xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

486f0a731365bfc5a6b660c0054e3908325c503d

22

py

Python

tests/gtrtest/__init__.py

plewis/phycas

9f5a4d9b2342dab907d14a46eb91f92ad80a5605

[ "MIT" ]

3

2015-09-24T23:12:57.000Z

2021-04-12T07:07:01.000Z

tests/gtrtest/__init__.py

plewis/phycas

9f5a4d9b2342dab907d14a46eb91f92ad80a5605

[ "MIT" ]

null

tests/gtrtest/__init__.py

plewis/phycas

9f5a4d9b2342dab907d14a46eb91f92ad80a5605

[ "MIT" ]

1

2015-11-23T10:35:43.000Z

from gtrtest import *

11

21

0.772727

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5.666667

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1

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1

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null

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1

0

5

6fa18635fb3f62309855602f9018e6aa8f8fb09f

187

py

Python

app/source/geo_django_rf/restapi/views/__init__.py

JanNash/geo-django-rf-server

57a2d12204cdd8abceaa1c46c22f2947a8d45c20

[ "BSD-3-Clause" ]

null

app/source/geo_django_rf/restapi/views/__init__.py

JanNash/geo-django-rf-server

57a2d12204cdd8abceaa1c46c22f2947a8d45c20

[ "BSD-3-Clause" ]

null

app/source/geo_django_rf/restapi/views/__init__.py

JanNash/geo-django-rf-server

57a2d12204cdd8abceaa1c46c22f2947a8d45c20

[ "BSD-3-Clause" ]

null

from .user_view_set import UserViewSet from .group_view_set import GroupViewSet from .profile_view_set import ProfileViewSet __all__ = ['UserViewSet', 'GroupViewSet', 'ProfileViewSet']

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0.823529

22

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187

6

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0

null

0

1

0

1

0

5

6fe5d3fc1678d65fd18e8ebb5876204bf458458b

46

py

Python

script.py

jonmabale/automate-the-boring-stuff

e9057ca38c8c59a423fcea88f362140bd40ebf5e

[ "MIT" ]

null

script.py

jonmabale/automate-the-boring-stuff

e9057ca38c8c59a423fcea88f362140bd40ebf5e

[ "MIT" ]

null

script.py

jonmabale/automate-the-boring-stuff

e9057ca38c8c59a423fcea88f362140bd40ebf5e

[ "MIT" ]

null

#! /usr/local/bin/env python3 # Sandbox file

11.5

29

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7

46

4.571429

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0.152174

46

3

30

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1

0

1

0

null

0

1

0

5

6ff2d7e0b80ef42bea493ae5d57e41f4e2684a01

132

py

Python

project/learning/admin.py

DmitrySevostianov/learning_test_project

f41eb38283a572ee6d11ee3b99da8eebab039d89

[ "MIT" ]

null

project/learning/admin.py

DmitrySevostianov/learning_test_project

f41eb38283a572ee6d11ee3b99da8eebab039d89

[ "MIT" ]

null

project/learning/admin.py

DmitrySevostianov/learning_test_project

f41eb38283a572ee6d11ee3b99da8eebab039d89

[ "MIT" ]

null

from django.contrib import admin from .models import Course, Lesson admin.site.register(Course) admin.site.register(Lesson)

18.857143

35

0.772727

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132

5.666667

0.555556

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0

null

0

1

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1

0

5

b5002230c75bb8e0da487ac3ad22219ca2331baa

8,740

py

Python

data.py

pkumar0508/project-euler

ffe91e7d02173142d01b45dded487b13582010fb

[ "Apache-2.0" ]

null

data.py

pkumar0508/project-euler

ffe91e7d02173142d01b45dded487b13582010fb

[ "Apache-2.0" ]

null

data.py

pkumar0508/project-euler

ffe91e7d02173142d01b45dded487b13582010fb

[ "Apache-2.0" ]

null

def parse_grid(s): return [[int(x) for x in row.split()] for row in s.strip().split('\n')] def parse_long_string(s): return ''.join(s.strip().split('\n')) def parse_number_list(s): return [int(x) for x in s.strip().split('\n')] problem0008 = ''' 73167176531330624919225119674426574742355349194934 96983520312774506326239578318016984801869478851843 85861560789112949495459501737958331952853208805511 12540698747158523863050715693290963295227443043557 66896648950445244523161731856403098711121722383113 62229893423380308135336276614282806444486645238749 30358907296290491560440772390713810515859307960866 70172427121883998797908792274921901699720888093776 65727333001053367881220235421809751254540594752243 52584907711670556013604839586446706324415722155397 53697817977846174064955149290862569321978468622482 83972241375657056057490261407972968652414535100474 82166370484403199890008895243450658541227588666881 16427171479924442928230863465674813919123162824586 17866458359124566529476545682848912883142607690042 24219022671055626321111109370544217506941658960408 07198403850962455444362981230987879927244284909188 84580156166097919133875499200524063689912560717606 05886116467109405077541002256983155200055935729725 71636269561882670428252483600823257530420752963450 ''' problem0011 = ''' 08 02 22 97 38 15 00 40 00 75 04 05 07 78 52 12 50 77 91 08 49 49 99 40 17 81 18 57 60 87 17 40 98 43 69 48 04 56 62 00 81 49 31 73 55 79 14 29 93 71 40 67 53 88 30 03 49 13 36 65 52 70 95 23 04 60 11 42 69 24 68 56 01 32 56 71 37 02 36 91 22 31 16 71 51 67 63 89 41 92 36 54 22 40 40 28 66 33 13 80 24 47 32 60 99 03 45 02 44 75 33 53 78 36 84 20 35 17 12 50 32 98 81 28 64 23 67 10 26 38 40 67 59 54 70 66 18 38 64 70 67 26 20 68 02 62 12 20 95 63 94 39 63 08 40 91 66 49 94 21 24 55 58 05 66 73 99 26 97 17 78 78 96 83 14 88 34 89 63 72 21 36 23 09 75 00 76 44 20 45 35 14 00 61 33 97 34 31 33 95 78 17 53 28 22 75 31 67 15 94 03 80 04 62 16 14 09 53 56 92 16 39 05 42 96 35 31 47 55 58 88 24 00 17 54 24 36 29 85 57 86 56 00 48 35 71 89 07 05 44 44 37 44 60 21 58 51 54 17 58 19 80 81 68 05 94 47 69 28 73 92 13 86 52 17 77 04 89 55 40 04 52 08 83 97 35 99 16 07 97 57 32 16 26 26 79 33 27 98 66 88 36 68 87 57 62 20 72 03 46 33 67 46 55 12 32 63 93 53 69 04 42 16 73 38 25 39 11 24 94 72 18 08 46 29 32 40 62 76 36 20 69 36 41 72 30 23 88 34 62 99 69 82 67 59 85 74 04 36 16 20 73 35 29 78 31 90 01 74 31 49 71 48 86 81 16 23 57 05 54 01 70 54 71 83 51 54 69 16 92 33 48 61 43 52 01 89 19 67 48 ''' problem0013 = ''' 37107287533902102798797998220837590246510135740250 46376937677490009712648124896970078050417018260538 74324986199524741059474233309513058123726617309629 91942213363574161572522430563301811072406154908250 23067588207539346171171980310421047513778063246676 89261670696623633820136378418383684178734361726757 28112879812849979408065481931592621691275889832738 44274228917432520321923589422876796487670272189318 47451445736001306439091167216856844588711603153276 70386486105843025439939619828917593665686757934951 62176457141856560629502157223196586755079324193331 64906352462741904929101432445813822663347944758178 92575867718337217661963751590579239728245598838407 58203565325359399008402633568948830189458628227828 80181199384826282014278194139940567587151170094390 35398664372827112653829987240784473053190104293586 86515506006295864861532075273371959191420517255829 71693888707715466499115593487603532921714970056938 54370070576826684624621495650076471787294438377604 53282654108756828443191190634694037855217779295145 36123272525000296071075082563815656710885258350721 45876576172410976447339110607218265236877223636045 17423706905851860660448207621209813287860733969412 81142660418086830619328460811191061556940512689692 51934325451728388641918047049293215058642563049483 62467221648435076201727918039944693004732956340691 15732444386908125794514089057706229429197107928209 55037687525678773091862540744969844508330393682126 18336384825330154686196124348767681297534375946515 80386287592878490201521685554828717201219257766954 78182833757993103614740356856449095527097864797581 16726320100436897842553539920931837441497806860984 48403098129077791799088218795327364475675590848030 87086987551392711854517078544161852424320693150332 59959406895756536782107074926966537676326235447210 69793950679652694742597709739166693763042633987085 41052684708299085211399427365734116182760315001271 65378607361501080857009149939512557028198746004375 35829035317434717326932123578154982629742552737307 94953759765105305946966067683156574377167401875275 88902802571733229619176668713819931811048770190271 25267680276078003013678680992525463401061632866526 36270218540497705585629946580636237993140746255962 24074486908231174977792365466257246923322810917141 91430288197103288597806669760892938638285025333403 34413065578016127815921815005561868836468420090470 23053081172816430487623791969842487255036638784583 11487696932154902810424020138335124462181441773470 63783299490636259666498587618221225225512486764533 67720186971698544312419572409913959008952310058822 95548255300263520781532296796249481641953868218774 76085327132285723110424803456124867697064507995236 37774242535411291684276865538926205024910326572967 23701913275725675285653248258265463092207058596522 29798860272258331913126375147341994889534765745501 18495701454879288984856827726077713721403798879715 38298203783031473527721580348144513491373226651381 34829543829199918180278916522431027392251122869539 40957953066405232632538044100059654939159879593635 29746152185502371307642255121183693803580388584903 41698116222072977186158236678424689157993532961922 62467957194401269043877107275048102390895523597457 23189706772547915061505504953922979530901129967519 86188088225875314529584099251203829009407770775672 11306739708304724483816533873502340845647058077308 82959174767140363198008187129011875491310547126581 97623331044818386269515456334926366572897563400500 42846280183517070527831839425882145521227251250327 55121603546981200581762165212827652751691296897789 32238195734329339946437501907836945765883352399886 75506164965184775180738168837861091527357929701337 62177842752192623401942399639168044983993173312731 32924185707147349566916674687634660915035914677504 99518671430235219628894890102423325116913619626622 73267460800591547471830798392868535206946944540724 76841822524674417161514036427982273348055556214818 97142617910342598647204516893989422179826088076852 87783646182799346313767754307809363333018982642090 10848802521674670883215120185883543223812876952786 71329612474782464538636993009049310363619763878039 62184073572399794223406235393808339651327408011116 66627891981488087797941876876144230030984490851411 60661826293682836764744779239180335110989069790714 85786944089552990653640447425576083659976645795096 66024396409905389607120198219976047599490197230297 64913982680032973156037120041377903785566085089252 16730939319872750275468906903707539413042652315011 94809377245048795150954100921645863754710598436791 78639167021187492431995700641917969777599028300699 15368713711936614952811305876380278410754449733078 40789923115535562561142322423255033685442488917353 44889911501440648020369068063960672322193204149535 41503128880339536053299340368006977710650566631954 81234880673210146739058568557934581403627822703280 82616570773948327592232845941706525094512325230608 22918802058777319719839450180888072429661980811197 77158542502016545090413245809786882778948721859617 72107838435069186155435662884062257473692284509516 20849603980134001723930671666823555245252804609722 53503534226472524250874054075591789781264330331690 ''' problem0018 = ''' 75 95 64 17 47 82 18 35 87 10 20 04 82 47 65 19 01 23 75 03 34 88 02 77 73 07 63 67 99 65 04 28 06 16 70 92 41 41 26 56 83 40 80 70 33 41 48 72 33 47 32 37 16 94 29 53 71 44 65 25 43 91 52 97 51 14 70 11 33 28 77 73 17 78 39 68 17 57 91 71 52 38 17 14 91 43 58 50 27 29 48 63 66 04 68 89 53 67 30 73 16 69 87 40 31 04 62 98 27 23 09 70 98 73 93 38 53 60 04 23 ''' def readCipher1(): with open('cipher1.txt') as f: lines = f.readlines() return [int(x) for x in lines[0].strip().split(',')] def readRoman(): with open('roman.txt') as f: lines = f.readlines() return [x.strip() for x in lines] def readkeylog(): with open('keylog.txt') as f: lines = f.readlines() return [x.strip() for x in lines] def readpoker(): with open('poker.txt') as f: lines = f.readlines() return [(x.split()[:5], x.split()[5:]) for x in lines]

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1

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5

b5158a4cc4c39f7f232fb11d618525122361b4ff

19,645

py

Python

tests/integration/list_submission_tests.py

dael-victoria-reyes/data-act-broker-backend

f83c7cad29cac24d95f45a262710dc1564de7dc1

[ "CC0-1.0" ]

1

2019-06-22T21:53:16.000Z

tests/integration/list_submission_tests.py

dael-victoria-reyes/data-act-broker-backend

f83c7cad29cac24d95f45a262710dc1564de7dc1

[ "CC0-1.0" ]

null

tests/integration/list_submission_tests.py

dael-victoria-reyes/data-act-broker-backend

f83c7cad29cac24d95f45a262710dc1564de7dc1

[ "CC0-1.0" ]

null

from dataactcore.interfaces.db import GlobalDB from dataactcore.models.userModel import User from dataactcore.models.lookups import PUBLISH_STATUS_DICT, FILE_TYPE_DICT, FILE_STATUS_DICT, JOB_TYPE_DICT from dataactvalidator.health_check import create_app from tests.integration.baseTestAPI import BaseTestAPI from tests.integration.integration_test_helper import insert_submission, insert_job class ListSubmissionTests(BaseTestAPI): """ Test list submissions endpoint """ @classmethod def setUpClass(cls): """Set up class-wide resources (test data)""" super(ListSubmissionTests, cls).setUpClass() # TODO: refactor into a pytest fixture with create_app().app_context(): # get an admin and non-admin user sess = GlobalDB.db().session cls.session = sess admin_user = sess.query(User).filter(User.email == cls.test_users['admin_user']).one() cls.admin_user_id = admin_user.user_id other_user = sess.query(User).filter(User.email == cls.test_users['agency_user']).one() cls.other_user_id = other_user.user_id # set up submissions for dabs cls.non_admin_dabs_sub_id = insert_submission(sess, cls.other_user_id, cgac_code="SYS", start_date="10/2015", end_date="12/2015", is_quarter=True, is_fabs=False, publish_status_id=PUBLISH_STATUS_DICT['unpublished'], updated_at='01/01/2010') cls.admin_dabs_sub_id = insert_submission(sess, cls.admin_user_id, cgac_code="000", start_date="10/2015", end_date="12/2015", is_quarter=True, is_fabs=False, publish_status_id=PUBLISH_STATUS_DICT['unpublished'], updated_at='01/01/2012') cls.certified_dabs_sub_id = insert_submission(sess, cls.admin_user_id, cgac_code="SYS", start_date="10/2015", end_date="12/2015", is_quarter=True, is_fabs=False, publish_status_id=PUBLISH_STATUS_DICT['published']) # Add a couple jobs for dabs files insert_job(sess, FILE_TYPE_DICT['appropriations'], FILE_STATUS_DICT['complete'], JOB_TYPE_DICT['file_upload'], cls.non_admin_dabs_sub_id, filename='/path/to/test/file_1.csv', file_size=123, num_rows=3) insert_job(sess, FILE_TYPE_DICT['award'], FILE_STATUS_DICT['complete'], JOB_TYPE_DICT['file_upload'], cls.non_admin_dabs_sub_id, filename='/path/to/test/file_2.csv', file_size=123, num_rows=3) insert_job(sess, FILE_TYPE_DICT['award'], FILE_STATUS_DICT['complete'], JOB_TYPE_DICT['file_upload'], cls.certified_dabs_sub_id, filename='/path/to/test/file_part_2.csv', file_size=123, num_rows=3) # set up submissions for fabs cls.non_admin_fabs_sub_id = insert_submission(sess, cls.admin_user_id, cgac_code="SYS", start_date="10/2015", end_date="12/2015", is_fabs=True, publish_status_id=PUBLISH_STATUS_DICT['unpublished']) cls.admin_fabs_sub_id = insert_submission(sess, cls.other_user_id, cgac_code="000", start_date="10/2015", end_date="12/2015", is_fabs=True, publish_status_id=PUBLISH_STATUS_DICT['unpublished']) cls.published_fabs_sub_id = insert_submission(sess, cls.other_user_id, cgac_code="000", start_date="10/2015", end_date="12/2015", is_fabs=True, publish_status_id=PUBLISH_STATUS_DICT['published']) # Add a job for a FABS submission insert_job(sess, FILE_TYPE_DICT['fabs'], FILE_STATUS_DICT['complete'], JOB_TYPE_DICT['file_upload'], cls.admin_fabs_sub_id, filename=str(cls.admin_fabs_sub_id) + '/test_file.csv', file_size=123, num_rows=3) def setUp(self): """ Test set-up. """ super(ListSubmissionTests, self).setUp() self.login_admin_user() def sub_ids(self, response): """ Helper function to parse out the submission ids from an HTTP response. """ self.assertEqual(response.status_code, 200) result = response.json self.assertIn('submissions', result) return {sub['submission_id'] for sub in result['submissions']} def test_list_submissions_dabs_admin(self): """ Test with DABS submissions for an admin user. """ response = self.app.post_json("/v1/list_submissions/", {"certified": "mixed"}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_dabs_sub_id, self.admin_dabs_sub_id, self.certified_dabs_sub_id}) response = self.app.post_json("/v1/list_submissions/", {"certified": "false"}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_dabs_sub_id, self.admin_dabs_sub_id}) response = self.app.post_json("/v1/list_submissions/", {"certified": "true"}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.certified_dabs_sub_id}) def test_list_submissions_dabs_non_admin(self): """ Test with DABS submissions for a non admin user. """ self.login_user() response = self.app.post_json("/v1/list_submissions/", {"certified": "mixed"}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_dabs_sub_id, self.admin_dabs_sub_id}) response = self.app.post_json("/v1/list_submissions/", {"certified": "false"}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_dabs_sub_id, self.admin_dabs_sub_id}) response = self.app.post_json("/v1/list_submissions/", {"certified": "true"}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), set()) def test_list_submissions_fabs_admin(self): """ Test with FABS submissions for an admin user. """ response = self.app.post_json("/v1/list_submissions/", {"certified": "mixed", "fabs": True}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_fabs_sub_id, self.admin_fabs_sub_id, self.published_fabs_sub_id}) response = self.app.post_json("/v1/list_submissions/", {"certified": "false", "fabs": True}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_fabs_sub_id, self.admin_fabs_sub_id}) response = self.app.post_json("/v1/list_submissions/", {"certified": "true", "fabs": True}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.published_fabs_sub_id}) def test_list_submissions_fabs_non_admin(self): """ Test with FABS submissions for a non admin user. """ self.login_user() response = self.app.post_json("/v1/list_submissions/", {"certified": "mixed", "fabs": True}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.admin_fabs_sub_id, self.published_fabs_sub_id}) response = self.app.post_json("/v1/list_submissions/", {"certified": "false", "fabs": True}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.admin_fabs_sub_id}) response = self.app.post_json("/v1/list_submissions/", {"certified": "true", "fabs": True}, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.published_fabs_sub_id}) def test_list_submissions_filter_id(self): """ Test listing submissions with a submission_id filter applied. """ # Listing only the relevant submissions, even when an ID is provided that can't be reached post_json = { "certified": "mixed", "filters": { "submission_ids": [self.non_admin_dabs_sub_id, self.admin_fabs_sub_id] } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_dabs_sub_id}) self.login_user() # Not returning a result if the user doesn't have access to the submission post_json["filters"] = { "submission_ids": [self.certified_dabs_sub_id] } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), set()) def test_list_submissions_filter_date(self): """ Test listing submissions with a start and end date filter applied. """ # Listing only submissions that have been updated in the time frame post_json = { "certified": "mixed", "filters": { "last_modified_range": { "start_date": '12/31/2009', "end_date": '01/30/2010' } } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_dabs_sub_id}) # Time frame with no submission updates post_json["filters"] = { "last_modified_range": { "start_date": '12/31/2010', "end_date": '01/30/2011' } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), set()) # One day date range (shows inclusivity) post_json["filters"] = { "last_modified_range": { "start_date": '01/01/2010', "end_date": '01/01/2010' } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_dabs_sub_id}) # Breaks if one of the date filters isn't provided and the other is post_json["filters"] = { "last_modified_range": { "start_date": '01/01/2010' } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}, expect_errors=True) self.assertEqual(response.status_code, 400) self.assertEqual(response.json["message"], "Both start_date and end_date must be provided") # Breaks if date isn't valid post_json["filters"] = { "last_modified_range": { "start_date": '30/30/2010', "end_date": '01/01/2010' } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}, expect_errors=True) self.assertEqual(response.status_code, 400) self.assertEqual(response.json["message"], "Start or end date cannot be parsed into a date of format " "MM/DD/YYYY") # Breaks if start date is after end date post_json["filters"] = { "last_modified_range": { "start_date": '01/02/2010', "end_date": '01/01/2010' } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}, expect_errors=True) self.assertEqual(response.status_code, 400) self.assertEqual(response.json["message"], "Last modified start date cannot be greater than the end date") # Breaks if last_modified_range isn't an object post_json["filters"] = { "last_modified_range": [123, 456] } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}, expect_errors=True) self.assertEqual(response.status_code, 400) self.assertEqual(response.json["message"], "last_modified_range filter must be null or an object") def test_list_submissions_filter_agency(self): """ Test listing submissions with an agency_code filter applied. """ # Listing only the relevant submissions post_json = { "certified": "mixed", "filters": { "agency_codes": ['000'] } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.admin_dabs_sub_id}) self.login_user() # Not returning a result if the user doesn't have access to the submission post_json = { "certified": "mixed", "fabs": True, "filters": { "agency_codes": ['SYS'] } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), set()) self.login_admin_user() # Invalid agency code, valid length post_json = { "certified": "mixed", "filters": { "agency_codes": ['111'] } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}, expect_errors=True) self.assertEqual(response.status_code, 400) self.assertEqual(response.json["message"], "All codes in the agency_codes filter must be valid agency codes") # Invalid agency code, wrong length post_json["filters"] = { "agency_codes": ['12345'] } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}, expect_errors=True) self.assertEqual(response.status_code, 400) self.assertEqual(response.json["message"], "All codes in the agency_codes filter must be valid agency codes") # Invalid agency code, contains non-string post_json["filters"] = { "agency_codes": [['123', '456', '789'], 'SYS'] } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}, expect_errors=True) self.assertEqual(response.status_code, 400) self.assertEqual(response.json["message"], "All codes in the agency_codes filter must be valid agency codes") # Non-array being passed over post_json["filters"] = { "agency_codes": 'SYS' } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}, expect_errors=True) self.assertEqual(response.status_code, 400) self.assertEqual(response.json["message"], "agency_codes filter must be null or an array") def test_list_submissions_filter_filename(self): """ Test listing submissions with an file_names filter applied. """ # List only submissions with job files post_json = { "certified": "mixed", "filters": { "file_names": ['file'] } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_dabs_sub_id, self.certified_dabs_sub_id}) # Not returning a result if the string doesn't exist in a file name (even if it exists in a path to it) post_json["filters"] = { "file_names": ['test'] } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), set()) # Returning both submissions if each has even one job that matches one of the given strings (testing multiple) post_json["filters"] = { "file_names": ['part', '_1'] } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_dabs_sub_id, self.certified_dabs_sub_id}) # Non-array being passed over (error) post_json["filters"] = { "file_names": 'part' } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}, expect_errors=True) self.assertEqual(response.status_code, 400) self.assertEqual(response.json["message"], "file_names filter must be null or an array") # non-local style submission post_json = { "certified": "mixed", "fabs": True, "filters": { "file_names": ['test'] } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.admin_fabs_sub_id}) # Ignores the ID (despite it being part of the file path, but not the name) post_json["filters"] = { "file_names": [str(self.admin_fabs_sub_id)] } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), set()) def test_list_submissions_filter_user_id(self): """ Test listing submissions with a user_id filter applied. """ # Listing only the relevant submissions, even when an ID is provided that can't be reached post_json = { "certified": "mixed", "filters": { "user_ids": [self.other_user_id, -1] } } response = self.app.post_json("/v1/list_submissions/", post_json, headers={"x-session-id": self.session_id}) self.assertEqual(self.sub_ids(response), {self.non_admin_dabs_sub_id})

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0.057122

0.070212

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0.811424

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null

0

5

d23da04e2ddd1fbd3ec8bd92fa0df474bf58c46a

893

py

Python

pava/implementation/natives/sun/java2d/loops/GraphicsPrimitiveMgr.py

laffra/pava

54d10cf7f8def2f96e254c0356623d08f221536f

[ "MIT" ]

4

2017-03-30T16:51:16.000Z

2020-10-05T12:25:47.000Z

pava/implementation/natives/sun/java2d/loops/GraphicsPrimitiveMgr.py

laffra/pava

54d10cf7f8def2f96e254c0356623d08f221536f

[ "MIT" ]

null

pava/implementation/natives/sun/java2d/loops/GraphicsPrimitiveMgr.py

laffra/pava

54d10cf7f8def2f96e254c0356623d08f221536f

[ "MIT" ]

null

def add_native_methods(clazz): def initIDs__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__(a0, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10, a11): raise NotImplementedError() def registerNativeLoops____(a0): raise NotImplementedError() clazz.initIDs__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__ = staticmethod(initIDs__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__java_lang_Class__) clazz.registerNativeLoops____ = staticmethod(registerNativeLoops____)

81.181818

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0.894737

133

893

4.864662

0.18797

0.408037

0.66306

0.788253

0.695518

0

0.018051

0.069429

893

10

420

89.3

0.760529

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0.285714

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0.428571

0

null

1

0

1

0

null

0

1

0

5

d242ff5b2251944490e665b0435d408a0f3a23e6

48

py

Python

src/tox_travis/__init__.py

Djailla/tox-travis

dc3d05c72822a45d48946b380be680039a9c2f50

[ "MIT" ]

117

2015-05-22T16:10:37.000Z

2017-09-15T17:15:12.000Z

src/tox_travis/__init__.py

Djailla/tox-travis

dc3d05c72822a45d48946b380be680039a9c2f50

[ "MIT" ]

89

2017-09-20T18:17:47.000Z

2021-01-04T21:39:40.000Z

src/tox_travis/__init__.py

Djailla/tox-travis

dc3d05c72822a45d48946b380be680039a9c2f50

[ "MIT" ]

32

2017-10-29T23:32:13.000Z

2022-02-16T11:52:43.000Z

"""Make it easy to work with Tox and Travis."""

24

47

0.666667

9

48

3.555556

1

0

0.1875

48

1

48

0.820513

0.854167

0

null

0

null

0

null

0

null

1

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true

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0

1

0

1

0

null

0

1

0

5

d2785244fb0e3480f011b5c2f22b31bc3ed1dbec

53

py

Python

ex3.py

Cloudlie/pythonlearning

347a2ea3b85450139e0718aec37ddf6998bd5678

[ "MIT" ]

null

ex3.py

Cloudlie/pythonlearning

347a2ea3b85450139e0718aec37ddf6998bd5678

[ "MIT" ]

null

ex3.py

Cloudlie/pythonlearning

347a2ea3b85450139e0718aec37ddf6998bd5678

[ "MIT" ]

null

print 'I will now count:' print 10 / 3 print 10.0/3

13.25

25

0.660377

12

53

2.916667

0.666667

0.4

0

0.170732

0.226415

53

3

26

17.666667

0.682927

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0.320755

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null

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null

1

0

1

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null

0

1

0

1

0

5

9627cc96d03d7d77333110a01623e996804293d3

127

py

Python

pytorch_h5dataset/utils.py

CeadeS/PyTorchH5Dataset

9ee6e49f2a780345abd708abf2e0c47bb5475e0a

[ "BSD-3-Clause" ]

null

pytorch_h5dataset/utils.py

CeadeS/PyTorchH5Dataset

9ee6e49f2a780345abd708abf2e0c47bb5475e0a

[ "BSD-3-Clause" ]

null

pytorch_h5dataset/utils.py

CeadeS/PyTorchH5Dataset

9ee6e49f2a780345abd708abf2e0c47bb5475e0a

[ "BSD-3-Clause" ]

null

from torch.nn import Module class NormImageUint8ToFloat(Module): def forward(self, im) : return 2.*((im/255.)-.5)

25.4

36

0.661417

17

127

4.941176

0.882353

0

0.058824

0.19685

127

5

37

25.4

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0

1

0.25

false

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0.25

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null

0

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0

null

0

1

0

1

0

5

9646deeed2d5bda54fb5df2def9304428850767b

381

py

Python

DeepLearning/Python/Chapter 4/Ch04-04-02-diff.py

BlueWay-KU/Study

a86405cdc3011eaed1b980b562b75df1e9ce90a8

[ "MIT" ]

null

DeepLearning/Python/Chapter 4/Ch04-04-02-diff.py

BlueWay-KU/Study

a86405cdc3011eaed1b980b562b75df1e9ce90a8

[ "MIT" ]

null

DeepLearning/Python/Chapter 4/Ch04-04-02-diff.py

BlueWay-KU/Study

a86405cdc3011eaed1b980b562b75df1e9ce90a8

[ "MIT" ]

null

def numerical_diff(f, x): h = 1e-4 return (f(x+h) - f(x-h)) / (2*h) def function_1(x): return 0.01*x**2 + 0.1*x def function_2(x): return x[0]**2 + x[1]**2 def function_tmp1(x0): return x0*x0 + 4.0**2.0 print(numerical_diff(function_tmp1, 3.0)) def function_tmp2(x1): return 3.0**2.0 + x1*x1 print(numerical_diff(function_tmp2, 4.0))

20.052632

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0.585302

76

381

2.815789

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381

19

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0.307692

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0.153846

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1

0

1

0

null

0

1

0

1

0

5

964ad81d4e7347ced2c0354c2533c9005bb9b08f

279

py

Python

napari/layers/image/__init__.py

MaksHess/napari

64a144607342c02177fc62fa83a3442ace0a98e7

[ "BSD-3-Clause" ]

1,345

2019-03-03T21:14:14.000Z

2022-03-31T19:46:39.000Z

napari/layers/image/__init__.py

MaksHess/napari

64a144607342c02177fc62fa83a3442ace0a98e7

[ "BSD-3-Clause" ]

3,904

2019-03-02T01:30:24.000Z

2022-03-31T20:17:27.000Z

napari/layers/image/__init__.py

MaksHess/napari

64a144607342c02177fc62fa83a3442ace0a98e7

[ "BSD-3-Clause" ]

306

2019-03-29T17:09:10.000Z

2022-03-30T09:54:11.000Z

from . import _image_key_bindings from .image import Image # Note that importing _image_key_bindings is needed as the Image layer gets # decorated with keybindings during that process, but it is not directly needed # by our users and so is deleted below del _image_key_bindings

34.875

79

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46

279

4.76087

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0.16129

279

7

80

39.857143

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null

0

1

0

1

0

1

0

5

9660f7b2a815a98e1362dbf8b9bc9edd3bbbda07

1,081

py

Python

python/test/test_permissions_api.py

openlattice/api-clients

1d5be9861785b295089b732f37464e31bf80c8ca

[ "Apache-2.0" ]

null

python/test/test_permissions_api.py

openlattice/api-clients

1d5be9861785b295089b732f37464e31bf80c8ca

[ "Apache-2.0" ]

1

2021-01-20T00:20:01.000Z

python/test/test_permissions_api.py

openlattice/api-clients

1d5be9861785b295089b732f37464e31bf80c8ca

[ "Apache-2.0" ]

null

# coding: utf-8 """ OpenLattice API OpenLattice API # noqa: E501 The version of the OpenAPI document: 0.0.1 Contact: support@openlattice.com Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import unittest import openlattice from openlattice.api.permissions_api import PermissionsApi # noqa: E501 from openlattice.rest import ApiException class TestPermissionsApi(unittest.TestCase): """PermissionsApi unit test stubs""" def setUp(self): self.api = openlattice.api.permissions_api.PermissionsApi() # noqa: E501 def tearDown(self): pass def test_get_acl(self): """Test case for get_acl Get the ACL for the given ACL Key, only if the user is the owner of the ACL Key. # noqa: E501 """ pass def test_update_acl(self): """Test case for update_acl Updates the ACL for a particular ACL Key, only if the user is the owner of the ACL Key. # noqa: E501 """ pass if __name__ == '__main__': unittest.main()

22.061224

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0.668825

144

1,081

4.875

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1,081

48

110

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false

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null

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null

0

1

0

1

0

1

0

5

9669c2ee2dc216abe33c57e73b6f8bf2d6511f51

66

py

Python

ladyns/__init__.py

Qi-Xin/ladyns

b4eb4ae9ee4184283bd26c6951bc4c614fc02351

[ "MIT" ]

1

2022-03-28T19:57:44.000Z

ladyns/__init__.py

Qi-Xin/ladyns

b4eb4ae9ee4184283bd26c6951bc4c614fc02351

[ "MIT" ]

null

ladyns/__init__.py

Qi-Xin/ladyns

b4eb4ae9ee4184283bd26c6951bc4c614fc02351

[ "MIT" ]

1

2021-06-14T23:15:57.000Z

from ladyns.estimate import * import ladyns.inference as inference

33

36

0.848485

9

66

6.222222

0.666667

0

0.106061

66

2

36

33

0.949153

0

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true

0

1

0

1

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null

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1

0

null

0

1

0

1

0

1

0

5

968b28cdc862b0021a7216beecd36e6a3c374aa5

10,139

py

Python

config/playbooks/vault/settings_production_secrets.py

aehlke/manabi

1dfdd4ecb9c1214b6a70268be0dcfeda9da8754b

[ "MIT" ]

14

2015-10-03T07:34:28.000Z

2021-09-20T07:10:29.000Z

config/playbooks/vault/settings_production_secrets.py

aehlke/manabi

1dfdd4ecb9c1214b6a70268be0dcfeda9da8754b

[ "MIT" ]

23

2019-10-25T08:47:23.000Z

2022-01-30T02:00:45.000Z

config/playbooks/vault/settings_production_secrets.py

aehlke/manabi

1dfdd4ecb9c1214b6a70268be0dcfeda9da8754b

[ "MIT" ]

7

2016-10-04T08:10:36.000Z

2021-09-20T07:10:33.000Z

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969612e4bc29b4bf5c332687933e52546d948fd2

192

py

Python

tina/pars/base.py

xuhao1/taichi_three

25fdf047da4c93df36a047a0be3cc47225d328c9

[ "MIT" ]

152

2020-06-17T09:08:59.000Z

2022-03-30T13:48:49.000Z

tina/pars/base.py

xuhao1/taichi_three

25fdf047da4c93df36a047a0be3cc47225d328c9

[ "MIT" ]

46

2020-06-20T15:15:57.000Z

2022-03-24T20:03:18.000Z

tina/pars/base.py

xuhao1/taichi_three

25fdf047da4c93df36a047a0be3cc47225d328c9

[ "MIT" ]

27

2020-06-20T14:25:55.000Z

2022-03-12T08:11:31.000Z

from ..common import * @ti.data_oriented class ParsEditBase: def __init__(self, pars): self.pars = pars def __getattr__(self, attr): return getattr(self.pars, attr)

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5

96967499a9604b253f13e3ec6374c8c3cbd4096c

372

py

Python

hknweb/candidate/admin/__init__.py

jyxzhang/hknweb

a01ffd8587859bf63c46213be6a0c8b87164a5c2

[ "MIT" ]

null

hknweb/candidate/admin/__init__.py

jyxzhang/hknweb

a01ffd8587859bf63c46213be6a0c8b87164a5c2

[ "MIT" ]

null

hknweb/candidate/admin/__init__.py

jyxzhang/hknweb

a01ffd8587859bf63c46213be6a0c8b87164a5c2

[ "MIT" ]

null

from hknweb.candidate.admin.announcement import AnnouncementAdmin from hknweb.candidate.admin.activities import BitByteActivityAdmin, OffChallengeAdmin from hknweb.candidate.admin.requirements import ( RequirementAdminGeneral, CandidateFormAdmin, MiscRequirementAdmin, RequirementMandatoryAdmin, RequirementMergeAdmin, MiscRequirementEntryAdmin, )

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739e79eb281f2735aab4b04c5ac957fb06434bb5

116

py

Python

examples/client-gen/tictactoe/instructions/__init__.py

kevinheavey/anchorpy

d4cc28365c6adaeaec7f5001fa6b8a3e719b41ad

[ "MIT" ]

87

2021-09-26T18:14:07.000Z

2022-03-28T08:22:24.000Z

examples/client-gen/tictactoe/instructions/__init__.py

kevinheavey/anchorpy

d4cc28365c6adaeaec7f5001fa6b8a3e719b41ad

[ "MIT" ]

15

2021-10-07T16:12:23.000Z

2022-03-20T21:04:40.000Z

examples/client-gen/tictactoe/instructions/__init__.py

kevinheavey/anchorpy

d4cc28365c6adaeaec7f5001fa6b8a3e719b41ad

[ "MIT" ]

16

2021-10-16T04:40:28.000Z

2022-03-18T16:49:40.000Z

from .setup_game import setup_game, SetupGameArgs, SetupGameAccounts from .play import play, PlayArgs, PlayAccounts

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1

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5

73b33dc4e6f144d064cbd8fff82be8d2ad2816b6

23,254

py

Python

src/titiler/core/tests/test_factories.py

mackdelany/titiler

b2a76185d96af9aa8b653fd8134bbaa591d637a5

[ "MIT" ]

null

src/titiler/core/tests/test_factories.py

mackdelany/titiler

b2a76185d96af9aa8b653fd8134bbaa591d637a5

[ "MIT" ]

null

src/titiler/core/tests/test_factories.py

mackdelany/titiler

b2a76185d96af9aa8b653fd8134bbaa591d637a5

[ "MIT" ]

null

"""Test TiTiler Tiler Factories.""" import json import os import pathlib from typing import Dict, Type from unittest.mock import patch from urllib.parse import urlencode import attr import morecantile from rio_tiler.io import BaseReader, COGReader, MultiBandReader, STACReader from titiler.core.dependencies import TMSParams, WebMercatorTMSParams from titiler.core.errors import DEFAULT_STATUS_CODES, add_exception_handlers from titiler.core.factory import ( MultiBandTilerFactory, MultiBaseTilerFactory, TilerFactory, TMSFactory, ) from titiler.core.resources.enums import OptionalHeader from .conftest import DATA_DIR, mock_rasterio_open, parse_img from fastapi import FastAPI from starlette.testclient import TestClient def test_TilerFactory(): """Test TilerFactory class.""" cog = TilerFactory() assert len(cog.router.routes) == 26 assert cog.tms_dependency == TMSParams cog = TilerFactory(router_prefix="something", tms_dependency=WebMercatorTMSParams) app = FastAPI() app.include_router(cog.router, prefix="/something") client = TestClient(app) response = client.get(f"/something/tilejson.json?url={DATA_DIR}/cog.tif") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert response.json()["tilejson"] response = client.get(f"/something/NZTM2000/tilejson.json?url={DATA_DIR}/cog.tif") assert response.status_code == 422 cog = TilerFactory(add_preview=False, add_part=False, add_statistics=False) assert len(cog.router.routes) == 17 app = FastAPI() cog = TilerFactory(optional_headers=[OptionalHeader.server_timing]) app.include_router(cog.router) add_exception_handlers(app, DEFAULT_STATUS_CODES) client = TestClient(app) response = client.get(f"/tiles/8/87/48?url={DATA_DIR}/cog.tif&rescale=0,1000") assert response.status_code == 200 assert response.headers["content-type"] == "image/jpeg" timing = response.headers["server-timing"] assert "dataread;dur" in timing assert "postprocess;dur" in timing assert "format;dur" in timing response = client.get( f"/tiles/8/87/48.tif?url={DATA_DIR}/cog.tif&expression=b1,b1,b1&return_mask=false" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/tiff; application=geotiff" meta = parse_img(response.content) assert meta["dtype"] == "int32" assert meta["count"] == 3 assert meta["width"] == 256 assert meta["height"] == 256 response = client.get( f"/tiles/8/84/47?url={DATA_DIR}/cog.tif&bidx=1&rescale=0,1000&colormap_name=viridis" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/png" cmap = urlencode( { "colormap": json.dumps( { "1": [58, 102, 24, 255], "2": [100, 177, 41], "3": "#b1b129", "4": "#ddcb9aFF", } ) } ) response = client.get(f"/tiles/8/84/47.png?url={DATA_DIR}/cog.tif&bidx=1&{cmap}") assert response.status_code == 200 assert response.headers["content-type"] == "image/png" # Bad colormap format cmap = urlencode({"colormap": json.dumps({"1": [58, 102]})}) response = client.get(f"/tiles/8/84/47.png?url={DATA_DIR}/cog.tif&bidx=1&{cmap}") assert response.status_code == 400 # no json encoding cmap = urlencode({"colormap": {"1": [58, 102]}}) response = client.get(f"/tiles/8/84/47.png?url={DATA_DIR}/cog.tif&bidx=1&{cmap}") assert response.status_code == 400 response = client.get( f"/preview?url={DATA_DIR}/cog.tif&rescale=0,1000&max_size=256" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/jpeg" timing = response.headers["server-timing"] assert "dataread;dur" in timing assert "postprocess;dur" in timing assert "format;dur" in timing response = client.get( f"/crop/-56.228,72.715,-54.547,73.188.png?url={DATA_DIR}/cog.tif&rescale=0,1000&max_size=256" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/png" timing = response.headers["server-timing"] assert "dataread;dur" in timing assert "postprocess;dur" in timing assert "format;dur" in timing response = client.get(f"/point/-56.228,72.715?url={DATA_DIR}/cog.tif") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" timing = response.headers["server-timing"] assert "dataread;dur" in timing response = client.get(f"/tilejson.json?url={DATA_DIR}/cog.tif") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert response.json()["tilejson"] response = client.get(f"/WorldCRS84Quad/tilejson.json?url={DATA_DIR}/cog.tif") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert response.json()["tilejson"] response_qs = client.get( f"/tilejson.json?url={DATA_DIR}/cog.tif&TileMatrixSetId=WorldCRS84Quad" ) assert response.json()["tiles"] == response_qs.json()["tiles"] response = client.get(f"/tilejson.json?url={DATA_DIR}/cog.tif&tile_format=png") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert response.json()["tilejson"] assert "png" in response.json()["tiles"][0] response = client.get(f"/tilejson.json?url={DATA_DIR}/cog.tif&minzoom=5&maxzoom=12") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert response.json()["tilejson"] assert response.json()["minzoom"] == 5 assert response.json()["maxzoom"] == 12 response = client.get( f"/WMTSCapabilities.xml?url={DATA_DIR}/cog.tif&minzoom=5&maxzoom=12" ) assert response.status_code == 200 assert response.headers["content-type"] == "application/xml" response = client.get(f"/bounds?url={DATA_DIR}/cog.tif") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert response.json()["bounds"] response = client.get(f"/info?url={DATA_DIR}/cog.tif") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert response.json()["band_metadata"] assert not response.json().get("minzoom") response = client.get(f"/info.geojson?url={DATA_DIR}/cog.tif") assert response.status_code == 200 assert response.headers["content-type"] == "application/geo+json" assert response.json()["type"] == "Feature" response = client.get(f"/metadata?url={DATA_DIR}/cog.tif&max_size=256") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert response.json()["statistics"] assert response.json()["band_metadata"] response = client.get( f"/metadata?url={DATA_DIR}/cog.tif&bounds=-56.228,72.715,-54.547,73.188&max_size=256" ) assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert response.json()["statistics"] assert response.json()["band_metadata"] response = client.get( f"/metadata?url={DATA_DIR}/cog.tif&bidx=1&histogram_range=0,100" ) assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert response.json()["statistics"]["1"]["histogram"][0][1] == 0.0 response = client.get(f"/metadata?url={DATA_DIR}/cog.tif&histogram_bins=4") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert len(response.json()["statistics"]["1"]["histogram"][0]) == 4 response = client.get( f"/metadata?url={DATA_DIR}/cog.tif&histogram_bins=1,2,3,4,5,6" ) assert response.status_code == 200 assert response.headers["content-type"] == "application/json" assert len(response.json()["statistics"]["1"]["histogram"][1]) == 6 assert response.json()["statistics"]["1"]["histogram"][1][0] == 1.0 response = client.get( f"/preview.png?url={DATA_DIR}/cog.tif&rescale=0,1000&max_size=256" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/png" meta = parse_img(response.content) assert 256 in (meta["width"], meta["height"]) response = client.get( f"/preview.png?url={DATA_DIR}/cog.tif&rescale=0,1000&max_size=256&height=512&width=512" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/png" meta = parse_img(response.content) assert meta["width"] == 512 assert meta["height"] == 512 response = client.get( f"/preview.png?url={DATA_DIR}/cog.tif&rescale=0,1000&max_size=0&nodata=0" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/png" meta = parse_img(response.content) assert meta["width"] == 2658 assert meta["height"] == 2667 response = client.get( f"/preview.png?url={DATA_DIR}/cog.tif&rescale=0,1000&max_size=0&nodata=0" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/png" meta = parse_img(response.content) assert meta["width"] == 2658 assert meta["height"] == 2667 response = client.get( f"/preview.tif?url={DATA_DIR}/cog_scale.tif&unscale=True&return_mask=false" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/tiff; application=geotiff" meta = parse_img(response.content) assert meta["dtype"] == "float32" assert meta["count"] == 1 response = client.get( f"/preview.tif?url={DATA_DIR}/cog_scale.tif&return_mask=false" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/tiff; application=geotiff" meta = parse_img(response.content) assert meta["dtype"] == "int16" assert meta["count"] == 1 feature = { "type": "Feature", "properties": {}, "geometry": { "type": "Polygon", "coordinates": [ [ [-59.23828124999999, 74.16408546675687], [-59.83154296874999, 73.15680773175981], [-58.73291015624999, 72.88087095711504], [-56.62353515625, 73.06104462497655], [-55.17333984375, 73.41588526207096], [-55.2392578125, 74.09799577518739], [-56.88720703125, 74.2895142503942], [-57.23876953124999, 74.30735341486248], [-59.23828124999999, 74.16408546675687], ] ], }, } feature_collection = {"type": "FeatureCollection", "features": [feature]} response = client.post(f"/crop?url={DATA_DIR}/cog.tif", json=feature) assert response.status_code == 200 assert response.headers["content-type"] == "image/png" response = client.post(f"/crop.tif?url={DATA_DIR}/cog.tif", json=feature) assert response.status_code == 200 assert response.headers["content-type"] == "image/tiff; application=geotiff" meta = parse_img(response.content) assert meta["dtype"] == "uint16" assert meta["count"] == 2 response = client.post(f"/crop/100x100.jpeg?url={DATA_DIR}/cog.tif", json=feature) assert response.status_code == 200 assert response.headers["content-type"] == "image/jpeg" meta = parse_img(response.content) assert meta["width"] == 100 assert meta["height"] == 100 # GET - statistics response = client.get(f"/statistics?url={DATA_DIR}/cog.tif&bidx=1,1,1") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" resp = response.json() assert len(resp) == 3 assert list(resp[0]) == [ "min", "max", "mean", "count", "sum", "std", "median", "majority", "minority", "unique", "percentile_2", "percentile_98", "valid_pixels", "masked_pixels", "valid_percent", ] response = client.get(f"/statistics?url={DATA_DIR}/cog.tif&bidx=1,1,1&p=4") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" resp = response.json() assert len(resp) == 3 assert list(resp[0]) == [ "min", "max", "mean", "count", "sum", "std", "median", "majority", "minority", "unique", "percentile_4", "valid_pixels", "masked_pixels", "valid_percent", ] response = client.get(f"/statistics?url={DATA_DIR}/cog.tif&categorical=true") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" resp = response.json() assert len(resp) == 1 assert list(resp[0]) == [ "categories", "valid_pixels", "masked_pixels", "valid_percent", ] assert len(resp[0]["categories"]) == 15 response = client.get( f"/statistics?url={DATA_DIR}/cog.tif&categorical=true&c=1&c=2&c=3&c=4" ) assert response.status_code == 200 assert response.headers["content-type"] == "application/json" resp = response.json() assert len(resp) == 1 assert list(resp[0]) == [ "categories", "valid_pixels", "masked_pixels", "valid_percent", ] assert len(resp[0]["categories"]) == 4 assert resp[0]["categories"]["4"] == 0 # POST - statistics response = client.post( f"/statistics?url={DATA_DIR}/cog.tif&bidx=1,1,1", json=feature ) assert response.status_code == 200 assert response.headers["content-type"] == "application/geo+json" resp = response.json() assert resp["type"] == "Feature" assert len(resp["properties"]["statistics"]) == 3 assert list(resp["properties"]["statistics"][0]) == [ "min", "max", "mean", "count", "sum", "std", "median", "majority", "minority", "unique", "percentile_2", "percentile_98", "valid_pixels", "masked_pixels", "valid_percent", ] response = client.post( f"/statistics?url={DATA_DIR}/cog.tif&bidx=1,1,1", json=feature_collection ) assert response.status_code == 200 assert response.headers["content-type"] == "application/geo+json" resp = response.json() assert resp["type"] == "FeatureCollection" assert len(resp["features"][0]["properties"]["statistics"]) == 3 assert list(resp["features"][0]["properties"]["statistics"][0]) == [ "min", "max", "mean", "count", "sum", "std", "median", "majority", "minority", "unique", "percentile_2", "percentile_98", "valid_pixels", "masked_pixels", "valid_percent", ] response = client.post( f"/statistics?url={DATA_DIR}/cog.tif&categorical=true", json=feature ) assert response.status_code == 200 assert response.headers["content-type"] == "application/geo+json" resp = response.json() assert resp["type"] == "Feature" assert len(resp["properties"]["statistics"]) == 1 assert list(resp["properties"]["statistics"][0]) == [ "categories", "valid_pixels", "masked_pixels", "valid_percent", ] assert len(resp["properties"]["statistics"][0]["categories"]) == 12 response = client.post( f"/statistics?url={DATA_DIR}/cog.tif&categorical=true&c=1&c=2&c=3&c=4", json=feature, ) assert response.status_code == 200 assert response.headers["content-type"] == "application/geo+json" resp = response.json() assert resp["type"] == "Feature" assert len(resp["properties"]["statistics"]) == 1 assert list(resp["properties"]["statistics"][0]) == [ "categories", "valid_pixels", "masked_pixels", "valid_percent", ] assert len(resp["properties"]["statistics"][0]["categories"]) == 4 assert resp["properties"]["statistics"][0]["categories"]["4"] == 0 @patch("rio_tiler.io.cogeo.rasterio") def test_MultiBaseTilerFactory(rio): """test MultiBaseTilerFactory.""" rio.open = mock_rasterio_open stac = MultiBaseTilerFactory(reader=STACReader) assert len(stac.router.routes) == 27 app = FastAPI() app.include_router(stac.router) add_exception_handlers(app, DEFAULT_STATUS_CODES) client = TestClient(app) response = client.get(f"/assets?url={DATA_DIR}/item.json") assert response.status_code == 200 assert len(response.json()) == 17 response = client.get(f"/bounds?url={DATA_DIR}/item.json") assert response.status_code == 200 assert len(response.json()["bounds"]) == 4 response = client.get(f"/info?url={DATA_DIR}/item.json&assets=B01") assert response.status_code == 200 assert response.json()["B01"] response = client.get(f"/info.geojson?url={DATA_DIR}/item.json&assets=B01") assert response.status_code == 200 assert response.headers["content-type"] == "application/geo+json" assert response.json()["type"] == "Feature" response = client.get(f"/metadata?url={DATA_DIR}/item.json&assets=B01&bidx=1") assert response.status_code == 200 assert response.json()["B01"]["statistics"]["1"] response = client.get( f"/preview.tif?url={DATA_DIR}/item.json&assets=B01&bidx=1,1,1&return_mask=false" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/tiff; application=geotiff" meta = parse_img(response.content) assert meta["dtype"] == "uint16" assert meta["count"] == 3 response = client.get(f"/preview.tif?url={DATA_DIR}/item.json") assert response.status_code == 400 response = client.get( f"/preview.tif?url={DATA_DIR}/item.json&expression=B01,B01,B01&return_mask=false" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/tiff; application=geotiff" meta = parse_img(response.content) assert meta["dtype"] == "int32" assert meta["count"] == 3 # GET - statistics response = client.get(f"/statistics?url={DATA_DIR}/item.json&assets=B01,B09") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" resp = response.json() assert len(resp) == 2 assert list(resp[0]) == [ "min", "max", "mean", "count", "sum", "std", "median", "majority", "minority", "unique", "percentile_2", "percentile_98", "valid_pixels", "masked_pixels", "valid_percent", ] @attr.s class BandFileReader(MultiBandReader): """Test MultiBand""" path: str = attr.ib() reader: Type[BaseReader] = attr.ib(default=COGReader) reader_options: Dict = attr.ib(factory=dict) tms: morecantile.TileMatrixSet = attr.ib( default=morecantile.tms.get("WebMercatorQuad") ) def __attrs_post_init__(self): """Parse Sceneid and get grid bounds.""" self.bands = sorted([p.stem for p in pathlib.Path(self.path).glob("B0*.tif")]) with self.reader(self._get_band_url(self.bands[0])) as cog: self.bounds = cog.bounds self.minzoom = cog.minzoom self.maxzoom = cog.maxzoom def _get_band_url(self, band: str) -> str: """Validate band's name and return band's url.""" return os.path.join(self.path, f"{band}.tif") def test_MultiBandTilerFactory(): """test MultiBandTilerFactory.""" bands = MultiBandTilerFactory(reader=BandFileReader) assert len(bands.router.routes) == 27 app = FastAPI() app.include_router(bands.router) add_exception_handlers(app, DEFAULT_STATUS_CODES) client = TestClient(app) response = client.get(f"/bands?url={DATA_DIR}") assert response.status_code == 200 assert response.json() == ["B01", "B09"] response = client.get(f"/info?url={DATA_DIR}&bands=B01") assert response.status_code == 200 assert response.json()["band_metadata"] == [["B01", {}]] response = client.get(f"/info.geojson?url={DATA_DIR}&bands=B01") assert response.status_code == 200 assert response.headers["content-type"] == "application/geo+json" response = client.get(f"/metadata?url={DATA_DIR}&bands=B01&bidx=1") assert response.status_code == 200 assert response.json()["statistics"]["B01"] response = client.get(f"/preview.tif?url={DATA_DIR}&return_mask=false") assert response.status_code == 400 response = client.get( f"/preview.tif?url={DATA_DIR}&bands=B01,B09,B01&return_mask=false" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/tiff; application=geotiff" meta = parse_img(response.content) assert meta["dtype"] == "uint16" assert meta["count"] == 3 response = client.get( f"/preview.tif?url={DATA_DIR}&expression=B01,B09,B01&return_mask=false" ) assert response.status_code == 200 assert response.headers["content-type"] == "image/tiff; application=geotiff" meta = parse_img(response.content) assert meta["dtype"] == "int32" assert meta["count"] == 3 # GET - statistics response = client.get(f"/statistics?url={DATA_DIR}&bands=B01,B09") assert response.status_code == 200 assert response.headers["content-type"] == "application/json" resp = response.json() assert len(resp) == 2 assert list(resp[0]) == [ "min", "max", "mean", "count", "sum", "std", "median", "majority", "minority", "unique", "percentile_2", "percentile_98", "valid_pixels", "masked_pixels", "valid_percent", ] def test_TMSFactory(): """test TMSFactory.""" tms_endpoints = TMSFactory(router_prefix="tms") assert len(tms_endpoints.router.routes) == 2 app = FastAPI() app.include_router(tms_endpoints.router, prefix="/tms") client = TestClient(app) response = client.get("/tms/tileMatrixSets") assert response.status_code == 200 body = response.json() assert len(body["tileMatrixSets"]) == 10 # morecantile has 10 defaults tms = list(filter(lambda m: m["id"] == "WebMercatorQuad", body["tileMatrixSets"]))[ 0 ] assert ( tms["links"][0]["href"] == "http://testserver/tms/tileMatrixSets/WebMercatorQuad" ) response = client.get("/tms/tileMatrixSets/WebMercatorQuad") assert response.status_code == 200 body = response.json() assert body["type"] == "TileMatrixSetType" assert body["identifier"] == "WebMercatorQuad"

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gateapi-python/gate_api/api/__init__.py

jarenmt/IEOPUMP

220f7f612d299f7305e82fe6c33661e6871f2d86

[ "MIT" ]

null

gateapi-python/gate_api/api/__init__.py

jarenmt/IEOPUMP

220f7f612d299f7305e82fe6c33661e6871f2d86

[ "MIT" ]

null

gateapi-python/gate_api/api/__init__.py

jarenmt/IEOPUMP

220f7f612d299f7305e82fe6c33661e6871f2d86

[ "MIT" ]

null

from __future__ import absolute_import # flake8: noqa # import apis into api package from gate_api.api.delivery_api import DeliveryApi from gate_api.api.futures_api import FuturesApi from gate_api.api.margin_api import MarginApi from gate_api.api.options_api import OptionsApi from gate_api.api.spot_api import SpotApi from gate_api.api.wallet_api import WalletApi from gate_api.api.withdrawal_api import WithdrawalApi

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py

Python

allrank/utils/args_utils.py

almajo/allRank

845c191ed00e112351437c8884cbe5573def9531

[ "Apache-2.0" ]

473

2019-10-10T13:51:24.000Z

2022-03-31T18:19:42.000Z

allrank/utils/args_utils.py

almajo/allRank

845c191ed00e112351437c8884cbe5573def9531

[ "Apache-2.0" ]

26

2020-01-23T09:06:17.000Z

2022-03-04T23:08:13.000Z

allrank/utils/args_utils.py

almajo/allRank

845c191ed00e112351437c8884cbe5573def9531

[ "Apache-2.0" ]

63

2019-10-14T18:12:27.000Z

2022-03-18T20:47:04.000Z

def split_as_strings(splits): return [str(x).strip() for x in splits.split(",")]

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py

Python

examples/catalyst_rl/env.py

gr33n-made/catalyst

bd413abc908ef7cbdeab42b0e805277a791e3ddb

[ "Apache-2.0" ]

2,693

2019-01-23T19:16:12.000Z

2022-03-31T02:12:42.000Z

examples/catalyst_rl/env.py

gr33n-made/catalyst

bd413abc908ef7cbdeab42b0e805277a791e3ddb

[ "Apache-2.0" ]

763

2019-01-22T20:12:56.000Z

2022-03-27T18:36:10.000Z

examples/catalyst_rl/env.py

gr33n-made/catalyst

bd413abc908ef7cbdeab42b0e805277a791e3ddb

[ "Apache-2.0" ]

445

2019-01-23T17:07:09.000Z

2022-03-30T05:38:45.000Z

# flake8: noqa class IEnvironment: pass

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py

Python

promisedio/loop/_internal.py

promisedio/uv

b2da55e28da4a3185d810055468389822ec94f2b

[ "MIT" ]

null

promisedio/loop/_internal.py

promisedio/uv

b2da55e28da4a3185d810055468389822ec94f2b

[ "MIT" ]

null

promisedio/loop/_internal.py

promisedio/uv

b2da55e28da4a3185d810055468389822ec94f2b

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py

Python

bvpl/coexist/find_corners.py

mirestrepo/voxels-at-lems

df47d031653d2ad877a97b3c1ea574b924b7d4c2

[ "BSD-2-Clause" ]

2

2015-09-18T00:17:16.000Z

2019-02-06T04:41:29.000Z

bvpl/coexist/find_corners.py

mirestrepo/voxels-at-lems

df47d031653d2ad877a97b3c1ea574b924b7d4c2

[ "BSD-2-Clause" ]

null

bvpl/coexist/find_corners.py

mirestrepo/voxels-at-lems

df47d031653d2ad877a97b3c1ea574b924b7d4c2

[ "BSD-2-Clause" ]

null

#!/usr/bin/python # Script to run find 2d corners on appearance grid # Author : Isabel Restrepo #8-31-2009 import bvpl_batch import time import sys import os #time.sleep(30); bvpl_batch.register_processes(); bvpl_batch.register_datatypes(); class dbvalue: def __init__(self, index, type): self.id = index # unsigned integer self.type = type # string save_hue = 0; #data_dir = "/Users/isa/Experiments/CapitolSFM/few_windows" #output_dir = "/Users/isa/Experiments/CapitolSFM/few_windows/ocp+app/all_directions" data_dir = sys.argv[1]; output_dir = sys.argv[2]; if not os.path.isdir( output_dir + "/"): os.mkdir( output_dir + "/"); print("Load Voxel Grid"); bvpl_batch.init_process("bvxmLoadGridProcess"); bvpl_batch.set_input_string(0, data_dir +"/KL_gaussf1.vox"); bvpl_batch.set_input_string(1,"bsta_gauss_f1"); bvpl_batch.run_process(); (world_id,world_type)= bvpl_batch.commit_output(0); app_grid = dbvalue(world_id,world_type); print("Load Voxel Grid"); bvpl_batch.init_process("bvxmLoadGridProcess"); bvpl_batch.set_input_string(0, data_dir +"/ocp.vox"); bvpl_batch.set_input_string(1,"float"); bvpl_batch.run_process(); (world_id,world_type)= bvpl_batch.commit_output(0); ocp_grid = dbvalue(world_id,world_type); print("Creating corner 2d kernel"); bvpl_batch.init_process("bvplCreateCorner2dKernelVectorProcess"); bvpl_batch.set_input_unsigned(0, 3); #half length bvpl_batch.set_input_unsigned(1, 3); #half width bvpl_batch.set_input_unsigned(2, 1); #half thickness bvpl_batch.run_process(); (kernel_id,kernel_type)= bvpl_batch.commit_output(0); kernel_vector = dbvalue(kernel_id,kernel_type); print("Running Kernels"); bvpl_batch.init_process("bvplOperateOcpAndAppProcess"); bvpl_batch.set_input_from_db(0,ocp_grid ); bvpl_batch.set_input_from_db(1,app_grid ); bvpl_batch.set_input_from_db(2,kernel_vector); bvpl_batch.set_input_string(3,"find_surface"); bvpl_batch.set_input_string(4,"gauss_convolution"); bvpl_batch.set_input_string(5, output_dir + "/resp.vox"); bvpl_batch.set_input_string(6, output_dir + "/id.vox"); bvpl_batch.run_process(); (all_resp_grid_id,all_resp_grid_type)= bvpl_batch.commit_output(0); all_resp_grid = dbvalue(all_resp_grid_id,all_resp_grid_type); (all_id_grid_id,all_id_grid_type)= bvpl_batch.commit_output(1); all_id_grid = dbvalue(all_id_grid_id, all_id_grid_type); print("Getting top response"); bvpl_batch.init_process("bvplExtractTopResponseProcess"); bvpl_batch.set_input_from_db(0,all_resp_grid ); bvpl_batch.set_input_from_db(1,all_id_grid); bvpl_batch.set_input_unsigned(2,0); bvpl_batch.set_input_string(3, output_dir + "/top_resp.vox"); bvpl_batch.set_input_string(4, output_dir + "/top_id.vox"); bvpl_batch.run_process(); (response_grid_id,response_grid_type)= bvpl_batch.commit_output(0); response_grid = dbvalue(response_grid_id,response_grid_type); (id_grid_id,id_grid_type)= bvpl_batch.commit_output(1); id_grid = dbvalue(id_grid_id,id_grid_type); if save_hue : print("Converting ID to Hue "); bvpl_batch.init_process("bvplConvertIdToHueProcess"); bvpl_batch.set_input_from_db(0,id_grid ); bvpl_batch.set_input_from_db(1,response_grid ); bvpl_batch.set_input_from_db(2,kernel_vector); bvpl_batch.set_input_string(3, output_dir + "/hue.vox"); bvpl_batch.set_input_string(4, output_dir + "/hue.svg"); bvpl_batch.run_process(); (hue_grid_id,hue_grid_type)= bvpl_batch.commit_output(0); hue_grid = dbvalue(hue_grid_id,hue_grid_type); print("Writing Orientation Grid"); bvpl_batch.init_process("bvxmGridToImageStackProcess"); bvpl_batch.set_input_from_db(0,hue_grid); bvpl_batch.set_input_string(1,"vnl_float_4"); bvpl_batch.set_input_string(2,output_dir + "/hue_world/"); bvpl_batch.run_process(); print("Writing Response Grid"); bvpl_batch.init_process("bvxmSaveGridRawProcess"); bvpl_batch.set_input_from_db(0,response_grid); bvpl_batch.set_input_string(1,output_dir + "/resp.raw"); bvpl_batch.run_process();

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0.792271

634

3,933

4.493691

0.179811

0.176904

0.122148

0.173043

0.593542

0.542998

0.443313

0.271674

0.17199

0.146718

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0.016231

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3,933

1

3,933

0.767538

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0.144244

0.046325

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false

0

0.047059

0

0.070588

0.094118

0

null

0

1

0

1

0

1

0

null

0

5

fb8c36aa376789586cde5492b07f43a84fe44151

173

py

Python

src/data/preprocessing/NoPreprocessing.py

ab3llini/ASLRecognizer

9a98887b13b73bb81bd4d6d8ebbfb13c4ef7e856

[ "MIT" ]

null

src/data/preprocessing/NoPreprocessing.py

ab3llini/ASLRecognizer

9a98887b13b73bb81bd4d6d8ebbfb13c4ef7e856

[ "MIT" ]

null

src/data/preprocessing/NoPreprocessing.py

ab3llini/ASLRecognizer

9a98887b13b73bb81bd4d6d8ebbfb13c4ef7e856

[ "MIT" ]

1

2019-04-16T17:20:28.000Z

from src.data.preprocessing.AbstractPreprocessing import AbstractPreprocessing class NoPreprocessing(AbstractPreprocessing): def preprocess(self, x): return x

24.714286

78

0.797688

16

173

8.625

0.8125

0

0.144509

173

7

79

24.714286

0.932432

0

1

0.25

false

0

0.25

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

fbab358d5b41a13b732ee800c535ed59a1434533

4,991

py

Python

ofm_client/v2/__init__.py

factset/ofm-python-sdk

3345fea40fa287e899dbab01b1a839a0eeab468c

[ "Apache-2.0" ]

1

2020-05-22T11:03:35.000Z

ofm_client/v2/__init__.py

factset/ofm-python-sdk

3345fea40fa287e899dbab01b1a839a0eeab468c

[ "Apache-2.0" ]

1

2020-05-15T07:54:51.000Z

ofm_client/v2/__init__.py

factset/ofm-python-sdk

3345fea40fa287e899dbab01b1a839a0eeab468c

[ "Apache-2.0" ]

1

2020-05-12T11:14:35.000Z

# coding: utf-8 # flake8: noqa """ Open:FactSet Marketplace API Headless CMS API used by the Open:FactSet Marketplace. # noqa: E501 OpenAPI spec version: v2.1.5 Contact: openfactset-frontend-engineering@factset.com """ from __future__ import absolute_import # import apis into sdk package from ofm_client.v2.api.attributes_api import AttributesApi from ofm_client.v2.api.attributes_groups_api import AttributesGroupsApi from ofm_client.v2.api.media_api import MediaApi from ofm_client.v2.api.partners_api import PartnersApi from ofm_client.v2.api.products_api import ProductsApi from ofm_client.v2.api.resources_api import ResourcesApi from ofm_client.v2.api.resources_sections_api import ResourcesSectionsApi # import ApiClient from ofm_client.v2.api_client import ApiClient from ofm_client.v2.configuration import Configuration # import models into sdk package from ofm_client.v2.models.document import Document from ofm_client.v2.models.document_section import DocumentSection from ofm_client.v2.models.get_attribute_dto import GetAttributeDto from ofm_client.v2.models.get_attributes_group_dto import GetAttributesGroupDto from ofm_client.v2.models.get_attributes_group_dto_attributes import GetAttributesGroupDtoAttributes from ofm_client.v2.models.get_partner_dto import GetPartnerDto from ofm_client.v2.models.get_partner_dto_forum_tags import GetPartnerDtoForumTags from ofm_client.v2.models.get_partner_dto_seo_meta import GetPartnerDtoSeoMeta from ofm_client.v2.models.get_partner_dto_social_media import GetPartnerDtoSocialMedia from ofm_client.v2.models.get_partner_dto_version_schema import GetPartnerDtoVersionSchema from ofm_client.v2.models.get_product_dto import GetProductDto from ofm_client.v2.models.get_product_dto_attributes import GetProductDtoAttributes from ofm_client.v2.models.get_product_dto_attributes_groups import GetProductDtoAttributesGroups from ofm_client.v2.models.get_product_dto_columns import GetProductDtoColumns from ofm_client.v2.models.get_product_dto_coverage_table import GetProductDtoCoverageTable from ofm_client.v2.models.get_product_dto_highlight import GetProductDtoHighlight from ofm_client.v2.models.get_product_dto_partner import GetProductDtoPartner from ofm_client.v2.models.get_product_dto_partner_social_media import GetProductDtoPartnerSocialMedia from ofm_client.v2.models.get_product_dto_preview_link import GetProductDtoPreviewLink from ofm_client.v2.models.get_product_dto_related_products import GetProductDtoRelatedProducts from ofm_client.v2.models.get_product_dto_seo_meta import GetProductDtoSeoMeta from ofm_client.v2.models.get_product_dto_third_party_urls import GetProductDtoThirdPartyUrls from ofm_client.v2.models.get_product_dto_version_schema import GetProductDtoVersionSchema from ofm_client.v2.models.get_resource_dto import GetResourceDto from ofm_client.v2.models.get_resources_section_dto import GetResourcesSectionDto from ofm_client.v2.models.get_resources_section_dto_meta import GetResourcesSectionDtoMeta from ofm_client.v2.models.inline_response200 import InlineResponse200 from ofm_client.v2.models.marking import Marking from ofm_client.v2.models.post_attribute_search_dto import PostAttributeSearchDto from ofm_client.v2.models.post_attributes_group_search_dto import PostAttributesGroupSearchDto from ofm_client.v2.models.post_partner_search_dto import PostPartnerSearchDto from ofm_client.v2.models.post_product_search_dto import PostProductSearchDto from ofm_client.v2.models.post_resource_search_dto import PostResourceSearchDto from ofm_client.v2.models.post_resources_section_search_dto import PostResourcesSectionSearchDto # import query builder into sdk package from ofm_client.v2.query_builder.search.interfaces.i_search_fields import ISearchFields from ofm_client.v2.query_builder.search.interfaces.i_search_field import ISearchField from ofm_client.v2.query_builder.search.interfaces.i_search import ISearch from ofm_client.v2.query_builder.search.search_term import SearchTerm from ofm_client.v2.query_builder.search.search import Search from ofm_client.v2.query_builder.filters.interfaces.i_filter_field import IFilterField from ofm_client.v2.query_builder.filters.interfaces.i_filter import IFilter from ofm_client.v2.query_builder.filters.filter_operators import FilterOperator from ofm_client.v2.query_builder.filters.filter_term import FilterTerm from ofm_client.v2.query_builder.filters.filter import Filter from ofm_client.v2.query_builder.sort.interfaces.i_sort import ISort from ofm_client.v2.query_builder.sort.interfaces.i_sort_field import ISortField from ofm_client.v2.query_builder.sort.sort_term import SortTerm from ofm_client.v2.query_builder.sort.sort_operators import SortOperator from ofm_client.v2.query_builder.sort.sort import Sort from ofm_client.v2.query_builder.query.interfaces.i_query import IQuery from ofm_client.v2.query_builder.query.query import Query from ofm_client.v2.query_builder.query_builder import QueryBuilder

54.25

101

0.885794

718

4,991

5.85376

0.194986

0.101594

0.188675

0.217702

0.505829

0.482275

0.388056

0.348085

0.162741

0.081846

0

0.016112

0.067321

4,991

91

102

54.846154

0.886788

0.065117

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

fbace7e66486adafd034a4f2096323d7832df664

125

py

Python

graphene_django_optimizer/utils.py

NyanKiyoshi/graphene-django-optimizer

f9ecbf8952312c46c0b1820253ee824d594ae4a6

[ "MIT" ]

7

2021-09-19T23:09:24.000Z

2022-03-03T23:35:37.000Z

graphene_django_optimizer/utils.py

NyanKiyoshi/graphene-django-optimizer

f9ecbf8952312c46c0b1820253ee824d594ae4a6

[ "MIT" ]

13

2020-03-24T17:53:51.000Z

2022-02-10T20:01:14.000Z

graphene_django_optimizer/utils.py

NyanKiyoshi/graphene-django-optimizer

f9ecbf8952312c46c0b1820253ee824d594ae4a6

[ "MIT" ]

1

2020-06-11T19:15:51.000Z

noop = lambda *args, **kwargs: None def is_iterable(obj): return hasattr(obj, '__iter__') and not isinstance(obj, str)

20.833333

64

0.696

18

125

4.555556

0.888889

0

0.168

125

5

65

25

0.788462

0

0.064

0

1

0.333333

false

0

0.333333

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

5

fbd1a58d13f55892897a899cdf4258c3098ff1b1

66

py

Python

src/zn_operation_table/__init__.py

JuanpiCasti/zn_operation_table_generator

4103d0cba5bcb089bd04217fe5c206019790c3da

[ "MIT" ]

null

src/zn_operation_table/__init__.py

JuanpiCasti/zn_operation_table_generator

4103d0cba5bcb089bd04217fe5c206019790c3da

[ "MIT" ]

null

src/zn_operation_table/__init__.py

JuanpiCasti/zn_operation_table_generator

4103d0cba5bcb089bd04217fe5c206019790c3da

[ "MIT" ]

null

from .zn_operation_table import build_table build_table(7, 'sum')

22

43

0.818182

11

66

4.545455

0.727273

0.4

0

0.016667

0.090909

66

3

44

22

0.816667

0

0.044776

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

fbdcbb7bdb409f9764e59166a70ba1c01ab05636

180

py

Python

exe_05_04_dicionario.py

blimundo/exercicios_python

2ef1bc15b28e599adf3c063b6d971878cc3ba168

[ "MIT" ]

null

exe_05_04_dicionario.py

blimundo/exercicios_python

2ef1bc15b28e599adf3c063b6d971878cc3ba168

[ "MIT" ]

null

exe_05_04_dicionario.py

blimundo/exercicios_python

2ef1bc15b28e599adf3c063b6d971878cc3ba168

[ "MIT" ]

null

"""Dicionário Escreva uma função que simula a função dict() do Python. """ def myDict(**keywords: dict) -> dict: return keywords print(myDict(a=10, b=20, c=30, d=40, e=50))

18

56

0.661111

30

180

3.966667

0.8

0

0.067114

0.172222

180

9

57

20

0.731544

0.377778

0

1

0.333333

true

0

0.333333

0.666667

0.333333

0

null

0

1

0

null

0

1

0

1

0

5

837519e9936c76ee5074c5f8caba8cec072207ec

212

py

Python

rsmtpd/response/smtp_503.py

alfmel/rsmtpd

10900876b1f83d6c141070a413f81edf3c98ac51

[ "Apache-2.0" ]

1

2017-06-12T04:10:07.000Z

rsmtpd/response/smtp_503.py

alfmel/rsmtpd

10900876b1f83d6c141070a413f81edf3c98ac51

[ "Apache-2.0" ]

null

rsmtpd/response/smtp_503.py

alfmel/rsmtpd

10900876b1f83d6c141070a413f81edf3c98ac51

[ "Apache-2.0" ]

null

from rsmtpd.response.action import OK from rsmtpd.response.base_response import BaseResponse class SmtpResponse503(BaseResponse): _smtp_code = 503 _message = "Bad sequence of commands" _action = OK

23.555556

54

0.773585

26

212

6.115385

0.692308

0.125786

0.226415

0

0.034091

0.169811

212

8

55

26.5

0.869318

0

0.113208

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

8387e524885296c2dbc7d1d7d30091c7628da8a9

44

py

Python

examples/str.splitlines/ex1.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

examples/str.splitlines/ex1.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

examples/str.splitlines/ex1.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

print('ab c\n\nde fg\rkl\r\n'.splitlines())

22

43

0.659091

10

44

2.9

0.9

0

0.068182

44

1

44

0.707317

0

0.477273

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

83b28608883fa70735f99ee3742348412301e368

2,584

py

Python

tests/app/articles/test_routing.py

cds-snc/notifier-admin

69aab94cb8d1711488e471cac52223c7f9f6f90e

[ "MIT" ]

null

tests/app/articles/test_routing.py

cds-snc/notifier-admin

69aab94cb8d1711488e471cac52223c7f9f6f90e

[ "MIT" ]

1

2019-07-05T15:09:55.000Z

2019-07-05T18:13:06.000Z

tests/app/articles/test_routing.py

cds-snc/notifier-admin

69aab94cb8d1711488e471cac52223c7f9f6f90e

[ "MIT" ]

null

import pytest from app.articles.routing import GC_ARTICLES_ROUTES, gca_url_for @pytest.mark.parametrize("route, lang, expectedURL", [("home", "en", "/home"), ("home", "fr", "/accueil")]) def test_gca_url_for_works_with_valid_routes(mocker, route, lang, expectedURL): mocker.patch("app.articles.routing.get_current_locale", return_value=lang) route = gca_url_for(route) assert route == expectedURL @pytest.mark.parametrize("route, lang", [("homez", "en"), ("homez", "fr")]) def test_gca_url_for_fails_with_invalid_routes(mocker, route, lang): mocker.patch("app.articles.routing.get_current_locale", return_value=lang) with pytest.raises(Exception): gca_url_for(route) @pytest.mark.parametrize( "route, lang, expectedURL", [("home", "en", "http://localhost/home"), ("home", "fr", "http://localhost/accueil")] ) def test_gca_url_for_creates_asbolute_url(app_, mocker, route, lang, expectedURL): mocker.patch("app.articles.routing.get_current_locale", return_value=lang) mocker.patch("app.articles.routing.url_for", return_value="http://localhost") route = gca_url_for(route, _external=True) assert route == expectedURL @pytest.mark.skip(reason="these tests reach out to GCA and are flaky; may re-enable inside of an integration-type suite") @pytest.mark.integration @pytest.mark.parametrize("route", list(GC_ARTICLES_ROUTES)) def test_ensure_all_french_gca_routes_in_GC_ARTICLES_ROUTES_exist(client_request, mocker, route): mocker.patch("app.articles.routing.get_current_locale", return_value="fr") mocker.patch("app.main.views.index.get_current_locale", return_value="fr") render_article = mocker.patch("app.main.views.index._render_articles_page", return_value="") url = gca_url_for(route) client_request.get_url(url, _expected_status=200, _test_page_title=False) assert render_article.called @pytest.mark.skip(reason="these tests reach out to GCA and are flaky; may re-enable inside of an integration-type suite") @pytest.mark.integration @pytest.mark.parametrize("route", list(GC_ARTICLES_ROUTES)) def test_ensure_all_english_gca_routes_in_GC_ARTICLES_ROUTES_exist(client_request, mocker, route): mocker.patch("app.articles.routing.get_current_locale", return_value="en") mocker.patch("app.main.views.index.get_current_locale", return_value="en") render_article = mocker.patch("app.main.views.index._render_articles_page", return_value="") url = gca_url_for(route) client_request.get_url(url, _expected_status=200, _test_page_title=False) assert render_article.called

43.066667

121

0.763545

370

2,584

5.032432

0.227027

0.032223

0.075188

0.082707

0.842642

0.773899

0.727175

0.676692

0

0.00259

0.103328

2,584

59

122

43.79661

0.801036

0

0.475

0

0.05

0.294118

0.148994

0

0.1

1

0.125

false

0

0.05

0

0.175

0

null

0

1

0

1

0

null

0

5

83c1ed2f845ac9af71c687712b733c8b05ec39f8

4,050

py

Python

vunet/evaluation/test_ids.py

gabolsgabs/vunet

d34726e55195c759ec63c003f2eaacda0a825865

[ "AFL-3.0" ]

1

2021-05-03T03:16:22.000Z

vunet/evaluation/test_ids.py

gabolsgabs/vunet

d34726e55195c759ec63c003f2eaacda0a825865

[ "AFL-3.0" ]

null

vunet/evaluation/test_ids.py

gabolsgabs/vunet

d34726e55195c759ec63c003f2eaacda0a825865

[ "AFL-3.0" ]

null

ids = [ "0054d4d2b1f340a088b9d911bdd31f28", "028cb9312382479e84e71cc9d0d85d1d", "02b296bbee3c4d5e84be5d2ab5658450", "04a7e4c7381040da900a531918b129c5", "0627b246b0094eb188582b5f85c89a9d", "07045583ddf5450c93550a40cbc92a63", "075a5e7e6a60403481b2795405ab28fb", "098e29e7e6b140129bbdfd0d4d6a7763", "09aae3f31367406bac6753701c291210", "09d9713573c94f7d953c4707161ffc50", "0aeadc81354d47f68df8f4a0cdf0c1a1", "0b2934ecce8243e4899176fd66c46e60", "138df7da0ff64766904e271ef1f0d759", "1994fef246cb41fd829236393ad12835", "1a55d67522e34965997da8c8fee10061", "1e6a3a469f0e470498e164aafef7f93f", "223a01dd434d4510ae2c4d2df1ff23a7", "275f6a8de8b94f52a4147e1c2cad691d", "28a731d3a485404595772283498258da", "2d23bfc645174d719d63496fc4270b18", "349ce242d0cc4093946be40a6feec9c7", "34f2089385954d67a151a52cb9777cac", "38e960304d594f4fbd60f276f8aefae5", "3a0475b9b872458abb9ffb67cd6b3b0a", "3a4fb09e5ed4464fb9b174f4d5b6fa97", "3bad8486391d41cebcbd02d4e0802531", "3f3fd8cce19549a0a0f636f2207e66ec", "3f731bbf73324e239c48ef60f0ea596b", "4490084e194a498bb9b1162ae9e3b89d", "47df0f19739944ecb26867ee88c65074", "4b85c941676c4b658c8ae88fdff769be", "4dcd58bb6abc4bec9aad7e99047f138d", "54e1ecf68ff34b2c91ab16d37afb37f6", "55a7131d82364d00acad36a65499cefa", "58b861a63f154fb6b9369e1ec95fa99a", "5a1e44647dfd422183fef2c084b85ba6", "5b6e6fb2dd9e405cb5031c793e0589e7", "5bd5e05cc268483cb2f15d05a7f13dd5", "5c6ffb8263bc45ce9b4d3e0b309d530a", "63c2d32a96b7433896c2a70c9bdf280e", "656e4837f36a49c6a8e3a00f610793bf", "6a6a9ad6e1a246fdaf86015327ceb680", "6c59d4e7f8274ee28c3e8dbaff26d77b", "7101337d219a47be976e0363f4e25d4d", "79e23003861449b99b575d54b86bff23", "7b561198d0594a9397fd22356dfb8c25", "7f78b39f6b2b4b26a4fdf7aa63055e51", "80339d51a0a44f99934dc1b6241ee47d", "83b4fbe9abf8420798d00fb77ac8c8fb", "85efa060214a405c9e58795a6c968792", "8802a1b650df456dbf20fd8c7c80780a", "8bd18197a2474508a4e1f11b6292317f", "8bfea0d225be4cf98ae9bee74ac63b57", "8ed3731457ae4d0ebc427dbeb3b984c3", "8f157cb75225415a953e8aa1ec31fe65", "9057e9bfa65544c7bb3cae2f7d089cda", "90affe98aafb4eb5b60b6e92d0740bfa", "977300d8aa4c4feaad3fa4734dfc7cf4", "a1d44044903d4661916db09d3ba3af86", "a2307f4fb6e844c18c85be373f2afaa7", "a3263734562b41e9be2429ba929cf2ce", "a689f3a4790c4dd2b6640e757908d33d", "a7bb0d130c40454896dbc9eff69e9883", "aa0438ef1c3b42c5b78ad0dd1d96935c", "aa37a2c59db740be98787e21232d823a", "aa68bd15ffff43ea9b81d9423ffd3066", "ab2f49b30d074bcda07ea9da7a20675f", "ac932de5abc946469a11d84101304e73", "adec67e8fbaf426aa5cf2d0f72ac3ab8", "ae480b71c18a409eae560944fc45c596", "aec6d16f0a9946c79401d1fd30f00d19", "b3cf740cc89f4546a770f9a40b48d30c", "b6e887f61bd642b580bdbcd2df61b974", "b8e906edbf1d4c4789609dac816dab79", "b9b6b683d5db43369bbe10ff9fbbf2cf", "bb9411207b1d4f64aad3f7f61188c7df", "bddb1d0dfc644be9b8a3c47174e189b3", "c18efc51dfc24c9a8f879f270eebaf30", "c2ba6a5c606f4c69865fc02d1abe42c7", "c372c4eeb29e42f38a138ff653e86337", "c4de84ec16c64ce3877a420d5046a26a", "c4e3f4420d7449c6acddd7b86155b17d", "c6fe0a4e98454ce987ede487825da760", "c9aff9dc5f3e444ba31c28d2df95509f", "c9cbd0064c4f4026a0568406a1405de0", "cc9d502762e84305a4c872f62169e895", "d19f2702ced74a77b8d4479452763188", "d538b4747e9640e490ce8cb7a84a0a0e", "e05f1471e4474245bdbb520a124771a6", "e167448352574f1d8e90009b1b34acd1", "e7376c9c173d4effbb1cfcac758aad48", "e76a7846ac9d4a4dae8997cb4e58ded2", "ea34afda101148f6a8da883646f1ebb0", "ebae2a2ec78c4c978f400e26fd416f27", "efc72bafe7b54befafaae134049c47cd", "f0db1df05d7940e69af522dff0f0b949", "f47fe77b965c44798f1cad8aa95782c5", "f5856979ed124e86ab54eed0943b9dd7", "fb11ab318a83472aac0b1d90403007fe", "fb38c36793654dbaa6107b91b7f88e6e", "ffbfd5b3ebe542858c9e2cf45dd26e10", ]

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null

0

5

83d66b32b58e6160c55d0a74af59a8a305bdd4c8

88

py

Python

leadrouter/__init__.py

RealGeeks/lead_router.py

61da9028421131f74e9538f1d698c7f8644f8574

[ "MIT" ]

null

leadrouter/__init__.py

RealGeeks/lead_router.py

61da9028421131f74e9538f1d698c7f8644f8574

[ "MIT" ]

1

2017-03-22T02:18:31.000Z

2017-03-23T00:47:45.000Z

leadrouter/__init__.py

RealGeeks/lead_router.py

61da9028421131f74e9538f1d698c7f8644f8574

[ "MIT" ]

null

from .client import Client, HTTPError from .publisher import Publisher, DebugPublisher

22

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10

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7.3

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88

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null

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1

0

5

83e3c43795916fd27fc5ea4b96f07114ec9e05c3

181

py

Python

src/compas_hpc/core/__init__.py

philianeles/compas

129a5a7e9d8832495d2bbee6ce7c6463ab50f2d1

[ "MIT" ]

null

src/compas_hpc/core/__init__.py

philianeles/compas

129a5a7e9d8832495d2bbee6ce7c6463ab50f2d1

[ "MIT" ]

null

src/compas_hpc/core/__init__.py

philianeles/compas

129a5a7e9d8832495d2bbee6ce7c6463ab50f2d1

[ "MIT" ]

null

from .euler import * from .cuda import * from .opencl import * from .euler import __all__ as a from .cuda import __all__ as b from .opencl import __all__ as c __all__ = a + b + c

18.1

32

0.718232

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181

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181

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1

0

null

0

1

0

1

0

5

83e623919770c4cf7c462855c24f1a5bf96e8ef6

53

py

Python

colorchron/colorwheel/__init__.py

harmsm/pantone

23f7875680666f5546757f988e872f86ad76b888

[ "MIT" ]

null

colorchron/colorwheel/__init__.py

harmsm/pantone

23f7875680666f5546757f988e872f86ad76b888

[ "MIT" ]

null

colorchron/colorwheel/__init__.py

harmsm/pantone

23f7875680666f5546757f988e872f86ad76b888

[ "MIT" ]

null

from .wheels import RGB, CMY, HSV, RYB, Chromachron

17.666667

51

0.735849

8

53

4.875

1

0

0.169811

53

2

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5

f7d30eb2aded559bff99826054d2369e7cdb4f24

22,703

py

Python

src/deutschland/travelwarning/api/default_api.py

andreasbossard/deutschland

6f561256c707e21f81b54b139b9acb745b901298

[ "Apache-2.0" ]

445

2021-07-26T22:00:26.000Z

2022-03-31T08:31:08.000Z

src/deutschland/travelwarning/api/default_api.py

andreasbossard/deutschland

6f561256c707e21f81b54b139b9acb745b901298

[ "Apache-2.0" ]

30

2021-07-27T15:42:23.000Z

2022-03-26T16:14:11.000Z

src/deutschland/travelwarning/api/default_api.py

andreasbossard/deutschland

6f561256c707e21f81b54b139b9acb745b901298

[ "Apache-2.0" ]

28

2021-07-27T10:48:43.000Z

2022-03-26T14:31:30.000Z

""" Auswärtiges Amt OpenData Schnittstelle Dies ist die Beschreibung für die Schnittstelle zum Zugriff auf die Daten des [Auswärtigen Amtes](https://www.auswaertiges-amt.de/de/) im Rahmen der [OpenData](https://www.auswaertiges-amt.de/de/open-data-schnittstelle/736118) Initiative. ## Deaktivierung Die Schnittstelle kann deaktiviert werden, in dem Fall wird ein leeres JSON-Objekt zurückgegeben. ## Fehlerfall Im Fehlerfall wird ein leeres JSON-Objekt zurückgegeben. ## Nutzungsbedingungen Die Nutzungsbedingungen sind auf der [OpenData-Schnittstelle](https://www.auswaertiges-amt.de/de/open-data-schnittstelle/736118) des Auswärtigen Amtes zu finden. ## Änderungen ### version 1.0.1 (September 2021) * `content` (-> Details des Reise- und Sicherheitshinweis) wurde von [`/travelwarning`](#operations-default-getTravelwarning) entfernt -> bitte ab jetzt [`/travelwarning/{contentId}`](#operations-default-getSingleTravelwarning) nutzen um `content` abzufragen # noqa: E501 The version of the OpenAPI document: 1.0.1 Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from deutschland.travelwarning.api_client import ApiClient from deutschland.travelwarning.api_client import Endpoint as _Endpoint from deutschland.travelwarning.model.response_address import ResponseAddress from deutschland.travelwarning.model.response_download import ResponseDownload from deutschland.travelwarning.model.response_warning import ResponseWarning from deutschland.travelwarning.model.response_warnings import ResponseWarnings from deutschland.travelwarning.model_utils import ( # noqa: F401 check_allowed_values, check_validations, date, datetime, file_type, none_type, validate_and_convert_types, ) class DefaultApi(object): """NOTE: This class is auto generated by OpenAPI Generator Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client self.get_healthcare_endpoint = _Endpoint( settings={ "response_type": (ResponseDownload,), "auth": [], "endpoint_path": "/healthcare", "operation_id": "get_healthcare", "http_method": "GET", "servers": None, }, params_map={ "all": [], "required": [], "nullable": [], "enum": [], "validation": [], }, root_map={ "validations": {}, "allowed_values": {}, "openapi_types": {}, "attribute_map": {}, "location_map": {}, "collection_format_map": {}, }, headers_map={ "accept": ["application/json"], "content_type": [], }, api_client=api_client, ) self.get_representatives_country_endpoint = _Endpoint( settings={ "response_type": (ResponseAddress,), "auth": [], "endpoint_path": "/representativesInCountry", "operation_id": "get_representatives_country", "http_method": "GET", "servers": None, }, params_map={ "all": [], "required": [], "nullable": [], "enum": [], "validation": [], }, root_map={ "validations": {}, "allowed_values": {}, "openapi_types": {}, "attribute_map": {}, "location_map": {}, "collection_format_map": {}, }, headers_map={ "accept": ["text/json;charset=UTF-8"], "content_type": [], }, api_client=api_client, ) self.get_representatives_germany_endpoint = _Endpoint( settings={ "response_type": (ResponseAddress,), "auth": [], "endpoint_path": "/representativesInGermany", "operation_id": "get_representatives_germany", "http_method": "GET", "servers": None, }, params_map={ "all": [], "required": [], "nullable": [], "enum": [], "validation": [], }, root_map={ "validations": {}, "allowed_values": {}, "openapi_types": {}, "attribute_map": {}, "location_map": {}, "collection_format_map": {}, }, headers_map={ "accept": ["text/json;charset=UTF-8"], "content_type": [], }, api_client=api_client, ) self.get_single_travelwarning_endpoint = _Endpoint( settings={ "response_type": (ResponseWarning,), "auth": [], "endpoint_path": "/travelwarning/{contentId}", "operation_id": "get_single_travelwarning", "http_method": "GET", "servers": None, }, params_map={ "all": [ "content_id", ], "required": [ "content_id", ], "nullable": [], "enum": [], "validation": [ "content_id", ], }, root_map={ "validations": { ("content_id",): { "inclusive_minimum": 1, }, }, "allowed_values": {}, "openapi_types": { "content_id": (int,), }, "attribute_map": { "content_id": "contentId", }, "location_map": { "content_id": "path", }, "collection_format_map": {}, }, headers_map={ "accept": ["text/json;charset=UTF-8"], "content_type": [], }, api_client=api_client, ) self.get_state_names_endpoint = _Endpoint( settings={ "response_type": (ResponseDownload,), "auth": [], "endpoint_path": "/stateNames", "operation_id": "get_state_names", "http_method": "GET", "servers": None, }, params_map={ "all": [], "required": [], "nullable": [], "enum": [], "validation": [], }, root_map={ "validations": {}, "allowed_values": {}, "openapi_types": {}, "attribute_map": {}, "location_map": {}, "collection_format_map": {}, }, headers_map={ "accept": ["application/json"], "content_type": [], }, api_client=api_client, ) self.get_travelwarning_endpoint = _Endpoint( settings={ "response_type": (ResponseWarnings,), "auth": [], "endpoint_path": "/travelwarning", "operation_id": "get_travelwarning", "http_method": "GET", "servers": None, }, params_map={ "all": [], "required": [], "nullable": [], "enum": [], "validation": [], }, root_map={ "validations": {}, "allowed_values": {}, "openapi_types": {}, "attribute_map": {}, "location_map": {}, "collection_format_map": {}, }, headers_map={ "accept": ["text/json;charset=UTF-8"], "content_type": [], }, api_client=api_client, ) def get_healthcare(self, **kwargs): """Gibt die Merkblätter des Gesundheitsdienstes zurück # noqa: E501 Merkblätter des Gesundheitsdienstes als Link auf ein PDF # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_healthcare(async_req=True) >>> result = thread.get() Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ResponseDownload If the method is called asynchronously, returns the request thread. """ kwargs["async_req"] = kwargs.get("async_req", False) kwargs["_return_http_data_only"] = kwargs.get("_return_http_data_only", True) kwargs["_preload_content"] = kwargs.get("_preload_content", True) kwargs["_request_timeout"] = kwargs.get("_request_timeout", None) kwargs["_check_input_type"] = kwargs.get("_check_input_type", True) kwargs["_check_return_type"] = kwargs.get("_check_return_type", True) kwargs["_host_index"] = kwargs.get("_host_index") return self.get_healthcare_endpoint.call_with_http_info(**kwargs) def get_representatives_country(self, **kwargs): """Gibt eine Liste der deutschen Vertretungen im Ausland zurück # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_representatives_country(async_req=True) >>> result = thread.get() Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ResponseAddress If the method is called asynchronously, returns the request thread. """ kwargs["async_req"] = kwargs.get("async_req", False) kwargs["_return_http_data_only"] = kwargs.get("_return_http_data_only", True) kwargs["_preload_content"] = kwargs.get("_preload_content", True) kwargs["_request_timeout"] = kwargs.get("_request_timeout", None) kwargs["_check_input_type"] = kwargs.get("_check_input_type", True) kwargs["_check_return_type"] = kwargs.get("_check_return_type", True) kwargs["_host_index"] = kwargs.get("_host_index") return self.get_representatives_country_endpoint.call_with_http_info(**kwargs) def get_representatives_germany(self, **kwargs): """Gibt eine Liste der ausländischen Vertretungen in Deutschland zurück # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_representatives_germany(async_req=True) >>> result = thread.get() Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ResponseAddress If the method is called asynchronously, returns the request thread. """ kwargs["async_req"] = kwargs.get("async_req", False) kwargs["_return_http_data_only"] = kwargs.get("_return_http_data_only", True) kwargs["_preload_content"] = kwargs.get("_preload_content", True) kwargs["_request_timeout"] = kwargs.get("_request_timeout", None) kwargs["_check_input_type"] = kwargs.get("_check_input_type", True) kwargs["_check_return_type"] = kwargs.get("_check_return_type", True) kwargs["_host_index"] = kwargs.get("_host_index") return self.get_representatives_germany_endpoint.call_with_http_info(**kwargs) def get_single_travelwarning(self, content_id, **kwargs): """Gibt einen Reise- und Sicherheitshinweis zurück # noqa: E501 Gibt den vollständigen Datensatz eines Reise- und Sicherheitshinweises zurück. Benötigt die jeweilige ID siehe /travelwarning # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_single_travelwarning(content_id, async_req=True) >>> result = thread.get() Args: content_id (int): Die ID des Reise- und Sicherheitshinweises, IDs siehe /travelwarning Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ResponseWarning If the method is called asynchronously, returns the request thread. """ kwargs["async_req"] = kwargs.get("async_req", False) kwargs["_return_http_data_only"] = kwargs.get("_return_http_data_only", True) kwargs["_preload_content"] = kwargs.get("_preload_content", True) kwargs["_request_timeout"] = kwargs.get("_request_timeout", None) kwargs["_check_input_type"] = kwargs.get("_check_input_type", True) kwargs["_check_return_type"] = kwargs.get("_check_return_type", True) kwargs["_host_index"] = kwargs.get("_host_index") kwargs["content_id"] = content_id return self.get_single_travelwarning_endpoint.call_with_http_info(**kwargs) def get_state_names(self, **kwargs): """Gibt das Verzeichnis der Staatennamen zurück # noqa: E501 Verzeichnis der Staatennamen als Link auf eine XML- oder CSV-Datei. Eine PDF-Datei mit Nutzungshinweisen wird ebenfalls zurückgegeben. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_state_names(async_req=True) >>> result = thread.get() Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ResponseDownload If the method is called asynchronously, returns the request thread. """ kwargs["async_req"] = kwargs.get("async_req", False) kwargs["_return_http_data_only"] = kwargs.get("_return_http_data_only", True) kwargs["_preload_content"] = kwargs.get("_preload_content", True) kwargs["_request_timeout"] = kwargs.get("_request_timeout", None) kwargs["_check_input_type"] = kwargs.get("_check_input_type", True) kwargs["_check_return_type"] = kwargs.get("_check_return_type", True) kwargs["_host_index"] = kwargs.get("_host_index") return self.get_state_names_endpoint.call_with_http_info(**kwargs) def get_travelwarning(self, **kwargs): """Gibt alle Reise- und Sicherheitshinweise zurück # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_travelwarning(async_req=True) >>> result = thread.get() Keyword Args: _return_http_data_only (bool): response data without head status code and headers. Default is True. _preload_content (bool): if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. _request_timeout (int/float/tuple): timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. Default is None. _check_input_type (bool): specifies if type checking should be done one the data sent to the server. Default is True. _check_return_type (bool): specifies if type checking should be done one the data received from the server. Default is True. _host_index (int/None): specifies the index of the server that we want to use. Default is read from the configuration. async_req (bool): execute request asynchronously Returns: ResponseWarnings If the method is called asynchronously, returns the request thread. """ kwargs["async_req"] = kwargs.get("async_req", False) kwargs["_return_http_data_only"] = kwargs.get("_return_http_data_only", True) kwargs["_preload_content"] = kwargs.get("_preload_content", True) kwargs["_request_timeout"] = kwargs.get("_request_timeout", None) kwargs["_check_input_type"] = kwargs.get("_check_input_type", True) kwargs["_check_return_type"] = kwargs.get("_check_return_type", True) kwargs["_host_index"] = kwargs.get("_host_index") return self.get_travelwarning_endpoint.call_with_http_info(**kwargs)

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0.084249

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null

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null

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5

f7de482bf794d9b7b199f206ea0ed8fd099b3454

117

py

Python

Musofirlar.Website/src/work/admin.py

SanjarbekSaminjonov/Musofirlar.uz

aab647e06c2f06979408d8f2d2a78758a8b3c65c

[ "Apache-2.0" ]

3

2021-12-22T09:01:50.000Z

2021-12-23T18:29:12.000Z

Musofirlar.Website/src/work/admin.py

SanjarbekSaminjonov/Musofirlar.uz

aab647e06c2f06979408d8f2d2a78758a8b3c65c

[ "Apache-2.0" ]

null

Musofirlar.Website/src/work/admin.py

SanjarbekSaminjonov/Musofirlar.uz

aab647e06c2f06979408d8f2d2a78758a8b3c65c

[ "Apache-2.0" ]

1

2021-12-28T06:15:33.000Z

from django.contrib import admin from .models import Work # Register your models here. admin.site.register(Work)

13

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0.153846

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1

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1

0

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5

790655962fe5f0dedfca81c1496d202aa334601e

47

py

Python

hello_world.py

jzfarmer/learning_python

279fc19d4405625b49f853575252bf1dee3cbb99

[ "MIT" ]

null

hello_world.py

jzfarmer/learning_python

279fc19d4405625b49f853575252bf1dee3cbb99

[ "MIT" ]

null

hello_world.py

jzfarmer/learning_python

279fc19d4405625b49f853575252bf1dee3cbb99

[ "MIT" ]

null

#!/usr/bin/env python3 print( 'hello world' )

11.75

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null

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1

0

1

0

5

790c4c9fb5edb13bf70de321a0f4fc05978d80e0

13,229

py

Python

test/test_process.py

rockyplum/vampy-host

a410d680be2c15d76e31488db789ed30e6f34910

[ "BSD-4-Clause-UC" ]

16

2016-11-19T07:24:54.000Z

2021-07-09T23:30:48.000Z

test/test_process.py

rockyplum/vampy-host

a410d680be2c15d76e31488db789ed30e6f34910

[ "BSD-4-Clause-UC" ]

6

2017-04-05T12:00:38.000Z

2022-01-13T17:51:34.000Z

test/test_process.py

rockyplum/vampy-host

a410d680be2c15d76e31488db789ed30e6f34910

[ "BSD-4-Clause-UC" ]

1

2017-04-03T16:33:51.000Z

import vamp import numpy as np import vamp.frames as fr plugin_key = "vamp-test-plugin:vamp-test-plugin" plugin_key_freq = "vamp-test-plugin:vamp-test-plugin-freq" rate = 44100 # Throughout this file we have the assumption that the plugin gets run with a # blocksize of 1024, and with a step of 1024 for the time-domain version or 512 # for the frequency-domain one. That is certainly expected to be the norm for a # plugin like this that declares no preference, and the Python Vamp module is # expected to follow the norm. blocksize = 1024 def input_data(n): # start at 1, not 0 so that all elts are non-zero return np.arange(n) + 1 def test_process_n(): buf = input_data(blocksize) results = list(vamp.process_audio(buf, rate, plugin_key, "input-summary")) assert len(results) == 1 def test_process_freq_n(): buf = input_data(blocksize) results = list(vamp.process_audio(buf, rate, plugin_key_freq, "input-summary", {})) assert len(results) == 2 # one complete block starting at zero, one half-full def test_process_default_output(): # If no output is specified, we should get the first one (instants) buf = input_data(blocksize) results = list(vamp.process_audio(buf, rate, plugin_key, "", {})) assert len(results) == 10 for i in range(len(results)): expectedTime = vamp.vampyhost.RealTime('seconds', i * 1.5) actualTime = results[i]["timestamp"] assert expectedTime == actualTime def test_process_summary_param(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key, "input-summary", { "produce_output": 0 })) assert len(results) == 0 def test_process_multi_summary_param(): buf = input_data(blocksize * 10) results = list(vamp.process_audio_multiple_outputs(buf, rate, plugin_key, [ "input-summary" ], { "produce_output": 0 })) assert len(results) == 0 def test_process_summary_param_bool(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key, "input-summary", { "produce_output": False })) assert len(results) == 0 def test_process_multi_summary_param_bool(): buf = input_data(blocksize * 10) results = list(vamp.process_audio_multiple_outputs(buf, rate, plugin_key, [ "input-summary" ], { "produce_output": False })) assert len(results) == 0 def test_process_summary(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key, "input-summary", {})) assert len(results) == 10 for i in range(len(results)): # # each feature has a single value, equal to the number of non-zero elts # in the input block (which is all of them, i.e. the blocksize) plus # the first elt (which is i * blockSize + 1) # expected = blocksize + i * blocksize + 1 actual = results[i]["values"][0] assert actual == expected def test_process_frames_summary(): buf = input_data(blocksize * 10) ff = fr.frames_from_array(buf, blocksize, blocksize) results = list(vamp.process_frames(ff, rate, blocksize, plugin_key, "input-summary", {})) assert len(results) == 10 for i in range(len(results)): # # each feature has a single value, equal to the number of non-zero elts # in the input block (which is all of them, i.e. the blocksize) plus # the first elt (which is i * blockSize + 1) # expected = blocksize + i * blocksize + 1 actual = results[i]["values"][0] assert actual == expected def test_process_multi_summary(): buf = input_data(blocksize * 10) results = list(vamp.process_audio_multiple_outputs(buf, rate, plugin_key, [ "input-summary" ], {})) assert len(results) == 10 for i in range(len(results)): # # each feature has a single value, equal to the number of non-zero elts # in the input block (which is all of them, i.e. the blocksize) plus # the first elt (which is i * blockSize + 1) # expected = blocksize + i * blocksize + 1 actual = results[i]["input-summary"]["values"][0] assert actual == expected def test_process_frames_multi_summary(): buf = input_data(blocksize * 10) ff = fr.frames_from_array(buf, blocksize, blocksize) results = list(vamp.process_frames_multiple_outputs(ff, rate, blocksize, plugin_key, [ "input-summary" ], {})) assert len(results) == 10 for i in range(len(results)): # # each feature has a single value, equal to the number of non-zero elts # in the input block (which is all of them, i.e. the blocksize) plus # the first elt (which is i * blockSize + 1) # expected = blocksize + i * blocksize + 1 actual = results[i]["input-summary"]["values"][0] assert actual == expected def test_process_freq_summary(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key_freq, "input-summary", {})) assert len(results) == 20 for i in range(len(results)): # # sort of as above, but much much subtler: # # * the input block is converted to frequency domain but then converted # back within the plugin, so the values being reported are time-domain # ones but with windowing and FFT shift # # * the effect of FFT shift is that the first element in the # re-converted frame is actually the one that was at the start of the # second half of the original frame # # * and the last block is only half-full, so the "first" elt in that # one, which actually comes from just after the middle of the block, # will be zero # # * windowing does not affect the value of the first elt, because # (before fft shift) it came from the peak of the window shape where # the window value is 1 # # * but windowing does affect the number of non-zero elts, because the # asymmetric window used has one value very close to zero in it # # * the step size (the increment in input value from one block to the # next) is only half the block size # expected = i * (blocksize/2) + blocksize/2 + 1 # "first" elt if (i == len(results)-1): expected = 0 expected = expected + blocksize - 1 # non-zero elts actual = results[i]["values"][0] eps = 1e-6 assert abs(actual - expected) < eps def test_process_freq_summary_shift(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key_freq, "input-summary", {}, process_timestamp_method = vamp.vampyhost.SHIFT_DATA)) assert len(results) == 20 for i in range(len(results)): # as test_process_freq_summary, except that the input is effectively # padded by the adapter with an additional half-blocksize of zeros # before conversion if i == 0: # this block doesn't interact at all well with our test, we get # spurious low values in the block converted back within the plugin # because of the big discontinuity & window ripple after fftshift pass else: expected = (i-1) * (blocksize/2) + blocksize/2 + 1 # for "first" elt expected = expected + blocksize - 1 # non-zero elts actual = results[i]["values"][0] eps = 1e-6 assert abs(actual - expected) < eps def test_process_multi_freq_summary(): buf = input_data(blocksize * 10) results = list(vamp.process_audio_multiple_outputs(buf, rate, plugin_key_freq, [ "input-summary" ], {})) assert len(results) == 20 for i in range(len(results)): expected = i * (blocksize/2) + blocksize/2 + 1 # "first" elt if (i == len(results)-1): expected = 0 expected = expected + blocksize - 1 # non-zero elts actual = results[i]["input-summary"]["values"][0] eps = 1e-6 assert abs(actual - expected) < eps def test_process_timestamps(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key, "input-timestamp", {})) assert len(results) == 10 for i in range(len(results)): # The timestamp should be the frame number of the first frame in the # input buffer expected = i * blocksize actual = results[i]["values"][0] assert actual == expected def test_process_multi_timestamps(): buf = input_data(blocksize * 10) results = list(vamp.process_audio_multiple_outputs(buf, rate, plugin_key, [ "input-timestamp" ])) assert len(results) == 10 for i in range(len(results)): # The timestamp should be the frame number of the first frame in the # input buffer expected = i * blocksize actual = results[i]["input-timestamp"]["values"][0] assert actual == expected def test_process_freq_timestamps(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key_freq, "input-timestamp", {})) assert len(results) == 20 for i in range(len(results)): # The timestamp should be the frame number of the frame just beyond # half-way through the input buffer expected = i * (blocksize/2) + blocksize/2 actual = results[i]["values"][0] if actual == 2047 and expected == 2048: print("This test fails because of a bug in the Vamp plugin SDK. Please update to SDK version 2.6.") assert actual == expected def test_process_freq_shift_timestamps(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key_freq, "input-timestamp", process_timestamp_method = vamp.vampyhost.SHIFT_DATA)) assert len(results) == 20 for i in range(len(results)): # The timestamp should be the frame number of the frame at the start of # the input buffer expected = i * (blocksize/2) actual = results[i]["values"][0] if actual == 2047 and expected == 2048: print("This test fails because of a bug in the Vamp plugin SDK. Please update to SDK version 2.6.") assert actual == expected def test_process_multi_freq_timestamps(): buf = input_data(blocksize * 10) results = list(vamp.process_audio_multiple_outputs(buf, rate, plugin_key_freq, [ "input-timestamp" ], {})) assert len(results) == 20 for i in range(len(results)): # The timestamp should be the frame number of the frame just beyond # half-way through the input buffer expected = i * (blocksize/2) + blocksize/2 actual = results[i]["input-timestamp"]["values"][0] if actual == 2047 and expected == 2048: print("This test fails because of a bug in the Vamp plugin SDK. Please update to SDK version 2.6.") assert actual == expected def test_process_blocksize_timestamps(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key, "input-timestamp", {}, block_size = blocksize * 2)) # step size defaults to block size assert len(results) == 5 for i in range(len(results)): # The timestamp should be the frame number of the first frame in the # input buffer expected = i * blocksize * 2 actual = results[i]["values"][0] assert actual == expected def test_process_stepsize_timestamps(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key, "input-timestamp", {}, step_size = int(blocksize / 2))) assert len(results) == 20 for i in range(len(results)): # The timestamp should be the frame number of the first frame in the # input buffer expected = (i * blocksize) / 2 actual = results[i]["values"][0] assert actual == expected def test_process_stepsize_blocksize_timestamps(): buf = input_data(blocksize * 10) results = list(vamp.process_audio(buf, rate, plugin_key, "input-timestamp", {}, block_size = blocksize * 2, step_size = int(blocksize / 2))) assert len(results) == 20 for i in range(len(results)): # The timestamp should be the frame number of the first frame in the # input buffer expected = (i * blocksize) / 2 actual = results[i]["values"][0] assert actual == expected def test_process_multiple_outputs(): buf = input_data(blocksize * 10) results = list(vamp.process_audio_multiple_outputs(buf, rate, plugin_key, [ "input-summary", "input-timestamp" ], {})) assert len(results) == 20 si = 0 ti = 0 for r in results: assert "input-summary" in r or "input-timestamp" in r if "input-summary" in r: expected = blocksize + si * blocksize + 1 actual = r["input-summary"]["values"][0] assert actual == expected si = si + 1 if "input-timestamp" in r: expected = ti * blocksize actual = r["input-timestamp"]["values"][0] assert actual == expected ti = ti + 1

43.516447

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0.731038

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0

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13,229

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148

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0.821639

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0.015

0

null

0

1

0

null

0

5

792cca4ef724bdafadab89c2e5b7d60a9a206772

62

py

Python

lib/tamper_scripts/uppercase_encode.py

ikstream/Zeus-Scanner

272839c44a950b9c3c9e6d83a2c76fdd51cd010b

[ "RSA-MD" ]

841

2017-09-08T10:25:35.000Z

2022-03-20T14:27:09.000Z

lib/tamper_scripts/uppercase_encode.py

An0nYm0u5101/Zeus-Scanner

21b87563062326cd480669f2922f650173a2a18e

[ "RSA-MD" ]

1,121

2017-09-21T14:42:50.000Z

2022-03-01T16:49:19.000Z

lib/tamper_scripts/uppercase_encode.py

An0nYm0u5101/Zeus-Scanner

21b87563062326cd480669f2922f650173a2a18e

[ "RSA-MD" ]

243

2017-09-09T21:35:50.000Z

2022-01-06T22:38:54.000Z

def tamper(payload, **kwargs): return str(payload).upper()

31

0.693548

8

62

5.375

0.875

0

0.129032

62

2

31

0.796296

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

7937f70a576a0bc4ed7922f73d7bd243fbf0639d

83

py

Python

app/database/base.py

WendyHzo/appBackend

cb7319a5e8635038afc54e2ea8b2a05bc943077a

[ "Apache-2.0" ]

null

app/database/base.py

WendyHzo/appBackend

cb7319a5e8635038afc54e2ea8b2a05bc943077a

[ "Apache-2.0" ]

null

app/database/base.py

WendyHzo/appBackend

cb7319a5e8635038afc54e2ea8b2a05bc943077a

[ "Apache-2.0" ]

null

from app.database.base_class import Base from app.models.liquors import licorera

27.666667

41

0.831325

13

83

5.230769

0.692308

0.205882

0

0.120482

83

2

42

41.5

0.931507

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

f70e4517d1db8c8e699000ac090e9cb2e6804237

68

py

Python

leo/test/unittest/at-nosent-test.py

ATikhonov2/leo-editor

225aac990a9b2804aaa9dea29574d6e072e30474

[ "MIT" ]

2

2020-01-19T18:11:05.000Z

2020-01-19T18:12:07.000Z

leo/test/unittest/at-nosent-test.py

ATikhonov2/leo-editor

225aac990a9b2804aaa9dea29574d6e072e30474

[ "MIT" ]

1

2020-06-19T02:28:25.000Z

leo/test/unittest/at-nosent-test.py

ATikhonov2/leo-editor

225aac990a9b2804aaa9dea29574d6e072e30474

[ "MIT" ]

null

def spam(): pass # Unicode test: Ã after. def eggs(): pass

11.333333

33

0.573529

10

68

3.9

0.8

0

0.294118

68

5

34

13.6

0.8125

0.323529

0

0.5

0

1

0.5

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

5

f736a3517e3c5f420c40d3bfa794b57a3d8b2046

17,362

py

Python

balance.py

Charterhouse/random_forest

b842f08fee1054dbff78b6fb3afd4006a7f14a6d

[ "MIT" ]

2

2019-10-24T07:22:46.000Z

2019-11-18T12:32:26.000Z

balance.py

Charterhouse/random_forest

b842f08fee1054dbff78b6fb3afd4006a7f14a6d

[ "MIT" ]

null

balance.py

Charterhouse/random_forest

b842f08fee1054dbff78b6fb3afd4006a7f14a6d

[ "MIT" ]

2

2020-03-03T18:30:14.000Z

2021-09-06T13:55:06.000Z

from mpyc.runtime import mpc from src.dataset import ObliviousDataset, Sample from src.output import output from src.secint import secint as s from src.forest import train_forest def sample(ins, out): return Sample([s(i) for i in ins], s(out)) samples = ObliviousDataset.create( sample([1, 1, 1, 2], 1), sample([1, 1, 1, 3], 1), sample([1, 1, 1, 4], 1), sample([1, 1, 1, 5], 1), sample([1, 1, 2, 1], 1), sample([1, 1, 2, 2], 1), sample([1, 1, 2, 3], 1), sample([1, 1, 2, 4], 1), sample([1, 1, 2, 5], 1), sample([1, 1, 3, 1], 1), sample([1, 1, 3, 2], 1), sample([1, 1, 3, 3], 1), sample([1, 1, 3, 4], 1), sample([1, 1, 3, 5], 1), sample([1, 1, 4, 1], 1), sample([1, 1, 4, 2], 1), sample([1, 1, 4, 3], 1), sample([1, 1, 4, 4], 1), sample([1, 1, 4, 5], 1), sample([1, 1, 5, 1], 1), sample([1, 1, 5, 2], 1), sample([1, 1, 5, 3], 1), sample([1, 1, 5, 4], 1), sample([1, 1, 5, 5], 1), sample([1, 2, 1, 1], 0), sample([1, 2, 1, 3], 1), sample([1, 2, 1, 4], 1), sample([1, 2, 1, 5], 1), sample([1, 2, 2, 2], 1), sample([1, 2, 2, 3], 1), sample([1, 2, 2, 4], 1), sample([1, 2, 2, 5], 1), sample([1, 2, 3, 1], 1), sample([1, 2, 3, 2], 1), sample([1, 2, 3, 3], 1), sample([1, 2, 3, 4], 1), sample([1, 2, 3, 5], 1), sample([1, 2, 4, 1], 1), sample([1, 2, 4, 2], 1), sample([1, 2, 4, 3], 1), sample([1, 2, 4, 4], 1), sample([1, 2, 4, 5], 1), sample([1, 2, 5, 1], 1), sample([1, 2, 5, 2], 1), sample([1, 2, 5, 3], 1), sample([1, 2, 5, 4], 1), sample([1, 2, 5, 5], 1), sample([1, 3, 1, 1], 0), sample([1, 3, 1, 2], 0), sample([1, 3, 1, 4], 1), sample([1, 3, 1, 5], 1), sample([1, 3, 2, 1], 0), sample([1, 3, 2, 2], 1), sample([1, 3, 2, 3], 1), sample([1, 3, 2, 4], 1), sample([1, 3, 2, 5], 1), sample([1, 3, 3, 2], 1), sample([1, 3, 3, 3], 1), sample([1, 3, 3, 4], 1), sample([1, 3, 3, 5], 1), sample([1, 3, 4, 1], 1), sample([1, 3, 4, 2], 1), sample([1, 3, 4, 3], 1), sample([1, 3, 4, 4], 1), sample([1, 3, 4, 5], 1), sample([1, 3, 5, 1], 1), sample([1, 3, 5, 2], 1), sample([1, 3, 5, 3], 1), sample([1, 3, 5, 4], 1), sample([1, 3, 5, 5], 1), sample([1, 4, 1, 1], 0), sample([1, 4, 1, 2], 0), sample([1, 4, 1, 3], 0), sample([1, 4, 1, 5], 1), sample([1, 4, 2, 1], 0), sample([1, 4, 2, 3], 1), sample([1, 4, 2, 4], 1), sample([1, 4, 2, 5], 1), sample([1, 4, 3, 1], 0), sample([1, 4, 3, 2], 1), sample([1, 4, 3, 3], 1), sample([1, 4, 3, 4], 1), sample([1, 4, 3, 5], 1), sample([1, 4, 4, 2], 1), sample([1, 4, 4, 3], 1), sample([1, 4, 4, 4], 1), sample([1, 4, 4, 5], 1), sample([1, 4, 5, 1], 1), sample([1, 4, 5, 2], 1), sample([1, 4, 5, 3], 1), sample([1, 4, 5, 4], 1), sample([1, 4, 5, 5], 1), sample([1, 5, 1, 1], 0), sample([1, 5, 1, 2], 0), sample([1, 5, 1, 3], 0), sample([1, 5, 1, 4], 0), sample([1, 5, 2, 1], 0), sample([1, 5, 2, 2], 0), sample([1, 5, 2, 3], 1), sample([1, 5, 2, 4], 1), sample([1, 5, 2, 5], 1), sample([1, 5, 3, 1], 0), sample([1, 5, 3, 2], 1), sample([1, 5, 3, 3], 1), sample([1, 5, 3, 4], 1), sample([1, 5, 3, 5], 1), sample([1, 5, 4, 1], 0), sample([1, 5, 4, 2], 1), sample([1, 5, 4, 3], 1), sample([1, 5, 4, 4], 1), sample([1, 5, 4, 5], 1), sample([1, 5, 5, 2], 1), sample([1, 5, 5, 3], 1), sample([1, 5, 5, 4], 1), sample([1, 5, 5, 5], 1), sample([2, 1, 1, 1], 0), sample([2, 1, 1, 3], 1), sample([2, 1, 1, 4], 1), sample([2, 1, 1, 5], 1), sample([2, 1, 2, 2], 1), sample([2, 1, 2, 3], 1), sample([2, 1, 2, 4], 1), sample([2, 1, 2, 5], 1), sample([2, 1, 3, 1], 1), sample([2, 1, 3, 2], 1), sample([2, 1, 3, 3], 1), sample([2, 1, 3, 4], 1), sample([2, 1, 3, 5], 1), sample([2, 1, 4, 1], 1), sample([2, 1, 4, 2], 1), sample([2, 1, 4, 3], 1), sample([2, 1, 4, 4], 1), sample([2, 1, 4, 5], 1), sample([2, 1, 5, 1], 1), sample([2, 1, 5, 2], 1), sample([2, 1, 5, 3], 1), sample([2, 1, 5, 4], 1), sample([2, 1, 5, 5], 1), sample([2, 2, 1, 1], 0), sample([2, 2, 1, 2], 0), sample([2, 2, 1, 3], 0), sample([2, 2, 1, 5], 1), sample([2, 2, 2, 1], 0), sample([2, 2, 2, 3], 1), sample([2, 2, 2, 4], 1), sample([2, 2, 2, 5], 1), sample([2, 2, 3, 1], 0), sample([2, 2, 3, 2], 1), sample([2, 2, 3, 3], 1), sample([2, 2, 3, 4], 1), sample([2, 2, 3, 5], 1), sample([2, 2, 4, 2], 1), sample([2, 2, 4, 3], 1), sample([2, 2, 4, 4], 1), sample([2, 2, 4, 5], 1), sample([2, 2, 5, 1], 1), sample([2, 2, 5, 2], 1), sample([2, 2, 5, 3], 1), sample([2, 2, 5, 4], 1), sample([2, 2, 5, 5], 1), sample([2, 3, 1, 1], 0), sample([2, 3, 1, 2], 0), sample([2, 3, 1, 3], 0), sample([2, 3, 1, 4], 0), sample([2, 3, 1, 5], 0), sample([2, 3, 2, 1], 0), sample([2, 3, 2, 2], 0), sample([2, 3, 2, 4], 1), sample([2, 3, 2, 5], 1), sample([2, 3, 3, 1], 0), sample([2, 3, 3, 3], 1), sample([2, 3, 3, 4], 1), sample([2, 3, 3, 5], 1), sample([2, 3, 4, 1], 0), sample([2, 3, 4, 2], 1), sample([2, 3, 4, 3], 1), sample([2, 3, 4, 4], 1), sample([2, 3, 4, 5], 1), sample([2, 3, 5, 1], 0), sample([2, 3, 5, 2], 1), sample([2, 3, 5, 3], 1), sample([2, 3, 5, 4], 1), sample([2, 3, 5, 5], 1), sample([2, 4, 1, 1], 0), sample([2, 4, 1, 2], 0), sample([2, 4, 1, 3], 0), sample([2, 4, 1, 4], 0), sample([2, 4, 1, 5], 0), sample([2, 4, 2, 1], 0), sample([2, 4, 2, 2], 0), sample([2, 4, 2, 3], 0), sample([2, 4, 2, 5], 1), sample([2, 4, 3, 1], 0), sample([2, 4, 3, 2], 0), sample([2, 4, 3, 3], 1), sample([2, 4, 3, 4], 1), sample([2, 4, 3, 5], 1), sample([2, 4, 4, 1], 0), sample([2, 4, 4, 3], 1), sample([2, 4, 4, 4], 1), sample([2, 4, 4, 5], 1), sample([2, 4, 5, 1], 0), sample([2, 4, 5, 2], 1), sample([2, 4, 5, 3], 1), sample([2, 4, 5, 4], 1), sample([2, 4, 5, 5], 1), sample([2, 5, 1, 1], 0), sample([2, 5, 1, 2], 0), sample([2, 5, 1, 3], 0), sample([2, 5, 1, 4], 0), sample([2, 5, 1, 5], 0), sample([2, 5, 2, 1], 0), sample([2, 5, 2, 2], 0), sample([2, 5, 2, 3], 0), sample([2, 5, 2, 4], 0), sample([2, 5, 3, 1], 0), sample([2, 5, 3, 2], 0), sample([2, 5, 3, 3], 0), sample([2, 5, 3, 4], 1), sample([2, 5, 3, 5], 1), sample([2, 5, 4, 1], 0), sample([2, 5, 4, 2], 0), sample([2, 5, 4, 3], 1), sample([2, 5, 4, 4], 1), sample([2, 5, 4, 5], 1), sample([2, 5, 5, 1], 0), sample([2, 5, 5, 3], 1), sample([2, 5, 5, 4], 1), sample([2, 5, 5, 5], 1), sample([3, 1, 1, 1], 0), sample([3, 1, 1, 2], 0), sample([3, 1, 1, 4], 1), sample([3, 1, 1, 5], 1), sample([3, 1, 2, 1], 0), sample([3, 1, 2, 2], 1), sample([3, 1, 2, 3], 1), sample([3, 1, 2, 4], 1), sample([3, 1, 2, 5], 1), sample([3, 1, 3, 2], 1), sample([3, 1, 3, 3], 1), sample([3, 1, 3, 4], 1), sample([3, 1, 3, 5], 1), sample([3, 1, 4, 1], 1), sample([3, 1, 4, 2], 1), sample([3, 1, 4, 3], 1), sample([3, 1, 4, 4], 1), sample([3, 1, 4, 5], 1), sample([3, 1, 5, 1], 1), sample([3, 1, 5, 2], 1), sample([3, 1, 5, 3], 1), sample([3, 1, 5, 4], 1), sample([3, 1, 5, 5], 1), sample([3, 2, 1, 1], 0), sample([3, 2, 1, 2], 0), sample([3, 2, 1, 3], 0), sample([3, 2, 1, 4], 0), sample([3, 2, 1, 5], 0), sample([3, 2, 2, 1], 0), sample([3, 2, 2, 2], 0), sample([3, 2, 2, 4], 1), sample([3, 2, 2, 5], 1), sample([3, 2, 3, 1], 0), sample([3, 2, 3, 3], 1), sample([3, 2, 3, 4], 1), sample([3, 2, 3, 5], 1), sample([3, 2, 4, 1], 0), sample([3, 2, 4, 2], 1), sample([3, 2, 4, 3], 1), sample([3, 2, 4, 4], 1), sample([3, 2, 4, 5], 1), sample([3, 2, 5, 1], 0), sample([3, 2, 5, 2], 1), sample([3, 2, 5, 3], 1), sample([3, 2, 5, 4], 1), sample([3, 2, 5, 5], 1), sample([3, 3, 1, 1], 0), sample([3, 3, 1, 2], 0), sample([3, 3, 1, 3], 0), sample([3, 3, 1, 4], 0), sample([3, 3, 1, 5], 0), sample([3, 3, 2, 1], 0), sample([3, 3, 2, 2], 0), sample([3, 3, 2, 3], 0), sample([3, 3, 2, 4], 0), sample([3, 3, 2, 5], 1), sample([3, 3, 3, 1], 0), sample([3, 3, 3, 2], 0), sample([3, 3, 3, 4], 1), sample([3, 3, 3, 5], 1), sample([3, 3, 4, 1], 0), sample([3, 3, 4, 2], 0), sample([3, 3, 4, 3], 1), sample([3, 3, 4, 4], 1), sample([3, 3, 4, 5], 1), sample([3, 3, 5, 1], 0), sample([3, 3, 5, 2], 1), sample([3, 3, 5, 3], 1), sample([3, 3, 5, 4], 1), sample([3, 3, 5, 5], 1), sample([3, 4, 1, 1], 0), sample([3, 4, 1, 2], 0), sample([3, 4, 1, 3], 0), sample([3, 4, 1, 4], 0), sample([3, 4, 1, 5], 0), sample([3, 4, 2, 1], 0), sample([3, 4, 2, 2], 0), sample([3, 4, 2, 3], 0), sample([3, 4, 2, 4], 0), sample([3, 4, 2, 5], 0), sample([3, 4, 3, 1], 0), sample([3, 4, 3, 2], 0), sample([3, 4, 3, 3], 0), sample([3, 4, 3, 5], 1), sample([3, 4, 4, 1], 0), sample([3, 4, 4, 2], 0), sample([3, 4, 4, 4], 1), sample([3, 4, 4, 5], 1), sample([3, 4, 5, 1], 0), sample([3, 4, 5, 2], 0), sample([3, 4, 5, 3], 1), sample([3, 4, 5, 4], 1), sample([3, 4, 5, 5], 1), sample([3, 5, 1, 1], 0), sample([3, 5, 1, 2], 0), sample([3, 5, 1, 3], 0), sample([3, 5, 1, 4], 0), sample([3, 5, 1, 5], 0), sample([3, 5, 2, 1], 0), sample([3, 5, 2, 2], 0), sample([3, 5, 2, 3], 0), sample([3, 5, 2, 4], 0), sample([3, 5, 2, 5], 0), sample([3, 5, 3, 1], 0), sample([3, 5, 3, 2], 0), sample([3, 5, 3, 3], 0), sample([3, 5, 3, 4], 0), sample([3, 5, 4, 1], 0), sample([3, 5, 4, 2], 0), sample([3, 5, 4, 3], 0), sample([3, 5, 4, 4], 1), sample([3, 5, 4, 5], 1), sample([3, 5, 5, 1], 0), sample([3, 5, 5, 2], 0), sample([3, 5, 5, 4], 1), sample([3, 5, 5, 5], 1), sample([4, 1, 1, 1], 0), sample([4, 1, 1, 2], 0), sample([4, 1, 1, 3], 0), sample([4, 1, 1, 5], 1), sample([4, 1, 2, 1], 0), sample([4, 1, 2, 3], 1), sample([4, 1, 2, 4], 1), sample([4, 1, 2, 5], 1), sample([4, 1, 3, 1], 0), sample([4, 1, 3, 2], 1), sample([4, 1, 3, 3], 1), sample([4, 1, 3, 4], 1), sample([4, 1, 3, 5], 1), sample([4, 1, 4, 2], 1), sample([4, 1, 4, 3], 1), sample([4, 1, 4, 4], 1), sample([4, 1, 4, 5], 1), sample([4, 1, 5, 1], 1), sample([4, 1, 5, 2], 1), sample([4, 1, 5, 3], 1), sample([4, 1, 5, 4], 1), sample([4, 1, 5, 5], 1), sample([4, 2, 1, 1], 0), sample([4, 2, 1, 2], 0), sample([4, 2, 1, 3], 0), sample([4, 2, 1, 4], 0), sample([4, 2, 1, 5], 0), sample([4, 2, 2, 1], 0), sample([4, 2, 2, 2], 0), sample([4, 2, 2, 3], 0), sample([4, 2, 2, 5], 1), sample([4, 2, 3, 1], 0), sample([4, 2, 3, 2], 0), sample([4, 2, 3, 3], 1), sample([4, 2, 3, 4], 1), sample([4, 2, 3, 5], 1), sample([4, 2, 4, 1], 0), sample([4, 2, 4, 3], 1), sample([4, 2, 4, 4], 1), sample([4, 2, 4, 5], 1), sample([4, 2, 5, 1], 0), sample([4, 2, 5, 2], 1), sample([4, 2, 5, 3], 1), sample([4, 2, 5, 4], 1), sample([4, 2, 5, 5], 1), sample([4, 3, 1, 1], 0), sample([4, 3, 1, 2], 0), sample([4, 3, 1, 3], 0), sample([4, 3, 1, 4], 0), sample([4, 3, 1, 5], 0), sample([4, 3, 2, 1], 0), sample([4, 3, 2, 2], 0), sample([4, 3, 2, 3], 0), sample([4, 3, 2, 4], 0), sample([4, 3, 2, 5], 0), sample([4, 3, 3, 1], 0), sample([4, 3, 3, 2], 0), sample([4, 3, 3, 3], 0), sample([4, 3, 3, 5], 1), sample([4, 3, 4, 1], 0), sample([4, 3, 4, 2], 0), sample([4, 3, 4, 4], 1), sample([4, 3, 4, 5], 1), sample([4, 3, 5, 1], 0), sample([4, 3, 5, 2], 0), sample([4, 3, 5, 3], 1), sample([4, 3, 5, 4], 1), sample([4, 3, 5, 5], 1), sample([4, 4, 1, 1], 0), sample([4, 4, 1, 2], 0), sample([4, 4, 1, 3], 0), sample([4, 4, 1, 4], 0), sample([4, 4, 1, 5], 0), sample([4, 4, 2, 1], 0), sample([4, 4, 2, 2], 0), sample([4, 4, 2, 3], 0), sample([4, 4, 2, 4], 0), sample([4, 4, 2, 5], 0), sample([4, 4, 3, 1], 0), sample([4, 4, 3, 2], 0), sample([4, 4, 3, 3], 0), sample([4, 4, 3, 4], 0), sample([4, 4, 3, 5], 0), sample([4, 4, 4, 1], 0), sample([4, 4, 4, 2], 0), sample([4, 4, 4, 3], 0), sample([4, 4, 4, 5], 1), sample([4, 4, 5, 1], 0), sample([4, 4, 5, 2], 0), sample([4, 4, 5, 3], 0), sample([4, 4, 5, 4], 1), sample([4, 4, 5, 5], 1), sample([4, 5, 1, 1], 0), sample([4, 5, 1, 2], 0), sample([4, 5, 1, 3], 0), sample([4, 5, 1, 4], 0), sample([4, 5, 1, 5], 0), sample([4, 5, 2, 1], 0), sample([4, 5, 2, 2], 0), sample([4, 5, 2, 3], 0), sample([4, 5, 2, 4], 0), sample([4, 5, 2, 5], 0), sample([4, 5, 3, 1], 0), sample([4, 5, 3, 2], 0), sample([4, 5, 3, 3], 0), sample([4, 5, 3, 4], 0), sample([4, 5, 3, 5], 0), sample([4, 5, 4, 1], 0), sample([4, 5, 4, 2], 0), sample([4, 5, 4, 3], 0), sample([4, 5, 4, 4], 0), sample([4, 5, 5, 1], 0), sample([4, 5, 5, 2], 0), sample([4, 5, 5, 3], 0), sample([4, 5, 5, 5], 1), sample([5, 1, 1, 1], 0), sample([5, 1, 1, 2], 0), sample([5, 1, 1, 3], 0), sample([5, 1, 1, 4], 0), sample([5, 1, 2, 1], 0), sample([5, 1, 2, 2], 0), sample([5, 1, 2, 3], 1), sample([5, 1, 2, 4], 1), sample([5, 1, 2, 5], 1), sample([5, 1, 3, 1], 0), sample([5, 1, 3, 2], 1), sample([5, 1, 3, 3], 1), sample([5, 1, 3, 4], 1), sample([5, 1, 3, 5], 1), sample([5, 1, 4, 1], 0), sample([5, 1, 4, 2], 1), sample([5, 1, 4, 3], 1), sample([5, 1, 4, 4], 1), sample([5, 1, 4, 5], 1), sample([5, 1, 5, 2], 1), sample([5, 1, 5, 3], 1), sample([5, 1, 5, 4], 1), sample([5, 1, 5, 5], 1), sample([5, 2, 1, 1], 0), sample([5, 2, 1, 2], 0), sample([5, 2, 1, 3], 0), sample([5, 2, 1, 4], 0), sample([5, 2, 1, 5], 0), sample([5, 2, 2, 1], 0), sample([5, 2, 2, 2], 0), sample([5, 2, 2, 3], 0), sample([5, 2, 2, 4], 0), sample([5, 2, 3, 1], 0), sample([5, 2, 3, 2], 0), sample([5, 2, 3, 3], 0), sample([5, 2, 3, 4], 1), sample([5, 2, 3, 5], 1), sample([5, 2, 4, 1], 0), sample([5, 2, 4, 2], 0), sample([5, 2, 4, 3], 1), sample([5, 2, 4, 4], 1), sample([5, 2, 4, 5], 1), sample([5, 2, 5, 1], 0), sample([5, 2, 5, 3], 1), sample([5, 2, 5, 4], 1), sample([5, 2, 5, 5], 1), sample([5, 3, 1, 1], 0), sample([5, 3, 1, 2], 0), sample([5, 3, 1, 3], 0), sample([5, 3, 1, 4], 0), sample([5, 3, 1, 5], 0), sample([5, 3, 2, 1], 0), sample([5, 3, 2, 2], 0), sample([5, 3, 2, 3], 0), sample([5, 3, 2, 4], 0), sample([5, 3, 2, 5], 0), sample([5, 3, 3, 1], 0), sample([5, 3, 3, 2], 0), sample([5, 3, 3, 3], 0), sample([5, 3, 3, 4], 0), sample([5, 3, 4, 1], 0), sample([5, 3, 4, 2], 0), sample([5, 3, 4, 3], 0), sample([5, 3, 4, 4], 1), sample([5, 3, 4, 5], 1), sample([5, 3, 5, 1], 0), sample([5, 3, 5, 2], 0), sample([5, 3, 5, 4], 1), sample([5, 3, 5, 5], 1), sample([5, 4, 1, 1], 0), sample([5, 4, 1, 2], 0), sample([5, 4, 1, 3], 0), sample([5, 4, 1, 4], 0), sample([5, 4, 1, 5], 0), sample([5, 4, 2, 1], 0), sample([5, 4, 2, 2], 0), sample([5, 4, 2, 3], 0), sample([5, 4, 2, 4], 0), sample([5, 4, 2, 5], 0), sample([5, 4, 3, 1], 0), sample([5, 4, 3, 2], 0), sample([5, 4, 3, 3], 0), sample([5, 4, 3, 4], 0), sample([5, 4, 3, 5], 0), sample([5, 4, 4, 1], 0), sample([5, 4, 4, 2], 0), sample([5, 4, 4, 3], 0), sample([5, 4, 4, 4], 0), sample([5, 4, 5, 1], 0), sample([5, 4, 5, 2], 0), sample([5, 4, 5, 3], 0), sample([5, 4, 5, 5], 1), sample([5, 5, 1, 1], 0), sample([5, 5, 1, 2], 0), sample([5, 5, 1, 3], 0), sample([5, 5, 1, 4], 0), sample([5, 5, 1, 5], 0), sample([5, 5, 2, 1], 0), sample([5, 5, 2, 2], 0), sample([5, 5, 2, 3], 0), sample([5, 5, 2, 4], 0), sample([5, 5, 2, 5], 0), sample([5, 5, 3, 1], 0), sample([5, 5, 3, 2], 0), sample([5, 5, 3, 3], 0), sample([5, 5, 3, 4], 0), sample([5, 5, 3, 5], 0), sample([5, 5, 4, 1], 0), sample([5, 5, 4, 2], 0), sample([5, 5, 4, 3], 0), sample([5, 5, 4, 4], 0), sample([5, 5, 4, 5], 0), sample([5, 5, 5, 1], 0), sample([5, 5, 5, 2], 0), sample([5, 5, 5, 3], 0), sample([5, 5, 5, 4], 0), continuous=[True, True, True, True] ) async def main(): async with mpc: forest = await output(await train_forest(samples, amount=2, depth=4)) for index, tree in enumerate(forest): print(f"Tree #{index}") tree.pretty_print() if __name__ == '__main__': mpc.run(main())

26.669739

77

0.388722

3,543

17,362

1.901778

0.013266

0.299199

0.116355

0.032057

0.938557

0

0.240187

0.308893

17,362

650

78

26.710769

0.32136

0

0.00121

0

1

0.001684

false

0

0.008418

0.001684

0.011785

0.003367

0

1

null

1

0

1

0

1

0

1

0

null

0

5

f753fbf3ff60b90fee53bf99ea41acdd1b952379

3,173

py

Python

networkx_mod/algorithms/__init__.py

movingpictures83/MATria

d3dbd0d15e00dbc26db39ace0663868180fdc471

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

null

networkx_mod/algorithms/__init__.py

movingpictures83/MATria

d3dbd0d15e00dbc26db39ace0663868180fdc471

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

null

networkx_mod/algorithms/__init__.py

movingpictures83/MATria

d3dbd0d15e00dbc26db39ace0663868180fdc471

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

null

from networkx_mod.algorithms.assortativity import * from networkx_mod.algorithms.block import * from networkx_mod.algorithms.boundary import * from networkx_mod.algorithms.centrality import * from networkx_mod.algorithms.cluster import * from networkx_mod.algorithms.clique import * from networkx_mod.algorithms.community import * from networkx_mod.algorithms.components import * from networkx_mod.algorithms.coloring import * from networkx_mod.algorithms.core import * from networkx_mod.algorithms.cycles import * from networkx_mod.algorithms.dag import * from networkx_mod.algorithms.distance_measures import * from networkx_mod.algorithms.dominance import * from networkx_mod.algorithms.dominating import * from networkx_mod.algorithms.hierarchy import * from networkx_mod.algorithms.matching import * from networkx_mod.algorithms.mis import * from networkx_mod.algorithms.mst import * from networkx_mod.algorithms.link_analysis import * from networkx_mod.algorithms.link_prediction import * from networkx_mod.algorithms.operators import * from networkx_mod.algorithms.shortest_paths import * from networkx_mod.algorithms.smetric import * from networkx_mod.algorithms.traversal import * from networkx_mod.algorithms.isolate import * from networkx_mod.algorithms.euler import * from networkx_mod.algorithms.vitality import * from networkx_mod.algorithms.chordal import * from networkx_mod.algorithms.richclub import * from networkx_mod.algorithms.distance_regular import * from networkx_mod.algorithms.swap import * from networkx_mod.algorithms.graphical import * from networkx_mod.algorithms.simple_paths import * import networkx_mod.algorithms.assortativity import networkx_mod.algorithms.bipartite import networkx_mod.algorithms.centrality import networkx_mod.algorithms.cluster import networkx_mod.algorithms.clique import networkx_mod.algorithms.components import networkx_mod.algorithms.connectivity import networkx_mod.algorithms.coloring import networkx_mod.algorithms.flow import networkx_mod.algorithms.isomorphism import networkx_mod.algorithms.link_analysis import networkx_mod.algorithms.shortest_paths import networkx_mod.algorithms.traversal import networkx_mod.algorithms.chordal import networkx_mod.algorithms.operators import networkx_mod.algorithms.tree # bipartite from networkx_mod.algorithms.bipartite import (projected_graph, project, is_bipartite, complete_bipartite_graph) # connectivity from networkx_mod.algorithms.connectivity import (minimum_edge_cut, minimum_node_cut, average_node_connectivity, edge_connectivity, node_connectivity, stoer_wagner, all_pairs_node_connectivity) # isomorphism from networkx_mod.algorithms.isomorphism import (is_isomorphic, could_be_isomorphic, fast_could_be_isomorphic, faster_could_be_isomorphic) # flow from networkx_mod.algorithms.flow import (maximum_flow, maximum_flow_value, minimum_cut, minimum_cut_value, capacity_scaling, network_simplex, min_cost_flow_cost, max_flow_min_cost, min_cost_flow, cost_of_flow) from .tree.recognition import * from .tree.branchings import ( maximum_branching, minimum_branching, maximum_spanning_arborescence, minimum_spanning_arborescence )

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f7705e3cc1b211d4663b54c4da3c65f968c2a26c

135

py

Python

zoo/__init__.py

uliana291/the-zoo

a15a4162c39553abe91224f4feff5d3b66f9413e

[ "MIT" ]

90

2018-11-20T10:58:24.000Z

2022-02-19T16:12:46.000Z

zoo/__init__.py

uliana291/the-zoo

a15a4162c39553abe91224f4feff5d3b66f9413e

[ "MIT" ]

348

2018-11-21T09:22:31.000Z

2021-11-03T13:45:08.000Z

zoo/__init__.py

aexvir/the-zoo

7816afb9a0a26c6058b030b4a987c73e952d92bd

[ "MIT" ]

11

2018-12-08T18:42:07.000Z

2021-02-21T06:27:58.000Z

from ddtrace import patch_all from .base.celery import app as celery_app from .base.wsgi import application patch_all(requests=True)

19.285714

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f7a10b6976072b5836edf56561287db490f53e79

73

py

Python

scripts/__init__.py

arte-dev/opensdg-ibestat

32cfd5856c7028df969e050435926b6d5bb29e2c

[ "MIT" ]

null

scripts/__init__.py

arte-dev/opensdg-ibestat

32cfd5856c7028df969e050435926b6d5bb29e2c

[ "MIT" ]

null

scripts/__init__.py

arte-dev/opensdg-ibestat

32cfd5856c7028df969e050435926b6d5bb29e2c

[ "MIT" ]

null

from . import overrides from . import build_data from . import check_data

24.333333

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5

e39fb3f56a514105f23d8bd18223641f39ed5f91

324

py

Python

scrapy/contrib/spidermiddleware/httperror.py

jesuslosada/scrapy

8be28fe4ca8b1cd011d5f7e03661da8a6bb3217b

[ "BSD-3-Clause" ]

22

2018-03-13T13:51:41.000Z

2022-02-19T07:27:48.000Z

scrapy/contrib/spidermiddleware/httperror.py

EnjoyLifeFund/Debian_py36_packages

1985d4c73fabd5f08f54b922e73a9306e09c77a5

[ "BSD-3-Clause", "BSD-2-Clause", "MIT" ]

10

2020-02-11T23:34:28.000Z

2022-03-11T23:16:12.000Z

scrapy/contrib/spidermiddleware/httperror.py

EnjoyLifeFund/Debian_py36_packages

1985d4c73fabd5f08f54b922e73a9306e09c77a5

[ "BSD-3-Clause", "BSD-2-Clause", "MIT" ]

6

2017-12-28T03:59:54.000Z

2020-02-26T16:01:45.000Z

import warnings from scrapy.exceptions import ScrapyDeprecationWarning warnings.warn("Module `scrapy.contrib.spidermiddleware.httperror` is deprecated, " "use `scrapy.spidermiddlewares.httperror` instead", ScrapyDeprecationWarning, stacklevel=2) from scrapy.spidermiddlewares.httperror import *

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1

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5

e3d24a4198b47fdceb1099d7e5b98d5d1e277f46

366

py

Python

igamelister/webscraper/interpolation.py

chris-vg/igamelister

807f4d504911341edbc7ffc187c3a19b29a72ace

[ "MIT" ]

null

igamelister/webscraper/interpolation.py

chris-vg/igamelister

807f4d504911341edbc7ffc187c3a19b29a72ace

[ "MIT" ]

null

igamelister/webscraper/interpolation.py

chris-vg/igamelister

807f4d504911341edbc7ffc187c3a19b29a72ace

[ "MIT" ]

null

from configparser import BasicInterpolation class TemplateInterpolation(BasicInterpolation): def __init__(self, **kwargs): self._interpolate_dict = kwargs def set(self, key: str, value): self._interpolate_dict[key] = value def before_get(self, parser, section, option, value, defaults): return value % self._interpolate_dict

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1

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null

0

1

0

1

0

5

e3e42d8bf5c1361f22824339a6783086aa4f4fd6

2,784

py

Python

test_mnist_with_keras.py

nothingbutpassion/dldiy

53c6365fb5689b47ec62cf3bb4c3d5bde621e8f4

[ "Apache-2.0" ]

1

2018-12-24T12:15:25.000Z

test_mnist_with_keras.py

nothingbutpassion/dldiy

53c6365fb5689b47ec62cf3bb4c3d5bde621e8f4

[ "Apache-2.0" ]

null

test_mnist_with_keras.py

nothingbutpassion/dldiy

53c6365fb5689b47ec62cf3bb4c3d5bde621e8f4

[ "Apache-2.0" ]

null

import numpy as np import matplotlib.pyplot as plt import datasets.mnist as mnist from tensorflow.keras import models from tensorflow.keras import layers from tensorflow.keras import optimizers from tensorflow.keras import losses def test_mnist(): (train_x, train_y), (test_x, test_y) = mnist.load_data() val_x = train_x[50000:] val_y = train_y[50000:] train_x = train_x[:50000] train_y = train_y[:50000] model = models.Sequential() model.add(layers.Dense(28, activation="relu", input_shape=(train_x.shape[1],))) model.add(layers.Dense(10, activation="relu")) model.add(layers.Dense(10, activation="softmax")) model.compile(optimizer=optimizers.SGD(lr=0.001), loss=losses.categorical_crossentropy, metrics=['accuracy']) model.summary() history = model.fit(train_x, train_y, batch_size=200, epochs=32, validation_data=(val_x, val_y)).history epochs = range(1, len(history["loss"])+1) plt.plot(epochs, history["loss"], 'ro', label="Traning loss") plt.plot(epochs, history["val_loss"], 'go',label="Validating loss") plt.plot(epochs, history["accuracy"], 'r', label="Traning accuracy") plt.plot(epochs, history["val_accuracy"], 'g', label="Validating accuracy") plt.title('Training/Validating loss/accuracy') plt.xlabel('Epochs') plt.ylabel('Loss/Accuracy') plt.legend() plt.show(block=True) def test_mnist_with_cov2d(): (train_x, train_y), (test_x, test_y) = mnist.load_data(flatten=False) val_x = train_x[50000:] val_y = train_y[50000:] train_x = train_x[:50000] train_y = train_y[:50000] model = models.Sequential() model.add(layers.Conv2D(4, (3, 3), strides=(1,1), padding='same', data_format="channels_first", activation="relu", input_shape=(1, 28, 28))) model.add(layers.MaxPooling2D(pool_size=(2, 2), strides=(2,2), data_format="channels_first")) model.add(layers.Flatten()) model.add(layers.Dense(10, activation="softmax")) model.compile(optimizer=optimizers.SGD(lr=0.001), loss=losses.categorical_crossentropy, metrics=['accuracy']) model.summary() history = model.fit(train_x, train_y, batch_size=200, epochs=20, validation_data=(val_x, val_y)).history epochs = range(1, len(history["loss"])+1) plt.plot(epochs, history["loss"], 'ro', label="Traning loss") plt.plot(epochs, history["val_loss"], 'go',label="Validating loss") plt.plot(epochs, history["acc"], 'r', label="Traning accuracy") plt.plot(epochs, history["val_acc"], 'g', label="Validating accuracy") plt.title('Training/Validating loss/accuracy') plt.xlabel('Epochs') plt.ylabel('Loss/Accuracy') plt.legend() plt.show(block=True) if __name__ == "__main__": test_mnist()

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5

e3e8d0c67a85eb26f40805821cf5852f52a05d55

210

py

Python

simple_salesforce/aio/__init__.py

MulliganFunding/simple-salesforce

6d43d252683e688eb50faab46c6030afc0aa9838

[ "Apache-2.0" ]

null

simple_salesforce/aio/__init__.py

MulliganFunding/simple-salesforce

6d43d252683e688eb50faab46c6030afc0aa9838

[ "Apache-2.0" ]

null

simple_salesforce/aio/__init__.py

MulliganFunding/simple-salesforce

6d43d252683e688eb50faab46c6030afc0aa9838

[ "Apache-2.0" ]

null

"""Simple-Salesforce Asyncio Package""" # flake8: noqa from .api import build_async_salesforce_client, AsyncSalesforce, AsyncSFType from .bulk import AsyncSFBulkHandler from .login import AsyncSalesforceLogin

30

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1

0

1

0

5

e3eba1d73095e338b7673269be9d1dcb3f1a33e6

1,126

py

Python

gloop/repositories/user_repository.py

pitzer42/gloop_old

9ad5ad9e10387e17dfd5a40e65d2910e10f59d77

[ "MIT" ]

null

gloop/repositories/user_repository.py

pitzer42/gloop_old

9ad5ad9e10387e17dfd5a40e65d2910e10f59d77

[ "MIT" ]

null

gloop/repositories/user_repository.py

pitzer42/gloop_old

9ad5ad9e10387e17dfd5a40e65d2910e10f59d77

[ "MIT" ]

null

from typing import ( NoReturn, List ) from abc import ( ABC, abstractmethod ) from gloop.models.user import User from gloop.repositories.data_ports import pass_by class UserRepository(ABC): @abstractmethod async def to_list(self, length=100, data_port=pass_by) -> List: raise NotImplemented() @abstractmethod async def count(self) -> int: raise NotImplemented() @abstractmethod async def insert(self, user: User, data_port=pass_by) -> NoReturn: raise NotImplemented() @abstractmethod async def get_by_name(self, name: str, data_port=pass_by) -> User: raise NotImplemented() @abstractmethod async def get_by_token(self, token: str, data_port=pass_by) -> User: raise NotImplemented() @abstractmethod async def delete_by_name(self, name: str) -> NoReturn: raise NotImplemented() @abstractmethod async def delete_token(self, token: str) -> NoReturn: raise NotImplemented() @abstractmethod async def set_token(self, name: str, token: str) -> NoReturn: raise NotImplemented()

23.458333

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5

540a8d103f0307647762947e43d82991001ba0d2

192

py

Python

aadnes_journey/models/character.py

mradrianhh/Aadnes-journey

13d6065eb0997b5ee9ea64e38de104d035178ef4

[ "MIT" ]

null

aadnes_journey/models/character.py

mradrianhh/Aadnes-journey

13d6065eb0997b5ee9ea64e38de104d035178ef4

[ "MIT" ]

null

aadnes_journey/models/character.py

mradrianhh/Aadnes-journey

13d6065eb0997b5ee9ea64e38de104d035178ef4

[ "MIT" ]

null

class Character(): __name: str # Getters and setters. def get_name(self) -> str: return self.__name def set_name(self, name: str) -> None: self.__name = name

19.2

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null

0

1

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1

0

5

58138e64152781a2db0bb9b073443ec70bd142cd

583

py

Python

src/locale/_cid.py

sffjunkie/locale

ad9a7605487e3d3db3bc0156a136fef27cb392e1

[ "Apache-2.0" ]

null

src/locale/_cid.py

sffjunkie/locale

ad9a7605487e3d3db3bc0156a136fef27cb392e1

[ "Apache-2.0" ]

null

src/locale/_cid.py

sffjunkie/locale

ad9a7605487e3d3db3bc0156a136fef27cb392e1

[ "Apache-2.0" ]

null

class CaseInsensitiveDict(dict): __transform__ = str.upper def __init__(self, *args, **kwargs): for k, v in dict(*args, **kwargs).items(): self[CaseInsensitiveDict.__transform__(k)] = v def __contains__(self, key): return dict.__contains__(self, CaseInsensitiveDict.__transform__(key)) def __getitem__(self, key): val = dict.__getitem__(self, CaseInsensitiveDict.__transform__(key)) return val def __repr__(self): dictrepr = dict.__repr__(self) return '%s(%s)' % (type(self).__name__, dictrepr)

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0

null

1

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null

0

1

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1

0

5

581d3b5619094793c2af904b989b57d0e070c317

684

py

Python

sdk/python/pulumi_gcp/pubsub/__init__.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

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

null

sdk/python/pulumi_gcp/pubsub/__init__.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

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

null

sdk/python/pulumi_gcp/pubsub/__init__.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

[ "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! *** from .. import _utilities import typing # Export this package's modules as members: from .get_topic import * from .lite_subscription import * from .lite_topic import * from .schema import * from .subscription import * from .subscription_iam_binding import * from .subscription_iam_member import * from .subscription_iam_policy import * from .topic import * from .topic_iam_binding import * from .topic_iam_member import * from .topic_iam_policy import * from ._inputs import * from . import outputs

31.090909

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1

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1

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5

583e5d3813f00f82a5a7bf5f196051e00f488e94

86

py

Python

admin/forms/__init__.py

Simple2B/cortex-backend

9cf6802b0eff9254875bcbe553517500ccfc9082

[ "MIT" ]

1

2021-10-17T13:28:51.000Z

admin/forms/__init__.py

Simple2B/cortex-backend

9cf6802b0eff9254875bcbe553517500ccfc9082

[ "MIT" ]

null

admin/forms/__init__.py

Simple2B/cortex-backend

9cf6802b0eff9254875bcbe553517500ccfc9082

[ "MIT" ]

null

# flake8: noqa F401 from .auth import LoginForm from .new_doctor import NewDoctorForm

21.5

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1

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5

5844e0c49edb7766cf0cffa86f40874fe3b523eb

64

py

Python

Python Exercise/Tensorboard.py

mewadashreya/MLOne-Basic

f5048379a3b276cd371ce89cca6a0949d2815ce9

[ "Apache-2.0" ]

1

2020-09-20T19:00:08.000Z

Python Exercise/Tensorboard.py

SarangDeshmukh7/MLOne-Basic

490161740e536e3c5689ad248de1be931160e7c7

[ "Apache-2.0" ]

null

Python Exercise/Tensorboard.py

SarangDeshmukh7/MLOne-Basic

490161740e536e3c5689ad248de1be931160e7c7

[ "Apache-2.0" ]

null

import tensorflow as tf import datetime print("Hello World")

16

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5

5849e48b30b1af8fb151c42e016aafdd544153e2

198

py

Python

projects/PointRend/point_rend/__init__.py

Shun14/detectron2-ResNeSt

cda53a237199da3bbe7526d41c41b9d8df4c4814

[ "Apache-2.0" ]

344

2020-04-18T18:33:33.000Z

2020-12-04T08:34:30.000Z

projects/PointRend/point_rend/__init__.py

ZhanqiZhang66/detectron2

be0d7283297f6314c8e683e0d1ff80b668aa9f4a

[ "Apache-2.0" ]

82

2020-01-29T23:48:32.000Z

2021-09-08T02:09:30.000Z

projects/PointRend/point_rend/__init__.py

ZhanqiZhang66/detectron2

be0d7283297f6314c8e683e0d1ff80b668aa9f4a

[ "Apache-2.0" ]

66

2020-04-20T08:30:49.000Z

2020-12-06T12:55:12.000Z

39.6

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585e40e2fc4d4f110d13fea49ba3922c3de83ab7

180

py

Python

src/data/__init__.py

marka17/digit-recognition

129fa77dc41eca4f4ffbc6a37045a194cd4beb12

[ "MIT" ]

null

src/data/__init__.py

marka17/digit-recognition

129fa77dc41eca4f4ffbc6a37045a194cd4beb12

[ "MIT" ]

null

src/data/__init__.py

marka17/digit-recognition

129fa77dc41eca4f4ffbc6a37045a194cd4beb12

[ "MIT" ]

null

from .dataset import SpeechDataset from .batch import Batch from .dataloader import PaddingCollator from .batch_processor import BatchProcessor from .dictionary import ctc_decode

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py

Python

quarkchain/reward.py

tim-yoshi/pyquarkchain

1847542c166a180b5ffc3c6e917751be85fa15a6

[ "MIT" ]

237

2018-09-18T00:47:14.000Z

2022-03-21T21:43:07.000Z

quarkchain/reward.py

tim-yoshi/pyquarkchain

1847542c166a180b5ffc3c6e917751be85fa15a6

[ "MIT" ]

409

2018-09-18T01:02:29.000Z

2022-01-24T20:51:58.000Z

quarkchain/reward.py

tim-yoshi/pyquarkchain

1847542c166a180b5ffc3c6e917751be85fa15a6

[ "MIT" ]

125

2018-09-18T00:47:28.000Z

2022-03-24T20:00:46.000Z

class ConstMinorBlockRewardCalcultor: def __init__(self, env): self.env = env def get_block_reward(self): return 100000000000000000000

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py

Python

openpyxlzip/cell/__init__.py

ankitJoshi03/openpyxlzip

f3b8aa2f80f9d8bc31ce5fcf05c822d88d2ff647

[ "MIT" ]

null

openpyxlzip/cell/__init__.py

ankitJoshi03/openpyxlzip

f3b8aa2f80f9d8bc31ce5fcf05c822d88d2ff647

[ "MIT" ]

null

openpyxlzip/cell/__init__.py

ankitJoshi03/openpyxlzip

f3b8aa2f80f9d8bc31ce5fcf05c822d88d2ff647

[ "MIT" ]

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28,108

py

Python

MKDecrypt.py

AmNe5iA/MKDecrypt

4bc8668e0fa53ef02dda2ff358912046d555ad09

[ "MIT" ]

7

2017-02-07T22:44:24.000Z

2021-09-29T13:28:16.000Z

MKDecrypt.py

AmNe5iA/MKDecrypt

4bc8668e0fa53ef02dda2ff358912046d555ad09

[ "MIT" ]

2

2018-03-12T22:24:52.000Z

2021-10-03T08:14:41.000Z

MKDecrypt.py

AmNe5iA/MKDecrypt

4bc8668e0fa53ef02dda2ff358912046d555ad09

[ "MIT" ]

7

2018-12-12T17:52:28.000Z

2022-03-07T13:23:30.000Z

#!/usr/bin/python3 # MKDecrypt.py (Master Key Decryptor) is a python script to assist with # decrypting encrypted volumes using the recovered masterkey for various # truecrypt type encrypted volumes. # Created by Matt Smith # email: amnesia_1337 (at) hotmail (dot) co (dot) uk # Limitations: May produce false negatives if the filesystem used is not one of # the standard truecrypt/veracrypt formats. The HFS+ implementation is # _sketchy_ but appears to work, for now. import os import stat import argparse import subprocess import binascii def main(): ## print empty line away from command line so easier for user to read print(' ') ## Setup arguments/options using imported argparse module parser = argparse.ArgumentParser(description='''%(prog)s (Master Key Decryptor) is a python script to assist with decrypting encrypted volumes using the recovered masterkey for various encrypted containers. Script should be run as root, sudo recommended.''', epilog='''Example: [sudo] ./%(prog)s -m /mnt truecrypt.tc 123...def''') parser.add_argument('-v', '--verbose', action='store_true', help=''' verbose output''') parser.add_argument('-X', '--volatility', action='store_true', help='specifies MASTERKEY is a volatility file instead of hex chars') rwgroup = parser.add_mutually_exclusive_group() rwgroup.add_argument('-r', '--read-only', action='store_true', help='opens FILE in read only mode (default)') rwgroup.add_argument('-w', '--read-write', action='store_true', help='opens FILE in read/write mode') parser.add_argument('-m', '--mountpoint', help='''mount encrypted volume at MOUNTPOINT''', default='N0P3') parser.add_argument('FILE', help='the encrypted container, FILE') parser.add_argument('MASTERKEY', help='''the MASTERKEY as a hexadecimal string''') args = parser.parse_args() ## check to see if you are using a raw volatility dump if(args.volatility): isMKFile = os.access(args.MASTERKEY, os.F_OK) if isMKFile: masterkeyfile = open(args.MASTERKEY,"rb").read() args.MASTERKEY = binascii.hexlify(masterkeyfile).decode('utf-8') else: print (args.MASTERKEY + ' is not a file.' ) exit(1) ## check to see if this script is being run as root/superuser. exit if not if not os.geteuid() == 0: print("This script needs to be run as root/superuser.") exit(1) ## setup ro(read-only) flag for passing to other programs ro = '' if not args.read_write: args.read_only=True ro = '-r' ## check master key length is correct and is only hex charachters if not len(args.MASTERKEY) == 128 and not len(args.MASTERKEY) == 256 and not len(args.MASTERKEY) == 384: print('MASTERKEY is not of the correct length. It should be 128, 256 or 384 hexadecimal characters in length.') exit(1) hexis = set('0123456789abcdefABCDEF') for c in args.MASTERKEY: if not c in hexis: print ( c + ' is not a hexadecimal character') exit(1) ## check file specified by user actually exists isFILE = os.access(args.FILE, os.F_OK) if isFILE and args.verbose: print (args.FILE + ' exists') elif not isFILE: print ('No such file: ' + args.FILE) exit(1) ## check mount option and mount point if args.mountpoint == 'N0P3': mp=False else: isDIR = os.path.isdir(args.mountpoint) if isDIR and args.verbose: print(args.mountpoint + ' exists') elif not isDIR: print('No such mountpoint: ' + args.mountpoint) exit(1) mp=True ## find a free MKDecrypt device mapper slot for i in range(8): dmname = "MKDecrypt" + str(i+1) dmslot = "/dev/mapper/" + dmname takenslot = os.access(dmslot, os.F_OK) if not takenslot: break elif i == 7: print('All 8 MKDecrypt slots are taken! Free some up.') exit(1) ## check to see if container is already a blockdev ## if so, skip mounting it as loop device mode=os.lstat(args.FILE).st_mode isBLKDEV = stat.S_ISBLK(mode) if isBLKDEV: loopdev = args.FILE ## otherwise mount container as loop device else: losetupcmd = 'losetup ' + ro + ' -f --show ' + args.FILE losetupoutput = subprocess.check_output(losetupcmd, shell=True, universal_newlines=True) loopdev = losetupoutput[:-1] if args.verbose: print (loopdev + ' has been setup as loop device of ' + args.FILE) ## get size in sectors of FILE and remove 512 sectors from the size. ## 512 sectors is from Truecrypt header (256 sectors at start of file) ## + backup header (256 sectors at end of file) evsize = int(subprocess.check_output(['blockdev', '--getsz', loopdev])) - 512 extevrange = evsize - 3 ## Define binary values for OEMs (VBR) for later test binMSDOS = str.encode('MSDOS') binMSWIN = str.encode('MSWIN') binEXFAT = str.encode('EXFAT') binNTFS = str.encode('NTFS ') binMKDOS = str.encode('mkdos') binIBM = str.encode('IBM ') binFREEDOS = str.encode('FreeD') binMKFS = str.encode('mkfs.') ## define binary values for Ext and HFS+ tests and setup flags for use after test ## set j=0 for all filesystems except HFS+ (changed later for HFS+) binExtSig = binascii.a2b_hex('53ef') bin000000 = binascii.a2b_hex('000000') binHFSJ = str.encode('H+') binHFSX = str.encode('HX') isExt = False isHFSP = False j = 0 ## if not cascaded encryption if len(args.MASTERKEY) == 128: crypts = [' aes-xts-plain64 ', ' serpent-xts-plain64 ', ' twofish-xts-plain64 ', ' camellia-xts-plain64 ', ' kuznyechik-xts-plain64 '] ## first check if normal/outer volume tryhiddenvol = False for crypt in crypts: ## create table entry for dmsetup command table = '"0 ' + str(evsize) + ' crypt' + crypt + args.MASTERKEY + ' 256 ' + loopdev + ' 256"' ## create dmsetup command ready to pass to shell, then pass it dmsetupcmd = 'dmsetup create ' + dmname + ' ' + ro + ' --table ' + table subprocess.call(dmsetupcmd, shell=True) ## test that the volume has decrypted correctly by reading (part of) the OEM from VBR test = open(dmslot, 'rb') test.seek(3) OEM = test.read(5) test.seek(1024) HFSPSig = test.read(2) test.seek(1080) ExtSig = test.read(2) test.seek(1097) ExtOS = test.read(3) test.seek(1120) FIARes = test.read(3) test.close() if ExtSig == binExtSig and ExtOS == bin000000: isExt = True elif HFSPSig == binHFSJ and FIARes == bin000000: isHFSP = True elif HFSPSig == binHFSX and FIARes == bin000000: isHFSP = True if OEM == binMSDOS or OEM == binMSWIN or OEM == binEXFAT or OEM == binNTFS or OEM == binMKDOS or OEM == binIBM or OEM == binFREEDOS or OEM == binMKFS or isExt or isHFSP: print('Normal/outer volume found in ' + args.FILE + ' using' + crypt) break ## if it hasn't worked remove device mapping else: rmdecfile = 'dmsetup remove ' + dmname subprocess.call(rmdecfile, shell=True) if crypt == ' kuznyechik-xts-plain64 ': ## if all encryption types have been tried then try hidden volumes tryhiddenvol = True if tryhiddenvol: print ('Masterkey does not decrypt a normal/outer volume. Trying for a hidden volume...') for crypt in crypts: ## create table entry for dmsetup command table = '"0 ' + str(evsize) + ' crypt' + crypt + args.MASTERKEY + ' 256 ' + loopdev + ' 256"' ## create dmsetup command ready to pass to shell, then pass it dmsetupcmd = 'dmsetup create ' + dmname + ' ' + ro + ' --table ' + table subprocess.call(dmsetupcmd, shell=True) ## search for OEM which indicates where hidden volume VBR is located within the container search = open(dmslot, 'rb') for i in range(evsize): ## provide the user with an update every 100,000 sectors if (i % 100000) == 0 : print('Scanning byte ' + str(i*512) + ' of ' + str(evsize*512) + ' using' + crypt, end=' \r') search.seek((i*512)+3) srchOEM = search.read(5) if i <= (extevrange): search.seek((i*512)+1024) srchHFSPSig = search.read(2) search.seek((i*512)+1080) srchExtSig = search.read(2) search.seek((i*512)+1097) srchExtOS = search.read(3) search.seek((i*512)+1120) srchFIARes = search.read(3) if srchExtSig == binExtSig and srchExtOS == bin000000: isExt = True elif srchHFSPSig == binHFSJ and srchFIARes == bin000000: isHFSP = True elif srchHFSPSig == binHFSX and srchFIARes == bin000000: isHFSP = True ## Linux HSF+ driver fails if backup header is not where expected ## so find backup header before attempting to mount... if isHFSP: print('HFS+ filesystem found. Searching for backup volume header... ') for j in range (evsize-i): search.seek((evsize - j)*512 - 1024) bckHFSPSig = search.read(2) search.seek((evsize - j)*512 - 928) bckFIARes = search.read(3) if bckHFSPSig == binHFSJ and bckFIARes == bin000000: break elif bckHFSPSig == binHFSX and bckFIARes == bin000000: break elif j == (evsize-i)-5: search.close() rmdmcmd = 'dmsetup remove ' + dmname subprocess.call(rmdmcmd, shell=True) if not isBLKDEV: subprocess.call(['losetup', '-d', loopdev]) print('Unable to find backup volume header. Is volume corrupted?') exit(1) if srchOEM == binMSDOS or srchOEM == binMSWIN or srchOEM == binEXFAT or srchOEM == binNTFS or srchOEM == binMKDOS or srchOEM == binIBM or srchOEM == binFREEDOS or srchOEM == binMKFS or isExt or isHFSP: search.close() print('Hidden volume found ' + str((i+256)*512) + ' bytes into ' + args.FILE + ' using' + crypt) rmdmcmd = 'dmsetup remove ' + dmname subprocess.call(rmdmcmd, shell=True) table = '"0 ' + str(evsize-(i+j)) + ' crypt' + crypt + args.MASTERKEY + ' ' + str(i+256) + ' ' + loopdev + ' ' + str(i+256) + '"' dmsetupcmd = 'dmsetup create ' + dmname + ' ' + ro + ' --table ' + table subprocess.call(dmsetupcmd, shell=True) break elif i == evsize-1: search.close() rmdmcmd = 'dmsetup remove ' + dmname subprocess.call(rmdmcmd, shell=True) if crypt == ' kuznyechik-xts-plain64 ': if not isBLKDEV: subprocess.call(['losetup', '-d', loopdev]) print('No volume decrypted in ' + args.FILE + '. Is masterkey correct?') exit(1) if srchOEM == binMSDOS or srchOEM == binMSWIN or srchOEM == binEXFAT or srchOEM == binNTFS or srchOEM == binMKDOS or srchOEM == binIBM or srchOEM == binFREEDOS or srchOEM == binMKFS or isExt or isHFSP: break ## if a 2 cascaded enryption type if len(args.MASTERKEY) == 256: ## split masterkey into 2 MK1 = args.MASTERKEY[128:] MK2 = args.MASTERKEY[:128] crypts = ['aes-twofish', 'camellia-kuznyechik', 'camellia-serpent', 'kuznyechik-aes', 'kuznyechik-twofish', 'serpent-aes', 'twofish-serpent'] tryhiddenvol = False ## first check for normal/outer volume for crypt in crypts: if crypt == 'aes-twofish': EN1 = ' aes-xts-plain64 ' EN2 = ' twofish-xts-plain64 ' elif crypt == 'camellia-kuznyechik': EN1 = ' camellia-xts-plain64 ' EN2 = ' kuznyechik-xts-plain64 ' elif crypt == 'camellia-serpent': EN1 = ' camellia-xts-plain64 ' EN2 = ' serpent-xts-plain64 ' elif crypt == 'kuznyechik-aes': EN1 = ' kuznyechik-xts-plain64 ' EN2 = ' aes-xts-plain64 ' elif crypt == 'kuznyechik-twofish': EN1 = ' kuznyechik-xts-plain64 ' EN2 = ' twofish-xts-plain64 ' elif crypt == 'serpent-aes': EN1 = ' serpent-xts-plain64 ' EN2 = ' aes-xts-plain64 ' elif crypt == 'twofish-serpent': EN1 = ' twofish-xts-plain64 ' EN2 = ' serpent-xts-plain64 ' table1 = '"0 ' + str(evsize) + ' crypt' + EN1 + MK1 + ' 256 ' + loopdev + ' 256"' table2 = '"0 ' + str(evsize) + ' crypt' + EN2 + MK2 + ' 256 ' + dmslot + '_1 0"' dmsetupcmd1 = 'dmsetup create ' + dmname + '_1 ' + ro + ' --table ' + table1 dmsetupcmd2 = 'dmsetup create ' + dmname + ' ' + ro + ' --table ' + table2 subprocess.call(dmsetupcmd1, shell=True) subprocess.call(dmsetupcmd2, shell=True) ## test that the volume has decrypted correctly by reading (part of) the OEM from VBR test = open(dmslot, 'rb') test.seek(3) OEM = test.read(5) test.seek(1024) HFSPSig = test.read(2) test.seek(1080) ExtSig = test.read(2) test.seek(1097) ExtOS = test.read(3) test.seek(1120) FIARes = test.read(3) test.close() if ExtSig == binExtSig and ExtOS == bin000000: isExt = True elif HFSPSig == binHFSJ and FIARes == bin000000: isHFSP = True elif HFSPSig == binHFSX and FIARes == bin000000: isHFSP = True if OEM == binMSDOS or OEM == binMSWIN or OEM == binEXFAT or OEM == binNTFS or OEM == binMKDOS or OEM == binIBM or OEM == binFREEDOS or OEM == binMKFS or isExt or isHFSP: print('Normal/outer volume found in '+ args.FILE + ' using' + EN1 + 'then' + EN2) break ## if it hasn't worked remove device mapping else: rmdecfile1 = 'dmsetup remove ' + dmname rmdecfile2 = 'dmsetup remove ' + dmname + '_1' subprocess.call(rmdecfile1, shell=True) subprocess.call(rmdecfile2, shell=True) ## if not normal volume check entire container for a hidden volume if crypt == 'twofish-serpent': tryhiddenvol = True if tryhiddenvol: print ('Masterkey does not decrypt a normal/outer volume. Trying for a hidden volume...') for crypt in crypts: if crypt == 'aes-twofish': EN1 = ' aes-xts-plain64 ' EN2 = ' twofish-xts-plain64 ' elif crypt == 'camellia-kuznyechik': EN1 = ' camellia-xts-plain64 ' EN2 = ' kuznyechik-xts-plain64 ' elif crypt == 'camellia-serpent': EN1 = ' camellia-xts-plain64 ' EN2 = ' serpent-xts-plain64 ' elif crypt == 'kuznyechik-aes': EN1 = ' kuznyechik-xts-plain64 ' EN2 = ' aes-xts-plain64 ' elif crypt == 'kuznyechik-twofish': EN1 = ' kuznyechik-xts-plain64 ' EN2 = ' twofish-xts-plain64 ' elif crypt == 'serpent-aes': EN1 = ' serpent-xts-plain64 ' EN2 = ' aes-xts-plain64 ' elif crypt == 'twofish-serpent': EN1 = ' twofish-xts-plain64 ' EN2 = ' serpent-xts-plain64 ' table1 = '"0 ' + str(evsize) + ' crypt' + EN1 + MK1 + ' 256 ' + loopdev + ' 256"' table2 = '"0 ' + str(evsize) + ' crypt' + EN2 + MK2 + ' 256 ' + dmslot + '_1 0"' dmsetupcmd1 = 'dmsetup create ' + dmname + '_1 ' + ro + ' --table ' + table1 dmsetupcmd2 = 'dmsetup create ' + dmname + ' ' + ro + ' --table ' + table2 subprocess.call(dmsetupcmd1, shell=True) subprocess.call(dmsetupcmd2, shell=True) ## search for OEM which indicates where hidden volume VBR is located within the container search = open(dmslot, 'rb') for i in range(evsize): ## provide the user with an update every 100,000 sectors if (i % 100000) == 0 : print('Scanning byte ' + str(i*512) + ' of ' + str(evsize*512) + ' using' + EN1 + 'then' + EN2, end=' \r') search.seek((i*512)+3) srchOEM = search.read(5) if i <= extevrange: search.seek((i*512)+1024) srchHFSPSig = search.read(2) search.seek((i*512)+1080) srchExtSig = search.read(2) search.seek((i*512)+1097) srchExtOS = search.read(3) search.seek((i*512)+1120) srchFIARes = search.read(3) if srchExtSig == binExtSig and srchExtOS == bin000000: isExt = True elif srchHFSPSig == binHFSJ and srchFIARes == bin000000: isHFSP = True elif srchHFSPSig == binHFSX and srchFIARes == bin000000: isHFSP = True ## Linux HSF+ driver fails if backup header is not where expected ## so find backup header before attempting to mount... if isHFSP: print('HFS+ filesystem found. Searching for backup volume header... ') for j in range (evsize-i): search.seek((evsize - j)*512 - 1024) bckHFSPSig = search.read(2) search.seek((evsize - j)*512 - 928) bckFIARes = search.read(3) if bckHFSPSig == binHFSJ and bckFIARes == bin000000: break elif bckHFSPSig == binHFSX and bckFIARes == bin000000: break elif j == (evsize-i)-5: search.close() rmdmcmd1 = 'dmsetup remove ' + dmname rmdmcmd2 = 'dmsetup remove ' + dmname + '_1' subprocess.call(rmdmcmd1, shell=True) subprocess.call(rmdmcmd2, shell=True) if not isBLKDEV: subprocess.call(['losetup', '-d', loopdev]) print('Unable to find backup volume header. Is volume corrupted?') exit(1) if srchOEM == binMSDOS or srchOEM == binMSWIN or srchOEM == binEXFAT or srchOEM == binNTFS or srchOEM == binMKDOS or srchOEM == binIBM or srchOEM == binFREEDOS or srchOEM == binMKFS or isExt or isHFSP: search.close() print('Hidden volume found ' + str((i+256)*512) + ' bytes into ' + args.FILE + ' using' + EN1 + 'then' + EN2 ) rmdmcmd1 = 'dmsetup remove ' + dmname rmdmcmd2 = 'dmsetup remove ' + dmname + '_1' subprocess.call(rmdmcmd1, shell=True) subprocess.call(rmdmcmd2, shell=True) table1 = '"0 ' + str(evsize-(i+j)) + ' crypt' + EN1 + MK1 + ' ' + str(i+256) + ' ' + loopdev + ' ' + str(i+256) + '"' table2 = '"0 ' + str(evsize-(i+j)) + ' crypt' + EN2 + MK2 + ' ' + str(i+256) + ' ' + dmslot + '_1 0"' dmsetupcmd1 = 'dmsetup create ' + dmname + '_1 ' + ro + ' --table ' + table1 dmsetupcmd2 = 'dmsetup create ' + dmname + ' ' + ro + ' --table ' + table2 subprocess.call(dmsetupcmd1, shell=True) subprocess.call(dmsetupcmd2, shell=True) break elif i == evsize-1: search.close() rmdmcmd1 = 'dmsetup remove ' + dmname rmdmcmd2 = 'dmsetup remove ' + dmname + '_1' subprocess.call(rmdmcmd1, shell=True) subprocess.call(rmdmcmd2, shell=True) if crypt == 'twofish-serpent': if not isBLKDEV: subprocess.call(['losetup', '-d', loopdev]) print('No volume decrypted in ' + args.FILE + '. Is masterkey correct?') exit(1) if srchOEM == binMSDOS or srchOEM == binMSWIN or srchOEM == binEXFAT or srchOEM == binNTFS or srchOEM == binMKDOS or srchOEM == binIBM or srchOEM == binFREEDOS or srchOEM == binMKFS or isExt or isHFSP: break ## if a 3 cascaded enryption type if len(args.MASTERKEY) == 384: ## split masterkeys into 3 MK1 = args.MASTERKEY[256:] MK2 = args.MASTERKEY[128:256] MK3 = args.MASTERKEY[:128] crypts = ['aes-twofish-serpent', 'kuznyechik-serpent-camellia', 'serpent-twofish-aes'] tryhiddenvol = False ## first check for normal/outer volume for crypt in crypts: if crypt == 'aes-twofish-serpent': EN1 = ' aes-xts-plain64 ' EN2 = ' twofish-xts-plain64 ' EN3 = ' serpent-xts-plain64 ' elif crypt == 'kuznyechik-serpent-camellia': EN1 = ' kuznyechik-xts-plain64 ' EN2 = ' serpent-xts-plain64 ' EN3 = ' camellia-xts-plain64 ' elif crypt == 'serpent-twofish-aes': EN1 = ' serpent-xts-plain64 ' EN2 = ' twofish-xts-plain64 ' EN3 = ' aes-xts-plain64 ' table1 = '"0 ' + str(evsize) + ' crypt' + EN1 + MK1 + ' 256 ' + loopdev + ' 256"' table2 = '"0 ' + str(evsize) + ' crypt' + EN2 + MK2 + ' 256 ' + dmslot + '_2 0"' table3 = '"0 ' + str(evsize) + ' crypt' + EN3 + MK3 + ' 256 ' + dmslot + '_1 0"' dmsetupcmd1 = 'dmsetup create ' + dmname + '_2 ' + ro + ' --table ' + table1 dmsetupcmd2 = 'dmsetup create ' + dmname + '_1 ' + ro + ' --table ' + table2 dmsetupcmd3 = 'dmsetup create ' + dmname + ' ' + ro + ' --table ' + table3 subprocess.call(dmsetupcmd1, shell=True) subprocess.call(dmsetupcmd2, shell=True) subprocess.call(dmsetupcmd3, shell=True) ## test that the volume has decrypted correctly by reading (part of) the OEM from VBR test = open(dmslot, 'rb') test.seek(3) OEM = test.read(5) test.seek(1024) HFSPSig = test.read(2) test.seek(1080) ExtSig = test.read(2) test.seek(1097) ExtOS = test.read(3) test.seek(1120) FIARes = test.read(3) test.close() if ExtSig == binExtSig and ExtOS == bin000000: isExt = True elif HFSPSig == binHFSJ and FIARes == bin000000: isHFSP = True elif HFSPSig == binHFSX and FIARes == bin000000: isHFSP = True if OEM == binMSDOS or OEM == binMSWIN or OEM == binEXFAT or OEM == binNTFS or OEM == binMKDOS or OEM == binIBM or OEM == binFREEDOS or OEM == binMKFS or isExt or isHFSP: print('Normal/outer volume found in ' + args.FILE + ' using' + EN1 + 'then' + EN2 + 'then' + EN3) break ## if it hasn't worked remove device mapping else: rmdecfile1 = 'dmsetup remove ' + dmname rmdecfile2 = 'dmsetup remove ' + dmname + '_1' rmdecfile3 = 'dmsetup remove ' + dmname + '_2' subprocess.call(rmdecfile1, shell=True) subprocess.call(rmdecfile2, shell=True) subprocess.call(rmdecfile3, shell=True) ## if not normal volume check entire container for a hidden volume if crypt == 'serpent-twofish-aes': tryhiddenvol = True if tryhiddenvol: print ('Masterkey does not decrypt a normal/outer volume. Trying for a hidden volume...') for crypt in crypts: if crypt == 'aes-twofish-serpent': EN1 = ' aes-xts-plain64 ' EN2 = ' twofish-xts-plain64 ' EN3 = ' serpent-xts-plain64 ' elif crypt == 'kuznyechik-serpent-camellia': EN1 = ' kuznyechik-xts-plain64 ' EN2 = ' serpent-xts-plain64 ' EN3 = ' camellia-xts-plain64 ' elif crypt == 'serpent-twofish-aes': EN1 = ' serpent-xts-plain64 ' EN2 = ' twofish-xts-plain64 ' EN3 = ' aes-xts-plain64 ' table1 = '"0 ' + str(evsize) + ' crypt' + EN1 + MK1 + ' 256 ' + loopdev + ' 256"' table2 = '"0 ' + str(evsize) + ' crypt' + EN2 + MK2 + ' 256 ' + dmslot + '_2 0"' table3 = '"0 ' + str(evsize) + ' crypt' + EN3 + MK3 + ' 256 ' + dmslot + '_1 0"' dmsetupcmd1 = 'dmsetup create ' + dmname + '_2 ' + ro + ' --table ' + table1 dmsetupcmd2 = 'dmsetup create ' + dmname + '_1 ' + ro + ' --table ' + table2 dmsetupcmd3 = 'dmsetup create ' + dmname + ' ' + ro + ' --table ' + table3 subprocess.call(dmsetupcmd1, shell=True) subprocess.call(dmsetupcmd2, shell=True) subprocess.call(dmsetupcmd3, shell=True) ## search truecrypthidden for OEM which indicates where hidden volume VBR is search = open(dmslot, 'rb') for i in range(evsize): ## provide the user with an update every 100,000 sectors if (i % 100000) == 0 : print('Scanning byte ' + str(i*512) + ' of ' + str(evsize*512) + ' using' + EN1 + 'then' + EN2 + 'then' + EN3, end=' \r') search.seek((i*512)+3) srchOEM = search.read(5) if i <= (extevrange): search.seek((i*512)+1024) srchHFSPSig = search.read(2) search.seek((i*512)+1080) srchExtSig = search.read(2) search.seek((i*512)+1097) srchExtOS = search.read(3) search.seek((i*512)+1120) srchFIARes = search.read(3) if srchExtSig == binExtSig and srchExtOS == bin000000: isExt = True elif srchHFSPSig == binHFSJ and srchFIARes == bin000000: isHFSP = True elif srchHFSPSig == binHFSX and srchFIARes == bin000000: isHFSP = True ## Linux HSF+ driver fails if backup header is not where expected ## so find backup header before attempting to mount... if isHFSP: print('HFS+ filesystem found. Searching for backup volume header... ') for j in range (evsize-i): search.seek((evsize - j)*512 - 1024) bckHFSPSig = search.read(2) search.seek((evsize - j)*512 - 928) bckFIARes = search.read(3) if bckHFSPSig == binHFSJ and bckFIARes == bin000000: break elif bckHFSPSig == binHFSX and bckFIARes == bin000000: break elif j == (evsize-i)-5: search.close() rmdmcmd1 = 'dmsetup remove ' + dmname rmdmcmd2 = 'dmsetup remove ' + dmname + '_1' rmdmcmd3 = 'dmsetup remove ' + dmname + '_2' subprocess.call(rmdmcmd1, shell=True) subprocess.call(rmdmcmd2, shell=True) subprocess.call(rmdmcmd3, shell=True) if not isBLKDEV: subprocess.call(['losetup', '-d', loopdev]) print('Unable to find backup volume header. Is volume corrupted?') exit(1) if srchOEM == binMSDOS or srchOEM == binMSWIN or srchOEM == binEXFAT or srchOEM == binNTFS or srchOEM == binMKDOS or srchOEM == binIBM or srchOEM == binFREEDOS or srchOEM == binMKFS or isExt or isHFSP: search.close() print('Hidden volume found ' + str((i+256)*512) + ' bytes into ' + args.FILE + ' using' + EN1 + 'then' + EN2 + 'then' + EN3) rmdmcmd1 = 'dmsetup remove ' + dmname rmdmcmd2 = 'dmsetup remove ' + dmname + '_1' rmdmcmd3 = 'dmsetup remove ' + dmname + '_2' subprocess.call(rmdmcmd1, shell=True) subprocess.call(rmdmcmd2, shell=True) subprocess.call(rmdmcmd3, shell=True) table1 = '"0 ' + str(evsize-(i+j)) + ' crypt' + EN1 + MK1 + ' ' + str(i+256) + ' ' + loopdev + ' ' + str(i+256) + '"' table2 = '"0 ' + str(evsize-(i+j)) + ' crypt' + EN2 + MK2 + ' ' + str(i+256) + ' ' + dmslot + '_2 0"' table3 = '"0 ' + str(evsize-(i+j)) + ' crypt' + EN3 + MK3 + ' ' + str(i+256) + ' ' + dmslot + '_1 0"' dmsetupcmd1 = 'dmsetup create ' + dmname + '_2 ' + ro + ' --table ' + table1 dmsetupcmd2 = 'dmsetup create ' + dmname + '_1 ' + ro + ' --table ' + table2 dmsetupcmd3 = 'dmsetup create ' + dmname + ' ' + ro + ' --table ' + table3 subprocess.call(dmsetupcmd1, shell=True) subprocess.call(dmsetupcmd2, shell=True) subprocess.call(dmsetupcmd3, shell=True) break elif i == evsize-1: search.close() rmdmcmd1 = 'dmsetup remove ' + dmname rmdmcmd2 = 'dmsetup remove ' + dmname + '_1' rmdmcmd3 = 'dmsetup remove ' + dmname + '_2' subprocess.call(rmdmcmd1, shell=True) subprocess.call(rmdmcmd2, shell=True) subprocess.call(rmdmcmd3, shell=True) if crypt == 'serpent-twofish-aes': if not isBLKDEV: subprocess.call(['losetup', '-d', loopdev]) print('No volume decrypted in ' + args.FILE + '. Is masterkey correct?') exit(1) if srchOEM == binMSDOS or srchOEM == binMSWIN or srchOEM == binEXFAT or srchOEM == binNTFS or srchOEM == binMKDOS or srchOEM == binIBM or srchOEM == binFREEDOS or srchOEM == binMKFS or isExt or isHFSP: break ## if requested, mount the decrypted volume if mp: mountcmd = 'mount ' + ro + ' ' + dmslot + ' ' + args.mountpoint subprocess.call(mountcmd, shell=True) print(args.FILE + ' has been decrypted at ' + dmslot + ' and mounted at ' + args.mountpoint) else: print(args.FILE + ' is decrypted at ' + dmslot) ## pause until user presses enter while also checking that ## mount and device mapping are no longer being used mount=True while mount: while mount: input('Once done, press Enter to dismount ' + args.FILE + '...') if mp: umountcmd = 'umount ' + dmslot check = subprocess.call(umountcmd, shell=True, stderr=subprocess.DEVNULL) if not check == 0: print(args.mountpoint + " is still in use!") break elif args.verbose: print("Unmounted from " + args.mountpoint) if len(args.MASTERKEY) >= 128: rmdmcmd = 'dmsetup remove ' + dmname check = subprocess.call(rmdmcmd, shell=True, stderr=subprocess.DEVNULL) if not check == 0: print("Device mapping: " + dmslot + " is still in use!") break else: if args.verbose: print("Removed device mapping: " + dmslot) if len(args.MASTERKEY) == 128: mount=False if len(args.MASTERKEY) >= 256: rmdmcmd = 'dmsetup remove ' + dmname + '_1' subprocess.call(rmdmcmd, shell=True, stderr=subprocess.DEVNULL) if len(args.MASTERKEY) == 256: mount=False if len(args.MASTERKEY) == 384: rmdmcmd = 'dmsetup remove ' + dmname + '_2' subprocess.call(rmdmcmd, shell=True, stderr=subprocess.DEVNULL) mount=False if not isBLKDEV: subprocess.call(['losetup', '-d', loopdev]) if args.verbose: print("Removed loop device: " + loopdev) if __name__ == '__main__': main()

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54a641444eb7e7d90e7bcdd09b05e094cbc229e2

2,163

py

Python

tests/test_connection.py

bureau14/qdb-api-python

2a010df3252d39bc4d529f545547c5cefb9fe86e

[ "BSD-3-Clause" ]

9

2015-09-02T20:13:13.000Z

2020-07-16T14:17:36.000Z

tests/test_connection.py

bureau14/qdb-api-python

2a010df3252d39bc4d529f545547c5cefb9fe86e

[ "BSD-3-Clause" ]

5

2018-02-20T10:47:02.000Z

2020-05-20T10:05:49.000Z

tests/test_connection.py

bureau14/qdb-api-python

2a010df3252d39bc4d529f545547c5cefb9fe86e

[ "BSD-3-Clause" ]

1

2018-04-01T11:12:56.000Z

# pylint: disable=C0103,C0111,C0302,W0212 import unittest import pytest import quasardb def test_connect_throws_input_error__when_uri_is_invalid(): with pytest.raises(quasardb.Error): quasardb.Cluster(uri='invalid_uri') def test_connect_throws_connection_error_when_no_cluster_on_given_uri(): with pytest.raises(quasardb.Error): quasardb.Cluster(uri='qdb://127.0.0.1:1') def test_connect_throws_connection_error_when_no_cluster_public_key( qdbd_settings): with pytest.raises(quasardb.Error): quasardb.Cluster( uri=qdbd_settings.get("uri").get("secure"), user_name=qdbd_settings.get("security").get("user_name"), user_private_key=qdbd_settings.get("security").get("user_private_key")) def test_connect_throws_connection_error_when_no_user_name(qdbd_settings): with pytest.raises(quasardb.Error): quasardb.Cluster( uri=qdbd_settings.get("uri").get("secure"), user_private_key=qdbd_settings.get( "security").get("user_private_key"), cluster_public_key=qdbd_settings.get("security").get("cluster_public_key")) def test_connect_throws_connection_error_when_no_user_private_key( qdbd_settings): with pytest.raises(quasardb.Error): quasardb.Cluster( uri=qdbd_settings.get("uri").get("secure"), user_name=qdbd_settings.get("security").get("user_name"), cluster_public_key=qdbd_settings.get("security").get("cluster_public_key")) def test_connect_ok_to_secure_cluster(qdbd_settings): quasardb.Cluster( uri=qdbd_settings.get("uri").get("secure"), user_name=qdbd_settings.get("security").get("user_name"), user_private_key=qdbd_settings.get("security").get("user_private_key"), cluster_public_key=qdbd_settings.get("security").get("cluster_public_key")) def test_connect_with_open_to_secure_cluster(qdbd_settings): with quasardb.Cluster(uri=qdbd_settings.get("uri").get("insecure")) as conn: topology = conn.node_topology( qdbd_settings.get('uri').get('insecure')) assert len(topology) > 0

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54aeb4d84ec0152af4725f5144f55305fddb5aad

166

py

Python

raspi_components/variable_resistor/resistor_errors.py

builderdev212/raspi_components

edbcb5b8eed6b1e4a2f1cc41ce08ea9b25051495

[ "MIT" ]

1

2021-11-09T16:29:45.000Z

raspi_components/variable_resistor/resistor_errors.py

builderdev212/raspi_components

edbcb5b8eed6b1e4a2f1cc41ce08ea9b25051495

[ "MIT" ]

null

raspi_components/variable_resistor/resistor_errors.py

builderdev212/raspi_components

edbcb5b8eed6b1e4a2f1cc41ce08ea9b25051495

[ "MIT" ]

null

class ResistorError(Exception): """ Raised when there is an error while working with the VariableResistor class. """ def __init__(self): pass

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5

54b7d521b6e8b2631e621d015681863d3d80e50c

1,292

py

Python

problem8.py

asuttles/euler

dfcacf7175e639c9a84ddd0e09a3de8f05ff4a23

[ "Unlicense" ]

null

problem8.py

asuttles/euler

dfcacf7175e639c9a84ddd0e09a3de8f05ff4a23

[ "Unlicense" ]

null

problem8.py

asuttles/euler

dfcacf7175e639c9a84ddd0e09a3de8f05ff4a23

[ "Unlicense" ]

null

numStr = """ 73167176531330624919225119674426574742355349194934 96983520312774506326239578318016984801869478851843 85861560789112949495459501737958331952853208805511 12540698747158523863050715693290963295227443043557 66896648950445244523161731856403098711121722383113 62229893423380308135336276614282806444486645238749 30358907296290491560440772390713810515859307960866 70172427121883998797908792274921901699720888093776 65727333001053367881220235421809751254540594752243 52584907711670556013604839586446706324415722155397 53697817977846174064955149290862569321978468622482 83972241375657056057490261407972968652414535100474 82166370484403199890008895243450658541227588666881 16427171479924442928230863465674813919123162824586 17866458359124566529476545682848912883142607690042 24219022671055626321111109370544217506941658960408 07198403850962455444362981230987879927244284909188 84580156166097919133875499200524063689912560717606 05886116467109405077541002256983155200055935729725 71636269561882670428252483600823257530420752963450""".replace('\n', '') maxProd = 0 for i in range(len(numStr)-13): prod = 1 for j in range(13): prod *= int(numStr[i+j]) if prod > maxProd: maxProd = prod print("The maximum product is: ", maxProd)

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54c0024080c3fe302e9d356ca747094f607c5587

164

py

Python

python/testData/inspections/PyUnresolvedReferencesInspection3K/NamespacePackageRedundantUnion/a.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

2

2018-12-29T09:53:39.000Z

2018-12-29T09:53:42.000Z

python/testData/inspections/PyUnresolvedReferencesInspection3K/NamespacePackageRedundantUnion/a.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/inspections/PyUnresolvedReferencesInspection3K/NamespacePackageRedundantUnion/a.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

1

2019-10-12T22:37:24.000Z

<warning descr="Unused import statement">from nspkg1 import <error descr="Cannot find reference 'not_found' in 'imported module nspkg1'">not_found</error></warning>

164

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null

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1

0

5

54c0c58f6c3108e04bcf42887a86fa7d0b7a7e08

3,411

py

Python

4-Object_Detection/RPN/backend.py

anandpaiv/TensorFlow2.0-Examples

f62a9b81ff00e697c7bd810273958b2226baa860

[ "MIT" ]

null

4-Object_Detection/RPN/backend.py

anandpaiv/TensorFlow2.0-Examples

f62a9b81ff00e697c7bd810273958b2226baa860

[ "MIT" ]

null

4-Object_Detection/RPN/backend.py

anandpaiv/TensorFlow2.0-Examples

f62a9b81ff00e697c7bd810273958b2226baa860

[ "MIT" ]

1

2019-10-05T16:38:16.000Z

#! /usr/bin/env python # coding=utf-8 #================================================================ # Copyright (C) 2019 * Ltd. All rights reserved. # # Editor : VIM # File name : backend.py # Author : YunYang1994 # Created date: 2019-07-16 00:24:11 # Description : # #================================================================ import numpy as np import tensorflow as tf weights = np.load("./vgg16.npy", encoding='latin1').item() inputs = tf.keras.layers.Input([224, 224, 3]) # Block 1 conv1_1 = tf.keras.layers.Conv2D(filters=64, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv1_1')(inputs) conv1_2 = tf.keras.layers.Conv2D(filters=64, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv1_2')(conv1_1) pool1_1 = tf.nn.max_pool(conv1_2, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME', name='pool1_1') # Block 2 conv2_1 = tf.keras.layers.Conv2D(filters=128, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv2_1')(pool1_1) conv2_2 = tf.keras.layers.Conv2D(filters=128, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv2_2')(conv2_1) pool2_1 = tf.nn.max_pool(conv2_2, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME', name='pool2_1') # Block 3 conv3_1 = tf.keras.layers.Conv2D(filters=256, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv3_1')(pool2_1) conv3_2 = tf.keras.layers.Conv2D(filters=256, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv3_2')(conv3_1) conv3_3 = tf.keras.layers.Conv2D(filters=256, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv3_3')(conv3_2) pool3_1 = tf.nn.max_pool(conv3_3, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME', name='pool3_1') # Block 4 conv4_1 = tf.keras.layers.Conv2D(filters=512, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv4_1')(pool3_1) conv4_2 = tf.keras.layers.Conv2D(filters=512, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv4_2')(conv4_1) conv4_3 = tf.keras.layers.Conv2D(filters=512, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv4_3')(conv4_2) pool4_1 = tf.nn.max_pool(conv4_3, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME', name='pool4_1') # Block 5 conv5_1 = tf.keras.layers.Conv2D(filters=512, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv5_1')(pool4_1) conv5_2 = tf.keras.layers.Conv2D(filters=512, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv5_2')(conv5_1) conv5_3 = tf.keras.layers.Conv2D(filters=512, kernel_size=3, strides=[1, 1], padding='same', activation='relu', use_bias=True, name='conv5_3')(conv5_2) model = tf.keras.Model(inputs, conv)

47.375

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0.593668

500

3,411

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0.17

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0.126992

0.732648

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3,411

71

108

48.042254

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0

0.057143

0

null

0

1

0

null

0

5

49c9133e250d775b590a619a074eab228b169edc

418

py

Python

paymaster/exceptions.py

IDilettant/paymaster_

d48549c714aa08876aadf3dc7f3456e47d581938

[ "MIT" ]

1

2021-12-12T09:49:23.000Z

paymaster/exceptions.py

IDilettant/paymaster_

d48549c714aa08876aadf3dc7f3456e47d581938

[ "MIT" ]

1

2021-11-29T18:15:09.000Z

2021-12-08T17:13:55.000Z

paymaster/exceptions.py

IDilettant/paymaster

d48549c714aa08876aadf3dc7f3456e47d581938

[ "MIT" ]

null

"""Exceptions module.""" class PaymasterException(Exception): """Base app exception.""" pass class AccountError(PaymasterException): """Exception of no account in database.""" pass class CurrencyError(PaymasterException): """Exception of no currency in currencies table.""" pass class BalanceValueError(PaymasterException): """Exception of negative account balance.""" pass

16.076923

55

0.698565

39

418

7.487179

0.538462

0.369863

0.297945

0.212329

0

0.188995

418

25

56

16.72

0.861357

0.382775

0

0.5

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true

0.5

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0.5

0

null

1

0

null

0

1

0

5

49d736ef1460d3cb4343de30155638ff7d197537

6,531

py

Python

cpp_src/cmd/reindexer_server/test/specs/queries_test.py

radiophysicist/reindexer

5a6e82158665f6e9c78536cc4a907143a157f1d7

[ "Apache-2.0" ]

null

cpp_src/cmd/reindexer_server/test/specs/queries_test.py

radiophysicist/reindexer

5a6e82158665f6e9c78536cc4a907143a157f1d7

[ "Apache-2.0" ]

null

cpp_src/cmd/reindexer_server/test/specs/queries_test.py

radiophysicist/reindexer

5a6e82158665f6e9c78536cc4a907143a157f1d7

[ "Apache-2.0" ]

null

import random from specs import BaseTest class QueriesTest(BaseTest): def setUp(self): super().setUp() self.helper_queries_testdata_prepare() def test_query_sql(self): """Should be able to execute an sql query""" sql_query = 'SELECT COUNT(*),* FROM ' + self.current_ns status, body = self.api_sql_exec(self.current_db, sql_query) self.assertEqual(True, status == self.API_STATUS['success'], body) self.assertEqual(True, 'items' in body, body) self.assertEqual(True, 'query_total_items' in body, body) def test_query_sql_post(self): """Should be able to post an sql query""" query_body = 'SELECT COUNT(*),* FROM ' + self.current_ns status, body = self.api_sql_post(self.current_db, query_body) self.assertEqual(True, status == self.API_STATUS['success'], body) self.assertEqual(True, 'items' in body, body) self.assertEqual(True, 'query_total_items' in body, body) def test_query_dsl_(self): """Should be able to exec a dsl query""" query_dsl = self.helper_query_dsl_construct(self.current_ns) status, body = self.api_query_dsl(self.current_db, query_dsl) self.assertEqual(True, status == self.API_STATUS['success'], body) self.assertEqual(True, 'items' in body, body) def test_query_dsl_sort_asc(self): """Should be able to exec a dsl query and get asc-sorted item list""" sort_field = self.helper_items_first_key_of_item(self.items) sort_desc = False sort = self.helper_query_dsl_sort_construct(sort_field, sort_desc) query_dsl = self.helper_query_dsl_construct(self.current_ns, sort=sort) status, body = self.api_query_dsl(self.current_db, query_dsl) self.assertEqual(True, status == self.API_STATUS['success'], body) self.assertEqual(True, 'items' in body, body) self.assertEqual(True, body['items'][0][sort_field] < body['items'][-1][sort_field], body) def test_query_dsl_sort_desc(self): """Should be able to exec a dsl query and get desc-sorted item list""" sort_field = self.helper_items_first_key_of_item(self.items) sort_desc = True sort = self.helper_query_dsl_sort_construct(sort_field, sort_desc) query_dsl = self.helper_query_dsl_construct(self.current_ns, sort=sort) status, body = self.api_query_dsl(self.current_db, query_dsl) self.assertEqual(True, status == self.API_STATUS['success'], body) self.assertEqual(True, 'items' in body, body) self.assertEqual(True, body['items'][0][sort_field] > body['items'][-1][sort_field], body) def test_query_dsl_distinct(self): """Should be able to exec a dsl query and get distinct item list""" status, body = self.api_get_items(self.current_db, self.current_ns) self.assertEqual(True, status == self.API_STATUS['success'], body) total_items = body['total_items'] items = [] items_count = 10 distinct_field_value_random = random.randint(0x1FFFFFFF, 0x7FFFFFFF) items = self.helper_item_array_construct(items_count) pk_field_name = self.helper_items_first_key_of_item(items) test_field_name = self.helper_items_second_key_of_item(items) for i in range(0, items_count): items[i][pk_field_name] = i + 1000 items[i][test_field_name] = distinct_field_value_random for item_body in items: status, body = self.api_create_item( self.current_db, self.current_ns, item_body) self.assertEqual(True, status == self.API_STATUS['success'], body) distinct = self.helper_items_second_key_of_item(items) limit = total_items + items_count query_dsl = self.helper_query_dsl_construct( self.current_ns, distinct=distinct, limit=limit,req_total="enabled") status, body = self.api_query_dsl(self.current_db, query_dsl) self.assertEqual(True, status == self.API_STATUS['success'], body) self.assertEqual(True, 'items' in body, body) self.assertEqual(True, 'query_total_items' in body, body) self.assertEqual( True, body['query_total_items'] == total_items + 1, body) def test_query_dsl_paginate(self): """Should be able to exec a dsl query and pagination works correct""" items = [] items_count = 10 items = self.helper_item_array_construct(items_count) pk_field_name = self.helper_items_first_key_of_item(items) for i in range(0, items_count): items[i][pk_field_name] = i + 1000 limit = 1 offset = self.items_count - 1 query_dsl = self.helper_query_dsl_construct( self.current_ns, limit=limit, offset=offset) status, body = self.api_query_dsl(self.current_db, query_dsl) self.assertEqual(True, status == self.API_STATUS['success'], body) self.assertEqual(True, 'items' in body, body) self.assertEqual(True, self.items[-1] in body['items'], body) self.assertEqual(True, len(body['items']) == 1, body) def test_query_dsl_total(self): """Should be able to exec a dsl query and get total_items""" query_dsl = self.helper_query_dsl_construct( self.current_ns, req_total='enabled') status, body = self.api_query_dsl(self.current_db, query_dsl) self.assertEqual(True, status == self.API_STATUS['success'], body) self.assertEqual(True, 'items' in body, body) self.assertEqual(True, 'query_total_items' in body, body) self.assertEqual(True, body['query_total_items'] == self.items_count, body) def test_query_dsl_filter_eq(self): """Should be able to exec a dsl query with EQ filter""" test_field_name = self.helper_items_second_key_of_item(self.items) test_value = 2 filter = self.helper_query_dsl_filter_construct( test_field_name, 'EQ', 'AND', test_value) filters = [] filters.append(filter) query_dsl = self.helper_query_dsl_construct( self.current_ns, filters=filters) status, body = self.api_query_dsl(self.current_db, query_dsl) self.assertEqual(True, status == self.API_STATUS['success'], body) self.assertEqual(True, 'items' in body, body) self.assertEqual(True, self.items[0] in body['items'], body)

39.823171

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4.548495

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0.07451

0.144363

0.12402

0.785539

0.769853

0.755147

0.742892

0.729902

0.702696

0

0.005767

0.22998

6,531

163

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40.067485

0.805528

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0.28972

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0.093458

false

0

0.018692

0

0.121495

0

null

0

1

0

null

0

5

49e6f82b2e8558b09aa633afaae5b29f72680ff3

165

py

Python

multigrids/__init__.py

rwspicer/multigrids

e4f18144f0e95fbf7da8e17ad2fcc2428763ce35

[ "MIT" ]

null

multigrids/__init__.py

rwspicer/multigrids

e4f18144f0e95fbf7da8e17ad2fcc2428763ce35

[ "MIT" ]

4

2021-11-02T21:09:58.000Z

2022-02-09T01:33:32.000Z

multigrids/__init__.py

rwspicer/multigrids

e4f18144f0e95fbf7da8e17ad2fcc2428763ce35

[ "MIT" ]

1

2020-06-22T20:39:04.000Z

from .__metadata__ import * from .multigrid import MultiGrid from .temporal import TemporalMultiGrid from .grid import Grid from .temporal_grid import TemporalGrid

23.571429

39

0.836364

20

165

6.65

0.4

0.180451

0

0.127273

165

6

40

27.5

0.923611

0

1

0

true

0

1

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1

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null

0

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null

0

1

0

1

0

1

0

5

b71ac3443df007ad8d892c3d528ccd7f09cba4b7

10,413

py

Python

test/test.py

SlavaSereb/fireblocks-key-recovery-tool

c17fc1ed6a58a3b987a5b082254978469a9d702e

[ "MIT" ]

2

2019-07-09T16:13:35.000Z

2021-01-28T14:13:31.000Z

test/test.py

SlavaSereb/fireblocks-key-recovery-tool

c17fc1ed6a58a3b987a5b082254978469a9d702e

[ "MIT" ]

1

2020-12-01T05:51:40.000Z

2020-12-01T05:54:14.000Z

test/test.py

SlavaSereb/fireblocks-key-recovery-tool

c17fc1ed6a58a3b987a5b082254978469a9d702e

[ "MIT" ]

6

2019-11-12T11:52:31.000Z

2021-03-15T14:20:26.000Z

import pytest import sys sys.path.append("..") from utils import recover def test_recovery(): result = recover.restore_key_and_chaincode("backup.zip", "priv.pem", "Thefireblocks1!") ecdsa_priv_key, ecdsa_chaincode = result['MPC_ECDSA_SECP256K1'] assert(ecdsa_priv_key == 0x473d1820ca4bf7cf6b018a8520b1ec0849cb99bce4fff45c5598723f67b3bd52) pub = recover.get_public_key("MPC_ECDSA_SECP256K1", ecdsa_priv_key) assert(pub == "021d84f3b6d7c6888f81c7cc381b658d85319f27e1ea9c93dff128667fb4b82ba0") assert(recover.encode_extended_key('MPC_ECDSA_SECP256K1', ecdsa_priv_key, ecdsa_chaincode, False) == "xprv9s21ZrQH143K24Mfq5zL5MhWK9hUhhGbd45hLXo2Pq2oqzMMo63oStZzF9aunJDs4SsrmoxycAo6xxBTHawSz5sYxEy8TpCkv66Sci373DJ") assert(recover.encode_extended_key('MPC_ECDSA_SECP256K1', pub, ecdsa_chaincode, True) == "xpub661MyMwAqRbcEYS8w7XLSVeEsBXy79zSzH1J8vCdxAZningWLdN3zgtU6QJJZSgiCXT6sq7wa2jCk5t4Vv1r1E4q1venKghAAdyzieufGyX") print("recovery OK") def test_full_recovery(): result = recover.restore_key_and_chaincode("backup_new.zip", "priv2.pem", "Thefireblocks1!") ecdsa_priv_key, ecdsa_chaincode = result['MPC_ECDSA_SECP256K1'] eddsa_priv_key, eddsa_chaincode = result['MPC_EDDSA_ED25519'] assert(ecdsa_priv_key == 0x66b1baf063db6e7152480334ebab0ab098e85f682b784754e46c18c962a1aa9d) assert(eddsa_priv_key == 0xd74820d02cc2aa09e2d0bcb36aeb92625b3d92c8d202063eab5513fd4453a44) assert(ecdsa_chaincode == bytes.fromhex('5d90bd21d2273a25d0aea082716bdc4529e007823260ad3479182f6672c25cc4')) assert(eddsa_chaincode == bytes.fromhex('5d90bd21d2273a25d0aea082716bdc4529e007823260ad3479182f6672c25cc4')) pub = recover.get_public_key("MPC_ECDSA_SECP256K1", ecdsa_priv_key) assert(pub == "02e0bf609d7ced9c49e9f4c1d1df0142bb95eb622fa617a9f7280fa23b7f013dc6") assert(recover.encode_extended_key('MPC_ECDSA_SECP256K1', ecdsa_priv_key, ecdsa_chaincode, False) == "xprv9s21ZrQH143K2zPNSbKDKusTNW4XVwvTCCEFvcLkeNyauqJJd9UjZg3AtfZbmXa22TFph2NdACUPoWR4sCqMCKQM1j7jRvLuBCF3YoapsX6") assert(recover.encode_extended_key('MPC_ECDSA_SECP256K1', pub, ecdsa_chaincode, True) == "xpub661MyMwAqRbcFUTqYcrDh3pBvXu1uQeJZR9rizkNCiWZnddTAgnz7UMejwX7u4xLmh2JMTtL7DdZmBWGUKa7v836UarassQ3DVFATMzRycV") pub = recover.get_public_key("MPC_EDDSA_ED25519", eddsa_priv_key) assert(pub == "0050cfee85dabebed78f43e94a1b7afd13c20461ad66efa083779bdeffd22269d9") assert(recover.encode_extended_key('MPC_EDDSA_ED25519', eddsa_priv_key, eddsa_chaincode, False) == "fprv4LsXPWzhTTp9ax8NGVwbnRFuT3avVQ4ydHNWcu8hCGZd18TRKxgAzbrpY9bLJRe4Y2AyX9TfQdDPbmqEYoDCTju9QFZbUgdsxsmUgfvuEDK") assert(recover.encode_extended_key('MPC_EDDSA_ED25519', pub, eddsa_chaincode, True) == "fpub8sZZXw2wbqVpURAAA9cCBpv2256rejFtCayHuRAzcYN1qciBxMVmB6UgiDAQTUZh5EP9JZciPQPjKAHyqPYHELqEHWkvo1sxreEJgLyfCJj") print("recovery OK") def test_recovery_old_format(): result = recover.restore_key_and_chaincode("backup_old_format.zip", "priv.pem", "Thefireblocks1!") ecdsa_priv_key, ecdsa_chaincode = result['MPC_ECDSA_SECP256K1'] assert(ecdsa_priv_key == 0x473d1820ca4bf7cf6b018a8520b1ec0849cb99bce4fff45c5598723f67b3bd52) pub = recover.get_public_key("MPC_ECDSA_SECP256K1", ecdsa_priv_key) assert(pub == "021d84f3b6d7c6888f81c7cc381b658d85319f27e1ea9c93dff128667fb4b82ba0") assert(recover.encode_extended_key('MPC_ECDSA_SECP256K1', ecdsa_priv_key, ecdsa_chaincode, False) == "xprv9s21ZrQH143K24Mfq5zL5MhWK9hUhhGbd45hLXo2Pq2oqzMMo63oStZzF9aunJDs4SsrmoxycAo6xxBTHawSz5sYxEy8TpCkv66Sci373DJ") assert(recover.encode_extended_key('MPC_ECDSA_SECP256K1', pub, ecdsa_chaincode, True) == "xpub661MyMwAqRbcEYS8w7XLSVeEsBXy79zSzH1J8vCdxAZningWLdN3zgtU6QJJZSgiCXT6sq7wa2jCk5t4Vv1r1E4q1venKghAAdyzieufGyX") print("recovery (old format) OK") def test_cmp_recovery(): result = recover.restore_key_and_chaincode("backup_cmp.zip", "priv.pem", "Fireblocks1!") ecdsa_priv_key, ecdsa_chaincode = result['MPC_CMP_ECDSA_SECP256K1'] eddsa_priv_key, eddsa_chaincode = result['MPC_CMP_EDDSA_ED25519'] assert(ecdsa_priv_key == 0xf57c18e98a24ca0b36fbbd103233aff128b740426da189ce208545d44bbad050) assert(eddsa_priv_key == 0xa536dc2f2d744ae78eb26fdfb4b9e234a649525e0a1142bf900cd9c26987007) pub = recover.get_public_key("MPC_CMP_ECDSA_SECP256K1", ecdsa_priv_key) assert(pub == "03321ad97aea16624280b83e1c1b36bb9cb293cac84925fe5fcf956386cd063fec") assert(recover.encode_extended_key('MPC_CMP_ECDSA_SECP256K1', ecdsa_priv_key, ecdsa_chaincode, False) == "xprv9s21ZrQH143K3PhnQQqPZm38HtkJ3bjcVmwc1SfGG8ddw3jXtrhSBNFNcVVx7VUL8vPpmMg1dqxhecVq8WJ1VHn9yoeRM88qfYEnEEi6XaQ") assert(recover.encode_extended_key('MPC_CMP_ECDSA_SECP256K1', pub, ecdsa_chaincode, True) == "xpub661MyMwAqRbcFsnFWSNPvtyrqvanT4TTrzsCoq4spUAcor4gSQ1gjAZrTkzR1o8XZ5uPq6WELaga3Zh1eJyfXLvfkWTfV7AjdFU5VuWMpPp") pub = recover.get_public_key("MPC_CMP_EDDSA_ED25519", eddsa_priv_key) assert(pub == "00701c977bd4d2038328dd8154c147f9d40225fc8e9fd98c010cc968ea8fabb362") assert(recover.encode_extended_key('MPC_CMP_EDDSA_ED25519', eddsa_priv_key, eddsa_chaincode, False) == "fprv4LsXPWzhTTp9bMSnEKTn2GRaNSGh33t8vs5rhjTCp2Dg2LtebftscJ52FxRRKeHGLfK6X5Lg3LcsGxQyHZ8ovvPsP2s9PLbZC2VFHc64vFH") assert(recover.encode_extended_key('MPC_CMP_EDDSA_ED25519', pub, eddsa_chaincode, True) == "fpub8sZZXw2wbqVpUpUa7y8NRg5gwTndCP53WAgdzFVWEJ24rq9RE4iTnngtS2FeusezUsAJb2sZiMvSDqYGeGVSs65wJqYcGzQRuZGM9NHHqog") print("cmp recovery OK") def test_one_custom_chaincode_recovery(): ''' The zip in this test was built from 'backup_new.zip', the file used in test_full_recovery() The only change is in an alternative chain code assigned specifically to MPC_ECDSA_SECP256K1, while MPC_EDDSA_ED25519 is not assigned a specific chaincode. Hence all the extracted keys are they same, and differce lies mostly in the extended form of the key, which encodes the chaincode. ''' result = recover.restore_key_and_chaincode("backup_with_one_custom_chaincode.zip", "priv2.pem", "Thefireblocks1!") ecdsa_priv_key, ecdsa_chaincode = result['MPC_ECDSA_SECP256K1'] eddsa_priv_key, eddsa_chaincode = result['MPC_EDDSA_ED25519'] assert(ecdsa_chaincode != eddsa_chaincode) assert(ecdsa_priv_key == 0x66b1baf063db6e7152480334ebab0ab098e85f682b784754e46c18c962a1aa9d) assert(eddsa_priv_key == 0xd74820d02cc2aa09e2d0bcb36aeb92625b3d92c8d202063eab5513fd4453a44) assert(ecdsa_chaincode == bytes.fromhex('865b4d6e745c64afc98a7fe32103d6ea775910d4d58e00fe17d2fdd4f8f8f1d0')) assert(eddsa_chaincode == bytes.fromhex('5d90bd21d2273a25d0aea082716bdc4529e007823260ad3479182f6672c25cc4')) pub = recover.get_public_key("MPC_ECDSA_SECP256K1", ecdsa_priv_key) assert(recover.encode_extended_key('MPC_ECDSA_SECP256K1', ecdsa_priv_key, ecdsa_chaincode, False) == "xprv9s21ZrQH143K3PwZ9jrXG7MZXgj92u6eeCz6M8w8a5RGYJoNmWQRA2eso47rJHr9qawKR9tQVTRki8XUPwVSuBPSnVxT6mQb99XUbruDGk7") assert(recover.encode_extended_key('MPC_ECDSA_SECP256K1', pub, ecdsa_chaincode, True) == "xpub661MyMwAqRbcFt22FmPXdFJJ5iZdSMpW1Ruh9XLk8QxFR78XK3ifhpyMeL5NRqEUapho5bQ7SUavfocg14EDcz2CFMhJYiTjBSXbWQcdkrR") pub = recover.get_public_key("MPC_EDDSA_ED25519", eddsa_priv_key) assert(pub == "0050cfee85dabebed78f43e94a1b7afd13c20461ad66efa083779bdeffd22269d9") assert(recover.encode_extended_key('MPC_EDDSA_ED25519', eddsa_priv_key, eddsa_chaincode, False) == "fprv4LsXPWzhTTp9ax8NGVwbnRFuT3avVQ4ydHNWcu8hCGZd18TRKxgAzbrpY9bLJRe4Y2AyX9TfQdDPbmqEYoDCTju9QFZbUgdsxsmUgfvuEDK") assert(recover.encode_extended_key('MPC_EDDSA_ED25519', pub, eddsa_chaincode, True) == "fpub8sZZXw2wbqVpURAAA9cCBpv2256rejFtCayHuRAzcYN1qciBxMVmB6UgiDAQTUZh5EP9JZciPQPjKAHyqPYHELqEHWkvo1sxreEJgLyfCJj") print("recovery OK") def test_two_custom_chaincode_recovery(): ''' The zip in this test was built from 'backup_new.zip', the file used in test_full_recovery() The only changes are two different chain code assigned specifically to MPC_ECDSA_SECP256K1 and MPC_EDDSA_ED25519. The chaincode assigned to MPC_ECDSA_SECP256K1 is the same as the one in 'backup_with_one_custom_chaincode.zip', the file used in test_one_custom_chaincode_recovery() Hence all the extracted keys are they same: only the extended forms of the keys are different, as they encode the respective chaincodes. ''' result = recover.restore_key_and_chaincode("backup_with_two_custom_chaincode.zip", "priv2.pem", "Thefireblocks1!") ecdsa_priv_key, ecdsa_chaincode = result['MPC_ECDSA_SECP256K1'] eddsa_priv_key, eddsa_chaincode = result['MPC_EDDSA_ED25519'] assert(ecdsa_chaincode != eddsa_chaincode) assert(ecdsa_priv_key == 0x66b1baf063db6e7152480334ebab0ab098e85f682b784754e46c18c962a1aa9d) assert(eddsa_priv_key == 0xd74820d02cc2aa09e2d0bcb36aeb92625b3d92c8d202063eab5513fd4453a44) assert(ecdsa_chaincode == bytes.fromhex('865b4d6e745c64afc98a7fe32103d6ea775910d4d58e00fe17d2fdd4f8f8f1d0')) assert(eddsa_chaincode == bytes.fromhex('89b11d04462618fa6d3981f891f2ae8968d8762f268fdec0a4c440ecafb072dd')) pub = recover.get_public_key("MPC_ECDSA_SECP256K1", ecdsa_priv_key) assert(recover.encode_extended_key('MPC_ECDSA_SECP256K1', ecdsa_priv_key, ecdsa_chaincode, False) == "xprv9s21ZrQH143K3PwZ9jrXG7MZXgj92u6eeCz6M8w8a5RGYJoNmWQRA2eso47rJHr9qawKR9tQVTRki8XUPwVSuBPSnVxT6mQb99XUbruDGk7") assert(recover.encode_extended_key('MPC_ECDSA_SECP256K1', pub, ecdsa_chaincode, True) == "xpub661MyMwAqRbcFt22FmPXdFJJ5iZdSMpW1Ruh9XLk8QxFR78XK3ifhpyMeL5NRqEUapho5bQ7SUavfocg14EDcz2CFMhJYiTjBSXbWQcdkrR") pub = recover.get_public_key("MPC_EDDSA_ED25519", eddsa_priv_key) assert(pub == "0050cfee85dabebed78f43e94a1b7afd13c20461ad66efa083779bdeffd22269d9") assert(recover.encode_extended_key('MPC_EDDSA_ED25519', eddsa_priv_key, eddsa_chaincode, False) == "fprv4LsXPWzhTTp9bPcFjmqM7U4drbDYRi1YzzFgrfnWAH3hsnLWeJioBzvyvwYJ5p5SuXjwhVd41wrB3tR1Ep41U2DpkJM3J9JGkuCKiBAyyGz") assert(recover.encode_extended_key('MPC_EDDSA_ED25519', pub, eddsa_chaincode, True) == "fpub8sZZXw2wbqVpUre3dRVwWsikRcjUb3CTaHrU9BpoaYr6iGbHGhYPNVYr717NEs15Sjx7Uun6zj2WmGskXQP6Ed9udZYNcUYMeff9hsYTcyr") print("recovery OK") if __name__ == '__main__': test_recovery() test_full_recovery() test_recovery_old_format() test_cmp_recovery() test_one_custom_chaincode_recovery() test_two_custom_chaincode_recovery()

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b73780eef2bf48771afe9fa2a602e87a5fc44603

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py

Python

ooi_instrument_agent/test/responses.py

oceanobservatories/ooi-instrument-agent

e22e4300079468bb99c543cbbf1cb5c8b4a96897

[ "Apache-2.0" ]

null

ooi_instrument_agent/test/responses.py

oceanobservatories/ooi-instrument-agent

e22e4300079468bb99c543cbbf1cb5c8b4a96897

[ "Apache-2.0" ]

null

ooi_instrument_agent/test/responses.py

oceanobservatories/ooi-instrument-agent

e22e4300079468bb99c543cbbf1cb5c8b4a96897

[ "Apache-2.0" ]

null

health_response = '''[ { "Checks": [ { "CheckID": "service:instrument_driver_RS10ENGC-XX00X-00-SPKIRA001", "Name": "Service 'instrument_driver' check", "Node": "uft21", "Notes": "", "Output": "", "ServiceID": "instrument_driver_RS10ENGC-XX00X-00-SPKIRA001", "ServiceName": "instrument_driver", "Status": "passing" }, { "CheckID": "serfHealth", "Name": "Serf Health Status", "Node": "uft21", "Notes": "", "Output": "Agent alive and reachable", "ServiceID": "", "ServiceName": "", "Status": "passing" } ], "Node": { "Address": "128.6.240.39", "Node": "uft21" }, "Service": { "Address": "", "ID": "instrument_driver_RS10ENGC-XX00X-00-SPKIRA001", "Port": 42558, "Service": "instrument_driver", "Tags": [ "RS10ENGC-XX00X-00-SPKIRA001" ] } }, { "Checks": [ { "CheckID": "service:instrument_driver_RS10ENGC-XX00X-00-TMPSFA001", "Name": "Service 'instrument_driver' check", "Node": "uft21", "Notes": "", "Output": "", "ServiceID": "instrument_driver_RS10ENGC-XX00X-00-TMPSFA001", "ServiceName": "instrument_driver", "Status": "passing" }, { "CheckID": "serfHealth", "Name": "Serf Health Status", "Node": "uft21", "Notes": "", "Output": "Agent alive and reachable", "ServiceID": "", "ServiceName": "", "Status": "passing" } ], "Node": { "Address": "128.6.240.39", "Node": "uft21" }, "Service": { "Address": "", "ID": "instrument_driver_RS10ENGC-XX00X-00-TMPSFA001", "Port": 41799, "Service": "instrument_driver", "Tags": [ "RS10ENGC-XX00X-00-TMPSFA001" ] } } ]''' port_agent_response = '''[ { "Checks": [ { "CheckID": "service:port-agent-RS10ENGC-XX00X-00-BOTPTA001", "Name": "Service 'port-agent' check", "Node": "uft21", "Notes": "", "Output": "", "ServiceID": "port-agent-RS10ENGC-XX00X-00-BOTPTA001", "ServiceName": "port-agent", "Status": "passing" }, { "CheckID": "serfHealth", "Name": "Serf Health Status", "Node": "uft21", "Notes": "", "Output": "Agent alive and reachable", "ServiceID": "", "ServiceName": "", "Status": "passing" } ], "Node": { "Address": "128.6.240.39", "Node": "uft21" }, "Service": { "Address": "", "ID": "port-agent-RS10ENGC-XX00X-00-BOTPTA001", "Port": 41347, "Service": "port-agent", "Tags": [ "RS10ENGC-XX00X-00-BOTPTA001" ] } } ]'''

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3f83407a9f58d733df9cdb9a852f98f8996c9fa2

139

py

Python

custom_components/ewii/pyewii/__init__.py

raakilde/hacs_addon

5688609ab54fae2d1817acbe825399d05c6662d7

[ "Apache-2.0" ]

null

custom_components/ewii/pyewii/__init__.py

raakilde/hacs_addon

5688609ab54fae2d1817acbe825399d05c6662d7

[ "Apache-2.0" ]

null

custom_components/ewii/pyewii/__init__.py

raakilde/hacs_addon

5688609ab54fae2d1817acbe825399d05c6662d7

[ "Apache-2.0" ]

null

""" Init file for pyewii """ from .ewii import Ewii from .models import TimeSeries from .models import RawMeterData __version__ = "0.5.0"

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b2100d37be87232bfc534454873162f78b195097

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py

Python

code_snippets/api-alert-mute.py

brettlangdon/documentation

87c23cb1d5e3e877bb37a19f7231b5d9239509dc

[ "BSD-3-Clause" ]

null

code_snippets/api-alert-mute.py

brettlangdon/documentation

87c23cb1d5e3e877bb37a19f7231b5d9239509dc

[ "BSD-3-Clause" ]

null

code_snippets/api-alert-mute.py

brettlangdon/documentation

87c23cb1d5e3e877bb37a19f7231b5d9239509dc

[ "BSD-3-Clause" ]

null

from dogapi import dog_http_api as api api.api_key = '9775a026f1ca7d1c6c5af9d94d9595a4' api.application_key = '87ce4a24b5553d2e482ea8a8500e71b8ad4554ff' # Mute all alerts api.mute_alerts()

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b766f104343393a31c7ae0559035981b390e3df6

114

py

Python

notifications/admin.py

jeffsimp88/twitterclone

696aa05da4feae15d7a0c2296a8d74be4ee32286

[ "MIT" ]

null

notifications/admin.py

jeffsimp88/twitterclone

696aa05da4feae15d7a0c2296a8d74be4ee32286

[ "MIT" ]

null

notifications/admin.py

jeffsimp88/twitterclone

696aa05da4feae15d7a0c2296a8d74be4ee32286

[ "MIT" ]

null

from django.contrib import admin from notifications.models import Notification admin.site.register(Notification)

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b769adfb80a9574b865d4ec01ad88141a9a905ac

43

py

Python

protobuf_weather_station/__init__.py

Telluric/Protobuf-Weather-Station.mpy

60619384bce797bca4178268aa2fd6516a77402f

[ "MIT" ]

null

protobuf_weather_station/__init__.py

Telluric/Protobuf-Weather-Station.mpy

60619384bce797bca4178268aa2fd6516a77402f

[ "MIT" ]

null

protobuf_weather_station/__init__.py

Telluric/Protobuf-Weather-Station.mpy

60619384bce797bca4178268aa2fd6516a77402f

[ "MIT" ]

null

from .WeatherStation import WeatherStation

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b7a2e0f97d3b9fdfeffa62a3542098fac97310dc

41

py

Python

conf.py

vminkov/sentinel-trails-documentation

d87d3129337ca47b28a2e94fc11ff9ce0a834225

[ "Apache-2.0" ]

null

conf.py

vminkov/sentinel-trails-documentation

d87d3129337ca47b28a2e94fc11ff9ce0a834225

[ "Apache-2.0" ]

null

conf.py

vminkov/sentinel-trails-documentation

d87d3129337ca47b28a2e94fc11ff9ce0a834225

[ "Apache-2.0" ]

null

extensions = ['sphinxcontrib.contentui']

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false

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null

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1

0

1

null

0

5

4d32cc0df613edc0b23134b438a5caa86cb830c8

37

py

Python

InventoryOptimExample/__init__.py

abbasmalekpour/InventoryOptim

20e0a2311d270341e91ed8af3b90f416b8efb02b

[ "MIT" ]

1

2020-12-09T01:32:07.000Z

InventoryOptimExample/__init__.py

abbasmalekpour/InventoryOptim

20e0a2311d270341e91ed8af3b90f416b8efb02b

[ "MIT" ]

null

InventoryOptimExample/__init__.py

abbasmalekpour/InventoryOptim

20e0a2311d270341e91ed8af3b90f416b8efb02b

[ "MIT" ]

2

2019-08-09T22:10:17.000Z

2019-11-12T04:50:31.000Z

from .inventory import InventoryOptim

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4d79e65ae09435b97dc5a221ef0a83ea788da7dd

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py

Python

test/transforms/test_to_sparse_tensor.py

NucciTheBoss/pytorch_geometric

e220a2c08fa1b2f1672d616c22eac2a67b5c8967

[ "MIT" ]

2,350

2021-09-12T08:32:50.000Z

2022-03-31T18:09:36.000Z

test/transforms/test_to_sparse_tensor.py

NucciTheBoss/pytorch_geometric

e220a2c08fa1b2f1672d616c22eac2a67b5c8967

[ "MIT" ]

588

2021-09-12T08:49:08.000Z

2022-03-31T21:02:13.000Z

test/transforms/test_to_sparse_tensor.py

NucciTheBoss/pytorch_geometric

e220a2c08fa1b2f1672d616c22eac2a67b5c8967

[ "MIT" ]

505

2021-09-13T13:13:32.000Z

2022-03-31T15:54:00.000Z

import torch from torch_geometric.data import Data, HeteroData from torch_geometric.transforms import ToSparseTensor def test_to_sparse_tensor(): assert ToSparseTensor().__repr__() == 'ToSparseTensor()' edge_index = torch.tensor([[0, 1, 1, 2], [1, 0, 2, 1]]) edge_weight = torch.randn(edge_index.size(1)) edge_attr = torch.randn(edge_index.size(1), 8) perm = torch.tensor([1, 0, 3, 2]) data = Data(edge_index=edge_index, edge_weight=edge_weight, edge_attr=edge_attr, num_nodes=3) data = ToSparseTensor()(data) assert len(data) == 3 assert data.adj_t.storage.row().tolist() == [0, 1, 1, 2] assert data.adj_t.storage.col().tolist() == [1, 0, 2, 1] assert data.adj_t.storage.value().tolist() == edge_weight[perm].tolist() assert data.edge_attr.tolist() == edge_attr[perm].tolist() assert data.num_nodes == 3 def test_to_sparse_tensor_and_keep_edge_index(): edge_index = torch.tensor([[0, 1, 1, 2], [1, 0, 2, 1]]) edge_weight = torch.randn(edge_index.size(1)) edge_attr = torch.randn(edge_index.size(1), 8) perm = torch.tensor([1, 0, 3, 2]) data = Data(edge_index=edge_index, edge_weight=edge_weight, edge_attr=edge_attr, num_nodes=3) data = ToSparseTensor(remove_edge_index=False)(data) assert len(data) == 5 assert data.adj_t.storage.row().tolist() == [0, 1, 1, 2] assert data.adj_t.storage.col().tolist() == [1, 0, 2, 1] assert data.adj_t.storage.value().tolist() == edge_weight[perm].tolist() assert data.edge_index.tolist() == edge_index[:, perm].tolist() assert data.edge_weight.tolist() == edge_weight[perm].tolist() assert data.edge_attr.tolist() == edge_attr[perm].tolist() assert data.num_nodes == 3 def test_hetero_to_sparse_tensor(): edge_index = torch.tensor([[0, 1, 1, 2], [1, 0, 2, 1]]) data = HeteroData() data['v'].num_nodes = 3 data['w'].num_nodes = 3 data['v', 'v'].edge_index = edge_index data['v', 'w'].edge_index = edge_index data = ToSparseTensor()(data) assert data['v', 'v'].adj_t.storage.row().tolist() == [0, 1, 1, 2] assert data['v', 'v'].adj_t.storage.col().tolist() == [1, 0, 2, 1] assert data['v', 'v'].adj_t.storage.value() is None assert data['v', 'w'].adj_t.storage.row().tolist() == [0, 1, 1, 2] assert data['v', 'w'].adj_t.storage.col().tolist() == [1, 0, 2, 1] assert data['v', 'w'].adj_t.storage.value() is None def test_to_sparse_tensor_num_nodes_equals_num_edges(): x = torch.arange(4) y = torch.arange(4) edge_index = torch.tensor([[0, 1, 1, 2], [1, 0, 2, 1]]) edge_weight = torch.randn(edge_index.size(1)) edge_attr = torch.randn(edge_index.size(1), 8) perm = torch.tensor([1, 0, 3, 2]) data = Data(x=x, edge_index=edge_index, edge_weight=edge_weight, edge_attr=edge_attr, y=y) data = ToSparseTensor()(data) assert len(data) == 4 assert data.x.tolist() == [0, 1, 2, 3] assert data.adj_t.storage.row().tolist() == [0, 1, 1, 2] assert data.adj_t.storage.col().tolist() == [1, 0, 2, 1] assert data.adj_t.storage.value().tolist() == edge_weight[perm].tolist() assert data.edge_attr.tolist() == edge_attr[perm].tolist() assert data.y.tolist() == [0, 1, 2, 3]

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5

4d7f10983207c620617673600af7546360e4b377

555

py

Python

thenewboston_node/core/utils/pytest.py

AbhayAysola/thenewboston-node

8a24cfd814eed590a7a1066e45b8b4877501aa35

[ "MIT" ]

30

2021-03-05T22:08:17.000Z

2021-09-23T02:45:45.000Z

thenewboston_node/core/utils/pytest.py

AbhayAysola/thenewboston-node

8a24cfd814eed590a7a1066e45b8b4877501aa35

[ "MIT" ]

148

2021-03-05T23:37:50.000Z

2021-11-02T02:18:58.000Z

thenewboston_node/core/utils/pytest.py

AbhayAysola/thenewboston-node

8a24cfd814eed590a7a1066e45b8b4877501aa35

[ "MIT" ]

14

2021-03-05T21:58:46.000Z

2021-10-15T17:27:52.000Z

import os import sys from .misc import yaml_coerce PYTEST_RUN_SLOW_TESTS = 'PYTEST_RUN_SLOW_TESTS' def is_pytest_running(): # TODO(dmu) HIGH: Implement a better way of detecting pytest return os.getenv('PYTEST_RUNNING') == 'true' or os.path.basename(sys.argv[0]) in ('pytest', 'py.test') def should_run(skip_name): return bool(yaml_coerce(os.getenv(skip_name))) def skip_slow(wrapped): import pytest # because pytest is a dev dependency return pytest.mark.skipif(not should_run(PYTEST_RUN_SLOW_TESTS), reason='Slow')(wrapped)

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4d945e29879165185ac990059a24e611125327f2

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py

Python

lib/models/fusion_modules/__init__.py

CFM-MSG/Code_LEORN

fabea1e1ded973a4db692e51e2df442bde55f626

[ "MIT" ]

1

2022-01-31T03:23:37.000Z

lib/models/fusion_modules/__init__.py

CFM-MSG/Code_LEORN

fabea1e1ded973a4db692e51e2df442bde55f626

[ "MIT" ]

null

lib/models/fusion_modules/__init__.py

CFM-MSG/Code_LEORN

fabea1e1ded973a4db692e51e2df442bde55f626

[ "MIT" ]

null

from .base_fusion import BaseFusion, EasyFusion, CatFusion from .semantic_enhancement import SemanticEnhancementModule

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5

4dacf9ddef29fa15efa3ab7e518fe4e0527469fb

76

py

Python

rules/__init__.py

jasonzhang970611/254final

923ea900df08557a6ede7777c916e25ee06ec9a8

[ "MIT" ]

null

rules/__init__.py

jasonzhang970611/254final

923ea900df08557a6ede7777c916e25ee06ec9a8

[ "MIT" ]

null

rules/__init__.py

jasonzhang970611/254final

923ea900df08557a6ede7777c916e25ee06ec9a8

[ "MIT" ]

1

2021-05-11T23:13:52.000Z

"""Rule module""" from .rule import Rule from .freestyle import FreeStyle

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4dd07b3108e3520f453e96d35adc718742b6cd79

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py

Python

app/main/meta/__init__.py

by46/coffee

f12e1e95f12da7e322a432a6386a1147c5549c3b

[ "MIT" ]

null

app/main/meta/__init__.py

by46/coffee

f12e1e95f12da7e322a432a6386a1147c5549c3b

[ "MIT" ]

null

app/main/meta/__init__.py

by46/coffee

f12e1e95f12da7e322a432a6386a1147c5549c3b

[ "MIT" ]

null

from .filter import filter_params from .user import UserModel from .coffee import CoffeeModel

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py

Python

ngsutils/fastq/t/test_barcode_split.py

bgruening/ngsutils

417e90dc1918fb553dd84990f2c54bd8cea8f44d

[ "BSD-3-Clause" ]

57

2015-03-09T01:26:45.000Z

2022-02-22T07:26:01.000Z

ngsutils/fastq/t/test_barcode_split.py

bgruening/ngsutils

417e90dc1918fb553dd84990f2c54bd8cea8f44d

[ "BSD-3-Clause" ]

33

2015-02-03T23:24:46.000Z

2022-03-16T20:08:10.000Z

ngsutils/fastq/t/test_barcode_split.py

bgruening/ngsutils

417e90dc1918fb553dd84990f2c54bd8cea8f44d

[ "BSD-3-Clause" ]

33

2015-01-18T16:47:47.000Z

2022-02-22T07:28:09.000Z

#!/usr/bin/env python ''' Tests for barcode_split Note: These tests use small barcodes, so some of the test sequences are pretty arbitrary. In real-life, the barcodes should be much longer (12-16bp). ''' import unittest import os import ngsutils.fastq.barcode_split from ngsutils.support import FASTA from ngsutils.fastq import FASTQ barcodes = { 'tag1': ('ATAT', '5'), 'tag2': ('TGTG', '5'), 'tag3': ('CTCT', '3') } barcodes2 = { 'tag1': ('AATTAA', '5'), 'tag2': ('GGTTCC', '5'), 'tag3': ('CCAACC', '3') } class BarcodeSplitTest(unittest.TestCase): def test_check_tags_5(self): valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'ATATaaaatttt', 0, 0, False) self.assertTrue(valid) self.assertEqual(results[0], 'tag1') self.assertTrue(results[2]) valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'TGTGaaaatttt', 0, 0, False) self.assertTrue(valid) self.assertEqual(results[0], 'tag2') self.assertTrue(results[2]) def test_check_tags_5_multi(self): "pulls out only the 5' ATAT, so the next ATAT is kept in-tact" valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'ATATATATaaaatttt', 0, 0, False) self.assertTrue(valid) self.assertEqual(results[0], 'tag1') self.assertTrue(results[2]) def test_check_tags_3(self): valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'aattttaaCTCT', 0, 0, False) # print valid, results self.assertTrue(valid) self.assertEqual(results[0], 'tag3') self.assertTrue(results[2]) def test_check_tags_5_fail(self): valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'aaaattttATAT', 0, 0, False) self.assertFalse(valid) self.assertEqual(results[0], 'tag1') # not at right location self.assertTrue(results[2]) def test_check_tags_5_revcomp(self): # matches ATAT in rev-comp valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'aaaattttATAT', 0, 0, True) self.assertTrue(valid) self.assertEqual(results[0], 'tag1') self.assertFalse(results[2]) def test_check_tags_5_mm(self): valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'ATTTacgtacgt', 0, 0, False) self.assertFalse(valid) self.assertEqual(results[0], 'tag1') self.assertTrue(results[2]) valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'ATTTacgtacgt', 1, 0, False) self.assertTrue(valid) self.assertEqual(results[0], 'tag1') self.assertTrue(results[2]) def test_check_tags_5_pos(self): valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'gATATacgtacgt', 0, 0, False) self.assertFalse(valid) self.assertEqual(results[0], 'tag1') self.assertTrue(results[2]) valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'gATATacgtacgt', 0, 1, False) self.assertTrue(valid) self.assertEqual(results[0], 'tag1') self.assertTrue(results[2]) def test_check_tags_3_mm(self): valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'ttttaaaaggggCGCT', 0, 0, False) self.assertFalse(valid) self.assertEqual(results[0], 'tag3') self.assertTrue(results[2]) valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'ttttaaaaggggCGCT', 1, 0, False) self.assertTrue(valid) self.assertEqual(results[0], 'tag3') self.assertTrue(results[2]) def test_check_tags_3_pos(self): valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'ttttaaaaggggCTCTg', 0, 0, False) self.assertFalse(valid) self.assertEqual(results[0], 'tag3') self.assertTrue(results[2]) valid, results = ngsutils.fastq.barcode_split.check_tags(barcodes, 'ttttaaaaggggCTCTg', 0, 1, False) self.assertTrue(valid) self.assertEqual(results[0], 'tag3') self.assertTrue(results[2]) def test_splitFasta(self): path = os.path.dirname(__file__) ngsutils.fastq.barcode_split.fastx_barcode_split(FASTA(os.path.join(path, 'test_barcodes.fasta')), os.path.join(path, 'out.%s.fasta'), barcodes2) self.assert_fasta_contains(os.path.join(path, 'out.%s.fasta'), { 'missing': 'foo-rc foo1 bar1 baz1 foo2 bar2 baz2 foo1-rc foo2-rc', 'tag1': 'foo', 'tag2': 'bar', 'tag3': 'baz' }) self._unlink_fastx(os.path.join(path, 'out.%s.fasta'), 'missing tag1 tag2 tag3'.split()) def test_splitFastaRevComp(self): path = os.path.dirname(__file__) ngsutils.fastq.barcode_split.fastx_barcode_split(FASTA(os.path.join(path, 'test_barcodes.fasta')), os.path.join(path, 'out.%s.fasta'), barcodes2, allow_revcomp=True) self.assert_fasta_contains(os.path.join(path, 'out.%s.fasta'), { 'missing': 'foo1 bar1 baz1 foo2 bar2 baz2 foo1-rc foo2-rc', 'tag1': 'foo foo-rc', 'tag2': 'bar', 'tag3': 'baz' }) self._unlink_fastx(os.path.join(path, 'out.%s.fasta'), 'missing tag1 tag2 tag3'.split()) def test_splitFastaEdit(self): path = os.path.dirname(__file__) ngsutils.fastq.barcode_split.fastx_barcode_split(FASTA(os.path.join(path, 'test_barcodes.fasta')), os.path.join(path, 'out.%s.fasta'), barcodes2, allow_revcomp=True, edits=1) self.assert_fasta_contains(os.path.join(path, 'out.%s.fasta'), { 'missing': 'foo2 bar2 baz2 foo2-rc', 'tag1': 'foo foo-rc foo1 foo1-rc', 'tag2': 'bar bar1', 'tag3': 'baz baz1' }) self._unlink_fastx(os.path.join(path, 'out.%s.fasta'), 'missing tag1 tag2 tag3'.split()) def test_splitFastaOffset(self): path = os.path.dirname(__file__) ngsutils.fastq.barcode_split.fastx_barcode_split(FASTA(os.path.join(path, 'test_barcodes.fasta')), os.path.join(path, 'out.%s.fasta'), barcodes2, allow_revcomp=True, pos=1) self.assert_fasta_contains(os.path.join(path, 'out.%s.fasta'), { 'missing': 'foo1 bar1 baz1 foo1-rc', 'tag1': 'foo foo-rc foo2 foo2-rc', 'tag2': 'bar bar2', 'tag3': 'baz baz2' }) self._unlink_fastx(os.path.join(path, 'out.%s.fasta'), 'missing tag1 tag2 tag3'.split()) def test_splitFastq(self): path = os.path.dirname(__file__) ngsutils.fastq.barcode_split.fastx_barcode_split(FASTQ(os.path.join(path, 'test_barcodes.fastq')), os.path.join(path, 'out.%s.fastq'), barcodes2, allow_revcomp=True) self.assert_fastq_contains(os.path.join(path, 'out.%s.fastq'), { 'missing': ('quux', '', ''), 'tag1': ('foo foo-rc', 'atcgatcgatcgatcg atcgatcgatcgatcg', 'AAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAA'), 'tag2': ('bar', 'gctagctagctagcta', 'AAAAAAAAAAAAAAAA'), 'tag3': ('baz', 'acgtacgtacgtacgt', 'AAAAAAAAAAAAAAAA') }) self._unlink_fastx(os.path.join(path, 'out.%s.fastq'), 'missing tag1 tag2 tag3'.split()) def _unlink_fastx(self, base, names): for name in names: os.unlink(base % name) def assert_fasta_contains(self, base, args): for tag in args: valid = args[tag].split() fa = FASTA(base % tag) count = 0 for read in fa.fetch(): if read.name in valid: count += 1 else: self.assertEqual('extra read in %s' % tag, read.name) self.assertEqual(count, len(valid)) def assert_fastq_contains(self, base, args): for tag in args: valid = args[tag][0].split() seq_qual = {} if args[tag][1]: for n, s, q in zip(valid, args[tag][1].split(), args[tag][2].split()): seq_qual[n] = (s, q) fq = FASTQ(base % tag) count = 0 for read in fq.fetch(): if read.name in valid: count += 1 if seq_qual: self.assertEqual(seq_qual[read.name], (read.seq, read.qual)) else: self.assertEqual('extra read in %s' % tag, read.name) self.assertEqual(count, len(valid)) if __name__ == '__main__': unittest.main()

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128e05b468000cd1e7d5d92d6b1ae4080ee7ff52

157

py

Python

Zad3/forum/admin.py

YuseqYaseq/Logic

295327312c6804dbbbf230e81b1724f81f26168e

[ "MIT" ]

null

Zad3/forum/admin.py

YuseqYaseq/Logic

295327312c6804dbbbf230e81b1724f81f26168e

[ "MIT" ]

null

Zad3/forum/admin.py

YuseqYaseq/Logic

295327312c6804dbbbf230e81b1724f81f26168e

[ "MIT" ]

null

from django.contrib import admin from .models import Thread, Message # Register your models here. admin.site.register(Thread) admin.site.register(Message)

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5

12bdd52654b4ce48d763184ee2676cd0d26a2800

334

py

Python

jupy4syn/commands/ctCommand.py

gabrielpreviato/test

a5e57d00a546bd8d939d5d71bb19364fb4524441

[ "0BSD" ]

null

jupy4syn/commands/ctCommand.py

gabrielpreviato/test

a5e57d00a546bd8d939d5d71bb19364fb4524441

[ "0BSD" ]

null

jupy4syn/commands/ctCommand.py

gabrielpreviato/test

a5e57d00a546bd8d939d5d71bb19364fb4524441

[ "0BSD" ]

null

from scan_utils import ct from jupy4syn.commands.ICommand import ICommand class ctCommand(ICommand): def __init__(self): pass def exec(self, parameters): return ct.main(parameters.split()) def args(self, initial_args): return initial_args def show(self, initial_args): return True

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5

12c9569738305d6b431a02f72bb8573b85ae4b25

1,052

py

Python

apkg/apkg.py

soimort/agda-pkg

1fb10020213bc7c590570ffe34aab4c66f47fb8b

[ "MIT" ]

null

apkg/apkg.py

soimort/agda-pkg

1fb10020213bc7c590570ffe34aab4c66f47fb8b

[ "MIT" ]

null

apkg/apkg.py

soimort/agda-pkg

1fb10020213bc7c590570ffe34aab4c66f47fb8b

[ "MIT" ]

1

2022-01-29T11:37:06.000Z

''' apkg ~~~~ A package manager for Agda. ''' # ---------------------------------------------------------------------------- import click from .commands import * from .commands.clean import clean from .commands.create import create from .commands.freeze import freeze from .commands.list import list from .commands.info import info from .commands.init import init from .commands.install import install from .commands.uninstall import uninstall from .commands.search import search from .commands.update import update from .commands.upgrade import upgrade # ---------------------------------------------------------------------------- @click.group() @click.version_option() def cli(): """A package manager for Agda.""" cli.add_command(init) cli.add_command(install) cli.add_command(uninstall) cli.add_command(freeze) cli.add_command(list) cli.add_command(info) cli.add_command(clean) cli.add_command(create) cli.add_command(search) cli.add_command(update) cli.add_command(upgrade)

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null

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1

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1

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5

12d25dede1b582f3c835994c10f7e87e8717fee0

224

py

Python

7_kyu/sum_of_odd_numbers.py

dimishpatriot/way_on_the_highway

4865db946632b7bd3d74509a20a307841c02169d

[ "MIT" ]

null

7_kyu/sum_of_odd_numbers.py

dimishpatriot/way_on_the_highway

4865db946632b7bd3d74509a20a307841c02169d

[ "MIT" ]

null

7_kyu/sum_of_odd_numbers.py

dimishpatriot/way_on_the_highway

4865db946632b7bd3d74509a20a307841c02169d

[ "MIT" ]

null

"""Given the triangle of consecutive odd numbers: 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 ... """ def row_sum_odd_numbers(n: int) -> int: return n ** 3

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0

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224

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1

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null

0

1

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1

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5

12e80b401aba984f4648146ff695556a389f7577

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py

Python

videoanalyst/model/loss/__init__.py

lizhenbang56/Manipulating-Template-Pixels-for-Model-Adaptation-of-Siamese-Visual-Tracking

76b88d8e68ac3d575a2ce81fc07ee2fce5f050d6

[ "MIT" ]

2

2020-07-30T08:26:08.000Z

2020-11-24T07:40:46.000Z

videoanalyst/model/loss/__init__.py

shartoo/video_analyst

db7c1b323f26ec19533a4b19804cf2c8a52643e5

[ "MIT" ]

null

videoanalyst/model/loss/__init__.py

shartoo/video_analyst

db7c1b323f26ec19533a4b19804cf2c8a52643e5

[ "MIT" ]

null

from .loss_impl import *

25

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1

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0.857143

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true

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null

0

1

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null

0

1

0

1

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5

42221f009ac99fc6f86326bcdd2d193656207aa9

58

py

Python

backend/socket_server/handler/client_disconnect.py

JohnnyDevNull/python-nuxt-starter

e6158818b7536212dafec2dfe3bc70385110440c

[ "MIT" ]

null

backend/socket_server/handler/client_disconnect.py

JohnnyDevNull/python-nuxt-starter

e6158818b7536212dafec2dfe3bc70385110440c

[ "MIT" ]

1

2022-01-22T12:45:49.000Z

backend/socket_server/handler/client_disconnect.py

JohnnyDevNull/python-nuxt-starter

e6158818b7536212dafec2dfe3bc70385110440c

[ "MIT" ]

null

def client_disconnect(): print('Client disconnected')

19.333333

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true

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1

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null

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1

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1

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5

42942027cf0d72a947321e707d1525fd58ad9f4b

22,616

py

Python

algotom/post/postprocessing.py

gbzan/algotom

314f05b6a226e666a8ae4417b151d896606e7db4

[ "Apache-2.0" ]

null

algotom/post/postprocessing.py

gbzan/algotom

314f05b6a226e666a8ae4417b151d896606e7db4

[ "Apache-2.0" ]

null

algotom/post/postprocessing.py

gbzan/algotom

314f05b6a226e666a8ae4417b151d896606e7db4

[ "Apache-2.0" ]

null

# ============================================================================ # ============================================================================ # Copyright (c) 2021 Nghia T. Vo. All rights reserved. # # 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. # ============================================================================ # Author: Nghia T. Vo # E-mail: # Description: Python implementations of postprocessing techniques. # Contributors: # ============================================================================ """ Module of methods in the postprocessing stage: - Get statistical information of reconstructed images or a dataset. - Downsample 2D, 3D array, or a dataset. - Rescale 2D, 3D array or a dataset to 8-bit or 16-bit data-type. - Removing ring artifacts in a reconstructed image by transform back and forth between the polar coordinates and the Cartesian coordinates. """ import os import numpy as np from scipy.ndimage import gaussian_filter import algotom.util.utility as util import algotom.io.loadersaver as losa import algotom.prep.removal as remo def get_statical_information(mat, percentile=(5, 95), denoise=False): """ Get statical information of an image. Parameters ---------- mat : array_like 2D array. Projection image, sinogram image, or reconstructed image. percentile : tuple of floats Tuple of (min_percentile, max_percentile) to compute. Must be between 0 and 100 inclusive. denoise: bool, optional Enable/disable denoising before extracting statistical information. Returns ------- gmin : float The minimum value of the data array. gmax : float The maximum value of the data array. min_percent : float The first computed percentile of the data array. max_percent : tuple of floats The last computed percentile of the data array. mean : float The mean of the data array. median : float The median of the data array. variance : float The variance of the data array. """ if denoise is True: mat = gaussian_filter(mat, 2) gmin = np.min(mat) gmax = np.max(mat) min_percent = np.percentile(mat, percentile[0]) max_percent = np.percentile(mat, percentile[-1]) median = np.median(mat) mean = np.mean(mat) variance = np.var(mat) return gmin, gmax, min_percent, max_percent, mean, median, variance def get_statical_information_dataset(input_, percentile=(5, 95), skip=5, denoise=False, key_path=None): """ Get statical information of a dataset. This can be a folder of tif files, a hdf file, or a 3D array. Parameters ---------- input_ : str, hdf file, or array_like It can be a folder path to tif files, a hdf file, or a 3D array. percentile : tuple of floats Tuple of (min_percentile, max_percentile) to compute. Must be between 0 and 100 inclusive. skip : int Skipping step of reading input. denoise: bool, optional Enable/disable denoising before extracting statistical information. key_path : str, optional Key path to the dataset if the input is the hdf file. Returns ------- gmin : float The global minimum value of the data array. gmax : float The global maximum value of the data array. min_percent : float The global min of the first computed percentile of the data array. max_percent : tuple of floats The global min of the last computed percentile of the data array. mean : float The mean of the data array. median : float The median of the data array. variance : float The mean of the variance of the data array. """ if isinstance(input_, str) and (os.path.splitext(input_)[-1] == ""): list_file = losa.find_file(input_ + "/*.tif*") depth = len(list_file) if depth == 0: raise ValueError("No tif files in the folder: {}".format(input_)) list_stat = [] for i in range(0, depth, skip): mat = losa.load_image(list_file[i]) if denoise is True: mat = gaussian_filter(mat, 2) list_stat.append(get_statical_information(mat, percentile, denoise)) else: if isinstance(input_, str): file_ext = os.path.splitext(input_)[-1] if not (file_ext == '.hdf' or file_ext == '.h5' or file_ext == ".nxs"): raise ValueError( "Can't open this type of file format {}".format(file_ext)) if key_path is None: raise ValueError( "Please provide the key path to the dataset!!!") input_ = losa.load_hdf(input_, key_path) depth = len(input_) list_stat = [] for i in range(0, depth, skip): mat = input_[i] if denoise is True: mat = gaussian_filter(mat, 2) list_stat.append(get_statical_information(mat, percentile, denoise)) list_stat = np.asarray(list_stat) gmin = np.min(list_stat[:, 0]) gmax = np.max(list_stat[:, 1]) min_percent = np.min(list_stat[:, 2]) max_percent = np.max(list_stat[:, 3]) median = np.median(list_stat[:, 4]) mean = np.mean(list_stat[:, 5]) variance = np.mean(list_stat[:, 6]) return gmin, gmax, min_percent, max_percent, mean, median, variance def downsample(mat, cell_size, method="mean"): """ Downsample an image. Parameters ---------- mat : array_like 2D array. cell_size : int or tuple of int Window size along axes used for grouping pixels. method : {"mean", "median", "max", "min"} Downsampling method. Returns ------- array_like Downsampled image. """ if method == "median": dsp_method = np.median elif method == "max": dsp_method = np.max elif method == "min": dsp_method = np.amin else: dsp_method = np.mean (height, width) = mat.shape if isinstance(cell_size, int): cell_size = (cell_size, cell_size) height_dsp = height // cell_size[0] width_dsp = width // cell_size[1] mat = mat[:height_dsp * cell_size[0], :width_dsp * cell_size[1]] mat_dsp = mat.reshape( height_dsp, cell_size[0], width_dsp, cell_size[1]) mat_dsp = dsp_method(dsp_method(mat_dsp, axis=-1), axis=1) return mat_dsp def downsample_dataset(input_, output, cell_size, method="mean", key_path=None): """ Downsample a dataset. This can be a folder of tif files, a hdf file, or a 3D array. Parameters ---------- input_ : str, array_like It can be a folder path to tif files, a hdf file, or 3D array. output : str, None It can be a folder path, a hdf file path, or None (memory consuming). cell_size : int or tuple of int Window size along axes used for grouping pixels. method : {"mean", "median", "max", "min"} Downsampling method. key_path : str, optional Key path to the dataset if the input is the hdf file. Returns ------- array_like or None If output is None, returning an 3D array. """ if output is not None: file_base, file_ext = os.path.splitext(output) if file_ext != "": file_base = os.path.dirname(output) if os.path.exists(file_base): raise ValueError("Folder exists!!! Please choose another path!!!") if method == "median": dsp_method = np.median elif method == "max": dsp_method = np.max elif method == "min": dsp_method = np.amin else: dsp_method = np.mean if isinstance(cell_size, int): cell_size = (cell_size, cell_size, cell_size) if isinstance(input_, str) and (os.path.splitext(input_)[-1] == ""): list_file = losa.find_file(input_ + "/*.tif*") depth = len(list_file) if depth == 0: raise ValueError("No tif files in the folder: {}".format(input_)) (height, width) = np.shape(losa.load_image(list_file[0])) depth_dsp = depth // cell_size[0] height_dsp = height // cell_size[1] width_dsp = width // cell_size[2] num = 0 if (depth_dsp != 0) and (height_dsp != 0) and (width_dsp != 0): if output is not None: file_base, file_ext = os.path.splitext(output) if file_ext != "": if not (file_ext == '.hdf' or file_ext == '.h5' or file_ext == ".nxs"): raise ValueError( "File extension must be hdf, h5, or nxs") output = file_base + file_ext data_out = losa.open_hdf_stream( output, (depth_dsp, height_dsp, width_dsp), key_path="downsample/data", overwrite=False) data_dsp = [] for i in range(0, depth, cell_size[0]): if (i + cell_size[0]) > depth: break else: mat = [] for j in range(i, i + cell_size[0]): mat.append(losa.load_image(list_file[j])) mat = np.asarray(mat) mat = mat[:, :height_dsp * cell_size[1], :width_dsp * cell_size[2]] mat = mat.reshape(1, cell_size[0], height_dsp, cell_size[1], width_dsp, cell_size[2]) mat_dsp = dsp_method( dsp_method(dsp_method(mat, axis=-1), axis=1), axis=2) if output is None: data_dsp.append(mat_dsp[0]) else: if file_ext == "": out_name = "0000" + str(num) losa.save_image( output + "/img_" + out_name[-5:] + ".tif", mat_dsp[0]) else: data_out[num] = mat_dsp[0] num += 1 else: raise ValueError("Incorrect cell size {}".format(cell_size)) else: if isinstance(input_, str): file_ext = os.path.splitext(input_)[-1] if not (file_ext == '.hdf' or file_ext == '.h5' or file_ext == ".nxs"): raise ValueError( "Can't open this type of file format {}".format(file_ext)) if key_path is None: raise ValueError( "Please provide the key path to the dataset!!!") input_ = losa.load_hdf(input_, key_path) (depth, height, width) = input_.shape depth_dsp = depth // cell_size[0] height_dsp = height // cell_size[1] width_dsp = width // cell_size[2] if (depth_dsp != 0) and (height_dsp != 0) and (width_dsp != 0): if output is None: input_ = input_[:depth_dsp * cell_size[0], :height_dsp * cell_size[1], :width_dsp * cell_size[2]] input_ = input_.reshape( depth_dsp, cell_size[0], height_dsp, cell_size[1], width_dsp, cell_size[2]) data_dsp = dsp_method( dsp_method(dsp_method(input_, axis=-1), axis=1), axis=2) else: file_base, file_ext = os.path.splitext(output) if file_ext != "": if not (file_ext == '.hdf' or file_ext == '.h5' or file_ext == ".nxs"): raise ValueError( "File extension must be hdf, h5, or nxs") output = file_base + file_ext data_out = losa.open_hdf_stream( output, (depth_dsp, height_dsp, width_dsp), key_path="downsample/data", overwrite=False) num = 0 for i in range(0, depth, cell_size[0]): if (i + cell_size[0]) > depth: break else: mat = input_[i:i + cell_size[0], :height_dsp * cell_size[1], :width_dsp * cell_size[2]] mat = mat.reshape(1, cell_size[0], height_dsp, cell_size[1], width_dsp, cell_size[2]) mat_dsp = dsp_method(dsp_method( dsp_method(mat, axis=-1), axis=1), axis=2) if file_ext != "": data_out[num] = mat_dsp[0] else: out_name = "0000" + str(num) losa.save_image( output + "/img_" + out_name[-5:] + ".tif", mat_dsp[0]) num += 1 else: raise ValueError("Incorrect cell size {}".format(cell_size)) if output is None: return np.asarray(data_dsp) def rescale(mat, nbit=16, minmax=None): """ Rescale a 32-bit array to 16-bit/8-bit data. Parameters ---------- mat : array_like nbit : {8,16} Rescaled data-type: 8-bit or 16-bit. minmax : tuple of float, or None Minimum and maximum values used for rescaling. Returns ------- array_like Rescaled array. """ if minmax is None: gmin, gmax = np.min(mat), np.max(mat) else: (gmin, gmax) = minmax mat = np.clip(mat, gmin, gmax) mat = (mat - gmin) / (gmax - gmin) if nbit == 8: mat = np.uint8(np.clip(mat * 255, 0, 255)) else: mat = np.uint16(np.clip(mat * 65535, 0, 65535)) return mat def rescale_dataset(input_, output, nbit=16, minmax=None, skip=None, key_path=None): """ Rescale a dataset to 8-bit or 16-bit data-type. The dataset can be a folder of tif files, a hdf file, or a 3D array. Parameters ---------- input_ : str, array_like It can be a folder path to tif files, a hdf file, or 3D array. output : str, None It can be a folder path, a hdf file path, or None (memory consuming). nbit : {8,16} Rescaled data-type: 8-bit or 16-bit. minmax : tuple of float, or None Minimum and maximum values used for rescaling. They are calculated if None is given. skip : int or None Skipping step of reading input used for getting statistical information. key_path : str, optional Key path to the dataset if the input is the hdf file. Returns ------- array_like or None If output is None, returning an 3D array. """ if output is not None: file_base, file_ext = os.path.splitext(output) if file_ext != "": file_base = os.path.dirname(output) if os.path.exists(file_base): raise ValueError("Folder exists!!! Please choose another path!!!") if isinstance(input_, str) and (os.path.splitext(input_)[-1] == ""): list_file = losa.find_file(input_ + "/*.tif*") depth = len(list_file) if depth == 0: raise ValueError("No tif files in the folder: {}".format(input_)) if minmax is None: if skip is None: skip = int(np.ceil(0.15 * depth)) (gmin, gmax) = get_statical_information_dataset(input_, skip=skip)[ 0:2] else: (gmin, gmax) = minmax if output is not None: file_base, file_ext = os.path.splitext(output) if file_ext != "": if not (file_ext == '.hdf' or file_ext == '.h5' or file_ext == ".nxs"): raise ValueError("File extension must be hdf, h5, or nxs") output = file_base + file_ext (height, width) = np.shape(losa.load_image(list_file[0])) if nbit == 8: data_type = "uint8" else: data_type = "uint16" data_out = losa.open_hdf_stream(output, (depth, height, width), key_path="rescale/data", data_type=data_type, overwrite=False) data_res = [] for i in range(0, depth): mat = rescale( losa.load_image(list_file[i]), nbit=nbit, minmax=(gmin, gmax)) if output is None: data_res.append(mat) else: file_base, file_ext = os.path.splitext(output) if file_ext == "": out_name = "0000" + str(i) losa.save_image(output + "/img_" + out_name[-5:] + ".tif", mat) else: data_out[i] = mat else: if isinstance(input_, str): file_ext = os.path.splitext(input_)[-1] if not (file_ext == '.hdf' or file_ext == '.h5' or file_ext == ".nxs"): raise ValueError( "Can't open this type of file format {}".format(file_ext)) if key_path is None: raise ValueError( "Please provide the key path to the dataset!!!") input_ = losa.load_hdf(input_, key_path) (depth, height, width) = input_.shape if minmax is None: if skip is None: skip = int(np.ceil(0.15 * depth)) (gmin, gmax) = get_statical_information_dataset(input_, skip=skip, key_path=key_path)[ 0:2] else: (gmin, gmax) = minmax data_res = [] if output is not None: file_base, file_ext = os.path.splitext(output) if file_ext != "": if not (file_ext == '.hdf' or file_ext == '.h5' or file_ext == ".nxs"): raise ValueError("File extension must be hdf, h5, or nxs") output = file_base + file_ext if nbit == 8: data_type = "uint8" else: data_type = "uint16" data_out = losa.open_hdf_stream( output, (depth, height, width), key_path="rescale/data", data_type=data_type, overwrite=False) for i in range(0, depth): mat = rescale(input_[i], nbit=nbit, minmax=(gmin, gmax)) if output is None: data_res.append(mat) else: file_base, file_ext = os.path.splitext(output) if file_ext != "": data_out[i] = mat else: out_name = "0000" + str(i) losa.save_image(output + "/img_" + out_name[-5:] + ".tif", mat) if output is None: return np.asarray(data_res) def remove_ring_based_fft(mat, u=20, n=8, v=1, sort=False): """ Remove ring artifacts in the reconstructed image by combining the polar transform and the fft-based method. Parameters ---------- mat : array_like Square array. Reconstructed image u : int Cutoff frequency. n : int Filter order. v : int Number of rows (* 2) to be applied the filter. sort : bool, optional Apply sorting (Ref. [2]) if True. Returns ------- array_like Ring-removed image. References ---------- .. [1] https://doi.org/10.1063/1.1149043 .. [2] https://doi.org/10.1364/OE.26.028396 """ (nrow, ncol) = mat.shape if nrow != ncol: raise ValueError( "Width and height of the reconstructed image are not the same") mask = util.make_circle_mask(ncol, 1.0) (x_mat, y_mat) = util.rectangular_from_polar(ncol, ncol, ncol, ncol) (r_mat, theta_mat) = util.polar_from_rectangular(ncol, ncol, ncol, ncol) polar_mat = util.mapping(mat, x_mat, y_mat) polar_mat = remo.remove_stripe_based_fft(polar_mat, u, n, v, sort=sort) mat_rec = util.mapping(polar_mat, r_mat, theta_mat) return mat_rec * mask def remove_ring_based_wavelet_fft(mat, level=5, size=1, wavelet_name="db9", sort=False): """ Remove ring artifacts in a reconstructed image by combining the polar transform and the wavelet-fft-based method (Ref. [1]). Parameters ---------- mat : array_like Square array. Reconstructed image level : int Wavelet decomposition level. size : int Damping parameter. Larger is stronger. wavelet_name : str Name of a wavelet. Search pywavelets API for a full list. sort : bool, optional Apply sorting (Ref. [2]) if True. Returns ------- array_like Ring-removed image. References ---------- .. [1] https://doi.org/10.1364/OE.17.008567 .. [2] https://doi.org/10.1364/OE.26.028396 """ (nrow, ncol) = mat.shape if nrow != ncol: raise ValueError( "Width and height of the reconstructed image are not the same") mask = util.make_circle_mask(ncol, 1.0) (x_mat, y_mat) = util.rectangular_from_polar(ncol, ncol, ncol, ncol) (r_mat, theta_mat) = util.polar_from_rectangular(ncol, ncol, ncol, ncol) polar_mat = util.mapping(mat, x_mat, y_mat) polar_mat = remo.remove_stripe_based_wavelet_fft(polar_mat, level, size, wavelet_name, sort=sort) mat_rec = util.mapping(polar_mat, r_mat, theta_mat) return mat_rec * mask

38.528109

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0.534887

2,827

22,616

4.125221

0.117439

0.034985

0.016978

0.016807

0.781598

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0.730921

0.719088

0.693878

0.67467

0

0.020492

0.350504

22,616

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0

1

0

1

0

1

0

null

0

5

429a3b9f7b2c80becb4ddde048b1884840251023

439

py

Python

proposals/translation.py

mindruion/test

d27ef1caf8f76aead934bc83be7729f79a4be503

[ "MIT" ]

2

2017-04-22T11:07:13.000Z

2018-03-02T12:23:24.000Z

proposals/translation.py

mindruion/test

d27ef1caf8f76aead934bc83be7729f79a4be503

[ "MIT" ]

124

2020-04-30T07:06:58.000Z

2022-03-28T12:50:16.000Z

proposals/translation.py

mindruion/test

d27ef1caf8f76aead934bc83be7729f79a4be503

[ "MIT" ]

1

2021-08-04T11:44:21.000Z

from modeltranslation.translator import register, TranslationOptions from .models import Funding, Relation, Institution @register(Funding) class FundingTranslationOptions(TranslationOptions): fields = ('description',) @register(Institution) class FundingTranslationOptions(TranslationOptions): fields = ('description',) @register(Relation) class RelationTranslationOptions(TranslationOptions): fields = ('description',)

23.105263

68

0.797267

33

439

10.606061

0.454545

0.205714

0.3

0.308571

0.417143

0

0.109339

439

18

69

24.388889

0.895141

0

0.454545

0

0.075171

0

1

0

false

0

0.181818

0

0.727273

0

1

null

1

0

null

0

1

0

5

c41fa389788d2bc39269275d11e4597f13ff2e7a

167

py

Python

python/geospark/register/__init__.py

Maxar-Corp/GeoSpark

6248c6773dc88bf3354ea9b223f16ceb064e7627

[ "Apache-2.0", "MIT" ]

1

2021-10-19T07:57:29.000Z

python/geospark/register/__init__.py

mayankkt9/GeoSpark

618da90413f7d86c59def92ba765fbd6d9d49761

[ "Apache-2.0", "MIT" ]

3

2020-03-24T18:20:35.000Z

2021-02-02T22:36:37.000Z

python/geospark/register/__init__.py

mayankkt9/GeoSpark

618da90413f7d86c59def92ba765fbd6d9d49761

[ "Apache-2.0", "MIT" ]

1

2021-09-26T15:51:22.000Z

from geospark.register.geo_registrator import GeoSparkRegistrator from geospark.register.uploading import upload_jars __all__ = ["GeoSparkRegistrator", "upload_jars"]

41.75

65

0.856287

18

167

7.555556

0.611111

0.176471

0.294118

0

0.071856

167

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41.75

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0.178571

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0

1

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null

0

1

0

1

0

5

c426ccec48489402b5fe37eec30fdf9b8a18263e

17

py

Python

app/co/__init__.py

random-forest/co

398a77914cbff2af93b4c6c114a97075a4a13aa8

[ "MIT" ]

null

app/co/__init__.py

random-forest/co

398a77914cbff2af93b4c6c114a97075a4a13aa8

[ "MIT" ]

null

app/co/__init__.py

random-forest/co

398a77914cbff2af93b4c6c114a97075a4a13aa8

[ "MIT" ]

null

from co import *

8.5

16

0.705882

3

17

4

1

0

0.235294

17

1

17

0.923077

0

1

0

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0

1

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0

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null

0

1

0

null

0

1

0

1

0

5

c434f990f7277abcb8d31f293bd2e90d463634cb

188

py

Python

tests/test_get_indices.py

gfsemelas/nesting

eda46bb6e1dc2844208849452dee50fd324486df

[ "MIT" ]

null

tests/test_get_indices.py

gfsemelas/nesting

eda46bb6e1dc2844208849452dee50fd324486df

[ "MIT" ]

null

tests/test_get_indices.py

gfsemelas/nesting

eda46bb6e1dc2844208849452dee50fd324486df

[ "MIT" ]

null

from nesting import get_indices def test_get_indices(): test_list = [1, 2, [3, 4], [5, [100, 200, ['hello']], 23, 11], 1, 7] assert get_indices(test_list, 'hello') == [3, 1, 2, 0]

37.6

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0.601064

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188

3.242424

0.636364

0.280374

0.261682

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0

1

0

null

0

1

0

5

c45a89abf0b9a7d3b7b0b281b5f210a53c85ca80

97

py

Python

Task/Filter/Python/filter-3.py

LaudateCorpus1/RosettaCodeData

9ad63ea473a958506c041077f1d810c0c7c8c18d

[ "Info-ZIP" ]

5

2021-01-29T20:08:05.000Z

2022-03-22T06:16:05.000Z

Task/Filter/Python/filter-3.py

seanwallawalla-forks/RosettaCodeData

9ad63ea473a958506c041077f1d810c0c7c8c18d

[ "Info-ZIP" ]

null

Task/Filter/Python/filter-3.py

seanwallawalla-forks/RosettaCodeData

9ad63ea473a958506c041077f1d810c0c7c8c18d

[ "Info-ZIP" ]

1

2021-04-13T04:19:31.000Z

values = range(10) values[::2] = [11,13,15,17,19] print values 11, 1, 13, 3, 15, 5, 17, 7, 19, 9

19.4

33

0.57732

22

97

2.545455

0.681818

0

0.35443

0.185567

97

4

34

24.25

0.35443

0

null

0

null

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1

0

1

0

1

0

null

0

1

0

5

c4793f07bcc999859482152f63e865ea46e63c05

51,884

py

Python

tests/parsers/test_vasp.py

lancekavalsky/pif-dft

8bb4047d7c5b7e2ee7dfee8ed4b8dd45e7943bde

[ "Apache-2.0" ]

5

2017-03-06T19:05:09.000Z

2018-10-22T16:56:04.000Z

tests/parsers/test_vasp.py

aced-differentiate/pif-dft

8bb4047d7c5b7e2ee7dfee8ed4b8dd45e7943bde

[ "Apache-2.0" ]

22

2017-02-01T03:38:44.000Z

2019-10-04T14:17:31.000Z

tests/parsers/test_vasp.py

aced-differentiate/pif-dft

8bb4047d7c5b7e2ee7dfee8ed4b8dd45e7943bde

[ "Apache-2.0" ]

10

2017-02-01T03:37:21.000Z

2020-04-22T20:34:19.000Z

import unittest from dfttopif.parsers import VaspParser from dfttopif.parsers.base import InvalidIngesterException from ..test_pif import unpack_example, delete_example from pypif.obj.common.value import Value import os import shutil class TestVASPParser(unittest.TestCase): def get_parser(self,name): '''Get a VaspParser for a certain test''' unpack_example(os.path.join('examples', 'vasp', name+'.tar.gz')) return VaspParser.generate_from_directory(name) def test_perov(self): # Parse the results parser = self.get_parser('perov_relax_U') # Test the settings self.assertEquals('VASP', parser.get_name()) strc = parser.get_output_structure() self.assertAlmostEquals(3.9088966983609255, strc.cell[1][1]) self.assertEquals(['La','Mn','O','O','O'], strc.get_chemical_symbols()) self.assertEquals('LaMnO3', parser.get_composition()) # Test the density self.assertEqual("g/(cm^3)", parser.get_density().units) self.assertAlmostEqual(6.7238121, parser.get_density().scalars[0].value, places=6) # Test the cutoff energy res = parser.get_cutoff_energy() self.assertEquals(400, res.scalars[0].value) self.assertEquals('eV', res.units) self.assertTrue(parser.is_converged().scalars[0].value) self.assertAlmostEqual(-39.85550532, parser.get_total_energy().scalars[0].value) self.assertEquals(None, parser.uses_SOC()) self.assertTrue(isinstance(parser.is_relaxed(), Value)) self.assertEquals('PAW_PBE', parser.get_xc_functional().scalars[0].value) self.assertEquals(['La','Mn','O'], list(map(lambda x: x.value, parser.get_pp_name().vectors[0]))) self.assertEquals(8640, parser.get_KPPRA().scalars[0].value) self.assertEquals('5.3.2', parser.get_version_number()) self.assertEquals({'Type': 2, 'Values':{'La':{'L':-1,'U':0.0,'J':0.0},'Mn':{'L':2,'U':3.8,'J':0.0},'O':{'L':-1,'U':0.0,'J':0.0}}}, parser.get_U_settings().as_dictionary()) self.assertEquals(None, parser.get_vdW_settings()) self.assertEquals(0.09, parser.get_pressure().scalars[0].value) self.assertEquals([[0.08970,0,0],[0,0.08970,0],[0,0,0.08970]], list(map(lambda x: list(map(lambda y: y.value, x)), parser.get_stresses().matrices[0]))) self.assertEquals(0, parser.get_band_gap().scalars[0].value) dos = parser.get_dos() self.assertEquals([-26.378, -26.241, -26.103000000000002, -25.966000000000001, -25.829000000000001, -25.690999999999999, -25.553999999999998, -25.417000000000002, -25.279, -25.141999999999999, -25.004999999999999, -24.867000000000001, -24.73, -24.593, -24.454999999999998, -24.318000000000001, -24.181000000000001, -24.042999999999999, -23.905999999999999, -23.768999999999998, -23.631, -23.494, -23.356999999999999, -23.219000000000001, -23.082000000000001, -22.945, -22.806999999999999, -22.670000000000002, -22.533000000000001, -22.395, -22.257999999999999, -22.120999999999999, -21.983000000000001, -21.846, -21.709, -21.571000000000002, -21.434000000000001, -21.297000000000001, -21.158999999999999, -21.021999999999998, -20.884, -20.747, -20.609999999999999, -20.472000000000001, -20.335000000000001, -20.198, -20.059999999999999, -19.922999999999998, -19.786000000000001, -19.648, -19.510999999999999, -19.373999999999999, -19.236000000000001, -19.099, -18.962, -18.824000000000002, -18.687000000000001, -18.550000000000001, -18.411999999999999, -18.274999999999999, -18.138000000000002, -18.0, -17.863, -17.725999999999999, -17.588000000000001, -17.451000000000001, -17.314, -17.175999999999998, -17.039000000000001, -16.902000000000001, -16.763999999999999, -16.626999999999999, -16.489999999999998, -16.352, -16.215, -16.077999999999999, -15.94, -15.803000000000001, -15.666, -15.528, -15.391, -15.254, -15.116, -14.978999999999999, -14.842000000000001, -14.704000000000001, -14.567, -14.43, -14.292, -14.154999999999999, -14.018000000000001, -13.880000000000001, -13.743, -13.606, -13.468, -13.331, -13.194000000000001, -13.055999999999999, -12.919, -12.782, -12.644, -12.507, -12.369999999999999, -12.231999999999999, -12.095000000000001, -11.958, -11.82, -11.683, -11.545999999999999, -11.407999999999999, -11.271000000000001, -11.134, -10.996, -10.859, -10.722, -10.584, -10.446999999999999, -10.31, -10.172000000000001, -10.035, -9.8979999999999997, -9.7599999999999998, -9.6229999999999993, -9.4860000000000007, -9.3480000000000008, -9.2110000000000003, -9.0739999999999998, -8.9359999999999999, -8.7989999999999995, -8.6620000000000008, -8.5239999999999991, -8.3870000000000005, -8.25, -8.1120000000000001, -7.9749999999999996, -7.8380000000000001, -7.7000000000000002, -7.5629999999999997, -7.4260000000000002, -7.2880000000000003, -7.1509999999999998, -7.0140000000000002, -6.8760000000000003, -6.7389999999999999, -6.6020000000000003, -6.4640000000000004, -6.327, -6.1890000000000001, -6.0519999999999996, -5.915, -5.7770000000000001, -5.6399999999999997, -5.5030000000000001, -5.3650000000000002, -5.2279999999999998, -5.0910000000000002, -4.9530000000000003, -4.8159999999999998, -4.6790000000000003, -4.5410000000000004, -4.4039999999999999, -4.2670000000000003, -4.1289999999999996, -3.992, -3.855, -3.7170000000000001, -3.5800000000000001, -3.4430000000000001, -3.3050000000000002, -3.1680000000000001, -3.0310000000000001, -2.8929999999999998, -2.7559999999999998, -2.6190000000000002, -2.4809999999999999, -2.3439999999999999, -2.2069999999999999, -2.069, -1.9319999999999999, -1.7949999999999999, -1.657, -1.52, -1.383, -1.2450000000000001, -1.1080000000000001, -0.97099999999999997, -0.83299999999999996, -0.69599999999999995, -0.55900000000000005, -0.42099999999999999, -0.28399999999999997, -0.14699999999999999, -0.0089999999999999993, 0.128, 0.26500000000000001, 0.40300000000000002, 0.54000000000000004, 0.67700000000000005, 0.81499999999999995, 0.95199999999999996, 1.089, 1.2270000000000001, 1.3640000000000001, 1.5009999999999999, 1.639, 1.776, 1.913, 2.0510000000000002, 2.1880000000000002, 2.3250000000000002, 2.4630000000000001, 2.6000000000000001, 2.7370000000000001, 2.875, 3.012, 3.149, 3.2869999999999999, 3.4239999999999999, 3.5609999999999999, 3.6989999999999998, 3.8359999999999999, 3.9729999999999999, 4.1109999999999998, 4.2480000000000002, 4.3849999999999998, 4.5229999999999997, 4.6600000000000001, 4.7969999999999997, 4.9349999999999996, 5.0720000000000001, 5.2089999999999996, 5.3470000000000004, 5.484, 5.6210000000000004, 5.7590000000000003, 5.8959999999999999, 6.0330000000000004, 6.1710000000000003, 6.3079999999999998, 6.4450000000000003, 6.5830000000000002, 6.7199999999999998, 6.8570000000000002, 6.9950000000000001, 7.1319999999999997, 7.2690000000000001, 7.407, 7.5439999999999996, 7.681, 7.819, 7.9560000000000004, 8.093, 8.2309999999999999, 8.3680000000000003, 8.5060000000000002, 8.6430000000000007, 8.7799999999999994, 8.9179999999999993, 9.0549999999999997, 9.1920000000000002, 9.3300000000000001, 9.4670000000000005, 9.6039999999999992, 9.7420000000000009, 9.8789999999999996, 10.016, 10.154, 10.291, 10.428000000000001, 10.566000000000001, 10.702999999999999, 10.84, 10.978, 11.115, 11.252000000000001, 11.390000000000001, 11.526999999999999, 11.664, 11.802, 11.939, 12.076000000000001, 12.214, 12.351000000000001, 12.488, 12.625999999999999, 12.763, 12.9, 13.038, 13.175000000000001, 13.311999999999999, 13.449999999999999, 13.587, 13.724, 13.862, 13.999000000000001, 14.135999999999999, 14.273999999999999, 14.411, 14.548, 14.686, 14.823], list(map(lambda x: x.value, dos.conditions.scalars))) self.assertEquals([0.0, 0.0, -1.19974e-35, -3.6470000000000002e-30, -1.3654e-25, -2.0122999999999998e-21, -1.1612e-17, -2.5870000000000001e-14, -2.3158e-11, -8.1289999999999995e-09, -1.1086000000000001e-06, -5.7370000000000001e-05, -0.0010558, -0.0053100000000000005, 0.0099659999999999992, 0.09085, 0.12007000000000001, 0.035970000000000002, -0.0050520000000000001, -0.002444, -0.00020777999999999999, -5.8720000000000007e-06, -6.1280000000000003e-08, -2.4453999999999996e-10, -3.7849999999999995e-13, -2.3017e-16, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.0769999999999999e-36, -1.263846e-31, -4.5653699999999997e-27, -6.5055699999999999e-23, -3.6695199999999999e-19, -7.9435000000000008e-16, -7.0263000000000001e-13, -2.4759000000000002e-10, -3.4771000000000001e-08, -1.9404999999999999e-06, -4.2440999999999996e-05, -0.00034220000000000002, -0.00067650000000000002, 0.0028322, 0.017154000000000003, 0.04342, 0.058620000000000005, 0.043749999999999997, 0.025759999999999998, 0.018255, 0.020630000000000003, 0.040410000000000001, 0.070239999999999997, 0.089269999999999988, 0.10810999999999998, 0.11366000000000001, 0.066860000000000003, 0.014122000000000001, -0.0024438999999999997, -0.0013060000000000001, -0.00014683900000000001, -5.8520999999999994e-06, -2.7914999999999999e-06, -5.1669999999999998e-05, -0.00035110000000000002, -0.00036900000000000002, 0.003519, 0.012931, 0.030180000000000002, 0.080740000000000006, 0.14502999999999999, 0.14307999999999998, 0.11418, 0.10038, 0.07102, 0.02673, 0.0029481000000000004, -0.0012769000000000001, -0.00048329999999999998, -5.4889999999999998e-05, -2.3511000000000002e-06, -3.941e-08, -2.6148000000000001e-10, -6.892999999999999e-13, -7.2260000000000005e-16, -1.4030000000000001e-19, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -2.361e-35, -1.513e-30, -3.6580000027900005e-26, -3.4550000174800002e-22, -1.24900004155e-18, -1.8020003855000002e-15, -1.0360013670000001e-12, -2.38501934e-10, -2.2271089e-08, -8.632447e-07, -1.4562029999999999e-05, -0.00011538919999999999, -0.00040824000000000004, 0.00026865999999999999, 0.0074427299999999998, 0.024236000000000001, 0.037592, 0.039448999999999998, 0.040390000000000002, 0.047368, 0.045290000000000004, 0.043109999999999996, 0.065069999999999989, 0.084000000000000005, 0.08388000000000001, 0.078009999999999996, 0.066009999999999999, 0.051519999999999996, 0.046550000000000001, 0.055629999999999999, 0.074740000000000001, 0.097983000000000001, 0.086382, 0.063489999999999991, 0.072400000000000006, 0.058990000000000001, 0.038935999999999998, 0.030331999999999998, 0.029690000000000001, 0.037170000000000002, 0.04317, 0.044810000000000003, 0.057980000000000004, 0.075889999999999999, 0.087109999999999993, 0.089520000000000002, 0.088499999999999995, 0.090439999999999993, 0.096759999999999999, 0.1026, 0.10458999999999999, 0.10609, 0.092800000000000007, 0.056925999999999997, 0.017107000000000001, 0.0022797, 0.0054678000000000001, 0.0087969099999999998, 0.0086576974000000008, 0.0093789968080000008, 0.0110199999868, 0.01219999999997858, 0.0067749999999999868, 0.0029060000000000002, 0.0047070000000000002, 0.0056299999999999996, 0.0087919999999999995, 0.01132, 0.0086099999999999996, 0.0044559999999999999, 0.0055139999999994412, 0.0090759999996227001, 0.0097889998984000016, 0.01070998865, 0.0092994370999999985, 0.0061547299999999997, 0.0065844000000000007, 0.0091786999999999997, 0.006215, 0.0083759999999999998, 0.068430000000000005, 0.21668999999999999, 0.37070000000000003, 0.47799999999999998, 0.36899999999999999, 0.13123000000000001, 0.018269000000000001, 0.011729999999999999, 0.022500600000000003, 0.02993055, 0.034198961999999999, 0.042799988399999996, 0.061819999945499998, 0.079549999999893997, 0.070929999999999924, 0.039800000000000002, 0.016230000000000001, 0.01172, 0.01259, 0.0074139999999999996, 0.00513, 0.003588, 0.00072320000000000001, -0.0001964, -6.6060000000000001e-05, -5.1070000000000004e-06, -1.346e-07, -1.308e-09, -4.815e-12, -6.7919999999999999e-15, -3.743e-18, 0.0, 0.0, 0.0, 0.0, 0.0], list(map(lambda x: x.value, dos.scalars))) total_mag = parser.get_total_magnetization() assert(total_mag.scalars[0].value == 3.9999992) assert(total_mag.units == "Bohr") # test number of atoms natoms = parser.get_number_of_atoms() self.assertEqual(natoms.scalars[0].value, 5) self.assertEqual(natoms.units, '/unit cell') # test volumes initial_volume = parser.get_initial_volume() self.assertAlmostEqual(initial_volume.scalars[0].value, 61.15) self.assertEqual(initial_volume.units, "Angstrom^3/cell") final_volume = parser.get_final_volume() self.assertAlmostEqual(final_volume.scalars[0].value, 59.73) self.assertEqual(final_volume.units, "Angstrom^3/cell") # Delete the data delete_example('perov_relax_U') def test_AlNi(self): parser = self.get_parser('AlNi_static_LDA') self._evaluate_AlNi(parser) delete_example('AlNi_static_LDA') def test_AlNi_without_incar(self): """Make sure AlNi test also works without an INCAR an INCAR still parses""" parser = self.get_parser('AlNi_static_LDA') os.unlink(os.path.join('AlNi_static_LDA','INCAR')) self._evaluate_AlNi(parser) delete_example('AlNi_static_LDA') def _evaluate_AlNi(self, parser): """Test that AlNi was parsed correctly""" # Test the settings self.assertEquals('VASP', parser.get_name()) strc = parser.get_output_structure() self.assertAlmostEquals(2.8333249999999999, strc.cell[0][0]) self.assertEquals(['Al','Ni'], strc.get_chemical_symbols()) self.assertEquals('AlNi', parser.get_composition()) res = parser.get_cutoff_energy() self.assertEquals(650, res.scalars[0].value) self.assertEquals('eV', res.units) self.assertTrue(parser.is_converged().scalars[0].value) res = parser.get_total_energy() self.assertAlmostEqual(-12.19669689, res.scalars[0].value) self.assertEquals('eV', res.units) self.assertEquals(None, parser.uses_SOC()) self.assertEquals(None, parser.is_relaxed()) self.assertEquals('PAW', parser.get_xc_functional().scalars[0].value) self.assertEquals(['Al','Ni'], list(map(lambda x: x.value, parser.get_pp_name().vectors[0]))) self.assertEquals(8192, parser.get_KPPRA().scalars[0].value) self.assertEquals('5.3.2', parser.get_version_number()) self.assertEquals(None, parser.get_U_settings()) self.assertEquals(None, parser.get_vdW_settings()) self.assertEquals(12.96, parser.get_pressure().scalars[0].value) self.assertEquals('kbar', parser.get_pressure().units) self.assertEquals([[12.96023,0,0],[0,12.96023,0],[0,0,12.96023]], list(map(lambda x: list(map(lambda y: y.value, x)), parser.get_stresses().matrices[0]))) self.assertEquals('kbar', parser.get_stresses().units) self.assertEquals(0, parser.get_band_gap().scalars[0].value) self.assertEquals('eV', parser.get_band_gap().units) dos = parser.get_dos() self.assertEquals([-3.0259999999999998, -2.903, -2.7810000000000001, -2.6579999999999999, -2.5350000000000001, -2.4119999999999999, -2.2890000000000001, -2.1659999999999999, -2.044, -1.921, -1.798, -1.675, -1.552, -1.4299999999999999, -1.3069999999999999, -1.1839999999999999, -1.0609999999999999, -0.93799999999999994, -0.81599999999999995, -0.69299999999999995, -0.56999999999999995, -0.44700000000000001, -0.32400000000000001, -0.20200000000000001, -0.079000000000000001, 0.043999999999999997, 0.16700000000000001, 0.28999999999999998, 0.41199999999999998, 0.53500000000000003, 0.65800000000000003, 0.78100000000000003, 0.90400000000000003, 1.026, 1.149, 1.272, 1.395, 1.518, 1.6399999999999999, 1.7629999999999999, 1.8859999999999999, 2.0089999999999999, 2.1320000000000001, 2.2549999999999999, 2.3769999999999998, 2.5, 2.6230000000000002, 2.746, 2.8690000000000002, 2.9910000000000001, 3.1139999999999999, 3.2370000000000001, 3.3599999999999999, 3.4830000000000001, 3.605, 3.7280000000000002, 3.851, 3.9740000000000002, 4.0970000000000004, 4.2190000000000003, 4.3419999999999996, 4.4649999999999999, 4.5880000000000001, 4.7110000000000003, 4.8330000000000002, 4.9560000000000004, 5.0789999999999997, 5.202, 5.3250000000000002, 5.4470000000000001, 5.5700000000000003, 5.6929999999999996, 5.8159999999999998, 5.9390000000000001, 6.0620000000000003, 6.1840000000000002, 6.3070000000000004, 6.4299999999999997, 6.5529999999999999, 6.6760000000000002, 6.798, 6.9210000000000003, 7.0439999999999996, 7.1669999999999998, 7.29, 7.4119999999999999, 7.5350000000000001, 7.6580000000000004, 7.7809999999999997, 7.9039999999999999, 8.0259999999999998, 8.1489999999999991, 8.2720000000000002, 8.3949999999999996, 8.5180000000000007, 8.6400000000000006, 8.7629999999999999, 8.8859999999999992, 9.0090000000000003, 9.1319999999999997, 9.2539999999999996, 9.3770000000000007, 9.5, 9.6229999999999993, 9.7460000000000004, 9.8689999999999998, 9.9909999999999997, 10.114000000000001, 10.237, 10.359999999999999, 10.483000000000001, 10.605, 10.728, 10.851000000000001, 10.974, 11.097, 11.218999999999999, 11.342000000000001, 11.465, 11.587999999999999, 11.711, 11.833, 11.956, 12.079000000000001, 12.202, 12.324999999999999, 12.446999999999999, 12.57, 12.693, 12.816000000000001, 12.939, 13.061, 13.183999999999999, 13.307, 13.43, 13.553000000000001, 13.675000000000001, 13.798, 13.920999999999999, 14.044, 14.167, 14.289999999999999, 14.412000000000001, 14.535, 14.657999999999999, 14.781000000000001, 14.904, 15.026, 15.148999999999999, 15.272, 15.395, 15.518000000000001, 15.640000000000001, 15.763, 15.885999999999999, 16.009, 16.132000000000001, 16.254000000000001, 16.376999999999999, 16.5, 16.623000000000001, 16.745999999999999, 16.867999999999999, 16.991, 17.114000000000001, 17.236999999999998, 17.359999999999999, 17.481999999999999, 17.605, 17.728000000000002, 17.850999999999999, 17.974, 18.097000000000001, 18.219000000000001, 18.341999999999999, 18.465, 18.588000000000001, 18.710999999999999, 18.832999999999998, 18.956, 19.079000000000001, 19.202000000000002, 19.324999999999999, 19.446999999999999, 19.57, 19.693000000000001, 19.815999999999999, 19.939, 20.061, 20.184000000000001, 20.306999999999999, 20.43, 20.553000000000001, 20.675000000000001, 20.797999999999998, 20.920999999999999, 21.044, 21.167000000000002, 21.289000000000001, 21.411999999999999, 21.535, 21.658000000000001, 21.780999999999999, 21.902999999999999, 22.026, 22.149000000000001, 22.271999999999998, 22.395, 22.518000000000001, 22.640000000000001, 22.763000000000002, 22.885999999999999, 23.009, 23.132000000000001, 23.254000000000001, 23.376999999999999, 23.5, 23.623000000000001, 23.745999999999999, 23.867999999999999, 23.991, 24.114000000000001, 24.236999999999998, 24.359999999999999, 24.481999999999999, 24.605, 24.728000000000002, 24.850999999999999, 24.974, 25.096, 25.219000000000001, 25.341999999999999, 25.465, 25.588000000000001, 25.710000000000001, 25.832999999999998, 25.956, 26.079000000000001, 26.202000000000002, 26.324999999999999, 26.446999999999999, 26.57, 26.693000000000001, 26.815999999999999, 26.939, 27.061, 27.184000000000001, 27.306999999999999, 27.43, 27.553000000000001, 27.675000000000001, 27.797999999999998, 27.920999999999999, 28.044, 28.167000000000002, 28.289000000000001, 28.411999999999999, 28.535, 28.658000000000001, 28.780999999999999, 28.902999999999999, 29.026, 29.149000000000001, 29.271999999999998, 29.395, 29.516999999999999, 29.640000000000001, 29.763000000000002, 29.885999999999999, 30.009, 30.131, 30.254000000000001, 30.376999999999999, 30.5, 30.623000000000001, 30.745999999999999, 30.867999999999999, 30.991, 31.114000000000001, 31.236999999999998, 31.359999999999999, 31.481999999999999, 31.605, 31.728000000000002, 31.850999999999999, 31.974, 32.095999999999997, 32.219000000000001, 32.341999999999999, 32.465000000000003, 32.588000000000001, 32.710000000000001, 32.832999999999998, 32.956000000000003, 33.079000000000001, 33.201999999999998, 33.323999999999998, 33.447000000000003, 33.57, 33.692999999999998, 33.816000000000003], list(map(lambda x: x.value, dos.conditions.scalars))) self.assertEquals('eV', dos.conditions.units) self.assertEquals([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.034779999999999998, 0.058860000000000003, 0.087639999999999996, 0.097239999999999993, 0.11268, 0.12908, 0.13766, 0.14779999999999999, 0.15936, 0.17232, 0.17985999999999999, 0.18837999999999999, 0.19753999999999999, 0.20760000000000001, 0.21779999999999999, 0.22600000000000001, 0.23419999999999999, 0.2422, 0.25080000000000002, 0.26000000000000001, 0.27000000000000002, 0.27900000000000003, 0.28699999999999998, 0.29499999999999998, 0.3044, 0.31419999999999998, 0.32419999999999999, 0.33460000000000001, 0.3448, 0.35659999999999997, 0.36940000000000001, 0.38340000000000002, 0.39860000000000001, 0.41520000000000001, 0.43580000000000002, 0.45839999999999997, 0.46700000000000003, 0.47920000000000001, 0.49320000000000003, 0.50960000000000005, 0.53200000000000003, 0.5534, 0.56879999999999997, 0.6048, 0.63600000000000001, 0.65880000000000005, 0.71020000000000005, 0.75839999999999996, 0.65300000000000002, 0.623, 0.61660000000000004, 0.62480000000000002, 0.63859999999999995, 0.66200000000000003, 0.7016, 0.76400000000000001, 0.82920000000000005, 0.96719999999999995, 1.7285999999999999, 2.1680000000000001, 1.8826000000000001, 1.599, 1.4379999999999999, 1.5680000000000001, 2.4300000000000002, 2.4079999999999999, 3.5880000000000001, 2.9319999999999999, 2.742, 1.9369000000000001, 0.71629999999999994, 3.5699999999999998, 4.3099999999999996, 3.242, 4.4660000000000002, 8.8300000000000001, 5.7919999999999998, 5.1760000000000002, 4.0540000000000003, 2.8900000000000001, 0.88260000000000005, 0.7258, 0.62339999999999995, 0.52700000000000002, 0.35659999999999997, 0.4929, 0.65859999999999996, 2.6619999999999999, 1.5973999999999999, 1.3284, 1.1026, 0.9264, 0.83499999999999996, 0.7722, 0.7046, 0.6482, 0.60140000000000005, 0.5484, 0.51039999999999996, 0.47660000000000002, 0.44700000000000001, 0.41199999999999998, 0.38600000000000001, 0.35539999999999999, 0.2994, 0.26019999999999999, 0.26479999999999998, 0.309, 0.35599999999999998, 0.3886, 0.44440000000000002, 0.5766, 0.6976, 0.73719999999999997, 0.80220000000000002, 0.8226, 0.89459999999999995, 0.86519999999999997, 0.82620000000000005, 0.78720000000000001, 0.77880000000000005, 0.83579999999999999, 0.74099999999999999, 0.73340000000000005, 0.7944, 0.73919999999999997, 0.73199999999999998, 0.74119999999999997, 0.69840000000000002, 0.73860000000000003, 0.71079999999999999, 0.70199999999999996, 0.77439999999999998, 0.74460000000000004, 0.79279999999999995, 0.89900000000000002, 0.82720000000000005, 0.81620000000000004, 0.85199999999999998, 0.85819999999999996, 0.876, 0.87819999999999998, 0.89100000000000001, 0.89880000000000004, 0.874, 0.85399999999999998, 0.85719999999999996, 0.8518, 0.84819999999999995, 0.83499999999999996, 0.8206, 0.80500000000000005, 0.78900000000000003, 0.77400000000000002, 0.75880000000000003, 0.753, 0.75580000000000003, 0.75080000000000002, 0.73280000000000001, 0.71079999999999999, 0.69040000000000001, 0.65900000000000003, 0.66139999999999999, 0.67700000000000005, 0.70620000000000005, 0.74180000000000001, 0.79459999999999997, 0.878, 0.98299999999999998, 1.0628, 1.1044, 1.0998000000000001, 1.0371999999999999, 0.92179999999999995, 0.85260000000000002, 0.80100000000000005, 0.75239999999999996, 0.70079999999999998, 0.66920000000000002, 0.65180000000000005, 0.64159999999999995, 0.63300000000000001, 0.62760000000000005, 0.62780000000000002, 0.64059999999999995, 0.66620000000000001, 0.6784, 0.68300000000000005, 0.67479999999999996, 0.6804, 0.755, 0.7802, 0.80659999999999998, 0.82120000000000004, 0.83640000000000003, 0.85660000000000003, 0.90500000000000003, 0.90880000000000005, 0.88019999999999998, 0.86419999999999997, 0.84719999999999995, 0.82740000000000002, 0.80020000000000002, 0.75800000000000001, 0.69979999999999998, 0.71360000000000001, 0.90400000000000003, 0.9768, 1.123, 1.2014, 0.93259999999999998, 0.81240000000000001, 0.71319999999999995, 0.65780000000000005, 0.65639999999999998, 0.6472, 0.62829999999999997, 0.63440000000000007, 0.6885, 0.76059999999999994, 0.83579999999999999, 0.93270000000000008, 1.0291000000000001, 1.0882000000000001, 1.0954000000000002, 1.0880999999999998, 1.0526, 0.98049999999999993, 0.86430000000000007, 0.8085, 0.41639999999999999, 0.29980000000000001, 0.24840000000000001, 0.1825, 0.13319999999999999, 0.091359999999999997, 0.065560000000000007, 0.048509999999999998, 0.039219999999999998, 0.030629999999999998, 0.02239, 0.016642000000000001, 0.015498000000000001, 0.01456, 0.013663, 0.012806999999999999, 0.011991, 0.011218000000000001, 0.010484, 0.009777000000000001, 0.0090940000000000014, 0.0084370000000000001, 0.0079260000000000008, 0.0081139999999999997, 0.0071549999999999999, 0.0062389999999999998, 0.0053679999999999995, 0.0045409999999999999, 0.0037580000000000001, 0.003019, 0.00232, 0.0016800999999999999, 0.0011435, 0.00070980000000000001, 0.0003791, 0.00015118999999999999, 2.6239999999999999e-05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], list(map(lambda x: x.value, dos.scalars))) self.assertEquals('number of states per unit cell', dos.units) # test number of atoms natoms = parser.get_number_of_atoms() self.assertEqual(natoms.scalars[0].value, 2) self.assertEqual(natoms.units, '/unit cell') # test volumes initial_volume = parser.get_initial_volume() self.assertAlmostEqual(initial_volume.scalars[0].value, 22.75) self.assertEqual(initial_volume.units, "Angstrom^3/cell") final_volume = parser.get_final_volume() self.assertAlmostEqual(final_volume.scalars[0].value, 22.75) self.assertEqual(final_volume.units, "Angstrom^3/cell") def test_SOC(self): # Parse the results parser = self.get_parser('heusler_static_SOC') # Test the settings self.assertEquals('VASP', parser.get_name()) res = parser.get_cutoff_energy() self.assertEquals(499, res.scalars[0].value) self.assertEquals('eV', res.units) # Make sure it gets the last ionic step strc = parser.get_output_structure() self.assertAlmostEquals(3.3681598291240786, strc.cell[1][0]) self.assertEquals(['Li','Pt','Sn','Y'], strc.get_chemical_symbols()) self.assertEquals('LiPtSnY', parser.get_composition()) self.assertTrue(parser.is_converged()) self.assertAlmostEqual(-22.273992, parser.get_total_energy().scalars[0].value) self.assertTrue(isinstance(parser.uses_SOC(), Value)) self.assertEquals(None, parser.is_relaxed()) self.assertEquals('PAW_PBE', parser.get_xc_functional().scalars[0].value) self.assertEquals(['Li_sv','Pt','Sn_d','Y_sv'], list(map(lambda x: x.value, parser.get_pp_name().vectors[0]))) self.assertEquals(1440, parser.get_KPPRA().scalars[0].value) self.assertEquals('5.2.11', parser.get_version_number()) self.assertEquals(None, parser.get_U_settings()) self.assertEquals(None, parser.get_vdW_settings()) self.assertEquals(None, parser.get_pressure()) self.assertEquals(None, parser.get_stresses()) self.assertEquals(0.757, parser.get_band_gap().scalars[0].value) dos = parser.get_dos() self.assertEquals([-42.363, -42.173000000000002, -41.984000000000002, -41.795000000000002, -41.604999999999997, -41.415999999999997, -41.226999999999997, -41.036999999999999, -40.847999999999999, -40.658000000000001, -40.469000000000001, -40.280000000000001, -40.090000000000003, -39.901000000000003, -39.710999999999999, -39.521999999999998, -39.332999999999998, -39.143000000000001, -38.954000000000001, -38.764000000000003, -38.575000000000003, -38.386000000000003, -38.195999999999998, -38.006999999999998, -37.817, -37.628, -37.439, -37.249000000000002, -37.060000000000002, -36.871000000000002, -36.680999999999997, -36.491999999999997, -36.302, -36.113, -35.923999999999999, -35.734000000000002, -35.545000000000002, -35.354999999999997, -35.165999999999997, -34.976999999999997, -34.786999999999999, -34.597999999999999, -34.408000000000001, -34.219000000000001, -34.030000000000001, -33.840000000000003, -33.651000000000003, -33.462000000000003, -33.271999999999998, -33.082999999999998, -32.893000000000001, -32.704000000000001, -32.515000000000001, -32.325000000000003, -32.136000000000003, -31.946000000000002, -31.757000000000001, -31.568000000000001, -31.378, -31.189, -30.998999999999999, -30.809999999999999, -30.620999999999999, -30.431000000000001, -30.242000000000001, -30.053000000000001, -29.863, -29.673999999999999, -29.484000000000002, -29.295000000000002, -29.106000000000002, -28.916, -28.727, -28.536999999999999, -28.347999999999999, -28.158999999999999, -27.969000000000001, -27.780000000000001, -27.59, -27.401, -27.212, -27.021999999999998, -26.832999999999998, -26.643999999999998, -26.454000000000001, -26.265000000000001, -26.074999999999999, -25.885999999999999, -25.696999999999999, -25.507000000000001, -25.318000000000001, -25.128, -24.939, -24.75, -24.559999999999999, -24.370999999999999, -24.181000000000001, -23.992000000000001, -23.803000000000001, -23.613, -23.423999999999999, -23.234999999999999, -23.045000000000002, -22.856000000000002, -22.666, -22.477, -22.288, -22.097999999999999, -21.908999999999999, -21.719000000000001, -21.530000000000001, -21.341000000000001, -21.151, -20.962, -20.771999999999998, -20.582999999999998, -20.393999999999998, -20.204000000000001, -20.015000000000001, -19.824999999999999, -19.635999999999999, -19.446999999999999, -19.257000000000001, -19.068000000000001, -18.879000000000001, -18.689, -18.5, -18.309999999999999, -18.120999999999999, -17.931999999999999, -17.742000000000001, -17.553000000000001, -17.363, -17.173999999999999, -16.984999999999999, -16.795000000000002, -16.606000000000002, -16.416, -16.227, -16.038, -15.848000000000001, -15.659000000000001, -15.470000000000001, -15.279999999999999, -15.090999999999999, -14.901, -14.712, -14.523, -14.333, -14.144, -13.954000000000001, -13.765000000000001, -13.576000000000001, -13.385999999999999, -13.196999999999999, -13.007, -12.818, -12.629, -12.439, -12.25, -12.061, -11.871, -11.682, -11.492000000000001, -11.303000000000001, -11.114000000000001, -10.923999999999999, -10.734999999999999, -10.545, -10.356, -10.167, -9.9770000000000003, -9.7880000000000003, -9.5980000000000008, -9.4090000000000007, -9.2200000000000006, -9.0299999999999994, -8.8409999999999993, -8.6519999999999992, -8.4619999999999997, -8.2729999999999997, -8.0830000000000002, -7.8940000000000001, -7.7050000000000001, -7.5149999999999997, -7.3259999999999996, -7.1360000000000001, -6.9470000000000001, -6.758, -6.5679999999999996, -6.3789999999999996, -6.1890000000000001, -6.0, -5.8109999999999999, -5.6210000000000004, -5.4320000000000004, -5.2430000000000003, -5.0529999999999999, -4.8639999999999999, -4.6740000000000004, -4.4850000000000003, -4.2960000000000003, -4.1059999999999999, -3.9169999999999998, -3.7269999999999999, -3.5379999999999998, -3.3490000000000002, -3.1589999999999998, -2.9700000000000002, -2.7799999999999998, -2.5910000000000002, -2.4020000000000001, -2.2120000000000002, -2.0230000000000001, -1.833, -1.6439999999999999, -1.4550000000000001, -1.2649999999999999, -1.0760000000000001, -0.88700000000000001, -0.69699999999999995, -0.50800000000000001, -0.318, -0.129, 0.059999999999999998, 0.25, 0.439, 0.629, 0.81799999999999995, 1.0069999999999999, 1.1970000000000001, 1.3859999999999999, 1.5760000000000001, 1.7649999999999999, 1.954, 2.1440000000000001, 2.3330000000000002, 2.5219999999999998, 2.7120000000000002, 2.9009999999999998, 3.0910000000000002, 3.2799999999999998, 3.4689999999999999, 3.6589999999999998, 3.8479999999999999, 4.0380000000000003, 4.2270000000000003, 4.4160000000000004, 4.6059999999999999, 4.7949999999999999, 4.9850000000000003, 5.1740000000000004, 5.3630000000000004, 5.5529999999999999, 5.742, 5.931, 6.1210000000000004, 6.3099999999999996, 6.5, 6.6890000000000001, 6.8780000000000001, 7.0679999999999996, 7.2569999999999997, 7.4470000000000001, 7.6360000000000001, 7.8250000000000002, 8.0150000000000006, 8.2040000000000006, 8.3940000000000001, 8.5830000000000002, 8.7720000000000002, 8.9619999999999997, 9.1509999999999998, 9.3399999999999999, 9.5299999999999994, 9.7189999999999994, 9.9090000000000007, 10.098000000000001, 10.287000000000001, 10.477, 10.666, 10.856, 11.045, 11.234, 11.423999999999999, 11.613, 11.803000000000001, 11.992000000000001, 12.180999999999999, 12.371, 12.56, 12.749000000000001, 12.939, 13.128, 13.318, 13.507, 13.696, 13.885999999999999, 14.074999999999999, 14.265000000000001, 14.454000000000001], list(map(lambda x: x.value, dos.conditions.scalars))) self.assertEquals([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 10.56, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 10.56, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 9.6470000000000002, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.6320000000000001, 6.9969999999999999, 21.120000000000001, 0.0, 0.0, 0.0, 0.0, 31.149999999999999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.040309999999999999, 0.57709999999999995, 0.31590000000000001, 0.26400000000000001, 0.21940000000000001, 0.22090000000000001, 0.25740000000000002, 0.28789999999999999, 3.5, 2.7050000000000001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.61719999999999997, 1.3440000000000001, 2.7330000000000001, 3.1349999999999998, 4.6900000000000004, 2.9540000000000002, 4.0010000000000003, 4.2530000000000001, 6.0140000000000002, 2.2869999999999999, 1.278, 3.1720000000000002, 5.4370000000000003, 6.3730000000000002, 3.6629999999999998, 1.8360000000000001, 1.4099999999999999, 0.98019999999999996, 0.94330000000000003, 0.65300000000000002, 1.74, 1.8180000000000001, 2.1400000000000001, 2.0209999999999999, 2.2629999999999999, 1.446, 0.72999999999999998, 1.3420000000000001, 0.0, 0.0, 1.1880000000000001e-13, 0.99199999999999999, 0.37909999999999999, 1.0660000000000001, 2.2519999999999998, 1.728, 2.125, 1.841, 1.766, 2.1459999999999999, 4.468, 6.1970000000000001, 6.0819999999999999, 2.77, 1.9319999999999999, 1.4470000000000001, 4.2309999999999999, 2.5150000000000001, 0.52410000000000001, 0.2462, 0.20069999999999999, 0.12670000000000001, 0.091480000000000006, 0.05867, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], list(map(lambda x: x.value, dos.scalars))) positions = parser.get_positions() xyz = list(map(lambda x: list(map(lambda y: y.value, x)), positions.vectors)) self.assertEqual([[5.05224, 5.05224, 5.05224], [1.68408, 1.68408, 1.68408], [3.36817, 3.36817, 3.36817], [0.0, 0.0, 0.0]], xyz) forces = parser.get_forces() for f in forces.vectors: for x in f: self.assertAlmostEqual(0.0, x.value) # test number of atoms natoms = parser.get_number_of_atoms() self.assertEqual(natoms.scalars[0].value, 4) self.assertEqual(natoms.units, '/unit cell') # test volumes initial_volume = parser.get_initial_volume() self.assertAlmostEqual(initial_volume.scalars[0].value, 76.42) self.assertEqual(initial_volume.units, "Angstrom^3/cell") final_volume = parser.get_final_volume() self.assertAlmostEqual(final_volume.scalars[0].value, 76.42) self.assertEqual(final_volume.units, "Angstrom^3/cell") # Delete the data delete_example('heusler_static_SOC') def test_vdW(self): # Parse the results parser = self.get_parser('vdW') # Test the settings self.assertEquals('VASP', parser.get_name()) strc = parser.get_output_structure() self.assertAlmostEquals(-12.6699720530641162, strc.cell[1][0]) self.assertEquals(['C']*48, strc.get_chemical_symbols()[:48]) self.assertEquals('Br16C48Fe6H48N12S12', parser.get_composition()) res = parser.get_cutoff_energy() self.assertEquals(520, res.scalars[0].value) self.assertEquals('eV', res.units) self.assertTrue(parser.is_converged().scalars[0].value) self.assertAlmostEqual(-707.48169596, parser.get_total_energy().scalars[0].value) self.assertEquals(None, parser.uses_SOC()) self.assertTrue(isinstance(parser.is_relaxed(), Value)) self.assertEquals('PAW_PBE', parser.get_xc_functional().scalars[0].value) self.assertEquals(['C','H','Br','Fe','N','S'], list(map(lambda x: x.value, parser.get_pp_name().vectors[0]))) self.assertEquals(142, parser.get_KPPRA().scalars[0].value) self.assertEquals('5.3.5', parser.get_version_number()) self.assertEquals(None, parser.get_U_settings()) self.assertEquals('optB88-vdW', parser.get_vdW_settings().scalars[0].value) self.assertEquals(-0.07, parser.get_pressure().scalars[0].value) self.assertEquals([[-4.09956,0,0],[0,-4.09956,0],[0,0,-4.00192]], list(map(lambda x: list(map(lambda y: y.value, x)), parser.get_stresses().matrices[0]))) self.assertEquals(0, parser.get_band_gap().scalars[0].value) dos = parser.get_dos() self.assertEquals([-22.135000000000002, -22.029, -21.923999999999999, -21.818999999999999, -21.713000000000001, -21.608000000000001, -21.501999999999999, -21.396999999999998, -21.291, -21.186, -21.079999999999998, -20.975000000000001, -20.869, -20.763999999999999, -20.658000000000001, -20.553000000000001, -20.448, -20.341999999999999, -20.236999999999998, -20.131, -20.026, -19.920000000000002, -19.815000000000001, -19.709, -19.603999999999999, -19.498000000000001, -19.393000000000001, -19.288, -19.181999999999999, -19.077000000000002, -18.971, -18.866, -18.760000000000002, -18.655000000000001, -18.548999999999999, -18.443999999999999, -18.338000000000001, -18.233000000000001, -18.128, -18.021999999999998, -17.917000000000002, -17.811, -17.706, -17.600000000000001, -17.495000000000001, -17.388999999999999, -17.283999999999999, -17.178000000000001, -17.073, -16.966999999999999, -16.861999999999998, -16.757000000000001, -16.651, -16.545999999999999, -16.440000000000001, -16.335000000000001, -16.228999999999999, -16.123999999999999, -16.018000000000001, -15.913, -15.807, -15.702, -15.597, -15.491, -15.385999999999999, -15.279999999999999, -15.175000000000001, -15.069000000000001, -14.964, -14.858000000000001, -14.753, -14.647, -14.542, -14.436, -14.331, -14.226000000000001, -14.119999999999999, -14.015000000000001, -13.909000000000001, -13.804, -13.698, -13.593, -13.487, -13.382, -13.276, -13.170999999999999, -13.066000000000001, -12.960000000000001, -12.855, -12.749000000000001, -12.644, -12.538, -12.433, -12.327, -12.222, -12.116, -12.010999999999999, -11.906000000000001, -11.800000000000001, -11.695, -11.589, -11.484, -11.378, -11.273, -11.167, -11.061999999999999, -10.956, -10.851000000000001, -10.744999999999999, -10.640000000000001, -10.535, -10.429, -10.324, -10.218, -10.113, -10.007, -9.9019999999999992, -9.7959999999999994, -9.6910000000000007, -9.5850000000000009, -9.4800000000000004, -9.375, -9.2690000000000001, -9.1639999999999997, -9.0579999999999998, -8.9529999999999994, -8.8469999999999995, -8.7420000000000009, -8.6359999999999992, -8.5310000000000006, -8.4250000000000007, -8.3200000000000003, -8.2149999999999999, -8.109, -8.0039999999999996, -7.8979999999999997, -7.7930000000000001, -7.6870000000000003, -7.5819999999999999, -7.476, -7.3710000000000004, -7.2649999999999997, -7.1600000000000001, -7.0540000000000003, -6.9489999999999998, -6.8440000000000003, -6.7380000000000004, -6.633, -6.5270000000000001, -6.4219999999999997, -6.3159999999999998, -6.2110000000000003, -6.1050000000000004, -6.0, -5.8940000000000001, -5.7889999999999997, -5.6840000000000002, -5.5780000000000003, -5.4729999999999999, -5.367, -5.2619999999999996, -5.1559999999999997, -5.0510000000000002, -4.9450000000000003, -4.8399999999999999, -4.734, -4.6289999999999996, -4.5229999999999997, -4.4180000000000001, -4.3129999999999997, -4.2069999999999999, -4.1020000000000003, -3.996, -3.891, -3.7850000000000001, -3.6800000000000002, -3.5739999999999998, -3.4689999999999999, -3.363, -3.258, -3.153, -3.0470000000000002, -2.9420000000000002, -2.8359999999999999, -2.7309999999999999, -2.625, -2.52, -2.4140000000000001, -2.3090000000000002, -2.2029999999999998, -2.0979999999999999, -1.9930000000000001, -1.887, -1.782, -1.6759999999999999, -1.571, -1.4650000000000001, -1.3600000000000001, -1.254, -1.149, -1.0429999999999999, -0.93799999999999994, -0.83199999999999996, -0.72699999999999998, -0.622, -0.51600000000000001, -0.41099999999999998, -0.30499999999999999, -0.20000000000000001, -0.094, 0.010999999999999999, 0.11700000000000001, 0.222, 0.32800000000000001, 0.433, 0.53800000000000003, 0.64400000000000002, 0.749, 0.85499999999999998, 0.95999999999999996, 1.0660000000000001, 1.171, 1.2769999999999999, 1.3819999999999999, 1.488, 1.593, 1.698, 1.804, 1.909, 2.0150000000000001, 2.1200000000000001, 2.226, 2.331, 2.4369999999999998, 2.5419999999999998, 2.6480000000000001, 2.7530000000000001, 2.859, 2.964, 3.069, 3.1749999999999998, 3.2799999999999998, 3.3860000000000001, 3.4910000000000001, 3.597, 3.702, 3.8079999999999998, 3.9129999999999998, 4.0190000000000001, 4.1239999999999997, 4.2290000000000001, 4.335, 4.4400000000000004, 4.5460000000000003, 4.6509999999999998, 4.7569999999999997, 4.8620000000000001, 4.968, 5.0730000000000004, 5.1790000000000003, 5.2839999999999998, 5.3890000000000002, 5.4950000000000001, 5.5999999999999996, 5.7060000000000004, 5.8109999999999999, 5.9169999999999998, 6.0220000000000002, 6.1280000000000001, 6.2329999999999997, 6.3390000000000004, 6.444, 6.5499999999999998, 6.6550000000000002, 6.7599999999999998, 6.8659999999999997, 6.9710000000000001, 7.077, 7.1820000000000004, 7.2880000000000003, 7.3929999999999998, 7.4989999999999997, 7.6040000000000001, 7.71, 7.8150000000000004, 7.9199999999999999, 8.0259999999999998, 8.1310000000000002, 8.2370000000000001, 8.3420000000000005, 8.4480000000000004, 8.5530000000000008, 8.6590000000000007, 8.7639999999999993, 8.8699999999999992, 8.9749999999999996, 9.0809999999999995, 9.1859999999999999, 9.2910000000000004, 9.3970000000000002, 9.5020000000000007], list(map(lambda x: x.value, dos.conditions.scalars))) self.assertEquals([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.6319999999999999e-17, 3.143e-15, 2.6169999999999999e-13, 1.5350000000000001e-11, 6.3450000000000003e-10, 1.85e-08, 3.8080000000000002e-07, 5.5450000000000003e-06, 5.7269999999999999e-05, 0.0004215, 0.0022279999999999999, 0.0085550000000000001, 0.024320000000000001, 0.052359999999999997, 0.087309999999999999, 0.1142, 0.1181, 0.1023, 0.091939999999999994, 0.107, 0.13159999999999999, 0.13059999999999999, 0.094570000000000001, 0.048860000000000001, 0.017909999999999999, 0.004653, 0.00085590000000000004, 0.0001114, 1.025e-05, 6.6710000000000004e-07, 3.0659999999999998e-08, 9.944e-10, 2.2749999999999999e-11, 3.6710000000000002e-13, 4.211e-15, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.6849999999999997e-17, 4.5060000000000002e-15, 3.6630000000000001e-13, 2.1149999999999999e-11, 8.6729999999999999e-10, 2.531e-08, 5.2679999999999998e-07, 7.8390000000000007e-06, 8.3570000000000001e-05, 0.00063960000000000004, 0.0035209999999999998, 0.01397, 0.040129999999999999, 0.084239999999999995, 0.13339999999999999, 0.17269999999999999, 0.20960000000000001, 0.25469999999999998, 0.28050000000000003, 0.24560000000000001, 0.15970000000000001, 0.075359999999999996, 0.026380000000000001, 0.011169999999999999, 0.020629999999999999, 0.056489999999999999, 0.1211, 0.19800000000000001, 0.2586, 0.29349999999999998, 0.31209999999999999, 0.3054, 0.25030000000000002, 0.1585, 0.075039999999999996, 0.02937, 0.020729999999999998, 0.03882, 0.073150000000000007, 0.1066, 0.1186, 0.1008, 0.065310000000000007, 0.031879999999999999, 0.011610000000000001, 0.0034150000000000001, 0.002552, 0.0084089999999999998, 0.025819999999999999, 0.058729999999999997, 0.098680000000000004, 0.1231, 0.11409999999999999, 0.078479999999999994, 0.040129999999999999, 0.016910000000000001, 0.01357, 0.031550000000000002, 0.070419999999999996, 0.1143, 0.13220000000000001, 0.1089, 0.063869999999999996, 0.026679999999999999, 0.0079389999999999999, 0.0016819999999999999, 0.00025619999999999999, 5.9740000000000001e-05, 0.00028899999999999998, 0.0018500000000000001, 0.0087819999999999999, 0.03082, 0.080199999999999994, 0.1552, 0.22389999999999999, 0.24160000000000001, 0.1958, 0.1208, 0.061920000000000003, 0.043180000000000003, 0.065579999999999999, 0.11210000000000001, 0.15129999999999999, 0.15820000000000001, 0.13919999999999999, 0.1203, 0.11260000000000001, 0.1028, 0.078009999999999996, 0.044979999999999999, 0.019029999999999998, 0.0059649999999999998, 0.0023180000000000002, 0.0052659999999999998, 0.018010000000000002, 0.047750000000000001, 0.097589999999999996, 0.1588, 0.20999999999999999, 0.22620000000000001, 0.19950000000000001, 0.15759999999999999, 0.14380000000000001, 0.17199999999999999, 0.21440000000000001, 0.23350000000000001, 0.21890000000000001, 0.19220000000000001, 0.18229999999999999, 0.1951, 0.2117, 0.21820000000000001, 0.219, 0.2167, 0.21029999999999999, 0.2117, 0.23849999999999999, 0.29120000000000001, 0.34539999999999998, 0.36799999999999999, 0.35039999999999999, 0.31669999999999998, 0.29139999999999999, 0.2722, 0.24679999999999999, 0.22059999999999999, 0.2094, 0.21229999999999999, 0.21179999999999999, 0.20000000000000001, 0.18690000000000001, 0.18140000000000001, 0.18840000000000001, 0.21740000000000001, 0.26579999999999998, 0.31019999999999998, 0.33589999999999998, 0.35599999999999998, 0.38740000000000002, 0.42420000000000002, 0.44290000000000002, 0.42880000000000001, 0.3901, 0.34289999999999998, 0.29120000000000001, 0.23169999999999999, 0.1731, 0.13800000000000001, 0.14460000000000001, 0.18640000000000001, 0.2293, 0.2344, 0.19320000000000001, 0.13400000000000001, 0.095130000000000006, 0.091319999999999998, 0.1056, 0.1113, 0.097659999999999997, 0.070879999999999999, 0.042029999999999998, 0.020400000000000001, 0.01214, 0.024029999999999999, 0.068360000000000004, 0.15179999999999999, 0.24809999999999999, 0.29959999999999998, 0.27460000000000001, 0.21390000000000001, 0.18720000000000001, 0.2112, 0.23899999999999999, 0.22289999999999999, 0.16350000000000001, 0.094339999999999993, 0.042779999999999999, 0.01506, 0.004032, 0.00080500000000000005, 0.00013300000000000001, 0.00013970000000000001, 0.00073349999999999999, 0.003088, 0.0099260000000000008, 0.025839999999999998, 0.057540000000000001, 0.11, 0.1724, 0.2135, 0.21379999999999999, 0.1966, 0.19850000000000001, 0.22040000000000001, 0.22919999999999999, 0.1983, 0.1343, 0.070239999999999997, 0.03288, 0.027310000000000001, 0.047260000000000003, 0.086449999999999999, 0.13769999999999999, 0.18809999999999999, 0.2185, 0.2104, 0.1613, 0.095079999999999998, 0.042020000000000002, 0.014149999999999999, 0.005764, 0.0096120000000000008, 0.023990000000000001, 0.048349999999999997, 0.080140000000000003, 0.1201, 0.1731, 0.2354, 0.28839999999999999, 0.31030000000000002, 0.29310000000000003, 0.25169999999999998, 0.21129999999999999, 0.17999999999999999, 0.1449, 0.099610000000000004, 0.054780000000000002, 0.02332, 0.0075259999999999997, 0.0018090000000000001, 0.0003191, 4.0849999999999997e-05, 3.7639999999999999e-06, 2.481e-07, 1.165e-08, 3.8859999999999998e-10, 9.1830000000000008e-12, 1.535e-13, 1.811e-15, 2.106e-17, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], list(map(lambda x: x.value, dos.scalars))) # test number of atoms natoms = parser.get_number_of_atoms() self.assertEqual(natoms.scalars[0].value, 142) self.assertEqual(natoms.units, '/unit cell') # test volumes initial_volume = parser.get_initial_volume() self.assertAlmostEqual(initial_volume.scalars[0].value, 2005.82) self.assertEqual(initial_volume.units, "Angstrom^3/cell") final_volume = parser.get_final_volume() self.assertAlmostEqual(final_volume.scalars[0].value, 2005.73) self.assertEqual(final_volume.units, "Angstrom^3/cell") # Delete the data delete_example('vdW') def test_filename_robustness(self): """Make sure that parser can handle OUTCARs having other extensions""" # Unpack an example and rename the OUTCAR file unpack_example(os.path.join('examples', 'vasp', 'perov_relax_U.tar.gz')) shutil.move(os.path.join('perov_relax_U', 'OUTCAR'), os.path.join('perov_relax_U', 'OUTCAR_newname')) # Make the parser try: parser = VaspParser.generate_from_directory("perov_relax_U") self.assertEquals(parser.get_name(), 'VASP') # Test the cutoff energy res = parser.get_cutoff_energy() self.assertEquals(400, res.scalars[0].value) self.assertEquals('eV', res.units) # Test whether it is converged self.assertTrue(parser.is_converged().scalars[0].value) # Test total energy self.assertAlmostEqual(-39.85550532, parser.get_total_energy().scalars[0].value) finally: delete_example('perov_relax_U') def test_fail_with_multiple_files(self): # Unpack an example and duplicate the OUTCAR file unpack_example(os.path.join('examples', 'vasp', 'perov_relax_U.tar.gz')) shutil.copy(os.path.join('perov_relax_U', 'OUTCAR'), os.path.join('perov_relax_U', 'OUTCAR_newname')) # Make the parser with self.assertRaises(InvalidIngesterException) as context: VaspParser.generate_from_directory('perov_relax_U') # Make the parser, but setting `files` to not include `OUTCAR_newname` acceptable_files = [f for f in os.listdir('perov_relax_U')] acceptable_files.remove('OUTCAR_newname') acceptable_files = [os.path.join('perov_relax_U', f) for f in acceptable_files] try: VaspParser(acceptable_files) finally: delete_example('perov_relax_U') if __name__ == '__main__': unittest.main()

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py

Python

library/.config/calibre/plugins/DeDRM/libraryfiles/subasyncio.py

funkeyfreak/calibre-drm-stripper

90813b644c86543fb423b4fd664685a02b43e525

[ "Apache-2.0" ]

null

library/.config/calibre/plugins/DeDRM/libraryfiles/subasyncio.py

funkeyfreak/calibre-drm-stripper

90813b644c86543fb423b4fd664685a02b43e525

[ "Apache-2.0" ]

null

library/.config/calibre/plugins/DeDRM/libraryfiles/subasyncio.py

funkeyfreak/calibre-drm-stripper

90813b644c86543fb423b4fd664685a02b43e525

[ "Apache-2.0" ]

1

2022-02-05T00:18:21.000Z

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Python

integration-test/343-winter-sports-resorts.py

rinnyB/vector-datasource

024909ed8245a4ad4a25c908413ba3602de6c335

[ "MIT" ]

null

integration-test/343-winter-sports-resorts.py

rinnyB/vector-datasource

024909ed8245a4ad4a25c908413ba3602de6c335

[ "MIT" ]

2

2021-03-31T20:22:37.000Z

2021-12-13T20:50:11.000Z

integration-test/343-winter-sports-resorts.py

rinnyB/vector-datasource

024909ed8245a4ad4a25c908413ba3602de6c335

[ "MIT" ]

null

# -*- encoding: utf-8 -*- from shapely.wkt import loads as wkt_loads import dsl from . import FixtureTest class WinterSportsResorts(FixtureTest): def test_heavenly_mountain_resort(self): # Heavenly Mountain Resort NV/CA self.generate_fixtures(dsl.way(317721523, wkt_loads('POLYGON ((-119.943792366025 38.9318315811565, -119.943406090453 38.93208195867911, -119.943148633292 38.93258278095151, -119.941582240931 38.93413511885359, -119.942264870716 38.93522659155598, -119.942130842075 38.93529968189359, -119.94225687571 38.9354414601634, -119.942742415121 38.9360757904203, -119.942739720175 38.93611855405371, -119.94269004334 38.9361504870115, -119.938846421733 38.93782376785669, -119.938751200313 38.93785695776939, -119.938692180999 38.93785905397387, -119.93861169195 38.9378174093664, -119.93753964249 38.93630085820809, -119.937377227086 38.93621351438268, -119.937251283283 38.93615272301678, -119.937196036893 38.93612596082418, -119.936677529311 38.93581005438838, -119.936152823354 38.93555745400288, -119.93555310807 38.9353437037623, -119.934459768538 38.9350131896996, -119.933534234301 38.93479049362628, -119.931754581891 38.93350077123829, -119.929458577857 38.9320318552936, -119.928578857699 38.93244917278829, -119.927505999755 38.93211536091647, -119.92529578483 38.93104711044089, -119.923407615934 38.9301457200956, -119.922098680734 38.9298118973828, -119.918815607865 38.93047961111808, -119.916197827296 38.93128078942348, -119.914137900518 38.9320318552936, -119.911799046844 38.9332003660422, -119.911133844376 38.9339013793977, -119.911176694015 38.93436871778529, -119.912099443475 38.93490285495809, -119.912271021694 38.93575408409009, -119.911477090646 38.93622141026889, -119.91106943517 38.93677216363341, -119.910597280657 38.93727302265959, -119.910318443593 38.93785709751631, -119.910039426865 38.93832447970939, -119.909460103339 38.9387917889493, -119.9087519614 38.93895871430539, -119.908194107609 38.93887521674029, -119.907893710978 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38.9315812726297, -119.943792366025 38.9318315811565))'), {u'way_area': u'1.8992e+07', u'source': u'openstreetmap.org', u'landuse': u'winter_sports', u'name': u'Heavenly Mountain Resort'})) # noqa self.assert_has_feature( 15, 5467, 12531, 'landuse', {'kind': 'winter_sports', 'sort_rank': 39})

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6735984150c8e3f3481d49e775155f7a88b53640

894

py

Python

17_regex/python/iso_8601.py

pjuangph/python2rust

cc99abe8738e5d1d7d9a34debb2892186ff77965

[ "CC0-1.0" ]

24

2021-07-09T13:56:45.000Z

2022-03-26T19:44:00.000Z

17_regex/python/iso_8601.py

pjuangph/python2rust

cc99abe8738e5d1d7d9a34debb2892186ff77965

[ "CC0-1.0" ]

null

17_regex/python/iso_8601.py

pjuangph/python2rust

cc99abe8738e5d1d7d9a34debb2892186ff77965

[ "CC0-1.0" ]

3

2021-07-09T17:16:31.000Z

2022-03-24T15:44:44.000Z

"Regex to check for ISO 8601 conform dates." import re def is_8601_date(line): # optionally use functools.cache RE = re.compile( r"^(?:(?=[02468][048]00|[13579][26]00|[0-9][0-9]0[48]|[0-9][0-9][2468][048]|[0-9][0-9][13579][26])\d{4}(?:(-|)(?:(?:00[1-9]|0[1-9][0-9]|[1-2][0-9][0-9]|3[0-5][0-9]|36[0-6])|(?:01|03|05|07|08|10|12)(?:\1(?:0[1-9]|[12][0-9]|3[01]))?|(?:04|06|09|11)(?:\1(?:0[1-9]|[12][0-9]|30))?|02(?:\1(?:0[1-9]|[12][0-9]))?|W(?:0[1-9]|[1-4][0-9]|5[0-3])(?:\1[1-7])?))?)$|^(?:(?![02468][048]00|[13579][26]00|[0-9][0-9]0[48]|[0-9][0-9][2468][048]|[0-9][0-9][13579][26])\d{4}(?:(-|)(?:(?:00[1-9]|0[1-9][0-9]|[1-2][0-9][0-9]|3[0-5][0-9]|36[0-5])|(?:01|03|05|07|08|10|12)(?:\2(?:0[1-9]|[12][0-9]|3[01]))?|(?:04|06|09|11)(?:\2(?:0[1-9]|[12][0-9]|30))?|(?:02)(?:\2(?:0[1-9]|1[0-9]|2[0-8]))?|W(?:0[1-9]|[1-4][0-9]|5[0-3])(?:\2[1-7])?))?)$" ) return RE.match(line)

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