xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

1052be7243d9d92006427132097908b44ba62ca1

232

py

Python

src/modules/activations.py

abheesht17/super-pixels

d650ecf5e227bf94d237c9d8eff57c8bbf5b8983

[ "MIT" ]

10

2021-05-20T02:18:30.000Z

2021-12-24T05:21:39.000Z

src/modules/activations.py

abheesht17/super-pixels

d650ecf5e227bf94d237c9d8eff57c8bbf5b8983

[ "MIT" ]

3

2021-05-20T01:19:47.000Z

2022-02-12T16:38:47.000Z

src/modules/activations.py

abheesht17/super-pixels

d650ecf5e227bf94d237c9d8eff57c8bbf5b8983

[ "MIT" ]

4

2021-05-20T01:30:14.000Z

2021-10-02T16:53:06.000Z

import torch.nn as nn from src.utils.mapper import configmapper configmapper.map("activations", "relu")(nn.ReLU) configmapper.map("activations", "logsoftmax")(nn.LogSoftmax) configmapper.map("activations", "softmax")(nn.Softmax)

25.777778

60

0.771552

29

232

6.172414

0.482759

0.251397

0.435754

0

0.073276

232

8

61

29

0.832558

0

0.232759

0

1

0

true

0

0.4

0

0.4

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

109f9d3b6d011c3e0fa01661b64139ed3ed3cd7e

214

py

Python

license_plate_processing/__init__.py

arekmula/license_plate_recognition

62e5374fc56a0709d6d951629449aed347e101d2

[ "MIT" ]

1

2021-02-11T07:16:06.000Z

license_plate_processing/__init__.py

arekmula/license_plate_recognition

62e5374fc56a0709d6d951629449aed347e101d2

[ "MIT" ]

null

license_plate_processing/__init__.py

arekmula/license_plate_recognition

62e5374fc56a0709d6d951629449aed347e101d2

[ "MIT" ]

1

2021-04-06T20:12:15.000Z

from .license_plate_recognizer import recognize_license_plate from .license_plate_recognizer import train_KNN from .character_classifier import get_chars_contour from .character_classifier import train_classifier

35.666667

61

0.901869

28

214

6.464286

0.464286

0.198895

0.176796

0.287293

0.353591

0

0.079439

214

5

62

42.8

0.918782

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

5e13148a6395a94a38b9bc27ab3ced83e32cb807

171

py

Python

examples/print_function.py

dhruvmanila/pyinspect

ce90df243e5e5ee100f13de4329c111454b8c891

[ "MIT" ]

87

2020-09-30T10:18:26.000Z

2022-03-10T08:56:04.000Z

examples/print_function.py

dhruvmanila/pyinspect

ce90df243e5e5ee100f13de4329c111454b8c891

[ "MIT" ]

16

2020-09-30T10:57:17.000Z

2022-01-16T02:10:45.000Z

examples/print_function.py

dhruvmanila/pyinspect

ce90df243e5e5ee100f13de4329c111454b8c891

[ "MIT" ]

5

2020-11-20T07:39:26.000Z

2022-01-13T04:54:51.000Z

""" This tutorial shows how to print a function's source code """ # import pyinspect import pyinspect as pi # Print a function's source code pi.showme(pi.search)

17.1

36

0.71345

27

171

4.518519

0.62963

0.098361

0.229508

0.245902

0.409836

0

0.204678

171

9

37

19

0.897059

0.619883

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

eab067e3356e1c018f23ae9576402fe6bf71b065

317

py

Python

src/common/common.py

glamod/glamod-cdm-lite

026d87d499feaf7ee3611cf1c112384f3819e653

[ "BSD-2-Clause" ]

1

2020-06-16T14:29:26.000Z

src/common/common.py

glamod/glamod-cdm-lite

026d87d499feaf7ee3611cf1c112384f3819e653

[ "BSD-2-Clause" ]

75

2020-01-17T12:25:58.000Z

2021-04-29T14:48:52.000Z

src/common/common.py

glamod/glamod-cdm-lite

026d87d499feaf7ee3611cf1c112384f3819e653

[ "BSD-2-Clause" ]

2

2020-07-03T11:11:04.000Z

2020-08-03T14:19:54.000Z

BASE_INPUT_DIR = '/gws/nopw/j04/c3s311a_lot2/data/marine/r092019/ICOADS_R3.0.0T/level1a' BASE_OUTPUT_DIR = '/gws/nopw/j04/c3s311a_lot2/data/marine/r092019_cdm_lite/ICOADS_R3.0.0T/level1a' BASE_LOG_DIR = '/gws/smf/j04/c3s311a_lot2/cdmlite/log/prep/marine' BASE_SQL_DIR = '/gws/smf/j04/c3s311a_lot2/cdmlite/marine/sql'

63.4

98

0.807571

57

317

4.210526

0.421053

0.1

0.233333

0.108333

0.775

0.591667

0.341667

0

0.157377

0.037855

317

4

99

79.25

0.629508

0

0.5

0.757098

0

1

0

false

0

null

0

1

0

1

0

1

0

1

null

0

6

d81f8b15fcd933e10762cc5ad987f34540611fa2

22

py

Python

paco/__init__.py

fabianlischka/paco

82a3d14df8ccc7628bdafde9dd2a7293be9bf94e

[ "MIT" ]

1

2018-01-18T10:11:31.000Z

paco/__init__.py

fabianlischka/paco

82a3d14df8ccc7628bdafde9dd2a7293be9bf94e

[ "MIT" ]

null

paco/__init__.py

fabianlischka/paco

82a3d14df8ccc7628bdafde9dd2a7293be9bf94e

[ "MIT" ]

null

from pacoRun import *

11

21

0.772727

3

22

5.666667

1

0

0.181818

22

1

22

0.944444

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

d83a264e7589ae042d41f3619803a27354de2102

133

py

Python

lib/glob.py

jplevyak/pyc

9f4bc49be78ba29427841460945ce63826fcd857

[ "BSD-3-Clause" ]

3

2019-08-21T22:01:35.000Z

2021-07-25T00:21:28.000Z

lib/glob.py

jplevyak/pyc

9f4bc49be78ba29427841460945ce63826fcd857

[ "BSD-3-Clause" ]

null

lib/glob.py

jplevyak/pyc

9f4bc49be78ba29427841460945ce63826fcd857

[ "BSD-3-Clause" ]

null

import os, os.path, fnmatch, re def iglob(s): return __iter('') def glob(s): return [''] def init(): pass

11.083333

32

0.518797

18

133

3.722222

0.722222

0.208955

0

0.323308

133

11

33

12.090909

0.744444

0

1

0.428571

false

0.142857

0.285714

0.857143

0

1

0

null

1

0

null

0

1

0

1

0

1

0

6

dc1fd8b5321721f8a223ba65bc79a1349804f6ea

204

py

Python

pylight/__init__.py

en0/pylight

ff91de63a40216484888548d83dcbc2de9d7ddb5

[ "MIT" ]

null

pylight/__init__.py

en0/pylight

ff91de63a40216484888548d83dcbc2de9d7ddb5

[ "MIT" ]

null

pylight/__init__.py

en0/pylight

ff91de63a40216484888548d83dcbc2de9d7ddb5

[ "MIT" ]

null

from pylight.interface import IBacklight, IBacklightManager, IActionBroker from pylight.backlight import Backlight from pylight.backlight_manager import BacklightManager from pylight.action import Action

40.8

74

0.882353

23

204

7.782609

0.478261

0.24581

0.223464

0

0.088235

204

4

75

51

0.962366

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

dc5eb2b80f86a9521d26ee3f67d7a4f539ca0e64

45

py

Python

file_catalog/schema/__init__.py

WIPACrepo/file_catalog

01c0947d32d621d28516ecce3604a0124c673925

[ "MIT" ]

null

file_catalog/schema/__init__.py

WIPACrepo/file_catalog

01c0947d32d621d28516ecce3604a0124c673925

[ "MIT" ]

61

2017-02-23T17:58:43.000Z

2022-03-24T22:13:24.000Z

file_catalog/schema/__init__.py

WIPACrepo/file_catalog

01c0947d32d621d28516ecce3604a0124c673925

[ "MIT" ]

2

2017-12-20T18:30:35.000Z

2018-01-08T15:15:03.000Z

"""Init.""" from . import types, validation

11.25

31

0.644444

5

45

5.8

1

0

0.155556

45

3

32

15

0.763158

0.111111

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

f49934d73c1a4813d11d90412962419c71420029

154

py

Python

credential.py

Reeju2019/Projects

8def4f7c954946a12ba7a063792621038861fcfb

[ "MIT" ]

null

credential.py

Reeju2019/Projects

8def4f7c954946a12ba7a063792621038861fcfb

[ "MIT" ]

null

credential.py

Reeju2019/Projects

8def4f7c954946a12ba7a063792621038861fcfb

[ "MIT" ]

null

account_sid = 'ACb764593ed8f98268235ba1c2768712ed' auth_token = '0e7b1a9daac9f36e8b855a25585b59f2' my_cell = '+918820931166' my_twilio = '+12624563373'

38.5

51

0.818182

12

154

10.166667

0.916667

0

0.464286

0.090909

154

4

52

38.5

0.407143

0

0.598684

0.434211

0

1

0

false

0

1

0

1

null

0

1

0

1

0

1

0

1

null

0

6

f4da6c51345b48463d19edef85bb5472f036fbb5

200

py

Python

pages/views.py

olubiyiontheweb/travelworld

ca9d2206108bd59fd222e384bcaab7efd6832e24

[ "MIT" ]

null

pages/views.py

olubiyiontheweb/travelworld

ca9d2206108bd59fd222e384bcaab7efd6832e24

[ "MIT" ]

null

pages/views.py

olubiyiontheweb/travelworld

ca9d2206108bd59fd222e384bcaab7efd6832e24

[ "MIT" ]

null

from django.shortcuts import render # Create your views here. def index(request): return render(request, "pages/index.html") def base(request): return render(request, "layout/base.html")

16.666667

46

0.725

27

200

5.37037

0.62963

0.17931

0.262069

0.358621

0

0.16

200

11

47

18.181818

0.863095

0.115

0

0.182857

0

1

0.4

false

0

0.2

0.4

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

f4ea8579a8421fbe2f3a224e6a25b3efafe0a274

133

py

Python

LookProjeto/checkout/admin.py

jeffreyquirino/backup_looksistem

46f3d372bb474b32c2fd0b249e1df029380a7925

[ "Apache-2.0" ]

null

LookProjeto/checkout/admin.py

jeffreyquirino/backup_looksistem

46f3d372bb474b32c2fd0b249e1df029380a7925

[ "Apache-2.0" ]

2

2020-06-06T01:14:59.000Z

2021-06-10T22:52:57.000Z

LookProjeto/checkout/admin.py

jeffreyquirino/backup_looksistem

46f3d372bb474b32c2fd0b249e1df029380a7925

[ "Apache-2.0" ]

null

from django.contrib import admin from .models import CartItem, Order, OrderItem admin.site.register([CartItem, Order, OrderItem])

19

49

0.789474

17

133

6.176471

0.647059

0.247619

0.419048

0

0.120301

133

6

50

22.166667

0.897436

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

76091a90147fe417e29516ac5aca6d19f3b6a51a

25,218

py

Python

pyy1/.pycharm_helpers/python_stubs/-1550516950/_datetime.py

pyy1988/pyy_test1

6bea878409e658aa87441384419be51aaab061e7

[ "Apache-2.0" ]

null

pyy1/.pycharm_helpers/python_stubs/-1550516950/_datetime.py

pyy1988/pyy_test1

6bea878409e658aa87441384419be51aaab061e7

[ "Apache-2.0" ]

null

pyy1/.pycharm_helpers/python_stubs/-1550516950/_datetime.py

pyy1988/pyy_test1

6bea878409e658aa87441384419be51aaab061e7

[ "Apache-2.0" ]

null

# encoding: utf-8 # module _datetime # from (built-in) # by generator 1.145 """ Fast implementation of the datetime type. """ # imports import datetime as __datetime # Variables with simple values MAXYEAR = 9999 MINYEAR = 1 # no functions # classes class date(object): """ date(year, month, day) --> date object """ def ctime(self): # real signature unknown; restored from __doc__ """ Return ctime() style string. """ pass @classmethod def fromordinal(cls, ordinal): # known case of _datetime.date.fromordinal """ int -> date corresponding to a proleptic Gregorian ordinal. """ return date(1,1,1) @classmethod def fromtimestamp(cls, timestamp): # known case of _datetime.date.fromtimestamp """ timestamp -> local date from a POSIX timestamp (like time.time()). """ return date(1,1,1) def isocalendar(self): # known case of _datetime.date.isocalendar """ Return a 3-tuple containing ISO year, week number, and weekday. """ return (1, 1, 1) def isoformat(self): # known case of _datetime.date.isoformat """ Return string in ISO 8601 format, YYYY-MM-DD. """ return "" def isoweekday(self): # known case of _datetime.date.isoweekday """ Return the day of the week represented by the date. Monday == 1 ... Sunday == 7 """ return 0 def replace(self, year=None, month=None, day=None): # known case of _datetime.date.replace """ Return date with new specified fields. """ return date(1,1,1) def strftime(self, format): # known case of _datetime.date.strftime """ format -> strftime() style string. """ return "" def timetuple(self): # known case of _datetime.date.timetuple """ Return time tuple, compatible with time.localtime(). """ return (0, 0, 0, 0, 0, 0, 0, 0, 0) @classmethod def today(self): # known case of _datetime.date.today """ Current date or datetime: same as self.__class__.fromtimestamp(time.time()). """ return date(1, 1, 1) def toordinal(self): # known case of _datetime.date.toordinal """ Return proleptic Gregorian ordinal. January 1 of year 1 is day 1. """ return 0 def weekday(self): # known case of _datetime.date.weekday """ Return the day of the week represented by the date. Monday == 0 ... Sunday == 6 """ return 0 def __add__(self, *args, **kwargs): # real signature unknown """ Return self+value. """ pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __format__(self, *args, **kwargs): # real signature unknown """ Formats self with strftime. """ pass def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __hash__(self, *args, **kwargs): # real signature unknown """ Return hash(self). """ pass def __init__(self, year, month, day): # real signature unknown; restored from __doc__ pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass @staticmethod # known case of __new__ def __new__(cls, year=None, month=None, day=None): # known case of _datetime.date.__new__ """ Create and return a new object. See help(type) for accurate signature. """ pass def __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass def __radd__(self, *args, **kwargs): # real signature unknown """ Return value+self. """ pass def __reduce__(self): # real signature unknown; restored from __doc__ """ __reduce__() -> (cls, state) """ pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass def __rsub__(self, *args, **kwargs): # real signature unknown """ Return value-self. """ pass def __str__(self, *args, **kwargs): # real signature unknown """ Return str(self). """ pass def __sub__(self, *args, **kwargs): # real signature unknown """ Return self-value. """ pass day = property(lambda self: 0) """:type: int""" month = property(lambda self: 0) """:type: int""" year = property(lambda self: 0) """:type: int""" max = None # (!) real value is '' min = None # (!) real value is '' resolution = None # (!) real value is '' class datetime(__datetime.date): """ datetime(year, month, day[, hour[, minute[, second[, microsecond[,tzinfo]]]]]) The year, month and day arguments are required. tzinfo may be None, or an instance of a tzinfo subclass. The remaining arguments may be ints. """ def astimezone(self, tz): # known case of _datetime.datetime.astimezone """ tz -> convert to local time in new timezone tz """ return datetime(1, 1, 1) @classmethod def combine(cls, date, time): # known case of _datetime.datetime.combine """ date, time -> datetime with same date and time fields """ return datetime(1, 1, 1) def ctime(self): # real signature unknown; restored from __doc__ """ Return ctime() style string. """ pass def date(self): # known case of _datetime.datetime.date """ Return date object with same year, month and day. """ return datetime(1, 1, 1) def dst(self): # real signature unknown; restored from __doc__ """ Return self.tzinfo.dst(self). """ pass @classmethod def fromtimestamp(cls, timestamp, tz=None): # known case of _datetime.datetime.fromtimestamp """ timestamp[, tz] -> tz's local time from POSIX timestamp. """ return datetime(1, 1, 1) def isoformat(self, sep='T'): # known case of _datetime.datetime.isoformat """ [sep] -> string in ISO 8601 format, YYYY-MM-DDTHH:MM:SS[.mmmmmm][+HH:MM]. sep is used to separate the year from the time, and defaults to 'T'. """ return "" @classmethod def now(cls, tz=None): # known case of _datetime.datetime.now """ Returns new datetime object representing current time local to tz. tz Timezone object. If no tz is specified, uses local timezone. """ return datetime(1, 1, 1) def replace(self, year=None, month=None, day=None, hour=None, minute=None, second=None, microsecond=None, tzinfo=None): # known case of _datetime.datetime.replace """ Return datetime with new specified fields. """ return datetime(1, 1, 1) @classmethod def strptime(cls, date_string, format): # known case of _datetime.datetime.strptime """ string, format -> new datetime parsed from a string (like time.strptime()). """ return "" def time(self): # known case of _datetime.datetime.time """ Return time object with same time but with tzinfo=None. """ return time(0, 0) def timestamp(self, *args, **kwargs): # real signature unknown """ Return POSIX timestamp as float. """ pass def timetuple(self): # known case of _datetime.datetime.timetuple """ Return time tuple, compatible with time.localtime(). """ return (0, 0, 0, 0, 0, 0, 0, 0, 0) def timetz(self): # known case of _datetime.datetime.timetz """ Return time object with same time and tzinfo. """ return time(0, 0) def tzname(self): # real signature unknown; restored from __doc__ """ Return self.tzinfo.tzname(self). """ pass @classmethod def utcfromtimestamp(self, timestamp): # known case of _datetime.datetime.utcfromtimestamp """ Construct a naive UTC datetime from a POSIX timestamp. """ return datetime(1, 1, 1) @classmethod def utcnow(cls): # known case of _datetime.datetime.utcnow """ Return a new datetime representing UTC day and time. """ return datetime(1, 1, 1) def utcoffset(self): # real signature unknown; restored from __doc__ """ Return self.tzinfo.utcoffset(self). """ pass def utctimetuple(self): # known case of _datetime.datetime.utctimetuple """ Return UTC time tuple, compatible with time.localtime(). """ return (0, 0, 0, 0, 0, 0, 0, 0, 0) def __add__(self, *args, **kwargs): # real signature unknown """ Return self+value. """ pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __hash__(self, *args, **kwargs): # real signature unknown """ Return hash(self). """ pass def __init__(self, year, month, day, hour=None, minute=None, second=None, microsecond=None, tzinfo=None): # real signature unknown; restored from __doc__ pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass @staticmethod # known case of __new__ def __new__(cls, year=None, month=None, day=None, hour=None, minute=None, second=None, microsecond=None, tzinfo=None): # known case of _datetime.datetime.__new__ """ Create and return a new object. See help(type) for accurate signature. """ pass def __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass def __radd__(self, *args, **kwargs): # real signature unknown """ Return value+self. """ pass def __reduce__(self): # real signature unknown; restored from __doc__ """ __reduce__() -> (cls, state) """ pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass def __rsub__(self, *args, **kwargs): # real signature unknown """ Return value-self. """ pass def __str__(self, *args, **kwargs): # real signature unknown """ Return str(self). """ pass def __sub__(self, *args, **kwargs): # real signature unknown """ Return self-value. """ pass hour = property(lambda self: 0) """:type: int""" microsecond = property(lambda self: 0) """:type: int""" minute = property(lambda self: 0) """:type: int""" second = property(lambda self: 0) """:type: int""" tzinfo = property(lambda self: object(), lambda self, v: None, lambda self: None) # default max = None # (!) real value is '' min = None # (!) real value is '' resolution = None # (!) real value is '' class time(object): """ time([hour[, minute[, second[, microsecond[, tzinfo]]]]]) --> a time object All arguments are optional. tzinfo may be None, or an instance of a tzinfo subclass. The remaining arguments may be ints. """ def dst(self): # real signature unknown; restored from __doc__ """ Return self.tzinfo.dst(self). """ pass def isoformat(self): # known case of _datetime.time.isoformat """ Return string in ISO 8601 format, HH:MM:SS[.mmmmmm][+HH:MM]. """ return "" def replace(self, hour=None, minute=None, second=None, microsecond=None, tzinfo=None): # known case of _datetime.time.replace """ Return time with new specified fields. """ return time(0, 0) def strftime(self, format): # known case of _datetime.time.strftime """ format -> strftime() style string. """ return "" def tzname(self): # real signature unknown; restored from __doc__ """ Return self.tzinfo.tzname(self). """ pass def utcoffset(self): # real signature unknown; restored from __doc__ """ Return self.tzinfo.utcoffset(self). """ pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __format__(self, *args, **kwargs): # real signature unknown """ Formats self with strftime. """ pass def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __hash__(self, *args, **kwargs): # real signature unknown """ Return hash(self). """ pass def __init__(self, hour=None, minute=None, second=None, microsecond=None, tzinfo=None): # real signature unknown; restored from __doc__ pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass @staticmethod # known case of __new__ def __new__(cls, hour=None, minute=None, second=None, microsecond=None, tzinfo=None): # known case of _datetime.time.__new__ """ Create and return a new object. See help(type) for accurate signature. """ pass def __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass def __reduce__(self): # real signature unknown; restored from __doc__ """ __reduce__() -> (cls, state) """ pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass def __str__(self, *args, **kwargs): # real signature unknown """ Return str(self). """ pass hour = property(lambda self: 0) """:type: int""" microsecond = property(lambda self: 0) """:type: int""" minute = property(lambda self: 0) """:type: int""" second = property(lambda self: 0) """:type: int""" tzinfo = property(lambda self: object(), lambda self, v: None, lambda self: None) # default max = None # (!) real value is '' min = None # (!) real value is '' resolution = None # (!) real value is '' class timedelta(object): """ Difference between two datetime values. """ def total_seconds(self, *args, **kwargs): # real signature unknown """ Total seconds in the duration. """ pass def __abs__(self, *args, **kwargs): # real signature unknown """ abs(self) """ pass def __add__(self, *args, **kwargs): # real signature unknown """ Return self+value. """ pass def __bool__(self, *args, **kwargs): # real signature unknown """ self != 0 """ pass def __divmod__(self, *args, **kwargs): # real signature unknown """ Return divmod(self, value). """ pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __floordiv__(self, *args, **kwargs): # real signature unknown """ Return self//value. """ pass def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __hash__(self, *args, **kwargs): # real signature unknown """ Return hash(self). """ pass def __init__(self, *args, **kwargs): # real signature unknown pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass def __mod__(self, *args, **kwargs): # real signature unknown """ Return self%value. """ pass def __mul__(self, *args, **kwargs): # real signature unknown """ Return self*value. """ pass def __neg__(self, *args, **kwargs): # real signature unknown """ -self """ pass @staticmethod # known case of __new__ def __new__(cls, days=None, seconds=None, microseconds=None, milliseconds=None, minutes=None, hours=None, weeks=None): # known case of _datetime.timedelta.__new__ """ Create and return a new object. See help(type) for accurate signature. """ pass def __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass def __pos__(self, *args, **kwargs): # real signature unknown """ +self """ pass def __radd__(self, *args, **kwargs): # real signature unknown """ Return value+self. """ pass def __rdivmod__(self, *args, **kwargs): # real signature unknown """ Return divmod(value, self). """ pass def __reduce__(self): # real signature unknown; restored from __doc__ """ __reduce__() -> (cls, state) """ pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass def __rfloordiv__(self, *args, **kwargs): # real signature unknown """ Return value//self. """ pass def __rmod__(self, *args, **kwargs): # real signature unknown """ Return value%self. """ pass def __rmul__(self, *args, **kwargs): # real signature unknown """ Return value*self. """ pass def __rsub__(self, *args, **kwargs): # real signature unknown """ Return value-self. """ pass def __rtruediv__(self, *args, **kwargs): # real signature unknown """ Return value/self. """ pass def __str__(self, *args, **kwargs): # real signature unknown """ Return str(self). """ pass def __sub__(self, *args, **kwargs): # real signature unknown """ Return self-value. """ pass def __truediv__(self, *args, **kwargs): # real signature unknown """ Return self/value. """ pass days = property(lambda self: 0) """Number of days. :type: int """ microseconds = property(lambda self: 0) """Number of microseconds (>= 0 and less than 1 second). :type: int """ seconds = property(lambda self: 0) """Number of seconds (>= 0 and less than 1 day). :type: int """ max = None # (!) real value is '' min = None # (!) real value is '' resolution = None # (!) real value is '' class tzinfo(object): """ Abstract base class for time zone info objects. """ def dst(self, date_time): # known case of _datetime.tzinfo.dst """ datetime -> DST offset in minutes east of UTC. """ return 0 def fromutc(self, date_time): # known case of _datetime.tzinfo.fromutc """ datetime in UTC -> datetime in local time. """ return datetime(1, 1, 1) def tzname(self, date_time): # known case of _datetime.tzinfo.tzname """ datetime -> string name of time zone. """ return "" def utcoffset(self, date_time): # known case of _datetime.tzinfo.utcoffset """ datetime -> timedelta showing offset from UTC, negative values indicating West of UTC """ return 0 def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown """ -> (cls, state) """ pass class timezone(__datetime.tzinfo): """ Fixed offset from UTC implementation of tzinfo. """ def dst(self, *args, **kwargs): # real signature unknown """ Return None. """ pass def fromutc(self, *args, **kwargs): # real signature unknown """ datetime in UTC -> datetime in local time. """ pass def tzname(self, *args, **kwargs): # real signature unknown """ If name is specified when timezone is created, returns the name. Otherwise returns offset as 'UTC(+|-)HH:MM'. """ pass def utcoffset(self, *args, **kwargs): # real signature unknown """ Return fixed offset. """ pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __getinitargs__(self, *args, **kwargs): # real signature unknown """ pickle support """ pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __hash__(self, *args, **kwargs): # real signature unknown """ Return hash(self). """ pass def __init__(self, *args, **kwargs): # real signature unknown pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass def __str__(self, *args, **kwargs): # real signature unknown """ Return str(self). """ pass max = None # (!) real value is '' min = None # (!) real value is '' utc = None # (!) real value is '' class __loader__(object): """ Meta path import for built-in modules. All methods are either class or static methods to avoid the need to instantiate the class. """ @classmethod def create_module(cls, *args, **kwargs): # real signature unknown """ Create a built-in module """ pass @classmethod def exec_module(cls, *args, **kwargs): # real signature unknown """ Exec a built-in module """ pass @classmethod def find_module(cls, *args, **kwargs): # real signature unknown """ Find the built-in module. If 'path' is ever specified then the search is considered a failure. This method is deprecated. Use find_spec() instead. """ pass @classmethod def find_spec(cls, *args, **kwargs): # real signature unknown pass @classmethod def get_code(cls, *args, **kwargs): # real signature unknown """ Return None as built-in modules do not have code objects. """ pass @classmethod def get_source(cls, *args, **kwargs): # real signature unknown """ Return None as built-in modules do not have source code. """ pass @classmethod def is_package(cls, *args, **kwargs): # real signature unknown """ Return False as built-in modules are never packages. """ pass @classmethod def load_module(cls, *args, **kwargs): # real signature unknown """ Load the specified module into sys.modules and return it. This method is deprecated. Use loader.exec_module instead. """ pass def module_repr(module): # reliably restored by inspect """ Return repr for the module. The method is deprecated. The import machinery does the job itself. """ pass def __init__(self, *args, **kwargs): # real signature unknown pass __weakref__ = property(lambda self: object(), lambda self, v: None, lambda self: None) # default """list of weak references to the object (if defined)""" __dict__ = None # (!) real value is '' # variables with complex values datetime_CAPI = None # (!) real value is '' __spec__ = None # (!) real value is ''

31.483146

166

0.59287

2,949

25,218

4.871482

0.098338

0.104065

0.1601

0.77579

0.730823

0.671516

0.598218

0.567312

0.562648

0

0.007065

0.275914

25,218

800

167

31.5225

0.779682

0.446229

0

0.768817

0

0.000083

0

1

0.408602

false

0.322581

0.002688

0

0.604839

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

1

0

6

5247555ef50d7b2db1edc398eb67f9fe2be3e86f

72

py

Python

mc2pbrt/liquid/__init__.py

PbrtCraft/mc2pbrt

145c844a7ec0fb3ee3c83dba67c2f8cdcf888ed4

[ "MIT" ]

3

2019-10-04T17:56:50.000Z

2019-11-11T13:39:24.000Z

mc2pbrt/liquid/__init__.py

PbrtCraft/mc2pbrt

145c844a7ec0fb3ee3c83dba67c2f8cdcf888ed4

[ "MIT" ]

8

2019-10-12T03:53:23.000Z

2022-03-12T00:01:21.000Z

mc2pbrt/liquid/__init__.py

PbrtCraft/mc2pbrt

145c844a7ec0fb3ee3c83dba67c2f8cdcf888ed4

[ "MIT" ]

1

2019-02-12T23:41:00.000Z

from liquid.lava import LavaSolver from liquid.water import WaterSolver

24

36

0.861111

10

72

6.2

0.7

0.322581

0

0.111111

72

2

37

36

0.96875

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

526038f645ec07f187329b116306cea6ab07104d

4,657

py

Python

indicators/tests/test_iptt_excel_endpoints.py

Falliatcom-sa/falliatcom

39fb926de072c296ed32d50cccfb8003ca870739

[ "Apache-2.0" ]

null

indicators/tests/test_iptt_excel_endpoints.py

Falliatcom-sa/falliatcom

39fb926de072c296ed32d50cccfb8003ca870739

[ "Apache-2.0" ]

5

2021-02-08T20:42:48.000Z

2022-03-12T00:19:38.000Z

indicators/tests/test_iptt_excel_endpoints.py

Falliatcom-sa/falliatcom

39fb926de072c296ed32d50cccfb8003ca870739

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """Excel endpoints (Timeperiods, TvA, and TvA full report) tested to ensure they download parsable content""" from django import test from django.urls import reverse from factories import ( workflow_models as w_factories, indicators_models as i_factories ) from indicators.models import Indicator class IPTTDownloadTestCases: def test_timeperiods_monthly_download(self): params = { 'reportType': '2', 'programId': self.program.pk, 'frequency': '7' } response = self.client.get(reverse('iptt_excel'), params) self.assertEqual(response.status_code, 200) def test_timeperiods_annual_download(self): params = { 'reportType': '2', 'programId': self.program.pk, 'frequency': '3' } response = self.client.get(reverse('iptt_excel'), params) self.assertEqual(response.status_code, 200) def test_timeperiods_group_by_levels_download(self): params = { 'reportType': '2', 'programId': self.program.pk, 'groupby': '2', 'frequency': '7' } response = self.client.get(reverse('iptt_excel'), params) self.assertEqual(response.status_code, 200) def test_timeperiods_limited_download(self): params = { 'reportType': '2', 'programId': self.program.pk, 'frequency': '6', 'start': '1', 'end': '2' } response = self.client.get(reverse('iptt_excel'), params) self.assertEqual(response.status_code, 200) def test_tva_download(self): params = { 'reportType': '1', 'programId': self.program.pk, 'frequency': '7' } response = self.client.get(reverse('iptt_excel'), params) self.assertEqual(response.status_code, 200) def test_tva_lop_download(self): params = { 'reportType': '1', 'programId': self.program.pk, 'frequency': '1' } response = self.client.get(reverse('iptt_excel'), params) self.assertEqual(response.status_code, 200) def test_tva_limited_download(self): params = { 'reportType': '1', 'programId': self.program.pk, 'frequency': '4', 'start': '1', 'end': '2' } response = self.client.get(reverse('iptt_excel'), params) self.assertEqual(response.status_code, 200) def test_tva_full_report_download(self): params = { 'programId': self.program.pk, 'fullTVA': 'true' } response = self.client.get(reverse('iptt_excel'), params) self.assertEqual(response.status_code, 200) class TestRFExcelDownload(test.TestCase, IPTTDownloadTestCases): def setUp(self): country = w_factories.CountryFactory() self.program = w_factories.RFProgramFactory(tiers=True, levels=2) self.program.country.add(country) for level in self.program.levels.all(): i_factories.RFIndicatorFactory(program=self.program, level=level, targets=500, results=400) tola_user = w_factories.TolaUserFactory(country=country) w_factories.grant_program_access(tola_user, self.program, country, 'high') self.client.force_login(tola_user.user) class TestNonRFExcelDownload(test.TestCase, IPTTDownloadTestCases): def setUp(self): country = w_factories.CountryFactory() self.program = w_factories.RFProgramFactory(migrated=False) self.program.country.add(country) for _, level in Indicator.OLD_LEVELS: i_factories.RFIndicatorFactory(program=self.program, old_level=level, targets=500, results=400) tola_user = w_factories.TolaUserFactory(country=country) w_factories.grant_program_access(tola_user, self.program, country, 'high') self.client.force_login(tola_user.user) class TestRFSpecialcharsExcelDownload(test.TestCase, IPTTDownloadTestCases): def setUp(self): country = w_factories.CountryFactory() self.program = w_factories.RFProgramFactory(tiers=['Spécîål Chars', '##1!@!#$', 'asdf'], levels=2) self.program.country.add(country) for level in self.program.levels.all(): i_factories.RFIndicatorFactory(program=self.program, level=level, targets=500, results=400) tola_user = w_factories.TolaUserFactory(country=country) w_factories.grant_program_access(tola_user, self.program, country, 'high') self.client.force_login(tola_user.user)

37.556452

109

0.635388

500

4,657

5.754

0.2

0.084115

0.050052

0.061175

0.816476

0.811609

0.79562

0.782412

0.764685

0

0.018534

0.24694

4,657

124

110

37.556452

0.801825

0.027056

0

0.641509

0

0.082855

0

0.075472

1

0.103774

false

0

0.037736

0

0.179245

0

null

0

1

0

null

0

6

5260b760b2a213ed86c8417ec53998fccf057d39

164

py

Python

devel/lib/python2.7/dist-packages/waterplus_map_tools/srv/__init__.py

THUwelcomerobot/robot

a8c8e5105cf4a3be478c89249e818aa970bfc243

[ "MIT" ]

null

devel/lib/python2.7/dist-packages/waterplus_map_tools/srv/__init__.py

THUwelcomerobot/robot

a8c8e5105cf4a3be478c89249e818aa970bfc243

[ "MIT" ]

null

devel/lib/python2.7/dist-packages/waterplus_map_tools/srv/__init__.py

THUwelcomerobot/robot

a8c8e5105cf4a3be478c89249e818aa970bfc243

[ "MIT" ]

null

from ._AddNewWaypoint import * from ._GetNumOfWaypoints import * from ._GetWaypointByIndex import * from ._GetWaypointByName import * from ._SaveWaypoints import *

27.333333

34

0.817073

15

164

8.6

0.466667

0.310078

0

0.121951

164

5

35

32.8

0.895833

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

5270c39b4d53b290d72762b495e1e4102fcc82a3

3,190

py

Python

micromath/pow/test_pow.py

hedrox/micromath

0f300da914c844e5ff0775f25119909f748de635

[ "MIT" ]

null

micromath/pow/test_pow.py

hedrox/micromath

0f300da914c844e5ff0775f25119909f748de635

[ "MIT" ]

null

micromath/pow/test_pow.py

hedrox/micromath

0f300da914c844e5ff0775f25119909f748de635

[ "MIT" ]

null

import logging import json import math from server import app app.testing = True logging.disable(logging.ERROR) class TestPow: def test_correct_pow(self): with app.test_client() as client: body = {'base': 32, 'power': 2} result = client.post('/api/v1/pow', json=body) assert result.status_code == 200 data = json.loads(result.data) assert math.isclose(float(data['result']), 1024.0) assert data['error'] is None def test_missing_attribute(self): with app.test_client() as client: body = {'power': 2} result = client.post('/api/v1/pow', json=body) assert result.status_code == 500 data = json.loads(result.data) assert data['result'] is None assert 'name' in data['error'] assert data['error']['name'] == 'ValidationError' def test_invalid_attribute_type(self): with app.test_client() as client: body = {'base': None, 'power': 2} result = client.post('/api/v1/pow', json=body) assert result.status_code == 500 data = json.loads(result.data) assert data['result'] is None assert 'name' in data['error'] assert data['error']['name'] == 'ValidationError' body = {'base': '2', 'power': 2} result = client.post('/api/v1/pow', json=body) assert result.status_code == 500 data = json.loads(result.data) assert data['result'] is None assert 'name' in data['error'] assert data['error']['name'] == 'ValidationError' def test_empty_body(self): with app.test_client() as client: body = {} result = client.post('/api/v1/pow', json=body) assert result.status_code == 500 data = json.loads(result.data) assert data['result'] is None assert 'name' in data['error'] assert data['error']['name'] == 'ValidationError' def test_extra_attribute(self): with app.test_client() as client: body = {'base': 32, 'power': 2, 'extra_key': 32} result = client.post('/api/v1/pow', json=body) assert result.status_code == 500 data = json.loads(result.data) assert data['result'] is None assert 'name' in data['error'] assert data['error']['name'] == 'ValidationError' def test_no_body(self): with app.test_client() as client: result = client.post('/api/v1/pow') assert result.status_code == 400 data = json.loads(result.data) assert data['result'] is None assert data['error'] == 'Data not provided' def test_invalid_api_version(self): with app.test_client() as client: body = {'base': 32, 'power': 2} result = client.post('/api/v2/pow', json=body) assert result.status_code == 404 data = json.loads(result.data) assert data['result'] is None assert data['error'] == 'API version v2 not found'

33.93617

62

0.554545

384

3,190

4.523438

0.158854

0.086356

0.07369

0.087507

0.807714

0.777202

0.758204

0.717904

0.667242

0

0.024212

0.313793

3,190

93

63

34.301075

0.769301

0

0.616438

0

0.130721

0

0.39726

1

0.09589

false

0

0.054795

0

0.164384

0

null

0

1

0

null

0

6

87543eab9c74a08254348553c8eea30b66f76a1f

3,601

py

Python

data_generator/config.py

lshupingxl/crnn.pytorch

62a18446b701c81cea9b1a42c1d278c3d5cd486d

[ "MIT" ]

1

2018-11-14T09:19:10.000Z

data_generator/config.py

lshupingxl/crnn.pytorch

62a18446b701c81cea9b1a42c1d278c3d5cd486d

[ "MIT" ]

null

data_generator/config.py

lshupingxl/crnn.pytorch

62a18446b701c81cea9b1a42c1d278c3d5cd486d

[ "MIT" ]

null

#!/usr/bin/env python __author__ = 'solivr' class CONST: DIMENSION_REDUCTION_W_POOLING = 2 * 2 # 2x2 pooling in dimension W on layer 1 and 2 class Alphabet: # 训练时的字母表应该包含空白字符，制作数据集时不应该包含空白字符 LettersLowercase = 'abcdefghijklmnopqrstuvwxyz' # 26 LettersCapitals = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' # 26 Digits = '0123456789' # 10 Symbols = '~!@#%^&*()+$_=,.。<>/?\`;:\'"[]{}《》' # 33 ChineseChar = '臣击居移鼻炉栀魏展多酚蘑数泥槽野蓝散售占服检含府葵咨德蔓退扫撕岩锂浅福穹蜡吸茯碍旭迪泛般材远猪柏肌止热活搔鑫芷湿耗锆荫稚盏赢梭抑听朋把取癃丝耀丸比厚利冻及衰晋弓怀育支華宽氦健蔡差袖科息济谊钢呼苷窿萤凝染凌结就扩扶分后凇联十础煎贵反巷糪时榆翻资桐起麸常言变大制隙能羟冠蒡气赖蔘张找肺百便恺冷锌衍专援景广三珊祥磨簧馆岛赫娃突薢贝熟值稣眠佳嫩仙晒酵淋甘拔袭于延霜埃响黑疣榈麒蚀茵轮齦翁水乳鳞转盆勃劈搏键泵毕枇斜寝葛职芃告各雪械长哈珂微庤教柯备癖每领聚因残维醯薯七趾绕总豪草园唐陈绷澳阀给液诱禾谱祛芬拜良壮愈诃医缬约涵短铬国戟叁心绿琼路际肯沃玛振孚销奈续民叫方癜拕产翠奠天龙应湘邮镑轩贰咀皂策痰涎链令沉痣喉冀造掩身杭最劲坤儿疚篮烧伟黏激汀境筝彤盒性怪復菲何辐婷鸡氏低癥芐瘤烯他楂葫桉潘易沥尼狂声糖兰萨轴稳尘锦过屋璃呋嘧妮塞瞳板檗泸森滩肾鲤檬斛庄颧廊捷语畸杏氯损膀陇浜超债爆榭系克塑逆扁室蒽环余飞忍谢桥党溪运作腰禅义翼托率胚缀唯杉可植粪庭泊手毒呕鼓碘孟鱼探险速几睡肥标紫烟醇袪渴丰引夏属浓脒饮鹏疡抢惨上庆穿熏崇蜕双妆哮另依向压嗦子海盖准瓣户蛇俭妈规希珈外酰滴力列疾业痹胖里殊弯交巨柿钉癣吲豉母醚闽晕诊萘喳捌曼铜舒恩浮论梢雯农期赛附汁镫迷股脉窥啶次蒿唇但状煨浦匀霰杜寻源柄贴泉商流搽原辰脏扬蛸导虫默疫兽模毛酞脾称珠与麝赝枝耵万茱博厄茂额瘰置风辛京杷文务久整央飘郭布重合伐茄块图关虾请朱任唥润坳都髋蜂奶蔷受厦众颔踝窝亥颐记恶月膏醋泳果贤庙叉层深配膝盈树馥抜锡瘘滋袋士异付吹幽泰急花赵核妇甜只询理南舌胀藻镍高噻锐辽鲜郁脲沐侬究马苓翳团紧芳清彩格哚圳硝犬查消栗氟耐孔促焙群咣黄鳄害戊栾嫬蛋呢并房被蒜尚硫出照木牛摘嗉蛰亚癸钻量容美聍弎添凡营遵观铵固物点枸垂船江猴已萸椒咗腮龄屈疼想葡湖刷酸旁奉嚏仲友芡叔呱喜秋丹枙帕杰螵洁幼敌颌试填泮刺欣阳灭肽藿光梗如带连敏蝶汞络拗莪妙苏雾释谜元补荞浆絮充租酯啉摄坑所秀莱迫胯磺荡佛杂夷苠淫拨钾还箴秘牌势渡东炔网留阁盘燥汗参桔素介虎首茛进闵菟药葆沛姓苍饱蕊种籓练待枳预满睛钆调苄员病淳蓣经委石盐埔氛晨眉早视四榴橡故墴凯难撞瑞褶沿基痘棘褐六亿羔之尾税腻芎密藤麦癓脯才伦授裸咖例疹全铁稹普抛疏杨师油融杀好泡灰冡纳未态疳赤峰垫霍玫酱甙测使瘠需淤枯社干纶索正寒惹栓鸟苡暂竣伍映卷断罕琳滤鲁烙缘疮泪按帽粒肆丁五复肪狻假睦颗乱墨蹬宙洽莨闸票望法则型晴垸菜乙逍左典护鲨吁皿王至杞停站米拓体罩诺夹喘的生季示事近担舟邱柳军随芩尤捈狗改卫载着娠湾西老腔胎摩浸琅穗窦壁崔秦皋火第提磷州糜芥市然特区条吨枣华缓黎祁钞羊乃哆暗谷茴稀觉意瓶界蒙混政刻走坦鞣输宫地槐径治冶角邦艽遥佰菌娜囡溶罐纸穴埋街鸿沫莎权择遂镜瓷噫甫趋膦头局腺粉度痛歆爽棉孜疗倩灸技二孢田卜馈云薄顺门替炼髓悉堵施厅它件橼扭积漕恒贞单死漱独钡简色套洗铸质蝎藏直胃谈宣达蔗纱计傲麟年爬录品定者葱抒话必类洞亭汇蟅刚监工橘名端勒汉靶矾边腹肝空芪姜籍镁详烷初裹圣梨渍萝唑蔻笛枫椽烁肮巴精解肟肃射完为劳撩乌升宇份显操棱椎样胶胺阴伸盼蒲氢疱疲涌蟹代归幻迈豆釉纺住楷旱泻枪硅史排甾隔县弃菪炒鹅虹喹硕仰酶帅竟嵩自曹和妥欧酒酐裕顶静齐塘菱脐鉍味传葶蓼眝冒背律感苋负换溴腾耳蛭半菇恬肢挫宏荧钛吊缝情阈忻犀昆启征俞伤龈问翘刮梅宁估有跌弱灌浣切店陆胸钯鉴岁尔念富限再钩下软成蔽眼荆疑去选彬研瘫防暖拆通呤做昔片根效刀嘌不芦等院岑公筛极床酣麻粘式松桩墩缴滑游柴嗪咬萎痤土历部来莘周或纈间膨骨芯针学具接甁芽末触注屏污萍绒锁镉臂尪官集捡蜗破焦玖醌波养形弹逐榕氮楼城山透姆挂九颈丙苹智化财封鹿肩以薇红徐茁承冬侧香家震创咳巧肛训衬乡铍泗败认茅迅离瓦罗薏珺曝喷芙泌盯倍滨除企吝平膜安白旦奇见凤潍赌允腱筋抗淮悦莲威个氧康咪插珀纷粗醛主潜梦综弧乐缺善陀睾序瘟痧翅括烫津卤杵步码村武紊嗜笋会协费温硒益思建放古吖柱伏脊莫锉位喃共萦灯强舜金竹错杆钴葩签蠲毫疬净臭折扑同春球非评铂呲价柒棒青致搐壳追仁买功也钼右包熨腐沟泽用表顾太棋恳电蓟炎两报畄夫矫内肼航辨血卓实场吗闪砂这先俄少申割钟祺忧锰螨柠加歧千钱河逸旋笨司聖淀沙贺免蕙送肤脱匮颠俊临夭浙嗽惠刘而乔毗蒎蟒肠管露循信羌恢级别兆脂供什囊妊痔辅立台误阶新铅碱抽炙摸剔牙卡佐食桑昌奥象拿桃迎癌辩豫曙尖朵仑助煮蝉阻渊北畅朗硬杯讯钵中号洒真毋港厘症脓舍晶窍须休醒竭批怡证庚洛锋打线机得兵前裂入苁坊樟睑英殷胰厂芍戴樱炭决玻芝凉节小脑保蒸拾推严陪寺牵丽鹤冲蜜仔螺避辣蟾宝洋处从咛在隆尿萆腋口胍帖要淞其啡莵皮痒救糊仪己顿料颉岳匹旨芒泾曲影巯对当志印危慧宾落举擦君扎萄绪灵斯目座冢催据悠银阿绣渗珍蔬堂烤颛羧患装知孕析衡降频剂呀硼快汾统匪襞肉笔叮吐瑟泼塔设构班缩适册术锯嚼伊卵瑚涤佩哌敷铋没世黛桂瓜苗川脈磁奎慈圆玉荷隐胞岐童弥伪伽腿茜熊冰副确底纤棕嵌浴卢瘀浊於修餐嘉相永糠胆滞蓉娘籽蛎无嘴寓段牡祝命雅氨眩雌献划面林苯收婴翔羚蚓衣减咏灶漠雍跟唾坎车癀拉纟醉梓八菊抚回韦盛是行幸琪陷锑肿祭荣开雄碧吡彭席祖纯酪郊挑聆腕艾酊汤纹钙指啊发呐酮拍嗓苦织吉淡星道茶丫沸派琥督丛本斑足傅叶像礼慢扰宜虑程绵亮增诚旧氩诗算剑佑抓夜控考沪窄藓伴明涂描采吴项塌寿器女坏氖甲碳汽障厌字攻齿看蚕內璐兴雁溃那招失人闭验咽音颅霞细悬动霉腥寄胱厉察钳鹰更锻培神荟日渣钠爱抹雷玄壹围洲硷写仟昼簇一铺组胡优镇铝账零宗' BLANK_SYMBOL = '-' DIGITS_ONLY = BLANK_SYMBOL + Digits SYMBOLS_ONLY = BLANK_SYMBOL + Symbols CHINESECHAR_ONLY = BLANK_SYMBOL + ChineseChar LETTERS_DIGITS = BLANK_SYMBOL + Digits + LettersCapitals + LettersLowercase LETTERS_DIGITS_LOWERCASE = BLANK_SYMBOL + LettersLowercase LETTERS_ONLY = BLANK_SYMBOL + LettersCapitals + LettersLowercase LETTERS_ONLY_LOWERCASE = BLANK_SYMBOL + BLANK_SYMBOL + LettersLowercase LETTERS_SYMBOLS = BLANK_SYMBOL + LettersCapitals + LettersLowercase + Symbols LETTERS_LOWERCASE_SYMBOLS = BLANK_SYMBOL + LettersLowercase + Symbols LETTERS_DIGITS_SYMBOLS = BLANK_SYMBOL + Digits + LettersCapitals + LettersLowercase + Symbols LETTERS__LOWERCASE_DIGITS_SYMBOLS= BLANK_SYMBOL + Digits + LettersLowercase + Symbols # CHINESECHAR_LETTERS_DIGIT_SYMBOLS = Digits + LettersCapitals + LettersLowercase + Symbols + ChineseChar CHINESECHAR_LETTERS_DIGIT_SYMBOLS = BLANK_SYMBOL +Digits + LettersCapitals + LettersLowercase + Symbols + ChineseChar

124.172414

2,174

0.898917

137

3,601

23.291971

0.284672

0.048261

0.031965

0.030085

0.107803

0.038859

0

0.007156

0.068592

3,601

29

2,175

124.172414

0.944246

0.058873

0

0.664991

0.659965

0

1

0

false

0

0.954545

0

1

null

0

1

0

1

null

0

1

0

6

8766caf448baa76ec800a27ba5d830d8e2e6618a

98,880

py

Python

vmware_nsx/tests/unit/services/lbaas/test_nsxp_driver.py

salv-orlando/vmware-nsx

6ad0d595aa8099004eb6dd5ff62c7a91b0e11dfd

[ "Apache-2.0" ]

null

vmware_nsx/tests/unit/services/lbaas/test_nsxp_driver.py

salv-orlando/vmware-nsx

6ad0d595aa8099004eb6dd5ff62c7a91b0e11dfd

[ "Apache-2.0" ]

null

vmware_nsx/tests/unit/services/lbaas/test_nsxp_driver.py

salv-orlando/vmware-nsx

6ad0d595aa8099004eb6dd5ff62c7a91b0e11dfd

[ "Apache-2.0" ]

null

# Copyright (c) 2019 VMware, Inc. # # 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. import copy from unittest import mock from neutron.tests import base from neutron_lib import context from neutron_lib import exceptions as n_exc from vmware_nsx.services.lbaas import base_mgr from vmware_nsx.services.lbaas import lb_const from vmware_nsx.services.lbaas.nsx_p.implementation import healthmonitor_mgr from vmware_nsx.services.lbaas.nsx_p.implementation import l7policy_mgr from vmware_nsx.services.lbaas.nsx_p.implementation import l7rule_mgr from vmware_nsx.services.lbaas.nsx_p.implementation import lb_utils as p_utils from vmware_nsx.services.lbaas.nsx_p.implementation import listener_mgr from vmware_nsx.services.lbaas.nsx_p.implementation import loadbalancer_mgr from vmware_nsx.services.lbaas.nsx_p.implementation import member_mgr from vmware_nsx.services.lbaas.nsx_p.implementation import pool_mgr from vmware_nsx.services.lbaas.nsx_v3.implementation import lb_utils from vmware_nsx.services.lbaas.octavia import octavia_listener from vmware_nsx.tests.unit.services.lbaas import lb_data_models as lb_models from vmware_nsx.tests.unit.services.lbaas import lb_translators from vmware_nsxlib.v3 import exceptions as nsxlib_exc from vmware_nsxlib.v3.policy import constants as policy_constants # TODO(asarfaty): Use octavia models for those tests LB_VIP = '10.0.0.10' LB_ROUTER_ID = 'router-x' ROUTER_ID = 'neutron-router-x' LB_ID = 'xxx-xxx' LB_TENANT_ID = 'yyy-yyy' LB_SERVICE_ID = LB_ID LB_NETWORK = {'router:external': False, 'id': 'xxxxx', 'name': 'network-1'} EXT_LB_NETWORK = {'router:external': True, 'id': 'public', 'name': 'network-2'} LISTENER_ID = 'listener-x' HTTP_LISTENER_ID = 'listener-http' HTTPS_LISTENER_ID = 'listener-https' UDP_LISTENER_ID = 'listener-udp' APP_PROFILE_ID = 'appp-x' LB_VS_ID = LISTENER_ID LB_APP_PROFILE = { "resource_type": "LbHttpProfile", "description": "my http profile", "id": APP_PROFILE_ID, "display_name": "httpprofile1", "ntlm": False, "request_header_size": 1024, "http_redirect_to_https": False, "idle_timeout": 1800, "x_forwarded_for": "INSERT", } POOL_ID = 'ppp-qqq' LB_POOL_ID = POOL_ID LB_POOL = { "display_name": "httppool1", "description": "my http pool", "id": LB_POOL_ID, "algorithm": "ROUND_ROBIN", } MEMBER_ID = 'mmm-mmm' MEMBER_ADDRESS = '10.0.0.200' LB_MEMBER = {'display_name': 'member1_' + MEMBER_ID, 'weight': 1, 'ip_address': MEMBER_ADDRESS, 'port': 80, 'backup_member': False, 'admin_state_up': True} LB_POOL_WITH_MEMBER = { "display_name": "httppool1", "description": "my http pool", "id": LB_POOL_ID, "algorithm": "ROUND_ROBIN", "members": [ { "display_name": "http-member1", "ip_address": MEMBER_ADDRESS, "port": "80", "weight": "1", "admin_state": "ENABLED" } ] } HM_ID = 'hhh-mmm' LB_MONITOR_ID = HM_ID L7POLICY_ID = 'l7policy-xxx' LB_RULE_ID = 'lb-rule-xx' L7RULE_ID = 'l7rule-111' LB_PP_ID = POOL_ID FAKE_CERT = {'id': 'cert-xyz'} SERVICE_STATUSES = { "virtual_servers": [{ "virtual_server_id": LB_VS_ID, "status": "UP" }], "service_id": LB_SERVICE_ID, "service_status": "UP", "pools": [{ "members": [{ "port": "80", "ip_address": MEMBER_ADDRESS, "status": "DOWN" }], "pool_id": LB_POOL_ID, "status": "DOWN" }] } VS_STATUSES = { "results": [{ "virtual_server_id": LB_VS_ID, "status": "UP" }] } class BaseTestEdgeLbaasV2(base.BaseTestCase): def _tested_entity(self): return None def completor(self, success=True): self.last_completor_succees = success self.last_completor_called = True def reset_completor(self): self.last_completor_succees = False self.last_completor_called = False def setUp(self): super(BaseTestEdgeLbaasV2, self).setUp() self.reset_completor() self.context = context.get_admin_context() octavia_objects = { 'loadbalancer': loadbalancer_mgr.EdgeLoadBalancerManagerFromDict(), 'listener': listener_mgr.EdgeListenerManagerFromDict(), 'pool': pool_mgr.EdgePoolManagerFromDict(), 'member': member_mgr.EdgeMemberManagerFromDict(), 'healthmonitor': healthmonitor_mgr.EdgeHealthMonitorManagerFromDict(), 'l7policy': l7policy_mgr.EdgeL7PolicyManagerFromDict(), 'l7rule': l7rule_mgr.EdgeL7RuleManagerFromDict()} self.edge_driver = octavia_listener.NSXOctaviaListenerEndpoint( **octavia_objects) self.lbv2_driver = mock.Mock() self.core_plugin = mock.Mock() self.core_plugin._nsx_version = '2.5.0' base_mgr.LoadbalancerBaseManager._lbv2_driver = self.lbv2_driver base_mgr.LoadbalancerBaseManager._core_plugin = self.core_plugin self._patch_lb_plugin(self.lbv2_driver, self._tested_entity) self._patch_policy_lb_clients(self.core_plugin) self.lb = lb_models.LoadBalancer(LB_ID, LB_TENANT_ID, 'lb1', '', 'some-subnet', 'port-id', LB_VIP) self.listener = lb_models.Listener(LISTENER_ID, LB_TENANT_ID, 'listener1', 'Dummy', None, LB_ID, 'HTTP', protocol_port=80, loadbalancer=self.lb) self.https_listener = lb_models.Listener( HTTP_LISTENER_ID, LB_TENANT_ID, 'listener2', '', None, LB_ID, 'HTTPS', protocol_port=443, loadbalancer=self.lb) self.terminated_https_listener = lb_models.Listener( HTTPS_LISTENER_ID, LB_TENANT_ID, 'listener3', '', None, LB_ID, 'TERMINATED_HTTPS', protocol_port=443, loadbalancer=self.lb) self.udp_listener = lb_models.Listener( UDP_LISTENER_ID, LB_TENANT_ID, 'listener4', '', None, LB_ID, 'UDP', protocol_port=90, loadbalancer=self.lb) self.allowed_cidr_listener = lb_models.Listener( LISTENER_ID, LB_TENANT_ID, 'listener4', '', None, LB_ID, 'HTTP', protocol_port=80, allowed_cidrs=['1.1.1.0/24'], loadbalancer=self.lb) self.pool = lb_models.Pool(POOL_ID, LB_TENANT_ID, 'pool1', '', None, 'HTTP', 'ROUND_ROBIN', loadbalancer_id=LB_ID, listener=self.listener, listeners=[self.listener], loadbalancer=self.lb) self.sess_persistence = lb_models.SessionPersistence( POOL_ID, 'HTTP_COOKIE', 'meh_cookie') self.pool_persistency = lb_models.Pool(POOL_ID, LB_TENANT_ID, 'pool1', '', None, 'HTTP', 'ROUND_ROBIN', loadbalancer_id=LB_ID, listener=self.listener, listeners=[self.listener], loadbalancer=self.lb, session_persistence=self.sess_persistence) self.member = lb_models.Member(MEMBER_ID, LB_TENANT_ID, POOL_ID, MEMBER_ADDRESS, 80, 1, pool=self.pool, name='member1', admin_state_up=True) self.hm = lb_models.HealthMonitor(HM_ID, LB_TENANT_ID, 'PING', 3, 3, 1, pool=self.pool, name='hm1') self.hm_http = lb_models.HealthMonitor(HM_ID, LB_TENANT_ID, 'HTTP', 3, 3, 1, pool=self.pool, http_method='GET', url_path="/meh", name='hm2') self.l7policy = lb_models.L7Policy(L7POLICY_ID, LB_TENANT_ID, name='policy-test', description='policy-desc', listener_id=LISTENER_ID, action='REDIRECT_TO_POOL', redirect_pool_id=POOL_ID, listener=self.listener, position=1) self.l7rule = lb_models.L7Rule(L7RULE_ID, LB_TENANT_ID, l7policy_id=L7POLICY_ID, compare_type='EQUAL_TO', invert=False, type='HEADER', key='key1', value='val1', policy=self.l7policy) # Translate LBaaS objects to dictionaries self.lb_dict = lb_translators.lb_loadbalancer_obj_to_dict( self.lb) self.listener_dict = lb_translators.lb_listener_obj_to_dict( self.listener) self.cidr_list_dict = lb_translators.lb_listener_obj_to_dict( self.allowed_cidr_listener) self.https_listener_dict = lb_translators.lb_listener_obj_to_dict( self.https_listener) self.terminated_https_listener_dict = lb_translators.\ lb_listener_obj_to_dict(self.terminated_https_listener) self.udp_listener_dict = lb_translators.lb_listener_obj_to_dict( self.udp_listener) self.pool_dict = lb_translators.lb_pool_obj_to_dict( self.pool) self.pool_persistency_dict = lb_translators.lb_pool_obj_to_dict( self.pool_persistency) self.member_dict = lb_translators.lb_member_obj_to_dict( self.member) self.hm_dict = lb_translators.lb_hm_obj_to_dict( self.hm) self.hm_http_dict = lb_translators.lb_hm_obj_to_dict( self.hm_http) self.l7policy_dict = lb_translators.lb_l7policy_obj_to_dict( self.l7policy) self.l7rule_dict = lb_translators.lb_l7rule_obj_to_dict( self.l7rule) def tearDown(self): self._unpatch_lb_plugin(self.lbv2_driver, self._tested_entity) super(BaseTestEdgeLbaasV2, self).tearDown() def _patch_lb_plugin(self, lb_plugin, manager): self.real_manager = getattr(lb_plugin, manager) lb_manager = mock.patch.object(lb_plugin, manager).start() mock.patch.object(lb_manager, 'create').start() mock.patch.object(lb_manager, 'update').start() mock.patch.object(lb_manager, 'delete').start() mock.patch.object(lb_manager, 'successful_completion').start() def _patch_policy_lb_clients(self, core_plugin): nsxpolicy = mock.patch.object(core_plugin, 'nsxpolicy').start() load_balancer = mock.patch.object(nsxpolicy, 'load_balancer').start() self.service_client = mock.patch.object(load_balancer, 'lb_service').start() self.app_client = mock.patch.object(load_balancer, 'lb_http_profile').start() self.vs_client = mock.patch.object(load_balancer, 'virtual_server').start() self.pool_client = mock.patch.object(load_balancer, 'lb_pool').start() self.monitor_client = mock.patch.object( load_balancer, 'lb_monitor_profile_icmp').start() self.http_monitor_client = mock.patch.object( load_balancer, 'lb_monitor_profile_http').start() self.rule_client = mock.patch.object(load_balancer, 'rule').start() self.pp_client = mock.patch.object( load_balancer, 'lb_source_ip_persistence_profile').start() self.pp_cookie_client = mock.patch.object( load_balancer, 'lb_cookie_persistence_profile').start() self.pp_generic_client = mock.patch.object( load_balancer, 'lb_persistence_profile').start() self.nsxpolicy = nsxpolicy def _unpatch_lb_plugin(self, lb_plugin, manager): setattr(lb_plugin, manager, self.real_manager) class TestEdgeLbaasV2Loadbalancer(BaseTestEdgeLbaasV2): def setUp(self): super(TestEdgeLbaasV2Loadbalancer, self).setUp() @property def _tested_entity(self): return 'load_balancer' def test_create(self): self.reset_completor() neutron_router = {'id': ROUTER_ID, 'name': 'dummy', 'external_gateway_info': {'external_fixed_ips': []}} with mock.patch.object(lb_utils, 'get_network_from_subnet', return_value=LB_NETWORK), \ mock.patch.object(lb_utils, 'get_router_from_network', return_value=ROUTER_ID),\ mock.patch.object(lb_utils, 'get_tags', return_value=[]),\ mock.patch.object(self.core_plugin, 'get_router', return_value=neutron_router), \ mock.patch.object(self.core_plugin, '_find_router_gw_subnets', return_value=[]),\ mock.patch.object(self.core_plugin, 'service_router_has_services', return_value=False) as plugin_has_sr,\ mock.patch.object(self.service_client, 'get_router_lb_service', return_value=None),\ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': []}),\ mock.patch.object(self.service_client, 'create_or_overwrite' ) as create_service: self.edge_driver.loadbalancer.create( self.context, self.lb_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) # Service should be created with connectivity path create_service.assert_called_once_with( mock.ANY, lb_service_id=LB_ID, description=self.lb_dict['description'], tags=mock.ANY, size='SMALL', connectivity_path=mock.ANY) # Verify that the tags contain the loadbalancer id actual_tags = create_service.mock_calls[0][-1]['tags'] found_tag = False for tag in actual_tags: if (tag['scope'] == p_utils.SERVICE_LB_TAG_SCOPE and tag['tag'] == LB_ID): found_tag = True self.assertTrue(found_tag) plugin_has_sr.assert_called_once_with(mock.ANY, ROUTER_ID) def test_create_same_router(self): self.reset_completor() neutron_router = {'id': ROUTER_ID, 'name': 'dummy', 'external_gateway_info': {'external_fixed_ips': []}} old_lb_id = 'aaa' lb_service = {'id': old_lb_id, 'tags': [{'scope': p_utils.SERVICE_LB_TAG_SCOPE, 'tag': old_lb_id}]} with mock.patch.object(lb_utils, 'get_network_from_subnet', return_value=LB_NETWORK), \ mock.patch.object(lb_utils, 'get_router_from_network', return_value=ROUTER_ID),\ mock.patch.object(self.core_plugin, 'get_router', return_value=neutron_router), \ mock.patch.object(self.core_plugin, '_find_router_gw_subnets', return_value=[]),\ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [lb_service]}),\ mock.patch.object(self.core_plugin, 'service_router_has_services', return_value=True) as plugin_has_sr,\ mock.patch.object(self.service_client, 'update_customized') as service_update: self.edge_driver.loadbalancer.create( self.context, self.lb_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) plugin_has_sr.assert_not_called() service_update.assert_called_once() def test_create_same_router_many_fail(self): lb_service = {'id': 'first_lb', 'tags': []} self.reset_completor() neutron_router = {'id': ROUTER_ID, 'name': 'dummy', 'external_gateway_info': {'external_fixed_ips': []}} with mock.patch.object(lb_utils, 'get_network_from_subnet', return_value=LB_NETWORK), \ mock.patch.object(lb_utils, 'get_router_from_network', return_value=ROUTER_ID),\ mock.patch.object(self.core_plugin, 'get_router', return_value=neutron_router), \ mock.patch.object(self.core_plugin, '_find_router_gw_subnets', return_value=[]),\ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [lb_service]}),\ mock.patch.object(self.service_client, 'update_customized', side_effect=n_exc.BadRequest(resource='', msg='') ) as service_update,\ mock.patch.object(self.service_client, 'get_router_lb_service', return_value=None): self.assertRaises( n_exc.BadRequest, self.edge_driver.loadbalancer.create, self.context, self.lb_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertFalse(self.last_completor_succees) service_update.assert_called_once() def test_create_external_vip(self): self.reset_completor() with mock.patch.object(lb_utils, 'get_router_from_network', return_value=None),\ mock.patch.object(lb_utils, 'get_network_from_subnet', return_value=EXT_LB_NETWORK), \ mock.patch.object(self.service_client, 'get_router_lb_service', return_value=None),\ mock.patch.object(self.service_client, 'create_or_overwrite', return_value={'id': LB_SERVICE_ID} ) as create_service: self.edge_driver.loadbalancer.create(self.context, self.lb_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) # Service should be created with no connectivity path create_service.assert_called_once_with( mock.ANY, lb_service_id=LB_ID, description=self.lb_dict['description'], tags=mock.ANY, size='SMALL', connectivity_path=None) def test_create_no_services(self): self.reset_completor() neutron_router = {'id': ROUTER_ID, 'name': 'dummy', 'external_gateway_info': {'external_fixed_ips': []}} with mock.patch.object(lb_utils, 'get_network_from_subnet', return_value=LB_NETWORK), \ mock.patch.object(lb_utils, 'get_router_from_network', return_value=ROUTER_ID),\ mock.patch.object(self.core_plugin, 'get_router', return_value=neutron_router), \ mock.patch.object(self.core_plugin, '_find_router_gw_subnets', return_value=[]),\ mock.patch.object(self.core_plugin, 'service_router_has_services', return_value=False) as plugin_has_sr, \ mock.patch.object(self.service_client, 'get_router_lb_service', return_value=None),\ mock.patch.object(self.service_client, 'create_or_overwrite' ) as create_service,\ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': []}),\ mock.patch.object(self.core_plugin, "create_service_router") as create_sr: self.edge_driver.loadbalancer.create( self.context, self.lb_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) # Service should be created with connectivity path create_service.assert_called_once_with( mock.ANY, lb_service_id=LB_ID, description=self.lb_dict['description'], tags=mock.ANY, size='SMALL', connectivity_path=mock.ANY) plugin_has_sr.assert_called_once_with(mock.ANY, ROUTER_ID) create_sr.assert_called_once() def test_create_with_port(self): self.reset_completor() neutron_router = {'id': ROUTER_ID, 'name': 'dummy', 'external_gateway_info': {'external_fixed_ips': []}} neutron_port = {'id': 'port-id', 'name': 'dummy', 'device_owner': ''} with mock.patch.object(lb_utils, 'get_network_from_subnet', return_value=LB_NETWORK), \ mock.patch.object(lb_utils, 'get_router_from_network', return_value=ROUTER_ID),\ mock.patch.object(self.core_plugin, 'get_router', return_value=neutron_router), \ mock.patch.object(self.core_plugin, 'get_port', return_value=neutron_port), \ mock.patch.object(self.core_plugin, 'update_port' ) as update_port, \ mock.patch.object(self.core_plugin, '_find_router_gw_subnets', return_value=[]),\ mock.patch.object(self.core_plugin, 'service_router_has_services', return_value=False) as plugin_has_sr,\ mock.patch.object(self.service_client, 'get_router_lb_service', return_value=None),\ mock.patch.object(self.service_client, 'create_or_overwrite' ) as create_service: self.edge_driver.loadbalancer.create( self.context, self.lb_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) # Service should be created with connectivity path create_service.assert_called_once_with( mock.ANY, lb_service_id=LB_ID, description=self.lb_dict['description'], tags=mock.ANY, size='SMALL', connectivity_path=mock.ANY) plugin_has_sr.assert_called_once_with(mock.ANY, ROUTER_ID) update_port.assert_called_once() def test_update(self): self.reset_completor() new_lb = lb_models.LoadBalancer(LB_ID, 'yyy-yyy', 'lb1-new', 'new-description', 'some-subnet', 'port-id', LB_VIP) new_lb_dict = lb_translators.lb_loadbalancer_obj_to_dict(new_lb) self.edge_driver.loadbalancer.update(self.context, self.lb_dict, new_lb_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete(self): self.reset_completor() lb_service = {'id': LB_SERVICE_ID} with mock.patch.object(lb_utils, 'get_router_from_network', return_value=ROUTER_ID),\ mock.patch.object(self.service_client, 'update_customized', side_effect=n_exc.BadRequest(resource='', msg='') ) as service_update,\ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [lb_service]}),\ mock.patch.object(self.service_client, 'delete' ) as mock_delete_lb_service: self.edge_driver.loadbalancer.delete( self.context, self.lb_dict, self.completor) mock_delete_lb_service.assert_called_with(LB_SERVICE_ID) service_update.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_cascade(self): self.reset_completor() lb_service = {'id': LB_SERVICE_ID} with mock.patch.object(lb_utils, 'get_router_from_network', return_value=ROUTER_ID),\ mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips, \ mock.patch.object(self.service_client, 'update_customized', side_effect=n_exc.BadRequest(resource='', msg='') ) as service_update,\ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [lb_service]}),\ mock.patch.object(self.service_client, 'delete' ) as mock_delete_lb_service: mock_get_floatingips.return_value = [] self.edge_driver.loadbalancer.delete_cascade( self.context, self.lb_dict, self.completor) mock_delete_lb_service.assert_called_with(LB_SERVICE_ID) service_update.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_with_router_id(self): self.reset_completor() lb_service = {'id': LB_SERVICE_ID, 'connectivity_path': 'infra/%s' % ROUTER_ID} with mock.patch.object(lb_utils, 'get_router_from_network', return_value=None),\ mock.patch.object(self.service_client, 'update_customized', side_effect=n_exc.BadRequest(resource='', msg='') ) as service_update,\ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [lb_service]}),\ mock.patch.object(self.service_client, 'delete' ) as mock_delete_lb_service: self.edge_driver.loadbalancer.delete(self.context, self.lb_dict, self.completor) mock_delete_lb_service.assert_called_with(LB_SERVICE_ID) service_update.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_no_services(self): self.reset_completor() lb_service = {'id': LB_SERVICE_ID, 'connectivity_path': 'infra/%s' % ROUTER_ID} with mock.patch.object(lb_utils, 'get_router_from_network', return_value=None),\ mock.patch.object(self.service_client, 'update_customized', side_effect=n_exc.BadRequest(resource='', msg='') ) as service_update,\ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [lb_service]}),\ mock.patch.object(self.core_plugin, 'service_router_has_services', return_value=False), \ mock.patch.object(self.core_plugin, 'delete_service_router') as delete_sr, \ mock.patch.object(self.service_client, 'delete' ) as mock_delete_lb_service: self.edge_driver.loadbalancer.delete(self.context, self.lb_dict, self.completor) mock_delete_lb_service.assert_called_with(LB_SERVICE_ID) delete_sr.assert_called_once_with(ROUTER_ID) service_update.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_with_port(self): self.reset_completor() lb_service = {'id': LB_SERVICE_ID} neutron_port = {'id': 'port-id', 'name': 'dummy', 'device_owner': lb_const.VMWARE_LB_VIP_OWNER} with mock.patch.object(lb_utils, 'get_router_from_network', return_value=ROUTER_ID),\ mock.patch.object(self.service_client, 'update_customized', side_effect=n_exc.BadRequest(resource='', msg='') ) as service_update,\ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [lb_service]}),\ mock.patch.object(self.core_plugin, 'get_port', return_value=neutron_port), \ mock.patch.object(self.core_plugin, 'update_port' ) as update_port, \ mock.patch.object(self.service_client, 'delete' ) as mock_delete_lb_service: self.edge_driver.loadbalancer.delete(self.context, self.lb_dict, self.completor) mock_delete_lb_service.assert_called_with(LB_SERVICE_ID) service_update.assert_called_once() update_port.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_add_tags_callback(self): callback = p_utils.add_service_tag_callback(LB_ID) # Add a tag body = {'tags': [{'scope': p_utils.SERVICE_LB_TAG_SCOPE, 'tag': 'dummy_id'}]} callback(body) self.assertEqual(2, len(body['tags'])) # Tag already there callback(body) self.assertEqual(2, len(body['tags'])) # Too many tags body['tags'] = [] for x in range(p_utils.SERVICE_LB_TAG_MAX): body['tags'].append({ 'scope': p_utils.SERVICE_LB_TAG_SCOPE, 'tag': 'dummy_id_%s' % x}) self.assertRaises(n_exc.BadRequest, callback, body) # No tags body['tags'] = [] callback(body) self.assertEqual(1, len(body['tags'])) def test_add_tags_callback_only_first(self): callback = p_utils.add_service_tag_callback(LB_ID, only_first=True) # No tags body = {'tags': []} callback(body) self.assertEqual(1, len(body['tags'])) # Tag already there self.assertRaises(n_exc.BadRequest, callback, body) # Another tag exists body['tags'] = [{'scope': p_utils.SERVICE_LB_TAG_SCOPE, 'tag': 'dummy'}] self.assertRaises(n_exc.BadRequest, callback, body) def test_del_tags_callback(self): callback = p_utils.remove_service_tag_callback(LB_ID) # remove a tag body = {'tags': [{'scope': p_utils.SERVICE_LB_TAG_SCOPE, 'tag': 'dummy_id'}, {'scope': p_utils.SERVICE_LB_TAG_SCOPE, 'tag': LB_ID}]} callback(body) self.assertEqual(1, len(body['tags'])) # Tag not there there callback(body) self.assertEqual(1, len(body['tags'])) # Last one body['tags'] = [{'scope': p_utils.SERVICE_LB_TAG_SCOPE, 'tag': LB_ID}] self.assertRaises(n_exc.BadRequest, callback, body) class TestEdgeLbaasV2Listener(BaseTestEdgeLbaasV2): def setUp(self): super(TestEdgeLbaasV2Listener, self).setUp() @property def _tested_entity(self): return 'listener' def _create_listener(self, protocol='HTTP', allowed_cidr=False): self.reset_completor() with mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips, \ mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)), \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [ {'id': LB_SERVICE_ID}]}),\ mock.patch.object(self.core_plugin.nsxpolicy.gateway_policy, 'get', side_effect=nsxlib_exc.ResourceNotFound), \ mock.patch.object(self.core_plugin.nsxpolicy.gateway_policy, 'create_with_entries') as create_gw_pol, \ mock.patch.object(self.vs_client, 'create_or_overwrite' ) as mock_add_virtual_server: mock_get_floatingips.return_value = [] listener = self.listener_dict listener_id = LISTENER_ID if protocol == 'HTTPS': listener = self.https_listener_dict listener_id = HTTP_LISTENER_ID elif protocol == 'UDP': listener = self.udp_listener_dict listener_id = UDP_LISTENER_ID if allowed_cidr: listener = self.cidr_list_dict self.edge_driver.listener.create(self.context, listener, self.completor) mock_add_virtual_server.assert_called_with( application_profile_id=listener_id, description=listener['description'], lb_service_id=LB_ID, ip_address=LB_VIP, tags=mock.ANY, name=mock.ANY, ports=[listener['protocol_port']], virtual_server_id=listener_id, pool_id='', lb_persistence_profile_id='') self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) if not allowed_cidr: create_gw_pol.assert_not_called() else: create_gw_pol.assert_called_once_with( 'LB %s allowed cidrs' % LB_ID, policy_constants.DEFAULT_DOMAIN, map_id=LB_ID, category=policy_constants.CATEGORY_LOCAL_GW, description=mock.ANY, entries=[mock.ANY], tags=mock.ANY) def test_create_http_listener(self): self._create_listener() def test_create_allowed_cidr_listener(self): orig_nsx_ver = self.core_plugin._nsx_version self.core_plugin._nsx_version = '3.1.0' with mock.patch.object(lb_utils, 'get_router_from_network', return_value=ROUTER_ID): self._create_listener(allowed_cidr=True) self.core_plugin._nsx_version = orig_nsx_ver def test_create_https_listener(self): self._create_listener(protocol='HTTPS') def test_create_udp_listener(self): self._create_listener(protocol='UDP') def test_create_terminated_https(self): #TODO(asarfaty): Add test with certificate self.reset_completor() with mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips, \ mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)), \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [ {'id': LB_SERVICE_ID}]}),\ mock.patch.object(self.vs_client, 'create_or_overwrite' ) as mock_add_virtual_server: mock_get_floatingips.return_value = [] self.edge_driver.listener.create( self.context, self.terminated_https_listener_dict, self.completor) mock_add_virtual_server.assert_called_with( application_profile_id=HTTPS_LISTENER_ID, description=self.terminated_https_listener_dict['description'], lb_service_id=LB_ID, ip_address=LB_VIP, tags=mock.ANY, name=mock.ANY, ports=[self.terminated_https_listener_dict['protocol_port']], virtual_server_id=HTTPS_LISTENER_ID, pool_id='', lb_persistence_profile_id='') self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_create_listener_with_default_pool(self): self.reset_completor() listener = lb_models.Listener(LISTENER_ID, LB_TENANT_ID, 'listener1', 'Dummy', self.pool.id, LB_ID, 'HTTP', protocol_port=80, loadbalancer=self.lb, default_pool=self.pool) listener_dict = lb_translators.lb_listener_obj_to_dict(listener) with mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips, \ mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)), \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [ {'id': LB_SERVICE_ID}]}),\ mock.patch.object(self.vs_client, 'create_or_overwrite' ) as mock_add_virtual_server: mock_get_floatingips.return_value = [] listener_dict['connection_limit'] = 7 self.edge_driver.listener.create(self.context, listener_dict, self.completor) mock_add_virtual_server.assert_called_with( application_profile_id=LISTENER_ID, description=listener_dict['description'], lb_service_id=LB_ID, ip_address=LB_VIP, tags=mock.ANY, name=mock.ANY, ports=[listener_dict['protocol_port']], max_concurrent_connections=7, virtual_server_id=LISTENER_ID, pool_id=POOL_ID) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_create_listener_with_used_default_pool(self): self.reset_completor() listener = lb_models.Listener(LISTENER_ID, LB_TENANT_ID, 'listener1', 'Dummy', self.pool.id, LB_ID, 'HTTP', protocol_port=80, loadbalancer=self.lb, default_pool=self.pool) listener_dict = lb_translators.lb_listener_obj_to_dict(listener) with mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips,\ mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)),\ mock.patch.object(self.vs_client, 'list', return_value=[{'pool_path': POOL_ID}]): mock_get_floatingips.return_value = [] self.assertRaises(n_exc.BadRequest, self.edge_driver.listener.create, self.context, listener_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertFalse(self.last_completor_succees) def test_create_listener_with_session_persistence(self): self.reset_completor() listener = lb_models.Listener(LISTENER_ID, LB_TENANT_ID, 'listener1', 'Dummy', self.pool_persistency.id, LB_ID, 'HTTP', protocol_port=80, loadbalancer=self.lb, default_pool=self.pool_persistency) listener_dict = lb_translators.lb_listener_obj_to_dict(listener) with mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips, \ mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)), \ mock.patch.object(self.vs_client, 'create_or_overwrite' ) as mock_add_virtual_server,\ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [ {'id': LB_SERVICE_ID}]}),\ mock.patch.object(self.vs_client, 'get', return_value={}),\ mock.patch.object(self.edge_driver.listener, '_get_pool_tags'),\ mock.patch.object(self.pp_cookie_client, 'create_or_overwrite' ) as mock_create_pp: mock_get_floatingips.return_value = [] listener_dict['connection_limit'] = -1 # Should be ignored self.edge_driver.listener.create(self.context, listener_dict, self.completor) mock_add_virtual_server.assert_called_with( application_profile_id=LISTENER_ID, description=listener_dict['description'], lb_service_id=LB_ID, ip_address=LB_VIP, tags=mock.ANY, name=mock.ANY, ports=[listener_dict['protocol_port']], virtual_server_id=LISTENER_ID, pool_id=listener_dict['default_pool_id']) mock_create_pp.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_create_listener_with_session_persistence_fail(self): self.reset_completor() listener = lb_models.Listener(LISTENER_ID, LB_TENANT_ID, 'listener1', 'Dummy', self.pool_persistency.id, LB_ID, 'TCP', protocol_port=80, loadbalancer=self.lb, default_pool=self.pool_persistency) listener_dict = lb_translators.lb_listener_obj_to_dict(listener) with mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)), \ mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips: mock_get_floatingips.return_value = [] self.assertRaises(n_exc.BadRequest, self.edge_driver.listener.create, self.context, listener_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertFalse(self.last_completor_succees) def test_create_listener_lb_no_name(self, protocol='HTTP'): self.reset_completor() with mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips, \ mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)), \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [ {'id': LB_SERVICE_ID}]}),\ mock.patch.object(self.vs_client, 'create_or_overwrite' ) as mock_add_virtual_server: mock_get_floatingips.return_value = [] listener = copy.deepcopy(self.listener_dict) listener['loadbalancer']['name'] = None listener_id = LISTENER_ID self.edge_driver.listener.create(self.context, listener, self.completor) mock_add_virtual_server.assert_called_with( application_profile_id=listener_id, description=listener['description'], lb_service_id=LB_ID, ip_address=LB_VIP, tags=mock.ANY, name=mock.ANY, ports=[listener['protocol_port']], virtual_server_id=listener_id, pool_id='', lb_persistence_profile_id='') self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_update(self): self.reset_completor() new_listener = lb_models.Listener(LISTENER_ID, LB_TENANT_ID, 'listener1-new', 'new-description', None, LB_ID, protocol_port=80, loadbalancer=self.lb) new_listener_dict = lb_translators.lb_listener_obj_to_dict( new_listener) with mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)), \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [ {'id': LB_SERVICE_ID}]}),\ mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips: mock_get_floatingips.return_value = [] self.edge_driver.listener.update(self.context, self.listener_dict, new_listener_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_update_with_default_pool(self): self.reset_completor() new_listener = lb_models.Listener(LISTENER_ID, LB_TENANT_ID, 'listener1-new', 'new-description', self.pool, LB_ID, protocol_port=80, loadbalancer=self.lb, default_pool=self.pool) new_listener_dict = lb_translators.lb_listener_obj_to_dict( new_listener) with mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)), \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [ {'id': LB_SERVICE_ID}]}),\ mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips: mock_get_floatingips.return_value = [] self.edge_driver.listener.update(self.context, self.listener_dict, new_listener_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_update_with_session_persistence(self): self.reset_completor() new_listener = lb_models.Listener(LISTENER_ID, LB_TENANT_ID, 'listener1-new', 'new-description', self.pool_persistency.id, LB_ID, protocol='HTTP', protocol_port=80, loadbalancer=self.lb, default_pool=self.pool_persistency) new_listener_dict = lb_translators.lb_listener_obj_to_dict( new_listener) with mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips, \ mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)), \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [ {'id': LB_SERVICE_ID}]}),\ mock.patch.object(self.edge_driver.listener, '_get_pool_tags'),\ mock.patch.object(self.vs_client, 'get', return_value={}),\ mock.patch.object(self.vs_client, 'update', return_value={'id': LB_VS_ID}), \ mock.patch.object(self.pp_cookie_client, 'create_or_overwrite' ) as mock_create_pp: mock_get_floatingips.return_value = [] self.edge_driver.listener.update(self.context, self.listener_dict, new_listener_dict, self.completor) mock_create_pp.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_update_with_session_persistence_change(self): self.reset_completor() old_listener = lb_models.Listener(LISTENER_ID, LB_TENANT_ID, 'listener1', 'description', self.pool_persistency.id, LB_ID, protocol='HTTP', protocol_port=80, loadbalancer=self.lb, default_pool=self.pool_persistency) old_listener_dict = lb_translators.lb_listener_obj_to_dict( old_listener) sess_persistence = lb_models.SessionPersistence( POOL_ID, 'SOURCE_IP') pool_persistency = lb_models.Pool('new_pool_id', LB_TENANT_ID, 'pool1', '', None, 'HTTP', 'ROUND_ROBIN', loadbalancer_id=LB_ID, listener=self.listener, listeners=[self.listener], loadbalancer=self.lb, session_persistence=sess_persistence) new_listener = lb_models.Listener(LISTENER_ID, LB_TENANT_ID, 'listener1-new', 'new-description', pool_persistency.id, LB_ID, protocol='HTTP', protocol_port=80, loadbalancer=self.lb, default_pool=pool_persistency) new_listener_dict = lb_translators.lb_listener_obj_to_dict( new_listener) with mock.patch.object(self.core_plugin, 'get_waf_profile_path_and_mode', return_value=(None, None)), \ mock.patch.object(self.pp_client, 'create_or_overwrite' ) as mock_create_pp, \ mock.patch.object(self.pp_generic_client, 'delete' ) as mock_delete_pp, \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [ {'id': LB_SERVICE_ID}]}),\ mock.patch.object(self.core_plugin, 'get_floatingips' ) as mock_get_floatingips, \ mock.patch.object(self.edge_driver.listener, '_get_pool_tags' ) as mock_get_pool_tags: mock_get_pool_tags.return_value = [] mock_get_floatingips.return_value = [] self.edge_driver.listener.update( self.context, old_listener_dict, new_listener_dict, self.completor) mock_create_pp.assert_called_once_with( name='persistence_pool1_new_p...ol_id', persistence_profile_id='new_pool_id_sourceip', tags=mock.ANY) # No reason to check parameters here, it's # all mocked out mock_delete_pp.assert_called_once() def test_delete(self): self.reset_completor() with mock.patch.object(self.service_client, 'get' ) as mock_get_lb_service, \ mock.patch.object(self.core_plugin, 'get_floatingips', return_value=[]), \ mock.patch.object(self.app_client, 'delete' ) as mock_delete_app_profile, \ mock.patch.object(self.vs_client, 'delete' ) as mock_delete_virtual_server: mock_get_lb_service.return_value = { 'id': LB_SERVICE_ID, 'virtual_server_ids': [LB_VS_ID]} self.edge_driver.listener.delete(self.context, self.listener_dict, self.completor) mock_delete_virtual_server.assert_called_with(LB_VS_ID) mock_delete_app_profile.assert_called_with(LISTENER_ID) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_cascade(self): self.reset_completor() with mock.patch.object(self.service_client, 'get' ) as mock_get_lb_service, \ mock.patch.object(self.core_plugin, 'get_floatingips', return_value=[]), \ mock.patch.object(self.app_client, 'delete' ) as mock_delete_app_profile, \ mock.patch.object(self.vs_client, 'delete' ) as mock_delete_virtual_server: mock_get_lb_service.return_value = { 'id': LB_SERVICE_ID, 'virtual_server_ids': [LB_VS_ID]} self.edge_driver.listener.delete_cascade( self.context, self.listener_dict, self.completor) mock_delete_virtual_server.assert_called_with(LB_VS_ID) mock_delete_app_profile.assert_called_with(LISTENER_ID) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) class TestEdgeLbaasV2Pool(BaseTestEdgeLbaasV2): def setUp(self): super(TestEdgeLbaasV2Pool, self).setUp() @property def _tested_entity(self): return 'pool' def test_create(self): self.reset_completor() with mock.patch.object(self.pp_client, 'create_or_overwrite' ) as mock_create_pp, \ mock.patch.object(self.vs_client, 'update', return_value=None ) as mock_vs_update: self.edge_driver.pool.create(self.context, self.pool_dict, self.completor) mock_create_pp.assert_not_called() mock_vs_update.assert_called_once_with( LB_VS_ID, pool_id=LB_POOL_ID, lb_persistence_profile_id=None) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def _test_create_with_persistency(self, vs_data, verify_func): self.reset_completor() with mock.patch.object(self.edge_driver.pool, '_get_pool_tags'),\ mock.patch.object(self.pp_cookie_client, 'create_or_overwrite' ) as mock_create_pp, \ mock.patch.object(self.pp_cookie_client, 'update', return_value=None) as mock_update_pp, \ mock.patch.object(self.vs_client, 'get' ) as mock_vs_get, \ mock.patch.object(self.vs_client, 'update', return_value=None ) as mock_vs_update: mock_vs_get.return_value = vs_data self.edge_driver.pool.create( self.context, self.pool_persistency_dict, self.completor) verify_func(mock_create_pp, mock_update_pp, mock_vs_update) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_create_with_persistency(self): def verify_func(mock_create_pp, mock_update_pp, mock_vs_update): mock_create_pp.assert_called_once_with( cookie_mode='INSERT', cookie_name='meh_cookie', name=mock.ANY, tags=mock.ANY, persistence_profile_id="%s_cookie" % LB_PP_ID) mock_update_pp.assert_not_called() mock_vs_update.assert_called_once_with( LB_VS_ID, pool_id=LB_POOL_ID, lb_persistence_profile_id="%s_cookie" % LB_PP_ID) vs_data = {'id': LB_VS_ID} self._test_create_with_persistency(vs_data, verify_func) def test_create_with_persistency_existing_profile(self): def verify_func(mock_create_pp, mock_update_pp, mock_vs_update): mock_create_pp.assert_not_called() mock_update_pp.assert_called_once_with( LB_PP_ID, cookie_mode='INSERT', cookie_name='meh_cookie', name=mock.ANY, tags=mock.ANY) mock_vs_update.assert_called_once_with( LB_VS_ID, pool_id=LB_POOL_ID, lb_persistence_profile_id=LB_PP_ID) vs_data = {'id': LB_VS_ID, 'lb_persistence_profile_path': LB_PP_ID} self._test_create_with_persistency(vs_data, verify_func) def test_create_with_persistency_no_listener(self): def verify_func(mock_create_pp, mock_update_pp, mock_vs_update): mock_create_pp.assert_not_called() mock_update_pp.assert_not_called() mock_vs_update.assert_not_called() vs_data = {'id': LB_VS_ID, 'lb_persistence_profile_path': LB_PP_ID} self.pool_persistency_dict['listener'] = None self.pool_persistency_dict['listeners'] = [] self._test_create_with_persistency(vs_data, verify_func) def test_create_multiple_listeners(self): """Verify creation will fail if multiple listeners are set""" pool = lb_models.Pool(POOL_ID, LB_TENANT_ID, 'pool1', '', None, 'HTTP', 'ROUND_ROBIN', loadbalancer_id=LB_ID, listeners=[self.listener, self.https_listener], loadbalancer=self.lb) pool_dict = lb_translators.lb_pool_obj_to_dict(pool) self.assertRaises(n_exc.BadRequest, self.edge_driver.pool.create, self.context, pool_dict, self.completor) def test_update(self): self.reset_completor() new_pool = lb_models.Pool(POOL_ID, LB_TENANT_ID, 'pool-name', '', None, 'HTTP', 'LEAST_CONNECTIONS', listener=self.listener) new_pool_dict = lb_translators.lb_pool_obj_to_dict(new_pool) self.edge_driver.pool.update(self.context, self.pool_dict, new_pool_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_update_multiple_listeners(self): """Verify update action will fail if multiple listeners are set""" self.reset_completor() new_pool = lb_models.Pool(POOL_ID, LB_TENANT_ID, 'pool1', '', None, 'HTTP', 'ROUND_ROBIN', loadbalancer_id=LB_ID, listeners=[self.listener, self.https_listener], loadbalancer=self.lb) new_pool_dict = lb_translators.lb_pool_obj_to_dict(new_pool) self.assertRaises(n_exc.BadRequest, self.edge_driver.pool.update, self.context, self.pool_dict, new_pool_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertFalse(self.last_completor_succees) def _test_update_with_persistency(self, vs_data, old_pool, new_pool, verify_func, cookie=False): self.reset_completor() old_pool_dict = lb_translators.lb_pool_obj_to_dict(old_pool) new_pool_dict = lb_translators.lb_pool_obj_to_dict(new_pool) with mock.patch.object(self.edge_driver.pool, '_get_pool_tags'),\ mock.patch.object(self.pp_client, 'create_or_overwrite' ) as mock_create_pp, \ mock.patch.object(self.pp_cookie_client, 'create_or_overwrite' ) as mock_create_cookie_pp, \ mock.patch.object(self.pp_client, 'update', return_value=None ) as mock_update_pp, \ mock.patch.object(self.pp_cookie_client, 'update', return_value=None) as mock_update_cookie_pp, \ mock.patch.object(self.pp_generic_client, 'delete', return_value=None) as mock_delete_pp, \ mock.patch.object(self.vs_client, 'get' ) as mock_vs_get, \ mock.patch.object(self.vs_client, 'update', return_value=None ) as mock_vs_update: mock_vs_get.return_value = vs_data self.edge_driver.pool.update(self.context, old_pool_dict, new_pool_dict, self.completor) verify_func( mock_create_cookie_pp if cookie else mock_create_pp, mock_update_cookie_pp if cookie else mock_update_pp, mock_delete_pp, mock_vs_update) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_update_with_persistency(self): def verify_func(mock_create_pp, mock_update_pp, mock_delete_pp, mock_vs_update): mock_create_pp.assert_called_once_with( cookie_mode='INSERT', cookie_name='meh_cookie', name=mock.ANY, tags=mock.ANY, persistence_profile_id="%s_cookie" % LB_PP_ID) mock_update_pp.assert_not_called() mock_delete_pp.assert_not_called() mock_vs_update.assert_called_once_with( LB_VS_ID, pool_id=LB_POOL_ID, lb_persistence_profile_id="%s_cookie" % LB_PP_ID) vs_data = {'id': LB_VS_ID} self._test_update_with_persistency(vs_data, self.pool, self.pool_persistency, verify_func, cookie=True) def test_update_switch_persistency_type(self): def verify_func(mock_create_pp, mock_update_pp, mock_delete_pp, mock_vs_update): mock_create_pp.assert_called_once_with( name=mock.ANY, tags=mock.ANY, persistence_profile_id="%s_sourceip" % LB_PP_ID) mock_update_pp.assert_not_called() mock_delete_pp.assert_called_once() mock_vs_update.assert_called_once_with( LB_VS_ID, pool_id=LB_POOL_ID, lb_persistence_profile_id="%s_sourceip" % LB_PP_ID) ip_sess_persistence = lb_models.SessionPersistence( POOL_ID, 'SOURCE_IP') pool_ip_persistency = lb_models.Pool( POOL_ID, LB_TENANT_ID, 'pool1', '', None, 'HTTP', 'ROUND_ROBIN', loadbalancer_id=LB_ID, listener=self.listener, listeners=[self.listener], loadbalancer=self.lb, session_persistence=ip_sess_persistence) vs_data = {'id': LB_VS_ID, 'lb_persistence_profile_path': 'meh'} self._test_update_with_persistency(vs_data, self.pool_persistency, pool_ip_persistency, verify_func,) def test_update_remove_persistency(self): def verify_func(mock_create_pp, mock_update_pp, mock_delete_pp, mock_vs_update): mock_create_pp.assert_not_called() mock_update_pp.assert_not_called() mock_delete_pp.assert_called_with(LB_PP_ID) mock_vs_update.assert_called_once_with( LB_VS_ID, pool_id=LB_POOL_ID, lb_persistence_profile_id=None) vs_data = {'id': LB_VS_ID, 'lb_persistence_profile_path': LB_PP_ID} self._test_update_with_persistency(vs_data, self.pool_persistency, self.pool, verify_func) def test_delete(self): self.reset_completor() with mock.patch.object(self.vs_client, 'update', return_value=None ) as mock_update_virtual_server, \ mock.patch.object(self.pool_client, 'delete' ) as mock_delete_pool: self.edge_driver.pool.delete(self.context, self.pool_dict, self.completor) mock_update_virtual_server.assert_called_with( LB_VS_ID, lb_persistence_profile_id=None, pool_id=None) mock_delete_pool.assert_called_with(LB_POOL_ID) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_cascade(self): self.reset_completor() with mock.patch.object(self.pool_client, 'delete' ) as mock_delete_pool: self.edge_driver.pool.delete_cascade( self.context, self.pool_dict, self.completor) mock_delete_pool.assert_called_with(LB_POOL_ID) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_with_persistency(self): self.reset_completor() with mock.patch.object(self.vs_client, 'get' ) as mock_vs_get, \ mock.patch.object(self.vs_client, 'update', return_value=None ) as mock_update_virtual_server, \ mock.patch.object(self.pool_client, 'delete' ) as mock_delete_pool, \ mock.patch.object(self.pp_generic_client, 'delete', return_value=None) as mock_delete_pp: mock_vs_get.return_value = { 'id': LB_VS_ID, 'lb_persistence_profile_path': LB_PP_ID} self.edge_driver.pool.delete( self.context, self.pool_persistency_dict, self.completor) mock_delete_pp.assert_called_once_with(LB_PP_ID) mock_update_virtual_server.assert_called_once_with( LB_VS_ID, lb_persistence_profile_id=None, pool_id=None) mock_delete_pool.assert_called_with(LB_POOL_ID) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def _verify_create(self, cookie_name, cookie_mode, mock_create_pp, mock_update_pp): if cookie_name: mock_create_pp.assert_called_once_with( persistence_profile_id="%s_cookie" % LB_PP_ID, cookie_name=cookie_name, cookie_mode=cookie_mode, name=mock.ANY, tags=mock.ANY) else: mock_create_pp.assert_called_once_with( persistence_profile_id="%s_sourceip" % LB_PP_ID, name=mock.ANY, tags=mock.ANY) # Compare tags - kw args are the last item of a mock call tuple self.assertCountEqual(mock_create_pp.mock_calls[0][-1]['tags'], [{'scope': 'os-lbaas-lb-id', 'tag': 'xxx-xxx'}, {'scope': 'os-lbaas-lb-name', 'tag': 'lb1'}, {'scope': 'os-lbaas-listener-id', 'tag': 'listener-x'}]) mock_update_pp.assert_not_called() def _verify_update(self, cookie_name, cookie_mode, mock_create_pp, mock_update_pp): if cookie_name: mock_update_pp.assert_called_once_with( "%s_cookie" % LB_PP_ID, cookie_name=cookie_name, cookie_mode=cookie_mode, name=mock.ANY, tags=mock.ANY) else: mock_update_pp.assert_called_once_with( "%s_sourceip" % LB_PP_ID, name=mock.ANY, tags=mock.ANY) # Compare tags - kw args are the last item of a mock call tuple self.assertCountEqual(mock_update_pp.mock_calls[0][-1]['tags'], [{'scope': 'os-lbaas-lb-id', 'tag': 'xxx-xxx'}, {'scope': 'os-lbaas-lb-name', 'tag': 'lb1'}, {'scope': 'os-lbaas-listener-id', 'tag': 'listener-x'}]) mock_create_pp.assert_not_called() def _verify_delete(self, cookie_name, cookie_mode, mock_create_pp, mock_update_pp): mock_create_pp.assert_not_called() mock_update_pp.assert_not_called() def _test_setup_session_persistence(self, session_persistence, vs_data, verify_func, cookie_name=None, cookie_mode=None, switch_type=False): with mock.patch.object(self.pp_client, 'create_or_overwrite' ) as mock_create_pp, \ mock.patch.object(self.pp_cookie_client, 'create_or_overwrite' ) as mock_create_cookie_pp, \ mock.patch.object(self.pp_client, 'update', return_value=None, ) as mock_update_pp,\ mock.patch.object(self.pp_cookie_client, 'update', return_value=None) as mock_update_cookie_pp: self.pool.session_persistence = session_persistence pool_dict = lb_translators.lb_pool_obj_to_dict(self.pool) pp_id, post_func = p_utils.setup_session_persistence( self.nsxpolicy, pool_dict, [], switch_type, self.listener_dict, vs_data) pp_id_suffix = "" if session_persistence: if session_persistence.type == "SOURCE_IP": pp_id_suffix = "sourceip" elif session_persistence.type in ["HTTP_COOKIE", "APP_COOKIE"]: pp_id_suffix = "cookie" self.assertEqual("%s_%s" % (LB_PP_ID, pp_id_suffix), pp_id) else: self.assertIsNone(pp_id) self.assertEqual( (self.nsxpolicy, vs_data['lb_persistence_profile_path'],), post_func.args) verify_func(cookie_name, cookie_mode, mock_create_cookie_pp if cookie_name else mock_create_pp, mock_update_cookie_pp if cookie_name else mock_update_pp) def test_setup_session_persistence_sourceip_new_profile(self): sess_persistence = lb_models.SessionPersistence( "%s_sourceip" % LB_PP_ID, 'SOURCE_IP') self._test_setup_session_persistence( sess_persistence, {'id': LB_VS_ID}, self._verify_create) def test_setup_session_persistence_httpcookie_new_profile(self): sess_persistence = lb_models.SessionPersistence( "%s_cookie" % LB_PP_ID, 'HTTP_COOKIE') self._test_setup_session_persistence( sess_persistence, {'id': LB_VS_ID}, self._verify_create, 'default_cookie_name', 'INSERT') def test_setup_session_persistence_appcookie_new_profile(self): sess_persistence = lb_models.SessionPersistence( "%s_cookie" % LB_PP_ID, 'APP_COOKIE', 'whatever') self._test_setup_session_persistence( sess_persistence, {'id': LB_VS_ID}, self._verify_create, 'whatever', 'REWRITE') def test_setup_session_persistence_none_from_existing(self): sess_persistence = None self._test_setup_session_persistence( sess_persistence, {'id': LB_VS_ID, 'lb_persistence_profile_path': "%s_sourceip" % LB_PP_ID}, self._verify_delete) def test_setup_session_persistence_sourceip_from_existing(self): sess_persistence = lb_models.SessionPersistence( "%s_sourceip" % LB_PP_ID, 'SOURCE_IP') self._test_setup_session_persistence( sess_persistence, {'id': LB_VS_ID, 'lb_persistence_profile_path': "%s_sourceip" % LB_PP_ID}, self._verify_update) def test_setup_session_persistence_httpcookie_from_existing(self): sess_persistence = lb_models.SessionPersistence( "%s_cookie" % LB_PP_ID, 'HTTP_COOKIE') self._test_setup_session_persistence( sess_persistence, {'id': LB_VS_ID, 'lb_persistence_profile_path': '%s_cookie' % LB_PP_ID}, self._verify_update, 'default_cookie_name', 'INSERT') def test_setup_session_persistence_appcookie_from_existing(self): sess_persistence = lb_models.SessionPersistence( "%s_cookie" % LB_PP_ID, 'APP_COOKIE', 'whatever') self._test_setup_session_persistence( sess_persistence, {'id': LB_VS_ID, 'lb_persistence_profile_path': '%s_cookie' % LB_PP_ID}, self._verify_update, 'whatever', 'REWRITE') class TestEdgeLbaasV2Member(BaseTestEdgeLbaasV2): def setUp(self): super(TestEdgeLbaasV2Member, self).setUp() @property def _tested_entity(self): return 'member' def test_create(self): self.reset_completor() with mock.patch.object(self.lbv2_driver.plugin, 'get_pool_members' ) as mock_get_pool_members, \ mock.patch.object(lb_utils, 'get_network_from_subnet' ) as mock_get_network, \ mock.patch.object(lb_utils, 'get_router_from_network' ) as mock_get_router, \ mock.patch.object(self.service_client, 'get_router_lb_service' ) as mock_get_lb_service, \ mock.patch.object(self.pool_client, 'get' ) as mock_get_pool, \ mock.patch.object(self.pool_client, 'create_pool_member_and_add_to_pool' ) as mock_update_pool_with_members: mock_get_pool_members.return_value = [self.member] mock_get_network.return_value = LB_NETWORK mock_get_router.return_value = LB_ROUTER_ID mock_get_lb_service.return_value = {'id': LB_SERVICE_ID} mock_get_pool.return_value = LB_POOL self.edge_driver.member.create( self.context, self.member_dict, self.completor) mock_update_pool_with_members.assert_called_with( LB_POOL_ID, MEMBER_ADDRESS, port=self.member_dict['protocol_port'], display_name=mock.ANY, weight=self.member_dict['weight'], backup_member=self.member_dict.get('backup', False), admin_state='ENABLED') self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_create_external_vip(self): self.reset_completor() lb_service = {'id': LB_SERVICE_ID} with mock.patch.object(self.lbv2_driver.plugin, 'get_pool_members' ) as mock_get_pool_members, \ mock.patch.object(lb_utils, 'get_network_from_subnet' ) as mock_get_network, \ mock.patch.object(lb_utils, 'get_router_from_network' ) as mock_get_router, \ mock.patch.object(self.service_client, 'get_router_lb_service' ) as mock_get_lb_service, \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [lb_service]}),\ mock.patch.object(self.core_plugin, 'service_router_has_services', return_value=False) as plugin_has_sr,\ mock.patch.object(self.core_plugin, 'service_router_has_loadbalancers', return_value=False),\ mock.patch.object(self.pool_client, 'get' ) as mock_get_pool, \ mock.patch.object(self.core_plugin, '_find_router_gw_subnets', return_value=[]),\ mock.patch.object(self.core_plugin, 'get_floatingips', return_value=[{ 'fixed_ip_address': MEMBER_ADDRESS, 'floating_ip_address': '1.1.1.1', 'router_id': LB_ROUTER_ID}]),\ mock.patch.object(self.pool_client, 'create_pool_member_and_add_to_pool' ) as mock_update_pool_with_members: mock_get_pool_members.return_value = [self.member] mock_get_network.return_value = EXT_LB_NETWORK mock_get_router.return_value = LB_ROUTER_ID mock_get_lb_service.return_value = {'id': LB_SERVICE_ID} mock_get_pool.return_value = LB_POOL self.edge_driver.member.create( self.context, self.member_dict, self.completor) mock_update_pool_with_members.assert_called_with( LB_POOL_ID, MEMBER_ADDRESS, port=self.member_dict['protocol_port'], display_name=mock.ANY, weight=self.member_dict['weight'], backup_member=self.member_dict.get('backup', False), admin_state='ENABLED') self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) plugin_has_sr.assert_called_once_with(mock.ANY, LB_ROUTER_ID) def test_create_external_vip_router_used(self): self.reset_completor() lb_service = {'id': LB_SERVICE_ID} with mock.patch.object(self.lbv2_driver.plugin, 'get_pool_members' ) as mock_get_pool_members, \ mock.patch.object(lb_utils, 'get_network_from_subnet' ) as mock_get_network, \ mock.patch.object(lb_utils, 'get_router_from_network' ) as mock_get_router, \ mock.patch.object(self.service_client, 'get_router_lb_service' ) as mock_get_lb_service, \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [lb_service]}),\ mock.patch.object(self.core_plugin, 'service_router_has_loadbalancers', return_value=True),\ mock.patch.object(self.pool_client, 'get' ) as mock_get_pool, \ mock.patch.object(self.core_plugin, '_find_router_gw_subnets', return_value=[]),\ mock.patch.object(self.core_plugin, 'get_floatingips', return_value=[{ 'fixed_ip_address': MEMBER_ADDRESS, 'router_id': LB_ROUTER_ID}]): mock_get_pool_members.return_value = [self.member] mock_get_network.return_value = EXT_LB_NETWORK mock_get_router.return_value = LB_ROUTER_ID mock_get_lb_service.return_value = {'id': LB_SERVICE_ID} mock_get_pool.return_value = LB_POOL self.assertRaises( n_exc.BadRequest, self.edge_driver.member.create, self.context, self.member_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertFalse(self.last_completor_succees) def test_create_external_vip_no_fip(self): self.reset_completor() lb_service = {'id': LB_SERVICE_ID} with mock.patch.object(self.lbv2_driver.plugin, 'get_pool_members' ) as mock_get_pool_members, \ mock.patch.object(lb_utils, 'get_network_from_subnet' ) as mock_get_network, \ mock.patch.object(lb_utils, 'get_router_from_network' ) as mock_get_router, \ mock.patch.object(self.service_client, 'get_router_lb_service' ) as mock_get_lb_service, \ mock.patch.object(self.core_plugin.nsxpolicy, 'search_by_tags', return_value={'results': [lb_service]}),\ mock.patch.object(self.core_plugin, 'service_router_has_loadbalancers', return_value=True),\ mock.patch.object(self.pool_client, 'get' ) as mock_get_pool, \ mock.patch.object(self.core_plugin, '_find_router_gw_subnets', return_value=[]),\ mock.patch.object(self.core_plugin, 'get_floatingips', return_value=[]): mock_get_pool_members.return_value = [self.member] mock_get_network.return_value = EXT_LB_NETWORK mock_get_router.return_value = LB_ROUTER_ID mock_get_lb_service.return_value = {'id': LB_SERVICE_ID} mock_get_pool.return_value = LB_POOL self.assertRaises( n_exc.BadRequest, self.edge_driver.member.create, self.context, self.member_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertFalse(self.last_completor_succees) def test_update(self): self.reset_completor() new_member = lb_models.Member(MEMBER_ID, LB_TENANT_ID, POOL_ID, MEMBER_ADDRESS, 80, 2, pool=self.pool, name='member-nnn-nnn') new_member_dict = lb_translators.lb_member_obj_to_dict(new_member) with mock.patch.object(self.pool_client, 'get' ) as mock_get_pool, \ mock.patch.object(lb_utils, 'get_network_from_subnet' ) as mock_get_network_from_subnet: mock_get_pool.return_value = LB_POOL_WITH_MEMBER mock_get_network_from_subnet.return_value = LB_NETWORK self.edge_driver.member.update(self.context, self.member_dict, new_member_dict, self.completor) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete(self): self.reset_completor() with mock.patch.object(self.pool_client, 'get' ) as mock_get_pool, \ mock.patch.object(lb_utils, 'get_network_from_subnet' ) as mock_get_network_from_subnet, \ mock.patch.object(self.pool_client, 'remove_pool_member' ) as mock_update_pool_with_members: mock_get_pool.return_value = LB_POOL_WITH_MEMBER mock_get_network_from_subnet.return_value = LB_NETWORK self.edge_driver.member.delete(self.context, self.member_dict, self.completor) mock_update_pool_with_members.assert_called_with( LB_POOL_ID, MEMBER_ADDRESS, port=self.member_dict['protocol_port']) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_cascade(self): self.reset_completor() with mock.patch.object(self.pool_client, 'get' ) as mock_get_pool, \ mock.patch.object(lb_utils, 'get_network_from_subnet' ) as mock_get_network_from_subnet, \ mock.patch.object(self.pool_client, 'remove_pool_member' ) as mock_update_pool_with_members: mock_get_pool.return_value = LB_POOL_WITH_MEMBER mock_get_network_from_subnet.return_value = LB_NETWORK self.edge_driver.member.delete_cascade( self.context, self.member_dict, self.completor) mock_update_pool_with_members.assert_not_called() self.assertFalse(self.last_completor_called) class TestEdgeLbaasV2HealthMonitor(BaseTestEdgeLbaasV2): def setUp(self): super(TestEdgeLbaasV2HealthMonitor, self).setUp() @property def _tested_entity(self): return 'health_monitor' def test_create(self): self.reset_completor() with mock.patch.object(self.monitor_client, 'create_or_overwrite' ) as mock_create_monitor, \ mock.patch.object(self.pool_client, 'add_monitor_to_pool' ) as mock_add_monitor_to_pool: self.edge_driver.healthmonitor.create( self.context, self.hm_dict, self.completor) mock_create_monitor.assert_called_once() mock_add_monitor_to_pool.assert_called_with( LB_POOL_ID, mock.ANY) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_create_http(self): self.reset_completor() with mock.patch.object(self.http_monitor_client, 'create_or_overwrite' ) as mock_create_monitor, \ mock.patch.object(self.pool_client, 'add_monitor_to_pool' ) as mock_add_monitor_to_pool: # Verify HTTP-specific monitor parameters are added self.edge_driver.healthmonitor.create( self.context, self.hm_http_dict, self.completor) kw_args = mock_create_monitor.mock_calls[0][2] self.assertEqual(self.hm_http.http_method, kw_args.get('request_method')) self.assertEqual(self.hm_http.url_path, kw_args.get('request_url')) mock_add_monitor_to_pool.assert_called_with( LB_POOL_ID, mock.ANY) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_create_without_pool(self): self.reset_completor() hm = lb_models.HealthMonitor(HM_ID, LB_TENANT_ID, 'PING', 3, 3, 1, pool=None, name='hm1') hm_dict = lb_translators.lb_hm_obj_to_dict(hm) with mock.patch.object(self.monitor_client, 'create_or_overwrite' ) as mock_create_monitor, \ mock.patch.object(self.pool_client, 'add_monitor_to_pool' ) as mock_add_monitor_to_pool: self.assertRaises( n_exc.BadRequest, self.edge_driver.healthmonitor.create, self.context, hm_dict, self.completor) mock_create_monitor.assert_called_once() mock_add_monitor_to_pool.assert_not_called() self.assertTrue(self.last_completor_called) self.assertFalse(self.last_completor_succees) def test_update(self): self.reset_completor() with mock.patch.object(self.monitor_client, 'update' ) as mock_update_monitor: new_hm = lb_models.HealthMonitor( HM_ID, LB_TENANT_ID, 'PING', 5, 5, 5, pool=self.pool, name='new_name') new_hm_dict = lb_translators.lb_hm_obj_to_dict(new_hm) self.edge_driver.healthmonitor.update( self.context, self.hm_dict, new_hm_dict, self.completor) mock_update_monitor.assert_called_with( LB_MONITOR_ID, name=mock.ANY, fall_count=5, interval=5, timeout=5) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete(self): self.reset_completor() with mock.patch.object(self.pool_client, 'remove_monitor_from_pool' ) as mock_remove_monitor_from_pool, \ mock.patch.object(self.monitor_client, 'delete' ) as mock_delete_monitor: self.edge_driver.healthmonitor.delete( self.context, self.hm_dict, self.completor) mock_remove_monitor_from_pool.assert_called_with( LB_POOL_ID, mock.ANY) mock_delete_monitor.assert_called_with(LB_MONITOR_ID) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_cascade(self): self.reset_completor() with mock.patch.object(self.pool_client, 'remove_monitor_from_pool' ) as mock_remove_monitor_from_pool, \ mock.patch.object(self.monitor_client, 'delete' ) as mock_delete_monitor: self.edge_driver.healthmonitor.delete_cascade( self.context, self.hm_dict, self.completor) mock_remove_monitor_from_pool.assert_called_with( LB_POOL_ID, mock.ANY) mock_delete_monitor.assert_called_with(LB_MONITOR_ID) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) class TestEdgeLbaasV2L7Policy(BaseTestEdgeLbaasV2): def setUp(self): super(TestEdgeLbaasV2L7Policy, self).setUp() @property def _tested_entity(self): return 'l7policy' def test_create(self): self.reset_completor() with mock.patch.object(self.vs_client, 'get' ) as mock_get_virtual_server, \ mock.patch.object(self.vs_client, 'add_lb_rule' ) as mock_update_virtual_server: mock_get_virtual_server.return_value = {'id': LB_VS_ID} self.edge_driver.l7policy.create( self.context, self.l7policy_dict, self.completor) mock_update_virtual_server.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_update(self): self.reset_completor() new_l7policy = lb_models.L7Policy(L7POLICY_ID, LB_TENANT_ID, name='new-policy', listener_id=LISTENER_ID, action='REJECT', listener=self.listener, position=2) new_policy_dict = lb_translators.lb_l7policy_obj_to_dict(new_l7policy) vs_with_rules = { 'id': LB_VS_ID, 'rule_ids': [LB_RULE_ID, 'abc', 'xyz'] } with mock.patch.object(self.vs_client, 'get' ) as mock_get_virtual_server, \ mock.patch.object(self.vs_client, 'update_lb_rule' ) as mock_update_virtual_server: mock_get_virtual_server.return_value = vs_with_rules self.edge_driver.l7policy.update(self.context, self.l7policy_dict, new_policy_dict, self.completor) mock_update_virtual_server.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete(self): self.reset_completor() with mock.patch.object(self.vs_client, 'remove_lb_rule' ) as mock_vs_remove_rule: self.edge_driver.l7policy.delete( self.context, self.l7policy_dict, self.completor) mock_vs_remove_rule.assert_called_with(LB_VS_ID, mock.ANY, check_name_suffix=True) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_cascade(self): self.reset_completor() with mock.patch.object(self.vs_client, 'remove_lb_rule' ) as mock_vs_remove_rule: self.edge_driver.l7policy.delete_cascade( self.context, self.l7policy_dict, self.completor) mock_vs_remove_rule.assert_called_with(LB_VS_ID, mock.ANY, check_name_suffix=True) self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) class TestEdgeLbaasV2L7Rule(BaseTestEdgeLbaasV2): def setUp(self): super(TestEdgeLbaasV2L7Rule, self).setUp() @property def _tested_entity(self): return 'l7rule' def test_create(self): self.reset_completor() self.l7policy.rules = [self.l7rule] with mock.patch.object(self.vs_client, 'update_lb_rule' ) as mock_update_virtual_server: self.edge_driver.l7rule.create( self.context, self.l7rule_dict, self.completor) mock_update_virtual_server.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_update(self): self.reset_completor() new_l7rule = lb_models.L7Rule(L7RULE_ID, LB_TENANT_ID, l7policy_id=L7POLICY_ID, compare_type='STARTS_WITH', invert=True, type='COOKIE', key='cookie1', value='xxxxx', policy=self.l7policy) new_rule_dict = lb_translators.lb_l7rule_obj_to_dict(new_l7rule) self.l7policy.rules = [new_l7rule] with mock.patch.object(self.vs_client, 'update_lb_rule' ) as mock_update_virtual_server: self.edge_driver.l7rule.update(self.context, self.l7rule_dict, new_rule_dict, self.completor) mock_update_virtual_server.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete(self): self.reset_completor() self.l7policy.rules = [self.l7rule] with mock.patch.object(self.vs_client, 'update_lb_rule' ) as mock_update_virtual_server: self.edge_driver.l7rule.delete( self.context, self.l7rule_dict, self.completor) mock_update_virtual_server.assert_called_once() self.assertTrue(self.last_completor_called) self.assertTrue(self.last_completor_succees) def test_delete_cascade(self): self.reset_completor() self.l7policy.rules = [self.l7rule] with mock.patch.object(self.vs_client, 'update_lb_rule' ) as mock_update_virtual_server: self.edge_driver.l7rule.delete_cascade( self.context, self.l7rule_dict, self.completor) mock_update_virtual_server.assert_not_called() self.assertFalse(self.last_completor_called)

48.44684

79

0.574474

10,680

98,880

4.925749

0.041011

0.040204

0.067006

0.0679

0.85481

0.823484

0.800521

0.780581

0.754576

0.722546

0

0.004151

0.339775

98,880

2,040

80

48.470588

0.801679

0.014513

0

0.670354

0

0.079428

0.024159

0

0.00049

0.126659

1

0.059181

false

0

0.011615

0.004425

0.079646

0

null

0

1

0

null

0

6

5e7ec730a85c58e6f5ecba1531a79f5d2d5de1ba

23,477

py

Python

SCODE-G/text_to_code/error_analysis.py

rizwan09/REDCODER

e889b3d3f37573be8418c0ac536c2201e8f1be26

[ "MIT" ]

22

2021-11-15T06:00:13.000Z

2022-03-25T14:33:15.000Z

SCODE-G/text_to_code/error_analysis.py

rizwan09/REDCODER

e889b3d3f37573be8418c0ac536c2201e8f1be26

[ "MIT" ]

2

2021-12-02T19:22:51.000Z

2022-02-19T10:50:58.000Z

SCODE-G/text_to_code/error_analysis.py

rizwan09/REDCODER

e889b3d3f37573be8418c0ac536c2201e8f1be26

[ "MIT" ]

2

2021-10-07T15:27:25.000Z

2021-12-08T07:12:13.000Z

import os, ipdb, csv import json import sys import weighted_ngram_match import syntax_match import dataflow_match import bleu_code from bleu import _bleu base_path='/home/rizwan/DPR_models/' output_path=base_path+'prediction_ori_raw_top_1_bleu_70.30.txt' output_path='/local/rizwan/workspace/projects/RaProLanG/plbart_ori_top_1_masked/-java-ms100000-wu5000-bsz64/output.hyp' output_path='/local/rizwan/workspace/projects/RaProLanG/maksed_with_top_2-java-ms100000-wu5000-bsz64/output.hyp' input_path=base_path+'source_ori_raw_top_1.txt' target_path=base_path+'test.target' annotation_path=base_path+'input_target_output_coder.csv' plbart_pred_path=base_path+'plbart_ori_pred.txt' ensamble_preds_path=base_path+'ensamble_pred.txt' retrieved_code_path=base_path+'retrieved.txt' def check_retrived_acc(retrieved_code_path, max_k=10, lang='python'): with open(retrieved_code_path) as f: retrieved_code = json.load(f) scores = [[0 for i in range(max_k)] for j in range(len(retrieved_code))] refss = [] hypss = [] dpr_scores= [ ] for idx, ex in enumerate(retrieved_code): try: target = ex['answers'].strip() except: ex = retrieved_code[ex] target = ex['answers'].strip() refss.append(target) for rank, ctx in enumerate(ex['ctxs']): try: dpr_scores.append(ctx['score']) except: dpr_scores.append(ctx['_score']) cand = ctx["text"].strip() if rank==0: hypss.append(cand) if cand==target: for j in range(rank, max_k): scores[idx][j] = 1 for i in range(max_k): EM = sum([score[i] for score in scores])/len(retrieved_code) print("At top ", i, " EM/Recall: ", EM*100, 'dpr score: ', dpr_scores[i]) if lang == 'js': lang = 'javascript' alpha, beta, gamma, theta = 0.25, 0.25, 0.25, 0.25 # preprocess inputs pre_references = [[ref.strip() for ref in refss]] hypothesis = [hyp.strip() for hyp in hypss] for i in range(len(pre_references)): assert len(hypothesis) == len(pre_references[i]) references = [] for i in range(len(hypothesis)): ref_for_instance = [] for j in range(len(pre_references)): ref_for_instance.append(pre_references[j][i]) references.append(ref_for_instance) assert len(references) == len(pre_references) * len(hypothesis) # calculate ngram match (BLEU) tokenized_hyps = [x.split() for x in hypothesis] tokenized_refs = [[x.split() for x in reference] for reference in references] ngram_match_score = bleu_code.corpus_bleu(tokenized_refs, tokenized_hyps) # calculate weighted ngram match keywords = [x.strip() for x in open('keywords/' + lang + '.txt', 'r', encoding='utf-8').readlines()] def make_weights(reference_tokens, key_word_list): return {token: 1 if token in key_word_list else 0.2 \ for token in reference_tokens} tokenized_refs_with_weights = [[[reference_tokens, make_weights(reference_tokens, keywords)] \ for reference_tokens in reference] for reference in tokenized_refs] weighted_ngram_match_score = weighted_ngram_match.corpus_bleu(tokenized_refs_with_weights, tokenized_hyps) # calculate syntax match syntax_match_score = syntax_match.corpus_syntax_match(references, hypothesis, lang) # calculate dataflow match dataflow_match_score = dataflow_match.corpus_dataflow_match(references, hypothesis, lang) # print('ngram match: {0}, weighted ngram match: {1}, syntax_match: {2}, dataflow_match: {3}'. \ # format(ngram_match_score, weighted_ngram_match_score, syntax_match_score, dataflow_match_score)) print('Ngram match:\t%.2f\nWeighted ngram:\t%.2f\nSyntax match:\t%.2f\nDataflow match:\t%.2f' % ( \ ngram_match_score * 100, weighted_ngram_match_score * 100, syntax_match_score * 100, dataflow_match_score * 100)) code_bleu_score = alpha * ngram_match_score \ + beta * weighted_ngram_match_score \ + gamma * syntax_match_score \ + theta * dataflow_match_score print('CodeBLEU score: %.2f' % (code_bleu_score * 100.0)) def check_retrived_acc_other_than_without_ref(retrieved_code_path, max_k=10, lang="python"): with open(retrieved_code_path) as f: retrieved_code = json.load(f) scores = [[] for j in range(len(retrieved_code))] refss = [] hypss = [] dpr_scores=[] for idx, ex in enumerate(retrieved_code): try: target = ex['answers'].strip() except: ex = retrieved_code[ex] target = ex['answers'].strip() refss.append(target) inserted=False for rank, ctx in enumerate(ex['ctxs']): cand = ctx["text"].strip() if cand!=target: if not inserted: hypss.append(cand) inserted=True scores[idx].append(_bleu(target, cand)) try: dpr_scores.append(ctx['score']) except: dpr_scores.append(ctx['_score']) if not inserted: hypss.append("") if len(scores[idx])!=max_k: for i in range(len(scores[idx]), max_k): scores[idx].append(0) min_len = min([len(score) for score in scores[:-1]]) print (min_len) for i in range(min_len): Blue = sum([score[i] for score in scores])/len(retrieved_code) print("At top ", i, " Bleu: ", Blue, 'dpr score: ', dpr_scores[i]) if lang == 'js': lang = 'javascript' alpha, beta, gamma, theta = 0.25, 0.25, 0.25, 0.25 # preprocess inputs pre_references = [[ref.strip() for ref in refss]] hypothesis = [hyp.strip() for hyp in hypss] for i in range(len(pre_references)): if len(hypothesis) != len(pre_references[i]): import ipdb ipdb.set_trace() references = [] for i in range(len(hypothesis)): ref_for_instance = [] for j in range(len(pre_references)): ref_for_instance.append(pre_references[j][i]) references.append(ref_for_instance) assert len(references) == len(pre_references) * len(hypothesis) # calculate ngram match (BLEU) tokenized_hyps = [x.split() for x in hypothesis] tokenized_refs = [[x.split() for x in reference] for reference in references] ngram_match_score = bleu_code.corpus_bleu(tokenized_refs, tokenized_hyps) # calculate weighted ngram match keywords = [x.strip() for x in open('keywords/' + lang + '.txt', 'r', encoding='utf-8').readlines()] def make_weights(reference_tokens, key_word_list): return {token: 1 if token in key_word_list else 0.2 \ for token in reference_tokens} tokenized_refs_with_weights = [[[reference_tokens, make_weights(reference_tokens, keywords)] \ for reference_tokens in reference] for reference in tokenized_refs] weighted_ngram_match_score = weighted_ngram_match.corpus_bleu(tokenized_refs_with_weights, tokenized_hyps) # calculate syntax match syntax_match_score = syntax_match.corpus_syntax_match(references, hypothesis, lang) # calculate dataflow match dataflow_match_score = dataflow_match.corpus_dataflow_match(references, hypothesis, lang) # print('ngram match: {0}, weighted ngram match: {1}, syntax_match: {2}, dataflow_match: {3}'. \ # format(ngram_match_score, weighted_ngram_match_score, syntax_match_score, dataflow_match_score)) print('Ngram match:\t%.2f\nWeighted ngram:\t%.2f\nSyntax match:\t%.2f\nDataflow match:\t%.2f' % ( \ ngram_match_score * 100, weighted_ngram_match_score * 100, syntax_match_score * 100, dataflow_match_score * 100)) code_bleu_score = alpha * ngram_match_score \ + beta * weighted_ngram_match_score \ + gamma * syntax_match_score \ + theta * dataflow_match_score print('CodeBLEU score: %.2f' % (code_bleu_score * 100.0)) def get_num_word_tokens(code): count = 0 for w in code.split(): if len(w)>1: count+=1 return count def error_analysis(): with open(annotation_path, 'w') as csvfile, \ open(ensamble_preds_path, 'w') as ensamble_pred_f, \ open(retrieved_code_path, 'w') as retrieved_f: csvwriter = csv.writer(csvfile) tars = [x.strip() for x in open(target_path, 'r', encoding='utf-8').readlines()] pres = [x.strip() for x in open(output_path, 'r', encoding='utf-8').readlines()] plbart_preds = [x.strip() for x in open(plbart_pred_path, 'r', encoding='utf-8').readlines()] retrievd_codes = [x.split('_CODE_SEP_')[-1].strip() for x in open(input_path, 'r', encoding='utf-8').readlines()] NLs = [x.split('concode')[0].strip() for x in open(input_path, 'r', encoding='utf-8').readlines()] correct_pred_coount = 0 correct_retrival_count = 0 copy_cpount = 0 not_copied_but_correct = 0 copied_and_correct = 0 for id, (nl, retrievd_code, output, target) in enumerate(zip(NLs, retrievd_codes, pres, tars)): retrieved_f.write(retrievd_code+"\n") blue_score=_bleu(target, output) # print(target, output, blue_score) csvwriter.writerow([nl, retrievd_code, target, output, output==target, retrievd_code==target, retrievd_code==output, blue_score]) if output==target: correct_pred_coount+=1 if retrievd_code==target: correct_retrival_count+=1 if retrievd_code==output: copy_cpount+=1 ensamble_pred_f.write(output+"\n") if output==target: copied_and_correct+=1 else: # print("wring: ", output, "->", plbart_preds[id]) if get_num_word_tokens(retrievd_code)>15: ensamble_pred_f.write(output + "\n") else: ensamble_pred_f.write(plbart_preds[id] + "\n") if output==target: not_copied_but_correct+=1 print("Acc/Em: ", correct_pred_coount, "in percentage: ", correct_pred_coount/len(tars)*100) print("Retrieved/: ", correct_retrival_count, "in percentage: ", correct_retrival_count/len(tars)*100) print("Copied: ", copy_cpount, "in percentage: ", copy_cpount/len(tars)*100) print("Not Copied: ", len(tars)-copy_cpount, "in percentage: ", (len(tars)-copy_cpount)/len(tars)*100) print("Not Copied but correct: ", not_copied_but_correct, "in percentage of not copied: ", not_copied_but_correct/(len(tars)-copy_cpount)*100) print("Copied and correct: ", copied_and_correct, "in percentage of copied: ", copied_and_correct/(copy_cpount)*100) # error_analysis() def call_ret(lang, k=3): retrievd_test_file='/local/rizwan/DPR_models/csnet/'+lang+'_csnet_pos_only_retrieval_dedup_test_30.json' print(retrievd_test_file) print("---" * 50) print("With Ref:: ") print("---" * 50) check_retrived_acc(retrievd_test_file, max_k=k, lang=lang) print("---"*50) print("Without Ref:: ") print("---" * 50) check_retrived_acc_other_than_without_ref(retrievd_test_file, max_k=k, lang=lang) # lang='java' # call_ret(lang, k=1) # lang='python' # call_ret(lang, k=1) # # # retrievd_test_file='/local/rizwan/DPR_models/biencoder_models_concode_without_code_tokens/java/python_csnet_pos_only_retrieval_dedup_test_20.json' # print(retrievd_test_file) # check_retrived_acc(retrievd_test_file, lang="python") # check_retrived_acc_other_than_without_ref(retrievd_test_file, lang="python") # # # # # # retrievd_test_file='/local/rizwan/DPR_models/biencoder_models_concode_without_code_tokens/java/java_csnet_pos_only_retrieval_dedup_test_20.json' # print(retrievd_test_file) # check_retrived_acc(retrievd_test_file, lang="java") # check_retrived_acc_other_than_without_ref(retrievd_test_file) retrievd_test_file='/local/rizwan/DPR_models/biencoder_models_concode_without_code_tokens/java/test_100.json' check_retrived_acc(retrievd_test_file, lang="java") check_retrived_acc_other_than_without_ref(retrievd_test_file) exit(0) # RETDIR='/local/rizwan/DPR_models/csnet/' # langs=[ 'python', 'java'] # test_ret_paths = { lang: RETDIR+lang+'_csnet_pos_only_retrieval_dedup_test_30.json' for lang in langs} # for lang in langs: # print('lang: ', lang, 'with') # check_retrived_acc(test_ret_paths[lang], lang=lang) # print('lang: ', lang, 'without') # check_retrived_acc_other_than_without_ref(test_ret_paths[lang], lang=lang) # RETDIR='/local/rizwan/workspace/projects/RaProLang/retrieval/bm25/' # langs=[ 'python', 'java'] # test_ret_paths = { lang: RETDIR+'codexglue-csnet-'+lang+'.test_bm25.json' for lang in langs} # for lang in langs: # print('lang: ', lang, 'with') # check_retrived_acc(test_ret_paths[lang], lang=lang) # print('lang: ', lang, 'without') # check_retrived_acc_other_than_without_ref(test_ret_paths[lang], lang=lang) # # print('Concode lang: ', lang, 'with') # filepth='/local/rizwan/workspace/projects/RaProLang/retrieval/bm25/concode.test_bm25.json' # check_retrived_acc(filepth, lang='java') # print('Concode lang: ', lang, 'without') # check_retrived_acc_other_than_without_ref(filepth, lang='java') # RETDIR='/local/rizwan/workspace/projects/RaProLang/retrieval/bm25/code_to_text/' # langs=[ 'java', 'python',] # test_ret_paths = { lang: RETDIR+'codexglue-csnet-'+lang+'.test_code_text_bm25.json' for lang in langs} # for lang in langs: # print('lang: ', lang, 'with') # check_retrived_acc(test_ret_paths[lang], lang=lang) # print('lang: ', lang, 'without') # check_retrived_acc_other_than_without_ref(test_ret_paths[lang], lang=lang) redcoder_ext_f='/local/rizwan/workspace/projects/RaProLanG/plbart-codexglue-csnet-python-comments-top-5-without-python-ms100000-wu5000-bsz64/output.hyp' redcoder_ext_f='/local/rizwan/workspace/projects/RaProLanG/plbart-codexglue-csnet-python-comments-top-5-without-python-ms100000-wu5000-bsz64/output.hyp' redcoder_f='/local/rizwan/workspace/projects/RaProLanG/plbart-codexglue-csnet-python-with-top-5-retrived-from-no-ref-no-mask-python-ms100000-wu5000-bsz72/output.hyp' plbart_f='/local/rizwan/workspace/projects/RaProLanG/plbart-codexglue-csnet-python-with-top-0-retrived-from-with-ref-no-mask-python-ms100000-wu5000-bsz72/output.hyp' retrived_f='/local/rizwan/workspace/projects/RaProLanG/data/plbart/csnet/python_retrievd_from_no_ref_top_5_mask_rate_0/test.source' retrived_f='/local/rizwan/workspace/projects/RaProLanG/data/plbart/csnet_with_comments/python_without_ref_top_5/test.source' target_f='/local/rizwan/workspace/projects/RaProLanG/data/plbart/csnet/python_retrievd_from_no_ref_top_5_mask_rate_0/test.target' # redcoder_f='/local/rizwan/workspace/projects/RaProLanG/plbart-codexglue-csnet-java-with-top-5-retrived-from-no-ref-no-mask-java-ms100000-wu5000-bsz72/output.hyp' # plbart_f='/local/rizwan/workspace/projects/RaProLanG/plbart-codexglue-csnet-java-with-top-0-retrived-from-with-ref-no-mask-java-ms100000-wu5000-bsz72/output.hyp' # redcoder_ext_f='/local/rizwan/workspace/projects/RaProLanG/plbart-codexglue-csnet-java-comments-top-5-without-java-ms100000-wu5000-bsz72/output.hyp' # target_f='/local/rizwan/workspace/projects/RaProLanG/data/plbart/csnet/java_retrievd_from_no_ref_top_5_mask_rate_0/test.target' # retrived_f='/local/rizwan/workspace/projects/RaProLanG/data/plbart/csnet_with_comments/java_without_ref_top_5/test.source' quants=[20, 40, 60, 80, 100, 50] num_examples = {x:0 for x in quants} plbarts={x:[] for x in quants} retriveds={x:[] for x in quants} redcoders={x:[] for x in quants} redcoders_exts={x:[] for x in quants} # with open(redcoder_ext_f) as rd_ext, open(redcoder_f) as rd, open(plbart_f) as plbrt, open(retrived_f) as rtvd, open(target_f) as target: # for rdext, rd, rtr, plbt, tgt in zip(rd_ext, rd, rtvd, plbrt, target): # # tgt = tgt.strip() # # calculate ngram match (BLEU) # tokenized_hyps = [plbt.split() ] # tokenized_refs = [[tgt.split() ] ] # plbart_bleu_score = bleu_code.corpus_bleu(tokenized_refs, tokenized_hyps) # # # tokenized_hyps = [ rtr.split('_CODE_SEP_')[1].split('_NL_')[0].strip().split()] # rtr_bleu_score = bleu_code.corpus_bleu(tokenized_refs, tokenized_hyps) # # tokenized_hyps = [rd.strip().split()] # rd_bleu_score = bleu_code.corpus_bleu(tokenized_refs, tokenized_hyps) # # tokenized_hyps = [rdext.strip().split()] # rdext_bleu_score = bleu_code.corpus_bleu(tokenized_refs, tokenized_hyps) # # # if rdext_bleu_score > rd_bleu_score and rd_bleu_score>rtr_bleu_score and rtr_bleu_score>plbart_bleu_score and \ # # len(tgt.split()) >= len(rdext.strip().split()) and len(rdext.strip().split())>= len(rtr.split('_CODE_SEP_')[1].strip().split())\ # # and len(rtr.split('_CODE_SEP_')[1].strip().split())>= len(plbt.split() ) and rdext_bleu_score>0.3 and rd_bleu_score>0.2 \ # # and tgt not in rtr: # # # # print('input: ', rtr.split('_CODE_SEP_')[0]) # # print("target:", tgt) # # # # # # print('='*10) # # print("plbart:", plbt) # # print("bleu:", plbart_bleu_score) # # print('=' * 10) # # print("rtrvd:", rtr) # # print("bleu:", rtr_bleu_score) # # # # print('=' * 10) # # print("rd:", rd) # # print("bleu:", rd_bleu_score) # # print('=' * 10) # # print('rdext: ' ,rdext) # # print("bleu:", rdext_bleu_score) # # # l=len(tgt.split()) # for q in quants: # if l<q: # num_examples[q]+=1 # plbarts[q].append(plbart_bleu_score) # retriveds[q].append(rtr_bleu_score) # redcoders[q].append(rd_bleu_score) # redcoders_exts[q].append(rdext_bleu_score) # break # redcoder_f='/local/rizwan/workspace/projects/RaProLanG/plbart-codexglue-csnet-java-with-top-5-retrived-from-no-ref-no-mask-java-ms100000-wu5000-bsz72/output.hyp' # plbart_f='/local/rizwan/workspace/projects/RaProLanG/plbart-codexglue-csnet-java-with-top-0-retrived-from-with-ref-no-mask-java-ms100000-wu5000-bsz72/output.hyp' # redcoder_ext_f='/local/rizwan/workspace/projects/RaProLanG/plbart-codexglue-csnet-java-comments-top-5-without-java-ms100000-wu5000-bsz72/output.hyp' # target_f='/local/rizwan/workspace/projects/RaProLanG/data/plbart/csnet/java_retrievd_from_no_ref_top_5_mask_rate_0/test.target' # retrived_f='/local/rizwan/workspace/projects/RaProLanG/data/plbart/csnet_with_comments/java_without_ref_top_5/test.source' quants=[20, 40, 60, 80, 100, 150, 500] num_examples = {x:0 for x in quants} plbarts={x:[] for x in quants} retriveds={x:[] for x in quants} redcoders={x:[] for x in quants} redcoders_exts={x:[] for x in quants} # print(num_examples) # print("plbarts:", ) # for x, y in plbarts.items(): # print("len: ", x, " number ", num_examples[x], "avg blue: ", sum(y)/len(y)) # print("retrievd:", ) # for x, y in retriveds.items(): # print("len: ", x, " number ", num_examples[x], "avg blue: ", sum(y)/len(y)) # print("redcoder:", ) # for x, y in redcoders.items(): # print("len: ", x, " number ", num_examples[x], "avg blue: ", sum(y)/len(y)) # print("redcoder-ext:", ) # for x, y in redcoders_exts.items(): # print("len: ", x, " number ", num_examples[x], "avg blue: ", sum(y)/len(y)) with open(redcoder_ext_f) as rd_ext, open(redcoder_f) as rd, open(plbart_f) as plbrt, open(retrived_f) as rtvd, open(target_f) as target: for rdext, rd, rtr, plbt, tgt in zip(rd_ext, rd, rtvd, plbrt, target): tgt = tgt.strip() # calculate ngram match (BLEU) tokenized_hyps = [plbt.split() ] tokenized_refs = [[tgt.split() ] ] plbart_bleu_score = bleu_code.corpus_bleu(tokenized_refs, tokenized_hyps) tokenized_hyps = [ rtr.split('_CODE_SEP_')[1].split('_NL_')[0].strip().split()] rtr_bleu_score = bleu_code.corpus_bleu(tokenized_refs, tokenized_hyps) tokenized_hyps = [rd.strip().split()] rd_bleu_score = bleu_code.corpus_bleu(tokenized_refs, tokenized_hyps) tokenized_hyps = [rdext.strip().split()] rdext_bleu_score = bleu_code.corpus_bleu(tokenized_refs, tokenized_hyps) # if rdext_bleu_score > rd_bleu_score and rd_bleu_score>rtr_bleu_score and rtr_bleu_score>plbart_bleu_score and \ # len(tgt.split()) >= len(rdext.strip().split()) and len(rdext.strip().split())>= len(rtr.split('_CODE_SEP_')[1].strip().split())\ # and len(rtr.split('_CODE_SEP_')[1].strip().split())>= len(plbt.split() ) and rdext_bleu_score>0.3 and rd_bleu_score>0.2 \ # and tgt not in rtr: # # print('input: ', rtr.split('_CODE_SEP_')[0]) # print("target:", tgt) # # # print('='*10) # print("plbart:", plbt) # print("bleu:", plbart_bleu_score) # print('=' * 10) # print("rtrvd:", rtr) # print("bleu:", rtr_bleu_score) # # print('=' * 10) # print("rd:", rd) # print("bleu:", rd_bleu_score) # print('=' * 10) # print('rdext: ' ,rdext) # print("bleu:", rdext_bleu_score) l=len(tgt.split()) for q in quants: if l<q: num_examples[q]+=1 plbarts[q].append(plbart_bleu_score) retriveds[q].append(rtr_bleu_score) redcoders[q].append(rd_bleu_score) redcoders_exts[q].append(rdext_bleu_score) break print(num_examples.keys(), num_examples.values()) print("plbarts:", ) xxxx=[] for x, y in plbarts.items(): if len(y)==0: print(x, 'num exmples ', num_examples[x]) else: print("len: ", x, " number ", num_examples[x], "avg blue: ", sum(y)/len(y)) xxxx.append(sum(y)/len(y)) print(xxxx) xxxx=[] print("retrievd:", ) for x, y in retriveds.items(): if len(y) == 0: print(x, 'num exmples ', num_examples[x]) else: print("len: ", x, " number ", num_examples[x], "avg blue: ", sum(y) / len(y)) xxxx.append(sum(y) / len(y)) print(xxxx) xxxx=[] print("redcoder:", ) for x, y in redcoders.items(): if len(y) == 0: print(x, 'num exmples ', num_examples[x]) else: print("len: ", x, " number ", num_examples[x], "avg blue: ", sum(y) / len(y)) xxxx.append(sum(y) / len(y)) print(xxxx) xxxx = [] print("redcoder-ext:", ) for x, y in redcoders_exts.items(): if len(y) == 0: print(x, 'num exmples ', num_examples[x]) else: print("len: ", x, " number ", num_examples[x], "avg blue: ", sum(y) / len(y)) xxxx.append(sum(y) / len(y)) print(xxxx) xxxx = []

40.477586

165

0.646846

3,194

23,477

4.502192

0.077019

0.027538

0.030598

0.042837

0.835396

0.819193

0.789708

0.770654

0.746036

0.728373

0

0.022431

0.213826

23,477

579

166

40.547496

0.756678

0.3388

0

0.546713

0

0.038062

0.153936

0.097384

0

0.010381

1

0.024221

false

0

0.031142

0.00692

0.065744

0.128028

0

null

0

1

0

null

0

6

5e8dba5dbde71a2b4075c47eac5c8c95997729cb

119

py

Python

Lib/test/libregrtest/__init__.py

shawwn/cpython

0ff8a3b374286d2218fc18f47556a5ace202dad3

[ "0BSD" ]

52,316

2015-01-01T15:56:25.000Z

2022-03-31T23:19:01.000Z

Lib/test/libregrtest/__init__.py

shawwn/cpython

0ff8a3b374286d2218fc18f47556a5ace202dad3

[ "0BSD" ]

25,286

2015-03-03T23:18:02.000Z

2022-03-31T23:17:27.000Z

Lib/test/libregrtest/__init__.py

shawwn/cpython

0ff8a3b374286d2218fc18f47556a5ace202dad3

[ "0BSD" ]

31,623

2015-01-01T13:29:37.000Z

2022-03-31T19:55:06.000Z

from test.libregrtest.cmdline import _parse_args, RESOURCE_NAMES, ALL_RESOURCES from test.libregrtest.main import main

39.666667

79

0.865546

17

119

5.823529

0.705882

0.161616

0.383838

0

0.084034

119

2

80

59.5

0.908257

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

0d841468ee48995a4f1b2c71ec7f69adcb37baae

4,001

py

Python

webdriver/tests/new_window/user_prompts.py

ziransun/wpt

ab8f451eb39eb198584d547f5d965ef54df2a86a

[ "BSD-3-Clause" ]

14,668

2015-01-01T01:57:10.000Z

2022-03-31T23:33:32.000Z

webdriver/tests/new_window/user_prompts.py

ziransun/wpt

ab8f451eb39eb198584d547f5d965ef54df2a86a

[ "BSD-3-Clause" ]

7,642

2018-05-28T09:38:03.000Z

2022-03-31T20:55:48.000Z

webdriver/tests/new_window/user_prompts.py

ziransun/wpt

ab8f451eb39eb198584d547f5d965ef54df2a86a

[ "BSD-3-Clause" ]

5,941

2015-01-02T11:32:21.000Z

2022-03-31T16:35:46.000Z

# META: timeout=long import pytest from tests.support.asserts import assert_dialog_handled, assert_error, assert_success def new_window(session, type_hint=None): return session.transport.send( "POST", "session/{session_id}/window/new".format(**vars(session)), {"type": type_hint}) @pytest.fixture def check_user_prompt_closed_without_exception(session, create_dialog): def check_user_prompt_closed_without_exception(dialog_type, retval): original_handles = session.handles create_dialog(dialog_type, text=dialog_type) response = new_window(session) value = assert_success(response) handles = session.handles assert len(handles) == len(original_handles) + 1 assert value["handle"] in handles assert value["handle"] not in original_handles assert_dialog_handled(session, expected_text=dialog_type, expected_retval=retval) return check_user_prompt_closed_without_exception @pytest.fixture def check_user_prompt_closed_with_exception(session, create_dialog): def check_user_prompt_closed_with_exception(dialog_type, retval): original_handles = session.handles create_dialog(dialog_type, text=dialog_type) response = new_window(session) assert_error(response, "unexpected alert open") assert_dialog_handled(session, expected_text=dialog_type, expected_retval=retval) assert len(session.handles) == len(original_handles) return check_user_prompt_closed_with_exception @pytest.fixture def check_user_prompt_not_closed_but_exception(session, create_dialog): def check_user_prompt_not_closed_but_exception(dialog_type): original_handles = session.handles create_dialog(dialog_type, text=dialog_type) response = new_window(session) assert_error(response, "unexpected alert open") assert session.alert.text == dialog_type session.alert.dismiss() assert len(session.handles) == len(original_handles) return check_user_prompt_not_closed_but_exception @pytest.mark.capabilities({"unhandledPromptBehavior": "accept"}) @pytest.mark.parametrize("dialog_type, retval", [ ("alert", None), ("confirm", True), ("prompt", ""), ]) def test_accept(check_user_prompt_closed_without_exception, dialog_type, retval): check_user_prompt_closed_without_exception(dialog_type, retval) @pytest.mark.capabilities({"unhandledPromptBehavior": "accept and notify"}) @pytest.mark.parametrize("dialog_type, retval", [ ("alert", None), ("confirm", True), ("prompt", ""), ]) def test_accept_and_notify(check_user_prompt_closed_with_exception, dialog_type, retval): check_user_prompt_closed_with_exception(dialog_type, retval) @pytest.mark.capabilities({"unhandledPromptBehavior": "dismiss"}) @pytest.mark.parametrize("dialog_type, retval", [ ("alert", None), ("confirm", False), ("prompt", None), ]) def test_dismiss(check_user_prompt_closed_without_exception, dialog_type, retval): check_user_prompt_closed_without_exception(dialog_type, retval) @pytest.mark.capabilities({"unhandledPromptBehavior": "dismiss and notify"}) @pytest.mark.parametrize("dialog_type, retval", [ ("alert", None), ("confirm", False), ("prompt", None), ]) def test_dismiss_and_notify(check_user_prompt_closed_with_exception, dialog_type, retval): check_user_prompt_closed_with_exception(dialog_type, retval) @pytest.mark.capabilities({"unhandledPromptBehavior": "ignore"}) @pytest.mark.parametrize("dialog_type", ["alert", "confirm", "prompt"]) def test_ignore(check_user_prompt_not_closed_but_exception, dialog_type): check_user_prompt_not_closed_but_exception(dialog_type) @pytest.mark.parametrize("dialog_type, retval", [ ("alert", None), ("confirm", False), ("prompt", None), ]) def test_default(check_user_prompt_closed_with_exception, dialog_type, retval): check_user_prompt_closed_with_exception(dialog_type, retval)

32.795082

90

0.751812

482

4,001

5.856846

0.139004

0.10627

0.111583

0.119022

0.841304

0.808006

0.794545

0.746015

0.724407

0.629826

0

0.000291

0.140215

4,001

121

91

33.066116

0.820349

0.004499

0

0.578313

0

0.119568

0.036674

0

0.144578

1

0.156627

false

0

0.024096

0.012048

0.228916

0

null

0

1

0

null

0

6

0dae3df0ccfd9196a49a50c0614288aafbccbc6d

29

py

Python

app/core/models/__init__.py

rdurica/example

733420f955b679d34adfb6bffa35b17177e086f6

[ "MIT" ]

null

app/core/models/__init__.py

rdurica/example

733420f955b679d34adfb6bffa35b17177e086f6

[ "MIT" ]

1

2022-03-15T22:42:58.000Z

2022-03-15T23:05:30.000Z

app/core/models/__init__.py

rdurica/example

733420f955b679d34adfb6bffa35b17177e086f6

[ "MIT" ]

null

from .profile import Profile

14.5

28

0.827586

4

29

6

0.75

0

0.137931

29

1

29

0.96

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

0db784e9ebd325d6eef15a4cd1b74fba12b1b17f

20,862

py

Python

tests/unit/test_expander.py

cicorias/putput

96bde3c2219070bfed1ca76d47a4fe7cd0bc4b44

[ "MIT" ]

1

2019-01-17T07:45:43.000Z

tests/unit/test_expander.py

cicorias/putput

96bde3c2219070bfed1ca76d47a4fe7cd0bc4b44

[ "MIT" ]

1

2019-01-17T07:47:04.000Z

tests/unit/test_expander.py

cicorias/putput

96bde3c2219070bfed1ca76d47a4fe7cd0bc4b44

[ "MIT" ]

null

import unittest from pathlib import Path from putput.expander import expand from putput.pipeline import _load_pattern_def from tests.unit.helper_functions import compare_all_pairs class TestExpander(unittest.TestCase): # pylint: disable=too-many-public-methods def setUp(self) -> None: self.maxDiff = None self._base_dir = Path(__file__).parent / 'pattern_definitions' / 'valid' def test_dynamic_token_patterns_only(self) -> None: dynamic_token_patterns_map = {'ARTIST': ('the beatles', 'kanye')} pattern_def = _load_pattern_def(self._base_dir / 'dynamic_token_patterns_only.yml') expected_utterance_combo = ((('the beatles', 'kanye'),),) expected_tokens = (('ARTIST',),) expected_groups = (((('None', 1)),),) _, generator = expand(pattern_def, dynamic_token_patterns_map=dynamic_token_patterns_map) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_static_token_patterns_only(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'static_token_patterns_only.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('he will want', 'she will want'), ('to play', 'to listen')),) expected_tokens = (('START', 'PLAY'),) expected_groups = (((('None', 1)), ('None', 1)),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_dynamic_and_static_token_patterns(self) -> None: dynamic_token_patterns_map = {'ARTIST': ('the beatles', 'kanye')} pattern_def = _load_pattern_def(self._base_dir / 'dynamic_and_static_token_patterns.yml') _, generator = expand(pattern_def, dynamic_token_patterns_map=dynamic_token_patterns_map) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('he will want', 'she will want'), ('to play', 'to listen'), ('the beatles', 'kanye')),) expected_tokens = (('START', 'PLAY', 'ARTIST'),) expected_groups = ((('None', 1), ('None', 1), ('None', 1)),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_static_and_base_tokens(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'static_and_base_tokens.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('he will want', 'she will want'), ('to play', 'to listen')),) expected_tokens = (('START', 'PLAY'),) expected_groups = ((('None', 1), ('None', 1)),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_static_and_base_tokens_and_group_tokens(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'static_and_base_tokens_and_group_tokens.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('hi',), ('he will want', 'she will want'), ('to play', 'to listen')),) expected_tokens = (('WAKE', 'START', 'PLAY'),) expected_groups = ((('None', 1), ('PLAY_PHRASE', 2),),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_keys_in_addition_to_utterance_patterns_token_patterns(self) -> None: dynamic_token_patterns_map = {'ARTIST': ('the beatles', 'kanye')} pattern_def = _load_pattern_def(self._base_dir / 'keys_in_addition_to_utterance_patterns_tokens_patterns.yml') _, generator = expand(pattern_def, dynamic_token_patterns_map=dynamic_token_patterns_map) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('he will want', 'she will want'), ('to play', 'to listen'), ('the beatles', 'kanye')),) expected_tokens = (('START', 'PLAY', 'ARTIST'),) expected_groups = ((('None', 1), ('None', 1), ('None', 1)),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_groups_with_range(self) -> None: artists = ('the beatles', 'kanye', 'nico', 'tom waits') dynamic_token_patterns_map = {'ARTIST': artists} pattern_def = _load_pattern_def(self._base_dir / 'groups_with_range.yml') _, generator = expand(pattern_def, dynamic_token_patterns_map=dynamic_token_patterns_map) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('she wants',), ('to play',), artists), (('she wants',), ('to play',), artists, artists), (('she wants',), ('to play',), artists, artists, artists),) expected_tokens = (('START', 'PLAY', 'ARTIST'), ('START', 'PLAY', 'ARTIST', 'ARTIST'), ('START', 'PLAY', 'ARTIST', 'ARTIST', 'ARTIST'),) expected_groups = ((('None', 1), ('PLAY_ARTISTS', 2)), (('None', 1), ('PLAY_ARTISTS', 3)), (('None', 1), ('PLAY_ARTISTS', 4)),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_groups_with_single_range(self) -> None: artists = ('the beatles', 'kanye', 'nico', 'tom waits') dynamic_token_patterns_map = {'ARTIST': artists} pattern_def = _load_pattern_def(self._base_dir / 'groups_with_single_range.yml') _, generator = expand(pattern_def, dynamic_token_patterns_map=dynamic_token_patterns_map) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('she wants',), ('to play',), artists, artists, artists),) expected_tokens = (('START', 'PLAY', 'ARTIST', 'ARTIST', 'ARTIST'),) expected_groups = ((('None', 1), ('PLAY_ARTISTS', 4)),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_utterance_patterns_with_range(self) -> None: artists = ('the beatles', 'kanye', 'nico', 'tom waits') dynamic_token_patterns_map = {'ARTIST': artists} pattern_def = _load_pattern_def(self._base_dir / 'utterance_patterns_with_range.yml') _, generator = expand(pattern_def, dynamic_token_patterns_map=dynamic_token_patterns_map) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('she wants',), ('to play',), artists), (('she wants',), ('to play',), artists, ('to play',), artists), (('she wants',), ('to play',), artists, ('to play',), artists, ('to play',), artists),) expected_tokens = (('START', 'PLAY', 'ARTIST'), ('START', 'PLAY', 'ARTIST', 'PLAY', 'ARTIST'), ('START', 'PLAY', 'ARTIST', 'PLAY', 'ARTIST', 'PLAY', 'ARTIST'),) expected_groups = ((('None', 1), ('PLAY_ARTIST', 2)), (('None', 1), ('PLAY_ARTIST', 2), ('PLAY_ARTIST', 2)), (('None', 1), ('PLAY_ARTIST', 2), ('PLAY_ARTIST', 2), ('PLAY_ARTIST', 2)),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_utterance_patterns_with_range_and_non_range(self) -> None: artists = ('the beatles', 'kanye', 'nico', 'tom waits') dynamic_token_patterns_map = {'ARTIST': artists} pattern_def = _load_pattern_def(self._base_dir / 'utterance_patterns_with_range_and_non_range.yml') _, generator = expand(pattern_def, dynamic_token_patterns_map=dynamic_token_patterns_map) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('she wants',),), (('she wants',), ('to play',), artists), (('she wants',), ('to play',), artists, ('to play',), artists), (('she wants',), ('to play',), artists, ('to play',), artists, ('to play',), artists),) expected_tokens = (('START',), ('START', 'PLAY', 'ARTIST'), ('START', 'PLAY', 'ARTIST', 'PLAY', 'ARTIST'), ('START', 'PLAY', 'ARTIST', 'PLAY', 'ARTIST', 'PLAY', 'ARTIST'),) expected_groups = ((('None', 1),), (('None', 1), ('PLAY_ARTIST', 2)), (('None', 1), ('PLAY_ARTIST', 2), ('PLAY_ARTIST', 2)), (('None', 1), ('PLAY_ARTIST', 2), ('PLAY_ARTIST', 2), ('PLAY_ARTIST', 2)),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_groups_with_range_and_non_range(self) -> None: artists = ('the beatles', 'kanye', 'nico', 'tom waits') dynamic_token_patterns_map = {'ARTIST': artists} pattern_def = _load_pattern_def(self._base_dir / 'groups_with_range_and_non_range.yml') _, generator = expand(pattern_def, dynamic_token_patterns_map=dynamic_token_patterns_map) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('she wants',), ('to play',), artists, artists, artists), (('she wants',), ('to play',), artists),) expected_tokens = (('START', 'PLAY', 'ARTIST', 'ARTIST', 'ARTIST'), ('START', 'PLAY', 'ARTIST'),) expected_groups = ((('None', 1), ('PLAY_ARTISTS', 4)), (('START_SONG', 3),),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_nested_group_tokens(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'nested_group_tokens.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('hi',), ('she wants',), ('to play', 'to listen'), ('to play', 'to listen')),) expected_tokens = (('WAKE', 'START', 'PLAY', 'PLAY'),) expected_groups = ((('None', 1), ('PLAY_PHRASE', 3),),) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_nested_group_tokens_and_ranges(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'nested_group_tokens_and_ranges.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('hi',), ('she wants',), ('to play', 'to listen')), (('hi',), ('she wants',), ('to play', 'to listen'), ('to play', 'to listen')), (('hi',), ('she wants',), ('to play', 'to listen'), ('to play', 'to listen'), ('to play', 'to listen')), (('hi',), ('she wants',), ('to play', 'to listen'), ('to play', 'to listen'), ('to play', 'to listen'), ('to play', 'to listen')),) expected_tokens = (('WAKE', 'START', 'PLAY'), ('WAKE', 'START', 'PLAY', 'PLAY'), ('WAKE', 'START', 'PLAY', 'PLAY', 'PLAY'), ('WAKE', 'START', 'PLAY', 'PLAY', 'PLAY', 'PLAY'),) expected_groups = ((('None', 1), ('PLAY_PHRASE', 2),), (('None', 1), ('PLAY_PHRASE', 3),), (('None', 1), ('PLAY_PHRASE', 4),), (('None', 1), ('PLAY_PHRASE', 5),)) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_single_optional_group(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'single_optional_group.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('hi',), ('she will want',), ('to play',)), (('hi',), ('she will want',), ('to play',), ('nico',))) expected_tokens = (('WAKE', 'START', 'PLAY'), ('WAKE', 'START', 'PLAY', 'ARTIST_1')) expected_groups = ((('None', 1), ('PLAY_PHRASE', 2)), (('None', 1), ('PLAY_PHRASE', 3))) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_single_optional_utterance_pattern(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'single_optional_utterance_pattern.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('hi',), ('she will want',), ('to play',)), (('hi',), ('she will want',), ('to play',), ('nico',))) expected_tokens = (('WAKE', 'START', 'PLAY'), ('WAKE', 'START', 'PLAY', 'ARTIST_1')) expected_groups = ((('None', 1), ('PLAY_PHRASE', 2)), (('None', 1), ('PLAY_PHRASE', 2), ('None', 1))) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_multiple_optional_group(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'multiple_optional_group.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('hi',), ('she will want',), ('to play',), ('nico',)), (('hi',), ('she will want',), ('to play',), ('tom waits',))) expected_tokens = (('WAKE', 'START', 'PLAY', 'ARTIST_1'), ('WAKE', 'START', 'PLAY', 'ARTIST_2')) expected_groups = ((('None', 1), ('PLAY_PHRASE', 3)), (('None', 1), ('PLAY_PHRASE', 3))) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_multiple_optional_utternace_pattern(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'multiple_optional_utternace_pattern.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('hi',), ('she will want',), ('to play',), ('nico',)), (('hi',), ('she will want',), ('to play',), ('tom waits',))) expected_tokens = (('WAKE', 'START', 'PLAY', 'ARTIST_1'), ('WAKE', 'START', 'PLAY', 'ARTIST_2')) expected_groups = ((('None', 1), ('PLAY_PHRASE', 2), ('None', 1)), (('None', 1), ('PLAY_PHRASE', 2), ('None', 1))) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_multiple_with_none_optional_group(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'multiple_with_none_optional_group.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('hi',), ('she will want',), ('to play',)), (('hi',), ('she will want',), ('to play',), ('nico',)), (('hi',), ('she will want',), ('to play',), ('tom waits',))) expected_tokens = (('WAKE', 'START', 'PLAY'), ('WAKE', 'START', 'PLAY', 'ARTIST_1'), ('WAKE', 'START', 'PLAY', 'ARTIST_2')) expected_groups = ((('None', 1), ('PLAY_PHRASE', 2)), (('None', 1), ('PLAY_PHRASE', 3)), (('None', 1), ('PLAY_PHRASE', 3))) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_multiple_with_none_optional_utterance_pattern(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'multiple_with_none_optional_utterance_pattern.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('hi',), ('she will want',), ('to play',)), (('hi',), ('she will want',), ('to play',), ('nico',)), (('hi',), ('she will want',), ('to play',), ('tom waits',))) expected_tokens = (('WAKE', 'START', 'PLAY'), ('WAKE', 'START', 'PLAY', 'ARTIST_1'), ('WAKE', 'START', 'PLAY', 'ARTIST_2')) expected_groups = ((('None', 1), ('PLAY_PHRASE', 2)), (('None', 1), ('PLAY_PHRASE', 2), ('None', 1)), (('None', 1), ('PLAY_PHRASE', 2), ('None', 1))) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) def test_intents_and_entities(self) -> None: pattern_def = _load_pattern_def(self._base_dir / 'intents_and_entities.yml') _, generator = expand(pattern_def) actual_utterance_combo, actual_tokens, actual_groups = zip(*generator) expected_utterance_combo = ((('he will want', 'she will want'), ('to play', 'to listen'), ('nico', 'kanye', 'tom waits')), (('he will want', 'she will want'), ('to play', 'to listen'), ('sunday morning', 'all falls down', 'table top joe'))) expected_tokens = (('START', 'PLAY', 'ARTIST'), ('START', 'PLAY', 'SONG')) expected_groups = ((('None', 1), ('None', 1), ('None', 1)), (('None', 1), ('None', 1), ('None', 1))) pairs = [(actual_utterance_combo, expected_utterance_combo), (actual_tokens, expected_tokens), (actual_groups, expected_groups)] compare_all_pairs(self, pairs) if __name__ == '__main__': unittest.main()

62.648649

118

0.56984

2,177

20,862

5.081764

0.048691

0.101238

0.079544

0.094007

0.948929

0.936093

0.930127

0.920184

0.904547

0.902016

0

0.006736

0.274135

20,862

332

119

62.837349

0.723833

0.001869

0

0.648208

0

0.17223

0.032851

0

1

0.068404

false

0

0.016287

0

0.087948

0

null

0

1

0

null

0

6

0dca432b061214b9b5c03fb5472f45901775fe4e

2,263

py

Python

dimensigon/web/api_1_0/resources/step_children.py

dimensigon/dimensigon

079d7c91a66e10f13510d89844fbadb27e005b40

[ "Apache-2.0" ]

2

2020-11-20T10:27:14.000Z

2021-02-21T13:57:56.000Z

dimensigon/web/api_1_0/resources/step_children.py

dimensigon/dimensigon

079d7c91a66e10f13510d89844fbadb27e005b40

[ "Apache-2.0" ]

null

dimensigon/web/api_1_0/resources/step_children.py

dimensigon/dimensigon

079d7c91a66e10f13510d89844fbadb27e005b40

[ "Apache-2.0" ]

null

from flask import request from flask_jwt_extended import jwt_required from flask_restful import Resource from dimensigon.domain.entities import Step from dimensigon.web import db from dimensigon.web.decorators import forward_or_dispatch, securizer, validate_schema, lock_catalog from dimensigon.web.json_schemas import step_children class StepRelationshipChildren(Resource): @forward_or_dispatch() @jwt_required() @securizer def get(self, step_id): s: Step = Step.query.get_or_raise(step_id) return dict(child_step_ids=[str(cs.id) for cs in s.children]), 200 @forward_or_dispatch() @jwt_required() @securizer @validate_schema(step_children) @lock_catalog def patch(self, step_id): s: Step = Step.query.get_or_raise(step_id) child_step_ids = request.get_json()['child_step_ids'] child_steps = [] for child_step_id in child_step_ids: child_steps.append(Step.query.get_or_raise(child_step_id)) s.orchestration.set_children(s, child_steps) db.session.commit() return dict(child_step_ids=[str(cs.id) for cs in s.children]), 200 @forward_or_dispatch() @jwt_required() @securizer @validate_schema(step_children) @lock_catalog def post(self, step_id): s = Step.query.get_or_raise(step_id) child_step_ids = request.get_json()['child_step_ids'] child_steps = [] for child_step_id in child_step_ids: child_steps.append(Step.query.get_or_raise(child_step_id)) s.orchestration.add_children(s, child_steps) db.session.commit() return dict(child_step_ids=[str(cs.id) for cs in s.children]), 200 @forward_or_dispatch() @jwt_required() @securizer @validate_schema(step_children) @lock_catalog def delete(self, step_id): s = Step.query.get_or_raise(step_id) child_step_ids = request.get_json()['child_step_ids'] child_steps = [] for child_step_id in child_step_ids: child_steps.append(Step.query.get_or_raise(child_step_id)) s.orchestration.delete_children(s, child_steps) db.session.commit() return dict(child_step_ids=[str(cs.id) for cs in s.children]), 200

32.328571

99

0.698188

323

2,263

4.563467

0.170279

0.116011

0.105834

0.066486

0.761194

0.736092

0

0.006685

0.206805

2,263

69

100

32.797101

0.814485

0

0.732143

0

0.018559

0

1

0.071429

false

0

0.125

0

0.285714

0

null

0

1

0

1

0

null

0

6

218708d496c65bc5bd87e288cd4cc2517787f821

5,871

py

Python

mercurial_reviewboard/tests/test_ui.py

cicd-team/mercurial-reviewboard

1bb2a3c2009a7340a244d8426ef4c78be9806a67

[ "MIT" ]

1

2020-07-29T03:21:30.000Z

mercurial_reviewboard/tests/test_ui.py

cicd-team/mercurial-reviewboard

1bb2a3c2009a7340a244d8426ef4c78be9806a67

[ "MIT" ]

1

2020-10-06T11:01:01.000Z

2021-01-27T10:21:23.000Z

mercurial_reviewboard/tests/test_ui.py

cicd-team/mercurial-reviewboard

1bb2a3c2009a7340a244d8426ef4c78be9806a67

[ "MIT" ]

null

from mock import Mock, patch_object from nose.tools import eq_, raises import mercurial_reviewboard from mercurial_reviewboard import postreview, util from mercurial_reviewboard.tests import get_initial_opts, get_repo, mock_ui class TestChangesetsOutput: expected_status = \ 'changesets:\n\t1:669e757d4a24 "1"\n\t0:a8ea53640b24 "0"\n\n' @patch_object(mercurial_reviewboard, 'new_review') def test_changeset_shown(self, mock_create_method): ui = mock_ui() repo = get_repo(ui, 'two_revs') opts = get_initial_opts() opts['parent'] = '000000' opts['outgoingchanges'] = False opts['outgoing'] = False postreview(ui, repo, **opts) eq_(self.expected_status, ui.status.call_args_list[1][0][0]) @patch_object(mercurial_reviewboard, 'update_review') def test_changeset_shown_on_existing(self, mock_create_method): ui = mock_ui() repo = get_repo(ui, 'two_revs') opts = get_initial_opts() opts['parent'] = '000000' opts['update'] = False opts['existing'] = '1' opts['outgoingchanges'] = False opts['outgoing'] = False postreview(ui, repo, **opts) eq_(self.expected_status, ui.status.call_args_list[1][0][0]) class TestMerge: @patch_object(mercurial_reviewboard, 'new_review') def test_changeset_shown(self, mock_create_method): """status should show all revisions on all included branches""" expected_status = \ 'changesets:\n\t5:1de20dbad49b "5"'\ '\n\t4:d955e65420c8 "4"\n\t3:13a89135f389 "3"'\ '\n\t2:e97ab41d91c8 "2"'\ '\n\t1:7051d9f99104 "1"\n\t0:1d4da73b2570 "0"\n\n' ui = mock_ui() repo = get_repo(ui, 'merge') opts = get_initial_opts() opts['parent'] = '000000' opts['outgoingchanges'] = False opts['outgoing'] = False postreview(ui, repo, **opts) eq_(expected_status, ui.status.call_args_list[1][0][0]) @patch_object(mercurial_reviewboard, 'new_review') def test_changeset_on_branch(self, mock_create_method): """in branch mode only show revisions on branch""" expected_status = \ 'review of branch: default\n\n'\ 'changesets:\n\t5:1de20dbad49b "5"'\ '\n\t2:e97ab41d91c8 "2"'\ '\n\t1:7051d9f99104 "1"\n\t0:1d4da73b2570 "0"\n\n' ui = mock_ui() repo = get_repo(ui, 'merge') opts = get_initial_opts() opts['branch'] = True opts['outgoingchanges'] = False opts['outgoing'] = False postreview(ui, repo, **opts) eq_(expected_status, ui.status.call_args_list[1][0][0]) class TestLaunchBrowser: @patch_object(mercurial_reviewboard, 'new_review') @patch_object(mercurial_reviewboard, 'launch_webbrowser') def test_browser_launch_default(self, mock_launch, mock_create_method): ui = mock_ui() repo = get_repo(ui, 'two_revs') opts = get_initial_opts() opts['outgoingchanges'] = False opts['outgoing'] = False postreview(ui, repo, **opts) assert mock_launch.called == False @patch_object(mercurial_reviewboard, 'new_review') @patch_object(mercurial_reviewboard, 'launch_webbrowser') def test_browser_launch_false(self, mock_launch, mock_create_method): ui = mock_ui() ui.setconfig('reviewboard', 'launch_webbrowser', 'false') repo = get_repo(ui, 'two_revs') opts = get_initial_opts() opts['outgoingchanges'] = False opts['outgoing'] = False postreview(ui, repo, **opts) assert mock_launch.called == False @patch_object(mercurial_reviewboard, 'new_review') @patch_object(mercurial_reviewboard, 'launch_webbrowser') def test_browser_launch_true(self, mock_launch, mock_create_method): mock_create_method.return_value = '1' ui = mock_ui() ui.setconfig('reviewboard', 'launch_webbrowser', 'true') repo = get_repo(ui, 'two_revs') opts = get_initial_opts() opts['outgoingchanges'] = False opts['outgoing'] = False postreview(ui, repo, **opts) eq_('http://example.com/r/1/', mock_launch.call_args[0][1]) @patch_object(mercurial_reviewboard, 'new_review') @patch_object(mercurial_reviewboard, 'launch_webbrowser') def test_browser_launch_server_arg(self, mock_launch, mock_create_method): mock_create_method.return_value = '1' ui = mock_ui() ui.setconfig('reviewboard', 'launch_webbrowser', 'true') repo = get_repo(ui, 'two_revs') opts = get_initial_opts() opts['server'] = 'example.org' opts['outgoingchanges'] = False opts['outgoing'] = False postreview(ui, repo, **opts) eq_('http://example.org/r/1/', mock_launch.call_args[0][1]) class TestServerConfiguration: @raises(util.Abort) @patch_object(mercurial_reviewboard, 'new_review') def test_no_reviewboard_configured(self, mock_create_review): ui = mock_ui() ui.setconfig('reviewboard', 'server', None) repo = get_repo(ui, 'two_revs') opts = get_initial_opts() postreview(ui, repo, **opts) @patch_object(mercurial_reviewboard, 'new_review') def test_reviewboard_option(self, mock_create_review): ui = mock_ui() ui.setconfig('reviewboard', 'server', None) repo = get_repo(ui, 'two_revs') opts = get_initial_opts() opts['server'] = 'example.com' opts['outgoingchanges'] = False opts['outgoing'] = False postreview(ui, repo, **opts) assert mock_create_review.called

34.946429

78

0.625447

684

5,871

5.090643

0.152047

0.097645

0.080414

0.124641

0.797243

0.789489

0.774268

0.723722

0.701608

0

0.036145

0.250724

5,871

167

79

35.155689

0.755399

0.017374

0

0.757813

0

0.007813

0.184092

0.029698

0

0.023438

1

0.078125

false

0

0.039063

0

0.15625

0

null

0

1

0

1

0

null

0

6

21a5eb586756990988ab5ac74d60bb77ed0982e6

9,738

py

Python

tests/services/test_sample_endpoints.py

sartography/uva-covid19-testing-communicator

39bd041463349d5bada0a3196b4b031f7e3bc3e6

[ "MIT" ]

1

2020-12-07T21:47:02.000Z

tests/services/test_sample_endpoints.py

sartography/uva-covid19-testing-communicator

39bd041463349d5bada0a3196b4b031f7e3bc3e6

[ "MIT" ]

14

2020-09-24T15:38:27.000Z

2021-03-29T19:23:46.000Z

tests/services/test_sample_endpoints.py

sartography/uva-covid19-testing-communicator

39bd041463349d5bada0a3196b4b031f7e3bc3e6

[ "MIT" ]

1

2020-09-22T18:01:29.000Z

from datetime import datetime from time import sleep from tests.base_test import BaseTest import json from communicator.models import Sample from communicator import db, app from communicator.api import admin from communicator.models.notification import Notification class TestSampleEndpoint(BaseTest): sample_json = {"barcode": "000000111-202009091449-4321", "location": "0102", "date": "2020-09-09T14:49:00+0000", "student_id": "000000111", "computing_id": "abc12d"} def test_create_sample(self): # Test add sample samples = db.session.query(Sample).all() self.assertEqual(0, len(samples)) rv = self.app.post('/v1.0/sample', content_type="application/json", data=json.dumps(self.sample_json)) samples = db.session.query(Sample).all() self.assertEqual(1, len(samples)) def test_create_sample_gets_correct_location_and_station(self): # Test add sample samples = db.session.query(Sample).all() self.assertEqual(0, len(samples)) rv = self.app.post('/v1.0/sample', content_type="application/json", data=json.dumps(self.sample_json)) samples = db.session.query(Sample).all() self.assertEqual(1, len(samples)) self.assertEqual(1, samples[0].location) self.assertEqual(2, samples[0].station) def test_create_sample_has_last_updated(self): rv = self.app.post('/v1.0/sample', content_type="application/json", data=json.dumps(self.sample_json)) samples = db.session.query(Sample).all() self.assertEqual(1, len(samples)) self.assertIsNotNone(samples[0].last_modified) def test_create_duplicate_sample_does_not_raise_error(self): # Test add sample samples = db.session.query(Sample).all() self.assertEqual(0, len(samples)) rv = self.app.post('/v1.0/sample', content_type="application/json", data=json.dumps(self.sample_json)) rv = self.app.post('/v1.0/sample', content_type="application/json", data=json.dumps(self.sample_json)) rv = self.app.post('/v1.0/sample', content_type="application/json", data=json.dumps(self.sample_json)) rv = self.app.post('/v1.0/sample', content_type="application/json", data=json.dumps(self.sample_json)) samples = db.session.query(Sample).all() self.assertEqual(1, len(samples)) def test_notify_by_email_by_file_name(self): db.session.add(Sample(barcode="000000111-202009091449-4321", location="4321", date="2020-09-09T14:49:00+0000", student_id="000000111", email="daniel.h.funk@gmail.com", result_code="12345", ivy_file="xxx")) db.session.add(Sample(barcode="000000112-202009091449-4321", location="4321", date="2020-09-09T14:49:00+0000", student_id="000000112", email="dan@gmail.com", result_code="12345", ivy_file="yyy")) db.session.commit() admin._notify_by_email('xxx') samples = db.session.query(Sample).filter(Sample.email_notified == True).all() self.assertEqual(1, len(samples)) samples = db.session.query(Sample).filter(Sample.email_notified != True).all() self.assertEqual(1, len(samples)) admin._notify_by_email() samples = db.session.query(Sample).filter(Sample.email_notified == True).all() self.assertEqual(2, len(samples)) def test_get_all_samples(self): s1 = Sample(barcode="000000111-202009091449-4321", location="4321", date= datetime.now(), student_id="000000111", email="daniel.h.funk@gmail.com", result_code="12345", ivy_file="xxx", email_notified=True, text_notified=True) s2 = Sample(barcode="000000112-202009091449-4321", location="4321", date= datetime.now(), student_id="000000112", email="dan@gmail.com", result_code="12345", ivy_file="yyy", email_notified=False, text_notified=False) db.session.add(s1) db.session.add(Notification(sample=s1, date="2020-12-09T14:49:00+0000", type="email", successful=True)) db.session.add(Notification(sample=s1, date="2020-12-09T14:49:00+0000", type="text", successful=True)) db.session.add(s2) rv = self.app.get('/v1.0/sample', content_type="application/json", headers={'X-CR-API-KEY': app.config.get('API_TOKEN')}) data = json.loads(rv.get_data(as_text=True)) self.assertEqual(2, len(data)) self.assertEqual("000000111-202009091449-4321", data[0]["barcode"]) self.assertEqual(2, len(data[0]["notifications"])) self.assertEqual(True, data[0]['email_notified']) self.assertEqual(True, data[0]["notifications"][0]["successful"]) self.assertEqual(0, len(data[1]["notifications"])) self.assertEqual(False, data[1]['email_notified']) print(data) def test_get_all_samples_by_last_modified(self): d1_str = '202012300101' # dec 30th 2020 d1 = datetime.strptime(d1_str, '%Y%m%d%H%M') s1_bar_code = '000000111-'+ d1_str +'-4321' d2_str = '202101010101' # Jan 1st 2021 d2 = datetime.strptime(d2_str, '%Y%m%d%H%M') s2_bar_code = '000000111-'+ d2_str +'-4321' s1 = Sample(barcode=s1_bar_code, location="4321", date= datetime.now(), last_modified=d1, student_id="000000111", email="daniel.h.funk@gmail.com", result_code="12345", ivy_file="xxx", email_notified=True, text_notified=True) s2 = Sample(barcode=s2_bar_code, location="4321", date= datetime.now(), last_modified=d2, student_id="000000112", email="dan@gmail.com", result_code="12345", ivy_file="yyy", email_notified=False, text_notified=False) db.session.add(s1) db.session.add(s2) rv = self.app.get(f'/v1.0/sample', content_type="application/json", headers={'X-CR-API-KEY': app.config.get('API_TOKEN')}) data = json.loads(rv.get_data(as_text=True)) self.assertEqual(2, len(data)) last_modified_arg = d1.isoformat() rv = self.app.get(f'/v1.0/sample?last_modified={last_modified_arg}', content_type="application/json", headers={'X-CR-API-KEY': app.config.get('API_TOKEN')}) data = json.loads(rv.get_data(as_text=True)) self.assertEqual(1, len(data)) self.assertEqual(s2.barcode, data[0]['barcode']) last_modified_arg = d2.isoformat() rv = self.app.get(f'/v1.0/sample?last_modified={last_modified_arg}', content_type="application/json", headers={'X-CR-API-KEY': app.config.get('API_TOKEN')}) data = json.loads(rv.get_data(as_text=True)) self.assertEqual(0, len(data)) def test_get_all_samples_by_created_on(self): d1_str = '202012300101' # dec 30th 2020 d1 = datetime.strptime(d1_str, '%Y%m%d%H%M') s1_bar_code = '000000111-' + d1_str + '-4321' d2_str = '202101010101' # Jan 1st 2021 d2 = datetime.strptime(d2_str, '%Y%m%d%H%M') s2_bar_code = '000000111-' + d2_str + '-4321' d3_str = '202101010101' # Jan 5th 2021 d3 = datetime.strptime(d3_str, '%Y%m%d%H%M') s1 = Sample(barcode=s1_bar_code, location="4321", date=datetime.now(), created_on=d1, last_modified=d3, # Note Modified date is later than created date. student_id="000000111", email="daniel.h.funk@gmail.com", result_code="12345", ivy_file="xxx", email_notified=True, text_notified=True) s2 = Sample(barcode=s2_bar_code, location="4321", date=datetime.now(), created_on=d2, last_modified=d2, student_id="000000112", email="dan@gmail.com", result_code="12345", ivy_file="yyy", email_notified=False, text_notified=False) db.session.add(s1) db.session.add(s2) created_on_arg = d1.isoformat() rv = self.app.get(f'/v1.0/sample?created_on={created_on_arg}', content_type="application/json", headers={'X-CR-API-KEY': app.config.get('API_TOKEN')}) data = json.loads(rv.get_data(as_text=True)) self.assertEqual(1, len(data)) # Even through s1 was modified on the 4th, it isn't returned. self.assertEqual(s2.barcode, data[0]['barcode'])

43.28

111

0.553091

1,131

9,738

4.60389

0.129973

0.072018

0.020741

0.059919

0.803726

0.763395

0.738045

0.716151

0.693874

0

0.097191

0.316389

9,738

224

112

43.473214

0.684993

0.022695

0

0.693122

0

0.154744

0.05323

0

0.137566

1

0.042328

false

0

0.042328

0

0.095238

0.005291

0

null

0

1

0

null

0

6

21f07bf6dd46ddb4fa2e72657a164839277dd295

1,426

py

Python

downtime/main/models.py

GSCrawley/downtime

57a1c8e00424c1948e1650cd980d541174febbd8

[ "MIT" ]

1

2020-05-03T03:57:26.000Z

downtime/main/models.py

GSCrawley/downtime

57a1c8e00424c1948e1650cd980d541174febbd8

[ "MIT" ]

null

downtime/main/models.py

GSCrawley/downtime

57a1c8e00424c1948e1650cd980d541174febbd8

[ "MIT" ]

null

from django.db import models from django.urls import reverse from django.utils.text import slugify class Movie(models.Model): title = models.CharField(max_length=200) slug = models.SlugField(editable=False, max_length=200) def get_absolute_url(self): kwargs = { "slug": self.slug } return reverse("main:movie-detail", kwargs=kwargs) def save(self, *args, **kwargs): value = self.title self.slug = slugify(value, allow_unicode=True) super().save(*args, **kwargs) class Music(models.Model): title = models.CharField(max_length=200) slug = models.SlugField(editable=False, max_length=200) def get_absolute_url(self): kwargs = { "slug": self.slug } return reverse("main:music-detail", kwargs=kwargs) def save(self, *args, **kwargs): value = self.title self.slug = slugify(value, allow_unicode=True) super().save(*args, **kwargs) class Book(models.Model): title = models.CharField(max_length=200) slug = models.SlugField(editable=False, max_length=200) def get_absolute_url(self): kwargs = { "slug": self.slug } return reverse("main:book-detail", kwargs=kwargs) def save(self, *args, **kwargs): value = self.title self.slug = slugify(value, allow_unicode=True) super().save(*args, **kwargs)

27.423077

59

0.626928

175

1,426

5.022857

0.228571

0.061433

0.081911

0.075085

0.868032

0

0.016744

0.246143

1,426

51

60

27.960784

0.80093

0

0.692308

0

0.043478

0

1

0.153846

false

0

0.076923

0

0.538462

0

null

0

1

0

null

0

6

21fe55970f8a96cb46581c12344ef3a2fe90cee2

36

py

Python

examples/math.log/ex2.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

examples/math.log/ex2.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

examples/math.log/ex2.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

import math print(math.log(10, 10))

12

23

0.722222

7

36

3.714286

0.714286

0

0.125

0.111111

36

2

24

18

0.6875

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

df0275c11536808e485c7226ba650de76d6af317

51

py

Python

backend/shopping-cart-service/tests/utils/mock_shared.py

qingshui-hui/aws-serverless-shopping-cart

3838c981b02726e1ff7b504f1aa0f99b1ddf9b5a

[ "MIT-0" ]

null

backend/shopping-cart-service/tests/utils/mock_shared.py

qingshui-hui/aws-serverless-shopping-cart

3838c981b02726e1ff7b504f1aa0f99b1ddf9b5a

[ "MIT-0" ]

null

backend/shopping-cart-service/tests/utils/mock_shared.py

qingshui-hui/aws-serverless-shopping-cart

3838c981b02726e1ff7b504f1aa0f99b1ddf9b5a

[ "MIT-0" ]

null

def get_user_sub(jwt_token): return jwt_token

12.75

28

0.764706

9

51

3.888889

0.777778

0.457143

0

0.176471

51

3

29

17

0.833333

0

1

0.5

false

0

0.5

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

df1232cc57cd4e7f243b95d0470fceb5adfeab65

46

py

Python

paquete/main.py

MT2321/cid-ProjectZero

65c2d1ed32557e6a1db6a3fcc3bc5a8707ba71fe

[ "MIT" ]

1

2020-01-26T17:58:23.000Z

paquete/main.py

CID-ITBA/similarity-lab

cc1d30ef3a2659cdf22c20f91a299ca1e884457b

[ "MIT" ]

null

paquete/main.py

CID-ITBA/similarity-lab

cc1d30ef3a2659cdf22c20f91a299ca1e884457b

[ "MIT" ]

null

from classPackg import SimiLab print("Hello")

15.333333

30

0.804348

6

46

6.166667

1

0

0.108696

46

3

31

15.333333

0.902439

0

0.106383

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

df7643f5aff51199a41a7ee00171184eccd77666

32

py

Python

app/__init__.py

DineshDevaraj/evalsr

4155881441fcc3aad6dd0dd18da791506e435102

[ "MIT" ]

null

app/__init__.py

DineshDevaraj/evalsr

4155881441fcc3aad6dd0dd18da791506e435102

[ "MIT" ]

null

app/__init__.py

DineshDevaraj/evalsr

4155881441fcc3aad6dd0dd18da791506e435102

[ "MIT" ]

1

2022-02-18T00:41:29.000Z

from app import routes_handler

10.666667

30

0.84375

5

32

5.2

1

0

0.15625

32

2

31

16

0.962963

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

10dedec216b0fc5598759113129f05a6347349ac

92

py

Python

Practice/Python/Math/Polar_Coordinates.py

alexanderbauer89/HackerRank

0fb6face083b0183692c9251ffe4bb635591393f

[ "MIT" ]

1

2021-11-17T02:47:11.000Z

Practice/Python/Math/Polar_Coordinates.py

alexanderbauer89/HackerRank

0fb6face083b0183692c9251ffe4bb635591393f

[ "MIT" ]

null

Practice/Python/Math/Polar_Coordinates.py

alexanderbauer89/HackerRank

0fb6face083b0183692c9251ffe4bb635591393f

[ "MIT" ]

null

import cmath r = complex(input().strip()) print(cmath.polar(r)[0]) print(cmath.polar(r)[1])

18.4

28

0.684783

16

92

3.9375

0.625

0.31746

0.47619

0.507937

0

0.023529

0.076087

92

4

29

23

0.717647

0

1

0

false

0

0.25

0

0.25

0.5

1

0

null

1

0

1

0

null

0

1

0

6

10ed72c404b901bb49cc03dbc6664335e9f0ce41

29

py

Python

crfasrnn/__init__.py

prashantraina/PlaneNet

51fa261f7e958191fce6077cf923539acadb707b

[ "MIT" ]

null

crfasrnn/__init__.py

prashantraina/PlaneNet

51fa261f7e958191fce6077cf923539acadb707b

[ "MIT" ]

null

crfasrnn/__init__.py

prashantraina/PlaneNet

51fa261f7e958191fce6077cf923539acadb707b

[ "MIT" ]

null

from . import crfasrnn_layer

14.5

28

0.827586

4

29

5.75

1

0

0.137931

29

1

29

0.92

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

10eedde2a016e974a9df496050e6b00b34bd879b

2,661

py

Python

tests/test_batch.py

umd-lib/aws-archiver

9de3bb8a48c2e18960cd70c7fb892093c48174d6

[ "MIT" ]

null

tests/test_batch.py

umd-lib/aws-archiver

9de3bb8a48c2e18960cd70c7fb892093c48174d6

[ "MIT" ]

5

2020-02-26T22:15:09.000Z

2021-07-10T14:35:35.000Z

tests/test_batch.py

umd-lib/aws-archiver

9de3bb8a48c2e18960cd70c7fb892093c48174d6

[ "MIT" ]

1

2020-02-25T16:10:41.000Z

import os import unittest from archiver.batch import Batch from archiver.manifests.manifest_factory import ManifestFactory class TestBatch(unittest.TestCase): def setUp(self): pass def test_load_inventory_manifest(self): manifest = ManifestFactory.create('tests/data/manifests/sample_inventory_manifest.csv') batch = Batch(manifest, bucket='test_bucket', asset_root='/', log_dir='/tmp') manifest.load_manifest('sample_inventory_manifest.csv', batch) self.assertEqual(11, batch.stats['total_assets']) self.assertEqual(11, batch.stats['assets_missing']) def test_load_md5sum_manifest(self): manifest = ManifestFactory.create('tests/data/manifests/sample_md5sum_manifest.txt') batch = Batch(manifest, bucket='test_bucket', asset_root='/', log_dir='/tmp') manifest.load_manifest('sample_md5sum_manifest.txt', batch) self.assertEqual(5, batch.stats['total_assets']) self.assertEqual(5, batch.stats['assets_missing']) def test_load_patsy_manifest(self): manifest = ManifestFactory.create('tests/data/manifests/sample_patsy_manifest.csv') batch = Batch(manifest, bucket='test_bucket', asset_root='/', log_dir='/tmp') manifest.load_manifest('sample_patsy_manifest.csv', batch) self.assertEqual(5, batch.stats['total_assets']) self.assertEqual(5, batch.stats['assets_missing']) def test_add_asset_without_specified_relpath(self): sample_file_1_path = os.path.abspath('tests/data/files/sample_file_1.txt') asset_root = os.path.abspath('.') manifest = ManifestFactory.create(None) batch = Batch(manifest, bucket='test_bucket', asset_root=asset_root, log_dir='/tmp') batch.add_asset(sample_file_1_path) self.assertEqual(1, batch.stats['total_assets']) self.assertEqual(1, batch.stats['assets_found']) asset = batch.contents[0] self.assertEqual('tests/data/files/sample_file_1.txt', asset.relpath) def test_add_asset_with_specified_relpath(self): sample_file_1_path = os.path.abspath('tests/data/files/sample_file_1.txt') asset_root = os.path.abspath('.') manifest = ManifestFactory.create(None) batch = Batch(manifest, bucket='test_bucket', asset_root=asset_root, log_dir='/tmp') batch.add_asset(sample_file_1_path, relpath='test/specific/relpath/sample_file_1.txt') self.assertEqual(1, batch.stats['total_assets']) self.assertEqual(1, batch.stats['assets_found']) asset = batch.contents[0] self.assertEqual('test/specific/relpath/sample_file_1.txt', asset.relpath)

46.684211

95

0.712514

339

2,661

5.333333

0.165192

0.099558

0.054757

0.066372

0.875553

0.815819

0.785398

0.727876

0.709624

0.60177

0

0.011654

0.161593

2,661

56

96

47.517857

0.798745

0

0.466667

0

0.228861

0.151447

0

0.266667

1

0.133333

false

0.022222

0.088889

0

0.244444

0

null

0

1

0

null

0

6

10f382ad6b39b23fcdf1affd0e41f9a7c5cc4a37

93

py

Python

aerosandbox/aerodynamics/aero_2D/singularities/__init__.py

scivm/AeroSandbox

616c579e49bc13c3023364773705eaac7df10da7

[ "MIT" ]

1

2021-04-07T08:59:31.000Z

aerosandbox/aerodynamics/aero_2D/singularities/__init__.py

scivm/AeroSandbox

616c579e49bc13c3023364773705eaac7df10da7

[ "MIT" ]

null

aerosandbox/aerodynamics/aero_2D/singularities/__init__.py

scivm/AeroSandbox

616c579e49bc13c3023364773705eaac7df10da7

[ "MIT" ]

1

2021-09-11T03:28:45.000Z

from .linear_strength_line_singularities import calculate_induced_velocity_line_singularities

93

0.956989

11

93

7.454545

0.818182

0.414634

0

0.032258

93

1

93

0.911111

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

10f5bd20deb0f1e493b5a3cbeb77201f20bb2955

3,705

py

Python

tests/upbit_ws_test.py

gyunt/aio-upbit

16f06d88622aee00c2f8edccb41b982e9bcbb6d0

[ "MIT" ]

4

2018-05-26T12:12:48.000Z

2020-02-13T16:12:43.000Z

tests/upbit_ws_test.py

gyunt/aio-upbit

16f06d88622aee00c2f8edccb41b982e9bcbb6d0

[ "MIT" ]

null

tests/upbit_ws_test.py

gyunt/aio-upbit

16f06d88622aee00c2f8edccb41b982e9bcbb6d0

[ "MIT" ]

1

2019-06-07T19:24:53.000Z

import unittest import asyncio from aioupbit import UpbitWs MARKET = 'KRW-BTC' MARKETS = [MARKET] def async_loop(*tasks): loop = asyncio.get_event_loop() loop.run_until_complete(asyncio.gather(*tasks)) class TestUpbitWsClient(unittest.TestCase): """ Integration tests for the Upbit WebSocket """ def setUp(self): pass def test_get_ticker(self): async def test(): async with UpbitWs() as u: actual = await u.get_ticker(MARKETS) self.assertGreater(len(actual), 0, 'get_ticker is 0-length.') self.assertEqual(actual['code'], MARKET, 'get_ticker has wrong data.') async_loop(test()) def test_get_trading_history(self): async def test(): async with UpbitWs() as u: actual = await u.get_trading_history(MARKETS) self.assertGreater(len(actual), 0, 'get_trading_history is 0-length.') self.assertEqual(actual['code'], MARKET, 'get_trading_history has wrong data.') async_loop(test()) def test_get_orderbook(self): async def test(): async with UpbitWs() as u: actual = await u.get_orderbook(MARKETS) self.assertGreater(len(actual), 0, 'get_orderbook is 0-length.') self.assertEqual(actual['code'], MARKET, 'get_orderbook has wrong data.') async_loop(test()) def test_get_ticker_streaming(self): async def test1(q): async with UpbitWs(queue=q) as u: await u.get_ticker_streaming(MARKETS) async def test2(q): count = 3 while count: actual = await q.get() self.assertGreater(len(actual), 0, 'get_ticker_streaming is 0-length.') self.assertEqual(actual['code'], MARKET, 'get_ticker_streaming has wrong data.') count -= 1 q = asyncio.Queue() tasks = [ test1(q), test2(q) ] loop = asyncio.get_event_loop() loop.run_until_complete( asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED)) def test_get_trading_history_streaming(self): async def test1(q): async with UpbitWs(queue=q) as u: await u.get_trading_history_streaming(MARKETS) async def test2(q): count = 3 while count: actual = await q.get() self.assertGreater(len(actual), 0, 'get_trading_history_streaming is 0-length.') self.assertEqual(actual['code'], MARKET, 'get_trading_history_streaming has wrong data.') count -= 1 q = asyncio.Queue() tasks = [ test1(q), test2(q) ] loop = asyncio.get_event_loop() loop.run_until_complete( asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED)) def test_get_orderbook_streaming(self): async def test1(q): async with UpbitWs(queue=q) as u: await u.get_orderbook_streaming(MARKETS) async def test2(q): count = 3 while count: actual = await q.get() self.assertGreater(len(actual), 0, 'get_orderbook_streaming is 0-length.') self.assertEqual(actual['code'], MARKET, 'get_orderbook_streaming has wrong data.') count -= 1 q = asyncio.Queue() tasks = [ test1(q), test2(q) ] loop = asyncio.get_event_loop() loop.run_until_complete( asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED))

34.95283

105

0.575169

429

3,705

4.79021

0.153846

0.030657

0.06618

0.075912

0.871046

0.843796

0.789781

0.761557

0.710462

0

0.01199

0.324696

3,705

105

106

35.285714

0.809353

0.011066

0

0.58427

0

0.118728

0.028517

0

0.134831

1

0.089888

false

0.011236

0.033708

0

0.134831

0

null

0

1

0

null

0

6

8020eea83d6ef91ec5ade027ae2b4e1e3f4123e9

65

py

Python

tests/functions/ignores/main.py

timmartin-airsupply/lambda-tools

2c0b52ce889631c63c6dc343439fd5be822eefec

[ "MIT" ]

3

2017-12-08T12:37:46.000Z

2018-04-13T01:08:35.000Z

tests/functions/ignores/main.py

timmartin-airsupply/lambda-tools

2c0b52ce889631c63c6dc343439fd5be822eefec

[ "MIT" ]

29

2017-10-11T06:15:07.000Z

2018-02-19T23:04:51.000Z

tests/functions/ignores/main.py

timmartin-airsupply/lambda-tools

2c0b52ce889631c63c6dc343439fd5be822eefec

[ "MIT" ]

3

2017-10-10T12:40:41.000Z

2021-11-24T10:24:46.000Z

import another def run(event, context): return 'Hello world'

16.25

24

0.723077

9

65

5.222222

1

0

0.184615

65

4

25

16.25

0.886792

0

0.166667

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

803cc3a1402383b4fa7c166f448962f547eeaa71

38

py

Python

force_feeder/__init__.py

willdickson/force_feeder

cb90fbdef69244c720823e11a9880dddbaf5e7af

[ "MIT" ]

null

force_feeder/__init__.py

willdickson/force_feeder

cb90fbdef69244c720823e11a9880dddbaf5e7af

[ "MIT" ]

null

force_feeder/__init__.py

willdickson/force_feeder

cb90fbdef69244c720823e11a9880dddbaf5e7af

[ "MIT" ]

null

from .force_feeder import ForceFeeder

19

37

0.868421

5

38

6.4

1

0

0.105263

38

1

38

0.941176

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

804e66ea740e677674d063f9d162a6aa6accd649

211

py

Python

translator/ast/token.py

akvarats/habr_antlr4_internal

0146af29b277c772fd342f905fe356a2cc789824

[ "Apache-2.0" ]

null

translator/ast/token.py

akvarats/habr_antlr4_internal

0146af29b277c772fd342f905fe356a2cc789824

[ "Apache-2.0" ]

null

translator/ast/token.py

akvarats/habr_antlr4_internal

0146af29b277c772fd342f905fe356a2cc789824

[ "Apache-2.0" ]

null

from .base import BaseNode class TokenNode(BaseNode): """ """ def __init__(self, text: str): super().__init__() self.text = text def get_text(self): return self.text or ""

17.583333

34

0.578199

25

211

4.52

0.6

0.212389

0

0.2891

211

11

35

19.181818

0.753333

0

1

0.285714

false

0

0.142857

0.714286

0

1

0

null

1

0

null

0

1

0

1

0

6

337fbc1ea75ddc9feb9b0a08929124f4626b090b

30

py

Python

tests/test_sinkhorn.py

nbgl/pytorch-ot

cd416befd3fa89bc3e4a858e0b6f8d28dfa9f18b

[ "MIT" ]

2

2020-11-17T15:29:14.000Z

2021-04-24T15:12:35.000Z

tests/test_sinkhorn.py

nbgl/torch-wasserstein

cd416befd3fa89bc3e4a858e0b6f8d28dfa9f18b

[ "MIT" ]

null

tests/test_sinkhorn.py

nbgl/torch-wasserstein

cd416befd3fa89bc3e4a858e0b6f8d28dfa9f18b

[ "MIT" ]

2

2020-10-09T02:43:01.000Z

2021-06-03T11:48:47.000Z

def test_sinkhorn(): pass

10

20

0.666667

4

30

4.75

1

0

0.233333

30

2

21

15

0.826087

0

1

0.5

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

6

33aad0d6a88a43d2cd62be2e70b8dee313eb8201

42

py

Python

builder/bot/tasks/__init__.py

Krossom/Loki

5d821fa8901340d51579bb260ef7efd4da6afc24

[ "MIT" ]

3

2019-11-24T05:35:54.000Z

2021-12-25T11:48:16.000Z

builder/bot/tasks/__init__.py

juan157/Loki

28fbcebfe25631c539f656e98efe789d526432e2

[ "MIT" ]

null

builder/bot/tasks/__init__.py

juan157/Loki

28fbcebfe25631c539f656e98efe789d526432e2

[ "MIT" ]

4

2019-06-18T21:56:29.000Z

2020-04-29T16:03:14.000Z

# Date: 09/27/2018 # Author: Pure-L0G1C

14

21

0.642857

7

42

3.857143

1

0

0.294118

0.190476

42

2

22

21

0.5

0.833333

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

1

0

null

0

1

0

6

1d1567a38243ae196a5936dace44084b58b189f4

302

py

Python

bot/Utils/systemUtils.py

LukasForst/toggl-wire-bot

1a242ef281b3cb501f30a1acee9cda7fd2cb2a84

[ "MIT" ]

null

bot/Utils/systemUtils.py

LukasForst/toggl-wire-bot

1a242ef281b3cb501f30a1acee9cda7fd2cb2a84

[ "MIT" ]

null

bot/Utils/systemUtils.py

LukasForst/toggl-wire-bot

1a242ef281b3cb501f30a1acee9cda7fd2cb2a84

[ "MIT" ]

null

import os def getTogglToken() -> str: return os.getenv("TOGGL_TOKEN") def getRomanToken() -> str: return os.getenv("ROMAN_TOKEN") def getRomanURL() -> str: # TODO return "http://proxy.services.zinfra.io" def getWorkspaceId() -> int: # TODO fetch from env return 4039412

15.1

44

0.652318

37

302

5.27027

0.648649

0.092308

0.112821

0.174359

0

0.029536

0.215232

302

19

45

15.894737

0.793249

0.07947

0

0.192727

0

0.052632

0

1

0.444444

true

0

0.111111

0.444444

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

1d2f047a8bacd45cb093c13b939cafc7ac729fed

148

py

Python

Language/Parsing/alphabet_symbol.py

anoppa/Proyecto-IA-Sim-Comp

71132bd0c6cb5aeff812fd96e0017be71178a5f3

[ "MIT" ]

1

2022-03-11T14:24:10.000Z

Language/Parsing/alphabet_symbol.py

anoppa/Proyecto-IA-Sim-Comp

71132bd0c6cb5aeff812fd96e0017be71178a5f3

[ "MIT" ]

null

Language/Parsing/alphabet_symbol.py

anoppa/Proyecto-IA-Sim-Comp

71132bd0c6cb5aeff812fd96e0017be71178a5f3

[ "MIT" ]

1

2022-01-19T04:29:19.000Z

class AlphabetSymbol: def __init__(self, symbol) -> None: self.symbol = symbol def __str__(self) -> str: return self.symbol

24.666667

39

0.628378

17

148

5

0.529412

0.352941

0

0.27027

148

6

40

24.666667

0.787037

0

1

0.4

false

0

0.2

0.8

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

1d4c158fa161b7a8f9ba8869ece2175233ec5956

151

py

Python

pysindy/differentiation/__init__.py

billtubbs/pysindy

f9ac15b5d073c71bb210b77ff6a5579beb8ed94b

[ "MIT" ]

7

2020-04-02T00:19:29.000Z

2021-11-02T07:22:28.000Z

pysindy/differentiation/__init__.py

billtubbs/pysindy

f9ac15b5d073c71bb210b77ff6a5579beb8ed94b

[ "MIT" ]

null

pysindy/differentiation/__init__.py

billtubbs/pysindy

f9ac15b5d073c71bb210b77ff6a5579beb8ed94b

[ "MIT" ]

null

from .base import BaseDifferentiation from .finite_difference import FiniteDifference from .smoothed_finite_difference import SmoothedFiniteDifference

37.75

64

0.900662

15

151

8.866667

0.6

0.240602

0.330827

0

0.07947

151

3

65

50.333333

0.956835

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

d517ed88248c7c2d6eead0e498ccb5c9a3d20ffc

40

py

Python

featuretools/core/api.py

zhxt95/featuretools

4fd90031e2b525ddaacddf46ff06a58103dbca35

[ "BSD-3-Clause" ]

null

featuretools/core/api.py

zhxt95/featuretools

4fd90031e2b525ddaacddf46ff06a58103dbca35

[ "BSD-3-Clause" ]

null

featuretools/core/api.py

zhxt95/featuretools

4fd90031e2b525ddaacddf46ff06a58103dbca35

[ "BSD-3-Clause" ]

null

# flake8: noqa from .base import FTBase

13.333333

24

0.75

6

40

5

1

0

0.030303

0.175

40

2

25

20

0.878788

0.3

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

d51d7e95d96506f7328ab467907216ad99442dbb

215

py

Python

Python practice/Mit opencourceware(2.7)/tuple.py

chiranjeevbitp/Python27new

d366efee57857402bae16cabf1df94c657490750

[ "bzip2-1.0.6" ]

null

Python practice/Mit opencourceware(2.7)/tuple.py

chiranjeevbitp/Python27new

d366efee57857402bae16cabf1df94c657490750

[ "bzip2-1.0.6" ]

null

Python practice/Mit opencourceware(2.7)/tuple.py

chiranjeevbitp/Python27new

d366efee57857402bae16cabf1df94c657490750

[ "bzip2-1.0.6" ]

null

##tuples and hashing .... if __name__ == '__main__': n = int(raw_input()) integer_list = map(int, raw_input().split()) t=tuple(integer_list) print integer_list print t print hash(t)

23.888889

49

0.604651

29

215

4.034483

0.62069

0.282051

0.188034

0

0.255814

215

8

50

26.875

0.73125

0.106977

0

0.043956

0

null

0

null

0.428571

1

0

null

1

0

1

0

null

0

1

0

1

0

6

d5314bb76821aec2ec61c7c2ecff4b4244d48ddb

13,694

py

Python

tests/test_kmeans.py

rlespinet/pomegranate

98c87d0ac6dc8494b8b0110d4913ece652aaa1f6

[ "MIT" ]

null

tests/test_kmeans.py

rlespinet/pomegranate

98c87d0ac6dc8494b8b0110d4913ece652aaa1f6

[ "MIT" ]

null

tests/test_kmeans.py

rlespinet/pomegranate

98c87d0ac6dc8494b8b0110d4913ece652aaa1f6

[ "MIT" ]

null

from pomegranate import * from nose.tools import with_setup from nose.tools import assert_true from nose.tools import assert_equal from nose.tools import assert_greater_equal from nose.tools import assert_greater from nose.tools import assert_raises from nose.tools import assert_not_equal from numpy.testing import assert_almost_equal from numpy.testing import assert_array_almost_equal from numpy.testing import assert_array_equal import random import pickle import numpy as np numpy.random.seed(0) def setup_three_dimensions(): global X X = numpy.array([[-0.13174492, 0.51895916, -1.13141796], [ 7.92260379, 7.86325294, 7.9884075 ], [-0.63378039, -0.96394236, -1.34125012], [ 8.16216236, 8.04655182, 6.68825619], [-0.69595565, -0.19004012, 0.40768949], [ 7.76271281, 8.94969945, 7.03687617], [-1.92481462, -1.03905815, -0.44048926], [ 7.90926091, 7.21944418, 7.15989354], [-0.97493454, -0.04714556, -0.38607725], [ 9.65781658, 7.04832845, 6.47613347]]) idxs = numpy.array([29, 19, 26, 11, 8, 27, 21, 7, 14, 13]) i, j = idxs // 3, idxs % 3 global X_nan X_nan = X.copy() X_nan[i, j] = numpy.nan global centroids centroids = numpy.array([[0, 0, 0], [8, 8, 8]]) global model model = Kmeans(2, centroids) def setup_five_dimensions(): global X X = numpy.array([[-0.04320239, 2.25402395, -0.3075753 , 0.01710706, 2.88816037], [ 3.6483074 , 5.03958367, 3.14457941, 4.94180558, 4.32880698], [ 7.48485345, 8.54100011, 7.90936486, 8.12260819, 6.6466098 ], [ 12.15394848, 10.52091121, 13.55495735, 10.48190106, 10.94417476], [ 1.21068778, 0.77311369, -0.31479566, -0.51865649, 0.4408653 ], [-0.62796182, -0.34947675, -1.09050772, -0.34591408, 0.78866514], [ 0.5661847 , 0.30785453, 0.38823634, 1.99717206, -0.99415221], [ 0.10871016, 2.06244903, -0.19580087, -0.22100353, -0.43777027], [ 3.06987578, 4.8633418 , 4.23645519, 4.20563589, 3.40046883], [ 3.0471144 , 3.43070459, 3.88690894, 3.61962816, 3.52399965], [ 3.3020318 , 5.16491752, 3.85249134, 2.7075964 , 4.03831846], [ 3.55266908, 2.69803949, 4.13340743, 5.72527752, 4.9840009 ], [ 7.27689336, 8.99614296, 7.10109146, 7.81354687, 7.27320546], [ 9.55443921, 7.70358635, 8.9762396 , 7.8054752 , 7.95933534], [ 7.55150108, 9.09523173, 8.38379803, 8.18932292, 7.70853 ], [ 9.59329137, 8.26811547, 9.82226673, 8.35257773, 8.21768809], [ 11.77294852, 12.33135372, 13.02160394, 12.05536766, 11.96375761], [ 11.08768408, 13.15689157, 12.59002102, 11.16137415, 9.84335332], [ 11.41978669, 11.45646564, 11.77622614, 11.96590564, 12.33083825], [ 12.13323296, 11.89683824, 12.18373541, 13.21432431, 11.79987739]]) idxs = numpy.array([77, 26, 61, 46, 18, 30, 94, 96, 45, 67, 4, 20, 23, 73, 37, 21, 58, 99, 51, 7, 69, 53, 81, 85, 95, 9, 98, 24, 28, 38]) i, j = idxs // 5, idxs % 5 global X_nan X_nan = X.copy() X_nan[i, j] = numpy.nan global centroids centroids = numpy.array([[0, 0, 0, 0, 0], [4, 4, 4, 4, 4], [8, 8, 8, 8, 8], [12, 12, 12, 12, 12]]) global model model = Kmeans(4, centroids) def test_kmeans_init(): centroids = [[2, 3], [5, 7]] model = Kmeans(2, centroids) assert_equal(model.d, 2) assert_equal(model.k, 2) assert_array_equal(model.centroids, centroids) @with_setup(setup_three_dimensions) def test_kmeans_from_samples(): model = Kmeans.from_samples(2, X, init='first-k') centroids = [[-0.872246, -0.344245, -0.578309], [ 8.282911, 7.825455, 7.069913]] assert_array_almost_equal(model.centroids, centroids) @with_setup(setup_three_dimensions) def test_kmeans_from_samples_parallel(): model = Kmeans.from_samples(2, X, init='first-k', n_jobs=2) centroids = [[-0.872246, -0.344245, -0.578309], [ 8.282911, 7.825455, 7.069913]] assert_array_almost_equal(model.centroids, centroids) @with_setup(setup_three_dimensions) def test_kmeans_predict(): y = numpy.array([0, 1, 0, 1, 0, 1, 0, 1, 0, 1]) y_hat = model.predict(X) assert_array_equal(y, y_hat) @with_setup(setup_three_dimensions) def test_kmeans_predict_parallel(): y = numpy.array([0, 1, 0, 1, 0, 1, 0, 1, 0, 1]) y_hat = model.predict(X, n_jobs=2) assert_array_equal(y, y_hat) y_hat = model.predict(X, n_jobs=4) assert_array_equal(y, y_hat) @with_setup(setup_five_dimensions) def test_kmeans_predict_large(): y = [0, 1, 2, 3, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3] y_hat = model.predict(X) assert_array_equal(y, y_hat) @with_setup(setup_five_dimensions) def test_kmeans_predict_large_parallel(): y = [0, 1, 2, 3, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3] y_hat = model.predict(X, n_jobs=2) assert_array_equal(y, y_hat) y_hat = model.predict(X, n_jobs=4) assert_array_equal(y, y_hat) @with_setup(setup_three_dimensions) def test_kmeans_fit(): model.fit(X) centroids = [[-0.872246, -0.344245, -0.578309], [ 8.282911, 7.825455, 7.069913]] assert_array_almost_equal(model.centroids, centroids) @with_setup(setup_three_dimensions) def test_kmeans_fit_parallel(): model.fit(X, n_jobs=2) centroids = [[-0.872246, -0.344245, -0.578309], [ 8.282911, 7.825455, 7.069913]] assert_array_almost_equal(model.centroids, centroids) model.fit(X, n_jobs=4) centroids = [[-0.872246, -0.344245, -0.578309], [ 8.282911, 7.825455, 7.069913]] assert_array_almost_equal(model.centroids, centroids) @with_setup(setup_five_dimensions) def test_kmeans_multiple_init(): model1 = Kmeans.from_samples(4, X, init='kmeans++', n_init=1) model2 = Kmeans.from_samples(4, X, init='kmeans++', n_init=25) dist1 = model1.distance(X).min(axis=1).sum() dist2 = model2.distance(X).min(axis=1).sum() assert_greater_equal(dist1, dist2) model1 = Kmeans.from_samples(4, X, init='first-k', n_init=1) model2 = Kmeans.from_samples(4, X, init='first-k', n_init=5) dist1 = model1.distance(X).min(axis=1).sum() dist2 = model2.distance(X).min(axis=1).sum() assert_equal(dist1, dist2) @with_setup(setup_five_dimensions) def test_kmeans_ooc_from_samples(): numpy.random.seed(0) model1 = Kmeans.from_samples(5, X, init='first-k', batch_size=20) model2 = Kmeans.from_samples(5, X, init='first-k', batch_size=None) assert_array_equal(model1.centroids, model2.centroids) @with_setup(setup_three_dimensions) def test_kmeans_ooc_fit(): centroids_copy = numpy.copy(centroids) model1 = Kmeans(2, centroids_copy, n_init=1) model1.fit(X) centroids_copy = numpy.copy(centroids) model2 = Kmeans(2, centroids_copy, n_init=1) model2.fit(X, batch_size=10) centroids_copy = numpy.copy(centroids) model3 = Kmeans(2, centroids_copy, n_init=1) model3.fit(X, batch_size=1) assert_array_almost_equal(model1.centroids, model2.centroids) assert_array_almost_equal(model1.centroids, model3.centroids) @with_setup(setup_five_dimensions) def test_kmeans_minibatch_from_samples(): model1 = Kmeans.from_samples(4, X, init='first-k', batch_size=10) model2 = Kmeans.from_samples(4, X, init='first-k', batch_size=None) model3 = Kmeans.from_samples(4, X, init='first-k', batch_size=10, batches_per_epoch=1) assert_array_almost_equal(model1.centroids, model2.centroids) assert_raises(AssertionError, assert_array_equal, model1.centroids, model3.centroids) @with_setup(setup_five_dimensions) def test_kmeans_minibatch_fit(): centroids_copy = numpy.copy(centroids) model1 = Kmeans(4, centroids_copy) model1.fit(X, batch_size=10) centroids_copy = numpy.copy(centroids) model2 = Kmeans(4, centroids_copy) model2.fit(X, batch_size=None) centroids_copy = numpy.copy(centroids) model3 = Kmeans(4, centroids_copy) model3.fit(X, batch_size=5, batches_per_epoch=1) assert_array_almost_equal(model1.centroids, model2.centroids) assert_raises(AssertionError, assert_array_equal, model1.centroids, model3.centroids) @with_setup(setup_three_dimensions) def test_kmeans_nan_from_samples(): model = Kmeans.from_samples(2, X_nan, init='first-k') centroids = [[-0.872246, 0.235907, -0.785954], [ 7.94916 , 7.825455, 7.395059]] assert_array_almost_equal(model.centroids, centroids) @with_setup(setup_three_dimensions) def test_kmeans_nan_from_samples_parallel(): model = Kmeans.from_samples(2, X_nan, init='first-k', n_jobs=2) centroids = [[-0.872246, 0.235907, -0.785954], [ 7.94916 , 7.825455, 7.395059]] assert_array_almost_equal(model.centroids, centroids) @with_setup(setup_three_dimensions) def test_kmeans_nan_fit(): model.fit(X_nan) centroids = [[-0.872246, 0.235907, -0.785954], [ 7.94916 , 7.825455, 7.395059]] assert_array_almost_equal(model.centroids, centroids) @with_setup(setup_three_dimensions) def test_kmeans_nan_fit_parallel(): model.fit(X_nan, n_jobs=2) centroids = [[-0.872246, 0.235907, -0.785954], [ 7.94916 , 7.825455, 7.395059]] assert_array_almost_equal(model.centroids, centroids) @with_setup(setup_five_dimensions) def test_kmeans_nan_fit_large(): model.fit(X_nan) centroids = [[ -0.187485, 1.541443, -0.331161, 1.00714 , -0.214419], [ 3.393221, 4.200322, 4.027316, 4.25569 , 3.986697], [ 8.292196, 8.401983, 7.798085, 8.023552, 7.461508], [ 11.782228, 11.711423, 12.625309, 11.727549, 10.917095]] assert_array_almost_equal(model.centroids, centroids) @with_setup(setup_five_dimensions) def test_kmeans_nan_fit_large_parallel(): model.fit(X_nan, n_jobs=2) centroids = [[ -0.187485, 1.541443, -0.331161, 1.00714 , -0.214419], [ 3.393221, 4.200322, 4.027316, 4.25569 , 3.986697], [ 8.292196, 8.401983, 7.798085, 8.023552, 7.461508], [ 11.782228, 11.711423, 12.625309, 11.727549, 10.917095]] assert_array_almost_equal(model.centroids, centroids) @with_setup(setup_three_dimensions) def test_kmeans_nan_predict(): y = numpy.array([0, 1, 0, 1, 0, 1, 0, 1, 0, 1]) y_hat = model.predict(X_nan) assert_array_almost_equal(y, y_hat) @with_setup(setup_three_dimensions) def test_kmeans_nan_predict_parallel(): y = numpy.array([0, 1, 0, 1, 0, 1, 0, 1, 0, 1]) y_hat = model.predict(X_nan, n_jobs=2) assert_array_almost_equal(y, y_hat) @with_setup(setup_five_dimensions) def test_kmeans_nan_large_predict(): y = numpy.array([0, 1, 2, 3, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3]) y_hat = model.predict(X_nan) assert_array_almost_equal(y, y_hat) @with_setup(setup_five_dimensions) def test_kmeans_nan_large_predict_parallel(): y = numpy.array([0, 1, 2, 3, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3]) y_hat = model.predict(X_nan, n_jobs=2) assert_array_almost_equal(y, y_hat) @with_setup(setup_five_dimensions) def test_kmeans_nan_multiple_init(): model1 = Kmeans.from_samples(4, X_nan, init='kmeans++', n_init=1) model2 = Kmeans.from_samples(4, X_nan, init='kmeans++', n_init=25) dist1 = model1.distance(X).min(axis=1).sum() dist2 = model2.distance(X).min(axis=1).sum() assert_greater(dist1, dist2) model1 = Kmeans.from_samples(4, X_nan, init='first-k', n_init=1) model2 = Kmeans.from_samples(4, X_nan, init='first-k', n_init=5) dist1 = model1.distance(X).min(axis=1).sum() dist2 = model2.distance(X).min(axis=1).sum() assert_equal(dist1, dist2) @with_setup(setup_five_dimensions) def test_kmeans_ooc_nan_from_samples(): model1 = Kmeans.from_samples(4, X_nan, init='first-k', batch_size=20) model2 = Kmeans.from_samples(4, X_nan, init='first-k', batch_size=None) assert_array_almost_equal(model1.centroids, model2.centroids) @with_setup(setup_five_dimensions) def test_kmeans_ooc_nan_fit(): centroids_copy = numpy.copy(centroids) model1 = Kmeans(4, centroids_copy, n_init=1) model1.fit(X_nan) centroids_copy = numpy.copy(centroids) model2 = Kmeans(4, centroids_copy, n_init=1) model2.fit(X_nan, batch_size=10) centroids_copy = numpy.copy(centroids) model3 = Kmeans(4, centroids_copy, n_init=1) model3.fit(X_nan, batch_size=1) assert_array_almost_equal(model1.centroids, model2.centroids, 4) assert_array_almost_equal(model1.centroids, model3.centroids, 4) @with_setup(setup_five_dimensions) def test_kmeans_minibatch_nan_from_samples(): model1 = Kmeans.from_samples(4, X_nan, init='first-k', batch_size=10) model2 = Kmeans.from_samples(4, X_nan, init='first-k', batch_size=None) model3 = Kmeans.from_samples(4, X_nan, init='first-k', batch_size=10, batches_per_epoch=1) model4 = Kmeans.from_samples(4, X_nan, init='first-k', batch_size=10, batches_per_epoch=2) assert_array_almost_equal(model1.centroids, model2.centroids) assert_array_almost_equal(model1.centroids, model4.centroids) assert_raises(AssertionError, assert_array_equal, model1.centroids, model3.centroids) @with_setup(setup_five_dimensions) def test_kmeans_minibatch_nan_fit(): centroids_copy = numpy.copy(centroids) model1 = Kmeans(4, centroids_copy, n_init=1) model1.fit(X, batch_size=10) centroids_copy = numpy.copy(centroids) model2 = Kmeans(4, centroids_copy, n_init=1) model2.fit(X, batch_size=None) centroids_copy = numpy.copy(centroids) model3 = Kmeans(4, centroids_copy, n_init=1) model3.fit(X, batch_size=10, batches_per_epoch=1) centroids_copy = numpy.copy(centroids) model4 = Kmeans(4, centroids_copy, n_init=1) model4.fit(X, batch_size=10, batches_per_epoch=2) assert_array_almost_equal(model1.centroids, model2.centroids) assert_array_almost_equal(model1.centroids, model4.centroids) assert_raises(AssertionError, assert_array_equal, model1.centroids, model3.centroids)

32.450237

91

0.704031

2,168

13,694

4.223247

0.127306

0.048056

0.041175

0.070336

0.812473

0.791721

0.785496

0.762232

0.719965

0.701289

0

0.197383

0.151672

13,694

421

92

32.527316

0.590772

0

0.538721

0

0.012049

0

0.178451

1

0.104377

false

0

0.047138

0

0.151515

0

null

0

1

0

null

0

6

d5334183de525fc0c4048854ebcc19aab774df8e

54

py

Python

pandaslookup/__init__.py

StefRe/pandas-lookup

14bc77be01c0749e257e20550871ec13db847a43

[ "MIT" ]

1

2021-02-22T12:40:00.000Z

pandaslookup/__init__.py

StefRe/pandas-lookup

14bc77be01c0749e257e20550871ec13db847a43

[ "MIT" ]

null

pandaslookup/__init__.py

StefRe/pandas-lookup

14bc77be01c0749e257e20550871ec13db847a43

[ "MIT" ]

1

2019-11-01T08:37:42.000Z

from .lookup import lookup, from_lookup # noqa: F401

27

53

0.759259

8

54

5

0.625

0.5

0

0.066667

0.166667

54

1

54

0.822222

0.185185

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

d54468d960cf5a9e171bd011f543b441120b47e2

2,245

py

Python

week3/MedianString.py

hot9cups/uhh-stuff

2c77b6ba8632f79d821cd37513e22c0f464ffdca

[ "MIT" ]

null

week3/MedianString.py

hot9cups/uhh-stuff

2c77b6ba8632f79d821cd37513e22c0f464ffdca

[ "MIT" ]

null

week3/MedianString.py

hot9cups/uhh-stuff

2c77b6ba8632f79d821cd37513e22c0f464ffdca

[ "MIT" ]

null

"""import sys import os from itertools import product sys.path.append(os.path.abspath('../week2')) # from GetNeighbors import get_neighbors from HammingDist import hamming_distance from time import time def median_string(dna, k): neighbors = set() # get_neighbors("A"*k, 0, k, neighbors) best_score = k * len(dna) best_motif = "" for pattern in product(('A', 'T', 'C', 'G'), repeat = k): pattern = "".join(pattern) score = 0 for dna_seq in dna: least_dist = k for i in range(len(dna_seq) - k + 1): dist = hamming_distance(pattern, dna_seq[i:i+k]) if dist < least_dist: least_dist = dist score += least_dist if score <= best_score: best_score = score best_motif = pattern return best_motif if __name__ == '__main__': with open("dataset_158_9.txt") as f: start = time() data = f.readlines() k = int(data[0].strip()) dna = [] for i in range(1, len(data)): dna.append(data[i].strip()) print(median_string(dna, k)) print(time() - start) """ import sys import os sys.path.append(os.path.abspath('../week2')) from GetNeighbors import get_neighbors from HammingDist import hamming_distance from time import time def median_string(dna, k): neighbors = set() get_neighbors("A"*k, 0, k, neighbors) best_score = k * len(dna) best_motif = "" for pattern in neighbors: score = 0 for dna_seq in dna: least_dist = k for i in range(len(dna_seq) - k + 1): dist = hamming_distance(pattern, dna_seq[i:i+k]) if dist < least_dist: least_dist = dist score += least_dist if score <= best_score: best_score = score best_motif = pattern return best_motif if __name__ == '__main__': with open("dataset_158_9.txt") as f: start = time() data = f.readlines() k = int(data[0].strip()) dna = [] for i in range(1, len(data)): dna.append(data[i].strip()) print(median_string(dna, k)) print(time() - start)

27.716049

64

0.562584

299

2,245

4.0301

0.204013

0.059751

0.049793

0.053112

0.912863

0

0.013089

0.319376

2,245

81

65

27.716049

0.775524

0.518486

0

0.031628

0

1

0.029412

false

0

0.147059

0

0.205882

0.058824

0

null

0

1

0

null

0

6

63363ffe4ea3026b62579b0d00fcfa0f26add645

31

py

Python

core_admin/skybot/models/__init__.py

linea-it/tno

f973381280504ceb1b606b5b3ccc79b6b8c2aa4f

[ "MIT" ]

null

core_admin/skybot/models/__init__.py

linea-it/tno

f973381280504ceb1b606b5b3ccc79b6b8c2aa4f

[ "MIT" ]

112

2018-04-24T19:10:55.000Z

2022-02-26T16:55:02.000Z

core_admin/skybot/models/__init__.py

linea-it/tno

f973381280504ceb1b606b5b3ccc79b6b8c2aa4f

[ "MIT" ]

null

from .position import Position

15.5

30

0.83871

4

31

6.5

0.75

0

0.129032

31

2

30

15.5

0.962963

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

633f9586a061833a89f573dcedef58d0c9951188

11

py

Python

tests/src/trivia/assignRightShift.py

lindlind/python-interpreter

ffcb38627dc128dddb04e769d0bff6466365271a

[ "MIT" ]

null

tests/src/trivia/assignRightShift.py

lindlind/python-interpreter

ffcb38627dc128dddb04e769d0bff6466365271a

[ "MIT" ]

null

tests/src/trivia/assignRightShift.py

lindlind/python-interpreter

ffcb38627dc128dddb04e769d0bff6466365271a

[ "MIT" ]

null

a = 14 >>2

5.5

10

0.363636

3

11

1.333333

1

0

0.428571

0.363636

11

1

11

0.142857

0

1

0

false

0

1

null

0

1

0

1

0

1

0

null

0

6

636ba7a5c4decebe5d8df4e70ed2d5c4739b4ed1

2,907

py

Python

tests/test_examples.py

cyrilbois/PFNET.py

81d2fd911c6e6aae4c5de0d1739c6f5361799ce2

[ "BSD-2-Clause" ]

3

2018-03-21T11:54:38.000Z

2020-12-29T16:46:14.000Z

tests/test_examples.py

cyrilbois/PFNET.py

81d2fd911c6e6aae4c5de0d1739c6f5361799ce2

[ "BSD-2-Clause" ]

23

2018-03-29T00:42:06.000Z

2021-01-05T19:15:05.000Z

tests/test_examples.py

cyrilbois/PFNET.py

81d2fd911c6e6aae4c5de0d1739c6f5361799ce2

[ "BSD-2-Clause" ]

5

2018-10-01T19:05:11.000Z

2020-05-27T06:19:11.000Z

import os import unittest from subprocess import call, STDOUT class TestExamples(unittest.TestCase): def test_constraints(self): FNULL = open(os.devnull, 'w') retcode = call(["python", "./examples/constraints.py", "./data/ieee14.m"], stdout=FNULL, stderr=STDOUT) self.assertEqual(retcode, 0) def test_contingencies(self): FNULL = open(os.devnull, 'w') retcode = call(["python", "./examples/contingencies.py", "./data/ieee14.m"], stdout=FNULL, stderr=STDOUT) self.assertEqual(retcode, 0) def test_functions(self): FNULL = open(os.devnull, 'w') retcode = call(["python", "./examples/functions.py", "./data/ieee14.m"], stdout=FNULL, stderr=STDOUT) self.assertEqual(retcode, 0) def test_muti_period(self): FNULL = open(os.devnull, 'w') retcode = call(["python", "./examples/multi_period.py", "./data/ieee14.m"], stdout=FNULL, stderr=STDOUT) self.assertEqual(retcode, 0) def test_networks(self): FNULL = open(os.devnull, 'w') retcode = call(["python", "./examples/networks.py", "./data/ieee14.m"], stdout=FNULL, stderr=STDOUT) self.assertEqual(retcode, 0) def test_parsers(self): FNULL = open(os.devnull, 'w') retcode = call(["python", "./examples/parsers.py", "./data/ieee14.m"], stdout=FNULL, stderr=STDOUT) self.assertEqual(retcode, 0) def test_problems(self): FNULL = open(os.devnull, 'w') retcode = call(["python", "./examples/problems.py", "./data/ieee14.m"], stdout=FNULL, stderr=STDOUT) self.assertEqual(retcode, 0) def test_projections(self): FNULL = open(os.devnull, 'w') retcode = call(["python", "./examples/projections.py", "./data/ieee14.m"], stdout=FNULL, stderr=STDOUT) self.assertEqual(retcode, 0) def test_start(self): FNULL = open(os.devnull, 'w') retcode = call(["python", "./examples/start.py", "./data/ieee14.m"], stdout=FNULL, stderr=STDOUT) self.assertEqual(retcode, 0) def test_variables(self): FNULL = open(os.devnull, 'w') retcode = call(["python", "./examples/variables.py", "./data/ieee14.m"], stdout=FNULL, stderr=STDOUT) self.assertEqual(retcode, 0)

30.28125

84

0.488476

275

2,907

5.12

0.141818

0.049716

0.09233

0.106534

0.804688

0

0.016529

0.375645

2,907

95

85

30.6

0.759229

0

0.625

0

0.155831

0.073615

0

0.15625

1

0.15625

false

0

0.046875

0

0.21875

0

null

0

1

0

null

0

6

8955030e6c2c624ff8c140bbb397dbbd0d330bea

177

py

Python

Python2/Day00-PrintHelloWorld.py

MatthewMerrill/HackerRank-30-Days-of-Code

65595c56fa4c8497a07b2386f1034eb0820e004e

[ "Unlicense" ]

null

Python2/Day00-PrintHelloWorld.py

MatthewMerrill/HackerRank-30-Days-of-Code

65595c56fa4c8497a07b2386f1034eb0820e004e

[ "Unlicense" ]

null

Python2/Day00-PrintHelloWorld.py

MatthewMerrill/HackerRank-30-Days-of-Code

65595c56fa4c8497a07b2386f1034eb0820e004e

[ "Unlicense" ]

null

# https://www.hackerrank.com/contests/30-days-of-code/challenges/day-0-print-hello-world/submissions/code/4682129 print("Hello World."); print("Welcome to 30 Days of Code.");

29.5

113

0.751412

28

177

4.75

0.678571

0.090226

0.120301

0.180451

0

0.072727

0.067797

177

5

114

35.4

0.733333

0.627119

0

0.619048

0

1

0

true

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

6

89a3bda8ed83b343fcce0856fa35de1af7e95ae5

90

py

Python

example/data/__init__.py

lemoner20/tensorlayer

69bd591f247b4a67f8968bd29c3660b22dbffae4

[ "Apache-2.0" ]

2

2019-03-27T02:24:50.000Z

2021-08-29T23:35:55.000Z

example/data/__init__.py

lemoner20/tensorlayer

69bd591f247b4a67f8968bd29c3660b22dbffae4

[ "Apache-2.0" ]

null

example/data/__init__.py

lemoner20/tensorlayer

69bd591f247b4a67f8968bd29c3660b22dbffae4

[ "Apache-2.0" ]

null

from __future__ import absolute_import from . import imagenet_classes # from . import

12.857143

38

0.788889

11

90

5.909091

0.545455

0.307692

0

0.177778

90

6

39

15

0.878378

0.144444

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

89a8c86859b59c8a61b971c72e6a5114e2d44a5e

156

py

Python

graphlayer/graphql/naming.py

mwilliamson/python-graphlayer

d71d99c314aca07816ce6a1a7329d0d7fecdfb2f

[ "BSD-2-Clause" ]

25

2019-03-11T16:48:52.000Z

2021-05-02T03:23:20.000Z

graphlayer/graphql/naming.py

mwilliamson/python-graphlayer

d71d99c314aca07816ce6a1a7329d0d7fecdfb2f

[ "BSD-2-Clause" ]

9

2019-03-24T10:43:44.000Z

2021-11-09T23:02:20.000Z

graphlayer/graphql/naming.py

mwilliamson/python-graphlayer

d71d99c314aca07816ce6a1a7329d0d7fecdfb2f

[ "BSD-2-Clause" ]

7

2018-12-30T17:52:07.000Z

2021-05-02T03:23:35.000Z

import re def snake_case_to_camel_case(value): return value[0].lower() + re.sub(r"_(.)", lambda match: match.group(1).upper(), value[1:]).rstrip("_")

26

106

0.666667

25

156

3.92

0.76

0

0.021739

0.115385

156

5

107

31.2

0.688406

0

0.032051

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

982db48df53e6527680b2a74b6d5db8ff8c4189d

103

py

Python

tests/test_active_learning_ts.py

bela127/active_learning_ts

b652995edfb14c37e486ddc8261d6093d6babdae

[ "MIT" ]

1

2022-02-14T09:38:22.000Z

tests/test_active_learning_ts.py

bela127/active_learning_ts

b652995edfb14c37e486ddc8261d6093d6babdae

[ "MIT" ]

1

2022-02-11T12:13:31.000Z

tests/test_active_learning_ts.py

bela127/active_learning_ts

b652995edfb14c37e486ddc8261d6093d6babdae

[ "MIT" ]

2

2021-12-15T12:56:30.000Z

2022-02-01T15:31:08.000Z

from active_learning_ts import __version__ def test_version(): assert __version__ == "0.2.3.0"

12.875

42

0.728155

15

103

4.266667

0.8

0

0.047059

0.174757

103

7

43

14.714286

0.705882

0

0.069307

0

0.333333

1

0.333333

true

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

98893a4725b328c9c8e79dfd93002adc81eb05ef

229

py

Python

src/memegenerator.py

akliamrous/AkliBot

424311d76ed9ae9f85cb4fee83cf04e7860d6574

[ "MIT" ]

null

src/memegenerator.py

akliamrous/AkliBot

424311d76ed9ae9f85cb4fee83cf04e7860d6574

[ "MIT" ]

null

src/memegenerator.py

akliamrous/AkliBot

424311d76ed9ae9f85cb4fee83cf04e7860d6574

[ "MIT" ]

null

import random import discord from discord.ext import commands class MemeGenerator(commands.Cog): def __init__(self, client): self.client = client def generateMeme(self): pass

15.266667

35

0.620087

24

229

5.75

0.625

0.144928

0

0.318777

229

14

36

16.357143

0.884615

0

1

0

1

0.25

false

0.125

0.375

0

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

98aac4857058379aa4e4c7d5429e30dcf794e73e

32

py

Python

app/routers/basic_router/__init__.py

mabittar/fast_api_starter

37cb388b55253994199f4bb1b709c70e95eea1b9

[ "MIT" ]

null

app/routers/basic_router/__init__.py

mabittar/fast_api_starter

37cb388b55253994199f4bb1b709c70e95eea1b9

[ "MIT" ]

null

app/routers/basic_router/__init__.py

mabittar/fast_api_starter

37cb388b55253994199f4bb1b709c70e95eea1b9

[ "MIT" ]

null

from .basic_router import router

32

0.875

5

32

5.4

0.8

0

0.09375

32

1

32

0.931034

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

7f52529f02a52c6d367fd2ddeea837c0a85eba4e

82

py

Python

Python/libraries/recognizers-sequence/recognizers_sequence/resources/__init__.py

acblacktea/Recognizers-Text

2170b8e35216f3fd56cce98fb33cde5339c9f088

[ "MIT" ]

1

2019-06-19T10:45:24.000Z

Python/libraries/recognizers-sequence/recognizers_sequence/resources/__init__.py

AzureMentor/Recognizers-Text

4f18e1d03607cc96e87095d8bf68c481c1b0756f

[ "MIT" ]

null

Python/libraries/recognizers-sequence/recognizers_sequence/resources/__init__.py

AzureMentor/Recognizers-Text

4f18e1d03607cc96e87095d8bf68c481c1b0756f

[ "MIT" ]

1

2019-03-21T13:02:12.000Z

from .base_phone_numbers import BasePhoneNumbers from .base_email import BaseEmail

41

48

0.890244

11

82

6.363636

0.727273

0.228571

0

0.085366

82

2

49

41

0.933333

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

7f7cc3f4864a7d653f7a1a38f0d447ab4e5199b4

8,894

py

Python

BurstCube/NoahSim/burstutils.py

nkasmanoff/Simulation

38d47db79cebe8504a03424c564f2207ae2275ac

[ "MIT" ]

null

BurstCube/NoahSim/burstutils.py

nkasmanoff/Simulation

38d47db79cebe8504a03424c564f2207ae2275ac

[ "MIT" ]

null

BurstCube/NoahSim/burstutils.py

nkasmanoff/Simulation

38d47db79cebe8504a03424c564f2207ae2275ac

[ "MIT" ]

null

import numpy as np import math as mth import random as rand import healpy as hp def length(v): """ Finds the length of a vector Parameters ---------- v : array numpy array representative of the vector you want to find the magnitude of. Returns ------- magv : float magnitude of v. """ magv = mth.sqrt(np.dot(v, v)) return magv def angle(v1, v2): """" Finds the angle between 2 vectors Parameters ---------- v1 : array v2 : array The arrays representing the vectors who's angle is to be calculated. Returns ------- ang : float Angle between the 2 vectors. """ ang = np.arccos(np.dot(v1, v2) / (length(v1) * length(v2))) return ang #Fuck around w this one. def look_up_A(detnorm,source,array=False): """The look up table for detector A. Currently for all these functions the coordinates are relative to the top of the spacecraft, not indivudial detectors. To tranform just rotate by this specific detnorm. Parameters ---------- detnorm : array The vector normal to detector A. source : array The vector pointing to where in the sky the GRB came from. Returns ------- x : float The exponent of dependence for the detector's response. """ if array: ang = findAngles(detnorm,source) if not array: ang = angle(detnorm,source) sourceang = hp.vec2ang(source) sourcetheta = sourceang[0] sourcephi = sourceang[1] #convert to degrees for now, not a big dealio or anything yet. sourcetheta = np.around(np.rad2deg(sourcetheta)) #This needs to be able to take in an array and produce corresponding R's. sourcephi = np.around(np.rad2deg(sourcephi)) X = np.arange(0, 180, 1) #full sky now. Y = np.arange(0, 360, 1) X, Y = np.meshgrid(X, Y) R = 0.76*np.ones(shape=np.shape(X)) if not array: if ang> np.pi/2: x = 0 else: mask1 = X == sourcetheta mask2 = Y == sourcephi x = R[mask1 & mask2] else: x = [] for i in range(len(source)): sourceang = hp.vec2ang(source[i]) mask1 = X == np.around(np.rad2deg(sourceang[0])) #theta mask mask2 = Y == np.around(np.rad2deg(sourceang[1])) #phi mask x.append(R[mask1 & mask2]) return x def look_up_B(detnorm,source,array=False): """The look up table for detector B. Currently for all these functions the coordinates are relative to the top of the spacecraft, not indivudial detectors. To tranform just rotate by this specific detnorm. Parameters ---------- detnorm : array The vector normal to detector B. source : array The vector pointing to where in the sky the GRB came from. Returns ------- x : float The exponent of dependence for the detector's response. """ if array: #for fitting purposes, creates the entire lookup table all at once. Unfortuntaley I only know how to do this by putting them in a loop as done below, which is time costly. ang = findAngles(detnorm,source) if not array: ang = angle(detnorm,source) sourceang = hp.vec2ang(source) sourcetheta = sourceang[0] sourcephi = sourceang[1] #convert to degrees for now, not a big dealio or anything yet. sourcetheta = np.around(np.rad2deg(sourcetheta)) #This needs to be able to take in an array and produce corresponding R's. sourcephi = np.round(np.rad2deg(sourcephi)) X = np.arange(0, 180, 1) #full sky now. Y = np.arange(0, 360, 1) X, Y = np.meshgrid(X, Y) #creates meshgrid for theta phi, and masks the source's position to get response exponent. R = 0.76*np.ones(shape=np.shape(X)) if not array: if ang> np.pi/2: x = 0 else: mask1 = X == sourcetheta mask2 = Y == sourcephi x = R[mask1 & mask2] else: x = [] for i in range(len(source)): sourceang = hp.vec2ang(source[i]) mask1 = X == np.around(np.rad2deg(sourceang[0])) #theta mask mask2 = Y == np.around(np.rad2deg(sourceang[1])) #phi mask x.append(R[mask1 & mask2]) return x def look_up_C(detnorm,source,array=False): """The look up table for detector C. Parameters ---------- detnorm : array The vector normal to detector C. source : array The vector pointing to where in the sky the GRB came from. Returns ------- x : float The exponent of dependence for the detector's response. Example: Let's say for this detector, past 30 degrees and for azimuths of 60 - 180, it's blocked. This is what it would look like: R = 0.76*np.ones(shape=np.shape(X)) R[30:,60:180] = 0 """ if array: ang = findAngles(detnorm,source) if not array: ang = angle(detnorm,source) sourceang = hp.vec2ang(source) sourcetheta = sourceang[0] sourcephi = sourceang[1] #convert to degrees for now, not a big dealio or anything yet. sourcetheta = np.around(np.rad2deg(sourcetheta)) #This needs to be able to take in an array and produce corresponding R's. sourcephi = np.around(np.rad2deg(sourcephi)) X = np.arange(0, 180, 1) #full sky now. Y = np.arange(0, 360, 1) X, Y = np.meshgrid(X, Y) R = 0.76*np.ones(shape=np.shape(X)) #response function if not array: if ang> np.pi/2: x = 0 else: mask1 = X == sourcetheta mask2 = Y == sourcephi x = R[mask1 & mask2] else: x = [] for i in range(len(source)): sourceang = hp.vec2ang(source[i]) mask1 = X == np.around(np.rad2deg(sourceang[0])) #theta mask mask2 = Y == np.around(np.rad2deg(sourceang[1])) #phi mask x.append(R[mask1 & mask2]) return x def look_up_D(detnorm,source,array=False): """The look up table for detector D. Parameters ---------- detnorm : array The vector normal to detector D. source : array The vector pointing to where in the sky the GRB came from. Returns ------- x : float The exponent of dependence for the detector's response. """ if array: ang = findAngles(detnorm,source) if not array: ang = angle(detnorm,source) sourceang = hp.vec2ang(source) sourcetheta = sourceang[0] sourcephi = sourceang[1] #convert to degrees for now, not a big dealio or anything yet. sourcetheta = np.around(np.rad2deg(sourcetheta)) #This needs to be able to take in an array and produce corresponding R's. sourcephi = np.around(np.rad2deg(sourcephi)) X = np.arange(0, 180, 1) #full sky now. Y = np.arange(0, 360, 1) X, Y = np.meshgrid(X, Y) R = 0.76*np.ones(shape=np.shape(X)) if not array: if ang> np.pi/2: x = 0 else: mask1 = X == sourcetheta mask2 = Y == sourcephi x = R[mask1 & mask2] else: x = [] for i in range(len(source)): sourceang = hp.vec2ang(source[i]) mask1 = X == np.around(np.rad2deg(sourceang[0])) #theta mask mask2 = Y == np.around(np.rad2deg(sourceang[1])) #phi mask x.append(R[mask1 & mask2]) return x def response(A,x): """Meant to imitate the actual response of a scintillator. Inputs 2 vectors, and responds with a cos^x dependence. Parameters ----------- A : float The angular separation in radians between the normal vector of the detector, and the position in the sky of the simulated GRB. x : float The dependence Returns ------- R : float The response function of how the scintillator will respond to a source at angle A. """ #meant to imitate the response of the detectors for effective area vs. angle, found to be around .77 # print(length(A),length(B)) #if cosine is negative, #Maybe include the pi/2 thing here. R = pow(abs(np.cos(A)),x) #How I fix the angle stuff now. if A > np.pi/2: R = 0 return R

24.705556

180

0.555318

1,189

8,894

4.147183

0.171573

0.029203

0.03042

0.051714

0.731495

0.712432

0.707767

0

0.028542

0.346076

8,894

359

181

24.774373

0.819292

0.416011

0

0.847328

0

1

0.053435

false

0

0.030534

0

0.137405

0

null

0

1

0

1

0

null

0

6

f6857747395115ddb83c6a519cd664579319ada4

203

py

Python

setcount.py

billylo1/hit-counter

7df9ea2898c05608149832a76c9b6c8400eb4de3

[ "MIT" ]

null

setcount.py

billylo1/hit-counter

7df9ea2898c05608149832a76c9b6c8400eb4de3

[ "MIT" ]

null

setcount.py

billylo1/hit-counter

7df9ea2898c05608149832a76c9b6c8400eb4de3

[ "MIT" ]

null

import config import db import utils db_connection = db.DbAccess(config.DATABASE_FILE_PATH) connection = db_connection.get_connection() db_connection.set_count(connection, 'pass.vaccine-ontario.ca', 21)

29

66

0.832512

29

203

5.586207

0.586207

0.222222

0.271605

0

0.010638

0.073892

203

7

66

29

0.851064

0

0.112745

0

1

0

false

0.166667

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

6

f6a217bcaa0c3d241a5352133e77c46fca3ef059

9,691

py

Python

integration/dagster/tests/test_sensor_cursor.py

denimalpaca/OpenLineage

0448d019b0559b22e96d52a8d5eecb16a9517767

[ "Apache-2.0" ]

1

2021-12-03T17:00:00.000Z

integration/dagster/tests/test_sensor_cursor.py

wjohnson/OpenLineage

3d9a2cd24de82270301169179d4630686b0e6f5d

[ "Apache-2.0" ]

null

integration/dagster/tests/test_sensor_cursor.py

wjohnson/OpenLineage

3d9a2cd24de82270301169179d4630686b0e6f5d

[ "Apache-2.0" ]

null

# 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. import os import json import uuid from unittest.mock import patch from dagster import SensorDefinition, build_sensor_context, DagsterEventType from dagster.core.test_utils import instance_for_test from openlineage.dagster.cursor import OpenLineageCursor, RunningPipeline, RunningStep from .conftest import make_test_event_log_record @patch.dict(os.environ, {"OPENLINEAGE_URL": "http://mock-url:5000"}) def test_basic_sensor_def(): from openlineage.dagster.sensor import openlineage_sensor # noqa: E402 sensor_def = openlineage_sensor() assert isinstance(sensor_def, SensorDefinition) assert not sensor_def.targets @patch.dict(os.environ, {"OPENLINEAGE_URL": "http://mock-url:5000"}) @patch("openlineage.dagster.sensor.get_event_log_records") def test_cursor_update_with_after_storage_id(mock_event_log_records): from openlineage.dagster.sensor import openlineage_sensor # noqa: E402 with instance_for_test() as instance: context = build_sensor_context(instance=instance, repository_name="hello") openlineage_sensor(after_storage_id=100).evaluate_tick(context) assert context.cursor == json.dumps({ "last_storage_id": 100, "running_pipelines": {} }) @patch("openlineage.dagster.sensor._ADAPTER") @patch("openlineage.dagster.sensor.make_step_run_id") @patch("openlineage.dagster.sensor.get_event_log_records") def test_cursor_update_with_successful_run(mock_event_log_records, mock_step_run_id, mock_adapter): # noqa: E501 from openlineage.dagster.sensor import openlineage_sensor # noqa: E402 with instance_for_test() as instance: ol_sensor_def = openlineage_sensor(record_filter_limit=1) # 1. pipeline start pipeline_run_id = str(uuid.uuid4()) mock_event_log_records.return_value = [ make_test_event_log_record( DagsterEventType.RUN_START, pipeline_run_id=pipeline_run_id ) ] context = build_sensor_context(instance=instance) ol_sensor_def.evaluate_tick(context) assert OpenLineageCursor.from_json(context.cursor) == OpenLineageCursor( last_storage_id=1, running_pipelines={ pipeline_run_id: RunningPipeline( running_steps={}, repository_name=None ) } ) # 2. step start step_run_id = str(uuid.uuid4()) step_key = "an_op" mock_step_run_id.return_value = step_run_id mock_event_log_records.return_value = [ make_test_event_log_record( DagsterEventType.STEP_START, pipeline_run_id=pipeline_run_id, step_key=step_key, storage_id=2 # noqa: E501 ) ] ol_sensor_def.evaluate_tick(context) assert OpenLineageCursor.from_json(context.cursor) == OpenLineageCursor( last_storage_id=2, running_pipelines={ pipeline_run_id: RunningPipeline( running_steps={ step_key: RunningStep( step_run_id=step_run_id, input_datasets=[], output_datasets=[]) }, repository_name=None ) } ) # 3. step success mock_event_log_records.return_value = [ make_test_event_log_record( DagsterEventType.STEP_SUCCESS, pipeline_run_id=pipeline_run_id, step_key=step_key, storage_id=3 # noqa: E501 ) ] ol_sensor_def.evaluate_tick(context) assert OpenLineageCursor.from_json(context.cursor) == OpenLineageCursor( last_storage_id=3, running_pipelines={ pipeline_run_id: RunningPipeline( running_steps={}, repository_name=None ) } ) # 4. pipeline success mock_event_log_records.return_value = [ make_test_event_log_record( DagsterEventType.RUN_SUCCESS, pipeline_run_id=pipeline_run_id, storage_id=4 ) ] ol_sensor_def.evaluate_tick(context) assert OpenLineageCursor.from_json(context.cursor) == OpenLineageCursor( last_storage_id=4, running_pipelines={} ) @patch("openlineage.dagster.sensor._ADAPTER") @patch("openlineage.dagster.sensor.make_step_run_id") @patch("openlineage.dagster.sensor.get_event_log_records") def test_cursor_update_with_failing_run(mock_event_log_records, mock_step_run_id, mock_adapter): from openlineage.dagster.sensor import openlineage_sensor # noqa: E402 with instance_for_test() as instance: ol_sensor_def = openlineage_sensor(record_filter_limit=1) # 1. pipeline start pipeline_run_id = str(uuid.uuid4()) mock_event_log_records.return_value = [ make_test_event_log_record( DagsterEventType.RUN_START, pipeline_run_id=pipeline_run_id ) ] context = build_sensor_context(instance=instance, cursor=None) ol_sensor_def.evaluate_tick(context) assert OpenLineageCursor.from_json(context.cursor) == OpenLineageCursor( last_storage_id=1, running_pipelines={ pipeline_run_id: RunningPipeline( running_steps={}, repository_name=None ) }, ) # 2. step start step_run_id = str(uuid.uuid4()) step_key = "an_op" mock_step_run_id.return_value = step_run_id mock_event_log_records.return_value = [ make_test_event_log_record( DagsterEventType.STEP_START, pipeline_run_id=pipeline_run_id, step_key=step_key, storage_id=2 # noqa: E501 ) ] ol_sensor_def.evaluate_tick(context) assert OpenLineageCursor.from_json(context.cursor) == OpenLineageCursor( last_storage_id=2, running_pipelines={ pipeline_run_id: RunningPipeline( running_steps={ step_key: RunningStep( step_run_id=step_run_id, input_datasets=[], output_datasets=[]) }, ) } ) # 3. step fail mock_event_log_records.return_value = [ make_test_event_log_record( DagsterEventType.STEP_FAILURE, pipeline_run_id=pipeline_run_id, step_key=step_key, storage_id=3 # noqa: E501 ) ] ol_sensor_def.evaluate_tick(context) assert OpenLineageCursor.from_json(context.cursor) == OpenLineageCursor( last_storage_id=3, running_pipelines={ pipeline_run_id: RunningPipeline( running_steps={}, repository_name=None ) } ) # 4. pipeline fail mock_event_log_records.return_value = [ make_test_event_log_record( DagsterEventType.RUN_SUCCESS, pipeline_run_id=pipeline_run_id, storage_id=4 ) ] ol_sensor_def.evaluate_tick(context) assert OpenLineageCursor.from_json(context.cursor) == OpenLineageCursor( last_storage_id=4, running_pipelines={} ) @patch("openlineage.dagster.sensor._ADAPTER") @patch("openlineage.dagster.sensor.make_step_run_id") @patch("openlineage.dagster.sensor.get_event_log_records") def test_cursor_update_with_exception_raised(mock_event_log_records, mock_step_run_id, mock_adapter): # noqa: E501 from openlineage.dagster.sensor import openlineage_sensor # noqa: E402 with instance_for_test() as instance: pipeline_run_id = str(uuid.uuid4()) step_key = "an_op" step_run_id = str(uuid.uuid4()) mock_step_run_id.return_value = step_run_id mock_event_log_records.return_value = [ make_test_event_log_record( DagsterEventType.STEP_START, pipeline_run_id=pipeline_run_id, step_key=step_key ), make_test_event_log_record( DagsterEventType.STEP_SUCCESS, pipeline_run_id=pipeline_run_id, step_key=step_key ), ] mock_adapter.complete_step.side_effect = Exception("test!") context = build_sensor_context(instance=instance) openlineage_sensor(record_filter_limit=2).evaluate_tick(context) assert OpenLineageCursor.from_json(context.cursor) == OpenLineageCursor( last_storage_id=1, running_pipelines={ pipeline_run_id: RunningPipeline( running_steps={ step_key: RunningStep( step_run_id=step_run_id, input_datasets=[], output_datasets=[]) }, repository_name=None ) } )

39.555102

125

0.634919

1,067

9,691

5.372071

0.137769

0.044487

0.068039

0.043091

0.821179

0.807746

0.788381

0.773203

0

0.01209

0.291611

9,691

244

126

39.717213

0.82287

0.079662

0

0.64532

0

0.062219

0.04793

0

0.059113

1

0.024631

false

0

0.064039

0

0.08867

0

null

0

1

0

null

0

6

f6c2aba46843d1ca7ff65364fe22763fa2ce9646

100

py

Python

lib/regex.py

itsmewulf/airdrop

b599e669a6777b78cbf68c6f808d1c3744352d73

[ "MIT" ]

null

lib/regex.py

itsmewulf/airdrop

b599e669a6777b78cbf68c6f808d1c3744352d73

[ "MIT" ]

null

lib/regex.py

itsmewulf/airdrop

b599e669a6777b78cbf68c6f808d1c3744352d73

[ "MIT" ]

null

import re ETH_ADDRESS_RE: re.Pattern = re.compile(r'^(?P<prefix>0x)?(?P<actual>[0-9a-fA-F]){40}$')

25

88

0.65

20

100

3.15

0.8

0

0.053763

0.07

100

3

89

33.333333

0.623656

0

0.5

0.44

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

1

null

0

1

0

1

0

6

120121ba961095e2c1470ce96d8c2eec73c18619

365

py

Python

chainer/optimizer_hooks/__init__.py

disktnk/chainer

133798db470f6fd95973b882b9ccbd0c9726ac13

[ "MIT" ]

1

2021-05-31T08:59:28.000Z

chainer/optimizer_hooks/__init__.py

disktnk/chainer

133798db470f6fd95973b882b9ccbd0c9726ac13

[ "MIT" ]

null

chainer/optimizer_hooks/__init__.py

disktnk/chainer

133798db470f6fd95973b882b9ccbd0c9726ac13

[ "MIT" ]

null

from chainer.optimizer_hooks.gradient_clipping import GradientClipping # NOQA from chainer.optimizer_hooks.gradient_hard_clipping import GradientHardClipping # NOQA from chainer.optimizer_hooks.gradient_noise import GradientNoise # NOQA from chainer.optimizer_hooks.lasso import Lasso # NOQA from chainer.optimizer_hooks.weight_decay import WeightDecay # NOQA

60.833333

87

0.863014

45

365

6.777778

0.377778

0.180328

0.327869

0.409836

0.540984

0.242623

0

0.09589

365

5

88

73

0.924242

0.065753

0

1

0

true

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

120bd5ce0a8d9cc9197f6981ed7b561c28f07b80

45

py

Python

python/nlutag/core/bp/__init__.py

jiportilla/ontology

8a66bb7f76f805c64fc76cfc40ab7dfbc1146f40

[ "MIT" ]

null

python/nlutag/core/bp/__init__.py

jiportilla/ontology

8a66bb7f76f805c64fc76cfc40ab7dfbc1146f40

[ "MIT" ]

null

python/nlutag/core/bp/__init__.py

jiportilla/ontology

8a66bb7f76f805c64fc76cfc40ab7dfbc1146f40

[ "MIT" ]

null

from .perform_deep_nlu import PerformDeepNLU

22.5

44

0.888889

6

45

6.333333

1

0

0.088889

45

1

45

0.926829

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

1226a85961d0be3901bc304489aebaee65a7d8a1

47

py

Python

aiger_coins/__init__.py

mvcisback/py-aiger-coins

3e7f5a84e56debe7001d63f2f271e29163781e68

[ "MIT" ]

null

aiger_coins/__init__.py

mvcisback/py-aiger-coins

3e7f5a84e56debe7001d63f2f271e29163781e68

[ "MIT" ]

7

2019-04-01T17:19:13.000Z

2019-11-01T17:33:15.000Z

aiger_coins/__init__.py

mvcisback/py-aiger-coins

3e7f5a84e56debe7001d63f2f271e29163781e68

[ "MIT" ]

2

2019-03-28T03:05:53.000Z

2021-01-05T23:03:53.000Z

# flake8: noqa from aiger_coins.pcirc import *

15.666667

31

0.765957

7

47

5

1

0

0.025

0.148936

47

2

32

23.5

0.85

0.255319

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

12417191af2f14ad976def3007844a00c8d34dee

257

py

Python

ui/components/navigation/templatetags/breadcrumbs.py

adelsonllima/djangoplus

a4ce50bf8231a0d9a4a40751f0d076c2e9931f44

[ "BSD-3-Clause" ]

21

2017-10-08T23:19:47.000Z

2020-01-16T20:02:08.000Z

ui/components/navigation/templatetags/breadcrumbs.py

adelsonllima/djangoplus

a4ce50bf8231a0d9a4a40751f0d076c2e9931f44

[ "BSD-3-Clause" ]

6

2020-06-03T05:30:52.000Z

2022-01-13T00:44:26.000Z

ui/components/navigation/templatetags/breadcrumbs.py

adelsonllima/djangoplus

a4ce50bf8231a0d9a4a40751f0d076c2e9931f44

[ "BSD-3-Clause" ]

9

2017-10-09T22:58:31.000Z

2021-11-20T15:20:18.000Z

# -*- coding: utf-8 -*- from djangoplus.ui.components.navigation.breadcrumbs import Breadcrumbs from django_jinja import library as register @register.global_function def breadcrumbs(request, view_title): return str(Breadcrumbs(request, view_title))

25.7

71

0.793774

32

257

6.25

0.71875

0.18

0.22

0.27

0

0.004386

0.11284

257

9

72

28.555556

0.872807

0.081712

0

1

0.2

false

0

0.4

0.2

0.8

0

null

0

1

0

1

0

null

0

1

0

6

89d529f6eb8cd3e0fb070f23989235e1cc5aeb88

91

py

Python

test.py

harizMunawar/kbbi-scraper

ece8daa7f3d53248ae9d6dd96ff724d092ee3283

[ "MIT" ]

1

2020-11-08T14:42:09.000Z

test.py

harizMunawar/kbbi-scraper

ece8daa7f3d53248ae9d6dd96ff724d092ee3283

[ "MIT" ]

null

test.py

harizMunawar/kbbi-scraper

ece8daa7f3d53248ae9d6dd96ff724d092ee3283

[ "MIT" ]

null

import kbbi_scraper as kbbi from kbbi_scraper import utils print(utils.definition('baju'))

22.75

31

0.824176

14

91

5.214286

0.642857

0.30137

0

0.098901

91

4

31

22.75

0.890244

0

0.043478

0

1

0

true

0

0.666667

0

0.666667

0.333333

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

89ef494262ee647789a44a61ab9f4153639f1934

46

py

Python

akData/parse/__init__.py

adamkerz/akData

673884671da54b2b96480616a3f2633ba4b4710d

[ "BSD-3-Clause" ]

null

akData/parse/__init__.py

adamkerz/akData

673884671da54b2b96480616a3f2633ba4b4710d

[ "BSD-3-Clause" ]

null

akData/parse/__init__.py

adamkerz/akData

673884671da54b2b96480616a3f2633ba4b4710d

[ "BSD-3-Clause" ]

null

from . import phoneNumber from . import abn

15.333333

26

0.73913

6

46

5.666667

0.666667

0.588235

0

0.217391

46

2

27

23

0.944444

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

c3ad7dfbbdcad727fa9a7a78d6719d6ce4a6a926

121

py

Python

app/home/views.py

cyq7on/MicroFilm

d889d2ee035f69b699c57bd4a3353f89c11adb93

[ "Apache-2.0" ]

1

2019-07-06T00:46:47.000Z

app/home/views.py

cyq7on/MicroFilm

d889d2ee035f69b699c57bd4a3353f89c11adb93

[ "Apache-2.0" ]

null

app/home/views.py

cyq7on/MicroFilm

d889d2ee035f69b699c57bd4a3353f89c11adb93

[ "Apache-2.0" ]

null

# coding:utf8 from . import home @home.route("/") def index(): return "<h1 style='color:green'>this is home<h1/>"

13.444444

54

0.628099

18

121

4.222222

0.833333

0

0.03

0.173554

121

8

55

15.125

0.73

0.090909

0

0.388889

0.222222

0

1

0.25

true

0

0.25

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

6

c3e21526c1c0fde2c6fe7ebf01c1bb4637d91ff4

85

py

Python

tsa/src/main/python/thalesians/tsa/finance.py

mikimaus78/ml_monorepo

b2c2627ff0e86e27f6829170d0dac168d8e5783b

[ "BSD-3-Clause" ]

117

2017-06-30T14:29:32.000Z

2022-02-10T00:54:35.000Z

tsa/src/main/python/thalesians/tsa/finance.py

mikimaus78/ml_monorepo

b2c2627ff0e86e27f6829170d0dac168d8e5783b

[ "BSD-3-Clause" ]

2

2019-02-23T18:54:22.000Z

2019-11-09T01:30:32.000Z

tsa/src/main/python/thalesians/tsa/finance.py

mikimaus78/ml_monorepo

b2c2627ff0e86e27f6829170d0dac168d8e5783b

[ "BSD-3-Clause" ]

37

2017-07-05T19:51:10.000Z

2021-04-27T00:11:18.000Z

def usd_trade_size_scaling(x, power=.5, factor=.1): return (x ** power) * factor

28.333333

51

0.670588

14

85

3.857143

0.785714

0.222222

0

0.028169

0.164706

85

2

52

42.5

0.732394

0

1

0.5

false

0

0.5

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

7f076af938ee4554e8ce7384ec09db857bafbb32

193

py

Python

common/settings.py

timmartin19/pycon-ripozo-tutorial

d6f68d0b7c8c8aacb090014c5ff1f34b21ded017

[ "MIT" ]

null

common/settings.py

timmartin19/pycon-ripozo-tutorial

d6f68d0b7c8c8aacb090014c5ff1f34b21ded017

[ "MIT" ]

null

common/settings.py

timmartin19/pycon-ripozo-tutorial

d6f68d0b7c8c8aacb090014c5ff1f34b21ded017

[ "MIT" ]

null

from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals SQLALCHEMY_URI = 'sqlite:///models.sqlite'

27.571429

42

0.854922

24

193

6.041667

0.541667

0.275862

0.441379

0

0.103627

193

6

43

32.166667

0.83815

0

0.119171

0

1

0

false

0

0.8

0

0.8

0.2

1

0

null

1

0

1

0

null

0

1

0

1

0

6

6154fce9b9d782a0b2321862925ac96b8e9fb22a

12,574

py

Python

test/flowchart/generate/Flowchart_Subchart.py

nanofrog/asyncflow

0412ba0d16219994b2baade76fe4223e402285ec

[ "MIT" ]

24

2021-06-29T05:41:46.000Z

2021-07-22T02:03:27.000Z

test/flowchart/generate/Flowchart_Subchart.py

nanofrog/asyncflow

0412ba0d16219994b2baade76fe4223e402285ec

[ "MIT" ]

1

2021-07-29T12:32:03.000Z

test/flowchart/generate/Flowchart_Subchart.py

nanofrog/asyncflow

0412ba0d16219994b2baade76fe4223e402285ec

[ "MIT" ]

11

2021-06-29T02:39:39.000Z

2021-07-05T09:37:32.000Z

import asyncflow ## Say("hello") @asyncflow.func def Subchart_SubchartTest_01_id_42a43a6e54514e45afcfd15f46cbbe03(self): ret = self.Say("hello") return True ## SubchartTest_01_sub() @asyncflow.func def Subchart_SubchartTest_01_id_dca03dece2a04233a5618dc68c9cf5bd(self): ret = asyncflow.call_sub("Subchart.SubchartTest_01_sub", self) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_01_id_fc24d0b59b914be2a62cb8e93bb04aa9(self): ret = self.Say("end") return True ## Say("hellosub") @asyncflow.func def Subchart_SubchartTest_01_sub_id_e73bdb60cc12406198c22d25bdaf9383(self): ret = self.Say("hellosub") return True ## wait(1) @asyncflow.func def Subchart_SubchartTest_01_sub_id_266276762f0c4ae59b8baa1b498f05b7(self): ret = asyncflow.wait(1) return True ## return(1) @asyncflow.func def Subchart_SubchartTest_01_sub_id_ea2ddbba34484e36a827e2f73d8ac897(self): ret = asyncflow.ret(1) return True ## $s1=CreateCharacter() @asyncflow.func def Subchart_SubchartTest_02_id_9c62aa07bc894002943af2b9760f9bf3(self): ret = asyncflow.set_var(0, self.CreateCharacter()) return True ## Say("hello") @asyncflow.func def Subchart_SubchartTest_02_id_fb738de1dcfd4041a45624584f8a6596(self): ret = self.Say("hello") return True ## $s1.SubchartTest_01_sub() @asyncflow.func def Subchart_SubchartTest_02_id_f67352ec4c7644ddb0cf903835f11f01(self): ret = asyncflow.call_sub("Subchart.SubchartTest_01_sub", asyncflow.get_var(0)) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_02_id_a31dbf21ae574b9eaed2d72273f22091(self): ret = self.Say("end") return True ## $s1=CreateCharacter() @asyncflow.func def Subchart_SubchartTest_03_id_53d285961cbb403482b040d60b7aa6ff(self): ret = asyncflow.set_var(0, self.CreateCharacter()) return True ## $s2=CreateCharacter() @asyncflow.func def Subchart_SubchartTest_03_id_d02f8ce037bf4cb2be0440f504764ad0(self): ret = asyncflow.set_var(1, self.CreateCharacter()) return True ## $s={$s1,$s2} @asyncflow.func def Subchart_SubchartTest_03_id_d802d10897ae44419a31852331f1e491(self): ret = asyncflow.set_var(2, [asyncflow.get_var(0), asyncflow.get_var(1)]) return True ## $index=1 @asyncflow.func def Subchart_SubchartTest_03_id_ca65b52b0dbb436887af98e9b59eba68(self): ret = asyncflow.set_var(3, 1) return True ## Say("hello") @asyncflow.func def Subchart_SubchartTest_03_id_370b0b893381472e862ec67b05ed37f5(self): ret = self.Say("hello") return True ## $s[$index].SubchartTest_01_sub() @asyncflow.func def Subchart_SubchartTest_03_id_b49315c6f6d44c8da2a24371dc5e59aa(self): ret = asyncflow.call_sub("Subchart.SubchartTest_01_sub", asyncflow.get_var(2)[asyncflow.get_var(3)]) return True ## $index=1+($index+1)%2 @asyncflow.func def Subchart_SubchartTest_03_id_133c1db850f448bbb58ab69a64c08ee0(self): ret = asyncflow.set_var(3, 1 + (asyncflow.get_var(3) + 1) % 2) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_03_id_77c1994817624bf1be2a13a3dd72eea4(self): ret = self.Say("end") return True ## Say("hello") @asyncflow.func def Subchart_SubchartTest_04_id_94165897646e4b1ca4f34c560a37a222(self): ret = self.Say("hello") return True ## SubchartTest_04_sub() @asyncflow.func def Subchart_SubchartTest_04_id_b1b6ff9be3104b0cab7f7af889e89d53(self): ret = asyncflow.call_sub("Subchart.SubchartTest_04_sub", self) return ret ## Say("end") @asyncflow.func def Subchart_SubchartTest_04_id_3d865c0443344fc79e675f19126bba6f(self): ret = self.Say("end") return True ## Say("hellosub") @asyncflow.func def Subchart_SubchartTest_04_sub_id_98a94c83e0424336a633ff94baa3a3e9(self): ret = self.Say("hellosub") return True ## wait(1) @asyncflow.func def Subchart_SubchartTest_04_sub_id_22db35f73af84406b441e216f7dc4852(self): ret = asyncflow.wait(1) return True ## $s1=CreateCharacter() @asyncflow.func def Subchart_SubchartTest_05_id_d6cd6a2b73e345fcb276e4e16ec9422e(self): ret = asyncflow.set_var(0, self.CreateCharacter()) return True ## Say("hello") @asyncflow.func def Subchart_SubchartTest_05_id_4d0de3891cf24f6ba32e8c2ce3b2efd9(self): ret = self.Say("hello") return True ## $s1.SubchartTest_04_sub() @asyncflow.func def Subchart_SubchartTest_05_id_081c769291b44bd2bc2c49ab14ed6520(self): ret = asyncflow.call_sub("Subchart.SubchartTest_04_sub", asyncflow.get_var(0)) return ret ## Say("end") @asyncflow.func def Subchart_SubchartTest_05_id_eecc6db7972445c9b24d38d3b5d6e02e(self): ret = self.Say("end") return True ## $s1=CreateCharacter() @asyncflow.func def Subchart_SubchartTest_06_id_90ee7f98deb04f14b95c689f558eacfa(self): ret = asyncflow.set_var(0, self.CreateCharacter()) return True ## $s2=CreateCharacter() @asyncflow.func def Subchart_SubchartTest_06_id_57b18856751b4df28098e7e0257bc109(self): ret = asyncflow.set_var(1, self.CreateCharacter()) return True ## $s={$s1,$s2} @asyncflow.func def Subchart_SubchartTest_06_id_0ded790ca5d94adca08635c4f0550e38(self): ret = asyncflow.set_var(2, [asyncflow.get_var(0), asyncflow.get_var(1)]) return True ## $index=1 @asyncflow.func def Subchart_SubchartTest_06_id_07130982db514acc8381dc1ac12ce561(self): ret = asyncflow.set_var(3, 1) return True ## Say("hello") @asyncflow.func def Subchart_SubchartTest_06_id_119bffe10d054c479b41c94e26f3df06(self): ret = self.Say("hello") return True ## $s[$index].SubchartTest_04_sub() @asyncflow.func def Subchart_SubchartTest_06_id_767f30ee29ce4085bc9c0ee2f511f49d(self): ret = asyncflow.call_sub("Subchart.SubchartTest_04_sub", asyncflow.get_var(2)[asyncflow.get_var(3)]) return ret ## $index=1+($index+1)%2 @asyncflow.func def Subchart_SubchartTest_06_id_1f7e7ecd8cd647238ee277018e7744f6(self): ret = asyncflow.set_var(3, 1 + (asyncflow.get_var(3) + 1) % 2) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_06_id_4e2f23bb60814ac19ad2c0de288116d4(self): ret = self.Say("end") return True ## Say("hello") @asyncflow.func def Subchart_SubchartTest_07_id_cc5b038230ff498988d5e3c97486f8d0(self): ret = self.Say("hello") return True ## SubchartTest_07_sub() @asyncflow.func def Subchart_SubchartTest_07_id_9d7479fd0ed64117ac868fa914e6bf23(self): ret = asyncflow.call_sub("Subchart.SubchartTest_07_sub", self) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_07_id_69f4517afe49446d81244fac4a1f69cc(self): ret = self.Say("end") return True ## Say("hellosub") @asyncflow.func def Subchart_SubchartTest_07_sub_id_dc32fef005424047a0cd29588cf9304e(self): ret = self.Say("hellosub") return True ## return(1) @asyncflow.func def Subchart_SubchartTest_07_sub_id_3881148c21a44fc29280ff8b3330fa4f(self): ret = asyncflow.ret(1) return True ## $s1=CreateCharacter() @asyncflow.func def Subchart_SubchartTest_08_id_ecb7cf4b2d254ae38663b6ca76241c22(self): ret = asyncflow.set_var(0, self.CreateCharacter()) return True ## Say("hello") @asyncflow.func def Subchart_SubchartTest_08_id_0ce4ec77462e491eb630ae99e9650937(self): ret = self.Say("hello") return True ## $s1.SubchartTest_07_sub() @asyncflow.func def Subchart_SubchartTest_08_id_c2b07004eedd4cd5aaecc630dde26f8f(self): ret = asyncflow.call_sub("Subchart.SubchartTest_07_sub", asyncflow.get_var(0)) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_08_id_441812d2ea634ca1891a2343159a0e9a(self): ret = self.Say("end") return True ## $s1=CreateCharacter() @asyncflow.func def Subchart_SubchartTest_09_id_c633b30637554a21a23d91a310e20ac6(self): ret = asyncflow.set_var(0, self.CreateCharacter()) return True ## $s2=CreateCharacter() @asyncflow.func def Subchart_SubchartTest_09_id_5a84181fef9644aaaa5433b337941ce2(self): ret = asyncflow.set_var(1, self.CreateCharacter()) return True ## $s={$s1,$s2} @asyncflow.func def Subchart_SubchartTest_09_id_e10130034cd14bc39fea3047237c975c(self): ret = asyncflow.set_var(2, [asyncflow.get_var(0), asyncflow.get_var(1)]) return True ## $index=1 @asyncflow.func def Subchart_SubchartTest_09_id_53dde06bda054e46a38bf7f721c5e538(self): ret = asyncflow.set_var(3, 1) return True ## Say("hello") @asyncflow.func def Subchart_SubchartTest_09_id_7147e19370734e80abd721248e055e1e(self): ret = self.Say("hello") return True ## $s[$index].SubchartTest_07_sub() @asyncflow.func def Subchart_SubchartTest_09_id_161afe7f9987433aa42e71d691785b95(self): ret = asyncflow.call_sub("Subchart.SubchartTest_07_sub", asyncflow.get_var(2)[asyncflow.get_var(3)]) return True ## $index=1+($index+1)%2 @asyncflow.func def Subchart_SubchartTest_09_id_b13723e7fa6944b0941fbb4de31b0ff2(self): ret = asyncflow.set_var(3, 1 + (asyncflow.get_var(3) + 1) % 2) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_09_id_c0d87c34083e42bba62f6803b1da01ad(self): ret = self.Say("end") return True ## $s1=CreateCharacter() @asyncflow.func def Subchart_SubchartTest_10_id_e1389f5d6a5b41559a579782cb791f31(self): ret = asyncflow.set_var(0, self.CreateCharacter()) return True ## $s1.SubchartTest_10_sub() @asyncflow.func def Subchart_SubchartTest_10_id_de1254a491ea42f0aa1f6935ab06102c(self): ret = asyncflow.call_sub("Subchart.SubchartTest_10_sub", asyncflow.get_var(0)) return True ## deregister($s1) @asyncflow.func def Subchart_SubchartTest_10_id_19ef73dcd7e946e7b5c2cbc34627d280(self): ret = asyncflow.deregister(asyncflow.get_var(0)) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_10_id_a896783bee8d414199a15c202d7b3736(self): ret = self.Say("end") return True ## Say("joinsub") @asyncflow.func def Subchart_SubchartTest_10_sub_id_37fb63219c8249df91a47fa358bfeeae(self): ret = self.Say("joinsub") return True ## wait(1) @asyncflow.func def Subchart_SubchartTest_10_sub_id_bec46862dfd441ff8121b81dcc28df46(self): ret = asyncflow.wait(1) return True ## return(1) @asyncflow.func def Subchart_SubchartTest_10_sub_id_36f67553b0044196ba245152c0987544(self): ret = asyncflow.ret(1) return True ## $s1=0 @asyncflow.func def Subchart_SubchartTest_11_id_4c2b870e43ba459494314448ce047cfd(self): ret = asyncflow.set_var(0, 0) return True ## $s1<3 @asyncflow.func def Subchart_SubchartTest_11_id_8134b765856745239df8c754ff132868(self): ret = asyncflow.get_var(0) < 3 return ret ## SubchartTest_01_sub() @asyncflow.func def Subchart_SubchartTest_11_id_b0909c46d2c9464a9cef61c790964e18(self): ret = asyncflow.call_sub("Subchart.SubchartTest_01_sub", self) return True ## $s1=$s1+1 @asyncflow.func def Subchart_SubchartTest_11_id_d8e5d41748cd4f79b0a8b879baec801f(self): ret = asyncflow.set_var(0, asyncflow.get_var(0) + 1) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_11_id_2ea6055927634502a84584bbd098f83b(self): ret = self.Say("end") return True ## $s1=0 @asyncflow.func def Subchart_SubchartTest_12_id_f91d56f7249d437698870d204a8c819f(self): ret = asyncflow.set_var(0, 0) return True ## $s1<3 @asyncflow.func def Subchart_SubchartTest_12_id_295a1f172ea24251802f1d8a9ace7a9d(self): ret = asyncflow.get_var(0) < 3 return ret ## SubchartTest_04_sub() @asyncflow.func def Subchart_SubchartTest_12_id_22db2edad8c04a7381589fc1c4f0050a(self): ret = asyncflow.call_sub("Subchart.SubchartTest_04_sub", self) return ret ## $s1=$s1+1 @asyncflow.func def Subchart_SubchartTest_12_id_c0bbb9a37a464ef78138014769ec09b7(self): ret = asyncflow.set_var(0, asyncflow.get_var(0) + 1) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_12_id_9c436c7877f445eeb9a446bb1401824c(self): ret = self.Say("end") return True ## $s1=0 @asyncflow.func def Subchart_SubchartTest_13_id_d02710f383004ded9eed2e1125cb75e7(self): ret = asyncflow.set_var(0, 0) return True ## $s1<3 @asyncflow.func def Subchart_SubchartTest_13_id_4d9b024b013d4e32920bb87454570c1e(self): ret = asyncflow.get_var(0) < 3 return ret ## SubchartTest_07_sub() @asyncflow.func def Subchart_SubchartTest_13_id_7bbd70650b024598aeca6d34d5ad70c2(self): ret = asyncflow.call_sub("Subchart.SubchartTest_07_sub", self) return True ## $s1=$s1+1 @asyncflow.func def Subchart_SubchartTest_13_id_8151dfbbf8e54164a7ea6cd70125a107(self): ret = asyncflow.set_var(0, asyncflow.get_var(0) + 1) return True ## Say("end") @asyncflow.func def Subchart_SubchartTest_13_id_76b0b09faf18488fb468531138d5696d(self): ret = self.Say("end") return True

32.241026

104

0.778591

1,526

12,574

6.138925

0.077982

0.185739

0.126388

0.189582

0.736336

0.735909

0.683711

0.597459

0.554441

0

0.166622

0.11317

12,574

389

105

32.323907

0.673482

0.091061

0

0.717172

0

0.042468

0.032272

0

1

0.249158

false

0

0.003367

0

0.501684

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

6

619467554ac8d464db10f377d6433a9beae4feb3

177

py

Python

cgxsh_encrypt_config.py

ebob9/cgxsh

0682922bae4354d2e306147e314dd309da968059

[ "MIT" ]

null

cgxsh_encrypt_config.py

ebob9/cgxsh

0682922bae4354d2e306147e314dd309da968059

[ "MIT" ]

3

2020-02-10T00:01:18.000Z

2022-03-28T00:26:45.000Z

cgxsh_encrypt_config.py

ebob9/cgxsh

0682922bae4354d2e306147e314dd309da968059

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- import sys from cgxsh_lib.file_crypto import encrypt_config_file if __name__ == '__main__': sys.exit(encrypt_config_file())

19.666667

53

0.723164

26

177

4.384615

0.769231

0.22807

0.298246

0

0.013072

0.135593

177

8

54

22.125

0.732026

0.242938

0

0.060606

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

4eebcf72a1c7fb13b3a3b39a1346f5851f34e22a

10,904

py

Python

src.py

edbezci/Hasher

9752175c3087d99b6bb20ddc688fe5450a7e7aca

[ "MIT" ]

null

src.py

edbezci/Hasher

9752175c3087d99b6bb20ddc688fe5450a7e7aca

[ "MIT" ]

null

src.py

edbezci/Hasher

9752175c3087d99b6bb20ddc688fe5450a7e7aca

[ "MIT" ]

null

import pygame import os import random import math import sys import timeit import functools import hlp import intro import md5 import sha1 import sha256 # initialise Pygame library, it is necessary in Programs using Pygame pygame.init() line_colour = pygame.Color(50, 50, 120) # initialise window size at 800 * 550 with a caption display = pygame.display.set_mode((1280, 550), pygame.FULLSCREEN | pygame.DOUBLEBUF | pygame.HWSURFACE) pygame.display.set_caption("Hashing Algorithm Comparison Tool") # frames per second determines how many frames should be refreshed per second clock = pygame.time.Clock() #Setting up the background image background_image = os.path.abspath("resources/desc_bgrnd.jpg") bg_image = pygame.image.load(background_image) bg = pygame.transform.scale(bg_image, (1280,550)) # Font bitterfont = os.path.abspath("resources/bitterfont.otf") def dspMd5(): pygame.display.set_caption("MD5 Algorithm") # adding a caption display = pygame.display.set_mode((1280, 550),pygame.FULLSCREEN) effc = timeit.Timer(functools.partial(md5.md5,intro.secret)) efcTime = effc.timeit(15) effcsha1 = timeit.Timer(functools.partial(sha1.sha1,intro.secret)) efcTimesha1 = effc.timeit(15) effcSHA2 = timeit.Timer(functools.partial(sha256.sha256,intro.secret)) efcTimeSHA2 = effc.timeit(15) m = max(efcTime,efcTimesha1,efcTimeSHA2) efcMD5 = (efcTime / m) * 250 efcSHA1 = (efcTimesha1 / m) * 250 efcSHA2 = (efcTimeSHA2 / m) * 250 while True: # starting the game loop display.fill((0,0,0)) # pygame method to fill the screen, takes colours and a display object #display.blit(bg,(0,0)) # pygame method, iterates over the events in pygame to determine what we are doing with every event for event in pygame.event.get(): if event.type == pygame.QUIT: # this one quits pygame.quit() # putting the quit pygame method exit() # takes the user from GUI to the script for exiting if event.type == pygame.KEYUP: # Here is to tell the computer to recognise if a keybord key is pressed. if event.key == pygame.K_ESCAPE: # if that keyboard key is ESC exit() # call for the exit function. surface = pygame.display.get_surface() w,h = surface.get_size() loc1, loc2 = surface.get_size() w = (w/2) - 60 h = (h/2) - 200 hlp.AddText("Encrypted Text: "+ intro.secret, (w-150, h)) hlp.AddText("Padded Text: " + str(md5.padding(intro.secret))[0:15]+"...", (w-150,h+40)) hlp.AddText("MD5 Hashing: "+ md5.md5(intro.secret), (w -150, loc2 - 175)) hlp.AddText(str(round(float(efcTime),4)) +" seconds passed to execute this algorithm", (w -150, 5*loc2/6)) hlp.Button("Exit", 350, 5, 100, 30, sys.exit) back = hlp.ButtonWithReturn("Back", 900, 5, 100, 30, 1) if back > 0: # if back has a value, which means it has been clicked, stop the bigger loop that we started, i.e. the game loop, and break the game loop break pygame.draw.line(display, line_colour, (400, 250), (400, 500), 2) # pygame method, takes display, colour, and positions of where the lines start and end pygame.draw.line(display, line_colour, (350, 500), (950, 500), 2) hlp.AddText("MD5", (465, 510), hlp.white) hlp.AddText("SHA1", (615, 510), hlp.white) hlp.AddText("SHA256", (765, 510), hlp.white) hlp.AddText("0s",(395,505), hlp.white) hlp.AddText(str(round(float(efcTime),5)), (460, 230), hlp.white) hlp.AddText(str(round(float(efcTimesha1),5)), (610, 230), hlp.white) hlp.AddText(str(round(float(efcTimeSHA2),5)), (760, 230), hlp.white) bPos = 500 pygame.draw.rect(display, hlp.button_colour, (465, bPos-efcMD5, 50, efcMD5)) pygame.draw.rect(display, hlp.button_colour, (615, bPos-efcSHA1, 50, efcSHA1)) pygame.draw.rect(display, hlp.button_colour, (765, bPos-efcSHA2, 50, efcSHA2)) pygame.display.flip() # will not run more than 30 frames per second clock.tick(30) intro.Introduction2() def dspSHA1(): pygame.display.set_caption("MD5 Algorithm") # adding a caption display = pygame.display.set_mode((1280, 550),pygame.FULLSCREEN) effc = timeit.Timer(functools.partial(sha1.sha1,intro.secret)) efcTime = effc.timeit(15) effcMDA = timeit.Timer(functools.partial(md5.md5,intro.secret)) efcTimeMDA = effc.timeit(15) effcSHA2 = timeit.Timer(functools.partial(sha256.sha256,intro.secret)) efcTimeSHA2 = effc.timeit(15) m = max(efcTime,efcTimeMDA,efcTimeSHA2) efcMD5 = (efcTimeMDA / m) * 250 efcSHA1 = (efcTime / m) * 250 efcSHA2 = (efcTimeSHA2 / m) * 250 while True: # starting the game loop display.fill((0,0,0)) # pygame method to fill the screen, takes colours and a display object #display.blit(bg,(0,0)) # pygame method, iterates over the events in pygame to determine what we are doing with every event for event in pygame.event.get(): if event.type == pygame.QUIT: # this one quits pygame.quit() # putting the quit pygame method exit() # takes the user from GUI to the script for exiting if event.type == pygame.KEYUP: # Here is to tell the computer to recognise if a keybord key is pressed. if event.key == pygame.K_ESCAPE: # if that keyboard key is ESC exit() # call for the exit function. surface = pygame.display.get_surface() loc1, loc2 = surface.get_size() w,h = surface.get_size() w = (w/2) - 60 h = (h/2) - 200 hlp.AddText("Encrypted Text: "+ intro.secret, (w-150, h)) hlp.AddText("Padded Text: " + str(md5.padding(intro.secret))[0:15]+"...", (w-150,h+30)) hlp.AddText("SHA1 Hashing: "+ sha1.sha1(intro.secret), (w -150, loc2 - 175)) hlp.AddText(str(round(float(efcTime),4)) +" seconds passed to execute this algorithm", (w-150, 5*loc2/6)) hlp.Button("Exit", 350, 5, 100, 30, sys.exit) back = hlp.ButtonWithReturn("Back", 900, 5, 100, 30, 1) if back > 0: # if back has a value, which means it has been clicked, stop the bigger loop that we started, i.e. the game loop, and break the game loop break pygame.draw.line(display, line_colour, (400, 250), (400, 500), 2) # pygame method, takes display, colour, and positions of where the lines start and end pygame.draw.line(display, line_colour, (350, 500), (950, 500), 2) hlp.AddText("0s",(395,505), hlp.white) hlp.AddText("SHA1", (465, 510), hlp.white) hlp.AddText("MD5", (615, 510), hlp.white) hlp.AddText("SHA256", (765, 510), hlp.white) hlp.AddText(str(round(float(efcTime),5)), (460, 230), hlp.white) hlp.AddText(str(round(float(efcTimeMDA),5)), (610, 230), hlp.white) hlp.AddText(str(round(float(efcTimeSHA2),5)), (760, 230), hlp.white) bPos = 500 pygame.draw.rect(display, hlp.button_colour, (465, bPos-efcSHA1, 50, efcSHA1)) pygame.draw.rect(display, hlp.button_colour, (615, bPos-efcMD5, 50, efcMD5)) pygame.draw.rect(display, hlp.button_colour, (765, bPos-efcSHA2, 50, efcSHA2)) pygame.display.flip() # will not run more than 30 frames per second clock.tick(30) intro.Introduction2() def dspSHA256(): pygame.display.set_caption("MD5 Algorithm") # adding a caption display = pygame.display.set_mode((1280, 550),pygame.FULLSCREEN) effc = timeit.Timer(functools.partial(sha256.sha256,intro.secret)) efcTime = effc.timeit(15) effcSHA1 = timeit.Timer(functools.partial(sha1.sha1,intro.secret)) efcTimeSHA1 = effc.timeit(15) effcMDA = timeit.Timer(functools.partial(md5.md5,intro.secret)) efcTimeMDA = effc.timeit(15) m = max(efcTime,efcTimeMDA,efcTimeSHA1) efcMD5 = (efcTimeMDA / m) * 250 efcSHA2 = (efcTime / m) * 250 efcSHA1 = (efcTimeSHA1 / m) * 250 while True: # starting the game loop display.fill((0,0,0)) # pygame method to fill the screen, takes colours and a display object #display.blit(bg,(0,0)) # pygame method, iterates over the events in pygame to determine what we are doing with every event for event in pygame.event.get(): if event.type == pygame.QUIT: # this one quits pygame.quit() # putting the quit pygame method exit() # takes the user from GUI to the script for exiting if event.type == pygame.KEYUP: # Here is to tell the computer to recognise if a keybord key is pressed. if event.key == pygame.K_ESCAPE: # if that keyboard key is ESC exit() # call for the exit function. surface = pygame.display.get_surface() loc1, loc2 = surface.get_size() w,h = surface.get_size() w = (w/2) - 60 h = (h/2) - 200 hlp.AddText("Encrypted Text: "+ intro.secret, (w-150, h)) hlp.AddText("Padded Text: " + str(md5.padding(intro.secret))[0:15]+"...", (w-150,h+30)) hlp.AddText("SHA256 Hashing: "+ sha256.sha256(intro.secret), (w -150, loc2 - 175)) hlp.AddText(str(round(float(efcTime),4)) +" seconds passed to execute this algorithm", (w-150, 5*loc2/6)) hlp.Button("Exit", 350, 5, 100, 30, sys.exit) back = hlp.ButtonWithReturn("Back", 900, 5, 100, 30, 1) if back > 0: # if back has a value, which means it has been clicked, stop the bigger loop that we started, i.e. the game loop, and break the game loop break pygame.draw.line(display, line_colour, (400, 250), (400, 500), 2) # pygame method, takes display, colour, and positions of where the lines start and end pygame.draw.line(display, line_colour, (350, 500), (950, 500), 2) hlp.AddText("0s",(395,505), hlp.white) hlp.AddText("SHA256", (465, 510), hlp.white) hlp.AddText("MD5", (615, 510), hlp.white) hlp.AddText("SHA1", (765, 510), hlp.white) hlp.AddText(str(round(float(efcTime),5)), (460, 230), hlp.white) hlp.AddText(str(round(float(efcTimeMDA),5)), (610, 230), hlp.white) hlp.AddText(str(round(float(efcTimeSHA1),5)), (760, 230), hlp.white) bPos = 500 pygame.draw.rect(display, hlp.button_colour, (465, bPos-efcSHA2, 50, efcSHA2)) pygame.draw.rect(display, hlp.button_colour, (615, bPos-efcMD5, 50, efcMD5)) pygame.draw.rect(display, hlp.button_colour, (765, bPos-efcSHA1, 50, efcSHA1)) pygame.display.flip() # will not run more than 30 frames per second clock.tick(30) intro.Introduction2()

49.117117

159

0.632245

1,533

10,904

4.47032

0.150033

0.048154

0.028892

0.047279

0.878593

0.87013

0.863272

0.850285

0.844885

0.84328

0

0.081608

0.238078

10,904

222

160

49.117117

0.74326

0.21836

0

0.689266

0

0.053209

0.005663

0

1

0.016949

false

0.016949

0.067797

0

0.084746

0

null

0

1

0

null

0

6

f614b329ee85ee5bebc72d26a2a5038fb3a1e1b1

1,355

py

Python

tests/commands/test_autofill.py

gnutix/taxi

3abad480bbc07a0ac1c47c16ee0989227234505b

[ "WTFPL" ]

17

2016-02-02T14:10:49.000Z

2021-11-30T00:04:29.000Z

tests/commands/test_autofill.py

gnutix/taxi

3abad480bbc07a0ac1c47c16ee0989227234505b

[ "WTFPL" ]

70

2015-01-08T17:02:42.000Z

2021-09-21T20:08:07.000Z

tests/commands/test_autofill.py

gnutix/taxi

3abad480bbc07a0ac1c47c16ee0989227234505b

[ "WTFPL" ]

8

2015-08-23T12:50:36.000Z

2021-11-26T10:33:45.000Z

from freezegun import freeze_time @freeze_time('2012-02-20') def test_autofill_bottom(cli, config, entries_file): config.set_dict({ 'taxi': { 'auto_fill_days': '1', 'auto_add': 'bottom' } }) cli('autofill') entries_file_contents = entries_file.readlines() assert entries_file_contents == [ "07/02/2012\n", "\n", "14/02/2012\n", "\n", "21/02/2012\n", "\n", "28/02/2012\n" ] @freeze_time('2012-02-20') def test_autofill_top(cli, config, entries_file): config.set_dict({ 'taxi': { 'auto_fill_days': '1', 'auto_add': 'top' } }) cli('autofill') entries_file_contents = entries_file.readlines() assert entries_file_contents == [ "28/02/2012\n", "\n", "21/02/2012\n", "\n", "14/02/2012\n", "\n", "07/02/2012\n" ] @freeze_time('2012-02-20') def test_autofill_existing_entries(cli, config, entries_file): config.set_dict({ 'taxi': { 'auto_fill_days': '1', 'auto_add': 'top' } }) entries_file.write("15/02/2012\n\n07/02/2012") cli('autofill') entries_file_contents = entries_file.readlines() assert entries_file_contents == [ "28/02/2012\n", "\n", "21/02/2012\n", "\n", "15/02/2012\n", "\n", "07/02/2012\n" ]

23.77193

73

0.55572

181

1,355

3.928177

0.20442

0.118143

0.127989

0.101266

0.860759

0.787623

0.734177

0

0.138446

0.259041

1,355

56

74

24.196429

0.569721

0

0.636364

0

0.245756

0.017712

0

0.068182

1

0.068182

false

0

0.022727

0

0.090909

0

null

0

1

0

null

0

6

f65db77d7a4a3afe4d42823fcc19a5240915c784

2,883

py

Python

cprint.py

hansalemaos/kivy_widget_attribute_printer

49741262d93c6f89a294f653e0a4969984b906c7

[ "MIT" ]

null

cprint.py

hansalemaos/kivy_widget_attribute_printer

49741262d93c6f89a294f653e0a4969984b906c7

[ "MIT" ]

null

cprint.py

hansalemaos/kivy_widget_attribute_printer

49741262d93c6f89a294f653e0a4969984b906c7

[ "MIT" ]

null

class cprint: ''' Use like: cprint.red('Hallo') cprint.green('green') print(cprint.red('Hallo', False) + cprint.green('green', False)) ''' Red = '\033[91m' Green = '\033[92m' Blue = '\033[94m' Cyan = '\033[96m' White = '\033[97m' Yellow = '\033[93m' Magenta = '\033[95m' Grey = '\033[90m' Black = '\033[90m' Default = '\033[99m' ENDC = '\033[0m' BOLD = '\033[1m' UNDERLINE = '\033[4m' @staticmethod def red(text, printtext=True): if printtext: print(cprint.Red + str(text) + cprint.ENDC + cprint.Default) return '' elif not printtext: return cprint.Red + str(text) + cprint.ENDC + cprint.Default def green(text, printtext=True): if printtext: print(cprint.Green + str(text) + cprint.ENDC + cprint.Default) return '' elif not printtext: return cprint.Green + str(text) + cprint.ENDC + cprint.Default def blue(text, printtext=True): if printtext: print(cprint.Blue + str(text) + cprint.ENDC + cprint.Default) return '' elif not printtext: return cprint.Blue + str(text) + cprint.ENDC + cprint.Default def cyan(text, printtext=True): if printtext: print(cprint.Cyan + str(text) + cprint.ENDC + cprint.Default) return '' elif not printtext: return cprint.Cyan + str(text) + cprint.ENDC + cprint.Default def white(text, printtext=True): if printtext: print(cprint.White + str(text) + cprint.ENDC + cprint.Default) return '' elif not printtext: return cprint.White + str(text) + cprint.ENDC + cprint.Default def yellow(text, printtext=True): if printtext: print(cprint.Yellow + str(text) + cprint.ENDC + cprint.Default) return '' elif not printtext: return cprint.Yellow + str(text) + cprint.ENDC + cprint.Default def magenta(text, printtext=True): if printtext: print(cprint.Magenta + str(text) + cprint.ENDC + cprint.Default) return '' elif not printtext: return cprint.Magenta + str(text) + cprint.ENDC + cprint.Default def grey(text, printtext=True): if printtext: print(cprint.Grey + str(text) + cprint.ENDC + cprint.Default) return '' elif not printtext: return cprint.Grey + str(text) + cprint.ENDC + cprint.Default def black(text, printtext=True): if printtext: print(cprint.Black + str(text) + cprint.ENDC + cprint.Default) return '' elif not printtext: return cprint.Black + str(text) + cprint.ENDC + cprint.Default

36.961538

77

0.554977

320

2,883

5

0.134375

0.07875

0.14625

0.19125

0.816875

0.61625

0.36

0

0.031926

0.326396

2,883

77

78

37.441558

0.791967

0.040236

0

0.391304

0

0.037956

0

1

0.130435

false

0

0.594203

0.666667

0

null

0

1

0

null

0

1

0

6

f668cb0fe3c5489249449b93730ed24fcf680a56

235

py

Python

src/Model/EatMove.py

anthonyf996/ChessApp

614f72bc641793681fd5ad7040d6a4c407c9ae9e

[ "MIT" ]

null

src/Model/EatMove.py

anthonyf996/ChessApp

614f72bc641793681fd5ad7040d6a4c407c9ae9e

[ "MIT" ]

null

src/Model/EatMove.py

anthonyf996/ChessApp

614f72bc641793681fd5ad7040d6a4c407c9ae9e

[ "MIT" ]

null

from SimpleMove import SimpleMove from MoveType import MoveType class EatMove(SimpleMove): def __init__(self, board, startPos, endPos): super().__init__(board, startPos, endPos) def getMoveType(self): return MoveType.EAT

23.5

46

0.761702

28

235

6.107143

0.571429

0.152047

0.222222

0

0.153191

235

9

47

26.111111

0.859296

0

1

0.285714

false

0

0.285714

0.142857

0.857143

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

f670893394b529fa82ec70970477b7d478bb7afb

257

py

Python

tests/test_config.py

skoenig/website-monitor

e3e6ce4978736f76b3f6fd6ca19e7e66cad9982e

[ "MIT" ]

null

tests/test_config.py

skoenig/website-monitor

e3e6ce4978736f76b3f6fd6ca19e7e66cad9982e

[ "MIT" ]

null

tests/test_config.py

skoenig/website-monitor

e3e6ce4978736f76b3f6fd6ca19e7e66cad9982e

[ "MIT" ]

null

import pytest from monitor.config import config from monitor.config import configure def test_config_type(): assert type(config) == dict def test_nonexistent_file(): with pytest.raises(FileNotFoundError): configure("/tmp/foobar.yaml")

17.133333

42

0.743191

32

257

5.84375

0.59375

0.117647

0.181818

0.245989

0

0.167315

257

14

43

18.357143

0.873832

0

0.062257

0

0.125

1

0.25

true

0

0.375

0

0.625

0

null

0

1

0

null

0

1

0

1

0

1

0

6

9cad5f3696699cae8bff9e1e06126d2ceb5da51f

23,122

py

Python

models/conv_ae.py

liujiyuan13/MvDOCC-code

1f2d4427dab9f90fbba1575621948f7acbdffddb

[ "MIT" ]

1

2021-05-18T01:29:20.000Z

models/conv_ae.py

liujiyuan13/MvDOCC-code

1f2d4427dab9f90fbba1575621948f7acbdffddb

[ "MIT" ]

null

models/conv_ae.py

liujiyuan13/MvDOCC-code

1f2d4427dab9f90fbba1575621948f7acbdffddb

[ "MIT" ]

null

import torch import torch.nn as nn import torch.nn.functional as F from torch.nn.init import xavier_normal_ slope = 0 def mv_outer_product(X): batch_size = X[0].size(0) X = [torch.cat([X[i], torch.ones(batch_size, 1).cuda()], dim=-1) for i in range(len(X))] for i in range(len(X) - 1): if i == 0: cur_fused_tensor = torch.bmm(X[i].unsqueeze(2), X[i+1].unsqueeze(1)) else: cur_fused_tensor = cur_fused_tensor.view(batch_size, -1, 1) cur_fused_tensor = torch.bmm(cur_fused_tensor, X[i+1].unsqueeze(1)) return cur_fused_tensor.view(batch_size, -1) class CAE_pytorch(nn.Module): def __init__(self, in_channels=3, rep_dim=32): super(CAE_pytorch, self).__init__() nf = 32 self.nf = nf # Encoder: 32x32-x_channel-16x16x32-8x8x64-4x4x128-32 self.enc_conv1 = nn.Conv2d(in_channels=in_channels, out_channels=nf, kernel_size=3, stride=2, padding=1) self.enc_bn1 = nn.BatchNorm2d(num_features=nf) self.enc_act1 = nn.LeakyReLU(slope, inplace=True) self.enc_conv2 = nn.Conv2d(in_channels=nf, out_channels=nf * 2, kernel_size=3, stride=2, padding=1) self.enc_bn2 = nn.BatchNorm2d(num_features=nf * 2) self.enc_act2 = nn.LeakyReLU(slope, inplace=True) self.enc_conv3 = nn.Conv2d(in_channels=nf * 2, out_channels=nf * 4, kernel_size=3, stride=2, padding=1) self.enc_bn3 = nn.BatchNorm2d(num_features=nf * 4) self.enc_act3 = nn.LeakyReLU(slope, inplace=True) self.enc_fc = nn.Linear(nf * 2 * 2 * 16, rep_dim) # Decoder self.dec_fc = nn.Linear(rep_dim, nf * 2 * 2 * 16) self.dec_bn0 = nn.BatchNorm1d(num_features=nf * 2 * 2 * 16) self.dec_act0 = nn.LeakyReLU(slope, inplace=True) self.dec_conv1 = nn.ConvTranspose2d(in_channels=nf * 4, out_channels=nf * 2, kernel_size=3, stride=2, padding=1, output_padding=1) self.dec_bn1 = nn.BatchNorm2d(num_features=nf * 2) self.dec_act1 = nn.LeakyReLU(slope, inplace=True) self.dec_conv2 = nn.ConvTranspose2d(in_channels=nf * 2, out_channels=nf, kernel_size=3, stride=2, padding=1, output_padding=1) self.dec_bn2 = nn.BatchNorm2d(num_features=nf) self.dec_act2 = nn.LeakyReLU(slope, inplace=True) self.dec_conv3 = nn.ConvTranspose2d(in_channels=nf, out_channels=in_channels, kernel_size=3, stride=2, padding=1, output_padding=1) self.output_act = nn.Tanh() def encode(self, x): x = self.enc_act1(self.enc_bn1(self.enc_conv1(x))) x = self.enc_act2(self.enc_bn2(self.enc_conv2(x))) x = self.enc_act3(self.enc_bn3(self.enc_conv3(x))) rep = self.enc_fc(x.view(x.size(0), -1)) return rep def decode(self, rep): x = self.dec_act0(self.dec_bn0(self.dec_fc(rep))) x = x.view(-1, self.nf * 4, 4, 4) x = self.dec_act1(self.dec_bn1(self.dec_conv1(x))) x = self.dec_act2(self.dec_bn2(self.dec_conv2(x))) x = self.output_act(self.dec_conv3(x)) return x def forward(self, x): output = self.decode(self.encode(x)) return output class CENC(nn.Module): def __init__(self, in_channels=3, rep_dim=32): super(CENC, self).__init__() nf = 32 self.nf = nf # Encoder: 32x32-x_channel-16x16x32-8x8x64-4x4x128-32 self.enc_conv1 = nn.Conv2d(in_channels=in_channels, out_channels=nf, kernel_size=3, stride=2, padding=1) self.enc_bn1 = nn.BatchNorm2d(num_features=nf) self.enc_act1 = nn.LeakyReLU(slope, inplace=True) self.enc_conv2 = nn.Conv2d(in_channels=nf, out_channels=nf * 2, kernel_size=3, stride=2, padding=1) self.enc_bn2 = nn.BatchNorm2d(num_features=nf * 2) self.enc_act2 = nn.LeakyReLU(slope, inplace=True) self.enc_conv3 = nn.Conv2d(in_channels=nf * 2, out_channels=nf * 4, kernel_size=3, stride=2, padding=1) self.enc_bn3 = nn.BatchNorm2d(num_features=nf * 4) self.enc_act3 = nn.LeakyReLU(slope, inplace=True) self.enc_fc = nn.Linear(nf * 2 * 2 * 16, rep_dim) def forward(self, x): x = self.enc_act1(self.enc_bn1(self.enc_conv1(x))) x = self.enc_act2(self.enc_bn2(self.enc_conv2(x))) x = self.enc_act3(self.enc_bn3(self.enc_conv3(x))) rep = self.enc_fc(x.view(x.size(0), -1)) return rep class CDEC(nn.Module): def __init__(self, in_channels=3, rep_dim=32): super(CDEC, self).__init__() nf = 32 self.nf = nf # Decoder self.dec_fc = nn.Linear(rep_dim, nf * 2 * 2 * 16) self.dec_bn0 = nn.BatchNorm1d(num_features=nf * 2 * 2 * 16) self.dec_act0 = nn.LeakyReLU(slope, inplace=True) self.dec_conv1 = nn.ConvTranspose2d(in_channels=nf * 4, out_channels=nf * 2, kernel_size=3, stride=2, padding=1, output_padding=1) self.dec_bn1 = nn.BatchNorm2d(num_features=nf * 2) self.dec_act1 = nn.LeakyReLU(slope, inplace=True) self.dec_conv2 = nn.ConvTranspose2d(in_channels=nf * 2, out_channels=nf, kernel_size=3, stride=2, padding=1, output_padding=1) self.dec_bn2 = nn.BatchNorm2d(num_features=nf) self.dec_act2 = nn.LeakyReLU(slope, inplace=True) self.dec_conv3 = nn.ConvTranspose2d(in_channels=nf, out_channels=in_channels, kernel_size=3, stride=2, padding=1, output_padding=1) self.output_act = nn.Tanh() def forward(self, rep): x = self.dec_act0(self.dec_bn0(self.dec_fc(rep))) x = x.view(-1, self.nf * 4, 4, 4) x = self.dec_act1(self.dec_bn1(self.dec_conv1(x))) x = self.dec_act2(self.dec_bn2(self.dec_conv2(x))) x = self.output_act(self.dec_conv3(x)) return x class mv_cae(nn.Module): def __init__(self, input_channel_set, rep_dim): super(mv_cae, self).__init__() self.cae_set = nn.ModuleList([CAE_pytorch(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) self.score_fuc = torch.nn.MSELoss(reduction='none') def get_latent(self, X): return [self.cae_set[i].encode((X[i])) for i in range(len(X))] def forward(self, X): return [self.cae_set[i](X[i]) for i in range(len(X))] def get_ad_scores(self, X): ''' :param X: A list with multi-view inputs :return: A list of (N, 1) tensor anomaly score (larger means more normal) ''' outputs_set = self.forward(X) outputs_set = [self.score_fuc(outputs_set[i], X[i]) for i in range(len(X))] scores_set = [-1. * torch.mean(torch.mean(torch.mean(outputs_set[i], dim=-1), dim=-1), dim=-1, keepdim=True) for i in range(len(X))] return scores_set class mvcae_fused(nn.Module): def __init__(self, input_channel_set, rep_dim, fuse_dim): super(mvcae_fused, self).__init__() self.cae_set = nn.ModuleList([CAE_pytorch(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) self.fuse = torch.nn.Sequential( nn.Linear(len(input_channel_set) * rep_dim, fuse_dim, bias=False), nn.BatchNorm1d(fuse_dim), nn.LeakyReLU(slope, inplace=True), nn.Linear(fuse_dim, len(input_channel_set) * rep_dim, bias=False), nn.BatchNorm1d(len(input_channel_set) * rep_dim), nn.LeakyReLU(slope, inplace=True)) self.score_fuc = torch.nn.MSELoss(reduction='none') def get_latent(self, X): return [self.cae_set[i].encode((X[i])) for i in range(len(X))] def forward(self, X): X_latent = self.get_latent(X) X_latent = torch.cat(X_latent, dim=1) X_fused = self.fuse(X_latent) X_fused = X_fused.view(X_fused.size(0), -1, len(self.cae_set)) return [self.cae_set[i].decode(X_fused[:, :, i]) for i in range(len(X))] def get_ad_scores(self, X): ''' :param X: A list with multi-view inputs :return: A list of (N, 1) tensor anomaly score (larger means more normal) ''' outputs_set = self.forward(X) outputs_set = [self.score_fuc(outputs_set[i], X[i]) for i in range(len(X))] scores_set = [-1. * torch.mean(torch.mean(torch.mean(outputs_set[i], dim=-1), dim=-1), dim=-1, keepdim=True) for i in range(len(X))] return scores_set class mvenc(nn.Module): def __init__(self, input_channel_set, rep_dim): super(mvenc, self).__init__() self.cae_set = nn.ModuleList([CENC(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) def forward(self, X): return [self.cae_set[i](X[i]) for i in range(len(X))] class mvenc_fused(nn.Module): def __init__(self, input_channel_set, rep_dim): super(mvenc_fused, self).__init__() self.cae_set = nn.ModuleList([CENC(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) self.fuse_layer = torch.nn.Sequential(nn.Linear(len(input_channel_set) * rep_dim, rep_dim, bias=False), nn.BatchNorm1d(num_features=rep_dim), nn.LeakyReLU(slope, inplace=True) ) def forward(self, X): cae_outputs = [self.cae_set[i](X[i]) for i in range(len(X))] cae_outputs = torch.cat(cae_outputs, dim=1) output = self.fuse_layer(cae_outputs) return output class mv_corrCAE(nn.Module): def __init__(self, input_channel_set, rep_dim): super(mv_corrCAE, self).__init__() self.cae_set = nn.ModuleList([CAE_pytorch(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) self.score_fuc = torch.nn.MSELoss(reduction='none') def get_latent(self, X): return [self.cae_set[i].encode((X[i])) for i in range(len(X))] def forward(self, X): latent_set = [self.cae_set[i].encode(X[i]) for i in range(len(X))] return latent_set, [self.cae_set[i].decode(latent_set[i]) for i in range(len(X))] def get_ad_scores(self, X): ''' :param X: A list with multi-view inputs :return: A list of (N, 1) tensor anomaly score (larger means more normal) ''' _, outputs_set = self.forward(X) outputs_set = [self.score_fuc(outputs_set[i], X[i]) for i in range(len(X))] scores_set = [-1. * torch.mean(torch.mean(torch.mean(outputs_set[i], dim=-1), dim=-1), dim=-1, keepdim=True) for i in range(len(X))] return scores_set class splitCAE(nn.Module): def __init__(self, input_channel_set, rep_dim, dec_mode='fixed'): super(splitCAE, self).__init__() self.enc_set = nn.ModuleList([CENC(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) self.dec_mode = dec_mode if self.dec_mode is 'fixed': self.dec_set = nn.ModuleList([CDEC(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) else: self.dec_set = nn.ModuleList([nn.ModuleList([CDEC(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) for y in range(len(input_channel_set))]) self.score_fuc = torch.nn.MSELoss(reduction='none') def forward(self, X): latent_set = [self.enc_set[i](X[i]) for i in range(len(X))] if self.dec_mode is 'fixed': output_set = [[self.dec_set[j](latent_set[i]) for j in range(len(X))] for i in range(len(X))] else: output_set = [[self.dec_set[i][j](latent_set[i]) for j in range(len(X))] for i in range(len(X))] return output_set def get_ad_scores(self, X): outputs_set = self.forward(X) scores_set = [[] for i in range(len(X))] for j in range(len(X)): # for each enc. cur_res_set = [self.score_fuc(outputs_set[j][i], X[i]) for i in range(len(X))] cur_scores_set = [-1. * torch.mean(torch.mean(torch.mean(cur_res_set[i], dim=-1), dim=-1), dim=-1, keepdim=True) for i in range(len(X))] for i in range(len(X)): # for each view scores_set[i].append(cur_scores_set[i]) for i in range(len(X)): # for each view scores_set[i] = torch.cat(scores_set[i], dim=-1) scores_set[i] = torch.mean(scores_set[i], dim=-1, keepdim=True) return scores_set class mvcae_ss(nn.Module): def __init__(self, input_channel_set, rep_dim, fuse_dim, mode='fuse', param_mode='fixed'): super(mvcae_ss, self).__init__() self.cae_set = nn.ModuleList([CAE_pytorch(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) self.mode = mode self.param_mode = param_mode # fuse all views and reconstruct all views if mode is 'fuse': if param_mode is 'nn': self.fuse_all = torch.nn.Sequential(nn.Linear(len(input_channel_set) * rep_dim, fuse_dim, bias=False), nn.BatchNorm1d(fuse_dim), nn.LeakyReLU(slope, inplace=True)) self.split_all = torch.nn.Sequential(nn.Linear(fuse_dim, len(input_channel_set) * rep_dim, bias=False), nn.BatchNorm1d(len(input_channel_set) * rep_dim), nn.LeakyReLU(slope, inplace=True)) elif param_mode is 'sum' or param_mode is 'max': pass else: raise NotImplementedError # fuse all views other than the target view and pred. the target view if mode is 'pred': if param_mode is 'fixed': self.fuse_pred = torch.nn.Sequential(nn.Linear((len(input_channel_set) - 1) * rep_dim, fuse_dim, bias=False), nn.BatchNorm1d(fuse_dim), nn.LeakyReLU(slope, inplace=True) ) else: self.fuse_pred = nn.ModuleList([torch.nn.Sequential(nn.Linear((len(input_channel_set) - 1) * rep_dim, fuse_dim, bias=False), nn.BatchNorm1d(fuse_dim), nn.LeakyReLU(slope, inplace=True)) for i in range(len(input_channel_set))]) # reconstruct all views from the embedding of one view if mode is 'split': if param_mode is 'fixed': self.split_pred = torch.nn.Sequential(nn.Linear(rep_dim, len(input_channel_set) * rep_dim, bias=False), nn.BatchNorm1d(len(input_channel_set) * rep_dim), nn.LeakyReLU(slope, inplace=True) ) else: self.split_pred = nn.ModuleList([torch.nn.Sequential(nn.Linear(rep_dim, len(input_channel_set) * rep_dim, bias=False), nn.BatchNorm1d(len(input_channel_set) * rep_dim), nn.LeakyReLU(slope, inplace=True)) for i in range(len(input_channel_set))]) self.score_fuc = torch.nn.MSELoss(reduction='none') def get_latent(self, X): return [self.cae_set[i].encode((X[i])) for i in range(len(X))] def forward(self, X): if self.mode is 'fuse': X_latent = self.get_latent(X) if self.param_mode is 'nn': X_latent = torch.cat(X_latent, dim=1) X_fused = self.fuse_all(X_latent) X_fused = self.split_all(X_fused) X_fused = X_fused.view(X_fused.size(0), -1, len(self.cae_set)) output_set = [self.cae_set[i].decode(X_fused[:, :, i]) for i in range(len(X))] elif self.param_mode is 'sum': X_fused = X_latent[0] for i in range(len(X_latent) - 1): X_fused += X_latent[i+1] X_fused /= len(X_latent) output_set = [self.cae_set[i].decode(X_fused) for i in range(len(X))] elif self.param_mode is 'max': X_latent = [X_latent[_].unsqueeze(2) for _ in range(len(X_latent))] X_fused = torch.max(torch.cat(X_latent, dim=-1), dim=-1)[0] output_set = [self.cae_set[i].decode(X_fused) for i in range(len(X))] else: raise NotImplementedError return output_set elif self.mode is 'pred': X_latent = self.get_latent(X) X_fused = [] for i in range(len(X)): cur_fused = [] for j in range(len(X)): if i != j: cur_fused.append(X_latent[j]) cur_fused = torch.cat(cur_fused, dim=1) if self.param_mode is 'fixed': X_fused.append(self.fuse_pred(cur_fused)) else: X_fused.append(self.fuse_pred[i](cur_fused)) return [self.cae_set[i].decode(X_fused[i]) for i in range(len(X))] elif self.mode is 'split': X_latent = self.get_latent(X) if self.param_mode is 'fixed': X_latent = [self.split_pred(X_latent[i]) for i in range(len(X_latent))] else: X_latent = [self.split_pred[i](X_latent[i]) for i in range(len(X_latent))] output_set = [] for i in range(len(X_latent)): cur_latent = X_latent[i] cur_latent = cur_latent.view(cur_latent.size(0), -1, len(self.cae_set)) cur_outputs = [self.cae_set[j].decode(cur_latent[:, :, j]) for j in range(len(X))] output_set.append(cur_outputs) return output_set else: raise NotImplementedError def get_ad_scores(self, X): ''' :param X: A list with multi-view inputs :return: A list of (N, 1) tensor anomaly score (larger means more normal) ''' if self.mode is 'fuse' or self.mode is 'pred': outputs_set = self.forward(X) outputs_set = [self.score_fuc(outputs_set[i], X[i]) for i in range(len(X))] scores_set = [-1. * torch.mean(torch.mean(torch.mean(outputs_set[i], dim=-1), dim=-1), dim=-1, keepdim=True) for i in range(len(X))] elif self.mode is 'split': outputs_set = self.forward(X) scores_set = [[] for i in range(len(X))] for j in range(len(X)): # for each enc. cur_res_set = [self.score_fuc(outputs_set[j][i], X[i]) for i in range(len(X))] cur_scores_set = [-1. * torch.mean(torch.mean(torch.mean(cur_res_set[i], dim=-1), dim=-1), dim=-1, keepdim=True) for i in range(len(X))] for i in range(len(X)): # for each view scores_set[i].append(cur_scores_set[i]) for i in range(len(X)): # for each view scores_set[i] = torch.cat(scores_set[i], dim=-1) scores_set[i] = torch.mean(scores_set[i], dim=-1, keepdim=True) else: raise NotImplementedError return scores_set class tensor_fusion_layer(nn.Module): def __init__(self, in_dim1, in_dim2, output_dim): super(tensor_fusion_layer, self).__init__() self.in_dim = (in_dim1+1) * (in_dim2+1) self.in_dim1 = in_dim1 self.in_dim2 = in_dim2 self.output_dim = output_dim self.fuse_layer = torch.nn.Sequential( nn.Linear(self.in_dim, self.output_dim, bias=False), nn.BatchNorm1d(output_dim), nn.LeakyReLU(slope, inplace=True), ) def forward(self, x, y): # both x and y must be a 2-D matrice assert x.size(0) == y.size(0) batch_size = x.size(0) assert x.size(1) == self.in_dim1 assert y.size(1) == self.in_dim2 assert len(x.size()) == 2 assert len(y.size()) == 2 x = torch.cat([x, torch.ones(batch_size, 1).cuda()], dim=-1) y = torch.cat([y, torch.ones(batch_size, 1).cuda()], dim=-1) fused_tensor = torch.bmm(x.unsqueeze(2), y.unsqueeze(1)).view(batch_size, -1) fused_tensor = self.fuse_layer(fused_tensor) return fused_tensor class mv_CAE_tf(nn.Module): def __init__(self, input_channel_set, rep_dim, rank=3): super(mv_CAE_tf, self).__init__() self.enc_set = nn.ModuleList([CENC(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) self.dec_set = nn.ModuleList([CDEC(in_channels=input_channel_set[x], rep_dim=rep_dim) for x in range(len(input_channel_set))]) self.score_fuc = torch.nn.MSELoss(reduction='none') output_dim = rep_dim self.factor_set = nn.Parameter(torch.Tensor(len(input_channel_set), rank, rep_dim + 1, output_dim)) self.factor_set = xavier_normal_(self.factor_set) self.fusion_weights = nn.Parameter(torch.Tensor(1, rank)) self.fusion_bias = nn.Parameter(torch.Tensor(1, output_dim)) xavier_normal_(self.fusion_weights) self.fusion_bias.data.fill_(0) # self.fuse_layer = torch.nn.Sequential( # nn.Linear((rep_dim+1) ** len(input_channel_set), rep_dim, bias=False), # nn.BatchNorm1d(rep_dim), # nn.LeakyReLU(slope, inplace=True), # ) # self.fuse_layer = [] # for i in range(len(input_channel_set) -1): # self.fuse_layer.append(tensor_fusion_layer(in_dim1=rep_dim, in_dim2=rep_dim, output_dim=rep_dim)) # self.fuse_layer = nn.ModuleList(self.fuse_layer) def get_latent(self, X): return [self.enc_set[i]((X[i])) for i in range(len(X))] def forward(self, X): latent_set = [self.enc_set[i](X[i]) for i in range(len(X))] latent_set = [torch.cat([torch.ones(latent_set[i].size(0), 1).cuda(), latent_set[i]], dim=-1) for i in range(len(X))] for i in range(len(X)): if i == 0: latent_fused = torch.matmul(latent_set[i], self.factor_set[i]) else: cur_latent_fused = torch.matmul(latent_set[i], self.factor_set[i]) latent_fused = latent_fused * cur_latent_fused fused_rep = torch.matmul(self.fusion_weights, latent_fused.permute(1, 0, 2)).squeeze() + self.fusion_bias # fused_rep = latent_set[0] # for i in range(len(X) - 1): # fused_rep = self.fuse_layer[i](fused_rep, latent_set[i+1]) # latent_fused = mv_outer_product(latent_set) # latent_set = self.fuse_layer(latent_fused) return [self.dec_set[i](fused_rep) for i in range(len(X))] def get_ad_scores(self, X): ''' :param X: A list with multi-view inputs :return: A list of (N, 1) tensor anomaly score (larger means more normal) ''' outputs_set = self.forward(X) outputs_set = [self.score_fuc(outputs_set[i], X[i]) for i in range(len(X))] scores_set = [-1. * torch.mean(torch.mean(torch.mean(outputs_set[i], dim=-1), dim=-1), dim=-1, keepdim=True) for i in range(len(X))] return scores_set

46.151697

194

0.606998

3,543

23,122

3.734124

0.05024

0.038095

0.054422

0.047392

0.81678

0.785034

0.761829

0.739683

0.7161

0.71542

0

0.022029

0.259839

23,122

500

195

46.244

0.751023

0.068074

0

0.607046

0

0.005759

0

0.01355

1

0.102981

false

0.00271

0.01084

0.01897

0.222222

0

null

0

1

0

null

0

6

9cba1ab361fbdd4d1c36902b797dfac5a8e2ef4a

9,760

py

Python

tests/test_app.py

rafaelsouzak2b/lista_favoritos

38cdda263a7a8d157cbfd9abdc4b6e4af3b9f4b8

[ "MIT" ]

null

tests/test_app.py

rafaelsouzak2b/lista_favoritos

38cdda263a7a8d157cbfd9abdc4b6e4af3b9f4b8

[ "MIT" ]

null

tests/test_app.py

rafaelsouzak2b/lista_favoritos

38cdda263a7a8d157cbfd9abdc4b6e4af3b9f4b8

[ "MIT" ]

null

import base64 import string import random import json random_str = string.ascii_letters from src.app.models.usuarios import UsuarioModel username = ''.join(random.choice(random_str) for i in range(10)) password = 'teste' nome_cliente = ''.join(random.choice(random_str) for i in range(10)) email_cliente = ''.join(random.choice(random_str) for i in range(20)) token = '' def test_inserir_usuario_201(client): ''' Teste de inserção de usuario ''' payload = { 'username': username, 'password': password } response = client.post('/api/usuario', json=payload) retorno = json.loads(response.data) assert response.status_code == 201 assert len(retorno) > 0 def test_inserir_usuario_ja_cadastrado_400(client): ''' Teste de inserção de usuario ja existente ''' payload = { 'username': username, 'password': password } response = client.post('/api/usuario', json=payload) assert response.status_code == 400 def test_inserir_usuario_400(client): ''' Teste de inserção de usuario sem payload ''' response = client.post('/api/usuario') assert response.status_code == 400 def test_autenticar_usuario_200(client): ''' Teste de geração de token ''' userpass = f'{username}:{password}' base64_val = base64.b64encode(userpass.encode()).decode() headers = { 'Authorization': f'Basic {base64_val}' } response = client.post('/api/usuario/auth', headers=headers) global token retorno = json.loads(response.data) token = retorno['token'] usuario_data = UsuarioModel.find_by_username(username) if usuario_data: usuario_data.delete_from_db() assert response.status_code == 200 assert len(retorno) > 0 def test_inserir_clientes_201(client): ''' Teste de inserção de cliente ''' headers = { 'Authorization': f'Bearer {token}' } payload = { 'nome': nome_cliente, 'email': email_cliente } response = client.post('/api/clientes', headers=headers, json=payload) retorno = json.loads(response.data) assert response.status_code == 201 assert len(retorno) > 0 def test_inserir_clientes_ja_cadastrado_400(client): ''' Teste de inserção de cliente ja cadastrado ''' headers = { 'Authorization': f'Bearer {token}' } payload = { 'nome': nome_cliente, 'email': email_cliente } response = client.post('/api/clientes', headers=headers, json=payload) assert response.status_code == 400 def test_inserir_clientes_400(client): ''' Teste de inserção de cliente sem payload ''' headers = { 'Authorization': f'Bearer {token}' } response = client.post('/api/clientes', headers=headers) assert response.status_code == 400 def test_visualizar_todos_clientes_200(client): ''' Teste de visualização de todos os clientes ''' headers = { 'Authorization': f'Bearer {token}' } response = client.get('/api/clientes', headers=headers) retorno = json.loads(response.data) assert response.status_code == 200 assert len(retorno) > 0 def test_visualizar_clientes_200(client): ''' Teste de visualização de cliente ''' headers = { 'Authorization': f'Bearer {token}' } response = client.get(f'/api/clientes/{email_cliente}', headers=headers) retorno = json.loads(response.data) assert response.status_code == 200 assert len(retorno) > 0 def test_visualizar_clientes_404(client): ''' Teste de visualização de cliente não cadastrado ''' headers = { 'Authorization': f'Bearer {token}' } response = client.get(f'/api/clientes/{email_cliente}k', headers=headers) assert response.status_code == 404 def test_alterar_clientes_200(client): ''' Teste de atualização de cliente ''' headers = { 'Authorization': f'Bearer {token}' } payload = { 'nome': nome_cliente, 'email': email_cliente } response = client.put(f'/api/clientes/{email_cliente}', headers=headers, json=payload) retorno = json.loads(response.data) assert response.status_code == 200 assert len(retorno) > 0 def test_alterar_clientes_404(client): ''' Teste de atualização de cliente não cadastrado ''' headers = { 'Authorization': f'Bearer {token}' } payload = { 'nome': nome_cliente, 'email': email_cliente } response = client.put(f'/api/clientes/{email_cliente}k', headers=headers, json=payload) assert response.status_code == 404 def test_alterar_clientes_400(client): ''' Teste de atualização de cliente sem payload ''' headers = { 'Authorization': f'Bearer {token}' } response = client.put(f'/api/clientes/{email_cliente}', headers=headers) assert response.status_code == 400 def test_deletar_clientes_404(client): ''' Teste de deletar cliente não cadastrado ''' headers = { 'Authorization': f'Bearer {token}' } response = client.delete(f'/api/clientes/{email_cliente}k', headers=headers) assert response.status_code == 404 def test_visualizar_lista_favoritos_200(client): ''' Teste de visualização da lista de favoritos ''' headers = { 'Authorization': f'Bearer {token}' } response = client.get(f'/api/clientes/{email_cliente}/favoritos', headers=headers) retorno = json.loads(response.data) assert response.status_code == 200 assert len(retorno) > 0 def test_visualizar_lista_favoritos_404(client): ''' Teste de visualização da lista de favoritos de cliente não cadastrado ''' headers = { 'Authorization': f'Bearer {token}' } response = client.get(f'/api/clientes/{email_cliente}k/favoritos', headers=headers) assert response.status_code == 404 def test_inserir_lista_favoritos_201(client): ''' Teste de inclusao de produto na lista de favoritos ''' headers = { 'Authorization': f'Bearer {token}' } response = client.post(f'/api/clientes/{email_cliente}/favoritos/1bf0f365-fbdd-4e21-9786-da459d78dd1f', headers=headers) retorno = json.loads(response.data) assert response.status_code == 201 assert len(retorno) > 0 def test_inserir_lista_favoritos_400(client): ''' Teste de inclusão de produto ja inserido na lista de favoritos ''' headers = { 'Authorization': f'Bearer {token}' } response = client.post(f'/api/clientes/{email_cliente}/favoritos/1bf0f365-fbdd-4e21-9786-da459d78dd1f', headers=headers) assert response.status_code == 400 def test_inserir_lista_favoritos_produto_nao_existe_400(client): ''' Teste de inclusão de produto não existente ''' headers = { 'Authorization': f'Bearer {token}' } response = client.post(f'/api/clientes/{email_cliente}/favoritos/teste', headers=headers) assert response.status_code == 400 def test_inserir_lista_favoritos_404(client): ''' Teste de inclusão de produto na lista de favoritos de cliente que não existe ''' headers = { 'Authorization': f'Bearer {token}' } response = client.post(f'/api/clientes/{email_cliente}k/favoritos/1bf0f365-fbdd-4e21-9786-da459d78dd1f', headers=headers) assert response.status_code == 404 def test_deletar_lista_favoritos_204(client): ''' Teste de exclusão do produto na lista de favoritos ''' headers = { 'Authorization': f'Bearer {token}' } response = client.delete(f'/api/clientes/{email_cliente}/favoritos/1bf0f365-fbdd-4e21-9786-da459d78dd1f', headers=headers) assert response.status_code == 204 def test_deletar_lista_favoritos_404(client): ''' Teste de exclusão do produto na lista de favoritos de produto que não esta na lista do cliente ''' headers = { 'Authorization': f'Bearer {token}' } response = client.delete(f'/api/clientes/{email_cliente}/favoritos/1bf0f365-fbdd-4e21-9786-da459d78dd1f', headers=headers) assert response.status_code == 404 def test_deletar_lista_favoritos_cliente_nao_cadastrado_404(client): ''' Teste de exclusão do produto na lista de favoritos de cliente que não esta cadastrado ''' headers = { 'Authorization': f'Bearer {token}' } response = client.delete(f'/api/clientes/{email_cliente}k/favoritos/1bf0f365-fbdd-4e21-9786-da459d78dd1f', headers=headers) assert response.status_code == 404 def test_deletar_toda_lista_favoritos_204(client): ''' Teste de exclusão de toda lista de favoritos do cliente ''' headers = { 'Authorization': f'Bearer {token}' } client.post(f'/api/clientes/{email_cliente}/favoritos/1bf0f365-fbdd-4e21-9786-da459d78dd1f', headers=headers) response = client.delete(f'/api/clientes/{email_cliente}/favoritos', headers=headers) assert response.status_code == 204 def test_deletar_toda_lista_favoritos_404(client): ''' Teste de exclusão de toda lista de favoritos de cliente não cadastrado ''' headers = { 'Authorization': f'Bearer {token}' } response = client.delete(f'/api/clientes/{email_cliente}f/favoritos', headers=headers) assert response.status_code == 404 def test_deletar_clientes_204(client): ''' Teste exclusão de cliente ''' headers = { 'Authorization': f'Bearer {token}' } response = client.delete(f'/api/clientes/{email_cliente}', headers=headers) assert response.status_code == 204

25.025641

127

0.661066

1,146

9,760

5.480803

0.094241

0.028976

0.082789

0.099347

0.888234

0.856711

0.823754

0.768827

0.730457

0.67935

0

0.040401

0.223975

9,760

389

128

25.089974

0.788883

0.130123

0

0.548544

0

0.219144

0.119218

0

0.002571

0.165049

1

0.126214

false

0.024272

0

0.150485

0

null

0

1

0

null

0

6

9cc051d0ea7c0fe603cbee8e1b9386269f730557

47

py

Python

python_modules/libraries/dagster-postgres/dagster_postgres/event_log/__init__.py

dbatten5/dagster

d76e50295054ffe5a72f9b292ef57febae499528

[ "Apache-2.0" ]

4,606

2018-06-21T17:45:20.000Z

2022-03-31T23:39:42.000Z

python_modules/libraries/dagster-postgres/dagster_postgres/event_log/__init__.py

dbatten5/dagster

d76e50295054ffe5a72f9b292ef57febae499528

[ "Apache-2.0" ]

6,221

2018-06-12T04:36:01.000Z

2022-03-31T21:43:05.000Z

python_modules/libraries/dagster-postgres/dagster_postgres/event_log/__init__.py

dbatten5/dagster

d76e50295054ffe5a72f9b292ef57febae499528

[ "Apache-2.0" ]

619

2018-08-22T22:43:09.000Z

2022-03-31T22:48:06.000Z

from .event_log import PostgresEventLogStorage

23.5

46

0.893617

5

47

8.2

1

0

0.085106

47

1

47

0.953488

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

14676e65cb32fd903fc7242ba9d84b87ff585f82

48

py

Python

ec2_compare/internal/usage_classes/__init__.py

weldpua2008/aws.ec2.compare

5149fc4c7cb42f4d7df1930ed8a06750155fe578

[ "Apache-2.0" ]

null

ec2_compare/internal/usage_classes/__init__.py

weldpua2008/aws.ec2.compare

5149fc4c7cb42f4d7df1930ed8a06750155fe578

[ "Apache-2.0" ]

null

ec2_compare/internal/usage_classes/__init__.py

weldpua2008/aws.ec2.compare

5149fc4c7cb42f4d7df1930ed8a06750155fe578

[ "Apache-2.0" ]

1

2021-12-15T11:58:22.000Z

# Automatically generated at December 05, 2020

16

46

0.791667

6

48

6.333333

1

0

0.15

0.166667

48

2

47

24

0.8

0.916667

0

null

1

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

1

0

null

0

1

0

6

1af96ce2d518d77f199b3cb1c2fd61d17f5c516b

45

py

Python

torchwisdom/vision/transforms/__init__.py

nunenuh/modelzoo.pytorch

0a0e5dda84d59243a084b053d98f2eabd76474f5

[ "MIT" ]

8

2019-03-23T17:53:52.000Z

2021-06-15T17:38:00.000Z

torchwisdom/vision/transforms/__init__.py

nunenuh/modelzoo.pytorch

0a0e5dda84d59243a084b053d98f2eabd76474f5

[ "MIT" ]

39

2019-03-26T08:22:40.000Z

2019-05-22T05:18:31.000Z

torchwisdom/vision/transforms/__init__.py

nunenuh/modelzoo.pytorch

0a0e5dda84d59243a084b053d98f2eabd76474f5

[ "MIT" ]

4

2019-04-05T06:32:09.000Z

2019-05-09T14:53:51.000Z

from .pair import * from .transforms import *

22.5

25

0.755556

6

45

5.666667

0.666667

0

0.155556

45

2

25

22.5

0.894737

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

2115aa77bce777b55b1e73c4147429d98339c71b

100

py

Python

models/partseg/__init__.py

luost26/Equivariant-OrientedMP

597f9c4ace953929e5eefef84e4c840d6636b818

[ "MIT" ]

5

2022-03-26T07:08:21.000Z

2022-03-31T12:23:40.000Z

models/partseg/__init__.py

luost26/Equivariant-OrientedMP

597f9c4ace953929e5eefef84e4c840d6636b818

[ "MIT" ]

null

models/partseg/__init__.py

luost26/Equivariant-OrientedMP

597f9c4ace953929e5eefef84e4c840d6636b818

[ "MIT" ]

null

from ._registry import get_model from .dgcnn import DGCNN from .oriented_dgcnn import OrientedDGCNN

25

41

0.85

14

100

5.857143

0.571429

0.268293

0

0.12

100

3

42

33.333333

0.931818

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

0d45b279b5c1aa7c488f801d2e344bb8fc198484

106

py

Python

app/models/core/store/__init__.py

polowis/virtComp

142c623da4722f7443d76fc8bef0e56c0aa3d48e

[ "MIT" ]

null

app/models/core/store/__init__.py

polowis/virtComp

142c623da4722f7443d76fc8bef0e56c0aa3d48e

[ "MIT" ]

null

app/models/core/store/__init__.py

polowis/virtComp

142c623da4722f7443d76fc8bef0e56c0aa3d48e

[ "MIT" ]

null

from .global_store import * # noqa from .global_store import __all__ as glob_store __all__ = glob_store

21.2

47

0.792453

16

106

4.5

0.5

0.277778

0.416667

0.583333

0

0.160377

106

5

48

21.2

0.808989

0.037736

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

6

0d49e3149723afb309e2deadab8ccfe16e442dc8

91

py

Python

nntools/experiment/__init__.py

ClementPla/NNTools

61562be2d931a7f720ceee1bd91a37a2b9a329af

[ "MIT" ]

null

nntools/experiment/__init__.py

ClementPla/NNTools

61562be2d931a7f720ceee1bd91a37a2b9a329af

[ "MIT" ]

null

nntools/experiment/__init__.py

ClementPla/NNTools

61562be2d931a7f720ceee1bd91a37a2b9a329af

[ "MIT" ]

null

from .experiment import Experiment from .supervised_experiment import SupervisedExperiment

30.333333

55

0.89011

9

91

8.888889

0.555556

0.4

0

0.087912

91

2

56

45.5

0.963855

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

b4b560b1d6111512544ff830bd87291cdf1f782e

61

py

Python

conpaas-services/src/conpaas/core/https/__init__.py

bopopescu/conpaas-1

cea3c02f499a729464697de7cf98c2041febc0ab

[ "BSD-3-Clause" ]

1

2015-09-20T18:20:01.000Z

conpaas-services/src/conpaas/core/https/__init__.py

bopopescu/conpaas-1

cea3c02f499a729464697de7cf98c2041febc0ab

[ "BSD-3-Clause" ]

1

2020-07-27T11:56:18.000Z

conpaas-services/src/conpaas/core/https/__init__.py

bopopescu/conpaas-1

cea3c02f499a729464697de7cf98c2041febc0ab

[ "BSD-3-Clause" ]

3

2018-09-14T16:54:14.000Z

2020-07-26T03:14:56.000Z

from . import client from . import server from . import x509

15.25

20

0.754098

9

61

5.111111

0.555556

0.652174

0

0.061224

0.196721

61

3

21

20.333333

0.877551

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

b4b9db60242f2b6da3850ce3a163f642fd2b3b5a

77

py

Python

python/src/test/resources/pyfunc/numpy_random18_test.py

maropu/lljvm-translator

322fbe24a27976948c8e8081a9552152dda58b4b

[ "Apache-2.0" ]

70

2017-12-12T10:54:00.000Z

2022-03-22T07:45:19.000Z

python/src/test/resources/pyfunc/numpy_random18_test.py

maropu/lljvm-as

322fbe24a27976948c8e8081a9552152dda58b4b

[ "Apache-2.0" ]

14

2018-02-28T01:29:46.000Z

2019-12-10T01:42:22.000Z

python/src/test/resources/pyfunc/numpy_random18_test.py

maropu/lljvm-as

322fbe24a27976948c8e8081a9552152dda58b4b

[ "Apache-2.0" ]

4

2019-07-21T07:58:25.000Z

2021-02-01T09:46:59.000Z

import numpy as np def numpy_random18_test(a): return np.random.choice(a)

15.4

28

0.766234

14

77

4.071429

0.785714

0

0.030303

0.142857

77

4

29

19.25

0.833333

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

b4d4611f79ba90ce501679525ce39af566fb31a0

179

py

Python

buzzard/_tools/__init__.py

ashnair1/buzzard

f9a9c2ac2929d997b1643f4730c67e3db45e181e

[ "Apache-2.0" ]

30

2019-12-07T21:16:41.000Z

2022-03-07T15:12:25.000Z

buzzard/_tools/__init__.py

ashnair1/buzzard

f9a9c2ac2929d997b1643f4730c67e3db45e181e

[ "Apache-2.0" ]

42

2018-01-31T20:03:55.000Z

2019-11-12T19:42:13.000Z

buzzard/_tools/__init__.py

ashnair1/buzzard

f9a9c2ac2929d997b1643f4730c67e3db45e181e

[ "Apache-2.0" ]

15

2018-01-31T19:47:22.000Z

2019-11-26T10:27:50.000Z

""" Collection of private tools """ from .parameters import * from .helper_classes import * from .rect import * from .multi_ordered_dict import * from .slices_of_matrix import *

17.9

33

0.759777

24

179

5.458333

0.625

0.305344

0

0.150838

179

9

34

19.888889

0.861842

0.150838

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

b4e8d94b296fefa3cf51048af1e428c77fdd70d5

139

py

Python

pagi/utils/env.py

khuongnd/pagi

33e6b6c9bf126c648b58320fa7d8d488f82b16d1

[ "MIT" ]

null

pagi/utils/env.py

khuongnd/pagi

33e6b6c9bf126c648b58320fa7d8d488f82b16d1

[ "MIT" ]

null

pagi/utils/env.py

khuongnd/pagi

33e6b6c9bf126c648b58320fa7d8d488f82b16d1

[ "MIT" ]

null

import torch def check_gpu_available(): return torch.cuda.is_available() if __name__ == "__main__": print(check_gpu_available())

17.375

36

0.733813

18

139

4.944444

0.722222

0.179775

0.382022

0

0.151079

139

8

37

17.375

0.754237

0

0.057143

0

1

0.2

true

0

0.2

0.6

0.2

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

b4f87a17ea8315bf8603190f62218c08495abbdc

45

py

Python

MTL_startup.py

mtlong/FGVC

b1c5b1a84b763e8b8236a68f2ffef9274dea49cd

[ "MIT" ]

null

MTL_startup.py

mtlong/FGVC

b1c5b1a84b763e8b8236a68f2ffef9274dea49cd

[ "MIT" ]

null

MTL_startup.py

mtlong/FGVC

b1c5b1a84b763e8b8236a68f2ffef9274dea49cd

[ "MIT" ]

null

print("Run to startup the python session")

11.25

42

0.733333

7

45

4.714286

1

0

0.177778

45

3

43

15

0.891892

0

0.767442

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

2ef76736dedb347f9bb8ed053ebcad1e84e246d4

130

py

Python

Stepik1.py

devilnotcry77/devil_not_cry

a9d342d053c788ec6db2d1c5967ed55104b40045

[ "Apache-2.0" ]

null

Stepik1.py

devilnotcry77/devil_not_cry

a9d342d053c788ec6db2d1c5967ed55104b40045

[ "Apache-2.0" ]

null

Stepik1.py

devilnotcry77/devil_not_cry

a9d342d053c788ec6db2d1c5967ed55104b40045

[ "Apache-2.0" ]

null

a = int(input()) b = int(input()) print(a+b) print(a-b) print(a*b) print(a/b) print(a//b) print(a%b) print((a**10 + b **10)**0.5)

13

28

0.561538

31

130

2.354839

0.258065

0.575342

0.986301

0.657534

0

0.052632

0.123077

130

9

29

14.444444

0.587719

0

1

0

false

0

0.777778

0

null

1

0

1

0

1

0

null

0

1

0

6

2efa35c517ff1949b4b0f06b7c7c0517d5e0f80d

177

py

Python

sis-web/rest/__init__.py

maxbilbow/7054CEM-sis

1c5067c9afc38e340fcce046048f8ae21d267365

[ "MIT" ]

null

sis-web/rest/__init__.py

maxbilbow/7054CEM-sis

1c5067c9afc38e340fcce046048f8ae21d267365

[ "MIT" ]

null

sis-web/rest/__init__.py

maxbilbow/7054CEM-sis

1c5067c9afc38e340fcce046048f8ae21d267365

[ "MIT" ]

null

def init(): import rest.auth_controller import rest.index import rest.membership_controller import rest.quote_controller import rest.user_profile_controller

25.285714

39

0.774011

22

177

6

0.5

0.378788

0.454545

0

0.180791

177

6

40

29.5

0.910345

0

1

0.166667

true

0

0.833333

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

2c179052e7a08ee25e6aa6d67f1e4168ebf0e7d0

1,734

py

Python

temboo/core/Library/Flickr/Photos/__init__.py

jordanemedlock/psychtruths

52e09033ade9608bd5143129f8a1bfac22d634dd

[ "Apache-2.0" ]

7

2016-03-07T02:07:21.000Z

2022-01-21T02:22:41.000Z

temboo/core/Library/Flickr/Photos/__init__.py

jordanemedlock/psychtruths

52e09033ade9608bd5143129f8a1bfac22d634dd

[ "Apache-2.0" ]

null

temboo/core/Library/Flickr/Photos/__init__.py

jordanemedlock/psychtruths

52e09033ade9608bd5143129f8a1bfac22d634dd

[ "Apache-2.0" ]

8

2016-06-14T06:01:11.000Z

2020-04-22T09:21:44.000Z

from temboo.Library.Flickr.Photos.AddTags import AddTags, AddTagsInputSet, AddTagsResultSet, AddTagsChoreographyExecution from temboo.Library.Flickr.Photos.Delete import Delete, DeleteInputSet, DeleteResultSet, DeleteChoreographyExecution from temboo.Library.Flickr.Photos.Download import Download, DownloadInputSet, DownloadResultSet, DownloadChoreographyExecution from temboo.Library.Flickr.Photos.GetInfo import GetInfo, GetInfoInputSet, GetInfoResultSet, GetInfoChoreographyExecution from temboo.Library.Flickr.Photos.ListGeoTaggedPhotos import ListGeoTaggedPhotos, ListGeoTaggedPhotosInputSet, ListGeoTaggedPhotosResultSet, ListGeoTaggedPhotosChoreographyExecution from temboo.Library.Flickr.Photos.ListPeople import ListPeople, ListPeopleInputSet, ListPeopleResultSet, ListPeopleChoreographyExecution from temboo.Library.Flickr.Photos.ListPhotosWithoutGeoTags import ListPhotosWithoutGeoTags, ListPhotosWithoutGeoTagsInputSet, ListPhotosWithoutGeoTagsResultSet, ListPhotosWithoutGeoTagsChoreographyExecution from temboo.Library.Flickr.Photos.ListPublicPhotos import ListPublicPhotos, ListPublicPhotosInputSet, ListPublicPhotosResultSet, ListPublicPhotosChoreographyExecution from temboo.Library.Flickr.Photos.ListRecentPhotos import ListRecentPhotos, ListRecentPhotosInputSet, ListRecentPhotosResultSet, ListRecentPhotosChoreographyExecution from temboo.Library.Flickr.Photos.Replace import Replace, ReplaceInputSet, ReplaceResultSet, ReplaceChoreographyExecution from temboo.Library.Flickr.Photos.SearchPhotos import SearchPhotos, SearchPhotosInputSet, SearchPhotosResultSet, SearchPhotosChoreographyExecution from temboo.Library.Flickr.Photos.Upload import Upload, UploadInputSet, UploadResultSet, UploadChoreographyExecution

133.384615

206

0.903114

132

1,734

11.863636

0.409091

0.076628

0.130268

0.176245

0.222222

0

0.048443

1,734

12

207

144.5

0.949091

0

1

0

true

0

1

0

1

0

1

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

25a76c2817bb7803e0468bbb40914707d3cf4648

61,669

py

Python

lib/data_loaders.py

SwagJ/FCGF

18cfb4d4e9f7a18487d6ef8941fcaeda387ab55f

[ "MIT" ]

null

lib/data_loaders.py

SwagJ/FCGF

18cfb4d4e9f7a18487d6ef8941fcaeda387ab55f

[ "MIT" ]

null

lib/data_loaders.py

SwagJ/FCGF

18cfb4d4e9f7a18487d6ef8941fcaeda387ab55f

[ "MIT" ]

null

# -*- coding: future_fstrings -*- # # Written by Chris Choy <chrischoy@ai.stanford.edu> # Distributed under MIT License import logging import random import torch import torch.utils.data import numpy as np import glob import os from scipy.linalg import expm, norm import pathlib from util.pointcloud import get_matching_indices, make_open3d_point_cloud, get_neighbor_indices, get_hardest_neigative_indices import lib.transforms as t import MinkowskiEngine as ME import open3d as o3d from scipy.interpolate import interp1d from scipy.spatial.transform import Rotation as R from scipy.spatial.transform import Slerp from lib.timer import Timer from lib.metrics import pdist #from lib.feature_extraction import prepare_feature import ntpath from sklearn.preprocessing import normalize kitti_cache = {} kitti_icp_cache = {} kaist_cache = {} kaist_icp_cache = {} def collate_pair_fn(list_data): xyz0, xyz1, coords0, coords1, feats0, feats1, matching_inds, trans, sample_num, neighbor0, neighbor1,num_neighbor0,num_neighbor1 = list( zip(*list_data)) xyz_batch0, xyz_batch1 = [], [] matching_inds_batch, trans_batch, len_batch = [], [], [] coords0_in_batch,coords1_in_batch = [],[] unique_match = [] centroid_in_batch = [] max_in_batch = [] neighbor0_in_batch = [] neighbor1_in_batch = [] num_neighbor0_in_batch = [] num_neighbor1_in_batch = [] correspondance_in_batch = [] #neg_ind_in_batch=[] pos1_coord_in_batch = [] pos0_coord_in_batch = [] batch_id = 0 curr_start_inds = np.zeros((1, 2)) #print(sample_num) sample_num = min(sample_num) def to_tensor(x): if isinstance(x, torch.Tensor): return x elif isinstance(x, np.ndarray): return torch.from_numpy(x) else: raise ValueError(f'Can not convert to torch tensor, {x}') for batch_id, _ in enumerate(coords0): N0 = coords0[batch_id].shape[0] N1 = coords1[batch_id].shape[0] #print("num of points:",N0,N1) #print("neighborhood0 size:",neighbor0[batch_id].shape) #print("neighborhood1 size:",neighbor1[batch_id].shape) neighbor0_in_batch.append(to_tensor(neighbor0[batch_id])) neighbor1_in_batch.append(to_tensor(neighbor1[batch_id])) num_neighbor0_in_batch.append(to_tensor(num_neighbor0[batch_id])) num_neighbor1_in_batch.append(to_tensor(num_neighbor1[batch_id])) xyz_batch0.append(to_tensor(xyz0[batch_id])) xyz_batch1.append(to_tensor(xyz1[batch_id])) #points normalization coord0_i = to_tensor(coords0[batch_id]).float() coord1_i = to_tensor(coords1[batch_id]).float() #print("coord0_i shape:",coord0_i.shape) #print("coord1_i shape:",coord1_i.shape) batch_corr = np.array(matching_inds[batch_id]) # normalization centroid0 = torch.mean(coord0_i, axis=0) centroid1 = torch.mean(coord1_i, axis=0) centroid_in_batch.append([centroid0,centroid1]) #print(centroid0,centroid1) centered0 = coord0_i - centroid0 centered1 = coord1_i - centroid1 max0 = torch.max(torch.sqrt(torch.sum(abs(centered0)**2,axis=-1))) max1 = torch.max(torch.sqrt(torch.sum(abs(centered1)**2,axis=-1))) max_in_batch.append([max0,max1]) normed_coords0 = centered0 / max0 normed_coords1 = centered1 / max1 #sample points in batch sel0 = np.random.choice(N0, sample_num, replace=False) sel1 = np.random.choice(N1, sample_num, replace=False) coords0_in_batch.append(normed_coords0[sel0,:].float()) coords1_in_batch.append(normed_coords1[sel1,:].float()) #sample positive correspondance _,unique_idx = np.unique(batch_corr[:,0],return_index=True) #unique_idx = torch.from_numpy(unique_idx) corr_match_idx = batch_corr[unique_idx] pos0_coord = normed_coords0[corr_match_idx[:,0],:] pos1_coord = normed_coords1[corr_match_idx[:,1],:] pos0_coord_in_batch.append(to_tensor(pos0_coord)) pos1_coord_in_batch.append(to_tensor(pos1_coord)) trans_batch.append(to_tensor(trans[batch_id])) #neg_ind_in_batch.append(to_tensor(neg_inds[batch_id]).int()) matching_inds_batch.append( torch.from_numpy(np.array(matching_inds[batch_id])).int()) correspondance_in_batch.append( torch.from_numpy(np.array(matching_inds[batch_id]) + curr_start_inds)) len_batch.append([N0, N1]) # Move the head curr_start_inds[0, 0] += N0 curr_start_inds[0, 1] += N1 #print("before sparse_collate:",coords0[0].shape) coords_batch0, feats_batch0 = ME.utils.sparse_collate(coords0, feats0) coords_batch1, feats_batch1 = ME.utils.sparse_collate(coords1, feats1) #print("after sparse_collate:",coords_batch0.shape) # Concatenate all lists xyz_batch0 = torch.cat(xyz_batch0, 0).float() xyz_batch1 = torch.cat(xyz_batch1, 0).float() trans_batch = torch.cat(trans_batch, 0).float() #matching_inds_batch = torch.cat(matching_inds_batch, 0).int() correspondance_in_batch = torch.cat(correspondance_in_batch, 0).int() coords0_downsampled = torch.stack(coords0_in_batch,0).float() coords1_downsampled = torch.stack(coords1_in_batch,0).float() #coords0 = to_tensor(np.array(coords0).astype(np.float32)) #coords1 = to_tensor(np.array(coords1).astype(np.float32)) #print(matching_inds_batch[0:100,:]) return { 'pcd0': xyz_batch0, 'pcd1': xyz_batch1, 'sinput0_C': coords_batch0, 'sinput0_F': feats_batch0.float(), 'sinput1_C': coords_batch1, 'sinput1_F': feats_batch1.float(), 'correspondences': correspondance_in_batch, # 'matching_inds': matching_inds_batch, # 'pos0' : pos0_coord_in_batch, # 'pos1' : pos1_coord_in_batch, 'T_gt': trans_batch, 'len_batch': len_batch, 'coords0': coords0_downsampled, 'coords1': coords1_downsampled, 'centroid': centroid_in_batch, 'max': max_in_batch, 'neighbor0': neighbor0_in_batch, 'neighbor1': neighbor1_in_batch, 'num_neighbor0': num_neighbor0_in_batch, 'num_neighbor1': num_neighbor1_in_batch, #'neg_inds': neg_ind_in_batch } # Rotation matrix along axis with angle theta def M(axis, theta): return expm(np.cross(np.eye(3), axis / norm(axis) * theta)) def sample_random_trans(pcd, randg, rotation_range=360): T = np.eye(4) R = M(randg.rand(3) - 0.5, rotation_range * np.pi / 180.0 * (randg.rand(1) - 0.5)) T[:3, :3] = R T[:3, 3] = R.dot(-np.mean(pcd, axis=0)) return T class PairDataset(torch.utils.data.Dataset): AUGMENT = None def __init__(self, phase, transform=None, random_rotation=True, random_scale=True, manual_seed=False, config=None): self.phase = phase self.files = [] self.data_objects = [] self.transform = transform self.voxel_size = config.voxel_size self.matching_search_voxel_size = \ config.voxel_size * config.positive_pair_search_voxel_size_multiplier self.random_scale = random_scale self.min_scale = config.min_scale self.max_scale = config.max_scale self.random_rotation = random_rotation self.rotation_range = config.rotation_range self.randg = np.random.RandomState() #self.get_feature = config.get_feature if manual_seed: self.reset_seed() def reset_seed(self, seed=0): logging.info(f"Resetting the data loader seed to {seed}") self.randg.seed(seed) def apply_transform(self, pts, trans): R = trans[:3, :3] T = trans[:3, 3] pts = pts @ R.T + T return pts def __len__(self): return len(self.files) class IndoorPairDataset(PairDataset): OVERLAP_RATIO = None AUGMENT = None def __init__(self, phase, transform=None, random_rotation=True, random_scale=True, manual_seed=False, config=None): PairDataset.__init__(self, phase, transform, random_rotation, random_scale, manual_seed, config) self.root = root = config.threed_match_dir self.get_feature = config.get_feature self.sample_num = config.sample_num logging.info(f"Loading the subset {phase} from {root}") subset_names = open(self.DATA_FILES[phase]).read().split() for name in subset_names: fname = name + "*%.2f.txt" % self.OVERLAP_RATIO fnames_txt = glob.glob(root + "/" + fname) assert len(fnames_txt) > 0, f"Make sure that the path {root} has data {fname}" for fname_txt in fnames_txt: with open(fname_txt) as f: content = f.readlines() fnames = [x.strip().split() for x in content] for fname in fnames: self.files.append([fname[0], fname[1]]) def __getitem__(self, idx): file0 = os.path.join(self.root, self.files[idx][0]) file1 = os.path.join(self.root, self.files[idx][1]) abs_dir0 = os.path.splitext(file0)[0] abs_dir1 = os.path.splitext(file1)[0] ntpath.basename(self.root) featname0 = self.root + 'features/' + ntpath.split(abs_dir0)[1] + '.npy' featname1 = self.root + 'features/' + ntpath.split(abs_dir1)[1] + '.npy' data0 = np.load(file0,allow_pickle=True) data1 = np.load(file1,allow_pickle=True) xyz0 = data0["pcd"] xyz1 = data1["pcd"] color0 = data0["color"] color1 = data1["color"] matching_search_voxel_size = self.matching_search_voxel_size if self.random_scale and random.random() < 0.95: scale = self.min_scale + \ (self.max_scale - self.min_scale) * random.random() matching_search_voxel_size *= scale xyz0 = scale * xyz0 xyz1 = scale * xyz1 if self.random_rotation: T0 = sample_random_trans(xyz0, self.randg, self.rotation_range) T1 = sample_random_trans(xyz1, self.randg, self.rotation_range) trans = T1 @ np.linalg.inv(T0) xyz0 = self.apply_transform(xyz0, T0) xyz1 = self.apply_transform(xyz1, T1) else: trans = np.identity(4) # Voxelization sel0 = ME.utils.sparse_quantize(xyz0 / self.voxel_size, return_index=True) sel1 = ME.utils.sparse_quantize(xyz1 / self.voxel_size, return_index=True) # Make point clouds using voxelized points #print("before:", xyz0.shape) pcd0 = make_open3d_point_cloud(xyz0) pcd1 = make_open3d_point_cloud(xyz1) # Select features and points using the returned voxelized indices pcd0.colors = o3d.utility.Vector3dVector(color0[sel0]) pcd1.colors = o3d.utility.Vector3dVector(color1[sel1]) pcd0.points = o3d.utility.Vector3dVector(np.array(pcd0.points)[sel0]) pcd1.points = o3d.utility.Vector3dVector(np.array(pcd1.points)[sel1]) # Get matches matches = get_matching_indices(pcd0, pcd1, trans, matching_search_voxel_size) # Get neighborhoods of pcd0 and pcd1 neighbor0_mask,num_neighbor0 = get_neighbor_indices(pcd0, 0.025*2.5) neighbor1_mask,num_neighbor1 = get_neighbor_indices(pcd1, 0.025*2.5) #print("pcd1 points shape:",np.shape(pcd1.points)) #neg_inds = get_hardest_neigative_indices(pcd1,0.125) #print("neg_inds shape:",neg_inds.shape) #num_neighbor0 = np.count_nonzero(neighbor0_mask != len(pcd0.points),axis=1) #num_neighbor1 = np.count_nonzero(neighbor1_mask != len(pcd1.points),axis=1) #print(num_neighbor0.shape) #print(matches[0:100,:]) # Get features npts0 = len(pcd0.colors) npts1 = len(pcd1.colors) #print("pcd0 color dim", np.shape(pcd0.colors)) #print("pcd1 color dim", np.shape(pcd1.colors)) #print("pcd0 color len:",npts0) #print("pcd1 color len:",npts1) feats_train0, feats_train1 = [], [] feats_train0.append(np.ones((npts0, 1))) feats_train1.append(np.ones((npts1, 1))) feats0 = np.hstack(feats_train0) feats1 = np.hstack(feats_train1) # Get coords xyz0 = np.array(pcd0.points) xyz1 = np.array(pcd1.points) #print("after:",xyz0.shape) coords0 = np.floor(xyz0 / self.voxel_size) coords1 = np.floor(xyz1 / self.voxel_size) #print("Max in pcd0 coord:",np.max(coords0,axis=0)) #print("Min in pcd0 coord:",np.min(coords0,axis=0)) #print("Max in pcd1 coord:",np.max(coords1,axis=0)) #print("Min in pcd1 coord:",np.min(coords1,axis=0)) if self.transform: coords0, feats0 = self.transform(coords0, feats0) coords1, feats1 = self.transform(coords1, feats1) if self.get_feature == True: feats0 = np.load(featname0, allow_pickle=True) feats1 = np.load(featname1, allow_pickle=True) feats0 = feats0[sel0] feats1 = feats1[sel1] feats0 = normalize(feats0) feats1 = normalize(feats1) #print("coords shape:",coords0.shape) #print("feature shape:", feats0.shape) if self.sample_num > min(npts0,npts1): sample_num = min(npts0,npts1) #print(sample_num) else: sample_num = self.sample_num return (xyz0, xyz1, coords0, coords1, feats0, feats1, matches, trans, sample_num, neighbor0_mask, neighbor1_mask,num_neighbor0,num_neighbor1) class KITTIPairDataset(PairDataset): AUGMENT = None DATA_FILES = { 'train': './config/train_kitti.txt', 'val': './config/val_kitti.txt', 'test': './config/test_kitti.txt' } TEST_RANDOM_ROTATION = False IS_ODOMETRY = True def __init__(self, phase, transform=None, random_rotation=True, random_scale=True, manual_seed=False, config=None): # For evaluation, use the odometry dataset training following the 3DFeat eval method if self.IS_ODOMETRY: self.root = root = config.kitti_root + '/dataset' random_rotation = self.TEST_RANDOM_ROTATION else: self.date = config.kitti_date self.root = root = os.path.join(config.kitti_root, self.date) self.icp_path = os.path.join(config.kitti_root, 'icp') self.get_feature = config.get_feature pathlib.Path(self.icp_path).mkdir(parents=True, exist_ok=True) PairDataset.__init__(self, phase, transform, random_rotation, random_scale, manual_seed, config) logging.info(f"Loading the subset {phase} from {root}") # Use the kitti root self.max_time_diff = max_time_diff = config.kitti_max_time_diff subset_names = open(self.DATA_FILES[phase]).read().split() for dirname in subset_names: drive_id = int(dirname) inames = self.get_all_scan_ids(drive_id) for start_time in inames: for time_diff in range(2, max_time_diff): pair_time = time_diff + start_time if pair_time in inames: self.files.append((drive_id, start_time, pair_time)) def get_all_scan_ids(self, drive_id): if self.IS_ODOMETRY: fnames = glob.glob(self.root + '/sequences/%02d/velodyne/*.bin' % drive_id) else: fnames = glob.glob(self.root + '/' + self.date + '_drive_%04d_sync/velodyne_points/data/*.bin' % drive_id) assert len( fnames) > 0, f"Make sure that the path {self.root} has drive id: {drive_id}" inames = [int(os.path.split(fname)[-1][:-4]) for fname in fnames] return inames @property def velo2cam(self): try: velo2cam = self._velo2cam except AttributeError: R = np.array([ 7.533745e-03, -9.999714e-01, -6.166020e-04, 1.480249e-02, 7.280733e-04, -9.998902e-01, 9.998621e-01, 7.523790e-03, 1.480755e-02 ]).reshape(3, 3) T = np.array([-4.069766e-03, -7.631618e-02, -2.717806e-01]).reshape(3, 1) velo2cam = np.hstack([R, T]) self._velo2cam = np.vstack((velo2cam, [0, 0, 0, 1])).T return self._velo2cam def get_video_odometry(self, drive, indices=None, ext='.txt', return_all=False): if self.IS_ODOMETRY: data_path = self.root + '/poses/%02d.txt' % drive #print(data_path) if data_path not in kitti_cache: kitti_cache[data_path] = np.genfromtxt(data_path) if return_all: return kitti_cache[data_path] else: return kitti_cache[data_path][indices] else: data_path = self.root + '/' + self.date + '_drive_%04d_sync/oxts/data' % drive odometry = [] if indices is None: fnames = glob.glob(self.root + '/' + self.date + '_drive_%04d_sync/velodyne_points/data/*.bin' % drive) indices = sorted([int(os.path.split(fname)[-1][:-4]) for fname in fnames]) for index in indices: filename = os.path.join(data_path, '%010d%s' % (index, ext)) if filename not in kitti_cache: kitti_cache[filename] = np.genfromtxt(filename) odometry.append(kitti_cache[filename]) odometry = np.array(odometry) return odometry def odometry_to_positions(self, odometry): if self.IS_ODOMETRY: T_w_cam0 = odometry.reshape(3, 4) T_w_cam0 = np.vstack((T_w_cam0, [0, 0, 0, 1])) return T_w_cam0 else: lat, lon, alt, roll, pitch, yaw = odometry.T[:6] R = 6378137 # Earth's radius in metres # convert to metres lat, lon = np.deg2rad(lat), np.deg2rad(lon) mx = R * lon * np.cos(lat) my = R * lat times = odometry.T[-1] return np.vstack([mx, my, alt, roll, pitch, yaw, times]).T def rot3d(self, axis, angle): ei = np.ones(3, dtype='bool') ei[axis] = 0 i = np.nonzero(ei)[0] m = np.eye(3) c, s = np.cos(angle), np.sin(angle) m[i[0], i[0]] = c m[i[0], i[1]] = -s m[i[1], i[0]] = s m[i[1], i[1]] = c return m def pos_transform(self, pos): x, y, z, rx, ry, rz, _ = pos[0] RT = np.eye(4) RT[:3, :3] = np.dot(np.dot(self.rot3d(0, rx), self.rot3d(1, ry)), self.rot3d(2, rz)) RT[:3, 3] = [x, y, z] return RT def get_position_transform(self, pos0, pos1, invert=False): T0 = self.pos_transform(pos0) T1 = self.pos_transform(pos1) return (np.dot(T1, np.linalg.inv(T0)).T if not invert else np.dot( np.linalg.inv(T1), T0).T) def _get_velodyne_fn(self, drive, t): if self.IS_ODOMETRY: fname = self.root + '/sequences/%02d/velodyne/%06d.bin' % (drive, t) else: fname = self.root + \ '/' + self.date + '_drive_%04d_sync/velodyne_points/data/%010d.bin' % ( drive, t) return fname def _get_feature_fn(self, drive, t): if self.IS_ODOMETRY: fname = self.root + '/sequences/%02d/features/%06d.npy' % (drive, t) else: fname = self.root + \ '/' + self.date + '_drive_%04d_sync/velodyne_points/data/%010d.bin' % ( drive, t) return fname def __getitem__(self, idx): drive = self.files[idx][0] t0, t1 = self.files[idx][1], self.files[idx][2] all_odometry = self.get_video_odometry(drive, [t0, t1]) positions = [self.odometry_to_positions(odometry) for odometry in all_odometry] fname0 = self._get_velodyne_fn(drive, t0) fname1 = self._get_velodyne_fn(drive, t1) if self.get_feature == True: featname0 = self._get_feature_fn(drive,t0) featname1 = self._get_feature_fn(drive,t1) # XYZ and reflectance xyzr0 = np.fromfile(fname0, dtype=np.float32).reshape(-1, 4) xyzr1 = np.fromfile(fname1, dtype=np.float32).reshape(-1, 4) xyz0 = xyzr0[:, :3] xyz1 = xyzr1[:, :3] key = '%d_%d_%d' % (drive, t0, t1) filename = self.icp_path + '/' + key + '.npy' if key not in kitti_icp_cache: if not os.path.exists(filename): # work on the downsampled xyzs, 0.05m == 5cm sel0 = ME.utils.sparse_quantize(xyz0 / 0.05, return_index=True) sel1 = ME.utils.sparse_quantize(xyz1 / 0.05, return_index=True) M = (self.velo2cam @ positions[0].T @ np.linalg.inv(positions[1].T) @ np.linalg.inv(self.velo2cam)).T xyz0_t = self.apply_transform(xyz0[sel0], M) pcd0 = make_open3d_point_cloud(xyz0_t) pcd1 = make_open3d_point_cloud(xyz1[sel1]) reg = o3d.registration.registration_icp( pcd0, pcd1, 0.2, np.eye(4), o3d.registration.TransformationEstimationPointToPoint(), o3d.registration.ICPConvergenceCriteria(max_iteration=200)) pcd0.transform(reg.transformation) # pcd0.transform(M2) or self.apply_transform(xyz0, M2) M2 = M @ reg.transformation # o3d.draw_geometries([pcd0, pcd1]) # write to a file np.save(filename, M2) else: M2 = np.load(filename,allow_pickle=True) kitti_icp_cache[key] = M2 else: M2 = kitti_icp_cache[key] if self.random_rotation: T0 = sample_random_trans(xyz0, self.randg, np.pi / 4) T1 = sample_random_trans(xyz1, self.randg, np.pi / 4) trans = T1 @ M2 @ np.linalg.inv(T0) xyz0 = self.apply_transform(xyz0, T0) xyz1 = self.apply_transform(xyz1, T1) else: trans = M2 matching_search_voxel_size = self.matching_search_voxel_size if self.random_scale and random.random() < 0.95: scale = self.min_scale + \ (self.max_scale - self.min_scale) * random.random() matching_search_voxel_size *= scale xyz0 = scale * xyz0 xyz1 = scale * xyz1 # Voxelization xyz0_th = torch.from_numpy(xyz0) xyz1_th = torch.from_numpy(xyz1) sel0 = ME.utils.sparse_quantize(xyz0_th / self.voxel_size, return_index=True) sel1 = ME.utils.sparse_quantize(xyz1_th / self.voxel_size, return_index=True) # Make point clouds using voxelized points pcd0 = make_open3d_point_cloud(xyz0[sel0]) pcd1 = make_open3d_point_cloud(xyz1[sel1]) # Get matches matches = get_matching_indices(pcd0, pcd1, trans, matching_search_voxel_size) if len(matches) < 1000: raise ValueError(f"{drive}, {t0}, {t1}") # Get features npts0 = len(sel0) npts1 = len(sel1) feats_train0, feats_train1 = [], [] unique_xyz0_th = xyz0_th[sel0] unique_xyz1_th = xyz1_th[sel1] feats_train0.append(torch.ones((npts0, 1))) feats_train1.append(torch.ones((npts1, 1))) feats0 = torch.cat(feats_train0, 1) feats1 = torch.cat(feats_train1, 1) coords0 = torch.floor(unique_xyz0_th / self.voxel_size) coords1 = torch.floor(unique_xyz1_th / self.voxel_size) if self.transform: coords0, feats0 = self.transform(coords0, feats0) coords1, feats1 = self.transform(coords1, feats1) if self.get_feature == True: feats0 = np.load(featname0, allow_pickle=True) feats1 = np.load(featname1, allow_pickle=True) feats0 = feats0[sel0] feats1 = feats1[sel1] feats0 = normalize(feats0) feats1 = normalize(feats1) return (unique_xyz0_th.float(), unique_xyz1_th.float(), coords0.int(), coords1.int(), feats0.float(), feats1.float(), matches, trans) class KITTINMPairDataset(KITTIPairDataset): r""" Generate KITTI pairs within N meter distance """ MIN_DIST = 10 def __init__(self, phase, transform=None, random_rotation=True, random_scale=True, manual_seed=False, config=None): if self.IS_ODOMETRY: self.root = root = os.path.join(config.kitti_root, 'dataset') random_rotation = self.TEST_RANDOM_ROTATION else: self.date = config.kitti_date self.root = root = os.path.join(config.kitti_root, self.date) self.icp_path = os.path.join(config.kitti_root, 'icp') self.get_feature = config.get_feature pathlib.Path(self.icp_path).mkdir(parents=True, exist_ok=True) PairDataset.__init__(self, phase, transform, random_rotation, random_scale, manual_seed, config) logging.info(f"Loading the subset {phase} from {root}") subset_names = open(self.DATA_FILES[phase]).read().split() if self.IS_ODOMETRY: for dirname in subset_names: drive_id = int(dirname) fnames = glob.glob(root + '/sequences/%02d/velodyne/*.bin' % drive_id) #print(fnames) assert len(fnames) > 0, f"Make sure that the path {root} has data {dirname}" inames = sorted([int(os.path.split(fname)[-1][:-4]) for fname in fnames]) #print(inames) all_odo = self.get_video_odometry(drive_id, return_all=True) all_pos = np.array([self.odometry_to_positions(odo) for odo in all_odo]) Ts = all_pos[:, :3, 3] pdist = (Ts.reshape(1, -1, 3) - Ts.reshape(-1, 1, 3))**2 pdist = np.sqrt(pdist.sum(-1)) valid_pairs = pdist > self.MIN_DIST #print(np.shape(valid_pairs)) curr_time = inames[0] while curr_time in inames: # Find the min index #print(curr_time) next_time = np.where(valid_pairs[curr_time][curr_time:curr_time + 100])[0] if len(next_time) == 0: curr_time += 1 else: # Follow https://github.com/yewzijian/3DFeatNet/blob/master/scripts_data_processing/kitti/process_kitti_data.m#L44 next_time = next_time[0] + curr_time - 1 if next_time in inames: #print("Appending Files") self.files.append((drive_id, curr_time, next_time)) curr_time = next_time + 1 else: for dirname in subset_names: drive_id = int(dirname) fnames = glob.glob(root + '/' + self.date + '_drive_%04d_sync/velodyne_points/data/*.bin' % drive_id) assert len(fnames) > 0, f"Make sure that the path {root} has data {dirname}" inames = sorted([int(os.path.split(fname)[-1][:-4]) for fname in fnames]) all_odo = self.get_video_odometry(drive_id, return_all=True) all_pos = np.array([self.odometry_to_positions(odo) for odo in all_odo]) Ts = all_pos[:, 0, :3] pdist = (Ts.reshape(1, -1, 3) - Ts.reshape(-1, 1, 3))**2 pdist = np.sqrt(pdist.sum(-1)) for start_time in inames: pair_time = np.where( pdist[start_time][start_time:start_time + 100] > self.MIN_DIST)[0] if len(pair_time) == 0: continue else: pair_time = pair_time[0] + start_time if pair_time in inames: self.files.append((drive_id, start_time, pair_time)) if self.IS_ODOMETRY: # Remove problematic sequence for item in [ (8, 15, 58), ]: print("items are ",item) if item in self.files: self.files.pop(self.files.index(item)) ######################################################### # # KAIST_DATASET_Left # # added config: kaist_root,kaist_date,kaist_max_time_diff # train_kaist.txt,val_kaist.txt,test_kaist.txt # ######################################################### class KAISTLPairDataset(PairDataset): AUGMENT = None DATA_FILES = { 'train': './config/train_kaist.txt', 'val': './config/val_kaist.txt', 'test': './config/test_kaist.txt' } TEST_RANDOM_ROTATION = False IS_ODOMETRY = True def __init__(self, phase, transform=None, random_rotation=True, random_scale=True, manual_seed=False, config=None): # For evaluation, use the odometry dataset training following the 3DFeat eval method if self.IS_ODOMETRY: self.root = root = config.kaist_root random_rotation = self.TEST_RANDOM_ROTATION else: self.date = config.kaist_date self.root = root = os.path.join(config.kaist_root, self.date) self.icp_path = os.path.join(config.kaist_root, 'icp') pathlib.Path(self.icp_path).mkdir(parents=True, exist_ok=True) PairDataset.__init__(self, phase, transform, random_rotation, random_scale, manual_seed, config) logging.info(f"Loading the subset {phase} from {root}") # Use the kitti root self.max_time_diff = max_time_diff = config.kaist_max_time_diff subset_names = open(self.DATA_FILES[phase]).read().split() for dirname in subset_names: drive_id = int(dirname) inames = self.get_all_scan_ids(drive_id) for start_time in inames: for time_diff in range(2, max_time_diff): pair_time = time_diff + start_time if pair_time in inames: self.files.append((drive_id, start_time, pair_time)) def get_all_scan_ids(self, drive_id): load_path = self.root + '/%02d/' % drive_id + 'left_valid.csv' valid_time = np.genfromtxt(load_path,delimiter=',') fnames = [] for time in valid_time: if self.IS_ODOMETRY: fnames.extend(glob.glob(self.root + '/%02d/VLP_left/' % drive_id + '%06d.bin' % time)) else: fnames.extend(glob.glob(self.root + '/' + self.date + '_drive_%04d_sync/velodyne_points/data/*.bin' % drive_id)) assert len( fnames) > 0, f"Make sure that the path {self.root} has drive id: {drive_id}" inames = [int(os.path.split(fname)[-1][:-4]) for fname in fnames] return inames @property def velo2cam(self): try: velo2cam = self._velo2cam except AttributeError: R = np.array([ 7.533745e-03, -9.999714e-01, -6.166020e-04, 1.480249e-02, 7.280733e-04, -9.998902e-01, 9.998621e-01, 7.523790e-03, 1.480755e-02 ]).reshape(3, 3) T = np.array([-4.069766e-03, -7.631618e-02, -2.717806e-01]).reshape(3, 1) velo2cam = np.hstack([R, T]) self._velo2cam = np.vstack((velo2cam, [0, 0, 0, 1])).T return self._velo2cam def get_video_odometry(self, drive, indices=None, ext='.txt', return_all=False): if self.IS_ODOMETRY: #logging.info(f"Drive id is {drive}") data_path = self.root + '/%02d/VLP_left_pose.csv' % drive #print(data_path) if data_path not in kaist_cache: kaist_cache[data_path] = np.genfromtxt(data_path,delimiter=',') #print(np.shape(kaist_cache[data_path])) if return_all: return kaist_cache[data_path] else: return kaist_cache[data_path][indices] else: data_path = self.root + '/' + self.date + '_drive_%04d_sync/oxts/data' % drive odometry = [] if indices is None: fnames = glob.glob(self.root + '/' + self.date + '_drive_%04d_sync/velodyne_points/data/*.bin' % drive) indices = sorted([int(os.path.split(fname)[-1][:-4]) for fname in fnames]) for index in indices: filename = os.path.join(data_path, '%010d%s' % (index, ext)) if filename not in kaist_cache: kaist_cache[filename] = np.genfromtxt(filename) odometry.append(kaist_cache[filename]) odometry = np.array(odometry) return odometry def odometry_to_positions(self, odometry): if self.IS_ODOMETRY: T_w_cam0 = odometry.reshape(3, 4) T_w_cam0 = np.vstack((T_w_cam0, [0, 0, 0, 1])) return T_w_cam0 else: lat, lon, alt, roll, pitch, yaw = odometry.T[:6] R = 6378137 # Earth's radius in metres # convert to metres lat, lon = np.deg2rad(lat), np.deg2rad(lon) mx = R * lon * np.cos(lat) my = R * lat times = odometry.T[-1] return np.vstack([mx, my, alt, roll, pitch, yaw, times]).T def rot3d(self, axis, angle): ei = np.ones(3, dtype='bool') ei[axis] = 0 i = np.nonzero(ei)[0] m = np.eye(3) c, s = np.cos(angle), np.sin(angle) m[i[0], i[0]] = c m[i[0], i[1]] = -s m[i[1], i[0]] = s m[i[1], i[1]] = c return m def pos_transform(self, pos): x, y, z, rx, ry, rz, _ = pos[0] RT = np.eye(4) RT[:3, :3] = np.dot(np.dot(self.rot3d(0, rx), self.rot3d(1, ry)), self.rot3d(2, rz)) RT[:3, 3] = [x, y, z] return RT def get_position_transform(self, pos0, pos1, invert=False): T0 = self.pos_transform(pos0) T1 = self.pos_transform(pos1) return (np.dot(T1, np.linalg.inv(T0)).T if not invert else np.dot( np.linalg.inv(T1), T0).T) def _get_velodyne_fn(self, drive, t): if self.IS_ODOMETRY: fname = self.root + '/%02d/VLP_left/%06d.bin' % (drive, t) else: fname = self.root + \ '/' + self.date + '_drive_%04d_sync/velodyne_points/data/%010d.bin' % ( drive, t) return fname def __getitem__(self, idx): drive = self.files[idx][0] inames = self.get_all_scan_ids(drive) t0, t1 = self.files[idx][1], self.files[idx][2] t0_odo,t1_odo = self.files[idx][1] - inames[0],self.files[idx][2] - inames[0] all_odometry = self.get_video_odometry(drive, [t0_odo, t1_odo]) positions = [self.odometry_to_positions(odometry) for odometry in all_odometry] fname0 = self._get_velodyne_fn(drive, t0) fname1 = self._get_velodyne_fn(drive, t1) # XYZ and reflectance xyzr0 = np.fromfile(fname0, dtype=np.float32).reshape(-1, 4) xyzr1 = np.fromfile(fname1, dtype=np.float32).reshape(-1, 4) xyz0 = xyzr0[:, :3] xyz1 = xyzr1[:, :3] key = '%d_%d_%d' % (drive, t0, t1) filename = self.icp_path + '/' + key + '.npy' if key not in kaist_icp_cache: if not os.path.exists(filename): # work on the downsampled xyzs, 0.05m == 5cm sel0 = ME.utils.sparse_quantize(xyz0 / 0.05, return_index=True) sel1 = ME.utils.sparse_quantize(xyz1 / 0.05, return_index=True) M = (self.velo2cam @ positions[0].T @ np.linalg.inv(positions[1].T) @ np.linalg.inv(self.velo2cam)).T xyz0_t = self.apply_transform(xyz0[sel0], M) pcd0 = make_open3d_point_cloud(xyz0_t) pcd1 = make_open3d_point_cloud(xyz1[sel1]) reg = o3d.registration.registration_icp( pcd0, pcd1, 0.2, np.eye(4), o3d.registration.TransformationEstimationPointToPoint(), o3d.registration.ICPConvergenceCriteria(max_iteration=200)) pcd0.transform(reg.transformation) # pcd0.transform(M2) or self.apply_transform(xyz0, M2) M2 = M @ reg.transformation # o3d.draw_geometries([pcd0, pcd1]) # write to a file np.save(filename, M2) else: M2 = np.load(filename,allow_pickle=True) kaist_icp_cache[key] = M2 else: M2 = kaist_icp_cache[key] if self.random_rotation: T0 = sample_random_trans(xyz0, self.randg, np.pi / 4) T1 = sample_random_trans(xyz1, self.randg, np.pi / 4) trans = T1 @ M2 @ np.linalg.inv(T0) xyz0 = self.apply_transform(xyz0, T0) xyz1 = self.apply_transform(xyz1, T1) else: trans = M2 matching_search_voxel_size = self.matching_search_voxel_size if self.random_scale and random.random() < 0.95: scale = self.min_scale + \ (self.max_scale - self.min_scale) * random.random() matching_search_voxel_size *= scale xyz0 = scale * xyz0 xyz1 = scale * xyz1 # Voxelization xyz0_th = torch.from_numpy(xyz0) xyz1_th = torch.from_numpy(xyz1) sel0 = ME.utils.sparse_quantize(xyz0_th / self.voxel_size, return_index=True) sel1 = ME.utils.sparse_quantize(xyz1_th / self.voxel_size, return_index=True) # Make point clouds using voxelized points pcd0 = make_open3d_point_cloud(xyz0[sel0]) pcd1 = make_open3d_point_cloud(xyz1[sel1]) # Get matches matches = get_matching_indices(pcd0, pcd1, trans, matching_search_voxel_size) #if len(matches) < 1000: #raise ValueError(f"{drive}, {t0}, {t1}") #return # Get features npts0 = len(sel0) npts1 = len(sel1) feats_train0, feats_train1 = [], [] unique_xyz0_th = xyz0_th[sel0] unique_xyz1_th = xyz1_th[sel1] feats_train0.append(torch.ones((npts0, 1))) feats_train1.append(torch.ones((npts1, 1))) feats0 = torch.cat(feats_train0, 1) feats1 = torch.cat(feats_train1, 1) coords0 = torch.floor(unique_xyz0_th / self.voxel_size) coords1 = torch.floor(unique_xyz1_th / self.voxel_size) if self.transform: coords0, feats0 = self.transform(coords0, feats0) coords1, feats1 = self.transform(coords1, feats1) return (unique_xyz0_th.float(), unique_xyz1_th.float(), coords0.int(), coords1.int(), feats0.float(), feats1.float(), matches, trans) class KAISTLNMPairDataset(KAISTLPairDataset): r""" Generate KITTI pairs within N meter distance """ MIN_DIST = 10 def __init__(self, phase, transform=None, random_rotation=True, random_scale=True, manual_seed=False, config=None): if self.IS_ODOMETRY: self.root = root = config.kaist_root random_rotation = self.TEST_RANDOM_ROTATION else: self.date = config.kaist_date self.root = root = os.path.join(config.kaist_root, self.date) self.icp_path = os.path.join(config.kaist_root, 'icp') pathlib.Path(self.icp_path).mkdir(parents=True, exist_ok=True) PairDataset.__init__(self, phase, transform, random_rotation, random_scale, manual_seed, config) logging.info(f"Loading the subset {phase} from {root}") subset_names = open(self.DATA_FILES[phase]).read().split() if self.IS_ODOMETRY: for dirname in subset_names: drive_id = int(dirname) logging.info(f"Processing Sequence {drive_id}") self.kaist_interpolate(left=True,data_root=root,drive_id=drive_id) load_path = root + '/%02d/' % drive_id + 'left_valid.csv' valid_time = np.genfromtxt(load_path,delimiter=',') fnames = [] for time in valid_time: fnames.extend(glob.glob(self.root + '/%02d/VLP_left/%06d.bin' % (drive_id, time))) #print(fnames) assert len(fnames) > 0, f"Make sure that the path {root} has data {dirname}" inames = sorted([int(os.path.split(fname)[-1][:-4]) for fname in fnames]) #print(inames) all_odo = self.get_video_odometry(drive_id, return_all=True) #print(all_odo.shape) all_pos = np.array([self.odometry_to_positions(odo) for odo in all_odo]) logging.info(f"Position Acquisition Done") Ts = all_pos[:, :3, 3] pdist = (Ts.reshape(1, -1, 3) - Ts.reshape(-1, 1, 3))**2 pdist = np.sqrt(pdist.sum(-1)) valid_pairs = pdist > self.MIN_DIST #print(np.shape(valid_pairs)) curr_time = inames[0] loop_names = np.asarray(inames) - inames[0] while curr_time in loop_names: #print(curr_time) # Find the min index next_time = np.where(valid_pairs[curr_time][curr_time:curr_time + 100])[0] #print(next_time) if len(next_time) == 0: curr_time += 1 else: # Follow https://github.com/yewzijian/3DFeatNet/blob/master/scripts_data_processing/kitti/process_kitti_data.m#L44 next_time = next_time[0] + curr_time - 1 if next_time in inames: if self.valid_pair(drive_id,curr_time + inames[0],next_time + inames[0], inames[0]): #print("Appending Files") self.files.append((drive_id, curr_time + inames[0], next_time + inames[0])) #logging.info(f"current time_stamp {curr_time}") curr_time = next_time + 1 else: for dirname in subset_names: drive_id = int(dirname) fnames = glob.glob(root + '/' + self.date + '_drive_%04d_sync/velodyne_points/data/*.bin' % drive_id) assert len(fnames) > 0, f"Make sure that the path {root} has data {dirname}" inames = sorted([int(os.path.split(fname)[-1][:-4]) for fname in fnames]) all_odo = self.get_video_odometry(drive_id, return_all=True) all_pos = np.array([self.odometry_to_positions(odo) for odo in all_odo]) Ts = all_pos[:, 0, :3] pdist = (Ts.reshape(1, -1, 3) - Ts.reshape(-1, 1, 3))**2 pdist = np.sqrt(pdist.sum(-1)) for start_time in inames: pair_time = np.where( pdist[start_time][start_time:start_time + 100] > self.MIN_DIST)[0] if len(pair_time) == 0: continue else: pair_time = pair_time[0] + start_time if pair_time in inames: self.files.append((drive_id, start_time, pair_time)) logging.info(f"length of files found {len(self.files)}") def kaist_interpolate(self,left=None,data_root=None,drive_id=None): pose_path = data_root + '/' + '%02d/' % drive_id + 'global_pose.csv' pose = np.genfromtxt(pose_path,delimiter=',') if left == True: stamp_path = data_root + '/' + '%02d/' % drive_id + 'VLP_left_stamp.csv' write_VLP_path = data_root + '/' + '%02d/' % drive_id + 'VLP_left_pose.csv' write_valid_path = data_root + '/' + '%02d/' % drive_id + 'left_valid.csv' time_stamp = np.genfromtxt(stamp_path,delimiter=',') else: stamp_path = data_root + '/' + '%02d/' % drive_id + 'VLP_right_stamp.csv' write_VLP_path = data_root + '/' + '%02d/' % drive_id + 'VLP_right_pose.csv' write_valid_path = data_root + '/' + '%02d/' % drive_id + 'right_valid.csv' time_stamp = np.genfromtxt(stamp_path,delimiter=',') time = pose[:,0] pose = pose[:,1:13] pose = pose.reshape(-1,3,4) rotate = pose[:,:,0:3] translation = pose[:,:,3] valid_start = (time_stamp > np.min(time)).astype(int) valid_end = (time_stamp < np.max(time)).astype(int) valid_idx = np.where(valid_start*valid_end == 1) valid_time = time_stamp[valid_idx] # interpolate translation matrix trans_interpolate = interp1d(time,translation,kind='linear',axis=0) trans = trans_interpolate(valid_time).reshape(valid_time.shape[0],3,1) # interpolate rotation matrix slerp = Slerp(time,R.from_matrix(rotate)) rotate = slerp(valid_time).as_matrix() VLP_pose = np.concatenate((rotate,trans),axis=2).reshape(valid_time.shape[0],12) valid_idx = np.asarray(valid_idx).T np.savetxt(write_VLP_path,VLP_pose,delimiter=',') np.savetxt(write_valid_path,valid_idx,delimiter=',') return def valid_pair(self,drive=None,t0=None,t1=None,offset=None): #logging.info(f"Function called") all_odometry = self.get_video_odometry(drive, [t0-offset, t1-offset]) #print(np.shape(all_odometry)) positions = [self.odometry_to_positions(odometry) for odometry in all_odometry] fname0 = self.root + '/%02d/VLP_left/%06d.bin' % (drive, t0) fname1 = self.root + '/%02d/VLP_left/%06d.bin' % (drive, t1) xyzr0 = np.fromfile(fname0, dtype=np.float32).reshape(-1, 4) xyzr1 = np.fromfile(fname1, dtype=np.float32).reshape(-1, 4) xyz0 = xyzr0[:, :3] xyz1 = xyzr1[:, :3] key = '%d_%d_%d' % (drive, t0, t1) filename = self.icp_path + '/' + key + '.npy' if key not in kitti_icp_cache: if not os.path.exists(filename): # work on the downsampled xyzs, 0.05m == 5cm sel0 = ME.utils.sparse_quantize(xyz0 / 0.05, return_index=True) sel1 = ME.utils.sparse_quantize(xyz1 / 0.05, return_index=True) M = (self.velo2cam @ positions[0].T @ np.linalg.inv(positions[1].T) @ np.linalg.inv(self.velo2cam)).T xyz0_t = self.apply_transform(xyz0[sel0], M) pcd0 = make_open3d_point_cloud(xyz0_t) pcd1 = make_open3d_point_cloud(xyz1[sel1]) reg = o3d.registration.registration_icp( pcd0, pcd1, 0.2, np.eye(4), o3d.registration.TransformationEstimationPointToPoint(), o3d.registration.ICPConvergenceCriteria(max_iteration=200)) pcd0.transform(reg.transformation) # pcd0.transform(M2) or self.apply_transform(xyz0, M2) M2 = M @ reg.transformation # o3d.draw_geometries([pcd0, pcd1]) # write to a file np.save(filename, M2) else: M2 = np.load(filename,allow_pickle=True) kitti_icp_cache[key] = M2 else: M2 = kitti_icp_cache[key] if self.random_rotation: T0 = sample_random_trans(xyz0, self.randg, np.pi / 4) T1 = sample_random_trans(xyz1, self.randg, np.pi / 4) trans = T1 @ M2 @ np.linalg.inv(T0) xyz0 = self.apply_transform(xyz0, T0) xyz1 = self.apply_transform(xyz1, T1) else: trans = M2 matching_search_voxel_size = self.matching_search_voxel_size if self.random_scale and random.random() < 0.95: scale = self.min_scale + \ (self.max_scale - self.min_scale) * random.random() matching_search_voxel_size *= scale xyz0 = scale * xyz0 xyz1 = scale * xyz1 xyz0_th = torch.from_numpy(xyz0) xyz1_th = torch.from_numpy(xyz1) sel0 = ME.utils.sparse_quantize(xyz0_th / self.voxel_size, return_index=True) sel1 = ME.utils.sparse_quantize(xyz1_th / self.voxel_size, return_index=True) # Make point clouds using voxelized points pcd0 = make_open3d_point_cloud(xyz0[sel0]) pcd1 = make_open3d_point_cloud(xyz1[sel1]) # Get matches matches = get_matching_indices(pcd0, pcd1, trans, matching_search_voxel_size) if len(matches) < 1000: return False else: return True #if self.IS_ODOMETRY: # Remove problematic sequence # for item in [ # (8, 15, 58), # ]: # print("items are ",item) # if item in self.files: # self.files.pop(self.files.index(item)) ######################################################### # # KAIST_DATASET_Right # # added config: kaist_root,kaist_date,kaist_max_time_diff # train_kaist.txt,val_kaist.txt,test_kaist.txt # ######################################################### class KAISTRPairDataset(PairDataset): AUGMENT = None DATA_FILES = { 'train': './config/train_kaist.txt', 'val': './config/val_kaist.txt', 'test': './config/test_kaist.txt' } TEST_RANDOM_ROTATION = False IS_ODOMETRY = True def __init__(self, phase, transform=None, random_rotation=True, random_scale=True, manual_seed=False, config=None): # For evaluation, use the odometry dataset training following the 3DFeat eval method if self.IS_ODOMETRY: self.root = root = config.kaist_root random_rotation = self.TEST_RANDOM_ROTATION else: self.date = config.kaist_date self.root = root = os.path.join(config.kaist_root, self.date) self.icp_path = os.path.join(config.kaist_root, 'icp') pathlib.Path(self.icp_path).mkdir(parents=True, exist_ok=True) PairDataset.__init__(self, phase, transform, random_rotation, random_scale, manual_seed, config) logging.info(f"Loading the subset {phase} from {root}") # Use the kitti root self.max_time_diff = max_time_diff = config.kaist_max_time_diff subset_names = open(self.DATA_FILES[phase]).read().split() for dirname in subset_names: drive_id = int(dirname) inames = self.get_all_scan_ids(drive_id) for start_time in inames: for time_diff in range(2, max_time_diff): pair_time = time_diff + start_time if pair_time in inames: self.files.append((drive_id, start_time, pair_time)) def get_all_scan_ids(self, drive_id): load_path = self.root + '/%02d/' % drive_id + 'right_valid.csv' valid_time = np.genfromtxt(load_path,delimiter=',') fnames = [] for time in valid_time: if self.IS_ODOMETRY: fnames.extend(glob.glob(self.root + '/%02d/VLP_right/' % drive_id + '%06d.bin' % time)) else: fnames.extend(glob.glob(self.root + '/' + self.date + '_drive_%04d_sync/velodyne_points/data/*.bin' % drive_id)) assert len( fnames) > 0, f"Make sure that the path {self.root} has drive id: {drive_id}" inames = [int(os.path.split(fname)[-1][:-4]) for fname in fnames] return inames @property def velo2cam(self): try: velo2cam = self._velo2cam except AttributeError: R = np.array([ 7.533745e-03, -9.999714e-01, -6.166020e-04, 1.480249e-02, 7.280733e-04, -9.998902e-01, 9.998621e-01, 7.523790e-03, 1.480755e-02 ]).reshape(3, 3) T = np.array([-4.069766e-03, -7.631618e-02, -2.717806e-01]).reshape(3, 1) velo2cam = np.hstack([R, T]) self._velo2cam = np.vstack((velo2cam, [0, 0, 0, 1])).T return self._velo2cam def get_video_odometry(self, drive, indices=None, ext='.txt', return_all=False): if self.IS_ODOMETRY: data_path = self.root + '/%02d/VLP_right_pose.csv' % drive if data_path not in kaist_cache: kaist_cache[data_path] = np.genfromtxt(data_path,delimiter=',') if return_all: return kaist_cache[data_path] else: return kaist_cache[data_path][indices] else: data_path = self.root + '/' + self.date + '_drive_%04d_sync/oxts/data' % drive odometry = [] if indices is None: fnames = glob.glob(self.root + '/' + self.date + '_drive_%04d_sync/velodyne_points/data/*.bin' % drive) indices = sorted([int(os.path.split(fname)[-1][:-4]) for fname in fnames]) for index in indices: filename = os.path.join(data_path, '%010d%s' % (index, ext)) if filename not in kaist_cache: kaist_cache[filename] = np.genfromtxt(filename) odometry.append(kaist_cache[filename]) odometry = np.array(odometry) return odometry def odometry_to_positions(self, odometry): if self.IS_ODOMETRY: T_w_cam0 = odometry.reshape(3, 4) T_w_cam0 = np.vstack((T_w_cam0, [0, 0, 0, 1])) return T_w_cam0 else: lat, lon, alt, roll, pitch, yaw = odometry.T[:6] R = 6378137 # Earth's radius in metres # convert to metres lat, lon = np.deg2rad(lat), np.deg2rad(lon) mx = R * lon * np.cos(lat) my = R * lat times = odometry.T[-1] return np.vstack([mx, my, alt, roll, pitch, yaw, times]).T def rot3d(self, axis, angle): ei = np.ones(3, dtype='bool') ei[axis] = 0 i = np.nonzero(ei)[0] m = np.eye(3) c, s = np.cos(angle), np.sin(angle) m[i[0], i[0]] = c m[i[0], i[1]] = -s m[i[1], i[0]] = s m[i[1], i[1]] = c return m def pos_transform(self, pos): x, y, z, rx, ry, rz, _ = pos[0] RT = np.eye(4) RT[:3, :3] = np.dot(np.dot(self.rot3d(0, rx), self.rot3d(1, ry)), self.rot3d(2, rz)) RT[:3, 3] = [x, y, z] return RT def get_position_transform(self, pos0, pos1, invert=False): T0 = self.pos_transform(pos0) T1 = self.pos_transform(pos1) return (np.dot(T1, np.linalg.inv(T0)).T if not invert else np.dot( np.linalg.inv(T1), T0).T) def _get_velodyne_fn(self, drive, t): if self.IS_ODOMETRY: fname = self.root + '/%02d/VLP_right/%06d.bin' % (drive, t) else: fname = self.root + \ '/' + self.date + '_drive_%04d_sync/velodyne_points/data/%010d.bin' % ( drive, t) return fname def __getitem__(self, idx): drive = self.files[idx][0] t0, t1 = self.files[idx][1], self.files[idx][2] all_odometry = self.get_video_odometry(drive, [t0, t1]) positions = [self.odometry_to_positions(odometry) for odometry in all_odometry] fname0 = self._get_velodyne_fn(drive, t0) fname1 = self._get_velodyne_fn(drive, t1) # XYZ and reflectance xyzr0 = np.fromfile(fname0, dtype=np.float32).reshape(-1, 4) xyzr1 = np.fromfile(fname1, dtype=np.float32).reshape(-1, 4) xyz0 = xyzr0[:, :3] xyz1 = xyzr1[:, :3] key = '%d_%d_%d' % (drive, t0, t1) filename = self.icp_path + '/' + key + '.npy' if key not in kaist_icp_cache: if not os.path.exists(filename): # work on the downsampled xyzs, 0.05m == 5cm sel0 = ME.utils.sparse_quantize(xyz0 / 0.05, return_index=True) sel1 = ME.utils.sparse_quantize(xyz1 / 0.05, return_index=True) M = (self.velo2cam @ positions[0].T @ np.linalg.inv(positions[1].T) @ np.linalg.inv(self.velo2cam)).T xyz0_t = self.apply_transform(xyz0[sel0], M) pcd0 = make_open3d_point_cloud(xyz0_t) pcd1 = make_open3d_point_cloud(xyz1[sel1]) reg = o3d.registration.registration_icp( pcd0, pcd1, 0.2, np.eye(4), o3d.registration.TransformationEstimationPointToPoint(), o3d.registration.ICPConvergenceCriteria(max_iteration=200)) pcd0.transform(reg.transformation) # pcd0.transform(M2) or self.apply_transform(xyz0, M2) M2 = M @ reg.transformation # o3d.draw_geometries([pcd0, pcd1]) # write to a file np.save(filename, M2) else: M2 = np.load(filename,allow_pickle=True) kaist_icp_cache[key] = M2 else: M2 = kaist_icp_cache[key] if self.random_rotation: T0 = sample_random_trans(xyz0, self.randg, np.pi / 4) T1 = sample_random_trans(xyz1, self.randg, np.pi / 4) trans = T1 @ M2 @ np.linalg.inv(T0) xyz0 = self.apply_transform(xyz0, T0) xyz1 = self.apply_transform(xyz1, T1) else: trans = M2 matching_search_voxel_size = self.matching_search_voxel_size if self.random_scale and random.random() < 0.95: scale = self.min_scale + \ (self.max_scale - self.min_scale) * random.random() matching_search_voxel_size *= scale xyz0 = scale * xyz0 xyz1 = scale * xyz1 # Voxelization xyz0_th = torch.from_numpy(xyz0) xyz1_th = torch.from_numpy(xyz1) sel0 = ME.utils.sparse_quantize(xyz0_th / self.voxel_size, return_index=True) sel1 = ME.utils.sparse_quantize(xyz1_th / self.voxel_size, return_index=True) # Make point clouds using voxelized points pcd0 = make_open3d_point_cloud(xyz0[sel0]) pcd1 = make_open3d_point_cloud(xyz1[sel1]) # Get matches matches = get_matching_indices(pcd0, pcd1, trans, matching_search_voxel_size) if len(matches) < 1000: raise ValueError(f"{drive}, {t0}, {t1}") # Get features npts0 = len(sel0) npts1 = len(sel1) feats_train0, feats_train1 = [], [] unique_xyz0_th = xyz0_th[sel0] unique_xyz1_th = xyz1_th[sel1] feats_train0.append(torch.ones((npts0, 1))) feats_train1.append(torch.ones((npts1, 1))) feats0 = torch.cat(feats_train0, 1) feats1 = torch.cat(feats_train1, 1) coords0 = torch.floor(unique_xyz0_th / self.voxel_size) coords1 = torch.floor(unique_xyz1_th / self.voxel_size) if self.transform: coords0, feats0 = self.transform(coords0, feats0) coords1, feats1 = self.transform(coords1, feats1) return (unique_xyz0_th.float(), unique_xyz1_th.float(), coords0.int(), coords1.int(), feats0.float(), feats1.float(), matches, trans) class KAISTRNMPairDataset(KAISTRPairDataset): r""" Generate KITTI pairs within N meter distance """ MIN_DIST = 10 def __init__(self, phase, transform=None, random_rotation=True, random_scale=True, manual_seed=False, config=None): if self.IS_ODOMETRY: self.root = root = config.kaist_root random_rotation = self.TEST_RANDOM_ROTATION else: self.date = config.kaist_date self.root = root = os.path.join(config.kaist_root, self.date) self.icp_path = os.path.join(config.kaist_root, 'icp') pathlib.Path(self.icp_path).mkdir(parents=True, exist_ok=True) PairDataset.__init__(self, phase, transform, random_rotation, random_scale, manual_seed, config) logging.info(f"Loading the subset {phase} from {root}") subset_names = open(self.DATA_FILES[phase]).read().split() if self.IS_ODOMETRY: for dirname in subset_names: drive_id = int(dirname) #print("Processing sequence ", drive_id) self.kaist_interpolate(left=False,data_root=root,drive_id=drive_id) load_path = root + '/%02d/' % drive_id + 'right_valid.csv' valid_time = np.genfromtxt(load_path,delimiter=',') fnames = [] for time in valid_time: fnames.extend(glob.glob(self.root + '/%02d/VLP_right/' % drive_id + '%06d.bin' % time)) assert len(fnames) > 0, f"Make sure that the path {root} has data {dirname}" inames = sorted([int(os.path.split(fname)[-1][:-4]) for fname in fnames]) #print(inames) all_odo = self.get_video_odometry(drive_id, return_all=True) all_pos = np.array([self.odometry_to_positions(odo) for odo in all_odo]) #print("Odometry and position acquisition done") Ts = all_pos[:, :3, 3] pdist = (Ts.reshape(1, -1, 3) - Ts.reshape(-1, 1, 3))**2 pdist = np.sqrt(pdist.sum(-1)) valid_pairs = pdist > self.MIN_DIST #print("Valid Pairs Generated") curr_time = inames[0] - inames[0] while curr_time in inames: # Find the min index next_time = np.where(valid_pairs[curr_time][curr_time:curr_time + 100])[0] if len(next_time) == 0: curr_time += 1 else: # Follow https://github.com/yewzijian/3DFeatNet/blob/master/scripts_data_processing/kitti/process_kitti_data.m#L44 next_time = next_time[0] + curr_time - 1 if next_time in inames: self.files.append((drive_id, curr_time + inames[0], next_time + inames[0])) curr_time = next_time + 1 else: for dirname in subset_names: drive_id = int(dirname) fnames = glob.glob(root + '/' + self.date + '_drive_%04d_sync/velodyne_points/data/*.bin' % drive_id) assert len(fnames) > 0, f"Make sure that the path {root} has data {dirname}" inames = sorted([int(os.path.split(fname)[-1][:-4]) for fname in fnames]) all_odo = self.get_video_odometry(drive_id, return_all=True) all_pos = np.array([self.odometry_to_positions(odo) for odo in all_odo]) Ts = all_pos[:, 0, :3] pdist = (Ts.reshape(1, -1, 3) - Ts.reshape(-1, 1, 3))**2 pdist = np.sqrt(pdist.sum(-1)) for start_time in inames: pair_time = np.where( pdist[start_time][start_time:start_time + 100] > self.MIN_DIST)[0] if len(pair_time) == 0: continue else: pair_time = pair_time[0] + start_time if pair_time in inames: self.files.append((drive_id, start_time, pair_time)) def kaist_interpolate(self,left=True,data_root=None,drive_id=None): pose_path = data_root + '/' + '%02d/' % drive_id + 'global_pose.csv' pose = np.genfromtxt(pose_path,delimiter=',') if left == True: stamp_path = data_root + '/' + '%02d/' % drive_id + 'VLP_left_stamp.csv' write_VLP_path = data_root + '/' + '%02d/' % drive_id + 'VLP_left_pose.csv' write_valid_path = data_root + '/' + '%02d/' % drive_id + 'left_valid.csv' time_stamp = np.genfromtxt(stamp_path,delimiter=',') else: stamp_path = data_root + '/' + '%02d/' % drive_id + 'VLP_right_stamp.csv' write_VLP_path = data_root + '/' + '%02d/' % drive_id + 'VLP_right_pose.csv' write_valid_path = data_root + '/' + '%02d/' % drive_id + 'right_valid.csv' time_stamp = np.genfromtxt(stamp_path,delimiter=',') time = pose[:,0] pose = pose[:,1:13] pose = pose.reshape(-1,3,4) rotate = pose[:,:,0:3] translation = pose[:,:,3] valid_start = (time_stamp > np.min(time)).astype(int) valid_end = (time_stamp < np.max(time)).astype(int) valid_idx = np.where(valid_start*valid_end == 1) valid_time = time_stamp[valid_idx] # interpolate translation matrix trans_interpolate = interp1d(time,translation,kind='linear',axis=0) trans = trans_interpolate(valid_time).reshape(valid_time.shape[0],3,1) # interpolate rotation matrix slerp = Slerp(time,R.from_matrix(rotate)) rotate = slerp(valid_time).as_matrix() VLP_pose = np.concatenate((rotate,trans),axis=2).reshape(valid_time.shape[0],12) valid_idx = np.asarray(valid_idx).T np.savetxt(write_VLP_path,VLP_pose,delimiter=',') np.savetxt(write_valid_path,valid_idx,delimiter=',') return #if self.IS_ODOMETRY: # Remove problematic sequence # for item in [ # (8, 15, 58), # ]: # print("items are ",item) # if item in self.files: # self.files.pop(self.files.index(item)) class ThreeDMatchPairDataset(IndoorPairDataset): OVERLAP_RATIO = 0.3 DATA_FILES = { 'train': './config/train_3dmatch.txt', 'val': './config/val_3dmatch.txt', 'test': './config/test_3dmatch.txt' } ALL_DATASETS = [ThreeDMatchPairDataset, KITTIPairDataset, KITTINMPairDataset,KAISTLNMPairDataset ,KAISTRNMPairDataset,KAISTLPairDataset,KAISTRPairDataset] dataset_str_mapping = {d.__name__: d for d in ALL_DATASETS} def make_data_loader(config, phase, batch_size, num_threads=0, shuffle=None): assert phase in ['train', 'trainval', 'val', 'test'] if shuffle is None: shuffle = phase != 'test' if config.dataset not in dataset_str_mapping.keys(): logging.error(f'Dataset {config.dataset}, does not exists in ' + ', '.join(dataset_str_mapping.keys())) Dataset = dataset_str_mapping[config.dataset] use_random_scale = False use_random_rotation = False transforms = [] if phase in ['train', 'trainval']: use_random_rotation = config.use_random_rotation use_random_scale = config.use_random_scale transforms += [t.Jitter()] dset = Dataset( phase, transform=t.Compose(transforms), random_scale=use_random_scale, random_rotation=use_random_rotation, config=config) print(len(dset)) loader = torch.utils.data.DataLoader( dset, batch_size=batch_size, shuffle=shuffle, num_workers=num_threads, collate_fn=collate_pair_fn, pin_memory=False, drop_last=True) return loader

35.937646

145

0.637825

8,611

61,669

4.357798

0.062246

0.014177

0.00533

0.01066

0.789074

0.773804

0.753951

0.746063

0.736736

0.734897

0

0.04193

0.22924

61,669

1,715

146

35.958601

0.747539

0.089461

0

0.750397

0

0.057647

0.021968

0

0.008744

1

0.038156

false

0

0.015898

0.00159

0.116852

0.00159

0

null

0

1

0

1

0

null

0

6

25be9a4117a1aa9065662b8826b55e8044a2f1dd

25

py

Python

pytealutils/tealstruct/__init__.py

gmcgoldr/pyteal-utils

3716ff74312d5136df89456e3db711037edccdcb

[ "MIT" ]

1

2021-12-06T21:58:47.000Z

pytealutils/tealstruct/__init__.py

gmcgoldr/pyteal-utils

3716ff74312d5136df89456e3db711037edccdcb

[ "MIT" ]

null

pytealutils/tealstruct/__init__.py

gmcgoldr/pyteal-utils

3716ff74312d5136df89456e3db711037edccdcb

[ "MIT" ]

null

from .tealstruct import *

25

0.8

3

25

6.666667

1

0

0.12

25

1

25

0.909091

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

25def628a3a1f48f661cad2f968c215e7ec06136

175

py

Python

testshop/test_models.py

Iv/django-shop

aa52dce6e9115d3b7a913ffa6027f978260b324c

[ "BSD-3-Clause" ]

null

testshop/test_models.py

Iv/django-shop

aa52dce6e9115d3b7a913ffa6027f978260b324c

[ "BSD-3-Clause" ]

null

testshop/test_models.py

Iv/django-shop

aa52dce6e9115d3b7a913ffa6027f978260b324c

[ "BSD-3-Clause" ]

1

2020-01-10T01:51:07.000Z

from django.test import TestCase class AddressTest(TestCase): def test_can_import(self): pass #from shop.models.defaults.address import Address # noqa

19.444444

65

0.708571

22

175

5.545455

0.727273

0

0.222857

175

8

66

21.875

0.897059

0.314286

0

1

0.25

false

0.25

0.5

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

d30050bcfc5ec36d576ab20f33cfe742c146c290

45

py

Python

QuadSwingUpEnv/QuadSwingUp/envs/__init__.py

shauray8/quadruple_inverted_pendulum

3b5746c534423d39da2582d4bae54ea7ecdacffd

[ "MIT" ]

null

QuadSwingUpEnv/QuadSwingUp/envs/__init__.py

shauray8/quadruple_inverted_pendulum

3b5746c534423d39da2582d4bae54ea7ecdacffd

[ "MIT" ]

null

QuadSwingUpEnv/QuadSwingUp/envs/__init__.py

shauray8/quadruple_inverted_pendulum

3b5746c534423d39da2582d4bae54ea7ecdacffd

[ "MIT" ]

null

from QuadSwingUp.envs.env import QuadSwingUp

22.5

44

0.866667

6

45

6.5

0.833333

0

0.088889

45

1

45

0.95122

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

d3042e007a40fc1ace083eb477d10762f0795123

229

py

Python

tensortrade/features/scalers/__init__.py

msincenselee/tensortrade

aeed3fbf1657ba1f3bf4bb81fec876d65284b79b

[ "Apache-2.0" ]

null

tensortrade/features/scalers/__init__.py

msincenselee/tensortrade

aeed3fbf1657ba1f3bf4bb81fec876d65284b79b

[ "Apache-2.0" ]

null

tensortrade/features/scalers/__init__.py

msincenselee/tensortrade

aeed3fbf1657ba1f3bf4bb81fec876d65284b79b

[ "Apache-2.0" ]

null

from .comparison_normalizer import ComparisonNormalizer from .min_max_normalizer import MinMaxNormalizer from .percent_change_normalizer import PercentChangeNormalizer from .standard_normalizer import StandardNormalizer # 标准化转换

32.714286

62

0.895197

23

229

8.652174

0.608696

0.321608

0

0.082969

229

6

63

38.166667

0.947619

0.021834

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6