] def test_complex_multiple_karma_no_reasons_quotes(database): # The Sinjo input assert parse_message('Foobar++ "Hello world"--', database) == [ RawKarma(name="Foobar", op="++", reason=None), RawKarma(name="Hello world", op="--", reason=None), ] def test_complex_multiple_karma_no_reasons_quotes_no_comma_separation(database): assert parse_message( '"easy lover"++ "phil collins"++ "philip bailey"++', database ) == [ RawKarma(name="easy lover", op="++", reason=None), RawKarma(name="phil collins", op="++", reason=None), RawKarma(name="philip bailey", op="++", reason=None), ] def test_complex_multiple_karma_with_reasons_and_quotes(database): assert parse_message( 'Foobar++ because baz blat, "Hello world"-- for "foo, bar"', database ) == [ RawKarma(name="Foobar", op="++", reason="baz blat"), RawKarma(name="Hello world", op="--", reason="foo, bar"), ] def test_karma_op_no_token(database): assert parse_message("++", database) is None def test_simple_invalid(database): assert parse_message("Foo+", database) is None def test_simple_invalid_with_reason(database): assert parse_message("Foo+ because baz", database) is None def test_simple_quoted_invalid_with_reason(database): assert parse_message('"Foo" because baz', database) is None def test_string_starts_quoted_no_karma(database): assert ( parse_message( '"Starting the sentence with a quote but there is no karma here', database ) is None ) def test_start_simple_mid_message(database): assert parse_message( "Hello, world! Foo++ this is a mid-message karma", database ) == [RawKarma(name="Foo", op="++", reason=None)] def test_start_simple_mid_message_with_reason(database): assert parse_message( "Hello, world! Foo++ because bar, this is a mid-message karma", database ) == [RawKarma(name="Foo", op="++", reason="bar")] def test_code_block_with_internal_reason(database): assert parse_message("```Foobar++ baz because foo```", database) is None def test_code_block_with_karma_op_after(database): assert parse_message("```Foobar baz```++", database) is None def test_code_block_external_reason(database): assert parse_message("```Foobar baz``` because foo", database) is None def test_code_block_with_karma_op_after_and_external_reason(database): assert parse_message("```Foobar baz```++ because foo", database) is None

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1

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null

0

1

0

6

48c1563c45b1d57c5c559f77f493731d9c7a45e1

10,454

py

Python

services/events/migrations/versions/5da14a4e4c7a_.py

conbon/my-dev-space

604e0311bb006d8b5efe3322657ab631be3a3c02

[ "MIT" ]

24

2018-06-27T22:50:04.000Z

2020-10-27T21:06:41.000Z

services/events/migrations/versions/5da14a4e4c7a_.py

conbon/my-dev-space

604e0311bb006d8b5efe3322657ab631be3a3c02

[ "MIT" ]

398

2018-05-01T06:00:11.000Z

2021-03-01T21:31:26.000Z

services/events/migrations/versions/5da14a4e4c7a_.py

conbon/my-dev-space

604e0311bb006d8b5efe3322657ab631be3a3c02

[ "MIT" ]

22

2018-06-27T20:42:07.000Z

2019-02-10T14:30:36.000Z

"""empty message Revision ID: 5da14a4e4c7a Revises: Create Date: 2018-07-26 18:58:46.019785 """ from alembic import op import sqlalchemy as sa from sqlalchemy.dialects import postgresql # revision identifiers, used by Alembic. revision = "5da14a4e4c7a" down_revision = None branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table( "channel", sa.Column( "id", postgresql.UUID(as_uuid=True), server_default=sa.text("uuid_generate_v4()"), nullable=False, ), sa.Column("name", sa.String(length=128), nullable=False), sa.Column("url", sa.String(length=2048), nullable=False), sa.Column("description", sa.String(length=50000), nullable=False), sa.Column("created", sa.DateTime(), nullable=False), sa.Column("updated", sa.DateTime(), nullable=False), sa.Column("deleted", sa.DateTime(), nullable=True), sa.Column("source", sa.String(length=50), nullable=False), sa.PrimaryKeyConstraint("id"), ) op.create_table( "diversity", sa.Column( "id", postgresql.UUID(as_uuid=True), server_default=sa.text("uuid_generate_v4()"), nullable=False, ), sa.Column("name", sa.String(length=128), nullable=False), sa.Column("description", sa.String(length=1000), nullable=True), sa.PrimaryKeyConstraint("id"), ) op.create_table( "entry", sa.Column( "id", postgresql.UUID(as_uuid=True), server_default=sa.text("uuid_generate_v4()"), nullable=False, ), sa.Column("type", sa.String(length=128), nullable=False), sa.Column("description", sa.String(length=1000), nullable=True), sa.PrimaryKeyConstraint("id"), ) op.create_table( "event", sa.Column( "id", postgresql.UUID(as_uuid=True), server_default=sa.text("uuid_generate_v4()"), nullable=False, ), sa.Column("name", sa.String(length=128), nullable=False), sa.Column("description", sa.String(length=50000), nullable=False), sa.Column("url", sa.String(length=2048), nullable=False), sa.Column("start", sa.DateTime(), nullable=False), sa.Column("end", sa.DateTime(), nullable=False), sa.Column("duration", sa.Integer(), nullable=False), sa.Column("category", sa.String(length=256), nullable=False), sa.Column("created", sa.DateTime(), nullable=False), sa.Column("updated", sa.DateTime(), nullable=False), sa.Column("deleted", sa.DateTime(), nullable=True), sa.Column("source", sa.String(length=50), nullable=False), sa.PrimaryKeyConstraint("id"), ) op.create_table( "meetup", sa.Column( "id", postgresql.UUID(as_uuid=True), server_default=sa.text("uuid_generate_v4()"), nullable=False, ), sa.Column("name", sa.String(length=128), nullable=False), sa.Column("logo", sa.String(length=1000), nullable=False), sa.Column("url", sa.String(length=2048), nullable=False), sa.Column("description", sa.String(length=50000), nullable=False), sa.Column("created", sa.DateTime(), nullable=False), sa.Column("updated", sa.DateTime(), nullable=False), sa.Column("deleted", sa.DateTime(), nullable=True), sa.Column("source", sa.String(length=50), nullable=False), sa.PrimaryKeyConstraint("id"), ) op.create_table( "speaker", sa.Column( "id", postgresql.UUID(as_uuid=True), server_default=sa.text("uuid_generate_v4()"), nullable=False, ), sa.Column("name", sa.String(length=128), nullable=False), sa.Column("avatar", sa.String(length=1024), nullable=False), sa.Column("bio", sa.String(length=1024), nullable=False), sa.Column("contact", sa.String(length=128), nullable=False), sa.Column("role", sa.String(length=128), nullable=False), sa.Column("location", sa.String(length=128), nullable=False), sa.Column("created", sa.DateTime(), nullable=False), sa.Column("updated", sa.DateTime(), nullable=False), sa.Column("deleted", sa.DateTime(), nullable=True), sa.Column("source", sa.String(length=50), nullable=False), sa.PrimaryKeyConstraint("id"), ) op.create_table( "topic", sa.Column( "id", postgresql.UUID(as_uuid=True), server_default=sa.text("uuid_generate_v4()"), nullable=False, ), sa.Column("name", sa.String(length=128), nullable=False), sa.Column("description", sa.String(length=1000), nullable=True), sa.Column("abbreviation", sa.String(length=10), nullable=True), sa.PrimaryKeyConstraint("id"), ) op.create_table( "video", sa.Column( "id", postgresql.UUID(as_uuid=True), server_default=sa.text("uuid_generate_v4()"), nullable=False, ), sa.Column("name", sa.String(length=128), nullable=False), sa.Column("url", sa.String(length=2048), nullable=False), sa.Column("description", sa.String(length=50000), nullable=False), sa.Column("created", sa.DateTime(), nullable=False), sa.Column("updated", sa.DateTime(), nullable=False), sa.Column("deleted", sa.DateTime(), nullable=True), sa.Column("source", sa.String(length=50), nullable=False), sa.PrimaryKeyConstraint("id"), ) op.create_table( "channel_topic_association", sa.Column("channel_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("topic_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["channel_id"], ["channel.id"]), sa.ForeignKeyConstraint(["topic_id"], ["topic.id"]), ) op.create_table( "event_entry_association", sa.Column("event_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("entry_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["entry_id"], ["entry.id"]), sa.ForeignKeyConstraint(["event_id"], ["event.id"]), ) op.create_table( "event_meetup_association", sa.Column("event_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("meetup_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["event_id"], ["event.id"]), sa.ForeignKeyConstraint(["meetup_id"], ["meetup.id"]), ) op.create_table( "event_topic_association", sa.Column("event_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("topic_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["event_id"], ["event.id"]), sa.ForeignKeyConstraint(["topic_id"], ["topic.id"]), ) op.create_table( "meetup_channel_association", sa.Column("meetup_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("channel_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["channel_id"], ["channel.id"]), sa.ForeignKeyConstraint(["meetup_id"], ["meetup.id"]), ) op.create_table( "meetup_event_association", sa.Column("meetup_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("event_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["event_id"], ["event.id"]), sa.ForeignKeyConstraint(["meetup_id"], ["meetup.id"]), ) op.create_table( "meetup_topic_association", sa.Column("meetup_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("topic_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["meetup_id"], ["meetup.id"]), sa.ForeignKeyConstraint(["topic_id"], ["topic.id"]), ) op.create_table( "speaker_diversity_association", sa.Column("speaker_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("diversity_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["diversity_id"], ["diversity.id"]), sa.ForeignKeyConstraint(["speaker_id"], ["speaker.id"]), ) op.create_table( "speaker_topic_association", sa.Column("speaker_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("topic_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["speaker_id"], ["speaker.id"]), sa.ForeignKeyConstraint(["topic_id"], ["topic.id"]), ) op.create_table( "video_channel_association", sa.Column("video_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("channel_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["channel_id"], ["channel.id"]), sa.ForeignKeyConstraint(["video_id"], ["video.id"]), ) op.create_table( "video_topic_association", sa.Column("video_id", postgresql.UUID(as_uuid=True), nullable=True), sa.Column("topic_id", postgresql.UUID(as_uuid=True), nullable=True), sa.ForeignKeyConstraint(["topic_id"], ["topic.id"]), sa.ForeignKeyConstraint(["video_id"], ["video.id"]), ) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_table("video_topic_association") op.drop_table("video_channel_association") op.drop_table("speaker_topic_association") op.drop_table("speaker_diversity_association") op.drop_table("meetup_topic_association") op.drop_table("meetup_event_association") op.drop_table("meetup_channel_association") op.drop_table("event_topic_association") op.drop_table("event_meetup_association") op.drop_table("event_entry_association") op.drop_table("channel_topic_association") op.drop_table("video") op.drop_table("topic") op.drop_table("speaker") op.drop_table("meetup") op.drop_table("event") op.drop_table("entry") op.drop_table("diversity") op.drop_table("channel") # ### end Alembic commands ###

41.320158

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81

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0.750333

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false

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1

0

null

0

6

48ea7a5c78b44d58ffa20048da1398281f5072a1

73,164

py

Python

gen/PSLexer.py

Na2CuCl4/latex2sympy

40f3b16ad13f8ab12d7704bb422cf8580b45b380

[ "MIT" ]

26

2021-05-12T09:48:28.000Z

2022-03-31T08:33:57.000Z

gen/PSLexer.py

Na2CuCl4/latex2sympy

40f3b16ad13f8ab12d7704bb422cf8580b45b380

[ "MIT" ]

null

gen/PSLexer.py

Na2CuCl4/latex2sympy

40f3b16ad13f8ab12d7704bb422cf8580b45b380

[ "MIT" ]

3

2021-10-09T03:16:53.000Z

2022-02-18T13:23:40.000Z

# Generated from PS.g4 by ANTLR 4.7.2 # encoding: utf-8 from __future__ import print_function from antlr4 import * from io import StringIO import sys def serializedATN(): with StringIO() as buf: buf.write(u"\3\u608b\ua72a\u8133\ub9ed\u417c\u3be7\u7786\u5964\2") buf.write(u"\u0087\u06c3\b\1\4\2\t\2\4\3\t\3\4\4\t\4\4\5\t\5\4\6") buf.write(u"\t\6\4\7\t\7\4\b\t\b\4\t\t\t\4\n\t\n\4\13\t\13\4\f\t") buf.write(u"\f\4\r\t\r\4\16\t\16\4\17\t\17\4\20\t\20\4\21\t\21\4") buf.write(u"\22\t\22\4\23\t\23\4\24\t\24\4\25\t\25\4\26\t\26\4\27") buf.write(u"\t\27\4\30\t\30\4\31\t\31\4\32\t\32\4\33\t\33\4\34\t") buf.write(u"\34\4\35\t\35\4\36\t\36\4\37\t\37\4 \t \4!\t!\4\"\t\"") buf.write(u"\4#\t#\4$\t$\4%\t%\4&\t&\4\'\t\'\4(\t(\4)\t)\4*\t*\4") buf.write(u"+\t+\4,\t,\4-\t-\4.\t.\4/\t/\4\60\t\60\4\61\t\61\4\62") buf.write(u"\t\62\4\63\t\63\4\64\t\64\4\65\t\65\4\66\t\66\4\67\t") buf.write(u"\67\48\t8\49\t9\4:\t:\4;\t;\4<\t<\4=\t=\4>\t>\4?\t?\4") buf.write(u"@\t@\4A\tA\4B\tB\4C\tC\4D\tD\4E\tE\4F\tF\4G\tG\4H\tH") buf.write(u"\4I\tI\4J\tJ\4K\tK\4L\tL\4M\tM\4N\tN\4O\tO\4P\tP\4Q\t") buf.write(u"Q\4R\tR\4S\tS\4T\tT\4U\tU\4V\tV\4W\tW\4X\tX\4Y\tY\4Z") buf.write(u"\tZ\4[\t[\4\\\t\\\4]\t]\4^\t^\4_\t_\4`\t`\4a\ta\4b\t") buf.write(u"b\4c\tc\4d\td\4e\te\4f\tf\4g\tg\4h\th\4i\ti\4j\tj\4k") buf.write(u"\tk\4l\tl\4m\tm\4n\tn\4o\to\4p\tp\4q\tq\4r\tr\4s\ts\4") buf.write(u"t\tt\4u\tu\4v\tv\4w\tw\4x\tx\4y\ty\4z\tz\4{\t{\4|\t|") buf.write(u"\4}\t}\4~\t~\4\177\t\177\4\u0080\t\u0080\4\u0081\t\u0081") buf.write(u"\4\u0082\t\u0082\4\u0083\t\u0083\4\u0084\t\u0084\4\u0085") buf.write(u"\t\u0085\4\u0086\t\u0086\4\u0087\t\u0087\4\u0088\t\u0088") buf.write(u"\4\u0089\t\u0089\4\u008a\t\u008a\4\u008b\t\u008b\4\u008c") buf.write(u"\t\u008c\4\u008d\t\u008d\4\u008e\t\u008e\4\u008f\t\u008f") buf.write(u"\4\u0090\t\u0090\4\u0091\t\u0091\3\2\3\2\3\2\3\3\3\3") buf.write(u"\3\4\6\4\u012a\n\4\r\4\16\4\u012b\3\4\3\4\3\5\3\5\3\5") buf.write(u"\3\5\3\5\3\6\3\6\3\7\3\7\3\b\3\b\3\t\3\t\3\n\3\n\3\13") buf.write(u"\3\13\3\f\3\f\3\f\3\f\3\f\3\f\3\f\3\f\3\r\3\r\3\r\3\r") buf.write(u"\3\r\3\r\3\r\3\r\3\16\3\16\3\17\3\17\3\20\3\20\3\20\3") buf.write(u"\21\3\21\3\21\3\22\3\22\3\22\3\22\3\22\3\22\3\22\3\22") buf.write(u"\3\23\3\23\3\23\3\23\3\23\3\23\3\23\3\23\3\24\3\24\3") buf.write(u"\25\3\25\3\26\3\26\3\26\3\26\3\26\3\26\3\26\3\26\3\27") buf.write(u"\3\27\3\27\3\27\3\27\3\27\3\27\3\27\3\30\3\30\3\31\3") buf.write(u"\31\3\31\3\31\3\31\3\31\3\31\3\32\3\32\3\32\3\32\3\32") buf.write(u"\3\32\3\32\3\33\3\33\3\33\3\33\3\33\3\33\3\34\3\34\3") buf.write(u"\34\3\34\3\34\3\34\3\34\3\34\3\35\3\35\3\35\3\35\3\35") buf.write(u"\3\35\3\35\3\35\3\36\3\36\3\36\3\36\3\36\3\36\3\36\3") buf.write(u"\36\3\36\3\36\3\37\3\37\3\37\3\37\3\37\3\37\3\37\3\37") buf.write(u"\3\37\3\37\3 \3 \3 \3 \3 \3 \3 \3!\3!\3!\3!\3!\3!\3!") buf.write(u"\3\"\3\"\3\"\3\"\3\"\3\"\3\"\3\"\3\"\3\"\3#\3#\3#\3#") buf.write(u"\3#\3#\3#\3#\3#\3#\3$\3$\3$\3$\3$\3$\3%\3%\3%\3%\3%\3") buf.write(u"%\3%\3&\3&\3&\3&\3&\3&\3&\3\'\3\'\3\'\3\'\3\'\3\'\3\'") buf.write(u"\3\'\3(\3(\3(\3(\3(\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)") buf.write(u"\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3") buf.write(u")\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)\3)") buf.write(u"\3)\3)\3)\3)\3)\3)\3)\3)\3)\5)\u0233\n)\3*\3*\3*\3*\3") buf.write(u"*\3+\3+\3+\3+\3+\3,\3,\3,\3,\3,\3,\3-\3-\3-\3-\3-\3.") buf.write(u"\3.\3.\3.\3/\3/\3/\3/\3/\3\60\3\60\3\60\3\60\3\60\3\61") buf.write(u"\3\61\3\61\3\61\3\61\3\62\3\62\3\62\3\62\3\62\3\63\3") buf.write(u"\63\3\63\3\63\3\63\3\64\3\64\3\64\3\64\3\64\3\65\3\65") buf.write(u"\3\65\3\65\3\65\3\66\3\66\3\66\3\66\3\66\3\66\3\66\3") buf.write(u"\66\3\67\3\67\3\67\3\67\3\67\3\67\3\67\3\67\38\38\38") buf.write(u"\38\38\38\38\38\39\39\39\39\39\39\39\39\3:\3:\3:\3:\3") buf.write(u":\3:\3:\3:\3;\3;\3;\3;\3;\3;\3;\3;\3<\3<\3<\3<\3<\3<") 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buf.write(u"c\2\2\u037b\u037c\7v\2\2\u037c\u037d\7j\2\2\u037d\u037e") buf.write(u"\7k\2\2\u037e\u037f\7v\2\2\u037f\u00ba\3\2\2\2\u0380") buf.write(u"\u0381\7^\2\2\u0381\u0382\7q\2\2\u0382\u0383\7r\2\2\u0383") buf.write(u"\u0384\7g\2\2\u0384\u0385\7t\2\2\u0385\u0386\7c\2\2\u0386") buf.write(u"\u0387\7v\2\2\u0387\u0388\7q\2\2\u0388\u0389\7t\2\2\u0389") buf.write(u"\u038a\7p\2\2\u038a\u038b\7c\2\2\u038b\u038c\7o\2\2\u038c") buf.write(u"\u038d\7g\2\2\u038d\u00bc\3\2\2\2\u038e\u038f\7o\2\2") buf.write(u"\u038f\u0390\7c\2\2\u0390\u0391\7v\2\2\u0391\u0392\7") buf.write(u"t\2\2\u0392\u0393\7k\2\2\u0393\u0394\7z\2\2\u0394\u00be") buf.write(u"\3\2\2\2\u0395\u0396\7r\2\2\u0396\u0397\7o\2\2\u0397") buf.write(u"\u0398\7c\2\2\u0398\u0399\7v\2\2\u0399\u039a\7t\2\2\u039a") buf.write(u"\u039b\7k\2\2\u039b\u039c\7z\2\2\u039c\u00c0\3\2\2\2") buf.write(u"\u039d\u039e\7d\2\2\u039e\u039f\7o\2\2\u039f\u03a0\7") buf.write(u"c\2\2\u03a0\u03a1\7v\2\2\u03a1\u03a2\7t\2\2\u03a2\u03a3") buf.write(u"\7k\2\2\u03a3\u03a4\7z\2\2\u03a4\u00c2\3\2\2\2\u03a5") buf.write(u"\u03a6\7x\2\2\u03a6\u03a7\7o\2\2\u03a7\u03a8\7c\2\2\u03a8") buf.write(u"\u03a9\7v\2\2\u03a9\u03aa\7t\2\2\u03aa\u03ab\7k\2\2\u03ab") buf.write(u"\u03ac\7z\2\2\u03ac\u00c4\3\2\2\2\u03ad\u03b1\5\u00bd") buf.write(u"_\2\u03ae\u03b1\5\u00bf`\2\u03af\u03b1\5\u00c1a\2\u03b0") buf.write(u"\u03ad\3\2\2\2\u03b0\u03ae\3\2\2\2\u03b0\u03af\3\2\2") buf.write(u"\2\u03b1\u00c6\3\2\2\2\u03b2\u03b3\7^\2\2\u03b3\u03b4") buf.write(u"\7d\2\2\u03b4\u03b5\7g\2\2\u03b5\u03b6\7i\2\2\u03b6\u03b7") buf.write(u"\7k\2\2\u03b7\u03b8\7p\2\2\u03b8\u03b9\3\2\2\2\u03b9") buf.write(u"\u03ba\5\33\16\2\u03ba\u03bb\5\u00c5c\2\u03bb\u03bc\5") buf.write(u"\35\17\2\u03bc\u00c8\3\2\2\2\u03bd\u03be\7^\2\2\u03be") buf.write(u"\u03bf\7g\2\2\u03bf\u03c0\7p\2\2\u03c0\u03c1\7f\2\2\u03c1") buf.write(u"\u03c2\3\2\2\2\u03c2\u03c3\5\33\16\2\u03c3\u03c4\5\u00c5") buf.write(u"c\2\u03c4\u03c5\5\35\17\2\u03c5\u00ca\3\2\2\2\u03c6\u03c7") 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buf.write(u"\u049f\7s\2\2\u049f\u04a0\7w\2\2\u04a0\u04a1\7k\2\2\u04a1") buf.write(u"\u04a3\7x\2\2\u04a2\u049a\3\2\2\2\u04a2\u049c\3\2\2\2") buf.write(u"\u04a3\u00fe\3\2\2\2\u04a4\u04a5\7>\2\2\u04a5\u0100\3") buf.write(u"\2\2\2\u04a6\u04a7\7^\2\2\u04a7\u04a8\7n\2\2\u04a8\u04a9") buf.write(u"\7g\2\2\u04a9\u04b7\7s\2\2\u04aa\u04ab\7^\2\2\u04ab\u04ac") buf.write(u"\7n\2\2\u04ac\u04b7\7g\2\2\u04ad\u04ae\7^\2\2\u04ae\u04af") buf.write(u"\7n\2\2\u04af\u04b0\7g\2\2\u04b0\u04b1\7s\2\2\u04b1\u04b2") buf.write(u"\7u\2\2\u04b2\u04b3\7n\2\2\u04b3\u04b4\7c\2\2\u04b4\u04b5") buf.write(u"\7p\2\2\u04b5\u04b7\7v\2\2\u04b6\u04a6\3\2\2\2\u04b6") buf.write(u"\u04aa\3\2\2\2\u04b6\u04ad\3\2\2\2\u04b7\u0102\3\2\2") buf.write(u"\2\u04b8\u04b9\7@\2\2\u04b9\u0104\3\2\2\2\u04ba\u04bb") buf.write(u"\7^\2\2\u04bb\u04bc\7i\2\2\u04bc\u04bd\7g\2\2\u04bd\u04cb") buf.write(u"\7s\2\2\u04be\u04bf\7^\2\2\u04bf\u04c0\7i\2\2\u04c0\u04cb") buf.write(u"\7g\2\2\u04c1\u04c2\7^\2\2\u04c2\u04c3\7i\2\2\u04c3\u04c4") buf.write(u"\7g\2\2\u04c4\u04c5\7s\2\2\u04c5\u04c6\7u\2\2\u04c6\u04c7") buf.write(u"\7n\2\2\u04c7\u04c8\7c\2\2\u04c8\u04c9\7p\2\2\u04c9\u04cb") buf.write(u"\7v\2\2\u04ca\u04ba\3\2\2\2\u04ca\u04be\3\2\2\2\u04ca") buf.write(u"\u04c1\3\2\2\2\u04cb\u0106\3\2\2\2\u04cc\u04cd\7#\2\2") buf.write(u"\u04cd\u04e3\7?\2\2\u04ce\u04cf\7#\2\2\u04cf\u04d0\7") buf.write(u"?\2\2\u04d0\u04e3\7?\2\2\u04d1\u04d2\7^\2\2\u04d2\u04d3") buf.write(u"\7p\2\2\u04d3\u04e3\7g\2\2\u04d4\u04d5\7^\2\2\u04d5\u04d6") buf.write(u"\7p\2\2\u04d6\u04d7\7g\2\2\u04d7\u04e3\7s\2\2\u04d8\u04d9") buf.write(u"\7^\2\2\u04d9\u04da\7p\2\2\u04da\u04db\7q\2\2\u04db\u04dc") buf.write(u"\7v\2\2\u04dc\u04dd\7^\2\2\u04dd\u04de\7g\2\2\u04de\u04df") buf.write(u"\7s\2\2\u04df\u04e0\7w\2\2\u04e0\u04e1\7k\2\2\u04e1\u04e3") buf.write(u"\7x\2\2\u04e2\u04cc\3\2\2\2\u04e2\u04ce\3\2\2\2\u04e2") buf.write(u"\u04d1\3\2\2\2\u04e2\u04d4\3\2\2\2\u04e2\u04d8\3\2\2") buf.write(u"\2\u04e3\u0108\3\2\2\2\u04e4\u04e5\7#\2\2\u04e5\u010a") buf.write(u"\3\2\2\2\u04e6\u04e7\7^\2\2\u04e7\u04e8\7\'\2\2\u04e8") buf.write(u"\u010c\3\2\2\2\u04e9\u04ea\5\u00f7|\2\u04ea\u04eb\5\u010b") buf.write(u"\u0086\2\u04eb\u010e\3\2\2\2\u04ec\u04ed\7^\2\2\u04ed") buf.write(u"\u04ee\7e\2\2\u04ee\u04ef\7j\2\2\u04ef\u04f0\7c\2\2\u04f0") buf.write(u"\u04f1\7t\2\2\u04f1\u04f2\7$\2\2\u04f2\u04f3\7\62\2\2") buf.write(u"\u04f3\u04f4\7\62\2\2\u04f4\u04f5\7\62\2\2\u04f5\u04f6") buf.write(u"\7\65\2\2\u04f6\u04f7\7;\2\2\u04f7\u066e\7\63\2\2\u04f8") buf.write(u"\u04f9\7^\2\2\u04f9\u04fa\7c\2\2\u04fa\u04fb\7n\2\2\u04fb") buf.write(u"\u04fc\7r\2\2\u04fc\u04fd\7j\2\2\u04fd\u066e\7c\2\2\u04fe") buf.write(u"\u04ff\7^\2\2\u04ff\u0500\7e\2\2\u0500\u0501\7j\2\2\u0501") buf.write(u"\u0502\7c\2\2\u0502\u0503\7t\2\2\u0503\u0504\7$\2\2\u0504") buf.write(u"\u0505\7\62\2\2\u0505\u0506\7\62\2\2\u0506\u0507\7\62") buf.write(u"\2\2\u0507\u0508\7\65\2\2\u0508\u0509\7;\2\2\u0509\u066e") buf.write(u"\7\64\2\2\u050a\u050b\7^\2\2\u050b\u050c\7d\2\2\u050c") buf.write(u"\u050d\7g\2\2\u050d\u050e\7v\2\2\u050e\u066e\7c\2\2\u050f") buf.write(u"\u0510\7^\2\2\u0510\u0511\7I\2\2\u0511\u0512\7c\2\2\u0512") buf.write(u"\u0513\7o\2\2\u0513\u0514\7o\2\2\u0514\u066e\7c\2\2\u0515") buf.write(u"\u0516\7^\2\2\u0516\u0517\7i\2\2\u0517\u0518\7c\2\2\u0518") buf.write(u"\u0519\7o\2\2\u0519\u051a\7o\2\2\u051a\u066e\7c\2\2\u051b") buf.write(u"\u051c\7^\2\2\u051c\u051d\7F\2\2\u051d\u051e\7g\2\2\u051e") buf.write(u"\u051f\7n\2\2\u051f\u0520\7v\2\2\u0520\u066e\7c\2\2\u0521") buf.write(u"\u0522\7^\2\2\u0522\u0523\7f\2\2\u0523\u0524\7g\2\2\u0524") buf.write(u"\u0525\7n\2\2\u0525\u0526\7v\2\2\u0526\u066e\7c\2\2\u0527") buf.write(u"\u0528\7^\2\2\u0528\u0529\7e\2\2\u0529\u052a\7j\2\2\u052a") buf.write(u"\u052b\7c\2\2\u052b\u052c\7t\2\2\u052c\u052d\7$\2\2\u052d") buf.write(u"\u052e\7\62\2\2\u052e\u052f\7\62\2\2\u052f\u0530\7\62") buf.write(u"\2\2\u0530\u0531\7\63\2\2\u0531\u0532\7;\2\2\u0532\u066e") buf.write(u"\7\62\2\2\u0533\u0534\7^\2\2\u0534\u0535\7g\2\2\u0535") buf.write(u"\u0536\7r\2\2\u0536\u0537\7u\2\2\u0537\u0538\7k\2\2\u0538") buf.write(u"\u0539\7n\2\2\u0539\u053a\7q\2\2\u053a\u066e\7p\2\2\u053b") buf.write(u"\u053c\7^\2\2\u053c\u053d\7x\2\2\u053d\u053e\7c\2\2\u053e") buf.write(u"\u053f\7t\2\2\u053f\u0540\7g\2\2\u0540\u0541\7r\2\2\u0541") buf.write(u"\u0542\7u\2\2\u0542\u0543\7k\2\2\u0543\u0544\7n\2\2\u0544") buf.write(u"\u0545\7q\2\2\u0545\u066e\7p\2\2\u0546\u0547\7^\2\2\u0547") buf.write(u"\u0548\7e\2\2\u0548\u0549\7j\2\2\u0549\u054a\7c\2\2\u054a") buf.write(u"\u054b\7t\2\2\u054b\u054c\7$\2\2\u054c\u054d\7\62\2\2") buf.write(u"\u054d\u054e\7\62\2\2\u054e\u054f\7\62\2\2\u054f\u0550") buf.write(u"\7\65\2\2\u0550\u0551\7;\2\2\u0551\u066e\78\2\2\u0552") buf.write(u"\u0553\7^\2\2\u0553\u0554\7|\2\2\u0554\u0555\7g\2\2\u0555") buf.write(u"\u0556\7v\2\2\u0556\u066e\7c\2\2\u0557\u0558\7^\2\2\u0558") buf.write(u"\u0559\7e\2\2\u0559\u055a\7j\2\2\u055a\u055b\7c\2\2\u055b") buf.write(u"\u055c\7t\2\2\u055c\u055d\7$\2\2\u055d\u055e\7\62\2\2") buf.write(u"\u055e\u055f\7\62\2\2\u055f\u0560\7\62\2\2\u0560\u0561") buf.write(u"\7\65\2\2\u0561\u0562\7;\2\2\u0562\u066e\79\2\2\u0563") buf.write(u"\u0564\7^\2\2\u0564\u0565\7g\2\2\u0565\u0566\7v\2\2\u0566") buf.write(u"\u066e\7c\2\2\u0567\u0568\7^\2\2\u0568\u0569\7V\2\2\u0569") buf.write(u"\u056a\7j\2\2\u056a\u056b\7g\2\2\u056b\u056c\7v\2\2\u056c") buf.write(u"\u066e\7c\2\2\u056d\u056e\7^\2\2\u056e\u056f\7v\2\2\u056f") buf.write(u"\u0570\7j\2\2\u0570\u0571\7g\2\2\u0571\u0572\7v\2\2\u0572") buf.write(u"\u066e\7c\2\2\u0573\u0574\7^\2\2\u0574\u0575\7x\2\2\u0575") buf.write(u"\u0576\7c\2\2\u0576\u0577\7t\2\2\u0577\u0578\7v\2\2\u0578") buf.write(u"\u0579\7j\2\2\u0579\u057a\7g\2\2\u057a\u057b\7v\2\2\u057b") buf.write(u"\u066e\7c\2\2\u057c\u057d\7^\2\2\u057d\u057e\7e\2\2\u057e") buf.write(u"\u057f\7j\2\2\u057f\u0580\7c\2\2\u0580\u0581\7t\2\2\u0581") buf.write(u"\u0582\7$\2\2\u0582\u0583\7\62\2\2\u0583\u0584\7\62\2") buf.write(u"\2\u0584\u0585\7\62\2\2\u0585\u0586\7\65\2\2\u0586\u0587") buf.write(u"\7;\2\2\u0587\u066e\7;\2\2\u0588\u0589\7^\2\2\u0589\u058a") buf.write(u"\7k\2\2\u058a\u058b\7q\2\2\u058b\u058c\7v\2\2\u058c\u066e") buf.write(u"\7c\2\2\u058d\u058e\7^\2\2\u058e\u058f\7e\2\2\u058f\u0590") buf.write(u"\7j\2\2\u0590\u0591\7c\2\2\u0591\u0592\7t\2\2\u0592\u0593") buf.write(u"\7$\2\2\u0593\u0594\7\62\2\2\u0594\u0595\7\62\2\2\u0595") buf.write(u"\u0596\7\62\2\2\u0596\u0597\7\65\2\2\u0597\u0598\7;\2") buf.write(u"\2\u0598\u066e\7C\2\2\u0599\u059a\7^\2\2\u059a\u059b") buf.write(u"\7m\2\2\u059b\u059c\7c\2\2\u059c\u059d\7r\2\2\u059d\u059e") buf.write(u"\7r\2\2\u059e\u066e\7c\2\2\u059f\u05a0\7^\2\2\u05a0\u05a1") buf.write(u"\7N\2\2\u05a1\u05a2\7c\2\2\u05a2\u05a3\7o\2\2\u05a3\u05a4") buf.write(u"\7d\2\2\u05a4\u05a5\7f\2\2\u05a5\u066e\7c\2\2\u05a6\u05a7") buf.write(u"\7^\2\2\u05a7\u05a8\7n\2\2\u05a8\u05a9\7c\2\2\u05a9\u05aa") buf.write(u"\7o\2\2\u05aa\u05ab\7d\2\2\u05ab\u05ac\7f\2\2\u05ac\u066e") buf.write(u"\7c\2\2\u05ad\u05ae\7^\2\2\u05ae\u05af\7e\2\2\u05af\u05b0") buf.write(u"\7j\2\2\u05b0\u05b1\7c\2\2\u05b1\u05b2\7t\2\2\u05b2\u05b3") buf.write(u"\7$\2\2\u05b3\u05b4\7\62\2\2\u05b4\u05b5\7\62\2\2\u05b5") buf.write(u"\u05b6\7\62\2\2\u05b6\u05b7\7\65\2\2\u05b7\u05b8\7;\2") buf.write(u"\2\u05b8\u066e\7E\2\2\u05b9\u05ba\7^\2\2\u05ba\u05bb") buf.write(u"\7o\2\2\u05bb\u066e\7w\2\2\u05bc\u05bd\7^\2\2\u05bd\u05be") buf.write(u"\7e\2\2\u05be\u05bf\7j\2\2\u05bf\u05c0\7c\2\2\u05c0\u05c1") buf.write(u"\7t\2\2\u05c1\u05c2\7$\2\2\u05c2\u05c3\7\62\2\2\u05c3") buf.write(u"\u05c4\7\62\2\2\u05c4\u05c5\7\62\2\2\u05c5\u05c6\7\65") buf.write(u"\2\2\u05c6\u05c7\7;\2\2\u05c7\u066e\7F\2\2\u05c8\u05c9") buf.write(u"\7^\2\2\u05c9\u05ca\7p\2\2\u05ca\u066e\7w\2\2\u05cb\u05cc") buf.write(u"\7^\2\2\u05cc\u05cd\7Z\2\2\u05cd\u066e\7k\2\2\u05ce\u05cf") buf.write(u"\7^\2\2\u05cf\u05d0\7z\2\2\u05d0\u066e\7k\2\2\u05d1\u05d2") buf.write(u"\7^\2\2\u05d2\u05d3\7e\2\2\u05d3\u05d4\7j\2\2\u05d4\u05d5") buf.write(u"\7c\2\2\u05d5\u05d6\7t\2\2\u05d6\u05d7\7$\2\2\u05d7\u05d8") buf.write(u"\7\62\2\2\u05d8\u05d9\7\62\2\2\u05d9\u05da\7\62\2\2\u05da") buf.write(u"\u05db\7\65\2\2\u05db\u05dc\7;\2\2\u05dc\u066e\7H\2\2") buf.write(u"\u05dd\u05de\7^\2\2\u05de\u05df\7q\2\2\u05df\u05e0\7") buf.write(u"o\2\2\u05e0\u05e1\7k\2\2\u05e1\u05e2\7e\2\2\u05e2\u05e3") buf.write(u"\7t\2\2\u05e3\u05e4\7q\2\2\u05e4\u066e\7p\2\2\u05e5\u05e6") buf.write(u"\7^\2\2\u05e6\u05e7\7R\2\2\u05e7\u066e\7k\2\2\u05e8\u05e9") buf.write(u"\7^\2\2\u05e9\u05ea\7x\2\2\u05ea\u05eb\7c\2\2\u05eb\u05ec") buf.write(u"\7t\2\2\u05ec\u05ed\7r\2\2\u05ed\u066e\7k\2\2\u05ee\u05ef") buf.write(u"\7^\2\2\u05ef\u05f0\7e\2\2\u05f0\u05f1\7j\2\2\u05f1\u05f2") buf.write(u"\7c\2\2\u05f2\u05f3\7t\2\2\u05f3\u05f4\7$\2\2\u05f4\u05f5") buf.write(u"\7\62\2\2\u05f5\u05f6\7\62\2\2\u05f6\u05f7\7\62\2\2\u05f7") buf.write(u"\u05f8\7\65\2\2\u05f8\u05f9\7C\2\2\u05f9\u066e\7\63\2") buf.write(u"\2\u05fa\u05fb\7^\2\2\u05fb\u05fc\7t\2\2\u05fc\u05fd") buf.write(u"\7j\2\2\u05fd\u066e\7q\2\2\u05fe\u05ff\7^\2\2\u05ff\u0600") buf.write(u"\7x\2\2\u0600\u0601\7c\2\2\u0601\u0602\7t\2\2\u0602\u0603") buf.write(u"\7t\2\2\u0603\u0604\7j\2\2\u0604\u066e\7q\2\2\u0605\u0606") buf.write(u"\7^\2\2\u0606\u0607\7U\2\2\u0607\u0608\7k\2\2\u0608\u0609") buf.write(u"\7i\2\2\u0609\u060a\7o\2\2\u060a\u066e\7c\2\2\u060b\u060c") buf.write(u"\7^\2\2\u060c\u060d\7u\2\2\u060d\u060e\7k\2\2\u060e\u060f") buf.write(u"\7i\2\2\u060f\u0610\7o\2\2\u0610\u066e\7c\2\2\u0611\u0612") buf.write(u"\7^\2\2\u0612\u0613\7x\2\2\u0613\u0614\7c\2\2\u0614\u0615") buf.write(u"\7t\2\2\u0615\u0616\7u\2\2\u0616\u0617\7k\2\2\u0617\u0618") buf.write(u"\7i\2\2\u0618\u0619\7o\2\2\u0619\u066e\7c\2\2\u061a\u061b") buf.write(u"\7^\2\2\u061b\u061c\7e\2\2\u061c\u061d\7j\2\2\u061d\u061e") buf.write(u"\7c\2\2\u061e\u061f\7t\2\2\u061f\u0620\7$\2\2\u0620\u0621") buf.write(u"\7\62\2\2\u0621\u0622\7\62\2\2\u0622\u0623\7\62\2\2\u0623") buf.write(u"\u0624\7\65\2\2\u0624\u0625\7C\2\2\u0625\u066e\7\66\2") buf.write(u"\2\u0626\u0627\7^\2\2\u0627\u0628\7v\2\2\u0628\u0629") buf.write(u"\7c\2\2\u0629\u066e\7w\2\2\u062a\u062b\7^\2\2\u062b\u062c") buf.write(u"\7W\2\2\u062c\u062d\7r\2\2\u062d\u062e\7u\2\2\u062e\u062f") buf.write(u"\7k\2\2\u062f\u0630\7n\2\2\u0630\u0631\7q\2\2\u0631\u066e") buf.write(u"\7p\2\2\u0632\u0633\7^\2\2\u0633\u0634\7w\2\2\u0634\u0635") buf.write(u"\7r\2\2\u0635\u0636\7u\2\2\u0636\u0637\7k\2\2\u0637\u0638") buf.write(u"\7n\2\2\u0638\u0639\7q\2\2\u0639\u066e\7p\2\2\u063a\u063b") buf.write(u"\7^\2\2\u063b\u063c\7R\2\2\u063c\u063d\7j\2\2\u063d\u066e") buf.write(u"\7k\2\2\u063e\u063f\7^\2\2\u063f\u0640\7r\2\2\u0640\u0641") buf.write(u"\7j\2\2\u0641\u066e\7k\2\2\u0642\u0643\7^\2\2\u0643\u0644") buf.write(u"\7x\2\2\u0644\u0645\7c\2\2\u0645\u0646\7t\2\2\u0646\u0647") buf.write(u"\7r\2\2\u0647\u0648\7j\2\2\u0648\u066e\7k\2\2\u0649\u064a") buf.write(u"\7^\2\2\u064a\u064b\7e\2\2\u064b\u064c\7j\2\2\u064c\u064d") buf.write(u"\7c\2\2\u064d\u064e\7t\2\2\u064e\u064f\7$\2\2\u064f\u0650") buf.write(u"\7\62\2\2\u0650\u0651\7\62\2\2\u0651\u0652\7\62\2\2\u0652") buf.write(u"\u0653\7\65\2\2\u0653\u0654\7C\2\2\u0654\u066e\79\2\2") buf.write(u"\u0655\u0656\7^\2\2\u0656\u0657\7e\2\2\u0657\u0658\7") buf.write(u"j\2\2\u0658\u066e\7k\2\2\u0659\u065a\7^\2\2\u065a\u065b") buf.write(u"\7R\2\2\u065b\u065c\7u\2\2\u065c\u066e\7k\2\2\u065d\u065e") buf.write(u"\7^\2\2\u065e\u065f\7r\2\2\u065f\u0660\7u\2\2\u0660\u066e") buf.write(u"\7k\2\2\u0661\u0662\7^\2\2\u0662\u0663\7Q\2\2\u0663\u0664") buf.write(u"\7o\2\2\u0664\u0665\7g\2\2\u0665\u0666\7i\2\2\u0666\u066e") buf.write(u"\7c\2\2\u0667\u0668\7^\2\2\u0668\u0669\7q\2\2\u0669\u066a") buf.write(u"\7o\2\2\u066a\u066b\7g\2\2\u066b\u066c\7i\2\2\u066c\u066e") buf.write(u"\7c\2\2\u066d\u04ec\3\2\2\2\u066d\u04f8\3\2\2\2\u066d") buf.write(u"\u04fe\3\2\2\2\u066d\u050a\3\2\2\2\u066d\u050f\3\2\2") buf.write(u"\2\u066d\u0515\3\2\2\2\u066d\u051b\3\2\2\2\u066d\u0521") buf.write(u"\3\2\2\2\u066d\u0527\3\2\2\2\u066d\u0533\3\2\2\2\u066d") buf.write(u"\u053b\3\2\2\2\u066d\u0546\3\2\2\2\u066d\u0552\3\2\2") buf.write(u"\2\u066d\u0557\3\2\2\2\u066d\u0563\3\2\2\2\u066d\u0567") buf.write(u"\3\2\2\2\u066d\u056d\3\2\2\2\u066d\u0573\3\2\2\2\u066d") buf.write(u"\u057c\3\2\2\2\u066d\u0588\3\2\2\2\u066d\u058d\3\2\2") buf.write(u"\2\u066d\u0599\3\2\2\2\u066d\u059f\3\2\2\2\u066d\u05a6") buf.write(u"\3\2\2\2\u066d\u05ad\3\2\2\2\u066d\u05b9\3\2\2\2\u066d") buf.write(u"\u05bc\3\2\2\2\u066d\u05c8\3\2\2\2\u066d\u05cb\3\2\2") buf.write(u"\2\u066d\u05ce\3\2\2\2\u066d\u05d1\3\2\2\2\u066d\u05dd") buf.write(u"\3\2\2\2\u066d\u05e5\3\2\2\2\u066d\u05e8\3\2\2\2\u066d") buf.write(u"\u05ee\3\2\2\2\u066d\u05fa\3\2\2\2\u066d\u05fe\3\2\2") buf.write(u"\2\u066d\u0605\3\2\2\2\u066d\u060b\3\2\2\2\u066d\u0611") buf.write(u"\3\2\2\2\u066d\u061a\3\2\2\2\u066d\u0626\3\2\2\2\u066d") buf.write(u"\u062a\3\2\2\2\u066d\u0632\3\2\2\2\u066d\u063a\3\2\2") buf.write(u"\2\u066d\u063e\3\2\2\2\u066d\u0642\3\2\2\2\u066d\u0649") buf.write(u"\3\2\2\2\u066d\u0655\3\2\2\2\u066d\u0659\3\2\2\2\u066d") buf.write(u"\u065d\3\2\2\2\u066d\u0661\3\2\2\2\u066d\u0667\3\2\2") buf.write(u"\2\u066e\u0110\3\2\2\2\u066f\u0671\5\u010f\u0088\2\u0670") buf.write(u"\u0672\t\7\2\2\u0671\u0670\3\2\2\2\u0671\u0672\3\2\2") buf.write(u"\2\u0672\u0112\3\2\2\2\u0673\u0674\7^\2\2\u0674\u0675") buf.write(u"\7r\2\2\u0675\u0676\7k\2\2\u0676\u0114\3\2\2\2\u0677") buf.write(u"\u0678\7^\2\2\u0678\u0679\7k\2\2\u0679\u067a\7p\2\2\u067a") buf.write(u"\u067b\7h\2\2\u067b\u067c\7v\2\2\u067c\u067d\7{\2\2\u067d") buf.write(u"\u0116\3\2\2\2\u067e\u0686\5\u0115\u008b\2\u067f\u0680") buf.write(u"\5\t\5\2\u0680\u0681\5\u0115\u008b\2\u0681\u0686\3\2") buf.write(u"\2\2\u0682\u0683\5\u0115\u008b\2\u0683\u0684\5\u010b") buf.write(u"\u0086\2\u0684\u0686\3\2\2\2\u0685\u067e\3\2\2\2\u0685") buf.write(u"\u067f\3\2\2\2\u0685\u0682\3\2\2\2\u0686\u0118\3\2\2") buf.write(u"\2\u0687\u0688\7^\2\2\u0688\u0689\7g\2\2\u0689\u068a") buf.write(u"\7o\2\2\u068a\u068b\7r\2\2\u068b\u068c\7v\2\2\u068c\u068d") buf.write(u"\7{\2\2\u068d\u068e\7u\2\2\u068e\u068f\7g\2\2\u068f\u0690") buf.write(u"\7v\2\2\u0690\u011a\3\2\2\2\u0691\u0695\5\u0113\u008a") buf.write(u"\2\u0692\u0695\5\u0117\u008c\2\u0693\u0695\5\u0119\u008d") buf.write(u"\2\u0694\u0691\3\2\2\2\u0694\u0692\3\2\2\2\u0694\u0693") buf.write(u"\3\2\2\2\u0695\u011c\3\2\2\2\u0696\u0697\7^\2\2\u0697") buf.write(u"\u0698\7x\2\2\u0698\u0699\7c\2\2\u0699\u069a\7t\2\2\u069a") buf.write(u"\u069b\7k\2\2\u069b\u069c\7c\2\2\u069c\u069d\7d\2\2\u069d") buf.write(u"\u069e\7n\2\2\u069e\u069f\7g\2\2\u069f\u011e\3\2\2\2") buf.write(u"\u06a0\u06a4\5\u0111\u0089\2\u06a1\u06a4\5\u00f3z\2\u06a2") buf.write(u"\u06a4\5\u00f5{\2\u06a3\u06a0\3\2\2\2\u06a3\u06a1\3\2") buf.write(u"\2\2\u06a3\u06a2\3\2\2\2\u06a4\u06a5\3\2\2\2\u06a5\u06a3") buf.write(u"\3\2\2\2\u06a5\u06a6\3\2\2\2\u06a6\u06ba\3\2\2\2\u06a7") buf.write(u"\u06b8\5\u00ddo\2\u06a8\u06ad\5\33\16\2\u06a9\u06ae\5") buf.write(u"\u0111\u0089\2\u06aa\u06ae\5\u00f3z\2\u06ab\u06ae\5\u00f5") buf.write(u"{\2\u06ac\u06ae\5\u00e5s\2\u06ad\u06a9\3\2\2\2\u06ad") buf.write(u"\u06aa\3\2\2\2\u06ad\u06ab\3\2\2\2\u06ad\u06ac\3\2\2") buf.write(u"\2\u06ae\u06af\3\2\2\2\u06af\u06ad\3\2\2\2\u06af\u06b0") buf.write(u"\3\2\2\2\u06b0\u06b1\3\2\2\2\u06b1\u06b2\5\35\17\2\u06b2") buf.write(u"\u06b9\3\2\2\2\u06b3\u06b7\5\u0111\u0089\2\u06b4\u06b7") buf.write(u"\5\u00f3z\2\u06b5\u06b7\5\u00f5{\2\u06b6\u06b3\3\2\2") buf.write(u"\2\u06b6\u06b4\3\2\2\2\u06b6\u06b5\3\2\2\2\u06b7\u06b9") buf.write(u"\3\2\2\2\u06b8\u06a8\3\2\2\2\u06b8\u06b6\3\2\2\2\u06b9") buf.write(u"\u06bb\3\2\2\2\u06ba\u06a7\3\2\2\2\u06ba\u06bb\3\2\2") buf.write(u"\2\u06bb\u0120\3\2\2\2\u06bc\u06bd\5\u011d\u008f\2\u06bd") buf.write(u"\u06be\5\33\16\2\u06be\u06bf\5\u011f\u0090\2\u06bf\u06c1") buf.write(u"\5\35\17\2\u06c0\u06c2\5\u010b\u0086\2\u06c1\u06c0\3") buf.write(u"\2\2\2\u06c1\u06c2\3\2\2\2\u06c2\u0122\3\2\2\2$\2\u012b") buf.write(u"\u0232\u03b0\u03f7\u041d\u0442\u044a\u044c\u045c\u0469") buf.write(u"\u0472\u0478\u0482\u0489\u048b\u0491\u0496\u04a2\u04b6") buf.write(u"\u04ca\u04e2\u066d\u0671\u0685\u0694\u06a3\u06a5\u06ad") buf.write(u"\u06af\u06b6\u06b8\u06ba\u06c1\3\b\2\2") return buf.getvalue() class PSLexer(Lexer): atn = ATNDeserializer().deserialize(serializedATN()) decisionsToDFA = [ DFA(ds, i) for i, ds in enumerate(atn.decisionToState) ] T__0 = 1 T__1 = 2 WS = 3 DOLLAR_SIGN = 4 ADD = 5 SUB = 6 MUL = 7 DIV = 8 L_PAREN = 9 R_PAREN = 10 L_GROUP = 11 R_GROUP = 12 L_BRACE = 13 R_BRACE = 14 L_BRACE_VISUAL = 15 R_BRACE_VISUAL = 16 L_BRACE_CMD = 17 R_BRACE_CMD = 18 L_BRACKET = 19 R_BRACKET = 20 L_BRACK = 21 R_BRACK = 22 BAR = 23 L_VERT = 24 R_VERT = 25 VERT = 26 L_FLOOR = 27 R_FLOOR = 28 LL_CORNER = 29 LR_CORNER = 30 L_CEIL = 31 R_CEIL = 32 UL_CORNER = 33 UR_CORNER = 34 L_LEFT = 35 R_RIGHT = 36 ML_LEFT = 37 MR_RIGHT = 38 FUNC_LIM = 39 LIM_APPROACH_SYM = 40 FUNC_INT = 41 FUNC_SUM = 42 FUNC_PROD = 43 FUNC_LOG = 44 FUNC_LN = 45 FUNC_EXP = 46 FUNC_SIN = 47 FUNC_COS = 48 FUNC_TAN = 49 FUNC_CSC = 50 FUNC_SEC = 51 FUNC_COT = 52 FUNC_ARCSIN = 53 FUNC_ARCCOS = 54 FUNC_ARCTAN = 55 FUNC_ARCCSC = 56 FUNC_ARCSEC = 57 FUNC_ARCCOT = 58 FUNC_SINH = 59 FUNC_COSH = 60 FUNC_TANH = 61 FUNC_ARSINH = 62 FUNC_ARCOSH = 63 FUNC_ARTANH = 64 FUNC_ARCSINH = 65 FUNC_ARCCOSH = 66 FUNC_ARCTANH = 67 FUNC_ARSINH_NAME = 68 FUNC_ARCSINH_NAME = 69 FUNC_ARCOSH_NAME = 70 FUNC_ARCCOSH_NAME = 71 FUNC_ARTANH_NAME = 72 FUNC_ARCTANH_NAME = 73 FUNC_GCD_NAME = 74 FUNC_LCM_NAME = 75 FUNC_FLOOR_NAME = 76 FUNC_CEIL_NAME = 77 FUNC_SQRT = 78 FUNC_GCD = 79 FUNC_LCM = 80 FUNC_FLOOR = 81 FUNC_CEIL = 82 FUNC_MAX = 83 FUNC_MIN = 84 CMD_TIMES = 85 CMD_CDOT = 86 CMD_DIV = 87 CMD_FRAC = 88 CMD_BINOM = 89 CMD_CHOOSE = 90 CMD_MOD = 91 CMD_MATHIT = 92 CMD_OPERATORNAME = 93 MATRIX_TYPE_MATRIX = 94 MATRIX_TYPE_PMATRIX = 95 MATRIX_TYPE_BMATRIX = 96 MATRIX_TYPE_DET = 97 MATRIX_TYPES = 98 CMD_MATRIX_START = 99 CMD_MATRIX_END = 100 CMD_DET_START = 101 CMD_DET_END = 102 MATRIX_DEL_COL = 103 MATRIX_DEL_ROW = 104 MATRIX_XRIGHTARROW = 105 TRANSFORM_EXCHANGE = 106 ROW_OR_COL = 107 ACCENT_OVERLINE = 108 ACCENT_BAR = 109 UNDERSCORE = 110 CARET = 111 COLON = 112 SEMICOLON = 113 COMMA = 114 PERIOD = 115 DIFFERENTIAL = 116 EXP_E = 117 E_NOTATION_E = 118 LETTER_NO_E = 119 NUMBER = 120 E_NOTATION = 121 ASSIGNMENT = 122 EQUAL = 123 LT = 124 LTE = 125 GT = 126 GTE = 127 UNEQUAL = 128 BANG = 129 PERCENT_NUMBER = 130 GREEK_CMD = 131 SYMBOL = 132 VARIABLE = 133 channelNames = [ u"DEFAULT_TOKEN_CHANNEL", u"HIDDEN" ] modeNames = [ u"DEFAULT_MODE" ] literalNames = [ u"<INVALID>", u"'^T'", u"'''", u"'\\$'", u"'+'", u"'-'", u"'*'", u"'/'", u"'('", u"')'", u"'\\lgroup'", u"'\\rgroup'", u"'{'", u"'}'", u"'\\{'", u"'\\}'", u"'\\lbrace'", u"'\\rbrace'", u"'['", u"']'", u"'\\lbrack'", u"'\\rbrack'", u"'|'", u"'\\lvert'", u"'\\rvert'", u"'\\vert'", u"'\\lfloor'", u"'\\rfloor'", u"'\\llcorner'", u"'\\lrcorner'", u"'\\lceil'", u"'\\rceil'", u"'\\ulcorner'", u"'\\urcorner'", u"'\\left'", u"'\\right'", u"'\\mleft'", u"'\\mright'", u"'\\lim'", u"'\\int'", u"'\\sum'", u"'\\prod'", u"'\\log'", u"'\\ln'", u"'\\exp'", u"'\\sin'", u"'\\cos'", u"'\\tan'", u"'\\csc'", u"'\\sec'", u"'\\cot'", u"'\\arcsin'", u"'\\arccos'", u"'\\arctan'", u"'\\arccsc'", u"'\\arcsec'", u"'\\arccot'", u"'\\sinh'", u"'\\cosh'", u"'\\tanh'", u"'\\arsinh'", u"'\\arcosh'", u"'\\artanh'", u"'\\arcsinh'", u"'\\arccosh'", u"'\\arctanh'", u"'arsinh'", u"'arcsinh'", u"'arcosh'", u"'arccosh'", u"'artanh'", u"'arctanh'", u"'gcd'", u"'lcm'", u"'floor'", u"'ceil'", u"'\\sqrt'", u"'\\gcd'", u"'\\lcm'", u"'\\floor'", u"'\\ceil'", u"'\\max'", u"'\\min'", u"'\\times'", u"'\\cdot'", u"'\\div'", u"'\\frac'", u"'\\binom'", u"'\\choose'", u"'\\mod'", u"'\\mathit'", u"'\\operatorname'", u"'matrix'", u"'pmatrix'", u"'bmatrix'", u"'vmatrix'", u"'&'", u"'\\\\'", u"'\\overline'", u"'\\bar'", u"'_'", u"'^'", u"':'", u"';'", u"','", u"'.'", u"'E'", u"'='", u"'<'", u"'>'", u"'!'" ] symbolicNames = [ u"<INVALID>", u"WS", u"DOLLAR_SIGN", u"ADD", u"SUB", u"MUL", u"DIV", u"L_PAREN", u"R_PAREN", u"L_GROUP", u"R_GROUP", u"L_BRACE", u"R_BRACE", u"L_BRACE_VISUAL", u"R_BRACE_VISUAL", u"L_BRACE_CMD", u"R_BRACE_CMD", u"L_BRACKET", u"R_BRACKET", u"L_BRACK", u"R_BRACK", u"BAR", u"L_VERT", u"R_VERT", u"VERT", u"L_FLOOR", u"R_FLOOR", u"LL_CORNER", u"LR_CORNER", u"L_CEIL", u"R_CEIL", u"UL_CORNER", u"UR_CORNER", u"L_LEFT", u"R_RIGHT", u"ML_LEFT", u"MR_RIGHT", u"FUNC_LIM", u"LIM_APPROACH_SYM", u"FUNC_INT", u"FUNC_SUM", u"FUNC_PROD", u"FUNC_LOG", u"FUNC_LN", u"FUNC_EXP", u"FUNC_SIN", u"FUNC_COS", u"FUNC_TAN", u"FUNC_CSC", u"FUNC_SEC", u"FUNC_COT", u"FUNC_ARCSIN", u"FUNC_ARCCOS", u"FUNC_ARCTAN", u"FUNC_ARCCSC", u"FUNC_ARCSEC", u"FUNC_ARCCOT", u"FUNC_SINH", u"FUNC_COSH", u"FUNC_TANH", u"FUNC_ARSINH", u"FUNC_ARCOSH", u"FUNC_ARTANH", u"FUNC_ARCSINH", u"FUNC_ARCCOSH", u"FUNC_ARCTANH", u"FUNC_ARSINH_NAME", u"FUNC_ARCSINH_NAME", u"FUNC_ARCOSH_NAME", u"FUNC_ARCCOSH_NAME", u"FUNC_ARTANH_NAME", u"FUNC_ARCTANH_NAME", u"FUNC_GCD_NAME", u"FUNC_LCM_NAME", u"FUNC_FLOOR_NAME", u"FUNC_CEIL_NAME", u"FUNC_SQRT", u"FUNC_GCD", u"FUNC_LCM", u"FUNC_FLOOR", u"FUNC_CEIL", u"FUNC_MAX", u"FUNC_MIN", u"CMD_TIMES", u"CMD_CDOT", u"CMD_DIV", u"CMD_FRAC", u"CMD_BINOM", u"CMD_CHOOSE", u"CMD_MOD", u"CMD_MATHIT", u"CMD_OPERATORNAME", u"MATRIX_TYPE_MATRIX", u"MATRIX_TYPE_PMATRIX", u"MATRIX_TYPE_BMATRIX", u"MATRIX_TYPE_DET", u"MATRIX_TYPES", u"CMD_MATRIX_START", u"CMD_MATRIX_END", u"CMD_DET_START", u"CMD_DET_END", u"MATRIX_DEL_COL", u"MATRIX_DEL_ROW", u"MATRIX_XRIGHTARROW", u"TRANSFORM_EXCHANGE", u"ROW_OR_COL", u"ACCENT_OVERLINE", u"ACCENT_BAR", u"UNDERSCORE", u"CARET", u"COLON", u"SEMICOLON", u"COMMA", u"PERIOD", u"DIFFERENTIAL", u"EXP_E", u"E_NOTATION_E", u"LETTER_NO_E", u"NUMBER", u"E_NOTATION", u"ASSIGNMENT", u"EQUAL", u"LT", u"LTE", u"GT", u"GTE", u"UNEQUAL", u"BANG", u"PERCENT_NUMBER", u"GREEK_CMD", u"SYMBOL", u"VARIABLE" ] ruleNames = [ u"T__0", u"T__1", u"WS", u"DOLLAR_SIGN", u"ADD", u"SUB", u"MUL", u"DIV", u"L_PAREN", u"R_PAREN", u"L_GROUP", u"R_GROUP", u"L_BRACE", u"R_BRACE", u"L_BRACE_VISUAL", u"R_BRACE_VISUAL", u"L_BRACE_CMD", u"R_BRACE_CMD", u"L_BRACKET", u"R_BRACKET", u"L_BRACK", u"R_BRACK", u"BAR", u"L_VERT", u"R_VERT", u"VERT", u"L_FLOOR", u"R_FLOOR", u"LL_CORNER", u"LR_CORNER", u"L_CEIL", u"R_CEIL", u"UL_CORNER", u"UR_CORNER", u"L_LEFT", u"R_RIGHT", u"ML_LEFT", u"MR_RIGHT", u"FUNC_LIM", u"LIM_APPROACH_SYM", u"FUNC_INT", u"FUNC_SUM", u"FUNC_PROD", u"FUNC_LOG", u"FUNC_LN", u"FUNC_EXP", u"FUNC_SIN", u"FUNC_COS", u"FUNC_TAN", u"FUNC_CSC", u"FUNC_SEC", u"FUNC_COT", u"FUNC_ARCSIN", u"FUNC_ARCCOS", u"FUNC_ARCTAN", u"FUNC_ARCCSC", u"FUNC_ARCSEC", u"FUNC_ARCCOT", u"FUNC_SINH", u"FUNC_COSH", u"FUNC_TANH", u"FUNC_ARSINH", u"FUNC_ARCOSH", u"FUNC_ARTANH", u"FUNC_ARCSINH", u"FUNC_ARCCOSH", u"FUNC_ARCTANH", u"FUNC_ARSINH_NAME", u"FUNC_ARCSINH_NAME", u"FUNC_ARCOSH_NAME", u"FUNC_ARCCOSH_NAME", u"FUNC_ARTANH_NAME", u"FUNC_ARCTANH_NAME", u"FUNC_GCD_NAME", u"FUNC_LCM_NAME", u"FUNC_FLOOR_NAME", u"FUNC_CEIL_NAME", u"FUNC_SQRT", u"FUNC_GCD", u"FUNC_LCM", u"FUNC_FLOOR", u"FUNC_CEIL", u"FUNC_MAX", u"FUNC_MIN", u"CMD_TIMES", u"CMD_CDOT", u"CMD_DIV", u"CMD_FRAC", u"CMD_BINOM", u"CMD_CHOOSE", u"CMD_MOD", u"CMD_MATHIT", u"CMD_OPERATORNAME", u"MATRIX_TYPE_MATRIX", u"MATRIX_TYPE_PMATRIX", u"MATRIX_TYPE_BMATRIX", u"MATRIX_TYPE_DET", u"MATRIX_TYPES", u"CMD_MATRIX_START", u"CMD_MATRIX_END", u"CMD_DET_START", u"CMD_DET_END", u"MATRIX_DEL_COL", u"MATRIX_DEL_ROW", u"MATRIX_XRIGHTARROW", u"TRANSFORM_EXCHANGE", u"ROW_OR_COL", u"ACCENT_OVERLINE", u"ACCENT_BAR", u"UNDERSCORE", u"CARET", u"COLON", u"SEMICOLON", u"COMMA", u"PERIOD", u"WS_CHAR", u"DIFFERENTIAL", u"EXP_E", u"E_NOTATION_E", u"LETTER_NO_E", u"LETTER", u"DIGIT", u"NUMBER", u"E_NOTATION", u"ASSIGNMENT", u"EQUAL", u"LT", u"LTE", u"GT", u"GTE", u"UNEQUAL", u"BANG", u"PERCENT_SIGN", u"PERCENT_NUMBER", u"GREEK_LETTER", u"GREEK_CMD", u"PI", u"INFTY_CMD", u"INFTY", u"EMPTYSET", u"SYMBOL", u"VARIABLE_CMD", u"VARIABLE_SYMBOL", u"VARIABLE" ] grammarFileName = u"PS.g4" def __init__(self, input=None, output=sys.stdout): super(PSLexer, self).__init__(input, output=output) self.checkVersion("4.7.2") self._interp = LexerATNSimulator(self, self.atn, self.decisionsToDFA, PredictionContextCache()) self._actions = None self._predicates = None

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48efad98a7d9f8242a7f7682c73ca7e052674cf8

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py

Python

crawler/39drug_crawler.py

wglassly/Hylobatidae

8bb998609c510ab3f32c58f59fc3469ef330aebd

[ "Apache-2.0" ]

1

2021-02-08T07:50:45.000Z

crawler/39drug_crawler.py

wglassly/Hylobatidae

8bb998609c510ab3f32c58f59fc3469ef330aebd

[ "Apache-2.0" ]

null

crawler/39drug_crawler.py

wglassly/Hylobatidae

8bb998609c510ab3f32c58f59fc3469ef330aebd

[ "Apache-2.0" ]

null

from selenium import webdriver

15.5

30

0.870968

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48fd6b270ae36b6dc52b188cda52e30974c3c454

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py

Python

datadotworld/client/_swagger/apis/uploads_api.py

DanialBetres/data.world-py

0e3acf2be9a07c5ab62ecac9289eb662088d54c7

[ "Apache-2.0" ]

99

2017-01-23T16:24:18.000Z

2022-03-30T22:51:58.000Z

datadotworld/client/_swagger/apis/uploads_api.py

DanialBetres/data.world-py

0e3acf2be9a07c5ab62ecac9289eb662088d54c7

[ "Apache-2.0" ]

77

2017-01-26T04:33:06.000Z

2022-03-11T09:39:50.000Z

datadotworld/client/_swagger/apis/uploads_api.py

DanialBetres/data.world-py

0e3acf2be9a07c5ab62ecac9289eb662088d54c7

[ "Apache-2.0" ]

29

2017-01-25T16:55:23.000Z

2022-01-31T01:44:15.000Z

# coding: utf-8 """ data.world API data.world is designed for data and the people who work with data. From professional projects to open data, data.world helps you host and share your data, collaborate with your team, and capture context and conclusions as you work. Using this API users are able to easily access data and manage their data projects regardless of language or tool of preference. Check out our [documentation](https://dwapi.apidocs.io) for tips on how to get started, tutorials and to interact with the API right within your browser. OpenAPI spec version: 0.14.1 Contact: [email protected] Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import sys import os import re # python 2 and python 3 compatibility library from six import iteritems from ..configuration import Configuration from ..api_client import ApiClient class UploadsApi(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): config = Configuration() if api_client: self.api_client = api_client else: if not config.api_client: config.api_client = ApiClient() self.api_client = config.api_client def upload_file(self, owner, id, name, **kwargs): """ Upload file Upload one file at a time to a dataset. This endpoint expects requests of type `application/octet-stream`. For example, assuming that you want to upload a local file named `file1.csv` to a hypothetical dataset `https://data.world/awesome-user/awesome-dataset` and choose its name on data.world to be `better-name.csv`, this is what the cURL command would look like. ```bash curl \\ -H \"Authorization: Bearer <YOUR_API_TOKEN>\" \\ -X PUT -H \"Content-Type: application/octet-stream\" \\ --data-binary @file1.csv \\ https://api.data.world/v0/uploads/awesome-user/awesome-dataset/files/better-name.csv ``` This method of upload is typically not supported by Swagger clients. Other HTTP clients can be used to supply the contents of the file directly in the body of the request. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.upload_file(owner, id, name, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str owner: User name and unique identifier of the creator of a dataset or project. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required) :param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required) :param str name: File name and unique identifier within dataset. (required) :param bool expand_archive: Indicates whether a compressed file should be expanded upon upload. :return: SuccessMessage If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.upload_file_with_http_info(owner, id, name, **kwargs) else: (data) = self.upload_file_with_http_info(owner, id, name, **kwargs) return data def upload_file_with_http_info(self, owner, id, name, **kwargs): """ Upload file Upload one file at a time to a dataset. This endpoint expects requests of type `application/octet-stream`. For example, assuming that you want to upload a local file named `file1.csv` to a hypothetical dataset `https://data.world/awesome-user/awesome-dataset` and choose its name on data.world to be `better-name.csv`, this is what the cURL command would look like. ```bash curl \\ -H \"Authorization: Bearer <YOUR_API_TOKEN>\" \\ -X PUT -H \"Content-Type: application/octet-stream\" \\ --data-binary @file1.csv \\ https://api.data.world/v0/uploads/awesome-user/awesome-dataset/files/better-name.csv ``` This method of upload is typically not supported by Swagger clients. Other HTTP clients can be used to supply the contents of the file directly in the body of the request. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.upload_file_with_http_info(owner, id, name, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str owner: User name and unique identifier of the creator of a dataset or project. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required) :param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required) :param str name: File name and unique identifier within dataset. (required) :param bool expand_archive: Indicates whether a compressed file should be expanded upon upload. :return: SuccessMessage If the method is called asynchronously, returns the request thread. """ all_params = ['owner', 'id', 'name', 'expand_archive'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method upload_file" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner' is set if ('owner' not in params) or (params['owner'] is None): raise ValueError("Missing the required parameter `owner` when calling `upload_file`") # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `upload_file`") # verify the required parameter 'name' is set if ('name' not in params) or (params['name'] is None): raise ValueError("Missing the required parameter `name` when calling `upload_file`") if 'owner' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['owner']): raise ValueError("Invalid value for parameter `owner` when calling `upload_file`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`") if 'id' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['id']): raise ValueError("Invalid value for parameter `id` when calling `upload_file`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`") if 'name' in params and len(params['name']) > 128: raise ValueError("Invalid value for parameter `name` when calling `upload_file`, number of items must be less than or equal to `128`") if 'name' in params and len(params['name']) < 1: raise ValueError("Invalid value for parameter `name` when calling `upload_file`, number of items must be greater than or equal to `1`") collection_formats = {} path_params = {} if 'owner' in params: path_params['owner'] = params['owner'] if 'id' in params: path_params['id'] = params['id'] if 'name' in params: path_params['name'] = params['name'] query_params = [] if 'expand_archive' in params: query_params.append(('expandArchive', params['expand_archive'])) header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/octet-stream', '*/*']) # Authentication setting auth_settings = ['token'] return self.api_client.call_api('/uploads/{owner}/{id}/files/{name}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='SuccessMessage', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def upload_files(self, owner, id, file, **kwargs): """ Upload files Upload multiple files at once to a dataset via multipart request. This endpoint expects requests of type `multipart/form-data` and you can include one or more parts named `file`, each containing a different file to be uploaded. For example, assuming that, you want to upload two local files named `file1.csv` and `file2.csv` to a hypothetical dataset `https://data.world/awesome-user/awesome-dataset`, this is what the cURL command would look like. ```bash curl \\ -H \"Authorization: Bearer <YOUR_API_TOKEN>\" \\ -F \"[email protected]\" \\ -F \"[email protected]\" \\ https://api.data.world/v0/uploads/awesome-user/awesome-dataset/files ``` Swagger clients will limit this method of upload to one file at a time. Other HTTP clients capable of making multipart/form-data requests can be used to upload multiple files in a single request. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.upload_files(owner, id, file, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str owner: User name and unique identifier of the creator of a dataset or project. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required) :param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required) :param file file: Multipart-encoded file contents (required) :param bool expand_archives: Indicates whether compressed files should be expanded upon upload. :return: SuccessMessage If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.upload_files_with_http_info(owner, id, file, **kwargs) else: (data) = self.upload_files_with_http_info(owner, id, file, **kwargs) return data def upload_files_with_http_info(self, owner, id, file, **kwargs): """ Upload files Upload multiple files at once to a dataset via multipart request. This endpoint expects requests of type `multipart/form-data` and you can include one or more parts named `file`, each containing a different file to be uploaded. For example, assuming that, you want to upload two local files named `file1.csv` and `file2.csv` to a hypothetical dataset `https://data.world/awesome-user/awesome-dataset`, this is what the cURL command would look like. ```bash curl \\ -H \"Authorization: Bearer <YOUR_API_TOKEN>\" \\ -F \"[email protected]\" \\ -F \"[email protected]\" \\ https://api.data.world/v0/uploads/awesome-user/awesome-dataset/files ``` Swagger clients will limit this method of upload to one file at a time. Other HTTP clients capable of making multipart/form-data requests can be used to upload multiple files in a single request. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.upload_files_with_http_info(owner, id, file, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str owner: User name and unique identifier of the creator of a dataset or project. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required) :param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required) :param file file: Multipart-encoded file contents (required) :param bool expand_archives: Indicates whether compressed files should be expanded upon upload. :return: SuccessMessage If the method is called asynchronously, returns the request thread. """ all_params = ['owner', 'id', 'file', 'expand_archives'] all_params.append('callback') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method upload_files" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner' is set if ('owner' not in params) or (params['owner'] is None): raise ValueError("Missing the required parameter `owner` when calling `upload_files`") # verify the required parameter 'id' is set if ('id' not in params) or (params['id'] is None): raise ValueError("Missing the required parameter `id` when calling `upload_files`") # verify the required parameter 'file' is set if ('file' not in params) or (params['file'] is None): raise ValueError("Missing the required parameter `file` when calling `upload_files`") if 'owner' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['owner']): raise ValueError("Invalid value for parameter `owner` when calling `upload_files`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`") if 'id' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['id']): raise ValueError("Invalid value for parameter `id` when calling `upload_files`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`") collection_formats = {} path_params = {} if 'owner' in params: path_params['owner'] = params['owner'] if 'id' in params: path_params['id'] = params['id'] query_params = [] if 'expand_archives' in params: query_params.append(('expandArchives', params['expand_archives'])) header_params = {} form_params = [] local_var_files = {} if 'file' in params: local_var_files['file'] = params['file'] body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['multipart/form-data']) # Authentication setting auth_settings = ['token'] return self.api_client.call_api('/uploads/{owner}/{id}/files', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='SuccessMessage', auth_settings=auth_settings, callback=params.get('callback'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

63.019868

854

0.635771

2,420

19,032

4.902066

0.124793

0.02276

0.008092

0.030346

0.891343

0.872713

0.868583

0.856276

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0

0.005614

0.260666

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0

0.046053

0

0.125

0

null

0

1

0

null

0

6

5b1127a80b0cc97cf385c079bc30958c2c4a1653

220

py

Python

corehq/apps/export/exceptions.py

dborowiecki/commcare-hq

f2f4fa67faec09040a98502f5657444075b63f2e

[ "BSD-3-Clause" ]

null

corehq/apps/export/exceptions.py

dborowiecki/commcare-hq

f2f4fa67faec09040a98502f5657444075b63f2e

[ "BSD-3-Clause" ]

null

corehq/apps/export/exceptions.py

dborowiecki/commcare-hq

f2f4fa67faec09040a98502f5657444075b63f2e

[ "BSD-3-Clause" ]

null

class ExportAppException(Exception): pass class BadExportConfiguration(ExportAppException): pass class ExportFormValidationException(Exception): pass class ExportAsyncException(Exception): pass

11.578947

49

0.772727

16

220

10.625

0.4375

0.229412

0.211765

0

0.172727

220

18

50

12.222222

0.934066

0

0.5

0

1

0

true

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0

0.5

0

1

0

1

null

1

0

null

0

1

0

6

d2ac686e4cd80daee2a49f1281a2ec1d4a4a44ac

44

py

Python

files/DST du 05 02 2020/dsfzfdsfdsf.py

HenraL/NSI_1ereG6_Programme_Python

9f46b848fa2331daca57e5e2e11cba41da45a67f

[ "Unlicense" ]

1

2021-06-15T13:44:47.000Z

files/DST du 05 02 2020/dsfzfdsfdsf.py

HenraL/NSI_1ereG6_Programme_Python

9f46b848fa2331daca57e5e2e11cba41da45a67f

[ "Unlicense" ]

null

files/DST du 05 02 2020/dsfzfdsfdsf.py

HenraL/NSI_1ereG6_Programme_Python

9f46b848fa2331daca57e5e2e11cba41da45a67f

[ "Unlicense" ]

null

from math import* def moyer(L): average

11

17

0.681818

7

44

4.285714

1

0

0.227273

44

3

18

14.666667

0.882353

0

1

0.333333

false

0

0.333333

0

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1

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null

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0

null

0

1

0

1

0

1

0

6

d2b8d15490f0dac9ecc4e35e5758b4c6daf42318

92

py

Python

test-registry/install/f.py

NathanTP/open-lambda

63b2f51bbe1ac121d14af9a5562c547227c4d2ab

[ "Apache-2.0" ]

826

2016-06-18T04:42:13.000Z

2022-03-31T13:21:33.000Z

test-registry/install/f.py

NathanTP/open-lambda

63b2f51bbe1ac121d14af9a5562c547227c4d2ab

[ "Apache-2.0" ]

62

2016-07-14T11:10:02.000Z

2022-02-12T18:33:55.000Z

test-registry/install/f.py

NathanTP/open-lambda

63b2f51bbe1ac121d14af9a5562c547227c4d2ab

[ "Apache-2.0" ]

105

2016-06-20T15:36:22.000Z

2022-02-01T06:04:58.000Z

import requests import urllib3 # ol-install: requests def f(event): return 'imported'

11.5

22

0.728261

12

92

5.583333

0.833333

0

0.013333

0.184783

92

7

23

13.142857

0.88

0.217391

0

0.114286

0

1

0.25

false

0

0.75

0.25

1.25

0

1

0

null

0

1

0

null

0

1

0

1

0

6

d2c590031ecc997be5e225a578049279cc6848d3

67

py

Python

src/ketrics_dev_tools/command_line.py

ketrics/ketrics-dev-tools

e1231615456a6fec8f71a0134ada1ea507984bd1

[ "MIT" ]

null

src/ketrics_dev_tools/command_line.py

ketrics/ketrics-dev-tools

e1231615456a6fec8f71a0134ada1ea507984bd1

[ "MIT" ]

null

src/ketrics_dev_tools/command_line.py

ketrics/ketrics-dev-tools

e1231615456a6fec8f71a0134ada1ea507984bd1

[ "MIT" ]

null

from . import KetricsDevTools def main(): KetricsDevTools()

9.571429

29

0.701493

6

67

7.833333

0.833333

0

0.208955

67

6

30

11.166667

0.886792

0

1

0.333333

true

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

d2cda599af5afa1f5e55bab4d4b114afd37eab3e

102

py

Python

basicsr/metrics/__init__.py

yuangan/Simple-SR

630d2f9441b116620af88ff882eca4673dedc047

[ "MIT" ]

10

2021-06-24T12:03:33.000Z

2022-03-05T03:29:34.000Z

basicsr/metrics/__init__.py

yuangan/Simple-SR

630d2f9441b116620af88ff882eca4673dedc047

[ "MIT" ]

null

basicsr/metrics/__init__.py

yuangan/Simple-SR

630d2f9441b116620af88ff882eca4673dedc047

[ "MIT" ]

2

2021-07-01T09:08:40.000Z

2022-02-23T15:31:31.000Z

from .psnr_ssim import calculate_psnr, calculate_ssim __all__ = ['calculate_psnr', 'calculate_ssim']

25.5

53

0.803922

13

102

5.615385

0.461538

0.356164

0.60274

0.712329

0

0.098039

102

3

54

34

0.793478

0

0.27451

0

1

0

false

0

0.5

0

0.5

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null

1

0

1

0

null

0

1

0

6

d2d06c18b99981c89ef1b5385e853aa6a731f149

3,601

py

Python

homework/yaryna/game_hw_1.py

aodarc/LIST-010

4579a047ca1ae0266f368349ea4536c6eb367f97

[ "MIT" ]

null

homework/yaryna/game_hw_1.py

aodarc/LIST-010

4579a047ca1ae0266f368349ea4536c6eb367f97

[ "MIT" ]

4

2018-12-19T13:41:12.000Z

2019-01-14T15:11:11.000Z

homework/yaryna/game_hw_1.py

aodarc/LIST-010

4579a047ca1ae0266f368349ea4536c6eb367f97

[ "MIT" ]

null

print("Hello! This game is about emotions. Try to put letters in the correct order and create words") n=0 word = "happy" print("ypahp") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "exited" print("txidee") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "lucky" print("cyulk") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "angry" print("ynrga") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "careful" print("lfarcue") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "suprised" print("priesdur") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "glad" print("lgda") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "sleepy" print("ypeels") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "shocked" print("edcoshk") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "upset" print("utsep") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "worried" print("ordiwer") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "unpleasant" print("taalnupesn") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "pessimistic" print("esmiiisstcp") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "unhappy" print("hyaupnp") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 word = "sorry" print("rysor") for i in range(1,3): word1= input("Enter your answer:") if word1==word: print("Great!") n+=1 break else: print("Try again!") i=i+1 if n >= 13: print("Congratulations! Yor result is {} !".format(n)) elif n >= 9 and n < 13: print("It was great! Your result is {} !".format (n)) else: print("You need be more careful! Your result is {} !".format(n))

18.186869

101

0.510691

507

3,601

3.627219

0.155819

0.078303

0.04894

0.089723

0.752583

0.73192

0

0.039801

0.330186

3,601

197

102

18.279188

0.722637

0

0.786127

0

0.253541

0

1

0

false

0

0.283237

0

null

0

1

0

1

0

null

0

6

d2fd925e580d01dde531681d96e9167fe4c49ae0

98

py

Python

src/footings_idi_model/outputs/__init__.py

dustindall/idi-model

5d026f4756f03f9cb797de5a8f0c3c6d2b349ccb

[ "BSD-3-Clause" ]

2

2020-10-06T15:52:12.000Z

2020-11-30T19:07:35.000Z

src/footings_idi_model/outputs/__init__.py

dustindall/idi-model

5d026f4756f03f9cb797de5a8f0c3c6d2b349ccb

[ "BSD-3-Clause" ]

29

2020-06-28T12:22:59.000Z

2021-04-21T11:03:07.000Z

src/footings_idi_model/outputs/__init__.py

footings/footings-idi-model

5d026f4756f03f9cb797de5a8f0c3c6d2b349ccb

[ "BSD-3-Clause" ]

1

2020-06-24T09:54:46.000Z

from .active_lives import ActiveLivesValOutput from .disabled_lives import DisabledLivesValOutput

32.666667

50

0.897959

10

98

8.6

0.7

0.255814

0

0.081633

98

2

51

49

0.955556

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

d2ffa16a49ebd94da73b301b967d348825c96b17

1,029

py

Python

tests/test_vocab_tsv.py

juhoinkinen/Annif

6ac84312ce6f4fbdfbbb681a62fe218d90abde93

[ "Apache-2.0" ]

null

tests/test_vocab_tsv.py

juhoinkinen/Annif

6ac84312ce6f4fbdfbbb681a62fe218d90abde93

[ "Apache-2.0" ]

null

tests/test_vocab_tsv.py

juhoinkinen/Annif

6ac84312ce6f4fbdfbbb681a62fe218d90abde93

[ "Apache-2.0" ]

null

"""Unit tests for TSV vocabulary functionality in Annif""" from annif.corpus import SubjectIndex def test_load_tsv_uri_brackets(tmpdir): tmpfile = tmpdir.join('subjects.tsv') tmpfile.write("<http://www.yso.fi/onto/yso/p8993>\thylyt\n" + "<http://www.yso.fi/onto/yso/p9285>\tneoliittinen kausi") index = SubjectIndex.load(str(tmpfile)) assert len(index) == 2 assert index[0] == ('http://www.yso.fi/onto/yso/p8993', 'hylyt') assert index[1] == ( 'http://www.yso.fi/onto/yso/p9285', 'neoliittinen kausi') def test_load_tsv_uri_nobrackets(tmpdir): tmpfile = tmpdir.join('subjects.tsv') tmpfile.write("http://www.yso.fi/onto/yso/p8993\thylyt\n" + "http://www.yso.fi/onto/yso/p9285\tneoliittinen kausi") index = SubjectIndex.load(str(tmpfile)) assert len(index) == 2 assert index[0] == ('http://www.yso.fi/onto/yso/p8993', 'hylyt') assert index[1] == ( 'http://www.yso.fi/onto/yso/p9285', 'neoliittinen kausi')

33.193548

75

0.637512

141

1,029

4.595745

0.304965

0.08642

0.123457

0.148148

0.851852

0.799383

0

0.0454

0.186589

1,029

30

76

34.3

0.728793

0.050535

0

0.666667

0

0.399588

0

0.285714

1

0.095238

false

0

0.047619

0

0.142857

0

null

0

1

0

null

0

6

825716fe09d94125ddd537a64cc888c9fa9ae569

188

py

Python

pypy/module/itertools/test/test_ztranslation.py

olliemath/pypy

8b873bd0b8bf76075aba3d915c260789f26f5788

[ "Apache-2.0", "OpenSSL" ]

null

pypy/module/itertools/test/test_ztranslation.py

olliemath/pypy

8b873bd0b8bf76075aba3d915c260789f26f5788

[ "Apache-2.0", "OpenSSL" ]

null

pypy/module/itertools/test/test_ztranslation.py

olliemath/pypy

8b873bd0b8bf76075aba3d915c260789f26f5788

[ "Apache-2.0", "OpenSSL" ]

1

2022-03-30T11:42:37.000Z

from pypy.objspace.fake.checkmodule import checkmodule def test_checkmodule(): # itertools.compress.__next__() crashes in backendopt checkmodule('itertools', ignore=['compress'])

31.333333

57

0.771277

20

188

7

0.75

0.285714

0

0.117021

188

5

58

37.6

0.843373

0.271277

0

0.125926

0

1

0.333333

true

0

0.333333

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

827fe775c62cfee94c84955030576b61939df637

16,769

py

Python

tests/test_cookies.py

jsenecal/async-fastapi-jwt-auth

dd825f51a2e93192d4128c85b0d4a73df1a9c418

[ "MIT" ]

4

2022-02-04T08:06:32.000Z

2022-03-25T23:22:07.000Z

tests/test_cookies.py

jsenecal/async-fastapi-jwt-auth

dd825f51a2e93192d4128c85b0d4a73df1a9c418

[ "MIT" ]

null

tests/test_cookies.py

jsenecal/async-fastapi-jwt-auth

dd825f51a2e93192d4128c85b0d4a73df1a9c418

[ "MIT" ]

1

2022-02-16T16:26:27.000Z

import pytest from async_fastapi_jwt_auth import AuthJWT from async_fastapi_jwt_auth.exceptions import AuthJWTException from fastapi import FastAPI, Request, Depends from fastapi.responses import JSONResponse from fastapi.testclient import TestClient @pytest.fixture(scope='function') def client(): app = FastAPI() @app.exception_handler(AuthJWTException) def authjwt_exception_handler(request: Request, exc: AuthJWTException): return JSONResponse( status_code=exc.status_code, content={"detail": exc.message} ) @app.get('/all-token') async def all_token(Authorize: AuthJWT = Depends()): access_token = await Authorize.create_access_token(subject=1, fresh=True) refresh_token = await Authorize.create_refresh_token(subject=1) await Authorize.set_access_cookies(access_token) await Authorize.set_refresh_cookies(refresh_token) return {"msg": "all token"} @app.get('/all-token-response') async def all_token_response(Authorize: AuthJWT = Depends()): access_token = await Authorize.create_access_token(subject=1, fresh=True) refresh_token = await Authorize.create_refresh_token(subject=1) response = JSONResponse(content={"msg": "all token"}) await Authorize.set_access_cookies(access_token, response) await Authorize.set_refresh_cookies(refresh_token, response) return response @app.get('/access-token') async def access_token(Authorize: AuthJWT = Depends()): access_token = await Authorize.create_access_token(subject=1) await Authorize.set_access_cookies(access_token) return {"msg": "access token"} @app.get('/access-token-response') async def access_token_response(Authorize: AuthJWT = Depends()): access_token = await Authorize.create_access_token(subject=1) response = JSONResponse(content={"msg": "access token"}) await Authorize.set_access_cookies(access_token, response) return response @app.get('/refresh-token') async def refresh_token(Authorize: AuthJWT = Depends()): refresh_token = await Authorize.create_refresh_token(subject=1) await Authorize.set_refresh_cookies(refresh_token) return {"msg": "refresh token"} @app.get('/refresh-token-response') async def refresh_token_response(Authorize: AuthJWT = Depends()): refresh_token = await Authorize.create_refresh_token(subject=1) response = JSONResponse(content={"msg": "refresh token"}) await Authorize.set_refresh_cookies(refresh_token, response) return response @app.get('/unset-all-token') async def unset_all_token(Authorize: AuthJWT = Depends()): await Authorize.unset_jwt_cookies() return {"msg": "unset all token"} @app.get('/unset-all-token-response') async def unset_all_token_response(Authorize: AuthJWT = Depends()): response = JSONResponse(content={"msg": "unset all token"}) await Authorize.unset_jwt_cookies(response) return response @app.get('/unset-access-token') async def unset_access_token(Authorize: AuthJWT = Depends()): await Authorize.unset_access_cookies() @app.get('/unset-refresh-token') async def unset_refresh_token(Authorize: AuthJWT = Depends()): await Authorize.unset_refresh_cookies() @app.post('/jwt-optional') async def jwt_optional(Authorize: AuthJWT = Depends()): await Authorize.jwt_optional() return {"hello": await Authorize.get_jwt_subject()} @app.post('/jwt-required') async def jwt_required(Authorize: AuthJWT = Depends()): await Authorize.jwt_required() return {"hello": await Authorize.get_jwt_subject()} @app.post('/jwt-refresh') async def jwt_refresh(Authorize: AuthJWT = Depends()): await Authorize.jwt_refresh_token_required() return {"hello": await Authorize.get_jwt_subject()} @app.post('/jwt-fresh') async def jwt_fresh(Authorize: AuthJWT = Depends()): await Authorize.fresh_jwt_required() return {"hello": await Authorize.get_jwt_subject()} client = TestClient(app) return client @pytest.mark.parametrize( "url", ["/access-token", "/refresh-token", "/unset-access-token", "/unset-refresh-token"] ) def test_warning_if_cookies_not_in_token_location(url, client): @AuthJWT.load_config def get_secret_key(): return [("authjwt_secret_key", "secret")] with pytest.raises(RuntimeWarning, match=r"authjwt_token_location"): client.get(url) async def test_set_cookie_not_valid_type_max_age(Authorize): @AuthJWT.load_config def get_cookie_location(): return [("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret")] token = await Authorize.create_access_token(subject=1) with pytest.raises(TypeError, match=r"max_age"): await Authorize.set_access_cookies(token, max_age="string") with pytest.raises(TypeError, match=r"max_age"): await Authorize.set_refresh_cookies(token, max_age="string") @pytest.mark.asyncio async def test_set_unset_cookies_not_valid_type_response(Authorize): @AuthJWT.load_config def get_cookie_location(): return [("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret")] token = await Authorize.create_access_token(subject=1) with pytest.raises(TypeError, match=r"response"): await Authorize.set_access_cookies(token, response={"msg": "hello"}) with pytest.raises(TypeError, match=r"response"): await Authorize.set_refresh_cookies(token, response={"msg": "hello"}) with pytest.raises(TypeError, match=r"response"): await Authorize.unset_jwt_cookies({"msg": "hello"}) with pytest.raises(TypeError, match=r"response"): await Authorize.unset_access_cookies({"msg": "hello"}) with pytest.raises(TypeError, match=r"response"): await Authorize.unset_refresh_cookies({"msg": "hello"}) @pytest.mark.parametrize("url", ["/access-token", "/refresh-token", "/access-token-response", "/refresh-token-response"]) def test_set_cookie_csrf_protect_false(url, client): @AuthJWT.load_config def get_cookie_location(): return [ ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret"), ("authjwt_cookie_csrf_protect", False) ] cookie_key = url.split("-")[0][1:] response = client.get(url) assert response.cookies.get("csrf_{}_token".format(cookie_key)) is None @pytest.mark.parametrize("url", ["/access-token", "/refresh-token", "/access-token-response", "/refresh-token-response"]) def test_set_cookie_csrf_protect_true(url, client): @AuthJWT.load_config def get_cookie_location(): return [("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret")] cookie_key = url.split("-")[0][1:] response = client.get(url) assert response.cookies.get("csrf_{}_token".format(cookie_key)) is not None def test_unset_all_cookie(client): @AuthJWT.load_config def get_cookie_location(): return [("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret")] response = client.get('/all-token') assert response.cookies.get("access_token_cookie") is not None assert response.cookies.get("csrf_access_token") is not None assert response.cookies.get("refresh_token_cookie") is not None assert response.cookies.get("csrf_refresh_token") is not None response = client.get('/unset-all-token') assert response.cookies.get("access_token_cookie") is None assert response.cookies.get("csrf_access_token") is None assert response.cookies.get("refresh_token_cookie") is None assert response.cookies.get("csrf_refresh_token") is None def test_unset_all_cookie_response(client): @AuthJWT.load_config def get_cookie_location(): return [("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret")] response = client.get('/all-token-response') assert response.cookies.get("access_token_cookie") is not None assert response.cookies.get("csrf_access_token") is not None assert response.cookies.get("refresh_token_cookie") is not None assert response.cookies.get("csrf_refresh_token") is not None response = client.get('/unset-all-token-response') assert response.cookies.get("access_token_cookie") is None assert response.cookies.get("csrf_access_token") is None assert response.cookies.get("refresh_token_cookie") is None assert response.cookies.get("csrf_refresh_token") is None def test_custom_cookie_key(client): @AuthJWT.load_config def get_cookie_location(): return [ ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret"), ("authjwt_access_cookie_key", "access_cookie"), ("authjwt_refresh_cookie_key", "refresh_cookie"), ("authjwt_access_csrf_cookie_key", "csrf_access"), ("authjwt_refresh_csrf_cookie_key", "csrf_refresh") ] response = client.get('/all-token') assert response.cookies.get("access_cookie") is not None assert response.cookies.get("csrf_access") is not None assert response.cookies.get("refresh_cookie") is not None assert response.cookies.get("csrf_refresh") is not None response = client.get('/unset-all-token') assert response.cookies.get("access_cookie") is None assert response.cookies.get("csrf_access") is None assert response.cookies.get("refresh_cookie") is None assert response.cookies.get("csrf_refresh") is None def test_cookie_optional_protected(client): @AuthJWT.load_config def get_cookie_location(): return [("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret")] url = '/jwt-optional' # without token response = client.post(url) assert response.status_code == 200 assert response.json() == {'hello': None} # change request methods and not check csrf token @AuthJWT.load_config def change_request_methods(): return [ ("authjwt_csrf_methods", {"GET"}), ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret") ] client.get('/access-token') response = client.post(url) assert response.status_code == 200 assert response.json() == {'hello': 1} # change csrf protect to False not check csrf token @AuthJWT.load_config def change_request_csrf_protect_to_false(): return [ ("authjwt_csrf_methods", {'POST', 'PUT', 'PATCH', 'DELETE'}), ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret"), ("authjwt_cookie_csrf_protect", False) ] client.get('/access-token') response = client.post(url) assert response.status_code == 200 assert response.json() == {'hello': 1} # missing csrf token @AuthJWT.load_config def change_csrf_protect_to_true(): return [ ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret"), ("authjwt_cookie_csrf_protect", True) ] res = client.get('/access-token') csrf_token = res.cookies.get("csrf_access_token") response = client.post(url) assert response.status_code == 401 assert response.json() == {'detail': 'Missing CSRF Token'} # csrf token do not match response = client.post(url, headers={"X-CSRF-Token": "invalid"}) assert response.status_code == 401 assert response.json() == {'detail': 'CSRF double submit tokens do not match'} response = client.post(url, headers={"X-CSRF-Token": csrf_token}) assert response.status_code == 200 assert response.json() == {'hello': 1} # missing claim csrf in token @AuthJWT.load_config def change_request_csrf_protect_to_falsee(): return [ ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret"), ("authjwt_cookie_csrf_protect", False) ] client.get('/access-token') @AuthJWT.load_config def change_request_csrf_protect_to_truee(): return [("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret")] response = client.post(url, headers={"X-CSRF-Token": "invalid"}) assert response.status_code == 422 assert response.json() == {'detail': 'Missing claim: csrf'} # custom csrf header name and cookie key @AuthJWT.load_config def custom_header_name_cookie_key(): return [ ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret"), ("authjwt_access_cookie_key", "access_cookie"), ("authjwt_access_csrf_header_name", "X-CSRF") ] res = client.get('/access-token') csrf_token = res.cookies.get("csrf_access_token") # valid request response = client.post(url, headers={"X-CSRF": csrf_token}) assert response.status_code == 200 assert response.json() == {'hello': 1} @pytest.mark.parametrize("url", ["/jwt-required", "/jwt-refresh", "/jwt-fresh"]) def test_cookie_protected(url, client): # custom csrf header name and cookie key @AuthJWT.load_config def custom_header_name_cookie_key(): return [ ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret"), ("authjwt_access_cookie_key", "access_cookie"), ("authjwt_access_csrf_header_name", "X-CSRF-Access"), ("authjwt_refresh_cookie_key", "refresh_cookie"), ("authjwt_refresh_csrf_header_name", "X-CSRF-Refresh") ] res = client.get('/all-token') csrf_access = res.cookies.get("csrf_access_token") csrf_refresh = res.cookies.get("csrf_refresh_token") if url != "/jwt-refresh": response = client.post(url, headers={"X-CSRF-Access": csrf_access}) else: response = client.post(url, headers={"X-CSRF-Refresh": csrf_refresh}) assert response.status_code == 200 assert response.json() == {'hello': 1} # missing csrf token response = client.post(url) assert response.status_code == 401 assert response.json() == {'detail': 'Missing CSRF Token'} # missing cookie client.get('/unset-all-token') response = client.post(url) assert response.status_code == 401 if url != "/jwt-refresh": assert response.json() == {'detail': 'Missing cookie access_cookie'} else: assert response.json() == {'detail': 'Missing cookie refresh_cookie'} # change csrf protect to False not check csrf token @AuthJWT.load_config def change_request_csrf_protect_to_false(): return [ ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret"), ("authjwt_cookie_csrf_protect", False) ] client.get('/all-token') response = client.post(url) assert response.status_code == 200 assert response.json() == {'hello': 1} # change request methods and not check csrf token @AuthJWT.load_config def change_request_methods(): return [ ("authjwt_csrf_methods", {"GET"}), ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret"), ("authjwt_cookie_csrf_protect", True) ] response = client.post(url) assert response.status_code == 200 assert response.json() == {'hello': 1} # missing claim csrf in token @AuthJWT.load_config def change_request_methods_to_default(): return [ ("authjwt_csrf_methods", {'POST', 'PUT', 'PATCH', 'DELETE'}), ("authjwt_token_location", {'cookies'}), ("authjwt_secret_key", "secret"), ] response = client.post(url, headers={"X-CSRF-Token": "invalid"}) assert response.status_code == 422 assert response.json() == {'detail': 'Missing claim: csrf'} # csrf token do not match res = client.get('/all-token') csrf_access = res.cookies.get("csrf_access_token") csrf_refresh = res.cookies.get("csrf_refresh_token") response = client.post(url, headers={"X-CSRF-Token": "invalid"}) assert response.status_code == 401 assert response.json() == {'detail': 'CSRF double submit tokens do not match'} # valid request if url != "/jwt-refresh": response = client.post(url, headers={"X-CSRF-Token": csrf_access}) else: response = client.post(url, headers={"X-CSRF-Token": csrf_refresh}) assert response.status_code == 200 assert response.json() == {'hello': 1}

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data/extractors/__init__.py

alanwang93/ATEC2018-NLP-PyTorch

8e00c6af1d3e1db7ab4433a0587784e45f830347

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data/extractors/__init__.py

alanwang93/ATEC2018-NLP-PyTorch

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data/extractors/__init__.py

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from .extractor import Extractor from .word_embed_extractor import WordEmbedExtractor from .similarity_extractor import SimilarityExtractor from .word_bool_extractor import WordBoolExtractor from .tfidf_extractor import TFIDFExtractor

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cvstudio/view/widgets/switch_button/__init__.py

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cvstudio/view/widgets/switch_button/__init__.py

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2020-06-15T02:21:55.000Z

cvstudio/view/widgets/switch_button/__init__.py

haruiz/PytorchCvStudio

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tests/test_cbers.py

cogeotiff/rio-tiler-pds

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2022-02-21T23:35:35.000Z

tests/test_cbers.py

cogeotiff/rio-tiler-pds

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tests/test_cbers.py

cogeotiff/rio-tiler-pds

52482c80baf7fd26cf06cd2af2961cca396b20e0

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"""tests rio_tiler.sentinel2""" import os from unittest.mock import patch import pytest import rasterio from rio_tiler.errors import InvalidBandName, MissingBands, TileOutsideBounds from rio_tiler_pds.cbers.aws import CBERSReader from rio_tiler_pds.cbers.utils import sceneid_parser from rio_tiler_pds.errors import InvalidCBERSSceneId CBERS_BUCKET = os.path.join(os.path.dirname(__file__), "fixtures", "cbers-pds") # CBERS4 test scenes CBERS_MUX_SCENE = "CBERS_4_MUX_20171121_057_094_L2" CBERS_AWFI_SCENE = "CBERS_4_AWFI_20170420_146_129_L2" CBERS_PAN10M_SCENE = "CBERS_4_PAN10M_20170427_161_109_L4" CBERS_PAN5M_SCENE = "CBERS_4_PAN5M_20170425_153_114_L4" # CBERS4A test scenes CBERS_4A_MUX_SCENE = "CBERS_4A_MUX_20200808_201_137_L4" CBERS_4A_WPM_SCENE = "CBERS_4A_WPM_20200730_209_139_L4" CBERS_4A_WFI_SCENE = "CBERS_4A_WFI_20200801_221_156_L4" @pytest.fixture(autouse=True) def testing_env_var(monkeypatch): """Set fake env to make sure we don't hit AWS services.""" monkeypatch.setenv("AWS_ACCESS_KEY_ID", "jqt") monkeypatch.setenv("AWS_SECRET_ACCESS_KEY", "rde") monkeypatch.delenv("AWS_PROFILE", raising=False) monkeypatch.setenv("AWS_CONFIG_FILE", "/tmp/noconfigheere") monkeypatch.setenv("AWS_SHARED_CREDENTIALS_FILE", "/tmp/noconfighereeither") monkeypatch.setenv("GDAL_DISABLE_READDIR_ON_OPEN", "EMPTY_DIR") def mock_rasterio_open(band): """Mock rasterio Open.""" assert band.startswith("s3://cbers-pds") band = band.replace("s3://cbers-pds", CBERS_BUCKET) return rasterio.open(band) @patch("rio_tiler.io.cogeo.rasterio") def test_AWSPDS_CBERSReader_CB4_MUX(rio): """Should work as expected (get bounds)""" rio.open = mock_rasterio_open scene = "CBERS_4_MUX_20171121_057_094" with pytest.raises(InvalidCBERSSceneId): with CBERSReader(scene): pass with CBERSReader(CBERS_MUX_SCENE) as cbers: bounds = cbers.bounds assert cbers.scene_params.get("scene") == CBERS_MUX_SCENE assert len(bounds) == 4 assert cbers.minzoom assert cbers.maxzoom assert cbers.bands == ("B5", "B6", "B7", "B8") with pytest.raises(MissingBands): cbers.info() with pytest.raises(InvalidBandName): cbers.info(bands="BAND5") metadata = cbers.info(bands="B5") assert len(metadata["band_metadata"]) == 1 assert metadata["band_descriptions"] == [("B5", "")] metadata = cbers.info(bands=cbers.bands) assert len(metadata["band_metadata"]) == 4 assert metadata["band_descriptions"] == [ ("B5", ""), ("B6", ""), ("B7", ""), ("B8", ""), ] with pytest.raises(MissingBands): cbers.stats() stats = cbers.stats(bands="B5") assert len(stats.items()) == 1 assert stats["B5"]["percentiles"] == [28, 98] stats = cbers.stats(bands=cbers.bands, hist_options={"bins": 20}) assert len(stats["B5"]["histogram"][0]) == 20 with pytest.raises(MissingBands): cbers.metadata() metadata = cbers.metadata(bands="B5") assert metadata["statistics"]["B5"]["percentiles"] == [28, 98] metadata = cbers.metadata(bands=cbers.bands) assert metadata["statistics"]["B5"]["percentiles"] == [28, 98] assert len(metadata["band_metadata"]) == 4 assert metadata["band_descriptions"] == [ ("B5", ""), ("B6", ""), ("B7", ""), ("B8", ""), ] tile_z = 10 tile_x = 664 tile_y = 495 data, mask = cbers.tile(tile_x, tile_y, tile_z, bands=cbers.scene_params["rgb"]) assert data.shape == (3, 256, 256) assert mask.shape == (256, 256) tile_z = 10 tile_x = 694 tile_y = 495 with pytest.raises(TileOutsideBounds): cbers.tile(tile_x, tile_y, tile_z, bands=cbers.scene_params["rgb"]) tile_z = 10 tile_x = 664 tile_y = 495 data, mask = cbers.tile( tile_x, tile_y, tile_z, expression="B8*0.8, B7*1.1, B6*0.8" ) assert data.shape == (3, 256, 256) assert mask.shape == (256, 256) @patch("rio_tiler.io.cogeo.rasterio") def test_AWSPDS_CBERSReader_CB4_AWFI(rio): """Should work as expected (get bounds)""" rio.open = mock_rasterio_open with CBERSReader(CBERS_AWFI_SCENE) as cbers: bounds = cbers.bounds assert cbers.scene_params.get("scene") == CBERS_AWFI_SCENE assert len(bounds) == 4 assert cbers.minzoom assert cbers.maxzoom assert cbers.bands == ("B13", "B14", "B15", "B16") tile_z = 10 tile_x = 401 tile_y = 585 data, mask = cbers.tile(tile_x, tile_y, tile_z, bands=cbers.scene_params["rgb"]) assert data.shape == (3, 256, 256) assert mask.shape == (256, 256) @patch("rio_tiler.io.cogeo.rasterio") def test_AWSPDS_CBERSReader_CB4_PAN10M(rio): """Should work as expected (get bounds)""" rio.open = mock_rasterio_open with CBERSReader(CBERS_PAN10M_SCENE) as cbers: bounds = cbers.bounds assert cbers.scene_params.get("scene") == CBERS_PAN10M_SCENE assert len(bounds) == 4 assert cbers.minzoom assert cbers.maxzoom assert cbers.bands == ("B2", "B3", "B4") tile_z = 10 tile_x = 370 tile_y = 535 data, mask = cbers.tile(tile_x, tile_y, tile_z, bands=cbers.scene_params["rgb"]) assert data.shape == (3, 256, 256) assert mask.shape == (256, 256) @patch("rio_tiler.io.cogeo.rasterio") def test_AWSPDS_CBERSReader_CB4_PAN5M(rio): """Should work as expected (get bounds)""" rio.open = mock_rasterio_open with CBERSReader(CBERS_PAN5M_SCENE) as cbers: bounds = cbers.bounds assert cbers.scene_params.get("scene") == CBERS_PAN5M_SCENE assert len(bounds) == 4 assert cbers.minzoom assert cbers.maxzoom assert cbers.bands == ("B1",) tile_z = 10 tile_x = 390 tile_y = 547 data, mask = cbers.tile(tile_x, tile_y, tile_z, bands=cbers.scene_params["rgb"]) assert data.shape == (3, 256, 256) assert mask.shape == (256, 256) @patch("rio_tiler.io.cogeo.rasterio") def test_AWSPDS_CBERSReader_CB4A_MUX(rio): """Should work as expected (get bounds)""" rio.open = mock_rasterio_open with CBERSReader(CBERS_4A_MUX_SCENE) as cbers: bounds = cbers.bounds assert cbers.scene_params.get("scene") == CBERS_4A_MUX_SCENE assert len(bounds) == 4 assert cbers.minzoom assert cbers.maxzoom assert cbers.bands == ("B5", "B6", "B7", "B8") with pytest.raises(MissingBands): cbers.info() with pytest.raises(InvalidBandName): cbers.info(bands="BAND5") metadata = cbers.info(bands="B5") assert len(metadata["band_metadata"]) == 1 assert metadata["band_descriptions"] == [("B5", "")] metadata = cbers.info(bands=cbers.bands) assert len(metadata["band_metadata"]) == 4 assert metadata["band_descriptions"] == [ ("B5", ""), ("B6", ""), ("B7", ""), ("B8", ""), ] with pytest.raises(MissingBands): cbers.stats() stats = cbers.stats(bands="B5") assert len(stats.items()) == 1 assert stats["B5"]["percentiles"] == [30, 52] stats = cbers.stats(bands=cbers.bands, hist_options=dict(bins=20)) assert len(stats["B5"]["histogram"][0]) == 20 with pytest.raises(MissingBands): cbers.metadata() metadata = cbers.metadata(bands="B5") assert metadata["statistics"]["B5"]["percentiles"] == [30, 52] metadata = cbers.metadata(bands=cbers.bands) assert metadata["statistics"]["B5"]["percentiles"] == [30, 52] assert len(metadata["band_metadata"]) == 4 assert metadata["band_descriptions"] == [ ("B5", ""), ("B6", ""), ("B7", ""), ("B8", ""), ] tile_z = 10 tile_x = 385 tile_y = 567 data, mask = cbers.tile(tile_x, tile_y, tile_z, bands=cbers.scene_params["rgb"]) assert data.shape == (3, 256, 256) assert mask.shape == (256, 256) tile_z = 10 tile_x = 694 tile_y = 495 with pytest.raises(TileOutsideBounds): cbers.tile(tile_x, tile_y, tile_z, bands=cbers.scene_params["rgb"]) tile_z = 10 tile_x = 385 tile_y = 567 data, mask = cbers.tile( tile_x, tile_y, tile_z, expression="B8*0.8, B7*1.1, B6*0.8" ) assert data.shape == (3, 256, 256) assert mask.shape == (256, 256) @patch("rio_tiler.io.cogeo.rasterio") def test_AWSPDS_CBERSReader_CB4A_WPM(rio): """Should work as expected (get bounds)""" rio.open = mock_rasterio_open with CBERSReader(CBERS_4A_WPM_SCENE) as cbers: bounds = cbers.bounds assert cbers.scene_params.get("scene") == CBERS_4A_WPM_SCENE assert len(bounds) == 4 assert cbers.minzoom assert cbers.maxzoom assert cbers.bands == ("B0", "B1", "B2", "B3", "B4") tile_z = 10 tile_x = 366 tile_y = 572 data, mask = cbers.tile(tile_x, tile_y, tile_z, bands=cbers.scene_params["rgb"]) assert data.shape == (3, 256, 256) assert mask.shape == (256, 256) @patch("rio_tiler.io.cogeo.rasterio") def test_AWSPDS_CBERSReader_CB4A_WFI(rio): """Should work as expected (get bounds)""" rio.open = mock_rasterio_open with CBERSReader(CBERS_4A_WFI_SCENE) as cbers: bounds = cbers.bounds assert cbers.scene_params.get("scene") == CBERS_4A_WFI_SCENE assert len(bounds) == 4 assert cbers.minzoom assert cbers.maxzoom assert cbers.bands == ("B13", "B14", "B15", "B16") tile_z = 10 tile_x = 316 tile_y = 614 data, mask = cbers.tile(tile_x, tile_y, tile_z, bands=cbers.scene_params["rgb"]) assert data.shape == (3, 256, 256) assert mask.shape == (256, 256) def test_cbers_id_valid(): """Parse valid CBERS sceneids and return metadata.""" scene = "CBERS_4_MUX_20171121_057_094_L2" expected_content = { "satellite": "CBERS", "mission": "4", "instrument": "MUX", "acquisitionYear": "2017", "acquisitionMonth": "11", "acquisitionDay": "21", "path": "057", "row": "094", "processingCorrectionLevel": "L2", "scene": "CBERS_4_MUX_20171121_057_094_L2", "date": "2017-11-21", "reference_band": "B6", "bands": ("B5", "B6", "B7", "B8"), "rgb": ("B7", "B6", "B5"), } assert sceneid_parser(scene) == expected_content scene = "CBERS_4_AWFI_20171121_057_094_L2" expected_content = { "satellite": "CBERS", "mission": "4", "instrument": "AWFI", "acquisitionYear": "2017", "acquisitionMonth": "11", "acquisitionDay": "21", "path": "057", "row": "094", "processingCorrectionLevel": "L2", "scene": "CBERS_4_AWFI_20171121_057_094_L2", "date": "2017-11-21", "reference_band": "B14", "bands": ("B13", "B14", "B15", "B16"), "rgb": ("B15", "B14", "B13"), } assert sceneid_parser(scene) == expected_content scene = "CBERS_4_PAN10M_20171121_057_094_L2" expected_content = { "satellite": "CBERS", "mission": "4", "instrument": "PAN10M", "acquisitionYear": "2017", "acquisitionMonth": "11", "acquisitionDay": "21", "path": "057", "row": "094", "processingCorrectionLevel": "L2", "scene": "CBERS_4_PAN10M_20171121_057_094_L2", "date": "2017-11-21", "reference_band": "B4", "bands": ("B2", "B3", "B4"), "rgb": ("B3", "B4", "B2"), } assert sceneid_parser(scene) == expected_content scene = "CBERS_4_PAN5M_20171121_057_094_L2" expected_content = { "satellite": "CBERS", "mission": "4", "instrument": "PAN5M", "acquisitionYear": "2017", "acquisitionMonth": "11", "acquisitionDay": "21", "path": "057", "row": "094", "processingCorrectionLevel": "L2", "scene": "CBERS_4_PAN5M_20171121_057_094_L2", "date": "2017-11-21", "reference_band": "B1", "bands": ("B1",), "rgb": ("B1", "B1", "B1"), } scene = "CBERS_4A_MUX_20200808_201_137_L4" expected_content = { "satellite": "CBERS", "mission": "4A", "instrument": "MUX", "acquisitionYear": "2020", "acquisitionMonth": "08", "acquisitionDay": "08", "path": "201", "row": "137", "processingCorrectionLevel": "L4", "scene": "CBERS_4A_MUX_20200808_201_137_L4", "date": "2020-08-08", "reference_band": "B6", "bands": ("B5", "B6", "B7", "B8"), "rgb": ("B7", "B6", "B5"), } # Same as above testing 2A and 2B levels scene = "CBERS_4A_MUX_20200808_201_137_L2A" expected_content = { "satellite": "CBERS", "mission": "4A", "instrument": "MUX", "acquisitionYear": "2020", "acquisitionMonth": "08", "acquisitionDay": "08", "path": "201", "row": "137", "processingCorrectionLevel": "L2A", "scene": "CBERS_4A_MUX_20200808_201_137_L2A", "date": "2020-08-08", "reference_band": "B6", "bands": ("B5", "B6", "B7", "B8"), "rgb": ("B7", "B6", "B5"), } assert sceneid_parser(scene) == expected_content scene = "CBERS_4A_WFI_20200801_221_156_L4" expected_content = { "satellite": "CBERS", "mission": "4A", "instrument": "WFI", "acquisitionYear": "2020", "acquisitionMonth": "08", "acquisitionDay": "01", "path": "221", "row": "156", "processingCorrectionLevel": "L4", "scene": "CBERS_4A_WFI_20200801_221_156_L4", "date": "2020-08-01", "reference_band": "B14", "bands": ("B13", "B14", "B15", "B16"), "rgb": ("B15", "B14", "B13"), } assert sceneid_parser(scene) == expected_content scene = "CBERS_4A_WPM_20200730_209_139_L4" expected_content = { "satellite": "CBERS", "mission": "4A", "instrument": "WPM", "acquisitionYear": "2020", "acquisitionMonth": "07", "acquisitionDay": "30", "path": "209", "row": "139", "processingCorrectionLevel": "L4", "scene": "CBERS_4A_WPM_20200730_209_139_L4", "date": "2020-07-30", "reference_band": "B2", "bands": ("B0", "B1", "B2", "B3", "B4"), "rgb": ("B3", "B2", "B1"), } assert sceneid_parser(scene) == expected_content

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Python

Python3/Lists/nested_comprehension.py

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Python3/Lists/nested_comprehension.py

norbertosanchezdichi/TIL

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[ "MIT" ]

null

Python3/Lists/nested_comprehension.py

norbertosanchezdichi/TIL

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nested_list = [list(range(1,4)), list(range(4,7)), list(range(8,10))] print(f'{nested_list =}') print(f'{[[single_list for single_list in nested_list] for single_list in nested_list] =}') print(f'{[["X" if num % 2 == 0 else "O" for num in range(1,4)] for num in range(1,4)] =}')

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Python_Birds/01_Programacao_Procedural/03_Modularizacao/debug.py

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Python_Birds/01_Programacao_Procedural/03_Modularizacao/debug.py

Miyake-Diogo/Python_Pro

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# Modularização # Debug # coloque os breakpoints onde se quer executar def soma(parcela1, parcela2): return parcela1 + parcela2 print(soma(1,2))

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cgivar2gvcf/__main__.py

madprime/cgivar2gvcf

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[ "MIT" ]

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2016-04-28T16:46:40.000Z

2021-08-14T18:55:50.000Z

cgivar2gvcf/__main__.py

madprime/cgivar2gvcf

13b4cd8da08669f7e4b0ceed77a7a17082f91037

[ "MIT" ]

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2015-12-31T21:26:38.000Z

2016-01-26T20:23:24.000Z

cgivar2gvcf/__main__.py

madprime/cgivar2vcf

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[ "MIT" ]

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from cgivar2gvcf import from_command_line from_command_line()

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marge/tests/__init__.py

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marge/tests/__init__.py

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marge/tests/__init__.py

FirstDraftGIS/marge

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from .cleaner import * from .models import * from .utils import *

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Python

urlrouter/models.py

mikespub-archive/wkornewald-allbuttonspressed

57adb0de9a61b8abec80e678b6589f6a5a3131b5

[ "BSD-3-Clause" ]

null

urlrouter/models.py

mikespub-archive/wkornewald-allbuttonspressed

57adb0de9a61b8abec80e678b6589f6a5a3131b5

[ "BSD-3-Clause" ]

null

urlrouter/models.py

mikespub-archive/wkornewald-allbuttonspressed

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[ "BSD-3-Clause" ]

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from . import api from django.db import models class URLRoute(models.Model): url = models.CharField(primary_key=True, max_length=256) handler = models.CharField(max_length=64) target = models.CharField(max_length=64, null=True)

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code/3_1_4.py

yuanyaaa/StimulateRandomProcess

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code/3_1_4.py

yuanyaaa/StimulateRandomProcess

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code/3_1_4.py

yuanyaaa/StimulateRandomProcess

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[ "Apache-2.0" ]

null

import numpy as np import random import matplotlib.pyplot as plt from mpl_toolkits.axes_grid1.inset_locator import mark_inset from mpl_toolkits.axes_grid1.inset_locator import inset_axes class MatchTurn: def __init__(self): self.epochs = [100, 1000, 10000] self.nrange = 51 self.E_Rn_x = [[], [], []] self.E_Rn_y = [[], [], []] # print(self.E_Rn_x) def Q1(self): for n in range(2, self.nrange): print(n) for e_index, epoch in enumerate(self.epochs): print(e_index, epoch) average_Rn = 0 for i in range(epoch): init = [i for i in range(0, n)] # print(init) iter_nums = 0 # print(len(init)) while len(init) != 0: old_init = init.copy() # print('old', old_init) random.shuffle(init) # print(init) init = [old_init[i] for i in range(len(init)) if init[i] != old_init[i]] iter_nums += 1 # print(init) average_Rn += iter_nums / epoch self.E_Rn_x[e_index].append(n) self.E_Rn_y[e_index].append(average_Rn) x = range(2, self.nrange) y = [x_ for x_ in x] fig, ax = plt.subplots(1, 1) handle_1, = plt.plot(x, y, lw=6, color='navajowhite') handle_2, = plt.plot(self.E_Rn_x[0], self.E_Rn_y[0], color='tomato', linestyle='--') handle_3, = plt.plot(self.E_Rn_x[1], self.E_Rn_y[1], color='violet', linestyle='--') handle_4, = plt.plot(self.E_Rn_x[2], self.E_Rn_y[2], color='aqua', linestyle='--') ax.legend(handles=[handle_1, handle_2, handle_3, handle_4], labels=[' Theoretical value ', 'simulate: epoch=100', 'simulate: epoch=1000', 'simulate: epoch=10000'], loc='best') # plt.plot(self.E_Rn_x, self.E_Rn_y) # 嵌入绘制局部放大图的坐标系 axins = inset_axes(ax, width="40%", height="30%", loc='lower left', bbox_to_anchor=(0.5, 0.1, 1, 1), bbox_transform=ax.transAxes) axins.plot(x, y, lw=6, color='navajowhite') axins.plot(self.E_Rn_x[0], self.E_Rn_y[0], color='tomato', linestyle='--') axins.plot(self.E_Rn_x[1], self.E_Rn_y[1], color='violet', linestyle='--') axins.plot(self.E_Rn_x[2], self.E_Rn_y[2], color='aqua', linestyle='--') # 设置放大区间 zone_left = 45 zone_right = 47 # 坐标轴的扩展比例（根据实际数据调整） x_ratio = 0.5 # x轴显示范围的扩展比例 y_ratio = 1 # y轴显示范围的扩展比例 # X轴的显示范围 xlim0 = x[zone_left] - (x[zone_right] - x[zone_left]) * x_ratio xlim1 = x[zone_right] + (x[zone_right] - x[zone_left]) * x_ratio # Y轴的显示范围 y = np.hstack((self.E_Rn_y[2][zone_left:zone_right], self.E_Rn_y[2][zone_left:zone_right])) ylim0 = np.min(y) - (np.max(y) - np.min(y)) * y_ratio ylim1 = np.max(y) + (np.max(y) - np.min(y)) * y_ratio # 调整子坐标系的显示范围 axins.set_xlim(xlim0, xlim1) axins.set_ylim(ylim0, ylim1) # 建立父坐标系与子坐标系的连接线 # loc1 loc2: 坐标系的四个角 # 1 (右上) 2 (左上) 3(左下) 4(右下) mark_inset(ax, axins, loc1=3, loc2=1, fc="none", ec='k', lw=1) self.plot_config(True, 'Num of People', 'E(Rn)', 'E(Rn)', '3_14_1_epoch10000.pdf') plt.savefig('3_14_1_epoch.pdf') def Q2(self): for n in range(2, self.nrange): print(n) for e_index, epoch in enumerate(self.epochs): print(e_index, epoch) average_Sn = 0 for i in range(epoch): init = [i for i in range(0, n)] iter_nums = 0 while len(init) != 0: old_init = init.copy() iter_nums += len(old_init) random.shuffle(init) init = [old_init[i] for i in range(len(init)) if init[i] != old_init[i]] average_Sn += iter_nums / epoch self.E_Rn_x[e_index].append(n) self.E_Rn_y[e_index].append(average_Sn) fig, ax = plt.subplots(1, 1) x = range(2, self.nrange) y = [x_ + x_ * x_ / 2 for x_ in x] handle_1, = plt.plot(x, y, lw=6, color='navajowhite') handle_2, = plt.plot(self.E_Rn_x[0], self.E_Rn_y[0], color='tomato', linestyle='--') handle_3, = plt.plot(self.E_Rn_x[1], self.E_Rn_y[1], color='violet', linestyle='--') handle_4, = plt.plot(self.E_Rn_x[2], self.E_Rn_y[2], color='aqua', linestyle='--') ax.legend(handles=[handle_1, handle_2, handle_3, handle_4], labels=[' Theoretical value ', 'simulate: epoch=100', 'simulate: epoch=1000', 'simulate: epoch=10000'], loc='best') self.plot_config(True, 'Num of People', 'E(Sn)', 'E(Sn)', '3_14_2_epoch.pdf') # plt.plot(self.E_Rn_x, self.E_Rn_y) # 嵌入绘制局部放大图的坐标系 axins = inset_axes(ax, width="40%", height="30%", loc='lower left', bbox_to_anchor=(0.5, 0.1, 1, 1), bbox_transform=ax.transAxes) axins.plot(x, y, lw=6, color='navajowhite') axins.plot(self.E_Rn_x[0], self.E_Rn_y[0], color='tomato', linestyle='--') axins.plot(self.E_Rn_x[1], self.E_Rn_y[1], color='violet', linestyle='--') axins.plot(self.E_Rn_x[2], self.E_Rn_y[2], color='aqua', linestyle='--') # 设置放大区间 zone_left = 45 zone_right = 47 # 坐标轴的扩展比例（根据实际数据调整） x_ratio = 0.5 # x轴显示范围的扩展比例 y_ratio = 1 # y轴显示范围的扩展比例 # X轴的显示范围 xlim0 = x[zone_left] - (x[zone_right] - x[zone_left]) * x_ratio xlim1 = x[zone_right] + (x[zone_right] - x[zone_left]) * x_ratio # Y轴的显示范围 y = np.hstack((self.E_Rn_y[2][zone_left:zone_right], self.E_Rn_y[2][zone_left:zone_right])) ylim0 = np.min(y) - (np.max(y) - np.min(y)) * y_ratio ylim1 = np.max(y) + (np.max(y) - np.min(y)) * y_ratio # 调整子坐标系的显示范围 axins.set_xlim(xlim0, xlim1) axins.set_ylim(ylim0, ylim1) # 建立父坐标系与子坐标系的连接线 # loc1 loc2: 坐标系的四个角 # 1 (右上) 2 (左上) 3(左下) 4(右下) mark_inset(ax, axins, loc1=3, loc2=1, fc="none", ec='k', lw=1) # plt.gca().add_artist(l1) self.plot_config(True, 'Num of People', 'E(Sn)', 'E(Sn)', '3_14_2_epoch100.pdf') plt.savefig('3_14_2_epoch.pdf') def Q3(self): for n in range(2, self.nrange): average_Cn = 0 print(n) for i in range(self.epoch): init = [i for i in range(0, n)] iter_nums = 0 while len(init) != 0: old_init = init.copy() random.shuffle(init) init = [old_init[i] for i in range(len(init)) if init[i] != old_init[i]] iter_nums += len(init) average_Cn += iter_nums / self.epoch / n self.E_Rn_x.append(n) self.E_Rn_y.append(average_Cn) fig, ax = plt.subplots(1, 1) x = range(2, self.nrange) y = [x_ / 2 for x_ in x] handle_1, = ax.plot(x, y, lw=6, color='thistle') handle_2, = ax.plot(self.E_Rn_x, self.E_Rn_y, color='darkslategray') self.plot_config(True, 'Num of People', 'E(Cn)', 'E(Cn)', '3_14_3_epoch' + str(self.epoch) + '.pdf') # plt.show() plt.legend(handles=[handle_1, handle_2], labels=['n/2', 'E(Cn)'], loc='best') # plt.savefig('test.pdf') # plt.plot(self.E_Rn_x, self.E_Rn_y) # 嵌入绘制局部放大图的坐标系 axins = inset_axes(ax, width="40%", height="30%", loc='lower left', bbox_to_anchor=(0.5, 0.1, 1, 1), bbox_transform=ax.transAxes) axins.plot(x, y, lw=6, color='thistle') axins.plot(self.E_Rn_x, self.E_Rn_y, color='darkslategray') # 设置放大区间 zone_left = 45 zone_right = 47 # 坐标轴的扩展比例（根据实际数据调整） x_ratio = 0.5 # x轴显示范围的扩展比例 y_ratio = 1 # y轴显示范围的扩展比例 # X轴的显示范围 xlim0 = x[zone_left] - (x[zone_right] - x[zone_left]) * x_ratio xlim1 = x[zone_right] + (x[zone_right] - x[zone_left]) * x_ratio # Y轴的显示范围 y = np.hstack((self.E_Rn_y[zone_left:zone_right], self.E_Rn_y[zone_left:zone_right])) ylim0 = np.min(y) - (np.max(y) - np.min(y)) * y_ratio ylim1 = np.max(y) + (np.max(y) - np.min(y)) * y_ratio # 调整子坐标系的显示范围 axins.set_xlim(xlim0, xlim1) axins.set_ylim(ylim0, ylim1) # 建立父坐标系与子坐标系的连接线 # loc1 loc2: 坐标系的四个角 # 1 (右上) 2 (左上) 3(左下) 4(右下) mark_inset(ax, axins, loc1=3, loc2=1, fc="none", ec='k', lw=1) # plt.gca().add_artist(l1) self.plot_config(True, 'Num of People', 'E(Cn)', 'E(Cn)', '3_14_3.png') plt.savefig('3_14_3_epoch' + str(self.epoch) + '.pdf') def plot_config(self, grid: bool, xlabel: str, ylabel: str, title: str, fig: str): if grid: plt.grid(linestyle='-.') plt.xlabel(xlabel) plt.ylabel(ylabel) plt.title(title) # plt.savefig(fig) # plt.show() if __name__ == '__main__': match_turn = MatchTurn() match_turn.Q2()

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6

c4d54df565b046e7b2fdc20d348d5002bc59e5bb

17,391

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Python

watertap/unit_models/zero_order/tests/test_uv_aop_zo.py

dangunter/watertap

5fe94e4c27dc1ae9e2872960e4183dccadd42d8e

[ "BSD-3-Clause-LBNL" ]

null

watertap/unit_models/zero_order/tests/test_uv_aop_zo.py

dangunter/watertap

5fe94e4c27dc1ae9e2872960e4183dccadd42d8e

[ "BSD-3-Clause-LBNL" ]

null

watertap/unit_models/zero_order/tests/test_uv_aop_zo.py

dangunter/watertap

5fe94e4c27dc1ae9e2872960e4183dccadd42d8e

[ "BSD-3-Clause-LBNL" ]

null

############################################################################### # WaterTAP Copyright (c) 2021, The Regents of the University of California, # through Lawrence Berkeley National Laboratory, Oak Ridge National # Laboratory, National Renewable Energy Laboratory, and National Energy # Technology Laboratory (subject to receipt of any required approvals from # the U.S. Dept. of Energy). All rights reserved. # # Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license # information, respectively. These files are also available online at the URL # "https://github.com/watertap-org/watertap/" # ############################################################################### """ Tests for zero-order UV-AOP model """ import pytest from io import StringIO from pyomo.environ import ( check_optimal_termination, ConcreteModel, Constraint, value, Var, Block) from pyomo.util.check_units import assert_units_consistent from idaes.core import FlowsheetBlock from idaes.core.util import get_solver from idaes.core.util.model_statistics import degrees_of_freedom from idaes.core.util.testing import initialization_tester from idaes.generic_models.costing import UnitModelCostingBlock from watertap.unit_models.zero_order import UVAOPZO from watertap.core.wt_database import Database from watertap.core.zero_order_properties import WaterParameterBlock from watertap.core.zero_order_costing import ZeroOrderCosting solver = get_solver() class TestUVAOPZO_with_default_removal: @pytest.fixture(scope="class") def model(self): m = ConcreteModel() m.db = Database() m.fs = FlowsheetBlock(default={"dynamic": False}) m.fs.params = WaterParameterBlock( default={"solute_list": ["viruses_enteric", "tss", "toc", "cryptosporidium", "total_coliforms_fecal_ecoli"]}) m.fs.unit = UVAOPZO(default={ "property_package": m.fs.params, "database": m.db}) m.fs.unit.inlet.flow_mass_comp[0, "H2O"].fix(10000) m.fs.unit.inlet.flow_mass_comp[0, "viruses_enteric"].fix(1) m.fs.unit.inlet.flow_mass_comp[0, "toc"].fix(2) m.fs.unit.inlet.flow_mass_comp[0, "tss"].fix(3) m.fs.unit.inlet.flow_mass_comp[0, "cryptosporidium"].fix(5) m.fs.unit.inlet.flow_mass_comp[0, "total_coliforms_fecal_ecoli"].fix(3) return m @pytest.mark.unit def test_build(self, model): assert model.fs.unit.config.database == model.db assert model.fs.unit._tech_type == 'uv_aop' assert isinstance(model.fs.unit.electricity, Var) assert isinstance(model.fs.unit.energy_electric_flow_vol_inlet, Var) assert isinstance(model.fs.unit.electricity_consumption, Constraint) assert isinstance(model.fs.unit.uv_reduced_equivalent_dose, Var) assert isinstance(model.fs.unit.uv_transmittance_in, Var) assert isinstance(model.fs.unit.oxidant_dose, Var) assert isinstance(model.fs.unit.chemical_flow_mass, Var) assert isinstance(model.fs.unit.chemical_flow_mass_constraint, Constraint) @pytest.mark.component def test_load_parameters(self, model): data = model.db.get_unit_operation_parameters("uv_aop") assert model.fs.unit.recovery_frac_mass_H2O[0].fixed assert model.fs.unit.recovery_frac_mass_H2O[0].value == 1 model.fs.unit.load_parameters_from_database(use_default_removal=True) assert model.fs.unit.recovery_frac_mass_H2O[0].value == 1 for (t, j), v in model.fs.unit.removal_frac_mass_solute.items(): assert v.fixed if j not in data["removal_frac_mass_solute"]: assert v.value == data["default_removal_frac_mass_solute"]["value"] else: assert v.value == data["removal_frac_mass_solute"][j]["value"] assert model.fs.unit.energy_electric_flow_vol_inlet.fixed assert model.fs.unit.energy_electric_flow_vol_inlet.value == data[ "energy_electric_flow_vol_inlet"]["value"] assert model.fs.unit.uv_reduced_equivalent_dose[0].fixed assert model.fs.unit.uv_reduced_equivalent_dose[0].value == data[ "uv_reduced_equivalent_dose"]["value"] assert model.fs.unit.uv_transmittance_in[0].fixed assert model.fs.unit.uv_transmittance_in[0].value == data[ "uv_transmittance_in"]["value"] @pytest.mark.component def test_degrees_of_freedom(self, model): assert degrees_of_freedom(model.fs.unit) == 0 @pytest.mark.component def test_unit_consistency(self, model): assert_units_consistent(model.fs.unit) @pytest.mark.component def test_initialize(self, model): initialization_tester(model) @pytest.mark.solver @pytest.mark.skipif(solver is None, reason="Solver not available") @pytest.mark.component def test_solve(self, model): results = solver.solve(model) # Check for optimal solution assert check_optimal_termination(results) @pytest.mark.solver @pytest.mark.skipif(solver is None, reason="Solver not available") @pytest.mark.component def test_solution(self, model): assert (pytest.approx(10.004685, rel=1e-5) == value(model.fs.unit.properties_treated[0].flow_vol)) assert (pytest.approx(0.1650012, rel=1e-5) == value( model.fs.unit.properties_treated[0].conc_mass_comp["toc"])) assert (pytest.approx(0.299860, rel=1e-5) == value( model.fs.unit.properties_treated[0].conc_mass_comp["tss"])) assert (pytest.approx(5.4974e-6, rel=1e-5) == value( model.fs.unit.properties_treated[0].conc_mass_comp["cryptosporidium"])) assert (pytest.approx(1.79916e-6, rel=1e-5) == value( model.fs.unit.properties_treated[0].conc_mass_comp["total_coliforms_fecal_ecoli"])) assert (pytest.approx(3605.04, rel=1e-5) == value(model.fs.unit.electricity[0])) @pytest.mark.component def test_report(self, model): stream = StringIO() model.fs.unit.report(ostream=stream) output = """ ==================================================================================== Unit : fs.unit Time: 0.0 ------------------------------------------------------------------------------------ Unit Performance Variables: Key : Value : Fixed : Bounds Electricity Demand : 3605.0 : False : (0, None) Electricity Intensity : 0.10000 : True : (None, None) Oxidant Dosage (mg/L) : 5.0000 : True : (None, None) Oxidant Flow (kg/s) : 0.050070 : False : (0, None) Solute Removal [cryptosporidium] : 0.99999 : True : (0, None) Solute Removal [toc] : 0.17461 : True : (0, None) Solute Removal [total_coliforms_fecal_ecoli] : 0.99999 : True : (0, None) Solute Removal [tss] : 0.0000 : True : (0, None) Solute Removal [viruses_enteric] : 0.96540 : True : (0, None) UV Reduced Equivalent Dosage (mJ/cm^2) : 100.00 : True : (None, None) UV Transmittance of Feed : 0.90000 : True : (None, None) ------------------------------------------------------------------------------------ Stream Table Inlet Treated Volumetric Flowrate 10.014 10.005 Mass Concentration H2O 998.60 999.53 Mass Concentration viruses_enteric 0.099860 0.0034581 Mass Concentration tss 0.29958 0.29986 Mass Concentration toc 0.19972 0.16500 Mass Concentration cryptosporidium 0.49930 5.4974e-06 Mass Concentration total_coliforms_fecal_ecoli 0.29958 1.7992e-06 ==================================================================================== """ assert output in stream.getvalue() class TestUVAOPZO_subtype_no_default_removal: @pytest.fixture(scope="class") def model(self): m = ConcreteModel() m.db = Database() m.fs = FlowsheetBlock(default={"dynamic": False}) m.fs.params = WaterParameterBlock( default={"solute_list": ["viruses_enteric", "toc", "cryptosporidium", "total_coliforms_fecal_ecoli"]}) m.fs.unit = UVAOPZO(default={ "property_package": m.fs.params, "database": m.db, "process_subtype": "hydrogen_peroxide"}) m.fs.unit.inlet.flow_mass_comp[0, "H2O"].fix(10000) m.fs.unit.inlet.flow_mass_comp[0, "viruses_enteric"].fix(1) m.fs.unit.inlet.flow_mass_comp[0, "toc"].fix(2) m.fs.unit.inlet.flow_mass_comp[0, "cryptosporidium"].fix(5) m.fs.unit.inlet.flow_mass_comp[0, "total_coliforms_fecal_ecoli"].fix(3) return m @pytest.mark.unit def test_build(self, model): assert model.fs.unit.config.database == model.db assert model.fs.unit._tech_type == 'uv_aop' assert model.fs.unit.config.process_subtype == "hydrogen_peroxide" assert isinstance(model.fs.unit.electricity, Var) assert isinstance(model.fs.unit.energy_electric_flow_vol_inlet, Var) assert isinstance(model.fs.unit.electricity_consumption, Constraint) assert isinstance(model.fs.unit.uv_reduced_equivalent_dose, Var) assert isinstance(model.fs.unit.uv_transmittance_in, Var) assert isinstance(model.fs.unit.oxidant_dose, Var) assert isinstance(model.fs.unit.chemical_flow_mass, Var) assert isinstance(model.fs.unit.chemical_flow_mass_constraint, Constraint) @pytest.mark.component def test_load_parameters(self, model): data = model.db.get_unit_operation_parameters("uv_aop", subtype=model.fs.unit.config.process_subtype) assert model.fs.unit.recovery_frac_mass_H2O[0].fixed assert model.fs.unit.recovery_frac_mass_H2O[0].value == 1 model.fs.unit.load_parameters_from_database() assert model.fs.unit.recovery_frac_mass_H2O[0].value == 1 for (t, j), v in model.fs.unit.removal_frac_mass_solute.items(): assert v.fixed if j not in data["removal_frac_mass_solute"]: assert v.value == data["default_removal_frac_mass_solute"]["value"] else: assert v.value == data["removal_frac_mass_solute"][j]["value"] assert model.fs.unit.energy_electric_flow_vol_inlet.fixed assert model.fs.unit.energy_electric_flow_vol_inlet.value == data[ "energy_electric_flow_vol_inlet"]["value"] assert model.fs.unit.uv_reduced_equivalent_dose[0].fixed assert model.fs.unit.uv_reduced_equivalent_dose[0].value == data[ "uv_reduced_equivalent_dose"]["value"] assert model.fs.unit.uv_transmittance_in[0].fixed assert model.fs.unit.uv_transmittance_in[0].value == data[ "uv_transmittance_in"]["value"] assert model.fs.unit.oxidant_dose[0].fixed assert model.fs.unit.oxidant_dose[0].value == data[ "oxidant_dose"]["value"] @pytest.mark.component def test_degrees_of_freedom(self, model): assert degrees_of_freedom(model.fs.unit) == 0 @pytest.mark.component def test_unit_consistency(self, model): assert_units_consistent(model.fs.unit) @pytest.mark.component def test_initialize(self, model): initialization_tester(model) @pytest.mark.solver @pytest.mark.skipif(solver is None, reason="Solver not available") @pytest.mark.component def test_solve(self, model): results = solver.solve(model) # Check for optimal solution assert check_optimal_termination(results) @pytest.mark.solver @pytest.mark.skipif(solver is None, reason="Solver not available") @pytest.mark.component def test_solution(self, model): assert (pytest.approx(10.001685, rel=1e-5) == value(model.fs.unit.properties_treated[0].flow_vol)) assert (pytest.approx(0.165051, rel=1e-5) == value( model.fs.unit.properties_treated[0].conc_mass_comp["toc"])) assert (pytest.approx(5.49907e-6, rel=1e-5) == value( model.fs.unit.properties_treated[0].conc_mass_comp["cryptosporidium"])) assert (pytest.approx(1.79970e-6, rel=1e-5) == value( model.fs.unit.properties_treated[0].conc_mass_comp["total_coliforms_fecal_ecoli"])) assert (pytest.approx(0.0034591, rel=1e-5) == value( model.fs.unit.properties_treated[0].conc_mass_comp["viruses_enteric"])) assert (pytest.approx(3603.96, rel=1e-5) == value(model.fs.unit.electricity[0])) assert (pytest.approx(0.050055, rel=1e-5) == value(model.fs.unit.chemical_flow_mass[0])) @pytest.mark.component def test_report(self, model): stream = StringIO() model.fs.unit.report(ostream=stream) output = """ ==================================================================================== Unit : fs.unit Time: 0.0 ------------------------------------------------------------------------------------ Unit Performance Variables: Key : Value : Fixed : Bounds Electricity Demand : 3604.0 : False : (0, None) Electricity Intensity : 0.10000 : True : (None, None) Oxidant Dosage (mg/L) : 5.0000 : True : (None, None) Oxidant Flow (kg/s) : 0.050055 : False : (0, None) Solute Removal [cryptosporidium] : 0.99999 : True : (0, None) Solute Removal [toc] : 0.17461 : True : (0, None) Solute Removal [total_coliforms_fecal_ecoli] : 0.99999 : True : (0, None) Solute Removal [viruses_enteric] : 0.96540 : True : (0, None) UV Reduced Equivalent Dosage (mJ/cm^2) : 100.00 : True : (None, None) UV Transmittance of Feed : 0.90000 : True : (None, None) ------------------------------------------------------------------------------------ Stream Table Inlet Treated Volumetric Flowrate 10.011 10.002 Mass Concentration H2O 998.90 999.83 Mass Concentration viruses_enteric 0.099890 0.0034591 Mass Concentration toc 0.19978 0.16505 Mass Concentration cryptosporidium 0.49945 5.4991e-06 Mass Concentration total_coliforms_fecal_ecoli 0.29967 1.7997e-06 ==================================================================================== """ assert output in stream.getvalue() def test_costing(): m = ConcreteModel() m.db = Database() m.fs = FlowsheetBlock(default={"dynamic": False}) m.fs.params = WaterParameterBlock( default={"solute_list": ["viruses_enteric", "toc", "cryptosporidium"]}) m.fs.costing = ZeroOrderCosting() m.fs.unit1 = UVAOPZO(default={ "property_package": m.fs.params, "database": m.db}) m.fs.unit1.inlet.flow_mass_comp[0, "H2O"].fix(10000) m.fs.unit1.inlet.flow_mass_comp[0, "viruses_enteric"].fix(1) m.fs.unit1.inlet.flow_mass_comp[0, "toc"].fix(2) m.fs.unit1.inlet.flow_mass_comp[0, "cryptosporidium"].fix(3) m.fs.unit1.load_parameters_from_database(use_default_removal=True) assert degrees_of_freedom(m.fs.unit1) == 0 m.fs.unit1.costing = UnitModelCostingBlock(default={ "flowsheet_costing_block": m.fs.costing}) assert isinstance(m.fs.unit1.chemical_flow_mass, Var) assert isinstance(m.fs.costing.uv_aop, Block) assert isinstance(m.fs.costing.uv_aop.uv_capital_a_parameter, Var) assert isinstance(m.fs.costing.uv_aop.uv_capital_b_parameter, Var) assert isinstance(m.fs.costing.uv_aop.uv_capital_c_parameter, Var) assert isinstance(m.fs.costing.uv_aop.uv_capital_d_parameter, Var) assert isinstance(m.fs.costing.uv_aop.aop_capital_a_parameter, Var) assert isinstance(m.fs.costing.uv_aop.aop_capital_b_parameter, Var) assert isinstance(m.fs.unit1.costing.capital_cost, Var) assert isinstance(m.fs.unit1.costing.capital_cost_constraint, Constraint) assert_units_consistent(m.fs) assert degrees_of_freedom(m.fs.unit1) == 0 assert m.fs.unit1.electricity[0] in \ m.fs.costing._registered_flows["electricity"] assert str(m.fs.costing._registered_flows["hydrogen_peroxide"][0]) == str( m.fs.unit1.chemical_flow_mass[0])

45.407311

100

0.600196

2,087

17,391

4.8184

0.134164

0.047733

0.071102

0.042263

0.812649

0.794749

0.776253

0.76601

0.743437

0.717184

0

0.040355

0.249094

17,391

382

101

45.526178

0.729688

0.035593

0

0.696667

0

0.006667

0.303405

0.074782

0

0.28

1

0.063333

false

0

0.043333

0

0.12

0

null

0

1

0

null

0

6

c4dcbd9e0164eaae599ac67bb5ac0e53caacccd6

941

py

Python

api/auth/apikeys.py

Retrylife/apiv2

a3c6cd4e556db9126a0e8aebbace7c3307b6a277

[ "MIT" ]

null

api/auth/apikeys.py

Retrylife/apiv2

a3c6cd4e556db9126a0e8aebbace7c3307b6a277

[ "MIT" ]

null

api/auth/apikeys.py

Retrylife/apiv2

a3c6cd4e556db9126a0e8aebbace7c3307b6a277

[ "MIT" ]

null

all_scopes = ["tba", "frc", "devrant", "github", "rss", "rtl", "rtl-access", "monitor"] read = { # debugging key "070f42125103c1b1edd465a102c052c245d1eb455a35c370614c037c83e2c65c9646c699e8fa27184bc8dcf74f14e23c8a01cf9160b7718b82a8645261b6458d": ["tba", "rtl-access", "devrant", "monitor"], # devrant status key retrylife.ca "cac386b5ca59ab4d6256f9ce548cd96af41bda212bc688c9ca710a5cec77fd078bbc3a5b0efb6232b7e705af4bb2bf2f412441c6610e4d2ca8b2af8451d5e69d": ["devrant"], # 5k24 live data key "8107b599263a5466f28fa6dc4d29a93feff43edcb2aa54761a7e3055fb57cb582b85a1cd403b5769f62fe38c593286994e9f121785ab36cc304db0f1255220a3": ["tba"], # SnappyFRC "32fb46261eec1a42cc641cc287274f1a21a179c45e03ea929659f2246570ccbf19bff93a118645fdcc4928272ae2bef2c169c326a4f0ceea05de16c5de0bc99d": ["tba"] } internal_keys = { "tba": "QPI1VLcQrowB0Oq8G0NdTjk30HpSaJ4fJuO4GV29ATKJkJIS6GNVZ1qnlLg0O6Ql", "monitor": None }

44.809524

180

0.807651

42

941

18.047619

0.666667

0.023747

0

0.397406

0.098831

941

21

181

44.809524

0.496462

0.07864

0

0.774942

0.668213

0

1

0

1

0

false

0

1

null

0

1

0

1

0

1

null

1

0

6

c4dd4802ca59c3df2a76ab98d481dc761a936ce9

26

py

Python

test2.py

MPogoda/compilers_python

48aed1cbe715d9121f3031e400d579d241754304

[ "MIT" ]

1

2022-03-27T06:47:36.000Z

test2.py

MPogoda/compilers_python

48aed1cbe715d9121f3031e400d579d241754304

[ "MIT" ]

null

test2.py

MPogoda/compilers_python

48aed1cbe715d9121f3031e400d579d241754304

[ "MIT" ]

null

class class class class:

8.666667

24

0.769231

4

26

5

0.25

1.5

0

0.192308

26

2

25

13

0.952381

0

null

0

null

0

1

0

null

1

0

1

0

null

0

1

0

6

f20f2c2658d8575c91afa0016cae29e6691a3018

115

py

Python

src/flasktex/views.py

hosiet/flasktex

a1fe0dd84fdeed5e5d99125af0d789f33895e396

[ "BSD-3-Clause" ]

1

2020-03-22T10:58:24.000Z

src/flasktex/views.py

hosiet/flasktex

a1fe0dd84fdeed5e5d99125af0d789f33895e396

[ "BSD-3-Clause" ]

null

src/flasktex/views.py

hosiet/flasktex

a1fe0dd84fdeed5e5d99125af0d789f33895e396

[ "BSD-3-Clause" ]

null

from flasktex import app import flasktex.api_1_0 @app.route("/") def ft_route_root(): return 'this is root.'

14.375

26

0.713043

19

115

4.105263

0.736842

0

0.020833

0.165217

115

7

27

16.428571

0.791667

0

0.121739

0

1

0.2

true

0

0.4

0.2

0.8

0

1

0

null

0

1

0

null

0

1

0

1

0

6

f21c573bfb74d312a7e25b3f0805322696a71a53

66

py

Python

GEOAkaze/__init__.py

ahsouri/GEOAkaze

63072998cb1a7e51fdd4a9c04102fd983ad6a2b6

[ "MIT" ]

null

GEOAkaze/__init__.py

ahsouri/GEOAkaze

63072998cb1a7e51fdd4a9c04102fd983ad6a2b6

[ "MIT" ]

null

GEOAkaze/__init__.py

ahsouri/GEOAkaze

63072998cb1a7e51fdd4a9c04102fd983ad6a2b6

[ "MIT" ]

null

from .GEOAkaze_mod import GEOAkaze from .make_kml import make_kml

22

34

0.848485

11

66

4.818182

0.545455

0.264151

0

0.121212

66

2

35

33

0.913793

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

f21d490fcdce47dd3ce94ca1890a9617d6bbec14

25

py

Python

LociAnalysis/refdb/__init__.py

bnbowman/LociAnalysis

c0f11c2a2b80c7cde61b9991283a17f97062118e

[ "BSD-3-Clause" ]

3

2017-09-22T15:17:42.000Z

2020-05-12T04:59:07.000Z

LociAnalysis/refdb/__init__.py

bnbowman/LociAnalysis

c0f11c2a2b80c7cde61b9991283a17f97062118e

[ "BSD-3-Clause" ]

null

LociAnalysis/refdb/__init__.py

bnbowman/LociAnalysis

c0f11c2a2b80c7cde61b9991283a17f97062118e

[ "BSD-3-Clause" ]

null

from .refdb import RefDb

12.5

24

0.8

4

25

5

0.75

0

0.16

25

1

25

0.952381

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

f2214abd577ec5293700ad33a303f96e92b0cb2c

77

py

Python

Python/Math/Power Mod Power.py

jaswal72/hacker-rank

95aaa71b4636928664341dc9c6f75d69af5f26ac

[ "MIT" ]

1

2017-03-27T18:21:38.000Z

Python/Math/Power Mod Power.py

jaswal72/hacker-rank

95aaa71b4636928664341dc9c6f75d69af5f26ac

[ "MIT" ]

null

Python/Math/Power Mod Power.py

jaswal72/hacker-rank

95aaa71b4636928664341dc9c6f75d69af5f26ac

[ "MIT" ]

null

a=int(input()) b=int(input()) c=int(input()) print pow(a,b) print pow(a,b,c)

12.833333

16

0.623377

18

77

2.666667

0.388889

0.5

0.375

0.416667

0

0.090909

77

5

17

15.4

0.685714

0

null

0

null

0.4

1

0

null

1

0

1

0

null

0

1

0

6

482d8de3b1f47ab2d0d7c2d39c36cf57fd806f9a

70

py

Python

bools/datetime/timedelta.py

lotcher/bools

bdd5c056d7bb6f8c304b56869c49966a9b6af1a1

[ "MIT" ]

11

2021-06-18T11:11:36.000Z

2022-02-10T05:59:28.000Z

bools/datetime/timedelta.py

lotcher/bools

bdd5c056d7bb6f8c304b56869c49966a9b6af1a1

[ "MIT" ]

null

bools/datetime/timedelta.py

lotcher/bools

bdd5c056d7bb6f8c304b56869c49966a9b6af1a1

[ "MIT" ]

null

from datetime import timedelta class Timedelta(timedelta): pass

11.666667

30

0.771429

8

70

6.75

0.75

0

0.185714

70

5

31

14

0.947368

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

48537630316dad32b2dcddf3786a98ab34c9bac3

38,936

py

Python

tests/invalid_models_tests/test_relative_fields.py

fizista/django

16f3a6a4c7bab11644d11c2be029374e5095cb56

[ "BSD-3-Clause" ]

1

2019-02-10T19:33:27.000Z

tests/invalid_models_tests/test_relative_fields.py

fizista/django

16f3a6a4c7bab11644d11c2be029374e5095cb56

[ "BSD-3-Clause" ]

null

tests/invalid_models_tests/test_relative_fields.py

fizista/django

16f3a6a4c7bab11644d11c2be029374e5095cb56

[ "BSD-3-Clause" ]

null

# -*- encoding: utf-8 -*- from __future__ import unicode_literals from django.core.checks import Error from django.db import models from django.test.utils import override_settings from django.test.testcases import skipIfDBFeature from .base import IsolatedModelsTestCase class RelativeFieldTests(IsolatedModelsTestCase): def test_valid_foreign_key_without_accessor(self): class Target(models.Model): # There would be a clash if Model.field installed an accessor. model = models.IntegerField() class Model(models.Model): field = models.ForeignKey(Target, related_name='+') field = Model._meta.get_field('field') errors = field.check() self.assertEqual(errors, []) def test_foreign_key_to_missing_model(self): # Model names are resolved when a model is being created, so we cannot # test relative fields in isolation and we need to attach them to a # model. class Model(models.Model): foreign_key = models.ForeignKey('Rel1') field = Model._meta.get_field('foreign_key') errors = field.check() expected = [ Error( ('The field has a relation with model Rel1, ' 'which has either not been installed or is abstract.'), hint=('Ensure that you did not misspell the model name and ' 'the model is not abstract. Does your INSTALLED_APPS ' 'setting contain the app where Rel1 is defined?'), obj=field, id='E030', ), ] self.assertEqual(errors, expected) def test_many_to_many_to_missing_model(self): class Model(models.Model): m2m = models.ManyToManyField("Rel2") field = Model._meta.get_field('m2m') errors = field.check(from_model=Model) expected = [ Error( ('The field has a relation with model Rel2, ' 'which has either not been installed or is abstract.'), hint=('Ensure that you did not misspell the model name and ' 'the model is not abstract. Does your INSTALLED_APPS ' 'setting contain the app where Rel2 is defined?'), obj=field, id='E030', ), ] self.assertEqual(errors, expected) def test_ambiguous_relationship_model(self): class Person(models.Model): pass class Group(models.Model): field = models.ManyToManyField('Person', through="AmbiguousRelationship", related_name='tertiary') class AmbiguousRelationship(models.Model): # Too much foreign keys to Person. first_person = models.ForeignKey(Person, related_name="first") second_person = models.ForeignKey(Person, related_name="second") second_model = models.ForeignKey(Group) field = Group._meta.get_field('field') errors = field.check(from_model=Group) expected = [ Error( ('The model is used as an intermediary model by ' 'invalid_models_tests.Group.field, but it has more than one ' 'foreign key to Person, ' 'which is ambiguous and is not permitted.'), hint=('If you want to create a recursive relationship, use ' 'ForeignKey("self", symmetrical=False, ' 'through="AmbiguousRelationship").'), obj=field, id='E027', ), ] self.assertEqual(errors, expected) def test_relationship_model_with_foreign_key_to_wrong_model(self): class WrongModel(models.Model): pass class Person(models.Model): pass class Group(models.Model): members = models.ManyToManyField('Person', through="InvalidRelationship") class InvalidRelationship(models.Model): person = models.ForeignKey(Person) wrong_foreign_key = models.ForeignKey(WrongModel) # The last foreign key should point to Group model. field = Group._meta.get_field('members') errors = field.check(from_model=Group) expected = [ Error( ('The model is used as an intermediary model by ' 'invalid_models_tests.Group.members, but it misses ' 'a foreign key to Group or Person.'), hint=None, obj=InvalidRelationship, id='E028', ), ] self.assertEqual(errors, expected) def test_relationship_model_missing_foreign_key(self): class Person(models.Model): pass class Group(models.Model): members = models.ManyToManyField('Person', through="InvalidRelationship") class InvalidRelationship(models.Model): group = models.ForeignKey(Group) # No foreign key to Person field = Group._meta.get_field('members') errors = field.check(from_model=Group) expected = [ Error( ('The model is used as an intermediary model by ' 'invalid_models_tests.Group.members, but it misses ' 'a foreign key to Group or Person.'), hint=None, obj=InvalidRelationship, id='E028', ), ] self.assertEqual(errors, expected) def test_missing_relationship_model(self): class Person(models.Model): pass class Group(models.Model): members = models.ManyToManyField('Person', through="MissingM2MModel") field = Group._meta.get_field('members') errors = field.check(from_model=Group) expected = [ Error( ('The field specifies a many-to-many relation through model ' 'MissingM2MModel, which has not been installed.'), hint=('Ensure that you did not misspell the model name and ' 'the model is not abstract. Does your INSTALLED_APPS ' 'setting contain the app where MissingM2MModel is defined?'), obj=field, id='E023', ), ] self.assertEqual(errors, expected) def test_symmetrical_self_referential_field(self): class Person(models.Model): # Implicit symmetrical=False. friends = models.ManyToManyField('self', through="Relationship") class Relationship(models.Model): first = models.ForeignKey(Person, related_name="rel_from_set") second = models.ForeignKey(Person, related_name="rel_to_set") field = Person._meta.get_field('friends') errors = field.check(from_model=Person) expected = [ Error( 'Many-to-many fields with intermediate tables must not be symmetrical.', hint=None, obj=field, id='E024', ), ] self.assertEqual(errors, expected) def test_too_many_foreign_keys_in_self_referential_model(self): class Person(models.Model): friends = models.ManyToManyField('self', through="InvalidRelationship", symmetrical=False) class InvalidRelationship(models.Model): first = models.ForeignKey(Person, related_name="rel_from_set_2") second = models.ForeignKey(Person, related_name="rel_to_set_2") third = models.ForeignKey(Person, related_name="too_many_by_far") field = Person._meta.get_field('friends') errors = field.check(from_model=Person) expected = [ Error( ('The model is used as an intermediary model by ' 'invalid_models_tests.Person.friends, but it has more than two ' 'foreign keys to Person, which is ambiguous and ' 'is not permitted.'), hint=None, obj=InvalidRelationship, id='E025', ), ] self.assertEqual(errors, expected) def test_symmetric_self_reference_with_intermediate_table(self): class Person(models.Model): # Explicit symmetrical=True. friends = models.ManyToManyField('self', through="Relationship", symmetrical=True) class Relationship(models.Model): first = models.ForeignKey(Person, related_name="rel_from_set") second = models.ForeignKey(Person, related_name="rel_to_set") field = Person._meta.get_field('friends') errors = field.check(from_model=Person) expected = [ Error( 'Many-to-many fields with intermediate tables must not be symmetrical.', hint=None, obj=field, id='E024', ), ] self.assertEqual(errors, expected) def test_foreign_key_to_abstract_model(self): class Model(models.Model): foreign_key = models.ForeignKey('AbstractModel') class AbstractModel(models.Model): class Meta: abstract = True field = Model._meta.get_field('foreign_key') errors = field.check() expected = [ Error( ('The field has a relation with model AbstractModel, ' 'which has either not been installed or is abstract.'), hint=('Ensure that you did not misspell the model name and ' 'the model is not abstract. Does your INSTALLED_APPS ' 'setting contain the app where AbstractModel is defined?'), obj=field, id='E030', ), ] self.assertEqual(errors, expected) def test_m2m_to_abstract_model(self): class AbstractModel(models.Model): class Meta: abstract = True class Model(models.Model): m2m = models.ManyToManyField('AbstractModel') field = Model._meta.get_field('m2m') errors = field.check(from_model=Model) expected = [ Error( ('The field has a relation with model AbstractModel, ' 'which has either not been installed or is abstract.'), hint=('Ensure that you did not misspell the model name and ' 'the model is not abstract. Does your INSTALLED_APPS ' 'setting contain the app where AbstractModel is defined?'), obj=field, id='E030', ), ] self.assertEqual(errors, expected) def test_unique_m2m(self): class Person(models.Model): name = models.CharField(max_length=5) class Group(models.Model): members = models.ManyToManyField('Person', unique=True) field = Group._meta.get_field('members') errors = field.check(from_model=Group) expected = [ Error( 'ManyToManyFields must not be unique.', hint=None, obj=field, id='E022', ), ] self.assertEqual(errors, expected) def test_foreign_key_to_non_unique_field(self): class Target(models.Model): bad = models.IntegerField() # No unique=True class Model(models.Model): foreign_key = models.ForeignKey('Target', to_field='bad') field = Model._meta.get_field('foreign_key') errors = field.check() expected = [ Error( 'Target.bad must have unique=True because it is referenced by a foreign key.', hint=None, obj=field, id='E019', ), ] self.assertEqual(errors, expected) def test_foreign_key_to_non_unique_field_under_explicit_model(self): class Target(models.Model): bad = models.IntegerField() class Model(models.Model): field = models.ForeignKey(Target, to_field='bad') field = Model._meta.get_field('field') errors = field.check() expected = [ Error( 'Target.bad must have unique=True because it is referenced by a foreign key.', hint=None, obj=field, id='E019', ), ] self.assertEqual(errors, expected) def test_foreign_object_to_non_unique_fields(self): class Person(models.Model): # Note that both fields are not unique. country_id = models.IntegerField() city_id = models.IntegerField() class MMembership(models.Model): person_country_id = models.IntegerField() person_city_id = models.IntegerField() person = models.ForeignObject(Person, from_fields=['person_country_id', 'person_city_id'], to_fields=['country_id', 'city_id']) field = MMembership._meta.get_field('person') errors = field.check() expected = [ Error( ('No unique=True constraint on field combination ' '"country_id,city_id" under model Person.'), hint=('Set unique=True argument on any of the fields ' '"country_id,city_id" under model Person.'), obj=field, id='E018', ) ] self.assertEqual(errors, expected) def test_on_delete_set_null_on_non_nullable_field(self): class Person(models.Model): pass class Model(models.Model): foreign_key = models.ForeignKey('Person', on_delete=models.SET_NULL) field = Model._meta.get_field('foreign_key') errors = field.check() expected = [ Error( 'The field specifies on_delete=SET_NULL, but cannot be null.', hint='Set null=True argument on the field.', obj=field, id='E020', ), ] self.assertEqual(errors, expected) def test_on_delete_set_default_without_default_value(self): class Person(models.Model): pass class Model(models.Model): foreign_key = models.ForeignKey('Person', on_delete=models.SET_DEFAULT) field = Model._meta.get_field('foreign_key') errors = field.check() expected = [ Error( 'The field specifies on_delete=SET_DEFAULT, but has no default value.', hint=None, obj=field, id='E021', ), ] self.assertEqual(errors, expected) @skipIfDBFeature('interprets_empty_strings_as_nulls') def test_nullable_primary_key(self): class Model(models.Model): field = models.IntegerField(primary_key=True, null=True) field = Model._meta.get_field('field') errors = field.check() expected = [ Error( 'Primary keys must not have null=True.', hint='Set null=False on the field or remove primary_key=True argument.', obj=field, id='E036', ), ] self.assertEqual(errors, expected) def test_not_swapped_model(self): class SwappableModel(models.Model): # A model that can be, but isn't swapped out. References to this # model should *not* raise any validation error. class Meta: swappable = 'TEST_SWAPPABLE_MODEL' class Model(models.Model): explicit_fk = models.ForeignKey(SwappableModel, related_name='explicit_fk') implicit_fk = models.ForeignKey('invalid_models_tests.SwappableModel', related_name='implicit_fk') explicit_m2m = models.ManyToManyField(SwappableModel, related_name='explicit_m2m') implicit_m2m = models.ManyToManyField( 'invalid_models_tests.SwappableModel', related_name='implicit_m2m') explicit_fk = Model._meta.get_field('explicit_fk') self.assertEqual(explicit_fk.check(), []) implicit_fk = Model._meta.get_field('implicit_fk') self.assertEqual(implicit_fk.check(), []) explicit_m2m = Model._meta.get_field('explicit_m2m') self.assertEqual(explicit_m2m.check(from_model=Model), []) implicit_m2m = Model._meta.get_field('implicit_m2m') self.assertEqual(implicit_m2m.check(from_model=Model), []) @override_settings(TEST_SWAPPED_MODEL='invalid_models_tests.Replacement') def test_referencing_to_swapped_model(self): class Replacement(models.Model): pass class SwappedModel(models.Model): class Meta: swappable = 'TEST_SWAPPED_MODEL' class Model(models.Model): explicit_fk = models.ForeignKey(SwappedModel, related_name='explicit_fk') implicit_fk = models.ForeignKey('invalid_models_tests.SwappedModel', related_name='implicit_fk') explicit_m2m = models.ManyToManyField(SwappedModel, related_name='explicit_m2m') implicit_m2m = models.ManyToManyField( 'invalid_models_tests.SwappedModel', related_name='implicit_m2m') fields = [ Model._meta.get_field('explicit_fk'), Model._meta.get_field('implicit_fk'), Model._meta.get_field('explicit_m2m'), Model._meta.get_field('implicit_m2m'), ] expected_error = Error( ('The field defines a relation with the model ' 'invalid_models_tests.SwappedModel, which has been swapped out.'), hint='Update the relation to point at settings.TEST_SWAPPED_MODEL', id='E029', ) for field in fields: expected_error.obj = field errors = field.check(from_model=Model) self.assertEqual(errors, [expected_error]) class AccessorClashTests(IsolatedModelsTestCase): def test_fk_to_integer(self): self._test_accessor_clash( target=models.IntegerField(), relative=models.ForeignKey('Target')) def test_fk_to_fk(self): self._test_accessor_clash( target=models.ForeignKey('Another'), relative=models.ForeignKey('Target')) def test_fk_to_m2m(self): self._test_accessor_clash( target=models.ManyToManyField('Another'), relative=models.ForeignKey('Target')) def test_m2m_to_integer(self): self._test_accessor_clash( target=models.IntegerField(), relative=models.ManyToManyField('Target')) def test_m2m_to_fk(self): self._test_accessor_clash( target=models.ForeignKey('Another'), relative=models.ManyToManyField('Target')) def test_m2m_to_m2m(self): self._test_accessor_clash( target=models.ManyToManyField('Another'), relative=models.ManyToManyField('Target')) def _test_accessor_clash(self, target, relative): class Another(models.Model): pass class Target(models.Model): model_set = target class Model(models.Model): rel = relative errors = Model.check() expected = [ Error( 'Accessor for field Model.rel clashes with field Target.model_set.', hint=('Rename field Target.model_set or add/change ' 'a related_name argument to the definition ' 'for field Model.rel.'), obj=Model._meta.get_field('rel'), id='E014', ), ] self.assertEqual(errors, expected) def test_clash_between_accessors(self): class Target(models.Model): pass class Model(models.Model): foreign = models.ForeignKey(Target) m2m = models.ManyToManyField(Target) errors = Model.check() expected = [ Error( 'Clash between accessors for Model.foreign and Model.m2m.', hint=('Add or change a related_name argument to the definition ' 'for Model.foreign or Model.m2m.'), obj=Model._meta.get_field('foreign'), id='E016', ), Error( 'Clash between accessors for Model.m2m and Model.foreign.', hint=('Add or change a related_name argument to the definition ' 'for Model.m2m or Model.foreign.'), obj=Model._meta.get_field('m2m'), id='E016', ), ] self.assertEqual(errors, expected) class ReverseQueryNameClashTests(IsolatedModelsTestCase): def test_fk_to_integer(self): self._test_reverse_query_name_clash( target=models.IntegerField(), relative=models.ForeignKey('Target')) def test_fk_to_fk(self): self._test_reverse_query_name_clash( target=models.ForeignKey('Another'), relative=models.ForeignKey('Target')) def test_fk_to_m2m(self): self._test_reverse_query_name_clash( target=models.ManyToManyField('Another'), relative=models.ForeignKey('Target')) def test_m2m_to_integer(self): self._test_reverse_query_name_clash( target=models.IntegerField(), relative=models.ManyToManyField('Target')) def test_m2m_to_fk(self): self._test_reverse_query_name_clash( target=models.ForeignKey('Another'), relative=models.ManyToManyField('Target')) def test_m2m_to_m2m(self): self._test_reverse_query_name_clash( target=models.ManyToManyField('Another'), relative=models.ManyToManyField('Target')) def _test_reverse_query_name_clash(self, target, relative): class Another(models.Model): pass class Target(models.Model): model = target class Model(models.Model): rel = relative errors = Model.check() expected = [ Error( 'Reverse query name for field Model.rel clashes with field Target.model.', hint=('Rename field Target.model or add/change ' 'a related_name argument to the definition ' 'for field Model.rel.'), obj=Model._meta.get_field('rel'), id='E015', ), ] self.assertEqual(errors, expected) class ExplicitRelatedNameClashTests(IsolatedModelsTestCase): def test_fk_to_integer(self): self._test_explicit_related_name_clash( target=models.IntegerField(), relative=models.ForeignKey('Target', related_name='clash')) def test_fk_to_fk(self): self._test_explicit_related_name_clash( target=models.ForeignKey('Another'), relative=models.ForeignKey('Target', related_name='clash')) def test_fk_to_m2m(self): self._test_explicit_related_name_clash( target=models.ManyToManyField('Another'), relative=models.ForeignKey('Target', related_name='clash')) def test_m2m_to_integer(self): self._test_explicit_related_name_clash( target=models.IntegerField(), relative=models.ManyToManyField('Target', related_name='clash')) def test_m2m_to_fk(self): self._test_explicit_related_name_clash( target=models.ForeignKey('Another'), relative=models.ManyToManyField('Target', related_name='clash')) def test_m2m_to_m2m(self): self._test_explicit_related_name_clash( target=models.ManyToManyField('Another'), relative=models.ManyToManyField('Target', related_name='clash')) def _test_explicit_related_name_clash(self, target, relative): class Another(models.Model): pass class Target(models.Model): clash = target class Model(models.Model): rel = relative errors = Model.check() expected = [ Error( 'Accessor for field Model.rel clashes with field Target.clash.', hint=('Rename field Target.clash or add/change ' 'a related_name argument to the definition ' 'for field Model.rel.'), obj=Model._meta.get_field('rel'), id='E014', ), Error( 'Reverse query name for field Model.rel clashes with field Target.clash.', hint=('Rename field Target.clash or add/change ' 'a related_name argument to the definition ' 'for field Model.rel.'), obj=Model._meta.get_field('rel'), id='E015', ), ] self.assertEqual(errors, expected) class ExplicitRelatedQueryNameClashTests(IsolatedModelsTestCase): def test_fk_to_integer(self): self._test_explicit_related_query_name_clash( target=models.IntegerField(), relative=models.ForeignKey('Target', related_query_name='clash')) def test_fk_to_fk(self): self._test_explicit_related_query_name_clash( target=models.ForeignKey('Another'), relative=models.ForeignKey('Target', related_query_name='clash')) def test_fk_to_m2m(self): self._test_explicit_related_query_name_clash( target=models.ManyToManyField('Another'), relative=models.ForeignKey('Target', related_query_name='clash')) def test_m2m_to_integer(self): self._test_explicit_related_query_name_clash( target=models.IntegerField(), relative=models.ManyToManyField('Target', related_query_name='clash')) def test_m2m_to_fk(self): self._test_explicit_related_query_name_clash( target=models.ForeignKey('Another'), relative=models.ManyToManyField('Target', related_query_name='clash')) def test_m2m_to_m2m(self): self._test_explicit_related_query_name_clash( target=models.ManyToManyField('Another'), relative=models.ManyToManyField('Target', related_query_name='clash')) def _test_explicit_related_query_name_clash(self, target, relative): class Another(models.Model): pass class Target(models.Model): clash = target class Model(models.Model): rel = relative errors = Model.check() expected = [ Error( 'Reverse query name for field Model.rel clashes with field Target.clash.', hint=('Rename field Target.clash or add/change a related_name ' 'argument to the definition for field Model.rel.'), obj=Model._meta.get_field('rel'), id='E015', ), ] self.assertEqual(errors, expected) class SelfReferentialM2MClashTests(IsolatedModelsTestCase): def test_clash_between_accessors(self): class Model(models.Model): first_m2m = models.ManyToManyField('self', symmetrical=False) second_m2m = models.ManyToManyField('self', symmetrical=False) errors = Model.check() expected = [ Error( 'Clash between accessors for Model.first_m2m and Model.second_m2m.', hint=('Add or change a related_name argument to the definition ' 'for Model.first_m2m or Model.second_m2m.'), obj=Model._meta.get_field('first_m2m'), id='E016', ), Error( 'Clash between accessors for Model.second_m2m and Model.first_m2m.', hint=('Add or change a related_name argument to the definition ' 'for Model.second_m2m or Model.first_m2m.'), obj=Model._meta.get_field('second_m2m'), id='E016', ), ] self.assertEqual(errors, expected) def test_accessor_clash(self): class Model(models.Model): model_set = models.ManyToManyField("self", symmetrical=False) errors = Model.check() expected = [ Error( 'Accessor for field Model.model_set clashes with field Model.model_set.', hint=('Rename field Model.model_set or add/change ' 'a related_name argument to the definition ' 'for field Model.model_set.'), obj=Model._meta.get_field('model_set'), id='E014', ), ] self.assertEqual(errors, expected) def test_reverse_query_name_clash(self): class Model(models.Model): model = models.ManyToManyField("self", symmetrical=False) errors = Model.check() expected = [ Error( 'Reverse query name for field Model.model clashes with field Model.model.', hint=('Rename field Model.model or add/change a related_name ' 'argument to the definition for field Model.model.'), obj=Model._meta.get_field('model'), id='E015', ), ] self.assertEqual(errors, expected) def test_clash_under_explicit_related_name(self): class Model(models.Model): clash = models.IntegerField() m2m = models.ManyToManyField("self", symmetrical=False, related_name='clash') errors = Model.check() expected = [ Error( 'Accessor for field Model.m2m clashes with field Model.clash.', hint=('Rename field Model.clash or add/change a related_name ' 'argument to the definition for field Model.m2m.'), obj=Model._meta.get_field('m2m'), id='E014', ), Error( 'Reverse query name for field Model.m2m clashes with field Model.clash.', hint=('Rename field Model.clash or add/change a related_name ' 'argument to the definition for field Model.m2m.'), obj=Model._meta.get_field('m2m'), id='E015', ), ] self.assertEqual(errors, expected) def test_valid_model(self): class Model(models.Model): first = models.ManyToManyField("self", symmetrical=False, related_name='first_accessor') second = models.ManyToManyField("self", symmetrical=False, related_name='second_accessor') errors = Model.check() self.assertEqual(errors, []) class SelfReferentialFKClashTests(IsolatedModelsTestCase): def test_accessor_clash(self): class Model(models.Model): model_set = models.ForeignKey("Model") errors = Model.check() expected = [ Error( 'Accessor for field Model.model_set clashes with field Model.model_set.', hint=('Rename field Model.model_set or add/change ' 'a related_name argument to the definition ' 'for field Model.model_set.'), obj=Model._meta.get_field('model_set'), id='E014', ), ] self.assertEqual(errors, expected) def test_reverse_query_name_clash(self): class Model(models.Model): model = models.ForeignKey("Model") errors = Model.check() expected = [ Error( 'Reverse query name for field Model.model clashes with field Model.model.', hint=('Rename field Model.model or add/change ' 'a related_name argument to the definition ' 'for field Model.model.'), obj=Model._meta.get_field('model'), id='E015', ), ] self.assertEqual(errors, expected) def test_clash_under_explicit_related_name(self): class Model(models.Model): clash = models.CharField(max_length=10) foreign = models.ForeignKey("Model", related_name='clash') errors = Model.check() expected = [ Error( 'Accessor for field Model.foreign clashes with field Model.clash.', hint=('Rename field Model.clash or add/change ' 'a related_name argument to the definition ' 'for field Model.foreign.'), obj=Model._meta.get_field('foreign'), id='E014', ), Error( 'Reverse query name for field Model.foreign clashes with field Model.clash.', hint=('Rename field Model.clash or add/change ' 'a related_name argument to the definition ' 'for field Model.foreign.'), obj=Model._meta.get_field('foreign'), id='E015', ), ] self.assertEqual(errors, expected) class ComplexClashTests(IsolatedModelsTestCase): # New tests should not be included here, because this is a single, # self-contained sanity check, not a test of everything. def test_complex_clash(self): class Target(models.Model): tgt_safe = models.CharField(max_length=10) clash = models.CharField(max_length=10) model = models.CharField(max_length=10) clash1_set = models.CharField(max_length=10) class Model(models.Model): src_safe = models.CharField(max_length=10) foreign_1 = models.ForeignKey(Target, related_name='id') foreign_2 = models.ForeignKey(Target, related_name='src_safe') m2m_1 = models.ManyToManyField(Target, related_name='id') m2m_2 = models.ManyToManyField(Target, related_name='src_safe') errors = Model.check() expected = [ Error( 'Accessor for field Model.foreign_1 clashes with field Target.id.', hint=('Rename field Target.id or add/change a related_name ' 'argument to the definition for field Model.foreign_1.'), obj=Model._meta.get_field('foreign_1'), id='E014', ), Error( 'Reverse query name for field Model.foreign_1 clashes with field Target.id.', hint=('Rename field Target.id or add/change a related_name ' 'argument to the definition for field Model.foreign_1.'), obj=Model._meta.get_field('foreign_1'), id='E015', ), Error( 'Clash between accessors for Model.foreign_1 and Model.m2m_1.', hint=('Add or change a related_name argument to ' 'the definition for Model.foreign_1 or Model.m2m_1.'), obj=Model._meta.get_field('foreign_1'), id='E016', ), Error( 'Clash between reverse query names for Model.foreign_1 and Model.m2m_1.', hint=('Add or change a related_name argument to ' 'the definition for Model.foreign_1 or Model.m2m_1.'), obj=Model._meta.get_field('foreign_1'), id='E017', ), Error( 'Clash between accessors for Model.foreign_2 and Model.m2m_2.', hint=('Add or change a related_name argument ' 'to the definition for Model.foreign_2 or Model.m2m_2.'), obj=Model._meta.get_field('foreign_2'), id='E016', ), Error( 'Clash between reverse query names for Model.foreign_2 and Model.m2m_2.', hint=('Add or change a related_name argument to ' 'the definition for Model.foreign_2 or Model.m2m_2.'), obj=Model._meta.get_field('foreign_2'), id='E017', ), Error( 'Accessor for field Model.m2m_1 clashes with field Target.id.', hint=('Rename field Target.id or add/change a related_name ' 'argument to the definition for field Model.m2m_1.'), obj=Model._meta.get_field('m2m_1'), id='E014', ), Error( 'Reverse query name for field Model.m2m_1 clashes with field Target.id.', hint=('Rename field Target.id or add/change a related_name ' 'argument to the definition for field Model.m2m_1.'), obj=Model._meta.get_field('m2m_1'), id='E015', ), Error( 'Clash between accessors for Model.m2m_1 and Model.foreign_1.', hint=('Add or change a related_name argument to the definition ' 'for Model.m2m_1 or Model.foreign_1.'), obj=Model._meta.get_field('m2m_1'), id='E016', ), Error( 'Clash between reverse query names for Model.m2m_1 and Model.foreign_1.', hint=('Add or change a related_name argument to ' 'the definition for Model.m2m_1 or Model.foreign_1.'), obj=Model._meta.get_field('m2m_1'), id='E017', ), Error( 'Clash between accessors for Model.m2m_2 and Model.foreign_2.', hint=('Add or change a related_name argument to the definition ' 'for Model.m2m_2 or Model.foreign_2.'), obj=Model._meta.get_field('m2m_2'), id='E016', ), Error( 'Clash between reverse query names for Model.m2m_2 and Model.foreign_2.', hint=('Add or change a related_name argument to the definition ' 'for Model.m2m_2 or Model.foreign_2.'), obj=Model._meta.get_field('m2m_2'), id='E017', ), ] self.assertEqual(errors, expected)

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null

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6

6f997a6a6ce02b0840b0af18b4849233bc37f985

30

py

Python

draalcore/models/__init__.py

jojanper/draalcore

3d3f5a53efe32c721c34d7e48267328a4e9e8402

[ "MIT" ]

1

2017-04-25T10:54:55.000Z

draalcore/models/__init__.py

jojanper/draalcore

3d3f5a53efe32c721c34d7e48267328a4e9e8402

[ "MIT" ]

1

2022-02-10T06:48:36.000Z

draalcore/models/__init__.py

jojanper/draalcore

3d3f5a53efe32c721c34d7e48267328a4e9e8402

[ "MIT" ]

null

from .fields import * # noqa

15

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true

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0

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null

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0

null

0

1

0

1

0

1

0

6

b5005f5b90507ed2579315c816fdec7d94e88283

237

py

Python

providers/base_provider.py

tophertimzen/sephiroth

3c0e106197fba506da44b697796297c28f274955

[ "WTFPL" ]

1

2020-05-19T08:23:36.000Z

providers/base_provider.py

tophertimzen/sephiroth

3c0e106197fba506da44b697796297c28f274955

[ "WTFPL" ]

null

providers/base_provider.py

tophertimzen/sephiroth

3c0e106197fba506da44b697796297c28f274955

[ "WTFPL" ]

1

2020-05-19T08:23:41.000Z

class BaseProvider(): def _get_ranges(self): raise NotImplementedError def _process_ranges(self): raise NotImplementedError def get_processed_ranges(self): return self.processed_ranges

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0.666667

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237

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0.883041

0

0.285714

0

1

0.428571

false

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