hexsha
string | size
int64 | ext
string | lang
string | max_stars_repo_path
string | max_stars_repo_name
string | max_stars_repo_head_hexsha
string | max_stars_repo_licenses
list | max_stars_count
int64 | max_stars_repo_stars_event_min_datetime
string | max_stars_repo_stars_event_max_datetime
string | max_issues_repo_path
string | max_issues_repo_name
string | max_issues_repo_head_hexsha
string | max_issues_repo_licenses
list | max_issues_count
int64 | max_issues_repo_issues_event_min_datetime
string | max_issues_repo_issues_event_max_datetime
string | max_forks_repo_path
string | max_forks_repo_name
string | max_forks_repo_head_hexsha
string | max_forks_repo_licenses
list | max_forks_count
int64 | max_forks_repo_forks_event_min_datetime
string | max_forks_repo_forks_event_max_datetime
string | content
string | avg_line_length
float64 | max_line_length
int64 | alphanum_fraction
float64 | qsc_code_num_words_quality_signal
int64 | qsc_code_num_chars_quality_signal
float64 | qsc_code_mean_word_length_quality_signal
float64 | qsc_code_frac_words_unique_quality_signal
float64 | qsc_code_frac_chars_top_2grams_quality_signal
float64 | qsc_code_frac_chars_top_3grams_quality_signal
float64 | qsc_code_frac_chars_top_4grams_quality_signal
float64 | qsc_code_frac_chars_dupe_5grams_quality_signal
float64 | qsc_code_frac_chars_dupe_6grams_quality_signal
float64 | qsc_code_frac_chars_dupe_7grams_quality_signal
float64 | qsc_code_frac_chars_dupe_8grams_quality_signal
float64 | qsc_code_frac_chars_dupe_9grams_quality_signal
float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
float64 | qsc_code_frac_chars_digital_quality_signal
float64 | qsc_code_frac_chars_whitespace_quality_signal
float64 | qsc_code_size_file_byte_quality_signal
float64 | qsc_code_num_lines_quality_signal
float64 | qsc_code_num_chars_line_max_quality_signal
float64 | qsc_code_num_chars_line_mean_quality_signal
float64 | qsc_code_frac_chars_alphabet_quality_signal
float64 | qsc_code_frac_chars_comments_quality_signal
float64 | qsc_code_cate_xml_start_quality_signal
float64 | qsc_code_frac_lines_dupe_lines_quality_signal
float64 | qsc_code_cate_autogen_quality_signal
float64 | qsc_code_frac_lines_long_string_quality_signal
float64 | qsc_code_frac_chars_string_length_quality_signal
float64 | qsc_code_frac_chars_long_word_length_quality_signal
float64 | qsc_code_frac_lines_string_concat_quality_signal
float64 | qsc_code_cate_encoded_data_quality_signal
float64 | qsc_code_frac_chars_hex_words_quality_signal
float64 | qsc_code_frac_lines_prompt_comments_quality_signal
float64 | qsc_code_frac_lines_assert_quality_signal
float64 | qsc_codepython_cate_ast_quality_signal
float64 | qsc_codepython_frac_lines_func_ratio_quality_signal
float64 | qsc_codepython_cate_var_zero_quality_signal
bool | qsc_codepython_frac_lines_pass_quality_signal
float64 | qsc_codepython_frac_lines_import_quality_signal
float64 | qsc_codepython_frac_lines_simplefunc_quality_signal
float64 | qsc_codepython_score_lines_no_logic_quality_signal
float64 | qsc_codepython_frac_lines_print_quality_signal
float64 | qsc_code_num_words
int64 | qsc_code_num_chars
int64 | qsc_code_mean_word_length
int64 | qsc_code_frac_words_unique
null | qsc_code_frac_chars_top_2grams
int64 | qsc_code_frac_chars_top_3grams
int64 | qsc_code_frac_chars_top_4grams
int64 | qsc_code_frac_chars_dupe_5grams
int64 | qsc_code_frac_chars_dupe_6grams
int64 | qsc_code_frac_chars_dupe_7grams
int64 | qsc_code_frac_chars_dupe_8grams
int64 | qsc_code_frac_chars_dupe_9grams
int64 | qsc_code_frac_chars_dupe_10grams
int64 | qsc_code_frac_chars_replacement_symbols
int64 | qsc_code_frac_chars_digital
int64 | qsc_code_frac_chars_whitespace
int64 | qsc_code_size_file_byte
int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
int64 | qsc_code_num_chars_line_mean
int64 | qsc_code_frac_chars_alphabet
int64 | qsc_code_frac_chars_comments
int64 | qsc_code_cate_xml_start
int64 | qsc_code_frac_lines_dupe_lines
int64 | qsc_code_cate_autogen
int64 | qsc_code_frac_lines_long_string
int64 | qsc_code_frac_chars_string_length
int64 | qsc_code_frac_chars_long_word_length
int64 | qsc_code_frac_lines_string_concat
null | qsc_code_cate_encoded_data
int64 | qsc_code_frac_chars_hex_words
int64 | qsc_code_frac_lines_prompt_comments
int64 | qsc_code_frac_lines_assert
int64 | qsc_codepython_cate_ast
int64 | qsc_codepython_frac_lines_func_ratio
int64 | qsc_codepython_cate_var_zero
int64 | qsc_codepython_frac_lines_pass
int64 | qsc_codepython_frac_lines_import
int64 | qsc_codepython_frac_lines_simplefunc
int64 | qsc_codepython_score_lines_no_logic
int64 | qsc_codepython_frac_lines_print
int64 | effective
string | hits
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
85bac601e58cdb897155b862b67330392dce4a9e
| 107
|
py
|
Python
|
python_toolbox/registrar/__init__.py
|
htryppcook/python_toolbox
|
3219c7ff09b1f38612834141bda2f46ccc8d2257
|
[
"MIT"
] | null | null | null |
python_toolbox/registrar/__init__.py
|
htryppcook/python_toolbox
|
3219c7ff09b1f38612834141bda2f46ccc8d2257
|
[
"MIT"
] | null | null | null |
python_toolbox/registrar/__init__.py
|
htryppcook/python_toolbox
|
3219c7ff09b1f38612834141bda2f46ccc8d2257
|
[
"MIT"
] | null | null | null |
from .registrar import Registrar
from .registrar import UnregisteredItemException
__all__ = ['registrar']
| 21.4
| 48
| 0.82243
| 10
| 107
| 8.4
| 0.5
| 0.309524
| 0.452381
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.11215
| 107
| 5
| 49
| 21.4
| 0.884211
| 0
| 0
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| 0
| 0
| 0.084112
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
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| 0
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| 0
| null | 1
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| 0
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| 1
| 0
| 0
| 0
|
0
| 5
|
a4104d21a2cd6063568b7170e5c35ed7e0809ca4
| 65
|
py
|
Python
|
RobotMovingPanel/interface/__init__.py
|
Vlad12344/Pulseapi_Integration
|
2acf93a17dd2911328141886b8724134fff84f00
|
[
"MIT"
] | null | null | null |
RobotMovingPanel/interface/__init__.py
|
Vlad12344/Pulseapi_Integration
|
2acf93a17dd2911328141886b8724134fff84f00
|
[
"MIT"
] | null | null | null |
RobotMovingPanel/interface/__init__.py
|
Vlad12344/Pulseapi_Integration
|
2acf93a17dd2911328141886b8724134fff84f00
|
[
"MIT"
] | null | null | null |
from RobotMovingPanel.interface.interfaceLogic import MovingPanel
| 65
| 65
| 0.923077
| 6
| 65
| 10
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0.046154
| 65
| 1
| 65
| 65
| 0.967742
| 0
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| null | 0
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| 1
| 0
| 1
| 0
|
0
| 5
|
a410572e9d0a0046c9fcf666f487a30a0781cf18
| 88
|
py
|
Python
|
8_kyu/CSV_representation_of_array.py
|
UlrichBerntien/Codewars-Katas
|
bbd025e67aa352d313564d3862db19fffa39f552
|
[
"MIT"
] | null | null | null |
8_kyu/CSV_representation_of_array.py
|
UlrichBerntien/Codewars-Katas
|
bbd025e67aa352d313564d3862db19fffa39f552
|
[
"MIT"
] | null | null | null |
8_kyu/CSV_representation_of_array.py
|
UlrichBerntien/Codewars-Katas
|
bbd025e67aa352d313564d3862db19fffa39f552
|
[
"MIT"
] | null | null | null |
def to_csv_text(array):
return "\n".join( ",".join(map(str,row)) for row in array )
| 29.333333
| 63
| 0.636364
| 16
| 88
| 3.375
| 0.8125
| 0
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| 0.159091
| 88
| 2
| 64
| 44
| 0.72973
| 0
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| 0.034091
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| false
| 0
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| null | 0
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| 0
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| null | 0
| 0
| 0
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| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
f10fade5c9fd7ae444f1d1337594502ddcfb424e
| 22,066
|
py
|
Python
|
createEBSPxml.py
|
guzhongru/popgen-stats
|
75cb0e0bb9b274fe1b071481068013fd7710e1b8
|
[
"MIT"
] | 45
|
2015-06-06T12:28:52.000Z
|
2021-07-28T22:56:46.000Z
|
createEBSPxml.py
|
guzhongru/popgen-stats
|
75cb0e0bb9b274fe1b071481068013fd7710e1b8
|
[
"MIT"
] | 11
|
2016-08-16T20:57:40.000Z
|
2020-07-07T16:37:31.000Z
|
createEBSPxml.py
|
tatumdmortimer/popgen-stats
|
eecdc4b10ea860cfd49e4fd21daa3b93b009350d
|
[
"MIT"
] | 20
|
2016-05-24T12:06:05.000Z
|
2021-07-13T09:16:57.000Z
|
#!/usr/bin/env python
import sys
import os
import getopt
import glob
from Bio import SeqIO
# This script reads in a directory of fasta alignments
# and creates the input xml for an EBSP analysis using BEAST v 1.8
def usage():
print "createEBSPxml.py <directory of fasta alignments> <file name prefix>"
if len(sys.argv) != 3:
usage()
sys.exit()
directory = sys.argv[1]
prefix = sys.argv[2]
alignments = glob.glob(directory + '*.fasta')
out_xml = open(prefix + '.xml', 'w')
out_xml.write("<beast>\n")
if len(alignments) == 0:
print ("Directory must contain files ending with .fasta")
alignmentNames = []
taxa = []
# get taxa names from first alignment
handle = open(alignments[0], "r")
for record in SeqIO.parse(handle, "fasta"):
taxa.append(record.id)
handle.close()
# write taxa section of xml file
out_xml.write("\t<taxa id=\"taxa\">\n")
for t in taxa:
out_xml.write("\t\t<taxon id=\"%s\"/>\n" % t)
out_xml.write("\t</taxa>\n")
# write alignments to xml file
out_xml.write("\n")
for i,a in enumerate(alignments):
alignmentNames.append(os.path.basename(a).split('.')[0])
out_xml.write("\t<alignment id=\"alignment%s\" dataType=\"nucleotide\">\n"
% str(i+1))
handle = open(a, "r")
for record in SeqIO.parse(handle, "fasta"):
out_xml.write("\t\t<sequence>\n")
out_xml.write("\t\t\t<taxon idref=\"%s\"/>\n" % record.id)
out_xml.write("\t\t\t%s\n" % record.seq)
out_xml.write("\t\t</sequence>\n")
out_xml.write("\t</alignment>\n")
#write patterns to xml file
out_xml.write("\n")
for j,n in enumerate(alignmentNames):
out_xml.write("\t<patterns id=\"%s.patterns\" from=\"1\" strip=\"false\">\n"
% n)
out_xml.write("\t\t<alignment idref=\"alignment%s\"/>\n" % str(j+1))
out_xml.write("\t</patterns>\n")
# write starting trees to xml file
out_xml.write("\n")
out_xml.write("\t<constantSize id=\"initialDemo\" units=\"substitutions\">\n")
out_xml.write("\t\t<populationSize>\n")
out_xml.write("\t\t\t<parameter id=\"initialDemo.popSize\" value=\"100.0\"/>\n")
out_xml.write("\t\t</populationSize>\n")
out_xml.write("\t</constantSize>\n")
for name in alignmentNames:
out_xml.write("\t<coalescentSimulator id=\"%s.startingTree\">\n" % name)
out_xml.write("\t\t<taxa idref=\"taxa\"/>\n")
out_xml.write("\t\t<constantSize idref=\"initialDemo\"/>\n")
out_xml.write("\t</coalescentSimulator>\n")
# write tree model to xml file
for aN in alignmentNames:
out_xml.write("\t<treeModel id=\"%s.treeModel\">\n" % aN)
out_xml.write("\t\t<coalescentTree idref=\"%s.startingTree\"/>\n" % aN)
out_xml.write("\t\t<rootHeight>\n")
out_xml.write("\t\t\t<parameter id=\"%s.treeModel.rootHeight\"/>\n" % aN)
out_xml.write("\t\t</rootHeight>\n")
out_xml.write("\t\t<nodeHeights internalNodes=\"true\">\n")
out_xml.write("\t\t\t<parameter id=\"%s.treeModel.internalNodeHeights\"/>\n"
% aN)
out_xml.write("\t\t</nodeHeights>\n")
out_xml.write("\t\t<nodeHeights internalNodes=\"true\" rootNode=\"true\">\n")
out_xml.write("\t\t\t<parameter id=\"%s.treeModel.allInternalNodeHeights\"/>\n"
% aN)
out_xml.write("\t\t</nodeHeights>\n")
out_xml.write("\t</treeModel>\n")
# write EBSP to xml file
out_xml.write("\n")
out_xml.write("\t<variableDemographic id=\"demographic\" type=\"linear\" useMidpoints=\"true\">\n")
out_xml.write("\t\t<populationSizes>\n")
out_xml.write("\t\t\t<parameter id=\"demographic.popSize\" value=\"0.023\"/>\n")
out_xml.write("\t\t</populationSizes>\n")
out_xml.write("\t\t<indicators>\n")
out_xml.write("\t\t\t<parameter id=\"demographic.indicators\" value=\"0.0\"/>\n"
)
out_xml.write("\t\t</indicators>\n")
out_xml.write("\t\t<trees>\n")
for align in alignmentNames:
out_xml.write("\t\t\t<ptree ploidy=\"1.0\">\n")
out_xml.write("\t\t\t\t<treeModel idref=\"%s.treeModel\"/>\n" % align)
out_xml.write("\t\t\t</ptree>\n")
out_xml.write("\t\t</trees>\n")
out_xml.write("\t</variableDemographic>\n")
out_xml.write("\t<coalescentLikelihood id=\"coalescent\">\n")
out_xml.write("\t\t<model>\n")
out_xml.write("\t\t\t<variableDemographic idref=\"demographic\"/>\n")
out_xml.write("\t\t</model>\n")
out_xml.write("\t</coalescentLikelihood>\n")
out_xml.write("\t<sumStatistic id=\"demographic.populationSizeChanges\" \
elementwise=\"true\">\n")
out_xml.write("\t\t<parameter idref=\"demographic.indicators\"/>\n")
out_xml.write("\t</sumStatistic>\n")
out_xml.write("\t<exponentialDistributionModel \
id=\"demographic.populationMeanDist\">\n")
out_xml.write("\t\t<mean>\n")
out_xml.write("\t\t\t<parameter id=\"demographic.populationMean\" \
value=\"0.023\"/>\n")
out_xml.write("\t\t</mean>\n")
out_xml.write("\t</exponentialDistributionModel>\n")
# write clock model to xml file
for aName in alignmentNames:
out_xml.write("\t<strictClockBranchRates id=\"%s.branchRates\">\n" % aName)
out_xml.write("\t\t<rate>\n")
out_xml.write("\t\t\t<parameter id=\"%s.clock.rate\" value=\"1.0\" \
lower=\"0.0\"/>\n" % aName)
out_xml.write("\t\t</rate>\n")
out_xml.write("\t</strictClockBranchRates>\n")
# write substitution and site models to xml file
out_xml.write("\n")
# for alignName in alignmentNames:
# out_xml.write("\t<gtrModel id=\"%s.gtr\">\n" % alignName)
# out_xml.write("\t\t<frequencies>\n")
# out_xml.write("\t\t\t<frequencyModel dataType=\"nucleotide\">\n")
# out_xml.write("\t\t\t\t<frequencies>\n")
# out_xml.write("\t\t\t\t\t<parameter id=\"%s.frequencies\" value=\"0.25 \
# 0.25 0.25 0.25\"/>\n" % alignName)
# out_xml.write("\t\t\t\t</frequencies>\n")
# out_xml.write("\t\t\t</frequencyModel>\n")
# out_xml.write("\t\t</frequencies>\n")
# out_xml.write("\t\t<rateAC>\n")
# out_xml.write("\t\t\t<parameter id=\"%s.ac\" value=\"1.0\" \
# lower=\"0.0\"/>\n" % alignName)
# out_xml.write("\t\t</rateAC>\n")
# out_xml.write("\t\t<rateAG>\n")
# out_xml.write("\t\t\t<parameter id=\"%s.ag\" value=\"1.0\" \
# lower=\"0.0\"/>\n" % alignName)
# out_xml.write("\t\t</rateAG>\n")
# out_xml.write("\t\t<rateAT>\n")
# out_xml.write("\t\t\t<parameter id=\"%s.at\" value=\"1.0\" \
# lower=\"0.0\"/>\n" % alignName)
# out_xml.write("\t\t</rateAT>\n")
# out_xml.write("\t\t<rateCG>\n")
# out_xml.write("\t\t\t<parameter id=\"%s.cg\" value=\"1.0\" \
# lower=\"0.0\"/>\n" % alignName)
# out_xml.write("\t\t</rateCG>\n")
# out_xml.write("\t\t<rateGT>\n")
# out_xml.write("\t\t\t<parameter id=\"%s.gt\" value=\"1.0\" \
# lower=\"0.0\"/>\n" % alignName)
# out_xml.write("\t\t</rateGT>\n")
# out_xml.write("\t</gtrModel>\n")
# out_xml.write("\t<siteModel id=\"%s.siteModel\">\n" % alignName)
# out_xml.write("\t\t<substitutionModel>\n")
# out_xml.write("\t\t\t<gtrModel idref=\"%s.gtr\"/>\n" % alignName)
# out_xml.write("\t\t</substitutionModel>\n")
# out_xml.write("\t\t<gammaShape gammaCategories=\"4\">\n")
# out_xml.write("\t\t\t<parameter id=\"%s.alpha\" value=\"0.5\" \
# lower=\"0.0\"/>\n" % alignName)
# out_xml.write("\t\t</gammaShape>\n")
# out_xml.write("\t\t<proportionInvariant>\n")
# out_xml.write("\t\t\t<parameter id=\"%s.pInv\" value=\"0.5\" \
# lower=\"0.0\" upper=\"1.0\"/>\n" % alignName)
# out_xml.write("\t\t</proportionInvariant>\n")
# out_xml.write("\t</siteModel>\n")
for alignName in alignmentNames:
out_xml.write("\t<HKYModel id=\"%s.hky\">\n" % alignName)
out_xml.write("\t\t<frequencies>\n")
out_xml.write("\t\t\t<frequencyModel dataType=\"nucleotide\">\n")
out_xml.write("\t\t\t\t<frequencies>\n")
out_xml.write("\t\t\t\t\t<parameter id=\"%s.frequencies\" value=\"0.25 \
0.25 0.25 0.25\"/>\n" % alignName)
out_xml.write("\t\t\t\t</frequencies>\n")
out_xml.write("\t\t\t</frequencyModel>\n")
out_xml.write("\t\t</frequencies>\n")
out_xml.write("\t\t<kappa>\n")
out_xml.write("\t\t\t<parameter id=\"%s.kappa\" value=\"2.0\" \
lower=\"0.0\"/>\n" % alignName)
out_xml.write("\t\t</kappa>\n")
out_xml.write("\t</HKYModel>\n")
out_xml.write("\t<siteModel id=\"%s.siteModel\">\n" % alignName)
out_xml.write("\t\t<substitutionModel>\n")
out_xml.write("\t\t\t<HKYModel idref=\"%s.hky\"/>\n" % alignName)
out_xml.write("\t\t</substitutionModel>\n")
out_xml.write("\t\t<gammaShape gammaCategories=\"4\">\n")
out_xml.write("\t\t\t<parameter id=\"%s.alpha\" value=\"0.5\" \
lower=\"0.0\"/>\n" % alignName)
out_xml.write("\t\t</gammaShape>\n")
out_xml.write("\t\t<proportionInvariant>\n")
out_xml.write("\t\t\t<parameter id=\"%s.pInv\" value=\"0.5\" \
lower=\"0.0\" upper=\"1.0\"/>\n" % alignName)
out_xml.write("\t\t</proportionInvariant>\n")
out_xml.write("\t</siteModel>\n")
# write tree likelihood to xml file
out_xml.write("\n")
for alName in alignmentNames:
out_xml.write("\t<treeLikelihood id=\"%s.treeLikelihood\" \
useAmbiguities=\"false\">\n" % alName)
out_xml.write("\t\t<patterns idref=\"%s.patterns\"/>\n" % alName)
out_xml.write("\t\t<treeModel idref=\"%s.treeModel\"/>\n" % alName)
out_xml.write("\t\t<siteModel idref=\"%s.siteModel\"/>\n" % alName)
out_xml.write("\t\t<strictClockBranchRates idref=\"%s.branchRates\"/>\n"
% alName)
out_xml.write("\t</treeLikelihood>\n")
# write operators to xml file
out_xml.write("\n")
out_xml.write("\t<operators id=\"operators\" \
optimizationSchedule=\"default\">\n")
# for b in alignmentNames:
# for c in ["ac", "ag", "at", "cg", "gt", "alpha", "pInv"]:
# out_xml.write("\t\t<scaleOperator scaleFactor=\"0.75\" \
# weight=\"0.1\">\n")
# out_xml.write("\t\t\t<parameter idref=\"%s.%s\"/>\n" % (b,c))
# out_xml.write("\t\t</scaleOperator>\n")
# out_xml.write("\t\t<deltaExchange delta=\"0.01\" weight=\"0.1\">\n")
# out_xml.write("\t\t\t<parameter idref=\"%s.frequencies\"/>\n" % b)
# out_xml.write("\t\t</deltaExchange>\n")
for b in alignmentNames:
for c in ["alpha", "pInv", "kappa"]:
out_xml.write("\t\t<scaleOperator scaleFactor=\"0.75\" \
weight=\"0.1\">\n")
out_xml.write("\t\t\t<parameter idref=\"%s.%s\"/>\n" % (b,c))
out_xml.write("\t\t</scaleOperator>\n")
out_xml.write("\t\t<deltaExchange delta=\"0.01\" weight=\"0.1\">\n")
out_xml.write("\t\t\t<parameter idref=\"%s.frequencies\"/>\n" % b)
out_xml.write("\t\t</deltaExchange>\n")
for d in alignmentNames:
out_xml.write("\t\t<scaleOperator scaleFactor=\"0.75\" weight=\"3\">\n")
out_xml.write("\t\t\t<parameter idref=\"%s.clock.rate\"/>\n" % d)
out_xml.write("\t\t</scaleOperator>\n")
out_xml.write("\t\t<upDownOperator scaleFactor=\"0.75\" weight=\"30\">\n")
out_xml.write("\t\t\t<up>\n")
for index,e in enumerate(alignmentNames):
if index > 0:
out_xml.write("\t\t\t\t<parameter idref=\"%s.clock.rate\"/>\n" % e)
out_xml.write("\t\t\t</up>\n")
out_xml.write("\t\t\t<down>\n")
out_xml.write("\t\t\t\t<parameter idref=\"demographic.populationMean\"/>\n")
out_xml.write("\t\t\t\t<parameter idref=\"demographic.popSize\"/>\n")
for f in alignmentNames:
out_xml.write("\t\t\t\t<parameter \
idref=\"%s.treeModel.allInternalNodeHeights\"/>\n" % f)
out_xml.write("\t\t\t</down>\n")
out_xml.write("\t\t</upDownOperator>\n")
for g in alignmentNames:
out_xml.write("\t\t<subtreeSlide size=\"0.0017\" gaussian=\"true\" \
weight=\"15\">\n")
out_xml.write("\t\t\t<treeModel idref=\"%s.treeModel\"/>\n" % g)
out_xml.write("\t\t</subtreeSlide>\n")
out_xml.write("\t\t<narrowExchange weight=\"15\">\n")
out_xml.write("\t\t\t<treeModel idref=\"%s.treeModel\"/>\n" % g)
out_xml.write("\t\t</narrowExchange>\n")
out_xml.write("\t\t<wideExchange weight=\"3\">\n")
out_xml.write("\t\t\t<treeModel idref=\"%s.treeModel\"/>\n" % g)
out_xml.write("\t\t</wideExchange>\n")
out_xml.write("\t\t<wilsonBalding weight=\"3\">\n")
out_xml.write("\t\t\t<treeModel idref=\"%s.treeModel\"/>\n" % g)
out_xml.write("\t\t</wilsonBalding>\n")
out_xml.write("\t\t<scaleOperator scaleFactor=\"0.75\" \
weight=\"3\">\n")
out_xml.write("\t\t\t<parameter idref=\"%s.treeModel.rootHeight\"/>\n" % g)
out_xml.write("\t\t</scaleOperator>\n")
out_xml.write("\t\t<uniformOperator weight=\"30\">\n")
out_xml.write("\t\t\t<parameter \
idref=\"%s.treeModel.internalNodeHeights\"/>\n" % g)
out_xml.write("\t\t</uniformOperator>\n")
out_xml.write("\t\t<scaleOperator scaleFactor=\"0.9\" weight=\"3\">\n\
\t\t\t<parameter idref=\"demographic.populationMean\"/>\n\
\t\t</scaleOperator>\n\
\t\t<sampleNonActiveOperator weight=\"40\">\n\
\t\t\t<distribution>\n\
\t\t\t\t<parameter idref=\"demographic.populationMeanDist\"/>\n\
\t\t\t</distribution>\n\
\t\t\t<data>\n\
\t\t\t\t<parameter idref=\"demographic.popSize\"/>\n\
\t\t\t</data>\n\
\t\t\t<indicators>\n\
\t\t\t\t<parameter idref=\"demographic.indicators\"/>\n\
\t\t\t</indicators>\n\
\t\t</sampleNonActiveOperator>\n\
\t\t<bitFlipOperator weight=\"100\">\n\
\t\t\t<parameter idref=\"demographic.indicators\"/>\n\
\t\t</bitFlipOperator>\n\
\t\t<scaleOperator scaleFactor=\"0.5\" weight=\"60\">\n\
\t\t\t<parameter idref=\"demographic.popSize\"/>\n\
\t\t\t<indicators pickoneprob=\"1.0\">\n\
\t\t\t\t<parameter idref=\"demographic.indicators\"/>\n\
\t\t\t</indicators>\n\
\t\t</scaleOperator>\n")
for h in alignmentNames:
out_xml.write("\t\t<upDownOperator scaleFactor=\"0.75\" weight=\"3\">\n")
out_xml.write("\t\t\t<up>\n")
out_xml.write("\t\t\t\t<parameter idref=\"%s.clock.rate\"/>\n" % h)
out_xml.write("\t\t\t</up>\n")
out_xml.write("\t\t\t<down>\n")
out_xml.write("\t\t\t\t<parameter \
idref=\"%s.treeModel.allInternalNodeHeights\"/>\n" % h)
out_xml.write("\t\t\t</down>\n")
out_xml.write("\t\t</upDownOperator>\n")
out_xml.write("\t</operators>\n")
# write MCMC to xml
out_xml.write("\t<mcmc id=\"mcmc\" chainLength=\"100000000\" \
autoOptimize=\"true\" operatorAnalysis=\"%s.ops\">\n" % prefix)
out_xml.write("\t\t<posterior id=\"posterior\">\n")
out_xml.write("\t\t\t<prior id=\"prior\">\n")
# for k in alignmentNames:
# out_xml.write("\t\t\t\t<gammaPrior shape=\"0.05\" scale=\"10.0\" \
# offset=\"0.0\">\n")
# out_xml.write("\t\t\t\t\t<parameter idref=\"%s.ac\"/>\n" % k)
# out_xml.write("\t\t\t\t</gammaPrior>\n")
# out_xml.write("\t\t\t\t<gammaPrior shape=\"0.05\" scale=\"20.0\" \
# offset=\"0.0\">\n")
# out_xml.write("\t\t\t\t\t<parameter idref=\"%s.ag\"/>\n" % k)
# out_xml.write("\t\t\t\t</gammaPrior>\n")
# out_xml.write("\t\t\t\t<gammaPrior shape=\"0.05\" scale=\"10.0\" \
# offset=\"0.0\">\n")
# out_xml.write("\t\t\t\t\t<parameter idref=\"%s.at\"/>\n" % k)
# out_xml.write("\t\t\t\t</gammaPrior>\n")
# out_xml.write("\t\t\t\t<gammaPrior shape=\"0.05\" scale=\"10.0\" \
# offset=\"0.0\">\n")
# out_xml.write("\t\t\t\t\t<parameter idref=\"%s.cg\"/>\n" % k)
# out_xml.write("\t\t\t\t</gammaPrior>\n")
# out_xml.write("\t\t\t\t<gammaPrior shape=\"0.05\" scale=\"10.0\" \
# offset=\"0.0\">\n")
# out_xml.write("\t\t\t\t\t<parameter idref=\"%s.gt\"/>\n" % k)
# out_xml.write("\t\t\t\t</gammaPrior>\n")
# out_xml.write("\t\t\t\t<uniformPrior lower=\"0.0\" upper=\"1.0\">\n")
# out_xml.write("\t\t\t\t\t<parameter idref=\"%s.frequencies\"/>\n" % k)
# out_xml.write("\t\t\t\t</uniformPrior>\n")
# out_xml.write("\t\t\t\t<exponentialPrior mean=\"0.5\" offset=\"0.0\">\n")
# out_xml.write("\t\t\t\t\t<parameter idref=\"%s.alpha\"/>\n" % k)
# out_xml.write("\t\t\t\t</exponentialPrior>\n")
# out_xml.write("\t\t\t\t<uniformPrior lower=\"0.0\" upper=\"1.0\">\n")
# out_xml.write("\t\t\t\t\t<parameter idref=\"%s.pInv\"/>\n" % k)
# out_xml.write("\t\t\t\t</uniformPrior>\n")
for k in alignmentNames:
out_xml.write("\t\t\t\t<logNormalPrior mean=\"1.0\" stdev=\"1.25\" \
offset=\"0.0\" meanInRealSpace=\"false\">\n")
out_xml.write("\t\t\t\t\t<parameter idref=\"%s.kappa\"/>\n" % k)
out_xml.write("\t\t\t\t</logNormalPrior>\n")
out_xml.write("\t\t\t\t<uniformPrior lower=\"0.0\" upper=\"1.0\">\n")
out_xml.write("\t\t\t\t\t<parameter idref=\"%s.frequencies\"/>\n" % k)
out_xml.write("\t\t\t\t</uniformPrior>\n")
out_xml.write("\t\t\t\t<exponentialPrior mean=\"0.5\" offset=\"0.0\">\n")
out_xml.write("\t\t\t\t\t<parameter idref=\"%s.alpha\"/>\n" % k)
out_xml.write("\t\t\t\t</exponentialPrior>\n")
out_xml.write("\t\t\t\t<uniformPrior lower=\"0.0\" upper=\"1.0\">\n")
out_xml.write("\t\t\t\t\t<parameter idref=\"%s.pInv\"/>\n" % k)
out_xml.write("\t\t\t\t</uniformPrior>\n")
for l in alignmentNames:
out_xml.write("\t\t\t\t<uniformPrior lower=\"0.0\" upper=\"5.0E18\">\n")
out_xml.write("\t\t\t\t\t<parameter idref=\"%s.clock.rate\"/>\n" % l)
out_xml.write("\t\t\t\t</uniformPrior>\n")
out_xml.write("\t\t\t\t<poissonPrior mean=\"0.693147\" offset=\"0.0\">\n\
\t\t\t\t\t<statistic idref=\"demographic.populationSizeChanges\"/>\n\
\t\t\t\t</poissonPrior>\n\
\t\t\t\t<oneOnXPrior>\n\
\t\t\t\t\t<parameter idref=\"demographic.populationMean\"/>\n\
\t\t\t\t</oneOnXPrior>\n\
\t\t\t\t<coalescentLikelihood idref=\"coalescent\"/>\n\
\t\t\t\t<mixedDistributionLikelihood>\n\
\t\t\t\t\t<distribution0>\n\
\t\t\t\t\t\t<exponentialDistributionModel \
idref=\"demographic.populationMeanDist\"/>\n\
\t\t\t\t\t</distribution0>\n\
\t\t\t\t\t<distribution1>\n\
\t\t\t\t\t\t<exponentialDistributionModel \
idref=\"demographic.populationMeanDist\"/>\n\
\t\t\t\t\t</distribution1>\n\
\t\t\t\t\t<data>\n\
\t\t\t\t\t\t<parameter idref=\"demographic.popSize\"/>\n\
\t\t\t\t\t</data>\n\
\t\t\t\t\t<indicators>\n\
\t\t\t\t\t\t<parameter idref=\"demographic.indicators\"/>\n\
\t\t\t\t\t</indicators>\n\
\t\t\t\t</mixedDistributionLikelihood>\n\
\t\t\t</prior>\n")
out_xml.write("\t\t\t<likelihood id=\"likelihood\">\n")
for m in alignmentNames:
out_xml.write("\t\t\t\t<treeLikelihood idref=\"%s.treeLikelihood\"/>\n" % m)
out_xml.write("\t\t\t</likelihood>\n")
out_xml.write("\t\t</posterior>\n")
out_xml.write("\t\t<operators idref=\"operators\"/>\n")
# write logs to xml
out_xml.write("\n")
out_xml.write("\t\t<log id=\"screenLog\" logEvery=\"10000\">\n\
\t\t\t<column label=\"Posterior\" dp=\"4\" width=\"12\">\n\
\t\t\t\t<posterior idref=\"posterior\"/>\n\
\t\t\t</column>\n\
\t\t\t<column label=\"Prior\" dp=\"4\" width=\"12\">\n\
\t\t\t\t<prior idref=\"prior\"/>\n\
\t\t\t</column>\n\
\t\t\t<column label=\"Likelihood\" dp=\"4\" width=\"12\">\n\
\t\t\t\t<likelihood idref=\"likelihood\"/>\n\
\t\t\t</column>\n\
\t\t</log>\n")
out_xml.write("\t\t<log id=\"fileLog\" logEvery=\"10000\" fileName=\"%s.log\" \
overwrite=\"false\">\n" % prefix)
out_xml.write("\t\t\t<posterior idref=\"posterior\"/>\n")
out_xml.write("\t\t\t<prior idref=\"prior\"/>\n")
out_xml.write("\t\t\t<likelihood idref=\"likelihood\"/>")
for o in alignmentNames:
out_xml.write("\t\t\t<parameter idref=\"%s.treeModel.rootHeight\"/>\n" % o)
out_xml.write("\t\t\t<sumStatistic \
idref=\"demographic.populationSizeChanges\"/>\n")
out_xml.write("\t\t\t<parameter idref=\"demographic.populationMean\"/>\n")
out_xml.write("\t\t\t<parameter idref=\"demographic.popSize\"/>\n")
out_xml.write("\t\t\t<parameter idref=\"demographic.indicators\"/>\n")
for p in alignmentNames:
# out_xml.write("\t\t\t<parameter idref=\"%s.ac\"/>\n" % p)
# out_xml.write("\t\t\t<parameter idref=\"%s.ag\"/>\n" % p)
# out_xml.write("\t\t\t<parameter idref=\"%s.at\"/>\n" % p)
# out_xml.write("\t\t\t<parameter idref=\"%s.cg\"/>\n" % p)
out_xml.write("\t\t\t<parameter idref=\"%s.kappa\"/>\n" % p)
out_xml.write("\t\t\t<parameter idref=\"%s.frequencies\"/>\n" % p)
out_xml.write("\t\t\t<parameter idref=\"%s.alpha\"/>\n" % p)
out_xml.write("\t\t\t<parameter idref=\"%s.pInv\"/>\n" % p)
for q in alignmentNames:
out_xml.write("\t\t\t<parameter idref=\"%s.clock.rate\"/>\n" % q)
for r in alignmentNames:
out_xml.write("\t\t\t<treeLikelihood idref=\"%s.treeLikelihood\"/>\n" % r)
out_xml.write("\t\t\t<coalescentLikelihood idref=\"coalescent\"/>\n")
out_xml.write("\t\t</log>\n")
for s in alignmentNames:
out_xml.write("\t\t<logTree id=\"%s.treeFileLog\" logEvery=\"10000\" \
nexusFormat=\"true\" fileName=\"%s.%s.trees\" sortTranslationTable=\"true\">\n"
% (s,prefix,s))
out_xml.write("\t\t\t<treeModel idref=\"%s.treeModel\"/>\n" % s)
out_xml.write("\t\t\t<trait name=\"rate\" tag=\"%s.rate\">\n" % s)
out_xml.write("\t\t\t\t<strictClockBranchRates idref=\"%s.branchRates\"/>\n"
% s)
out_xml.write("\t\t\t</trait>\n")
out_xml.write("\t\t\t<posterior idref=\"posterior\"/>\n")
out_xml.write("\t\t</logTree>\n")
out_xml.write("\t</mcmc>\n")
# write .csv info to xml file
out_xml.write("\n")
out_xml.write("\t<report>\n\
\t\t<property name=\"timer\">\n\
\t\t\t<mcmc idref=\"mcmc\"/>\n\
\t\t</property>\n\
\t</report>\n")
out_xml.write("\t<VDAnalysis id=\"demographic.analysis\" burnIn=\"0.1\" \
useMidpoints=\"true\">\n")
out_xml.write("\t\t<logFileName>\n\t\t\t%s.log\n\t\t</logFileName>\n" % prefix)
out_xml.write("\t\t<treeFileNames>\n")
for t in alignmentNames:
out_xml.write("\t\t\t<treeOfLoci>\n")
out_xml.write("\t\t\t\t%s.%s.trees\n" % (prefix,t))
out_xml.write("\t\t\t</treeOfLoci>\n")
out_xml.write("\t\t</treeFileNames>\n")
out_xml.write("\t\t<populationModelType>\n")
out_xml.write("\t\t\tlinear\n")
out_xml.write("\t\t</populationModelType>\n")
out_xml.write("\t\t<populationFirstColumn>\n")
out_xml.write("\t\t\tdemographic.popSize1\n")
out_xml.write("\t\t</populationFirstColumn>\n")
out_xml.write("\t\t<indicatorsFirstColumn>\n")
out_xml.write("\t\t\tdemographic.indicators1\n")
out_xml.write("\t\t</indicatorsFirstColumn>\n")
out_xml.write("\t</VDAnalysis>\n")
out_xml.write("\t<CSVexport fileName=\"%s.csv\" separator=\",\">\n" % prefix)
out_xml.write("\t\t<columns>\n")
out_xml.write("\t\t\t<VDAnalysis idref=\"demographic.analysis\"/>\n")
out_xml.write("\t\t</columns>\n")
out_xml.write("\t</CSVexport>\n")
out_xml.write("</beast>\n")
out_xml.close()
| 42.763566
| 99
| 0.629521
| 3,725
| 22,066
| 3.649664
| 0.078121
| 0.087679
| 0.065318
| 0.249798
| 0.811843
| 0.772784
| 0.71313
| 0.659875
| 0.612578
| 0.569842
| 0
| 0.014854
| 0.106091
| 22,066
| 515
| 100
| 42.846602
| 0.674373
| 0.224871
| 0
| 0.153005
| 0
| 0.002732
| 0.366176
| 0.120235
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.013661
| null | null | 0.005464
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
f1468718865e12cb79081e81de11ebeb002abd0e
| 220
|
py
|
Python
|
src/blog/admin.py
|
rooneyrulz/django_blog
|
fca83dbc312747493cc660c6fc74553cc7a91c42
|
[
"MIT"
] | 4
|
2019-10-08T03:15:33.000Z
|
2020-03-04T08:43:03.000Z
|
src/blog/admin.py
|
km427/django_blog
|
fca83dbc312747493cc660c6fc74553cc7a91c42
|
[
"MIT"
] | 7
|
2020-06-05T23:21:08.000Z
|
2022-02-10T14:30:07.000Z
|
src/blog/admin.py
|
km427/django_blog
|
fca83dbc312747493cc660c6fc74553cc7a91c42
|
[
"MIT"
] | 1
|
2019-10-25T12:21:13.000Z
|
2019-10-25T12:21:13.000Z
|
from django.contrib import admin
from .models import Blog
admin.site.site_header = 'Blog Admin'
admin.site.site_title = 'Blog Admin Area'
admin.site.index_title = 'Welcome to Blog Admin Area'
admin.site.register(Blog)
| 24.444444
| 53
| 0.781818
| 35
| 220
| 4.828571
| 0.428571
| 0.213018
| 0.153846
| 0.213018
| 0.260355
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.122727
| 220
| 9
| 54
| 24.444444
| 0.875648
| 0
| 0
| 0
| 0
| 0
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
f16449d6a46edf7e5c87d24457ffe12e59bd62ff
| 479
|
py
|
Python
|
mct_camera_tools/nodes/test_camera_master_param_srv.py
|
iorodeo/mct
|
fa8b85f36533c9b1486ca4f6b0c40c3daa6f4e11
|
[
"Apache-2.0"
] | null | null | null |
mct_camera_tools/nodes/test_camera_master_param_srv.py
|
iorodeo/mct
|
fa8b85f36533c9b1486ca4f6b0c40c3daa6f4e11
|
[
"Apache-2.0"
] | null | null | null |
mct_camera_tools/nodes/test_camera_master_param_srv.py
|
iorodeo/mct
|
fa8b85f36533c9b1486ca4f6b0c40c3daa6f4e11
|
[
"Apache-2.0"
] | null | null | null |
from __future__ import print_function
import roslib
roslib.load_manifest('mct_camera_tools')
import rospy
import sys
from mct_camera_tools import camera_master
camera_master.set_camera_launch_param('calibration', False)
print(camera_master.get_camera_launch_param())
#camera_master.set_camera_launch_param('tracking', True)
#print(camera_master.get_camera_launch_param())
#camera_master.set_camera_launch_param('default', False)
#print(camera_master.get_camera_launch_param())
| 31.933333
| 59
| 0.858038
| 69
| 479
| 5.449275
| 0.333333
| 0.223404
| 0.271277
| 0.167553
| 0.577128
| 0.577128
| 0.492021
| 0.492021
| 0.367021
| 0.367021
| 0
| 0
| 0.05428
| 479
| 14
| 60
| 34.214286
| 0.830022
| 0.421712
| 0
| 0
| 0
| 0
| 0.098901
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.625
| 0
| 0.625
| 0.25
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
f16684d24f2eb0b6501946f20a92ee119a68a1bb
| 149
|
py
|
Python
|
wedos_api/__init__.py
|
esoadamo/Python-WAPI
|
48b7765cc95975e3a7d51f417166a781ce655848
|
[
"MIT"
] | null | null | null |
wedos_api/__init__.py
|
esoadamo/Python-WAPI
|
48b7765cc95975e3a7d51f417166a781ce655848
|
[
"MIT"
] | null | null | null |
wedos_api/__init__.py
|
esoadamo/Python-WAPI
|
48b7765cc95975e3a7d51f417166a781ce655848
|
[
"MIT"
] | null | null | null |
from .models import WAPIRequest, WAPIResponse, WAPIDomainRecordType, WAPIDomainRecord, WAPIDomainStatus
from .api import WAPI, WAPIDomain, WAPIError
| 49.666667
| 103
| 0.852349
| 14
| 149
| 9.071429
| 0.857143
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| 2
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| 1
| 0
|
0
| 5
|
f17121398eba7612387337fea297ee2969788d73
| 21
|
py
|
Python
|
background.py
|
mcdenhoed/redo
|
075fae23c8ae4d6e35d6bc6aa9d847ba149605e1
|
[
"BSD-3-Clause"
] | 2
|
2017-05-11T05:57:31.000Z
|
2018-02-25T18:15:09.000Z
|
background.py
|
mcdenhoed/redo
|
075fae23c8ae4d6e35d6bc6aa9d847ba149605e1
|
[
"BSD-3-Clause"
] | null | null | null |
background.py
|
mcdenhoed/redo
|
075fae23c8ae4d6e35d6bc6aa9d847ba149605e1
|
[
"BSD-3-Clause"
] | 2
|
2017-04-29T14:59:58.000Z
|
2018-03-13T16:31:31.000Z
|
import sys,os,pygame
| 10.5
| 20
| 0.809524
| 4
| 21
| 4.25
| 1
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| 0.095238
| 21
| 1
| 21
| 21
| 0.894737
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| 1
| 0
| 0
| 0
|
0
| 5
|
74afc75ed2891508e35436cc70caa6b5d03d71b4
| 101
|
py
|
Python
|
src/pytools/parallelization/__init__.py
|
BCG-Gamma/pytools
|
d7be703e0665917cd75b671564d5c0163f13b77b
|
[
"Apache-2.0"
] | 17
|
2021-01-12T08:07:11.000Z
|
2022-03-03T22:59:04.000Z
|
src/pytools/parallelization/__init__.py
|
BCG-Gamma/pytools
|
d7be703e0665917cd75b671564d5c0163f13b77b
|
[
"Apache-2.0"
] | 10
|
2021-01-08T17:04:39.000Z
|
2022-01-18T13:21:52.000Z
|
src/pytools/parallelization/__init__.py
|
BCG-Gamma/pytools
|
d7be703e0665917cd75b671564d5c0163f13b77b
|
[
"Apache-2.0"
] | 1
|
2021-11-06T00:16:43.000Z
|
2021-11-06T00:16:43.000Z
|
"""
Parallelization support based on the :mod:`joblib` package.
"""
from ._parallelization import *
| 16.833333
| 59
| 0.732673
| 11
| 101
| 6.636364
| 0.909091
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| 0.138614
| 101
| 5
| 60
| 20.2
| 0.83908
| 0.584158
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| 1
| 0
| 1
| 0
|
0
| 5
|
2d2e3a58b0e06598af726fb00de9f29e497e159c
| 68
|
py
|
Python
|
ac88web/__init__.py
|
AlignedCookie88/ac88web
|
9bef4ae37acd152c55702959c1a61111b28fa47f
|
[
"MIT"
] | null | null | null |
ac88web/__init__.py
|
AlignedCookie88/ac88web
|
9bef4ae37acd152c55702959c1a61111b28fa47f
|
[
"MIT"
] | null | null | null |
ac88web/__init__.py
|
AlignedCookie88/ac88web
|
9bef4ae37acd152c55702959c1a61111b28fa47f
|
[
"MIT"
] | null | null | null |
from .core import run, host, aborthost, compilecode, defport, html
| 34
| 67
| 0.764706
| 9
| 68
| 5.777778
| 1
| 0
| 0
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| 0
| 0.147059
| 68
| 1
| 68
| 68
| 0.896552
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| 1
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| 1
| 0
| 1
| 0
|
0
| 5
|
2d443a9aa7f5187d03001d1b82bcca8d938fb0c0
| 92
|
py
|
Python
|
kink/errors/execution_error.py
|
dosisod/kink
|
3602a0ccca13759c574e8676ce27d5547b4b1173
|
[
"MIT"
] | 95
|
2020-04-11T09:23:04.000Z
|
2022-03-30T06:08:31.000Z
|
kink/errors/execution_error.py
|
dosisod/kink
|
3602a0ccca13759c574e8676ce27d5547b4b1173
|
[
"MIT"
] | 14
|
2020-07-09T21:10:34.000Z
|
2022-03-28T07:27:48.000Z
|
kink/errors/execution_error.py
|
dosisod/kink
|
3602a0ccca13759c574e8676ce27d5547b4b1173
|
[
"MIT"
] | 7
|
2021-04-27T07:29:41.000Z
|
2022-02-13T00:10:20.000Z
|
from .conainer_error import ContainerError
class ExecutionError(ContainerError):
pass
| 15.333333
| 42
| 0.815217
| 9
| 92
| 8.222222
| 0.888889
| 0
| 0
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| 0
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| 92
| 5
| 43
| 18.4
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| 0.333333
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| 1
| 1
| 0
| 0
| 0
|
0
| 5
|
741cbef49e7ab8da82a38b14649e0de46ce2d01a
| 134
|
py
|
Python
|
CodeHS/Functions and Exceptions/FunctionsandVariables.py
|
Kev-in123/ICS2O7
|
425c59975d4ce6aa0937fd8715b51d04487e4fa9
|
[
"MIT"
] | 2
|
2021-08-10T18:16:08.000Z
|
2021-09-26T19:49:26.000Z
|
CodeHS/Functions and Exceptions/FunctionsandVariables.py
|
Kev-in123/ICS2O7
|
425c59975d4ce6aa0937fd8715b51d04487e4fa9
|
[
"MIT"
] | null | null | null |
CodeHS/Functions and Exceptions/FunctionsandVariables.py
|
Kev-in123/ICS2O7
|
425c59975d4ce6aa0937fd8715b51d04487e4fa9
|
[
"MIT"
] | null | null | null |
"""
This program prints a variable saved in a function.
"""
def print_something():
x = 10
print(x)
print_something()
| 14.888889
| 52
| 0.626866
| 18
| 134
| 4.555556
| 0.722222
| 0.341463
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0.020202
| 0.261194
| 134
| 9
| 53
| 14.888889
| 0.808081
| 0.380597
| 0
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| 1
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| null | 0
| 0
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| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
7470789e94ce02666f5391c69441bdb5a376ef6e
| 39
|
py
|
Python
|
src/vgInitMovies.py
|
bburns/PyVoyager
|
20eea9dd445c503cd00d6a18c88af8ec93ef1c74
|
[
"MIT"
] | 6
|
2016-10-25T14:42:02.000Z
|
2021-11-30T23:38:23.000Z
|
src/vgInitMovies.py
|
bburns/PyVoyager
|
20eea9dd445c503cd00d6a18c88af8ec93ef1c74
|
[
"MIT"
] | null | null | null |
src/vgInitMovies.py
|
bburns/PyVoyager
|
20eea9dd445c503cd00d6a18c88af8ec93ef1c74
|
[
"MIT"
] | null | null | null |
# initialize the movies.csv db
| 3.9
| 30
| 0.615385
| 5
| 39
| 4.8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0.333333
| 39
| 9
| 31
| 4.333333
| 0.923077
| 0.717949
| 0
| null | 0
| null | 0
| 0
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| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
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| 1
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| null | 0
| 0
| 0
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| 0
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| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
7479c455fbcf70ddc5be78e1affc19d675b3ae86
| 148
|
py
|
Python
|
examples/lambda-feature-demo/function/main.py
|
jrzeszutek/cloudify-aws-plugin
|
59832b4ac5ddad496110085ed2e21dd36db5e9df
|
[
"Apache-2.0"
] | 13
|
2015-05-28T23:21:05.000Z
|
2022-03-20T05:38:20.000Z
|
examples/lambda-feature-demo/function/main.py
|
jrzeszutek/cloudify-aws-plugin
|
59832b4ac5ddad496110085ed2e21dd36db5e9df
|
[
"Apache-2.0"
] | 49
|
2015-01-04T16:05:34.000Z
|
2022-03-27T11:35:13.000Z
|
examples/lambda-feature-demo/function/main.py
|
jrzeszutek/cloudify-aws-plugin
|
59832b4ac5ddad496110085ed2e21dd36db5e9df
|
[
"Apache-2.0"
] | 41
|
2015-01-21T17:16:05.000Z
|
2022-03-31T06:47:48.000Z
|
'''Example Lambda package file'''
def lambda_handler(event, context):
'''Example lambda function'''
return 'Hello from Cloudify & Lambda'
| 21.142857
| 41
| 0.695946
| 17
| 148
| 6
| 0.764706
| 0.254902
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0.175676
| 148
| 6
| 42
| 24.666667
| 0.836066
| 0.344595
| 0
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| 0
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| 0.325581
| 0
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| 1
| 0.5
| false
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| 0
| 0
| 1
| 0
|
0
| 5
|
7497b5e78280107abbc88d62cb1da43f89e84f7f
| 95
|
py
|
Python
|
echecs_espoir/route/include_libs.py
|
obespoir/echecs
|
e4bb8be1d360b6c568725aee4dfe4c037a855a49
|
[
"AFL-3.0"
] | 14
|
2020-03-22T14:03:51.000Z
|
2022-02-21T09:28:39.000Z
|
echecs_espoir/route/include_libs.py
|
obespoir/echecs
|
e4bb8be1d360b6c568725aee4dfe4c037a855a49
|
[
"AFL-3.0"
] | null | null | null |
echecs_espoir/route/include_libs.py
|
obespoir/echecs
|
e4bb8be1d360b6c568725aee4dfe4c037a855a49
|
[
"AFL-3.0"
] | 7
|
2020-03-22T13:57:43.000Z
|
2022-02-21T09:30:17.000Z
|
# coding=utf-8
"""
author = jamon
"""
from route import http_handler, rpc_handler, ws_handler
| 13.571429
| 55
| 0.726316
| 14
| 95
| 4.714286
| 0.857143
| 0
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| 0
| 0.012346
| 0.147368
| 95
| 6
| 56
| 15.833333
| 0.802469
| 0.294737
| 0
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| null | 0
| 0
| 0
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| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
77a63ff530c26c24bedeff227f29c4bb9e9a9d79
| 158
|
py
|
Python
|
src/slr_helper/parsers/slr_helper_csv_parser.py
|
makrei-p/slr_helper
|
434931c4076035be25449c298b5b63ad58fa1124
|
[
"MIT"
] | null | null | null |
src/slr_helper/parsers/slr_helper_csv_parser.py
|
makrei-p/slr_helper
|
434931c4076035be25449c298b5b63ad58fa1124
|
[
"MIT"
] | null | null | null |
src/slr_helper/parsers/slr_helper_csv_parser.py
|
makrei-p/slr_helper
|
434931c4076035be25449c298b5b63ad58fa1124
|
[
"MIT"
] | null | null | null |
import pandas as pd
from .parser import Parser
class SlrHelperCsvParser(Parser):
def get_df(self, file_url: str):
return pd.read_csv(file_url)
| 17.555556
| 36
| 0.727848
| 24
| 158
| 4.625
| 0.75
| 0.126126
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.196203
| 158
| 8
| 37
| 19.75
| 0.874016
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.4
| 0.2
| 1
| 0
| 1
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| 0
| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
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| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 5
|
77c3ba5423cb9cdd87dc1a6af1d58d93d706fd88
| 8,106
|
py
|
Python
|
test/unit/test_policies.py
|
amplify-education/astroscaler
|
54d709632b28ebe6f1ec93afa97bf72a9a65f9c5
|
[
"MIT"
] | 5
|
2017-10-26T18:59:32.000Z
|
2020-01-10T18:11:15.000Z
|
test/unit/test_policies.py
|
amplify-education/astroscaler
|
54d709632b28ebe6f1ec93afa97bf72a9a65f9c5
|
[
"MIT"
] | null | null | null |
test/unit/test_policies.py
|
amplify-education/astroscaler
|
54d709632b28ebe6f1ec93afa97bf72a9a65f9c5
|
[
"MIT"
] | null | null | null |
"""Module for testing our policies"""
from unittest import TestCase
from botocore.exceptions import ClientError
from mock import MagicMock
from astroscaler.policies import SelfPolicy, AWSPolicy
MOCK_ENVIRONMENT = "mock_env"
class TestAstroscalerPolicies(TestCase):
"""Class for testing Astroscaler policies"""
def test_aws_policy_not_found(self):
""" Test that AWS Policy fails safely if its underlying policy cannot be found """
mock_client = MagicMock()
mock_client.describe_policies.side_effect = IndexError
mock_group = MagicMock()
mock_group.name = 'test group'
policy = AWSPolicy(
name='test',
client=mock_client,
monitor_name='test monitor'
)
response = policy.should_execute(group=mock_group)
self.assertFalse(response)
mock_client.describe_policies.assert_called_once_with(
AutoScalingGroupName=mock_group.name,
PolicyNames=[policy.name]
)
def test_aws_policy_not_simple(self):
""" Test that AWS Policy fails safely if its underlying policy is not simple """
mock_client = MagicMock()
mock_client.describe_policies.return_value = {
"ScalingPolicies": [
{
"PolicyType": "NotSimple",
"PolicyName": "A not so simple policy"
}
]
}
mock_group = MagicMock()
mock_group.name = 'test group'
policy = AWSPolicy(
name='test',
client=mock_client,
monitor_name='test monitor'
)
response = policy.should_execute(group=mock_group)
self.assertFalse(response)
mock_client.describe_policies.assert_called_once_with(
AutoScalingGroupName=mock_group.name,
PolicyNames=[policy.name]
)
def test_aws_policy_exact_adjustment(self):
""" Test that AWS Policy fails safely if its tries to exactly adjust to the current size """
mock_client = MagicMock()
mock_client.describe_policies.return_value = {
"ScalingPolicies": [
{
"PolicyType": "SimpleScaling",
"PolicyName": "Change nothing",
"AdjustmentType": "ExactCapacity",
"ScalingAdjustment": 1
}
]
}
mock_group = MagicMock()
mock_group.name = 'test group'
mock_group.desired_size = 1
policy = AWSPolicy(
name='test',
client=mock_client,
monitor_name='test monitor'
)
response = policy.should_execute(group=mock_group)
self.assertFalse(response)
mock_client.describe_policies.assert_called_once_with(
AutoScalingGroupName=mock_group.name,
PolicyNames=[policy.name]
)
def test_aws_policy_cannot_execute(self):
""" Test that AWS Policy handles client errors """
mock_client = MagicMock()
mock_client.execute_policy.side_effect = ClientError(
error_response={"Error": {}},
operation_name=None
)
mock_group = MagicMock()
mock_group.name = 'test group'
policy = AWSPolicy(
name='test',
client=mock_client,
monitor_name='test monitor'
)
policy.should_execute = MagicMock(return_value=True)
response = policy.execute(groups=[mock_group])
self.assertEqual(response, [])
mock_client.execute_policy.assert_called_once_with(
AutoScalingGroupName=mock_group.name,
PolicyName=policy.name,
HonorCooldown=True
)
def test_self_policy_fail_group_cooling_down(self):
""" Test that Self Policy does not execute if group is cooling """
policy = SelfPolicy(
monitor_name='test monitor',
adjustment="+5",
cooldown=60
)
mock_group = MagicMock(max_size=10, min_size=1, desired_size=5)
mock_group.is_cooling_down.return_value = True
response = policy.should_execute(group=mock_group)
self.assertFalse(response)
def test_self_policy_handles_cannot_scale(self):
""" Test that Self Policy does not explode if it cannot scale """
policy = SelfPolicy(
monitor_name='test monitor',
adjustment="+5",
cooldown=60
)
mock_group = MagicMock(max_size=10, min_size=1, desired_size=5)
response = policy.execute(groups=[mock_group])
self.assertFalse(response)
def test_self_policy_handles_exact_adjustment(self):
""" Test that Self Policy can scale to an exact number"""
policy = SelfPolicy(
monitor_name='test monitor',
adjustment="7",
cooldown=60
)
mock_group = MagicMock(max_size=10, min_size=1, desired_size=5)
mock_group.is_cooling_down.return_value = False
policy.execute(groups=[mock_group])
mock_group.resize.assert_called_once_with(7)
def test_self_policy_handles_add_exact(self):
""" Test that Self Policy can scale with a positive integer"""
policy = SelfPolicy(
monitor_name='test monitor',
adjustment="+2",
cooldown=60
)
mock_group = MagicMock(max_size=10, min_size=1, desired_size=5)
mock_group.is_cooling_down.return_value = False
policy.execute(groups=[mock_group])
mock_group.resize.assert_called_once_with(7)
def test_self_policy_handles_sub_exact(self):
""" Test that Self Policy can scale with a negative integer"""
policy = SelfPolicy(
monitor_name='test monitor',
adjustment="-2",
cooldown=60
)
mock_group = MagicMock(max_size=10, min_size=1, desired_size=5)
mock_group.is_cooling_down.return_value = False
policy.execute(groups=[mock_group])
mock_group.resize.assert_called_once_with(3)
def test_self_policy_handles_add_percent(self):
""" Test that Self Policy can scale with a positive percentage"""
policy = SelfPolicy(
monitor_name='test monitor',
adjustment="+20%",
cooldown=60
)
mock_group = MagicMock(max_size=10, min_size=1, desired_size=5)
mock_group.is_cooling_down.return_value = False
policy.execute(groups=[mock_group])
mock_group.resize.assert_called_once_with(6)
def test_self_policy_handles_sub_percent(self):
""" Test that Self Policy can scale with a negative percentage"""
policy = SelfPolicy(
monitor_name='test monitor',
adjustment="-20%",
cooldown=60
)
mock_group = MagicMock(max_size=10, min_size=1, desired_size=5)
mock_group.is_cooling_down.return_value = False
policy.execute(groups=[mock_group])
mock_group.resize.assert_called_once_with(4)
def test_self_policy_handles_exact_percent(self):
""" Test that Self Policy can scale with an exact percentage"""
policy = SelfPolicy(
monitor_name='test monitor',
adjustment="20%",
cooldown=60
)
mock_group = MagicMock(max_size=10, min_size=1, desired_size=5)
mock_group.is_cooling_down.return_value = False
policy.execute(groups=[mock_group])
mock_group.resize.assert_called_once_with(6)
def test_self_policy_handles_nonsense(self):
""" Test that Self Policy does not explode with a nonsense adjustment"""
policy = SelfPolicy(
monitor_name='test monitor',
adjustment="dsafasd",
cooldown=60
)
mock_group = MagicMock(max_size=10, min_size=1, desired_size=5)
mock_group.is_cooling_down.return_value = False
policy.execute(groups=[mock_group])
mock_group.resize.assert_not_called()
| 30.588679
| 100
| 0.621021
| 900
| 8,106
| 5.32
| 0.136667
| 0.093985
| 0.032581
| 0.059733
| 0.822264
| 0.798037
| 0.783417
| 0.727652
| 0.693191
| 0.676901
| 0
| 0.012756
| 0.29398
| 8,106
| 264
| 101
| 30.704545
| 0.823869
| 0.107698
| 0
| 0.60221
| 0
| 0
| 0.059351
| 0
| 0
| 0
| 0
| 0
| 0.093923
| 1
| 0.071823
| false
| 0
| 0.022099
| 0
| 0.099448
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
7accfbdec6b8371a7c01ed5a1db58f99be40c2e8
| 115
|
py
|
Python
|
templates/toto/chat/eventserver.py
|
VNUELIVE/Toto
|
6940b4114fc6b680e0d40ae248b7d2599c954f81
|
[
"MIT"
] | null | null | null |
templates/toto/chat/eventserver.py
|
VNUELIVE/Toto
|
6940b4114fc6b680e0d40ae248b7d2599c954f81
|
[
"MIT"
] | null | null | null |
templates/toto/chat/eventserver.py
|
VNUELIVE/Toto
|
6940b4114fc6b680e0d40ae248b7d2599c954f81
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
import toto.server
if __name__ == "__main__":
toto.server.TotoServer('event.conf').run()
| 16.428571
| 44
| 0.704348
| 16
| 115
| 4.5625
| 0.875
| 0.273973
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.113043
| 115
| 6
| 45
| 19.166667
| 0.715686
| 0.173913
| 0
| 0
| 0
| 0
| 0.191489
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
7ae5dd25ec2055499d34e82081783acdc6a9b532
| 24
|
py
|
Python
|
python/task/__init__.py
|
SasCezar/sling
|
809e21a9986d2522d5014b5836ba222498c099a2
|
[
"Apache-2.0"
] | null | null | null |
python/task/__init__.py
|
SasCezar/sling
|
809e21a9986d2522d5014b5836ba222498c099a2
|
[
"Apache-2.0"
] | null | null | null |
python/task/__init__.py
|
SasCezar/sling
|
809e21a9986d2522d5014b5836ba222498c099a2
|
[
"Apache-2.0"
] | null | null | null |
from workflow import *
| 8
| 22
| 0.75
| 3
| 24
| 6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.208333
| 24
| 2
| 23
| 12
| 0.947368
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
7af569bd1bee9f730e7d6c38607c3f158c5531ed
| 302
|
py
|
Python
|
fly/exceptions.py
|
beyond-heshipeng/fly
|
40033120157849572f2d93bd73c03df4d7432bcb
|
[
"Apache-2.0"
] | null | null | null |
fly/exceptions.py
|
beyond-heshipeng/fly
|
40033120157849572f2d93bd73c03df4d7432bcb
|
[
"Apache-2.0"
] | null | null | null |
fly/exceptions.py
|
beyond-heshipeng/fly
|
40033120157849572f2d93bd73c03df4d7432bcb
|
[
"Apache-2.0"
] | null | null | null |
class InvalidRequestMethodErr(Exception):
pass
class InvalidDownloadMiddlewareErr(Exception):
pass
class InvalidMiddlewareErr(Exception):
pass
class QueueEmptyErr(Exception):
pass
class InvalidDownloaderErr(Exception):
pass
class UnhandledDownloadErr(Exception):
pass
| 13.130435
| 46
| 0.768212
| 24
| 302
| 9.666667
| 0.375
| 0.336207
| 0.387931
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.172185
| 302
| 22
| 47
| 13.727273
| 0.928
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
bb04b32773728a169819e821646fe6300113d363
| 35
|
py
|
Python
|
BasicExerciseAndKnowledge/w3cschool/n85.py
|
Jonathan1214/learn-python
|
19d0299b30e953069f19402bff5c464c4d5580be
|
[
"MIT"
] | null | null | null |
BasicExerciseAndKnowledge/w3cschool/n85.py
|
Jonathan1214/learn-python
|
19d0299b30e953069f19402bff5c464c4d5580be
|
[
"MIT"
] | null | null | null |
BasicExerciseAndKnowledge/w3cschool/n85.py
|
Jonathan1214/learn-python
|
19d0299b30e953069f19402bff5c464c4d5580be
|
[
"MIT"
] | null | null | null |
#coding:utf-8
# 题目：判断一个素数能被几个9整除
| 7
| 18
| 0.714286
| 5
| 35
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.066667
| 0.142857
| 35
| 4
| 19
| 8.75
| 0.766667
| 0.828571
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
bb06b0c109c21fdb45720ee6b6b73855423dd965
| 320
|
py
|
Python
|
lightnlp/utils/score_func.py
|
CNLPT/lightNLP
|
c7f128422ba5b16f514bb294145cb3b562e95829
|
[
"Apache-2.0"
] | 889
|
2019-03-11T00:58:46.000Z
|
2022-03-27T07:12:06.000Z
|
lightnlp/utils/score_func.py
|
CNLPT/lightNLP
|
c7f128422ba5b16f514bb294145cb3b562e95829
|
[
"Apache-2.0"
] | 14
|
2019-03-25T09:21:38.000Z
|
2020-12-28T11:41:55.000Z
|
lightnlp/utils/score_func.py
|
CNLPT/lightNLP
|
c7f128422ba5b16f514bb294145cb3b562e95829
|
[
"Apache-2.0"
] | 237
|
2019-03-19T08:30:17.000Z
|
2022-03-14T03:38:30.000Z
|
import torch
import torch.nn as nn
import torch.nn.functional as F
p1 = torch.nn.PairwiseDistance(p=1)
p2 = torch.nn.PairwiseDistance(p=2)
def l1_score(vec1, vec2):
return p1(vec1, vec2)
def l2_score(vec1, vec2):
return p2(vec1, vec2)
def cos_score(vec1, vec2):
return F.cosine_similarity(vec1, vec2)
| 16.842105
| 42
| 0.71875
| 54
| 320
| 4.185185
| 0.407407
| 0.212389
| 0.172566
| 0.252212
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.074906
| 0.165625
| 320
| 18
| 43
| 17.777778
| 0.771536
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.272727
| false
| 0
| 0.272727
| 0.272727
| 0.818182
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
bb26f1916349153e55ef59af70338c1863620de9
| 105
|
py
|
Python
|
animal.py
|
zhiranyan/AVOD-BottleneckLstm
|
87e4597ba1f301d35f568f6abf577d19e805d6a4
|
[
"MIT"
] | 1
|
2021-08-19T16:26:34.000Z
|
2021-08-19T16:26:34.000Z
|
animal.py
|
zhiranyan/AVOD-BottleneckLstm
|
87e4597ba1f301d35f568f6abf577d19e805d6a4
|
[
"MIT"
] | null | null | null |
animal.py
|
zhiranyan/AVOD-BottleneckLstm
|
87e4597ba1f301d35f568f6abf577d19e805d6a4
|
[
"MIT"
] | null | null | null |
class Animal():
def __init__(self,name):
self.name =name
#a = Animal("dog")
#print(a.name)
| 15
| 26
| 0.590476
| 15
| 105
| 3.866667
| 0.6
| 0.275862
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.228571
| 105
| 6
| 27
| 17.5
| 0.716049
| 0.285714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
bb32484bbbbdc4cd8c84f2fe98da6fbb54298f7e
| 60
|
py
|
Python
|
sinfer/__init__.py
|
geoyee/SlideInfer
|
1f790f895f66b6322c5d337ef16a30393cfa41ed
|
[
"Apache-2.0"
] | 4
|
2022-03-28T15:58:34.000Z
|
2022-03-31T16:00:36.000Z
|
sinfer/__init__.py
|
geoyee/SlideInfer
|
1f790f895f66b6322c5d337ef16a30393cfa41ed
|
[
"Apache-2.0"
] | null | null | null |
sinfer/__init__.py
|
geoyee/SlideInfer
|
1f790f895f66b6322c5d337ef16a30393cfa41ed
|
[
"Apache-2.0"
] | null | null | null |
from .task import SegSlider, DetSlider, ClsSlider, GanSlider
| 60
| 60
| 0.833333
| 7
| 60
| 7.142857
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 60
| 1
| 60
| 60
| 0.925926
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
bb54b726adf00afe066b54a2033288efbb4e060f
| 1,282
|
py
|
Python
|
mayan/apps/document_states/migrations/0026_auto_20220305_1702.py
|
ercusz/Mayan-EDMS
|
46accc39f3f252c43b8d9d2b19478ae7f13bd11d
|
[
"Apache-2.0"
] | null | null | null |
mayan/apps/document_states/migrations/0026_auto_20220305_1702.py
|
ercusz/Mayan-EDMS
|
46accc39f3f252c43b8d9d2b19478ae7f13bd11d
|
[
"Apache-2.0"
] | null | null | null |
mayan/apps/document_states/migrations/0026_auto_20220305_1702.py
|
ercusz/Mayan-EDMS
|
46accc39f3f252c43b8d9d2b19478ae7f13bd11d
|
[
"Apache-2.0"
] | null | null | null |
# Generated by Django 2.2.24 on 2022-03-05 17:02
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('document_states', '0025_auto_20220305_1636'),
]
operations = [
migrations.AddField(
model_name='workflow',
name='end_datetime',
field=models.DateTimeField(blank=True, help_text='Date and time for this workflow is deactivated.', null=True, verbose_name='End Date'),
),
migrations.AddField(
model_name='workflow',
name='start_datetime',
field=models.DateTimeField(blank=True, help_text='Date and time for this workflow is activated.', null=True, verbose_name='Start Date'),
),
migrations.AlterField(
model_name='workflowstate',
name='end_datetime',
field=models.DateTimeField(blank=True, help_text='Date and time for this state is deactivated.', null=True, verbose_name='End Date'),
),
migrations.AlterField(
model_name='workflowstate',
name='start_datetime',
field=models.DateTimeField(blank=True, help_text='Date and time for this state is activated.', null=True, verbose_name='Start Date'),
),
]
| 37.705882
| 148
| 0.634945
| 146
| 1,282
| 5.438356
| 0.356164
| 0.04534
| 0.095718
| 0.161209
| 0.801008
| 0.801008
| 0.725441
| 0.632242
| 0.539043
| 0.420655
| 0
| 0.033473
| 0.25429
| 1,282
| 33
| 149
| 38.848485
| 0.797071
| 0.035881
| 0
| 0.592593
| 1
| 0
| 0.280389
| 0.018639
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.037037
| 0
| 0.148148
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
24a193dffdaa77b8887eac4b9439b1f6bc910ded
| 55
|
py
|
Python
|
springlib/__init__.py
|
iChunyu/LearnPython
|
dc46845da83e068d44a7b9a544af31436dde9ae2
|
[
"MIT"
] | 2
|
2022-02-15T07:28:16.000Z
|
2022-02-15T07:28:38.000Z
|
springlib/__init__.py
|
iChunyu/LearnPython
|
dc46845da83e068d44a7b9a544af31436dde9ae2
|
[
"MIT"
] | null | null | null |
springlib/__init__.py
|
iChunyu/LearnPython
|
dc46845da83e068d44a7b9a544af31436dde9ae2
|
[
"MIT"
] | null | null | null |
from .lpsd import lpsd
from .rmImpulse import rmImpulse
| 27.5
| 32
| 0.836364
| 8
| 55
| 5.75
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.127273
| 55
| 2
| 32
| 27.5
| 0.958333
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
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| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
24dcef4c266d043cad8bd3af84697825be5fbe13
| 164
|
py
|
Python
|
mikelint/utils/__init__.py
|
mike-fam/mikelint
|
4e512039d11e9bbfde18a8cadcbc4608295e663f
|
[
"MIT"
] | 2
|
2021-04-27T01:13:37.000Z
|
2021-05-21T02:28:24.000Z
|
mikelint/utils/__init__.py
|
mike-fam/mikelint
|
4e512039d11e9bbfde18a8cadcbc4608295e663f
|
[
"MIT"
] | 3
|
2021-05-05T10:21:25.000Z
|
2021-05-30T12:51:43.000Z
|
mikelint/utils/__init__.py
|
mike-fam/mikelint
|
4e512039d11e9bbfde18a8cadcbc4608295e663f
|
[
"MIT"
] | null | null | null |
from .strings import indent, new_line
from .tree import SyntaxTree
from .violation import ViolationResult, BaseViolation
from .encoders import DataclassJsonEncoder
| 32.8
| 53
| 0.853659
| 19
| 164
| 7.315789
| 0.684211
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109756
| 164
| 4
| 54
| 41
| 0.952055
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
24def393fd7663279dfd13b7c6f60f38620f5122
| 2,239
|
py
|
Python
|
src/app_util/http_s.py
|
jnsougata/app_util
|
941421523d38973486321f26b38aa4735ca0a9b2
|
[
"MIT"
] | 2
|
2022-01-31T02:43:59.000Z
|
2022-02-06T12:32:06.000Z
|
src/app_util/http_s.py
|
jnsougata/app_util
|
941421523d38973486321f26b38aa4735ca0a9b2
|
[
"MIT"
] | null | null | null |
src/app_util/http_s.py
|
jnsougata/app_util
|
941421523d38973486321f26b38aa4735ca0a9b2
|
[
"MIT"
] | null | null | null |
import discord
from discord.http import Route
async def post_command(client, command, guild_id: int = None):
if guild_id:
r = Route('POST', f'/applications/{client.application_id}/guilds/{guild_id}/commands')
else:
r = Route('POST', f'/applications/{client.application_id}/commands')
return await client.http.request(r, json=command.to_dict())
async def patch_existing_command(client, old, new):
if old.guild_specific:
r = Route('PATCH', f'/applications/{old.application_id}/guilds/{old.guild_id}/commands/{old.id}')
else:
r = Route('PATCH', f'/applications/{old.application_id}/commands/{old.id}')
return await client.http.request(r, json=new.to_dict())
async def fetch_any_command(client, command_id: int, guild_id: int = None):
if guild_id:
r = Route('GET', f'/applications/{client.application_id}/guilds/{guild_id}/commands/{command_id}')
else:
r = Route('GET', f'/applications/{client.application_id}/commands/{command_id}')
return await client.http.request(r)
async def fetch_global_commands(client):
r = Route('GET', f'/applications/{client.application_id}/commands')
return await client.http.request(r)
async def fetch_guild_commands(client, guild_id: int):
r = Route('GET', f'/applications/{client.application_id}/guilds/{guild_id}/commands')
return await client.http.request(r)
async def fetch_overwrites(client, command_id: int, guild_id: int):
r = Route('GET', f'/applications/{client.application_id}/guilds/{guild_id}/commands/{command_id}/permissions')
return await client.http.request(r)
async def put_overwrites(client, command_id: int, guild_id: int, overwrites: dict):
r = Route('PUT',
f'/applications/{client.application_id}/guilds/{guild_id}/commands/{command_id}/permissions')
return await client.http.request(r, json=overwrites)
async def delete_command(client, command_id: int, guild_id: int = None):
if guild_id:
r = Route('DELETE', f'/applications/{client.application_id}/guilds/{guild_id}/commands/{command_id}')
else:
r = Route('DELETE', f'/applications/{client.application_id}/commands/{command_id}')
return await client.http.request(r)
| 39.982143
| 114
| 0.708352
| 312
| 2,239
| 4.913462
| 0.13141
| 0.073059
| 0.12394
| 0.195695
| 0.801696
| 0.801696
| 0.801696
| 0.773646
| 0.65623
| 0.586432
| 0
| 0
| 0.143814
| 2,239
| 55
| 115
| 40.709091
| 0.799687
| 0
| 0
| 0.307692
| 0
| 0
| 0.376954
| 0.355516
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.051282
| 0
| 0.25641
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
24e369ec77b47f9a254a434c58816455be211136
| 54
|
py
|
Python
|
payments/models/__init__.py
|
Shopyangu-engineering/Shopyangu-Payments
|
2a9d0b4583f2b8cc473c6e2b3a36bc4aad1194bb
|
[
"BSD-3-Clause"
] | null | null | null |
payments/models/__init__.py
|
Shopyangu-engineering/Shopyangu-Payments
|
2a9d0b4583f2b8cc473c6e2b3a36bc4aad1194bb
|
[
"BSD-3-Clause"
] | null | null | null |
payments/models/__init__.py
|
Shopyangu-engineering/Shopyangu-Payments
|
2a9d0b4583f2b8cc473c6e2b3a36bc4aad1194bb
|
[
"BSD-3-Clause"
] | null | null | null |
from .mpesa_models import MpesaExpressRequest # noqa
| 27
| 53
| 0.833333
| 6
| 54
| 7.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12963
| 54
| 1
| 54
| 54
| 0.93617
| 0.074074
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
7000a6449ddd82338654e726a7573a82891357bb
| 103
|
py
|
Python
|
src/jacho/recurrent_kernel/__init__.py
|
GJBoth/jacho
|
5140010048035056ba83bf65d498ae2ee9709ca9
|
[
"MIT"
] | 4
|
2021-09-30T09:04:21.000Z
|
2021-10-11T11:51:20.000Z
|
src/jacho/recurrent_kernel/__init__.py
|
GJBoth/jacho
|
5140010048035056ba83bf65d498ae2ee9709ca9
|
[
"MIT"
] | null | null | null |
src/jacho/recurrent_kernel/__init__.py
|
GJBoth/jacho
|
5140010048035056ba83bf65d498ae2ee9709ca9
|
[
"MIT"
] | null | null | null |
from .recurrent_kernel import RecurrentKernel
from .kernels import erf_kernel
from .train import train
| 25.75
| 45
| 0.854369
| 14
| 103
| 6.142857
| 0.571429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116505
| 103
| 3
| 46
| 34.333333
| 0.945055
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
701b40c8c4422cb9d5793d9ec3bbb9925906b1ea
| 35
|
py
|
Python
|
survos2/frontend/qtcompat.py
|
DiamondLightSource/SuRVoS2
|
42bacfb6a5cc267f38ca1337e51a443eae1a9d2b
|
[
"MIT"
] | 4
|
2017-10-10T14:47:16.000Z
|
2022-01-14T05:57:50.000Z
|
survos2/frontend/qtcompat.py
|
DiamondLightSource/SuRVoS2
|
42bacfb6a5cc267f38ca1337e51a443eae1a9d2b
|
[
"MIT"
] | 1
|
2022-01-11T21:11:12.000Z
|
2022-01-12T08:22:34.000Z
|
survos2/frontend/qtcompat.py
|
DiamondLightSource/SuRVoS2
|
42bacfb6a5cc267f38ca1337e51a443eae1a9d2b
|
[
"MIT"
] | 2
|
2018-03-06T06:31:29.000Z
|
2019-03-04T03:33:18.000Z
|
try:
pass
except:
pass
| 7
| 9
| 0.485714
| 4
| 35
| 4.25
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.457143
| 35
| 4
| 10
| 8.75
| 0.894737
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
7040c6035dc796b22e46b88aaa56839d3fa91d25
| 47
|
py
|
Python
|
src/Python/helloworld.py
|
t-gok/Hacktoberfest
|
2c9385f7b43242c962aa2499cc404ed9419b2a33
|
[
"MIT"
] | 1
|
2019-02-26T18:49:01.000Z
|
2019-02-26T18:49:01.000Z
|
src/Python/helloworld.py
|
t-gok/Hacktoberfest
|
2c9385f7b43242c962aa2499cc404ed9419b2a33
|
[
"MIT"
] | null | null | null |
src/Python/helloworld.py
|
t-gok/Hacktoberfest
|
2c9385f7b43242c962aa2499cc404ed9419b2a33
|
[
"MIT"
] | null | null | null |
print ("Hello World");
print ("Privet Mir!");
| 11.75
| 22
| 0.617021
| 6
| 47
| 4.833333
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148936
| 47
| 3
| 23
| 15.666667
| 0.725
| 0
| 0
| 0
| 0
| 0
| 0.478261
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
70651662784d866acd83cc4a6e7e007df3f813d8
| 21
|
py
|
Python
|
rl/A3C_2_actors/__init__.py
|
apersonnaz/rl-guided-galaxy-exploration
|
639ae2285429c95394c3dcd566947f5691b6c673
|
[
"MIT"
] | null | null | null |
rl/A3C_2_actors/__init__.py
|
apersonnaz/rl-guided-galaxy-exploration
|
639ae2285429c95394c3dcd566947f5691b6c673
|
[
"MIT"
] | null | null | null |
rl/A3C_2_actors/__init__.py
|
apersonnaz/rl-guided-galaxy-exploration
|
639ae2285429c95394c3dcd566947f5691b6c673
|
[
"MIT"
] | 1
|
2021-03-04T07:25:02.000Z
|
2021-03-04T07:25:02.000Z
|
# from .A3C import *
| 10.5
| 20
| 0.619048
| 3
| 21
| 4.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.0625
| 0.238095
| 21
| 1
| 21
| 21
| 0.75
| 0.857143
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
707335f903f8b001c100edb6227d6d61077d00a5
| 200
|
py
|
Python
|
pythonFiles/src/utils.py
|
jendrikjoe/vscode-importmagic
|
051dcf6df3092f6cf242ffc5ffc788ee7b440997
|
[
"MIT"
] | 39
|
2018-04-13T08:34:36.000Z
|
2021-11-24T09:55:48.000Z
|
pythonFiles/src/utils.py
|
jendrikjoe/vscode-importmagic
|
051dcf6df3092f6cf242ffc5ffc788ee7b440997
|
[
"MIT"
] | 26
|
2018-06-21T09:46:11.000Z
|
2021-10-05T23:33:14.000Z
|
pythonFiles/src/utils.py
|
jendrikjoe/vscode-importmagic
|
051dcf6df3092f6cf242ffc5ffc788ee7b440997
|
[
"MIT"
] | 11
|
2018-08-05T21:43:30.000Z
|
2022-02-24T14:57:51.000Z
|
from hashlib import md5
import json
def md5_hash(v):
return md5(v.encode()).hexdigest()
def pipeout(pipe, response):
pipe.write(json.dumps(response))
pipe.write('\n')
pipe.flush()
| 15.384615
| 38
| 0.67
| 29
| 200
| 4.586207
| 0.62069
| 0.180451
| 0.255639
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018293
| 0.18
| 200
| 12
| 39
| 16.666667
| 0.792683
| 0
| 0
| 0
| 0
| 0
| 0.01
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0.125
| 0.625
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
7087f6439237ffe83f7a0cc1ba3542ca67b47dec
| 268
|
py
|
Python
|
inc_search/exceptions.py
|
nguyentritai2906/inc_search
|
b6def2ddf3d8635127d4bfa210ec132a93cb8454
|
[
"MIT"
] | null | null | null |
inc_search/exceptions.py
|
nguyentritai2906/inc_search
|
b6def2ddf3d8635127d4bfa210ec132a93cb8454
|
[
"MIT"
] | null | null | null |
inc_search/exceptions.py
|
nguyentritai2906/inc_search
|
b6def2ddf3d8635127d4bfa210ec132a93cb8454
|
[
"MIT"
] | 2
|
2021-05-12T06:56:36.000Z
|
2021-05-12T06:57:08.000Z
|
class LexpyError(Exception):
pass
class InvalidWildCardExpressionError(LexpyError):
def __init__(self, expr, message):
self.expr = expr
self.message = message
def __str__(self):
return repr(': '.join([self.message, self.expr]))
| 20.615385
| 57
| 0.656716
| 28
| 268
| 6
| 0.5
| 0.142857
| 0.178571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.227612
| 268
| 12
| 58
| 22.333333
| 0.811594
| 0
| 0
| 0
| 0
| 0
| 0.007463
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0.125
| 0
| 0.125
| 0.625
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 5
|
5639eff97bbf568b2ad10330ffd42599b264288e
| 110
|
py
|
Python
|
flypy/runtime/interfaces/__init__.py
|
filmackay/flypy
|
d64e70959c5c8af9e914dcc3ce1068fb99859c3a
|
[
"BSD-2-Clause"
] | null | null | null |
flypy/runtime/interfaces/__init__.py
|
filmackay/flypy
|
d64e70959c5c8af9e914dcc3ce1068fb99859c3a
|
[
"BSD-2-Clause"
] | null | null | null |
flypy/runtime/interfaces/__init__.py
|
filmackay/flypy
|
d64e70959c5c8af9e914dcc3ce1068fb99859c3a
|
[
"BSD-2-Clause"
] | 1
|
2020-01-01T00:43:24.000Z
|
2020-01-01T00:43:24.000Z
|
from .interface import copy_methods
from .numbers import *
from .iterables import Iterable, Iterator, Sequence
| 36.666667
| 51
| 0.827273
| 14
| 110
| 6.428571
| 0.714286
| 0
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| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0.118182
| 110
| 3
| 51
| 36.666667
| 0.927835
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| null | 0
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| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
568234ca8fc4b2930d0d2c98f37986ae7f3b17db
| 203
|
py
|
Python
|
pyfitter/__init__.py
|
Fassial/pytools
|
bb8691206b58deb57d8043a8ba4dfab2019383fb
|
[
"MIT"
] | null | null | null |
pyfitter/__init__.py
|
Fassial/pytools
|
bb8691206b58deb57d8043a8ba4dfab2019383fb
|
[
"MIT"
] | null | null | null |
pyfitter/__init__.py
|
Fassial/pytools
|
bb8691206b58deb57d8043a8ba4dfab2019383fb
|
[
"MIT"
] | null | null | null |
"""
Created on 21:13, Oct. 14th, 2021
Author: fassial
Filename: __init__.py
"""
# import fitter
from .fitter import Fitter, get_distributions, get_common_distributions
# import stats
from . import stats
| 20.3
| 71
| 0.768473
| 28
| 203
| 5.321429
| 0.678571
| 0.161074
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| 0.137931
| 203
| 9
| 72
| 22.555556
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| 1
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| 1
| 0
|
0
| 5
|
568dca8f2fd71e60407feb77e5e6d211a6b5e896
| 263
|
py
|
Python
|
built-in/TensorFlow/Official/cv/image_classification/ResnetVariant_for_TensorFlow/automl/vega/core/pipeline/__init__.py
|
Huawei-Ascend/modelzoo
|
df51ed9c1d6dbde1deef63f2a037a369f8554406
|
[
"Apache-2.0"
] | 12
|
2020-12-13T08:34:24.000Z
|
2022-03-20T15:17:17.000Z
|
built-in/TensorFlow/Official/cv/image_classification/ResnetVariant_for_TensorFlow/automl/vega/core/pipeline/__init__.py
|
Huawei-Ascend/modelzoo
|
df51ed9c1d6dbde1deef63f2a037a369f8554406
|
[
"Apache-2.0"
] | 3
|
2021-03-31T20:15:40.000Z
|
2022-02-09T23:50:46.000Z
|
built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/core/pipeline/__init__.py
|
Huawei-Ascend/modelzoo
|
df51ed9c1d6dbde1deef63f2a037a369f8554406
|
[
"Apache-2.0"
] | 2
|
2021-07-10T12:40:46.000Z
|
2021-12-17T07:55:15.000Z
|
# -*- coding:utf-8 -*-
from .pipe_step import PipeStep
from .nas_pipe_step import NasPipeStep
from .pipeline import Pipeline
from .generator import Generator
from .fully_train_pipe_step import FullyTrainPipeStep
from .benchmark_pipe_step import BenchmarkPipeStep
| 32.875
| 53
| 0.836502
| 35
| 263
| 6.057143
| 0.485714
| 0.150943
| 0.264151
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004255
| 0.106464
| 263
| 7
| 54
| 37.571429
| 0.897872
| 0.076046
| 0
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| true
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
3b47b6f01335854e83151cecdc2c8734126cc6c4
| 62
|
py
|
Python
|
main.py
|
fakegit/pyrobud
|
9626d534dc65b1cb4f93590a49c606c93b82a4e1
|
[
"MIT"
] | 2
|
2019-10-24T03:37:33.000Z
|
2019-12-23T02:09:10.000Z
|
main.py
|
fakegit/pyrobud
|
9626d534dc65b1cb4f93590a49c606c93b82a4e1
|
[
"MIT"
] | 15
|
2021-12-22T13:53:46.000Z
|
2022-03-31T17:44:03.000Z
|
main.py
|
fakegit/pyrobud
|
9626d534dc65b1cb4f93590a49c606c93b82a4e1
|
[
"MIT"
] | 1
|
2020-05-30T20:22:32.000Z
|
2020-05-30T20:22:32.000Z
|
#!/usr/bin/env python3
from pyrobud import main
main.main()
| 10.333333
| 24
| 0.725806
| 10
| 62
| 4.5
| 0.8
| 0.355556
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018868
| 0.145161
| 62
| 5
| 25
| 12.4
| 0.830189
| 0.33871
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| 1
| 0
| 0
| 0
|
0
| 5
|
3b837f00ccf7d5422667f905688a83ebca531ce2
| 276
|
py
|
Python
|
core/systems/__init__.py
|
athindran/ProBF
|
a7961dd88568615f363fb264bc89ec526d8c1b28
|
[
"MIT"
] | null | null | null |
core/systems/__init__.py
|
athindran/ProBF
|
a7961dd88568615f363fb264bc89ec526d8c1b28
|
[
"MIT"
] | null | null | null |
core/systems/__init__.py
|
athindran/ProBF
|
a7961dd88568615f363fb264bc89ec526d8c1b28
|
[
"MIT"
] | null | null | null |
from .cart_pole import CartPole
from .double_inverted_pendulum import DoubleInvertedPendulum
from .inverted_pendulum import InvertedPendulum
from .planar_quadrotor import PlanarQuadrotor
from .segway import Segway
from .dubins import Dubins
from .RoboticArm import RoboticArm
| 34.5
| 60
| 0.873188
| 33
| 276
| 7.151515
| 0.484848
| 0.135593
| 0.186441
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.101449
| 276
| 7
| 61
| 39.428571
| 0.951613
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
8ea0fd48025681652e200d389a8e6aceea6a741a
| 168
|
py
|
Python
|
pics/admin.py
|
devseme/Gallery
|
25ff09967992db4de310cd39ab04ac637035b929
|
[
"MIT"
] | null | null | null |
pics/admin.py
|
devseme/Gallery
|
25ff09967992db4de310cd39ab04ac637035b929
|
[
"MIT"
] | null | null | null |
pics/admin.py
|
devseme/Gallery
|
25ff09967992db4de310cd39ab04ac637035b929
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import photos,Category,Location
admin.site.register(photos)
admin.site.register(Category)
admin.site.register(Location)
| 21
| 44
| 0.827381
| 23
| 168
| 6.043478
| 0.478261
| 0.194245
| 0.366906
| 0
| 0
| 0
| 0
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| 0
| 0
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| 0.077381
| 168
| 7
| 45
| 24
| 0.896774
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| 0
| 0
|
0
| 5
|
d90c533551eac6d629999d0859054d985388142f
| 4,275
|
py
|
Python
|
tests/client/test_client_tenant_token.py
|
Luzkan/meilisearch-python
|
f9d5fa25f3a77c6a35454c45537635ba7b9abb4d
|
[
"MIT"
] | null | null | null |
tests/client/test_client_tenant_token.py
|
Luzkan/meilisearch-python
|
f9d5fa25f3a77c6a35454c45537635ba7b9abb4d
|
[
"MIT"
] | null | null | null |
tests/client/test_client_tenant_token.py
|
Luzkan/meilisearch-python
|
f9d5fa25f3a77c6a35454c45537635ba7b9abb4d
|
[
"MIT"
] | null | null | null |
# pylint: disable=invalid-name
from re import search
import pytest
import meilisearch
from tests import BASE_URL, MASTER_KEY
from meilisearch.errors import MeiliSearchApiError
import datetime
def test_generate_tenant_token_with_search_rules(get_private_key, index_with_documents):
"""Tests create a tenant token with only search rules."""
index_with_documents()
client = meilisearch.Client(BASE_URL, get_private_key['key'])
token = client.generate_tenant_token(search_rules=["*"])
token_client = meilisearch.Client(BASE_URL, token)
response = token_client.index('indexUID').search('', {
'limit': 5
})
assert isinstance(response, dict)
assert len(response['hits']) == 5
assert response['query'] == ''
def test_generate_tenant_token_with_search_rules_on_one_index(get_private_key, empty_index):
"""Tests create a tenant token with search rules set for one index."""
empty_index()
empty_index('tenant_token')
client = meilisearch.Client(BASE_URL, get_private_key['key'])
token = client.generate_tenant_token(search_rules=['indexUID'])
token_client = meilisearch.Client(BASE_URL, token)
response = token_client.index('indexUID').search('')
assert isinstance(response, dict)
assert response['query'] == ''
with pytest.raises(MeiliSearchApiError):
response = token_client.index('tenant_token').search('')
def test_generate_tenant_token_with_api_key(client, get_private_key, empty_index):
"""Tests create a tenant token with search rules and an api key."""
empty_index()
token = client.generate_tenant_token(search_rules=["*"], api_key=get_private_key['key'])
token_client = meilisearch.Client(BASE_URL, token)
response = token_client.index('indexUID').search('')
assert isinstance(response, dict)
assert response['query'] == ''
def test_generate_tenant_token_with_expires_at(client, get_private_key, empty_index):
"""Tests create a tenant token with search rules and expiration date."""
empty_index()
client = meilisearch.Client(BASE_URL, get_private_key['key'])
tomorrow = datetime.datetime.utcnow() + datetime.timedelta(days=1)
token = client.generate_tenant_token(search_rules=["*"], expires_at=tomorrow)
token_client = meilisearch.Client(BASE_URL, token)
response = token_client.index('indexUID').search('')
assert isinstance(response, dict)
assert response['query'] == ''
def test_generate_tenant_token_with_empty_search_rules_in_list(get_private_key):
"""Tests create a tenant token without search rules."""
client = meilisearch.Client(BASE_URL, get_private_key['key'])
with pytest.raises(Exception):
client.generate_tenant_token(search_rules=[''])
def test_generate_tenant_token_without_search_rules_in_list(get_private_key):
"""Tests create a tenant token without search rules."""
client = meilisearch.Client(BASE_URL, get_private_key['key'])
with pytest.raises(Exception):
client.generate_tenant_token(search_rules=[])
def test_generate_tenant_token_without_search_rules_in_dict(get_private_key):
"""Tests create a tenant token without search rules."""
client = meilisearch.Client(BASE_URL, get_private_key['key'])
with pytest.raises(Exception):
client.generate_tenant_token(search_rules={})
def test_generate_tenant_token_with_empty_search_rules_in_dict(get_private_key):
"""Tests create a tenant token without search rules."""
client = meilisearch.Client(BASE_URL, get_private_key['key'])
with pytest.raises(Exception):
client.generate_tenant_token(search_rules={''})
def test_generate_tenant_token_with_bad_expires_at(client, get_private_key):
"""Tests create a tenant token with a bad expires at."""
client = meilisearch.Client(BASE_URL, get_private_key['key'])
yesterday = datetime.datetime.utcnow() + datetime.timedelta(days=-1)
with pytest.raises(Exception):
client.generate_tenant_token(search_rules=["*"], expires_at=yesterday)
def test_generate_tenant_token_with_no_api_key(client):
"""Tests create a tenant token with no api key."""
client = meilisearch.Client(BASE_URL)
with pytest.raises(Exception):
client.generate_tenant_token(search_rules=["*"])
| 39.953271
| 92
| 0.746433
| 561
| 4,275
| 5.365419
| 0.121212
| 0.116944
| 0.126246
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| 0.819269
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| 0.711296
| 0.66412
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| 106
| 93
| 40.330189
| 0.819297
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| 0
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|
0
| 5
|
d91327f9011bf8361bf2bfe10ce309092b019272
| 71
|
py
|
Python
|
hako/codegen/__init__.py
|
hsfzxjy/hako
|
820fc4dbed831bfc6ad23acf783229b1d9f8b6a4
|
[
"Apache-2.0"
] | 2
|
2021-12-19T04:57:28.000Z
|
2021-12-22T05:32:51.000Z
|
hako/codegen/__init__.py
|
hsfzxjy/hako
|
820fc4dbed831bfc6ad23acf783229b1d9f8b6a4
|
[
"Apache-2.0"
] | null | null | null |
hako/codegen/__init__.py
|
hsfzxjy/hako
|
820fc4dbed831bfc6ad23acf783229b1d9f8b6a4
|
[
"Apache-2.0"
] | null | null | null |
from .builder import CodeBuilder
from .magic import register_constants
| 23.666667
| 37
| 0.859155
| 9
| 71
| 6.666667
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0.112676
| 71
| 2
| 38
| 35.5
| 0.952381
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| 1
| 0
| 1
| 0
|
0
| 5
|
d93576d8bbd178a0e4a247260a8ffccb8c8b7eb0
| 49
|
py
|
Python
|
src/quantfinpy/instrument/__init__.py
|
TradingPy/quantfinpy
|
20569c67314557b907dd2306dd48ec8be1b4a1a6
|
[
"BSD-3-Clause"
] | 2
|
2022-03-13T12:44:17.000Z
|
2022-03-31T18:00:21.000Z
|
src/quantfinpy/instrument/__init__.py
|
TradingPy/quantfinpy
|
20569c67314557b907dd2306dd48ec8be1b4a1a6
|
[
"BSD-3-Clause"
] | null | null | null |
src/quantfinpy/instrument/__init__.py
|
TradingPy/quantfinpy
|
20569c67314557b907dd2306dd48ec8be1b4a1a6
|
[
"BSD-3-Clause"
] | null | null | null |
"""Module for defining financial instruments."""
| 24.5
| 48
| 0.755102
| 5
| 49
| 7.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102041
| 49
| 1
| 49
| 49
| 0.840909
| 0.857143
| 0
| null | 0
| null | 0
| 0
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| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
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| null | 0
| 0
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| 0
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| null | 0
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| 0
| 0
| 0
| 0
|
0
| 5
|
d93e5071b64758d83b7f80d76edfa686256e3164
| 5,912
|
gyp
|
Python
|
deps/zxing/zxing.gyp
|
rwaldron/node-dv
|
3b0c5265d74bfb0f4b811fde525d76aad7126169
|
[
"MIT"
] | 264
|
2015-01-04T10:58:41.000Z
|
2022-03-30T21:26:07.000Z
|
deps/zxing/zxing.gyp
|
rwaldron/node-dv
|
3b0c5265d74bfb0f4b811fde525d76aad7126169
|
[
"MIT"
] | 30
|
2015-02-16T21:06:34.000Z
|
2019-07-18T10:22:57.000Z
|
deps/zxing/zxing.gyp
|
creatale/node-dv
|
6150a6daec48b7d73e33f7cb846e8fd1cd19a7c8
|
[
"MIT"
] | 57
|
2015-02-20T16:38:48.000Z
|
2020-12-27T08:57:10.000Z
|
{
'includes': [ '../common.gyp' ],
'targets': [
{
'target_name': 'libzxing',
'type': 'static_library',
'include_dirs': [
'core/src',
],
'sources': [
'core/src/bigint/BigInteger.cc',
'core/src/bigint/BigIntegerAlgorithms.cc',
'core/src/bigint/BigIntegerUtils.cc',
'core/src/bigint/BigUnsigned.cc',
'core/src/bigint/BigUnsignedInABase.cc',
'core/src/zxing/BarcodeFormat.cpp',
'core/src/zxing/Binarizer.cpp',
'core/src/zxing/BinaryBitmap.cpp',
'core/src/zxing/ChecksumException.cpp',
'core/src/zxing/DecodeHints.cpp',
'core/src/zxing/Exception.cpp',
'core/src/zxing/FormatException.cpp',
'core/src/zxing/InvertedLuminanceSource.cpp',
'core/src/zxing/LuminanceSource.cpp',
'core/src/zxing/MultiFormatReader.cpp',
'core/src/zxing/Reader.cpp',
'core/src/zxing/Result.cpp',
'core/src/zxing/ResultIO.cpp',
'core/src/zxing/ResultPoint.cpp',
'core/src/zxing/ResultPointCallback.cpp',
'core/src/zxing/aztec/AztecDetectorResult.cpp',
'core/src/zxing/aztec/AztecReader.cpp',
'core/src/zxing/aztec/decoder/1Decoder.cpp',
'core/src/zxing/aztec/detector/1Detector.cpp',
'core/src/zxing/common/BitArray.cpp',
'core/src/zxing/common/BitArrayIO.cpp',
'core/src/zxing/common/BitMatrix.cpp',
'core/src/zxing/common/BitSource.cpp',
'core/src/zxing/common/CharacterSetECI.cpp',
'core/src/zxing/common/DecoderResult.cpp',
'core/src/zxing/common/DetectorResult.cpp',
'core/src/zxing/common/GlobalHistogramBinarizer.cpp',
'core/src/zxing/common/GreyscaleLuminanceSource.cpp',
'core/src/zxing/common/GreyscaleRotatedLuminanceSource.cpp',
'core/src/zxing/common/GridSampler.cpp',
'core/src/zxing/common/HybridBinarizer.cpp',
'core/src/zxing/common/IllegalArgumentException.cpp',
'core/src/zxing/common/PerspectiveTransform.cpp',
'core/src/zxing/common/Str.cpp',
'core/src/zxing/common/StringUtils.cpp',
'core/src/zxing/common/detector/MonochromeRectangleDetector.cpp',
'core/src/zxing/common/detector/WhiteRectangleDetector.cpp',
'core/src/zxing/common/reedsolomon/GenericGF.cpp',
'core/src/zxing/common/reedsolomon/GenericGFPoly.cpp',
'core/src/zxing/common/reedsolomon/ReedSolomonDecoder.cpp',
'core/src/zxing/common/reedsolomon/ReedSolomonException.cpp',
'core/src/zxing/datamatrix/1Version.cpp',
'core/src/zxing/datamatrix/DataMatrixReader.cpp',
'core/src/zxing/datamatrix/decoder/1BitMatrixParser.cpp',
'core/src/zxing/datamatrix/decoder/1DataBlock.cpp',
'core/src/zxing/datamatrix/decoder/1DecodedBitStreamParser.cpp',
'core/src/zxing/datamatrix/decoder/2Decoder.cpp',
'core/src/zxing/datamatrix/detector/2Detector.cpp',
'core/src/zxing/datamatrix/detector/CornerPoint.cpp',
'core/src/zxing/datamatrix/detector/DetectorException.cpp',
'core/src/zxing/multi/ByQuadrantReader.cpp',
'core/src/zxing/multi/GenericMultipleBarcodeReader.cpp',
'core/src/zxing/multi/MultipleBarcodeReader.cpp',
'core/src/zxing/multi/qrcode/QRCodeMultiReader.cpp',
'core/src/zxing/multi/qrcode/detector/MultiDetector.cpp',
'core/src/zxing/multi/qrcode/detector/MultiFinderPatternFinder.cpp',
'core/src/zxing/oned/CodaBarReader.cpp',
'core/src/zxing/oned/Code128Reader.cpp',
'core/src/zxing/oned/Code39Reader.cpp',
'core/src/zxing/oned/Code93Reader.cpp',
'core/src/zxing/oned/EAN13Reader.cpp',
'core/src/zxing/oned/EAN8Reader.cpp',
'core/src/zxing/oned/ITFReader.cpp',
'core/src/zxing/oned/MultiFormatOneDReader.cpp',
'core/src/zxing/oned/MultiFormatUPCEANReader.cpp',
'core/src/zxing/oned/OneDReader.cpp',
'core/src/zxing/oned/OneDResultPoint.cpp',
'core/src/zxing/oned/UPCAReader.cpp',
'core/src/zxing/oned/UPCEANReader.cpp',
'core/src/zxing/oned/UPCEReader.cpp',
'core/src/zxing/pdf417/PDF417Reader.cpp',
'core/src/zxing/pdf417/decoder/2BitMatrixParser.cpp',
'core/src/zxing/pdf417/decoder/2DecodedBitStreamParser.cpp',
'core/src/zxing/pdf417/decoder/3Decoder.cpp',
'core/src/zxing/pdf417/decoder/ec/ErrorCorrection.cpp',
'core/src/zxing/pdf417/decoder/ec/ModulusGF.cpp',
'core/src/zxing/pdf417/decoder/ec/ModulusPoly.cpp',
'core/src/zxing/pdf417/detector/3Detector.cpp',
'core/src/zxing/pdf417/detector/LinesSampler.cpp',
'core/src/zxing/qrcode/2Version.cpp',
'core/src/zxing/qrcode/ErrorCorrectionLevel.cpp',
'core/src/zxing/qrcode/FormatInformation.cpp',
'core/src/zxing/qrcode/QRCodeReader.cpp',
'core/src/zxing/qrcode/decoder/2DataBlock.cpp',
'core/src/zxing/qrcode/decoder/3BitMatrixParser.cpp',
'core/src/zxing/qrcode/decoder/3DecodedBitStreamParser.cpp',
'core/src/zxing/qrcode/decoder/4Decoder.cpp',
'core/src/zxing/qrcode/decoder/DataMask.cpp',
'core/src/zxing/qrcode/decoder/Mode.cpp',
'core/src/zxing/qrcode/detector/4Detector.cpp',
'core/src/zxing/qrcode/detector/AlignmentPattern.cpp',
'core/src/zxing/qrcode/detector/AlignmentPatternFinder.cpp',
'core/src/zxing/qrcode/detector/FinderPattern.cpp',
'core/src/zxing/qrcode/detector/FinderPatternFinder.cpp',
'core/src/zxing/qrcode/detector/FinderPatternInfo.cpp',
],
'conditions': [
['OS=="win"',
{
'include_dirs': [
'core/src/win32/zxing/',
],
'sources': [
'core/src/win32/zxing/win_iconv.c',
],
}
],
],
},
]
}
| 46.551181
| 76
| 0.655447
| 655
| 5,912
| 5.908397
| 0.206107
| 0.186305
| 0.294574
| 0.364341
| 0.511111
| 0.279328
| 0.040827
| 0
| 0
| 0
| 0
| 0.012936
| 0.189276
| 5,912
| 126
| 77
| 46.920635
| 0.794492
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| 0
| 0.079365
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| 0.746955
| 0.724966
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| null | 0
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| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
7965a80067ea1361813c8a0cfc36fae9b11730d0
| 57
|
py
|
Python
|
pyrobolearn/models/cpg/__init__.py
|
Pandinosaurus/pyrobolearn
|
9cd7c060723fda7d2779fa255ac998c2c82b8436
|
[
"Apache-2.0"
] | 2
|
2021-01-21T21:08:30.000Z
|
2022-03-29T16:45:49.000Z
|
pyrobolearn/models/cpg/__init__.py
|
Pandinosaurus/pyrobolearn
|
9cd7c060723fda7d2779fa255ac998c2c82b8436
|
[
"Apache-2.0"
] | null | null | null |
pyrobolearn/models/cpg/__init__.py
|
Pandinosaurus/pyrobolearn
|
9cd7c060723fda7d2779fa255ac998c2c82b8436
|
[
"Apache-2.0"
] | 1
|
2020-09-29T21:25:39.000Z
|
2020-09-29T21:25:39.000Z
|
# -*- coding: utf-8 -*-
# import cpg
from .cpg import *
| 11.4
| 23
| 0.561404
| 8
| 57
| 4
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.022727
| 0.22807
| 57
| 4
| 24
| 14.25
| 0.704545
| 0.561404
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| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
796798ed93460d1716d811dc6b8f0371a5990def
| 148
|
py
|
Python
|
project/db/serializers/forgot_password_serializer.py
|
sunday-ucheawaji/API-
|
07fb4b596cfe8e85b8575a8e70a8c886d3ab627a
|
[
"MIT"
] | null | null | null |
project/db/serializers/forgot_password_serializer.py
|
sunday-ucheawaji/API-
|
07fb4b596cfe8e85b8575a8e70a8c886d3ab627a
|
[
"MIT"
] | null | null | null |
project/db/serializers/forgot_password_serializer.py
|
sunday-ucheawaji/API-
|
07fb4b596cfe8e85b8575a8e70a8c886d3ab627a
|
[
"MIT"
] | 1
|
2022-02-09T14:13:20.000Z
|
2022-02-09T14:13:20.000Z
|
from rest_framework import serializers
class ForgotPasswordSerializer(serializers.Serializer):
email = serializers.EmailField(required=True)
| 21.142857
| 55
| 0.831081
| 14
| 148
| 8.714286
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108108
| 148
| 6
| 56
| 24.666667
| 0.924242
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.333333
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
|
0
| 5
|
7973ea113747233bec9dd30dd443aa2647d66f8b
| 153
|
py
|
Python
|
skqulacs/circuit/__init__.py
|
kenjikun/scikit-qulacs
|
afc502f63927ab61da964698da54ec4b410c30c4
|
[
"MIT"
] | null | null | null |
skqulacs/circuit/__init__.py
|
kenjikun/scikit-qulacs
|
afc502f63927ab61da964698da54ec4b410c30c4
|
[
"MIT"
] | null | null | null |
skqulacs/circuit/__init__.py
|
kenjikun/scikit-qulacs
|
afc502f63927ab61da964698da54ec4b410c30c4
|
[
"MIT"
] | null | null | null |
from .circuit import LearningCircuit
from .pre_defined import create_qcl_ansatz, create_farhi_circuit, create_defqsv
from .graph import show_blochsphere
| 38.25
| 79
| 0.875817
| 21
| 153
| 6.047619
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.091503
| 153
| 3
| 80
| 51
| 0.913669
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
799ffbb234f555a58e859f2ca3f78079747e1e60
| 202
|
py
|
Python
|
tests/unittests/test_state_utils.py
|
owlvey/archon
|
99811d830a709756c7a62e9d75a38e2b87549b7b
|
[
"Apache-2.0"
] | 1
|
2021-04-15T21:55:08.000Z
|
2021-04-15T21:55:08.000Z
|
tests/unittests/test_state_utils.py
|
owlvey/archon
|
99811d830a709756c7a62e9d75a38e2b87549b7b
|
[
"Apache-2.0"
] | null | null | null |
tests/unittests/test_state_utils.py
|
owlvey/archon
|
99811d830a709756c7a62e9d75a38e2b87549b7b
|
[
"Apache-2.0"
] | null | null | null |
from engine.core.StateUtil import StateUtil
from engine.core.JourneyEntity import JourneyEntity
import unittest
class StateUtilsUnitTest(unittest.TestCase):
def test_dataframe(self):
pass
| 22.444444
| 51
| 0.80198
| 23
| 202
| 7
| 0.652174
| 0.124224
| 0.173913
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.143564
| 202
| 9
| 52
| 22.444444
| 0.930636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0.166667
| 0.5
| 0
| 0.833333
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
|
0
| 5
|
79ca32f91f81eff1170db6354bfe14eb4d7fb209
| 431
|
py
|
Python
|
chainervr/datasets/epic_kitchen/__init__.py
|
otsubo/chainervr
|
92ab44ea68ed930342698e9da1809eca2ac064f7
|
[
"MIT"
] | 7
|
2018-07-31T02:18:52.000Z
|
2021-01-22T05:14:35.000Z
|
chainervr/datasets/epic_kitchen/__init__.py
|
otsubo/chainervr
|
92ab44ea68ed930342698e9da1809eca2ac064f7
|
[
"MIT"
] | 1
|
2018-08-20T13:37:17.000Z
|
2018-08-20T13:37:17.000Z
|
chainervr/datasets/epic_kitchen/__init__.py
|
otsubo/chainervr
|
92ab44ea68ed930342698e9da1809eca2ac064f7
|
[
"MIT"
] | 1
|
2018-08-20T13:33:04.000Z
|
2018-08-20T13:33:04.000Z
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Author: Yuki Furuta <furushchev@jsk.imi.i.u-tokyo.ac.jp>
from epic_kitchen_object_detection_dataset import EpicKitchenObjectDetectionDataset
from epic_kitchen_object_detection_dataset import epic_kitchen_object_detection_label_names
#
from epic_kitchen_action_dataset import EpicKitchenActionDataset
from epic_kitchen_action_dataset import epic_kitchen_object_detection_label_names
| 43.1
| 91
| 0.87007
| 58
| 431
| 6.051724
| 0.517241
| 0.188034
| 0.17094
| 0.296296
| 0.643875
| 0.643875
| 0.487179
| 0.279202
| 0
| 0
| 0
| 0.002494
| 0.069606
| 431
| 9
| 92
| 47.888889
| 0.872818
| 0.229698
| 0
| 0
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| 0
| 0
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| 0
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| 0
| 1
| 0
| true
| 0
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| 1
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| 0
| 0
| null | 0
| 0
| 1
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| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
8dc080546ba63f3ddea79c224742b4978a008fe2
| 253
|
py
|
Python
|
src/search/views/__init__.py
|
ResearchHub/ResearchHub-Backend-Open
|
d36dca33afae2d442690694bb2ab17180d84bcd3
|
[
"MIT"
] | 18
|
2021-05-20T13:20:16.000Z
|
2022-02-11T02:40:18.000Z
|
src/search/views/__init__.py
|
ResearchHub/ResearchHub-Backend-Open
|
d36dca33afae2d442690694bb2ab17180d84bcd3
|
[
"MIT"
] | 109
|
2021-05-21T20:14:23.000Z
|
2022-03-31T20:56:10.000Z
|
src/search/views/__init__.py
|
ResearchHub/ResearchHub-Backend-Open
|
d36dca33afae2d442690694bb2ab17180d84bcd3
|
[
"MIT"
] | 4
|
2021-05-17T13:47:53.000Z
|
2022-02-12T10:48:21.000Z
|
# flake8: noqa
from .person import PersonDocumentView
from .combined import CombinedView #, crossref, orcid
from .paper import PaperDocumentView
from .thread import ThreadDocumentView
from .hub import HubDocumentView
from .post import PostDocumentView
| 31.625
| 54
| 0.833992
| 28
| 253
| 7.535714
| 0.642857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004505
| 0.12253
| 253
| 7
| 55
| 36.142857
| 0.945946
| 0.114625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
5c0ca454a7289523d28749d8db58507f0096246f
| 108
|
py
|
Python
|
src/14000/14729.py3.py
|
upple/BOJ
|
e6dbf9fd17fa2b458c6a781d803123b14c18e6f1
|
[
"MIT"
] | 8
|
2018-04-12T15:54:09.000Z
|
2020-06-05T07:41:15.000Z
|
src/14000/14729.py3.py
|
upple/BOJ
|
e6dbf9fd17fa2b458c6a781d803123b14c18e6f1
|
[
"MIT"
] | null | null | null |
src/14000/14729.py3.py
|
upple/BOJ
|
e6dbf9fd17fa2b458c6a781d803123b14c18e6f1
|
[
"MIT"
] | null | null | null |
import sys
[print('%.3f'%i) for i in sorted([float(sys.stdin.readline()) for _ in range(int(input()))])[:7]]
| 54
| 97
| 0.648148
| 19
| 108
| 3.631579
| 0.789474
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.020408
| 0.092593
| 108
| 2
| 97
| 54
| 0.683673
| 0
| 0
| 0
| 0
| 0
| 0.036697
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0.5
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 5
|
5c37a162a2268e3d910f689c754e02cc5f6847c6
| 267
|
py
|
Python
|
colour/biochemistry/__init__.py
|
SGeetansh/colour
|
a196f9536c44e2101cde53446550d64303c0ab46
|
[
"BSD-3-Clause"
] | 6
|
2019-06-18T18:53:29.000Z
|
2021-09-10T21:02:45.000Z
|
colour/biochemistry/__init__.py
|
SGeetansh/colour
|
a196f9536c44e2101cde53446550d64303c0ab46
|
[
"BSD-3-Clause"
] | null | null | null |
colour/biochemistry/__init__.py
|
SGeetansh/colour
|
a196f9536c44e2101cde53446550d64303c0ab46
|
[
"BSD-3-Clause"
] | null | null | null |
# -*- coding: utf-8 -*-
from .michaelis_menten import (reaction_rate_MichealisMenten,
substrate_concentration_MichealisMenten)
__all__ = []
__all__ += [
'reaction_rate_MichealisMenten', 'substrate_concentration_MichealisMenten'
]
| 26.7
| 78
| 0.696629
| 21
| 267
| 8.047619
| 0.619048
| 0.142012
| 0.319527
| 0.426036
| 0.757396
| 0.757396
| 0
| 0
| 0
| 0
| 0
| 0.004739
| 0.209738
| 267
| 9
| 79
| 29.666667
| 0.796209
| 0.078652
| 0
| 0
| 0
| 0
| 0.278689
| 0.278689
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.166667
| 0
| 0.166667
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
30887a220768298bc63de0c7a000a767f9d06e4e
| 99
|
py
|
Python
|
main.py
|
marcoshr/executable
|
caeed90bda722fed3a570a8a7b9a2691bee8b174
|
[
"MIT"
] | null | null | null |
main.py
|
marcoshr/executable
|
caeed90bda722fed3a570a8a7b9a2691bee8b174
|
[
"MIT"
] | null | null | null |
main.py
|
marcoshr/executable
|
caeed90bda722fed3a570a8a7b9a2691bee8b174
|
[
"MIT"
] | null | null | null |
from countdown import countdown
import gui # EDIT GUY.PY
print("Finishing program...")
countdown(2)
| 24.75
| 31
| 0.777778
| 14
| 99
| 5.5
| 0.785714
| 0.38961
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011364
| 0.111111
| 99
| 4
| 32
| 24.75
| 0.863636
| 0.111111
| 0
| 0
| 0
| 0
| 0.229885
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0.25
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
30c73244e3cb3406cd4311618b79759481bdb88d
| 167
|
py
|
Python
|
datafaucet/pandas/__init__.py
|
natbusa/datalabframework
|
77f1249f55c76f20f2ef6253c0af2f1943f36226
|
[
"MIT"
] | 21
|
2018-09-01T05:50:54.000Z
|
2019-06-17T08:39:18.000Z
|
datafaucet/pandas/__init__.py
|
natbusa/datafaucet
|
77f1249f55c76f20f2ef6253c0af2f1943f36226
|
[
"MIT"
] | 9
|
2018-09-06T12:02:58.000Z
|
2019-04-15T16:52:52.000Z
|
datafaucet/pandas/__init__.py
|
natbusa/datalabframework
|
77f1249f55c76f20f2ef6253c0af2f1943f36226
|
[
"MIT"
] | 18
|
2017-06-27T22:00:36.000Z
|
2019-07-03T09:45:39.000Z
|
from datafaucet.engines import register
from .engine import PandasEngine
register(PandasEngine, 'pandas')
# monkey patch the pyspark sql DataFrame
from .df import *
| 20.875
| 40
| 0.802395
| 21
| 167
| 6.380952
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.137725
| 167
| 7
| 41
| 23.857143
| 0.930556
| 0.227545
| 0
| 0
| 0
| 0
| 0.047244
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.75
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
30fef7bf7406a55dc2b4845ee1899616d6c1c09d
| 50
|
py
|
Python
|
relogic/components/__init__.py
|
Impavidity/relogic
|
f647106e143cd603b95b63e06ea530cdd516aefe
|
[
"MIT"
] | 24
|
2019-07-20T02:10:21.000Z
|
2022-03-15T07:13:07.000Z
|
relogic/components/__init__.py
|
One-paper-luck/relogic
|
f647106e143cd603b95b63e06ea530cdd516aefe
|
[
"MIT"
] | 3
|
2019-11-28T04:19:25.000Z
|
2019-11-30T23:29:19.000Z
|
relogic/components/__init__.py
|
One-paper-luck/relogic
|
f647106e143cd603b95b63e06ea530cdd516aefe
|
[
"MIT"
] | 5
|
2019-11-27T03:12:07.000Z
|
2021-12-08T11:45:43.000Z
|
from relogic.components.component import Component
| 50
| 50
| 0.9
| 6
| 50
| 7.5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.06
| 50
| 1
| 50
| 50
| 0.957447
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a518034ef28b74b3b79ffcb7298b423605484b7b
| 67
|
py
|
Python
|
Main.py
|
Badwolf369/CS161
|
6e5ffcd51a0b8c50af30a8ad6765555a89c53150
|
[
"MIT"
] | null | null | null |
Main.py
|
Badwolf369/CS161
|
6e5ffcd51a0b8c50af30a8ad6765555a89c53150
|
[
"MIT"
] | null | null | null |
Main.py
|
Badwolf369/CS161
|
6e5ffcd51a0b8c50af30a8ad6765555a89c53150
|
[
"MIT"
] | null | null | null |
from Typer import write
write('This is a test of importing files')
| 22.333333
| 42
| 0.776119
| 12
| 67
| 4.333333
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.164179
| 67
| 3
| 42
| 22.333333
| 0.928571
| 0
| 0
| 0
| 0
| 0
| 0.485294
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
eb4fb7cd910c0dabab7440d3a9d6b9e9dd404597
| 19
|
py
|
Python
|
my_classes/.history/ModulesPackages_PackageNamespaces/example3a/module1_source_20210725220158.py
|
minefarmer/deep-Dive-1
|
b0675b853180c5b5781888266ea63a3793b8d855
|
[
"Unlicense"
] | null | null | null |
my_classes/.history/ModulesPackages_PackageNamespaces/example3a/module1_source_20210725220158.py
|
minefarmer/deep-Dive-1
|
b0675b853180c5b5781888266ea63a3793b8d855
|
[
"Unlicense"
] | null | null | null |
my_classes/.history/ModulesPackages_PackageNamespaces/example3a/module1_source_20210725220158.py
|
minefarmer/deep-Dive-1
|
b0675b853180c5b5781888266ea63a3793b8d855
|
[
"Unlicense"
] | null | null | null |
print('Running ')
| 6.333333
| 17
| 0.631579
| 2
| 19
| 6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 19
| 3
| 17
| 6.333333
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0.444444
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
eb58badfac279ab6930ec95aadbaa28b0035af00
| 188
|
py
|
Python
|
Set_02/phone_list/phone_list.py
|
joezombie/AFLV
|
9bf20ba881750afc0770174d4fadaf980af6aa37
|
[
"MIT"
] | null | null | null |
Set_02/phone_list/phone_list.py
|
joezombie/AFLV
|
9bf20ba881750afc0770174d4fadaf980af6aa37
|
[
"MIT"
] | null | null | null |
Set_02/phone_list/phone_list.py
|
joezombie/AFLV
|
9bf20ba881750afc0770174d4fadaf980af6aa37
|
[
"MIT"
] | null | null | null |
import sys
nCases = int(sys.stdin.readline())
for i in range(nCases):
nNumbers = int(sys.stdin.readline())
for i in range(nNumbers):
print sys.stdin.readline().rstrip()
| 18.8
| 43
| 0.659574
| 27
| 188
| 4.592593
| 0.481481
| 0.193548
| 0.387097
| 0.306452
| 0.483871
| 0.483871
| 0.483871
| 0.483871
| 0
| 0
| 0
| 0
| 0.196809
| 188
| 9
| 44
| 20.888889
| 0.821192
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.166667
| null | null | 0.166667
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
eb772246f74a9dfa792e8967a9006a0fcd6fbc08
| 22
|
py
|
Python
|
Python/hello_waldo.py
|
saurabhcommand/Hello-world
|
647bad9da901a52d455f05ecc37c6823c22dc77e
|
[
"MIT"
] | 1,428
|
2018-10-03T15:15:17.000Z
|
2019-03-31T18:38:36.000Z
|
Python/hello_waldo.py
|
saurabhcommand/Hello-world
|
647bad9da901a52d455f05ecc37c6823c22dc77e
|
[
"MIT"
] | 1,162
|
2018-10-03T15:05:49.000Z
|
2018-10-18T14:17:52.000Z
|
Python/hello_waldo.py
|
saurabhcommand/Hello-world
|
647bad9da901a52d455f05ecc37c6823c22dc77e
|
[
"MIT"
] | 3,909
|
2018-10-03T15:07:19.000Z
|
2019-03-31T18:39:08.000Z
|
print('Hello Waldo!')
| 11
| 21
| 0.681818
| 3
| 22
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.090909
| 22
| 1
| 22
| 22
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0.545455
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
eb7c908cc8ff62a4664923b3605bb681bc956918
| 60
|
py
|
Python
|
kw3pan/pancakeswap/factory/busd/__init__.py
|
kkristof200/py_web3_pancakeswap
|
ae9dc7021b7da2365ce675f29f89e103fe44d77f
|
[
"MIT"
] | 6
|
2021-05-09T12:43:37.000Z
|
2021-12-07T01:56:02.000Z
|
kw3pan/pancakeswap/factory/busd/__init__.py
|
kkristof200/py_web3_pancakeswap
|
ae9dc7021b7da2365ce675f29f89e103fe44d77f
|
[
"MIT"
] | null | null | null |
kw3pan/pancakeswap/factory/busd/__init__.py
|
kkristof200/py_web3_pancakeswap
|
ae9dc7021b7da2365ce675f29f89e103fe44d77f
|
[
"MIT"
] | null | null | null |
from .pancakeswap_busd_factory import PancakeswapBusdFactory
| 60
| 60
| 0.933333
| 6
| 60
| 9
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.05
| 60
| 1
| 60
| 60
| 0.947368
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
eb875993fac5c282c3c13e10890da302281f7aed
| 1,022
|
py
|
Python
|
lib/api_swagger_client/swagger_client/__init__.py
|
31337mbf/yapo
|
b790e112efccfb8f818dc7711989a9174b2c65fb
|
[
"MIT"
] | null | null | null |
lib/api_swagger_client/swagger_client/__init__.py
|
31337mbf/yapo
|
b790e112efccfb8f818dc7711989a9174b2c65fb
|
[
"MIT"
] | null | null | null |
lib/api_swagger_client/swagger_client/__init__.py
|
31337mbf/yapo
|
b790e112efccfb8f818dc7711989a9174b2c65fb
|
[
"MIT"
] | null | null | null |
# coding: utf-8
# flake8: noqa
"""
cifrum API
No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) # noqa: E501
OpenAPI spec version: 0.1.0
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
# import apis into sdk package
from swagger_client.api.adjusted_values_api import AdjustedValuesApi
from swagger_client.api.infos_api import InfosApi
from swagger_client.api.raw_values_api import RawValuesApi
from swagger_client.api.routes_api import RoutesApi
# import ApiClient
from swagger_client.api_client import ApiClient
from swagger_client.configuration import Configuration
# import models into sdk package
from swagger_client.models.models_message import ModelsMessage
from swagger_client.models.models_mutual_fund_ru_info import ModelsMutualFundRuInfo
from swagger_client.models.models_raw_value import ModelsRawValue
from swagger_client.models.models_raw_values import ModelsRawValues
| 34.066667
| 119
| 0.831703
| 140
| 1,022
| 5.85
| 0.392857
| 0.13431
| 0.20757
| 0.1221
| 0.374847
| 0.246642
| 0.092796
| 0
| 0
| 0
| 0
| 0.00882
| 0.112524
| 1,022
| 29
| 120
| 35.241379
| 0.894157
| 0.319961
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
ebe1cd152f6e8cf5298f4c3c4304cb019b9c2088
| 52
|
py
|
Python
|
yalm/__init__.py
|
anshuldutt21/spdx-python-licensematching
|
ed4bbe205536edcafce745c3d012bf9d802845b9
|
[
"Apache-2.0"
] | 4
|
2021-01-13T06:45:02.000Z
|
2021-07-13T18:28:22.000Z
|
yalm/__init__.py
|
m1kit/yalm-python
|
a0a98b70f1398dac171c9d202439d46a2723eda8
|
[
"Apache-2.0"
] | 25
|
2021-06-05T10:06:40.000Z
|
2021-08-22T11:09:50.000Z
|
yalm/__init__.py
|
anshuldutt21/spdx-python-licensematching
|
ed4bbe205536edcafce745c3d012bf9d802845b9
|
[
"Apache-2.0"
] | 3
|
2020-10-07T15:20:16.000Z
|
2021-05-18T10:08:59.000Z
|
from .licenses import spdx_licenses, detect_license
| 26
| 51
| 0.865385
| 7
| 52
| 6.142857
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.096154
| 52
| 1
| 52
| 52
| 0.914894
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
ebe406c965e3680688075fe5604f983b6e7e8635
| 9,767
|
py
|
Python
|
lib/models/utils/indexnet.py
|
haotianliu001/HRNet-Lesion
|
9dae108879456e084b2200e39d7e58c1c08c2b16
|
[
"MIT"
] | null | null | null |
lib/models/utils/indexnet.py
|
haotianliu001/HRNet-Lesion
|
9dae108879456e084b2200e39d7e58c1c08c2b16
|
[
"MIT"
] | null | null | null |
lib/models/utils/indexnet.py
|
haotianliu001/HRNet-Lesion
|
9dae108879456e084b2200e39d7e58c1c08c2b16
|
[
"MIT"
] | null | null | null |
"""
IndexNet Matting
REF: https://github.com/poppinace/indexnet_matting/blob/ddb374a3e0e1ef3042437b7a88785950d6b0fbe1/scripts/hlindex.py#L37
Indices Matter: Learning to Index for Deep Image Matting
IEEE/CVF International Conference on Computer Vision, 2019
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..bn_helper import BatchNorm2d_class
class HolisticIndexBlock(nn.Module):
def __init__(self, inp, use_nonlinear=False, use_context=False, batch_norm=nn.BatchNorm2d):
super(HolisticIndexBlock, self).__init__()
if use_context:
kernel_size, padding = 4, 1
else:
kernel_size, padding = 2, 0
if use_nonlinear:
self.indexnet = nn.Sequential(
nn.Conv2d(inp, 2 * inp, kernel_size=kernel_size, stride=2, padding=padding, bias=False),
batch_norm(2 * inp),
nn.ReLU6(inplace=True),
nn.Conv2d(2 * inp, 4, kernel_size=1, stride=1, padding=0, bias=False)
)
else:
self.indexnet = nn.Conv2d(inp, 4, kernel_size=kernel_size, stride=2, padding=padding, bias=False)
def forward(self, x):
x = self.indexnet(x)
y = torch.sigmoid(x)
z = F.softmax(y, dim=1)
idx_en = F.pixel_shuffle(z, 2)
idx_de = F.pixel_shuffle(y, 2)
return idx_en, idx_de
class DepthwiseO2OIndexBlock(nn.Module):
def __init__(self, inp, use_nonlinear=False, use_context=False, batch_norm=nn.BatchNorm2d):
super(DepthwiseO2OIndexBlock, self).__init__()
self.indexnet1 = self._build_index_block(inp, use_nonlinear, use_context, batch_norm)
self.indexnet2 = self._build_index_block(inp, use_nonlinear, use_context, batch_norm)
self.indexnet3 = self._build_index_block(inp, use_nonlinear, use_context, batch_norm)
self.indexnet4 = self._build_index_block(inp, use_nonlinear, use_context, batch_norm)
def _build_index_block(self, inp, use_nonlinear, use_context, batch_norm):
if use_context:
kernel_size, padding = 4, 1
else:
kernel_size, padding = 2, 0
if use_nonlinear:
return nn.Sequential(
nn.Conv2d(inp, inp, kernel_size=kernel_size, stride=2, padding=padding, groups=inp, bias=False),
batch_norm(inp),
nn.ReLU6(inplace=True),
nn.Conv2d(inp, inp, kernel_size=1, stride=1, padding=0, groups=inp, bias=False)
)
else:
return nn.Sequential(
nn.Conv2d(inp, inp, kernel_size=kernel_size, stride=2, padding=padding, groups=inp, bias=False)
)
def forward(self, x):
bs, c, h, w = x.size()
x1 = self.indexnet1(x).unsqueeze(2)
x2 = self.indexnet2(x).unsqueeze(2)
x3 = self.indexnet3(x).unsqueeze(2)
x4 = self.indexnet4(x).unsqueeze(2)
x = torch.cat((x1, x2, x3, x4), dim=2)
# normalization
y = torch.sigmoid(x)
z = F.softmax(y, dim=2)
# pixel shuffling
y = y.view(bs, c * 4, int(h / 2), int(w / 2))
z = z.view(bs, c * 4, int(h / 2), int(w / 2))
idx_en = F.pixel_shuffle(z, 2)
idx_de = F.pixel_shuffle(y, 2)
return idx_en, idx_de
class DepthwiseM2OIndexBlock(nn.Module):
def __init__(self, inp, use_nonlinear=False, use_context=False, batch_norm=nn.BatchNorm2d):
super(DepthwiseM2OIndexBlock, self).__init__()
self.use_nonlinear = use_nonlinear
self.indexnet1 = self._build_index_block(inp, use_nonlinear, use_context, batch_norm)
self.indexnet2 = self._build_index_block(inp, use_nonlinear, use_context, batch_norm)
self.indexnet3 = self._build_index_block(inp, use_nonlinear, use_context, batch_norm)
self.indexnet4 = self._build_index_block(inp, use_nonlinear, use_context, batch_norm)
def _build_index_block(self, inp, use_nonlinear, use_context, batch_norm):
if use_context:
kernel_size, padding = 4, 1
else:
kernel_size, padding = 2, 0
if use_nonlinear:
return nn.Sequential(
nn.Conv2d(inp, inp, kernel_size=kernel_size, stride=2, padding=padding, bias=False),
batch_norm(inp),
nn.ReLU6(inplace=True),
nn.Conv2d(inp, inp, kernel_size=1, stride=1, padding=0, bias=False)
)
else:
return nn.Sequential(
nn.Conv2d(inp, inp, kernel_size=kernel_size, stride=2, padding=padding, bias=False)
)
def forward(self, x):
bs, c, h, w = x.size()
x1 = self.indexnet1(x).unsqueeze(2)
x2 = self.indexnet2(x).unsqueeze(2)
x3 = self.indexnet3(x).unsqueeze(2)
x4 = self.indexnet4(x).unsqueeze(2)
x = torch.cat((x1, x2, x3, x4), dim=2)
# normalization
y = torch.sigmoid(x)
z = F.softmax(y, dim=2)
# pixel shuffling
y = y.view(bs, c * 4, int(h / 2), int(w / 2))
z = z.view(bs, c * 4, int(h / 2), int(w / 2))
idx_en = F.pixel_shuffle(z, 2)
idx_de = F.pixel_shuffle(y, 2)
return idx_en, idx_de
class IndexDown(HolisticIndexBlock):
def forward(self, x):
x_new = self.indexnet(x)
y = torch.sigmoid(x_new)
z = F.softmax(y, dim=1)
idx_en = F.pixel_shuffle(z, 2)
idx_de = F.pixel_shuffle(y, 2)
x = x * idx_en
x = 4 * F.avg_pool2d(x, (2, 2), stride=2)
return x, idx_de
class IndexDownModule(nn.Module):
def __init__(self,
inplane, outplane, num=1,
kernel_size=3,
use_nonlinear=False,
use_context=False,
batch_norm=nn.BatchNorm2d):
super(IndexDownModule, self).__init__()
self.kernel_size = kernel_size
self.num = num
downsample_list = []
for i in range(self.num):
downsample_list.append(
IndexDown(inplane, use_nonlinear=use_nonlinear, use_context=use_context, batch_norm=batch_norm))
downsample_list.append(
nn.Sequential(
nn.Conv2d(
inplane,
outplane,
kernel_size=self.kernel_size,
stride=1,
padding=self.kernel_size // 2,
bias=False),
batch_norm(outplane),
)
)
self.downsample_list = nn.Sequential(*downsample_list)
def forward(self, x):
index_list = []
for i in range(self.num):
x, index = self.downsample_list[i](x)
index_list.append(index)
x = self.downsample_list[-1](x) # 1x1 conv
return x, index_list
class IndexUpModule(nn.Module):
def __init__(self,
inplane, outplane, num=1,
kernel_size=3,
batch_norm=nn.BatchNorm2d):
super(IndexUpModule, self).__init__()
self.kernel_size = kernel_size
self.num = num
self.conv = nn.Sequential(
nn.Conv2d(
inplane,
outplane,
kernel_size=self.kernel_size,
stride=1,
padding=self.kernel_size // 2,
bias=False),
batch_norm(outplane)
)
def forward(self, x, index_list=None):
x = self.conv(x) # 1x1 conv
for i in range(self.num):
if index_list is not None:
x = index_list[self.num - i - 1] * F.interpolate(x, scale_factor=2, mode='nearest')
else:
x = F.interpolate(x, scale_factor=2, mode='nearest')
return x
class IndexedDecoder(nn.Module):
def __init__(self, inp, oup, kernel_size=5, batch_norm=nn.BatchNorm2d):
super(IndexedDecoder, self).__init__()
self.upsample = nn.MaxUnpool2d((2, 2), stride=2)
self.dconv = nn.Sequential(
nn.Conv2d(inp, oup, kernel_size=kernel_size, stride=1, padding=kernel_size // 2, bias=False),
batch_norm(oup),
nn.ReLU6(inplace=True)
)
self._init_weight()
def forward(self, l_encode, l_low, indices=None):
l_encode = self.upsample(l_encode, indices) if indices is not None else l_encode
l_encode = torch.cat((l_encode, l_low), dim=1)
return self.dconv(l_encode)
def _init_weight(self):
for m in self.modules():
if isinstance(m, nn.Conv2d):
torch.nn.init.kaiming_normal_(m.weight)
elif isinstance(m, BatchNorm2d_class):
m.weight.data.fill_(1)
m.bias.data.zero_()
class IndexedUpsamlping(nn.Module):
def __init__(self, inp, oup, kernel_size=5, batch_norm=nn.BatchNorm2d):
super(IndexedUpsamlping, self).__init__()
self.oup = oup
self.dconv = nn.Sequential(
nn.Conv2d(inp, oup, kernel_size=kernel_size, stride=1, padding=kernel_size // 2, bias=False),
batch_norm(oup),
nn.ReLU6(inplace=True)
)
self._init_weight()
def forward(self, l_encode, l_low, indices=None):
_, c, _, _ = l_encode.size()
if indices is not None:
l_encode = indices * F.interpolate(l_encode, size=l_low.size()[2:], mode='nearest')
l_cat = torch.cat((l_encode, l_low), dim=1)
return self.dconv(l_cat)
def _init_weight(self):
for m in self.modules():
if isinstance(m, nn.Conv2d):
torch.nn.init.kaiming_normal_(m.weight)
elif isinstance(m, BatchNorm2d_class):
m.weight.data.fill_(1)
m.bias.data.zero_()
| 34.390845
| 119
| 0.587181
| 1,268
| 9,767
| 4.303628
| 0.119085
| 0.075133
| 0.035734
| 0.044347
| 0.764706
| 0.745831
| 0.734469
| 0.713762
| 0.700568
| 0.698003
| 0
| 0.029175
| 0.301628
| 9,767
| 283
| 120
| 34.512367
| 0.770855
| 0.033992
| 0
| 0.643519
| 0
| 0
| 0.002229
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.087963
| false
| 0
| 0.018519
| 0
| 0.199074
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
ccef12028d2462ecb96c46b86f80803d7ebaeb91
| 262
|
py
|
Python
|
softlearning/samplers/__init__.py
|
anyboby/ConstrainedMBPO
|
036f4ffefc464e676a287c35c92cc5c0b8925fcf
|
[
"MIT"
] | 5
|
2020-02-12T17:09:09.000Z
|
2021-09-29T16:06:40.000Z
|
softlearning/samplers/__init__.py
|
anyboby/ConstrainedMBPO
|
036f4ffefc464e676a287c35c92cc5c0b8925fcf
|
[
"MIT"
] | 10
|
2020-08-31T02:50:02.000Z
|
2022-02-09T23:36:43.000Z
|
softlearning/samplers/__init__.py
|
anyboby/ConstrainedMBPO
|
036f4ffefc464e676a287c35c92cc5c0b8925fcf
|
[
"MIT"
] | 2
|
2022-03-15T01:45:26.000Z
|
2022-03-15T06:46:47.000Z
|
from .base_sampler import BaseSampler
from .dummy_sampler import DummySampler
from .remote_sampler import RemoteSampler
from .extra_policy_info_sampler import ExtraPolicyInfoSampler
from .utils import rollout, rollouts
from .simple_sampler import SimpleSampler
| 32.75
| 61
| 0.874046
| 32
| 262
| 6.9375
| 0.5625
| 0.292793
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.099237
| 262
| 7
| 62
| 37.428571
| 0.940678
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
| 0
| 0
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| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
ccf5304c230bf3f8a828fa379dbd7596cd9b0173
| 95
|
py
|
Python
|
app/settings.py
|
dhost-project/build-microservice
|
4376169a2753f37fe8c7985525bd3fd3af6f11e7
|
[
"MIT"
] | null | null | null |
app/settings.py
|
dhost-project/build-microservice
|
4376169a2753f37fe8c7985525bd3fd3af6f11e7
|
[
"MIT"
] | null | null | null |
app/settings.py
|
dhost-project/build-microservice
|
4376169a2753f37fe8c7985525bd3fd3af6f11e7
|
[
"MIT"
] | null | null | null |
import os
HOST = os.environ.get("HOST", "localhost")
PORT = int(os.environ.get("PORT", 5000))
| 19
| 42
| 0.673684
| 15
| 95
| 4.266667
| 0.6
| 0.28125
| 0.375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.047619
| 0.115789
| 95
| 4
| 43
| 23.75
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0.178947
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
693bf7bd70007dc084aeb4b7d74950184de9986e
| 470
|
py
|
Python
|
RecoVertex/Configuration/python/RecoVertexCosmicTracks_cff.py
|
NTrevisani/cmssw
|
a212a27526f34eb9507cf8b875c93896e6544781
|
[
"Apache-2.0"
] | 3
|
2018-08-24T19:10:26.000Z
|
2019-02-19T11:45:32.000Z
|
RecoVertex/Configuration/python/RecoVertexCosmicTracks_cff.py
|
NTrevisani/cmssw
|
a212a27526f34eb9507cf8b875c93896e6544781
|
[
"Apache-2.0"
] | 7
|
2016-07-17T02:34:54.000Z
|
2019-08-13T07:58:37.000Z
|
RecoVertex/Configuration/python/RecoVertexCosmicTracks_cff.py
|
NTrevisani/cmssw
|
a212a27526f34eb9507cf8b875c93896e6544781
|
[
"Apache-2.0"
] | 5
|
2018-08-21T16:37:52.000Z
|
2020-01-09T13:33:17.000Z
|
import FWCore.ParameterSet.Config as cms
# Reco Vertex
# initialize magnetic field #########################
from TrackingTools.TransientTrack.TransientTrackBuilder_cfi import *
import RecoVertex.PrimaryVertexProducer.OfflinePrimaryVerticesFromCosmicTracks_cfi
offlinePrimaryVertices = RecoVertex.PrimaryVertexProducer.OfflinePrimaryVerticesFromCosmicTracks_cfi.offlinePrimaryVerticesFromCosmicTracks.clone()
vertexrecoCosmics = cms.Sequence(offlinePrimaryVertices)
| 39.166667
| 147
| 0.844681
| 33
| 470
| 11.939394
| 0.69697
| 0.15736
| 0.350254
| 0.365482
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.059574
| 470
| 11
| 148
| 42.727273
| 0.891403
| 0.078723
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.6
| 0
| 0.6
| 0
| 0
| 0
| 1
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
696b474c06c03727e5a54601f33b1d4c4e51607f
| 195
|
py
|
Python
|
src/aoc/utils/bitwise.py
|
rudisimo/advent-of-code-2021
|
4c92916a3b1bacd2dc234ac65adab5dc9bbbd2cb
|
[
"MIT"
] | null | null | null |
src/aoc/utils/bitwise.py
|
rudisimo/advent-of-code-2021
|
4c92916a3b1bacd2dc234ac65adab5dc9bbbd2cb
|
[
"MIT"
] | null | null | null |
src/aoc/utils/bitwise.py
|
rudisimo/advent-of-code-2021
|
4c92916a3b1bacd2dc234ac65adab5dc9bbbd2cb
|
[
"MIT"
] | null | null | null |
from typing import List
from typing import Union
def common_bits(bits: List[int]) -> Union[int, int]:
bitset = set(bits)
return min(bitset, key=bits.count), max(bitset, key=bits.count)
| 24.375
| 67
| 0.707692
| 31
| 195
| 4.419355
| 0.516129
| 0.145985
| 0.233577
| 0.262774
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.164103
| 195
| 7
| 68
| 27.857143
| 0.840491
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.4
| 0
| 0.8
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
697015ada2264a262981d188710a73b41f56d776
| 250
|
py
|
Python
|
code/backend/src/api/__init__.py
|
tobiasclaas/semantic-data-lake
|
16fc25a74918c9ac4d95f14bf3c15af053cee53e
|
[
"MIT"
] | 1
|
2022-02-23T14:32:38.000Z
|
2022-02-23T14:32:38.000Z
|
code/backend/src/api/__init__.py
|
tobiasclaas/semantic-data-lake
|
16fc25a74918c9ac4d95f14bf3c15af053cee53e
|
[
"MIT"
] | null | null | null |
code/backend/src/api/__init__.py
|
tobiasclaas/semantic-data-lake
|
16fc25a74918c9ac4d95f14bf3c15af053cee53e
|
[
"MIT"
] | null | null | null |
from flask import Flask, Blueprint
from api import blueprints
def register(server: Flask):
for blueprint in vars(blueprints).values():
if isinstance(blueprint, Blueprint):
server.register_blueprint(blueprint, url_prefix="")
| 27.777778
| 63
| 0.724
| 29
| 250
| 6.172414
| 0.586207
| 0.201117
| 0
| 0
| 0
| 0
| 0
| 0
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0
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|
15c4a327933d78dc8ad08bb9e28b6ec10a41de85
| 230
|
py
|
Python
|
Back/submittext/admin.py
|
sadeghjafari5528/404-
|
0499b93cc473ec4def96d95364180eb4f4dafb11
|
[
"MIT"
] | null | null | null |
Back/submittext/admin.py
|
sadeghjafari5528/404-
|
0499b93cc473ec4def96d95364180eb4f4dafb11
|
[
"MIT"
] | 1
|
2020-12-27T14:59:35.000Z
|
2020-12-27T14:59:35.000Z
|
Back/submittext/admin.py
|
sadeghjafari5528/404-
|
0499b93cc473ec4def96d95364180eb4f4dafb11
|
[
"MIT"
] | 2
|
2020-10-30T08:08:32.000Z
|
2020-10-30T20:47:51.000Z
|
from django.contrib import admin
from .models import Answer , Question , User_Answer , User_Question
admin.site.register(Question)
admin.site.register(Answer)
admin.site.register(User_Answer)
admin.site.register(User_Question)
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| 67
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0
| 5
|
15cb9efbb9bac877963c0053fb475b9b1bb048bb
| 129
|
py
|
Python
|
tests/fixtures/cli/my-workflows-project/my_workflows_project/dags/hello_world_dag.py
|
The-Academic-Observatory/observatory-platform
|
31f27537d45ea5ab5f9bc069283e956b0e1f004d
|
[
"Apache-2.0",
"BSD-2-Clause"
] | 9
|
2020-07-21T02:06:55.000Z
|
2022-01-17T08:30:21.000Z
|
tests/fixtures/cli/my-workflows-project/my_workflows_project/dags/hello_world_dag.py
|
The-Academic-Observatory/observatory-platform
|
31f27537d45ea5ab5f9bc069283e956b0e1f004d
|
[
"Apache-2.0",
"BSD-2-Clause"
] | 387
|
2020-07-20T21:43:16.000Z
|
2022-03-31T02:31:55.000Z
|
tests/fixtures/cli/my-workflows-project/my_workflows_project/dags/hello_world_dag.py
|
The-Academic-Observatory/observatory-platform
|
31f27537d45ea5ab5f9bc069283e956b0e1f004d
|
[
"Apache-2.0",
"BSD-2-Clause"
] | 6
|
2020-07-20T12:03:37.000Z
|
2021-03-05T15:38:23.000Z
|
version https://git-lfs.github.com/spec/v1
oid sha256:ab4ad7d38c4b1e1b2c9d669db55f041d5ff8e72426541f402ae3a3f20c98941f
size 1388
| 32.25
| 75
| 0.883721
| 13
| 129
| 8.769231
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| 129
| 3
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|
0
| 5
|
15ccdd126011d5d91f017df95709bbf71749ef4c
| 84
|
py
|
Python
|
semana-04/exercicios/veiculos.py
|
larissajusten/ufsc-object-oriented-programming
|
839e6abcc20580ea1a47479232c3ed3cb0153e4b
|
[
"MIT"
] | 6
|
2021-11-29T05:43:19.000Z
|
2022-03-15T21:54:54.000Z
|
semana-04/exercicios/veiculos.py
|
larissajusten/ufsc-object-oriented-programming
|
839e6abcc20580ea1a47479232c3ed3cb0153e4b
|
[
"MIT"
] | 3
|
2021-11-21T03:44:03.000Z
|
2021-11-21T03:44:05.000Z
|
semana-04/exercicios/veiculos.py
|
larissajusten/ufsc-object-oriented-programming
|
839e6abcc20580ea1a47479232c3ed3cb0153e4b
|
[
"MIT"
] | null | null | null |
# Aplique os conceitos de classe abstrata e método abstrato no exemplo dos veículos.
| 84
| 84
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|
0
| 5
|
15dadac13359a5d1bf54da4f92ab1d7a1fb3a6cb
| 6,649
|
py
|
Python
|
tests/v2/test_models.py
|
benchuang11046/afs2-model
|
c821f078a2c1379b16273dc34d5d488a3d032f06
|
[
"Apache-2.0"
] | 2
|
2019-05-27T06:19:33.000Z
|
2021-01-24T14:39:25.000Z
|
tests/v2/test_models.py
|
benchuang11046/afs2-model
|
c821f078a2c1379b16273dc34d5d488a3d032f06
|
[
"Apache-2.0"
] | 24
|
2019-04-26T02:02:02.000Z
|
2020-05-14T10:18:55.000Z
|
tests/v2/test_models.py
|
benchuang11046/afs2-model
|
c821f078a2c1379b16273dc34d5d488a3d032f06
|
[
"Apache-2.0"
] | null | null | null |
from uuid import UUID
import pytest
def test_create_model(test_env, afs_models, clean_mr, delete_mr_and_model, model_file, model_repository_name):
resp = afs_models.upload_model(
model_path="unit_test_model",
accuracy=1.0,
loss=1.0,
tags={"tag_key": "tag_value"},
extra_evaluation={"extra_loss": 1.23},
model_repository_name=model_repository_name,
model_name="test_model",
)
assert isinstance(resp, dict)
assert "uuid" in resp
assert "name" in resp
assert "created_at" in resp
assert "tags" in resp
assert "evaluation_result" in resp
assert "feature_importance" in resp
assert "coefficient" in resp
def test_get_model_id(test_env, afs_models, model, delete_mr_and_model, model_file, model_repository_name):
get_resp = afs_models.get_model_id(
model_name="test_model",
model_repository_name=model_repository_name,
last_one=True,
)
assert get_resp == model["uuid"]
def test_delete_model(test_env, afs_models, model, delete_model_respository, model_repository_name):
resp = afs_models.delete_model(
model_name="test_model", model_repository_name=model_repository_name
)
assert resp == True
get_resp = afs_models.get_model_id(
model_name="test_model",
model_repository_name=model_repository_name,
last_one=True
)
assert get_resp == None
def test_get_model_info(test_env, afs_models, model, delete_mr_and_model, model_repository_name):
resp = afs_models.get_model_info(
model_name="test_model", model_repository_name=model_repository_name
)
assert resp["uuid"] == model["uuid"]
def test_get_latest_model_info(test_env, afs_models, model, delete_mr_and_model, model_repository_name):
resp = afs_models.get_latest_model_info(
model_repository_name=model_repository_name
)
assert resp["uuid"] == model["uuid"]
def test_download_model(test_env, afs_models, model, delete_mr_and_model, model_repository_name):
resp = afs_models.download_model(
save_path="download_model.h5",
model_repository_name=model_repository_name,
model_name="test_model",
)
assert resp == True
with open("download_model.h5", "r") as f:
content = f.read()
assert content == "unit test"
def test_create_firehose_apm_model(
test_env, afs_models, clean_mr, apm_node_env, delete_mr_and_model, model_file, model_repository_name
):
resp = afs_models.upload_model(
model_path="unit_test_model",
accuracy=1.0,
loss=1.0,
tags={"tag_key": "tag_value"},
model_repository_name=model_repository_name,
model_name="test_model",
)
assert isinstance(resp, dict)
assert "uuid" in resp
assert "name" in resp
assert "created_at" in resp
assert "tags" in resp
assert "evaluation_result" in resp
assert "apm_node" in resp["tags"]
assert "feature_importance" in resp
assert "coefficient" in resp
assert "3" in resp["tags"]["apm_node"]
get_resp = afs_models.get_model_id(
model_name="test_model",
model_repository_name=model_repository_name,
last_one=True,
)
assert get_resp == resp["uuid"]
def test_error1_create_firehose_apm_model(
test_env, afs_models, clean_mr, error1_apm_node_env, delete_mr_and_model, model_file, model_repository_name
):
resp = afs_models.upload_model(
model_path="unit_test_model",
accuracy=1.0,
loss=1.0,
tags={"tag_key": "tag_value"},
model_repository_name=model_repository_name,
model_name="test_model",
)
assert isinstance(resp, dict)
assert "uuid" in resp
assert "name" in resp
assert "created_at" in resp
assert "tags" in resp
assert "evaluation_result" in resp
assert "feature_importance" in resp
assert "coefficient" in resp
get_resp = afs_models.get_model_id(
model_name="test_model",
model_repository_name=model_repository_name,
last_one=True,
)
assert get_resp == resp["uuid"]
def test_create_model_with_datasetid_target(test_env, afs_models, clean_mr, delete_mr_and_model, model_file, model_repository_name):
resp = afs_models.upload_model(
model_path="unit_test_model",
accuracy=1.0,
loss=1.0,
tags={"tag_key": "tag_value"},
extra_evaluation={"extra_loss": 1.23},
model_repository_name=model_repository_name,
model_name="test_model",
)
assert isinstance(resp, dict)
assert "uuid" in resp
assert "name" in resp
assert "created_at" in resp
assert "tags" in resp
assert "evaluation_result" in resp
assert "feature_importance" in resp
assert "coefficient" in resp
assert "dataset_id" in resp
assert "afs_target" in resp
print(resp)
def test_create_model_with_ft_and_cofficient(test_env, afs_models, clean_mr, delete_mr_and_model, model_file, model_repository_name):
feature_importance = [
{'feature': 'petal_length', 'feature_importance': 0.9473576807512394},
{'feature': 'petal_width', 'feature_importance': 0.038191635936882906},
{'feature': 'sepal_length', 'feature_importance': 0.011053241240641932},
{'feature': 'sepal_width', 'feature_importance': 0.0033974420712357825}
]
coefficient = [
{'feature': 'B-0070-0068-1-FN66F_strength', 'coefficient': -4.730741400252476},
{'feature': 'B-0070-0068-1-FN66F_vendor', 'coefficient': -0.9335123601234512},
{'feature': 'B-0070-0068-1-FN66F_tensile','coefficient': 0.16411707246054036},
{'feature': 'B-0070-0068-1-FN66F_lot','coefficient': -0.08745686004816221},
{'feature': 'Machine','coefficient': 0.015048547152059243},
{'feature': 'Lot','coefficient': -0.010971975766858174},
{'feature': 'RPM','coefficient': 0.0003730247816832932},
{'feature': 'record_purpose','coefficient': 0.0}
]
resp = afs_models.upload_model(
model_path="unit_test_model",
accuracy=1.0,
loss=1.0,
tags={"tag_key": "tag_value"},
extra_evaluation={"extra_loss": 1.23},
feature_importance=feature_importance,
coefficient=coefficient,
model_repository_name=model_repository_name,
model_name="test_model",
)
assert isinstance(resp, dict)
assert "uuid" in resp
assert "name" in resp
assert "created_at" in resp
assert "tags" in resp
assert "evaluation_result" in resp
assert "feature_importance" in resp
assert "coefficient" in resp
print(resp)
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| 133
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| 34.811518
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| 0
| 0
|
0
| 5
|
15e03db2accdf86fb41e02d5542735c21cc28fe0
| 117
|
py
|
Python
|
Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/types/__init__.py
|
osoco/better-ways-of-thinking-about-software
|
83e70d23c873509e22362a09a10d3510e10f6992
|
[
"MIT"
] | 3
|
2021-12-15T04:58:18.000Z
|
2022-02-06T12:15:37.000Z
|
Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/types/__init__.py
|
osoco/better-ways-of-thinking-about-software
|
83e70d23c873509e22362a09a10d3510e10f6992
|
[
"MIT"
] | null | null | null |
Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/types/__init__.py
|
osoco/better-ways-of-thinking-about-software
|
83e70d23c873509e22362a09a10d3510e10f6992
|
[
"MIT"
] | 1
|
2022-02-06T10:48:15.000Z
|
2022-02-06T10:48:15.000Z
|
"""
Add here typing utilities API functions and classes.
"""
from .admin import admin_display
from .user import User
| 19.5
| 52
| 0.769231
| 17
| 117
| 5.235294
| 0.764706
| 0
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| 0.153846
| 117
| 5
| 53
| 23.4
| 0.89899
| 0.444444
| 0
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| null | 0
| 0
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| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
15fe390add7a95df55dc010cb620231ee23a5298
| 116
|
py
|
Python
|
evenflow/__init__.py
|
underscorefan/itsachemtrail_gatherer
|
7f85c09fa465d730f66935a5d683dc79f9f250db
|
[
"MIT"
] | null | null | null |
evenflow/__init__.py
|
underscorefan/itsachemtrail_gatherer
|
7f85c09fa465d730f66935a5d683dc79f9f250db
|
[
"MIT"
] | null | null | null |
evenflow/__init__.py
|
underscorefan/itsachemtrail_gatherer
|
7f85c09fa465d730f66935a5d683dc79f9f250db
|
[
"MIT"
] | null | null | null |
from evenflow.read_conf import Conf
from evenflow.pkg_info import *
from evenflow.scrapers.feed import FeedScraper
| 23.2
| 46
| 0.844828
| 17
| 116
| 5.647059
| 0.588235
| 0.375
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| 0.112069
| 116
| 4
| 47
| 29
| 0.932039
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| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
c60d5be62ed4c0d0f0997ad913d5bddeb94ba849
| 356
|
py
|
Python
|
oculus/models.py
|
edisonzhao/OculusServer
|
0337637f27d47991fdaf4e0f0612bac9400ac554
|
[
"Apache-2.0"
] | null | null | null |
oculus/models.py
|
edisonzhao/OculusServer
|
0337637f27d47991fdaf4e0f0612bac9400ac554
|
[
"Apache-2.0"
] | null | null | null |
oculus/models.py
|
edisonzhao/OculusServer
|
0337637f27d47991fdaf4e0f0612bac9400ac554
|
[
"Apache-2.0"
] | null | null | null |
from django.db import models
class Position(models.Model):
w = models.CharField(max_length=128, null=True, blank=True)
x = models.CharField(max_length=128, null=True, blank=True)
y = models.CharField(max_length=128, null=True, blank=True)
z = models.CharField(max_length=128, null=True, blank=True)
time_received = models.DateField()
| 35.6
| 63
| 0.730337
| 53
| 356
| 4.811321
| 0.415094
| 0.235294
| 0.282353
| 0.376471
| 0.690196
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| 0.690196
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| 0.690196
| 0
| 0
| 0.039344
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| 356
| 9
| 64
| 39.555556
| 0.796721
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0
| 5
|
c6584e7b1954e12f7407861db59487c242378e10
| 53
|
py
|
Python
|
labs_web/views/auth/__init__.py
|
okorienev/labs_web
|
9bfd69ffc2196832523d5809cf921debe530f886
|
[
"BSD-3-Clause"
] | 2
|
2018-04-22T11:34:09.000Z
|
2018-05-09T20:14:48.000Z
|
labs_web/views/auth/__init__.py
|
AlexPraefectus/labs_web
|
9bfd69ffc2196832523d5809cf921debe530f886
|
[
"BSD-3-Clause"
] | null | null | null |
labs_web/views/auth/__init__.py
|
AlexPraefectus/labs_web
|
9bfd69ffc2196832523d5809cf921debe530f886
|
[
"BSD-3-Clause"
] | null | null | null |
from .login import Login
from .auth_main import auth
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| 27
| 0.811321
| 9
| 53
| 4.666667
| 0.555556
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| 2
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|
0
| 5
|
d66e6152ca43259cb9d363711b486a80fb5e0f0a
| 73
|
py
|
Python
|
fishergw/taylorf2/__init__.py
|
cpacilio/fishergw
|
7cdb956066a3e174e4ca215876195606cd920f03
|
[
"MIT"
] | 2
|
2021-11-16T09:02:20.000Z
|
2022-02-11T02:42:13.000Z
|
fishergw/taylorf2/__init__.py
|
cpacilio/fishergw
|
7cdb956066a3e174e4ca215876195606cd920f03
|
[
"MIT"
] | 1
|
2022-01-05T19:46:03.000Z
|
2022-01-05T19:46:03.000Z
|
fishergw/taylorf2/__init__.py
|
cpacilio/fishergw
|
7cdb956066a3e174e4ca215876195606cd920f03
|
[
"MIT"
] | 2
|
2021-11-02T11:24:15.000Z
|
2022-02-03T01:42:02.000Z
|
from .waveform import TaylorF2, CompactObject
from .fisher import Fisher
| 24.333333
| 45
| 0.835616
| 9
| 73
| 6.777778
| 0.666667
| 0
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| 73
| 2
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| 1
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|
0
| 5
|
d6c9450983f3336d7541e46da6956fe7c51f82da
| 198
|
py
|
Python
|
gebastel/fct_ptr.py
|
bernd-clemenz/pmon
|
8b61de4864ffed2d7ee224c283090ed1948533ae
|
[
"MIT"
] | 1
|
2020-06-01T19:20:09.000Z
|
2020-06-01T19:20:09.000Z
|
gebastel/fct_ptr.py
|
bernd-clemenz/pmon
|
8b61de4864ffed2d7ee224c283090ed1948533ae
|
[
"MIT"
] | null | null | null |
gebastel/fct_ptr.py
|
bernd-clemenz/pmon
|
8b61de4864ffed2d7ee224c283090ed1948533ae
|
[
"MIT"
] | null | null | null |
#!/usr/bin/python3
class FctCheck:
def __init__(self):
pass
def ding_dong(self):
print('')
def _check_me(self, arg):
return True if arg is not None else False
| 16.5
| 49
| 0.59596
| 28
| 198
| 3.964286
| 0.821429
| 0
| 0
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| 0
| 0.007246
| 0.30303
| 198
| 11
| 50
| 18
| 0.797101
| 0.085859
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| false
| 0.142857
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| 0.714286
| 0.142857
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| null | 0
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| 1
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| 1
| 1
| 0
|
0
| 5
|
ba6cba1bd1b0a8dec3132820705b23b509e5b8b8
| 93
|
py
|
Python
|
chaturanga/__init__.py
|
Cheran-Senthil/Knights
|
0731d848f798bab16dda006188b77ad423ee07cc
|
[
"MIT"
] | 4
|
2019-01-27T14:01:03.000Z
|
2021-08-16T04:50:52.000Z
|
chaturanga/__init__.py
|
Cheran-Senthil/Knights
|
0731d848f798bab16dda006188b77ad423ee07cc
|
[
"MIT"
] | null | null | null |
chaturanga/__init__.py
|
Cheran-Senthil/Knights
|
0731d848f798bab16dda006188b77ad423ee07cc
|
[
"MIT"
] | 1
|
2018-10-25T20:57:43.000Z
|
2018-10-25T20:57:43.000Z
|
"""Initialization file"""
from .chessboard import Chessboard
from .bot import eval_func, bot
| 23.25
| 34
| 0.784946
| 12
| 93
| 6
| 0.666667
| 0
| 0
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| 0
| 0.11828
| 93
| 3
| 35
| 31
| 0.878049
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| 1
| 0
| 1
| 0
|
0
| 5
|
ba95f992e333c873bf0bf0f9b2a686e0b12babaa
| 116
|
py
|
Python
|
run.py
|
liusida/lstm_rl
|
641f94989e8669c97b03e41d003d0061b374ca79
|
[
"MIT"
] | null | null | null |
run.py
|
liusida/lstm_rl
|
641f94989e8669c97b03e41d003d0061b374ca79
|
[
"MIT"
] | null | null | null |
run.py
|
liusida/lstm_rl
|
641f94989e8669c97b03e41d003d0061b374ca79
|
[
"MIT"
] | null | null | null |
from lstm_rl.lstm_rl import LSTMRL
# import lstm_rl.envs # need this to register the bullet envs
LSTMRL().train()
| 23.2
| 62
| 0.767241
| 20
| 116
| 4.3
| 0.65
| 0.209302
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0.155172
| 116
| 4
| 63
| 29
| 0.877551
| 0.508621
| 0
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| 0
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| null | 1
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| null | 0
| 0
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| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
bac973cd9747e948283c5053c7e5ed4febd92b33
| 205
|
py
|
Python
|
test/hlt/pytest/python/com/huawei/iotplatform/client/dto/BatchTaskCreateOutDTO.py
|
yuanyi-thu/AIOT-
|
27f67d98324593c4c6c66bbd5e2a4aa7b9a4ac1e
|
[
"BSD-3-Clause"
] | 128
|
2018-10-29T04:11:47.000Z
|
2022-03-07T02:19:14.000Z
|
test/hlt/pytest/python/com/huawei/iotplatform/client/dto/BatchTaskCreateOutDTO.py
|
yuanyi-thu/AIOT-
|
27f67d98324593c4c6c66bbd5e2a4aa7b9a4ac1e
|
[
"BSD-3-Clause"
] | 40
|
2018-11-02T00:40:48.000Z
|
2021-12-07T09:33:56.000Z
|
test/hlt/pytest/python/com/huawei/iotplatform/client/dto/BatchTaskCreateOutDTO.py
|
yuanyi-thu/AIOT-
|
27f67d98324593c4c6c66bbd5e2a4aa7b9a4ac1e
|
[
"BSD-3-Clause"
] | 118
|
2018-10-29T08:43:57.000Z
|
2022-01-07T06:49:25.000Z
|
class BatchTaskCreateOutDTO(object):
def __init__(self):
self.taskID = None
def getTaskID(self):
return self.taskID
def setTaskID(self, taskID):
self.taskID = taskID
| 18.636364
| 36
| 0.639024
| 22
| 205
| 5.772727
| 0.5
| 0.314961
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.273171
| 205
| 10
| 37
| 20.5
| 0.852349
| 0
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| 1
| 0.428571
| false
| 0
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| 0.142857
| 0.714286
| 0
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| null | 1
| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
2432f76bf984ab24c73f9dad440b17602a0d534d
| 56
|
py
|
Python
|
cache_control_with_cloudfront_functions/__init__.py
|
bitesizedserverless/cache-control-with-cloudfront-functions
|
2c943acac014b5298ac9f919871284d4a9571144
|
[
"MIT"
] | null | null | null |
cache_control_with_cloudfront_functions/__init__.py
|
bitesizedserverless/cache-control-with-cloudfront-functions
|
2c943acac014b5298ac9f919871284d4a9571144
|
[
"MIT"
] | null | null | null |
cache_control_with_cloudfront_functions/__init__.py
|
bitesizedserverless/cache-control-with-cloudfront-functions
|
2c943acac014b5298ac9f919871284d4a9571144
|
[
"MIT"
] | null | null | null |
"""Main CacheControlWithCloudfrontFunctions package."""
| 28
| 55
| 0.821429
| 3
| 56
| 15.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.053571
| 56
| 1
| 56
| 56
| 0.867925
| 0.875
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
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| 1
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
244057c81cffab3124a9559e1ecc10b7f47b4080
| 295
|
py
|
Python
|
app/tools/errors.py
|
alexandrecorso/actraceroute
|
3d4889fd769f5801a9bf3ef49cf063c0e4a6b060
|
[
"MIT"
] | null | null | null |
app/tools/errors.py
|
alexandrecorso/actraceroute
|
3d4889fd769f5801a9bf3ef49cf063c0e4a6b060
|
[
"MIT"
] | 1
|
2021-05-10T10:32:29.000Z
|
2021-05-10T10:32:29.000Z
|
app/tools/errors.py
|
alexandrecorso/actraceroute
|
3d4889fd769f5801a9bf3ef49cf063c0e4a6b060
|
[
"MIT"
] | null | null | null |
class DNSError(Exception):
"""Raised when the resolv cannot be done"""
pass
class TimeExceeded(Exception):
"""Raised when the packet cannot reach the destination"""
pass
class UnknownError(Exception):
"""Raised when the error is unknown (not implemented yet)"""
pass
| 21.071429
| 64
| 0.694915
| 36
| 295
| 5.694444
| 0.611111
| 0.219512
| 0.278049
| 0.321951
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.20678
| 295
| 13
| 65
| 22.692308
| 0.876068
| 0.488136
| 0
| 0.5
| 0
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| 1
| 0
| true
| 0.5
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| 0.5
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| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
2454596990eb855520e7ad93f590d15e8835791a
| 60
|
py
|
Python
|
Adafruit_GPIO/__init__.py
|
MuddSub/Adafruit_Python_GPIO
|
68dd30554795c790f2d76da4f5a0e6e7d497324b
|
[
"MIT"
] | null | null | null |
Adafruit_GPIO/__init__.py
|
MuddSub/Adafruit_Python_GPIO
|
68dd30554795c790f2d76da4f5a0e6e7d497324b
|
[
"MIT"
] | null | null | null |
Adafruit_GPIO/__init__.py
|
MuddSub/Adafruit_Python_GPIO
|
68dd30554795c790f2d76da4f5a0e6e7d497324b
|
[
"MIT"
] | null | null | null |
from __future__ import absolute_import
from .GPIO import *
| 15
| 38
| 0.816667
| 8
| 60
| 5.5
| 0.625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15
| 60
| 3
| 39
| 20
| 0.862745
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
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| 1
| 0
| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
037acbdeca754e2aed5c6937978e496499b9dc1c
| 151
|
py
|
Python
|
odin/search/beam_search.py
|
tirkarthi/odin-ai
|
7900bef82ad8801d0c73880330d5b24d9ff7cd06
|
[
"MIT"
] | 7
|
2020-12-29T19:35:58.000Z
|
2022-01-31T21:01:30.000Z
|
odin/search/beam_search.py
|
tirkarthi/odin-ai
|
7900bef82ad8801d0c73880330d5b24d9ff7cd06
|
[
"MIT"
] | 3
|
2020-02-06T16:44:17.000Z
|
2020-09-26T05:26:14.000Z
|
odin/search/beam_search.py
|
tirkarthi/odin-ai
|
7900bef82ad8801d0c73880330d5b24d9ff7cd06
|
[
"MIT"
] | 6
|
2019-02-14T01:36:28.000Z
|
2020-10-30T13:16:32.000Z
|
from __future__ import absolute_import, division, print_function
def beam_search(matrix, beam_size=2, n_best=4):
pass
def greedy_search():
pass
| 16.777778
| 64
| 0.781457
| 23
| 151
| 4.695652
| 0.782609
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015385
| 0.139073
| 151
| 8
| 65
| 18.875
| 0.815385
| 0
| 0
| 0.4
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0.4
| 0.2
| 0
| 0.6
| 0.2
| 1
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| null | 0
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| 0
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| 0
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| null | 0
| 0
| 0
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| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
302cab259c8a61c9aa83e3a7f5a24f5b41731d3c
| 53
|
py
|
Python
|
flypy/__init__.py
|
token631/fly.py
|
e37ea1f63aaedafeb462249dafa6dc97200cb856
|
[
"MIT"
] | null | null | null |
flypy/__init__.py
|
token631/fly.py
|
e37ea1f63aaedafeb462249dafa6dc97200cb856
|
[
"MIT"
] | null | null | null |
flypy/__init__.py
|
token631/fly.py
|
e37ea1f63aaedafeb462249dafa6dc97200cb856
|
[
"MIT"
] | null | null | null |
from .exceptions import *
from .flypyClient import *
| 17.666667
| 26
| 0.773585
| 6
| 53
| 6.833333
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.150943
| 53
| 2
| 27
| 26.5
| 0.911111
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| 1
| 0
| 1
| 0
|
0
| 5
|
3064e0254d2a6da32473ed6376c41b14b8db866a
| 821
|
py
|
Python
|
recipes/pymot/setup.py
|
corneliusroemer/bioconda-recipes
|
e1eced9063e15f6a97ab2b8e42cf3e38af4c93ba
|
[
"MIT"
] | null | null | null |
recipes/pymot/setup.py
|
corneliusroemer/bioconda-recipes
|
e1eced9063e15f6a97ab2b8e42cf3e38af4c93ba
|
[
"MIT"
] | null | null | null |
recipes/pymot/setup.py
|
corneliusroemer/bioconda-recipes
|
e1eced9063e15f6a97ab2b8e42cf3e38af4c93ba
|
[
"MIT"
] | null | null | null |
#!/usr/bin/python
from setuptools import setup, find_packages
from os import listdir
pyfiles = [f.replace('.py', '') for f in listdir('.') if f.endswith('.py')]
setup(name='PyMOT', version='13.09.2016', description='The Multiple Object Tracking (MOT) metrics "multiple object tracking precision" (MOTP) and "multiple object tracking accuracy" (MOTA) allow for objective comparison of tracker characteristics [0]. The MOTP shows the ability of the tracker to estimate precise object positions, independent of its skill at recognizing object configurations, keeping consistent trajectories, and so forth. The MOTA accounts for all object configuration errors made by the tracker, false positives, misses, mismatches, over all frames.', url='https://github.com/Videmo/pymot', packages=find_packages(), py_modules=pyfiles)
| 102.625
| 657
| 0.780755
| 116
| 821
| 5.5
| 0.681034
| 0.065831
| 0.103448
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012448
| 0.119367
| 821
| 7
| 658
| 117.285714
| 0.869986
| 0.019488
| 0
| 0
| 0
| 0.25
| 0.706468
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
30739922ca2b5d9bd460c0c9635117bbb28c081a
| 5,534
|
py
|
Python
|
algorithms/ana/lib/__init__.py
|
pulp-platform/quantlib
|
bff5351f937c7dfd88e1ae44a146a257beca0585
|
[
"Apache-2.0"
] | null | null | null |
algorithms/ana/lib/__init__.py
|
pulp-platform/quantlib
|
bff5351f937c7dfd88e1ae44a146a257beca0585
|
[
"Apache-2.0"
] | null | null | null |
algorithms/ana/lib/__init__.py
|
pulp-platform/quantlib
|
bff5351f937c7dfd88e1ae44a146a257beca0585
|
[
"Apache-2.0"
] | 1
|
2022-01-02T10:10:46.000Z
|
2022-01-02T10:10:46.000Z
|
#
# __init__.py
#
# Author(s):
# Matteo Spallanzani <spmatteo@iis.ee.ethz.ch>
#
# Copyright (c) 2020-2021 ETH Zurich.
#
# 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 torch
from quantlib.algorithms.ana.lib import ana_normal, ana_logistic, ana_uniform, ana_triangular
try:
import ana_uniform_cuda
import ana_triangular_cuda
import ana_normal_cuda
import ana_logistic_cuda
use_ana_cuda_kernels = True
except ImportError:
use_ana_cuda_kernels = False
__all__ = [
'ANAUniform',
'ANATriangular',
'ANANormal',
'ANALogistic',
]
# uniform noise
class ANAUniform(torch.autograd.Function):
"""A stochastic process composed by step functions.
This class defines a stochastic process whose elementary events are step
functions with fixed quantization levels (codominion) and uniform noise on
the jumps positions.
"""
@staticmethod
def forward(ctx, x_in, q, t, mi, sigma, strategy, training):
ctx.save_for_backward(x_in, q, t, mi, sigma)
if use_ana_cuda_kernels and x_in.is_cuda:
x_out = ana_uniform_cuda.forward(x_in, q, t, mi, sigma, strategy, torch.Tensor([training]).to(sigma))
else:
x_out = ana_uniform.forward(x_in, q, t, mi, sigma, strategy, training)
return x_out
@staticmethod
def backward(ctx, grad_in):
x_in, q, t, mi, sigma = ctx.saved_tensors
if use_ana_cuda_kernels and grad_in.is_cuda:
grad_out = ana_uniform_cuda.backward(grad_in, x_in, q, t, mi, sigma)
else:
grad_out = ana_uniform.backward(grad_in, x_in, q, t, mi, sigma)
return grad_out, None, None, None, None, None, None
# triangular noise
class ANATriangular(torch.autograd.Function):
"""A stochastic process composed by step functions.
This class defines a stochastic process whose elementary events are step
functions with fixed quantization levels (codominion) and triangular noise
on the jumps positions.
"""
@staticmethod
def forward(ctx, x_in, q, t, mi, sigma, strategy, training):
ctx.save_for_backward(x_in, q, t, mi, sigma)
if use_ana_cuda_kernels and x_in.is_cuda:
x_out = ana_triangular_cuda.forward(x_in, q, t, mi, sigma, strategy, torch.Tensor([training]).to(sigma))
else:
x_out = ana_triangular.forward(x_in, q, t, mi, sigma, strategy, training)
return x_out
@staticmethod
def backward(ctx, grad_in):
x_in, q, t, mi, sigma = ctx.saved_tensors
if use_ana_cuda_kernels and grad_in.is_cuda:
grad_out = ana_triangular_cuda.backward(grad_in, x_in, q, t, mi, sigma)
else:
grad_out = ana_triangular.backward(grad_in, x_in, q, t, mi, sigma)
return grad_out, None, None, None, None, None, None
# normal noise
class ANANormal(torch.autograd.Function):
"""A stochastic process composed by step functions.
This class defines a stochastic process whose elementary events are step
functions with fixed quantization levels (codominion) and normal noise on
the jumps positions.
"""
@staticmethod
def forward(ctx, x_in, q, t, mi, sigma, strategy, training):
ctx.save_for_backward(x_in, q, t, mi, sigma)
if use_ana_cuda_kernels and x_in.is_cuda:
x_out = ana_normal_cuda.forward(x_in, q, t, mi, sigma, strategy, torch.Tensor([training]).to(sigma))
else:
x_out = ana_normal.forward(x_in, q, t, mi, sigma, strategy, training)
return x_out
@staticmethod
def backward(ctx, grad_in):
x_in, q, t, mi, sigma = ctx.saved_tensors
if use_ana_cuda_kernels and grad_in.is_cuda:
grad_out = ana_normal_cuda.backward(grad_in, x_in, q, t, mi, sigma)
else:
grad_out = ana_normal.backward(grad_in, x_in, q, t, mi, sigma)
return grad_out, None, None, None, None, None, None
# logistic noise
class ANALogistic(torch.autograd.Function):
"""A stochastic process composed by step functions.
This class defines a stochastic process whose elementary events are step
functions with fixed quantization levels (codominion) and logistic noise on
the jumps positions.
"""
@staticmethod
def forward(ctx, x_in, q, t, mi, sigma, strategy, training):
ctx.save_for_backward(x_in, q, t, mi, sigma)
if use_ana_cuda_kernels and x_in.is_cuda:
x_out = ana_logistic_cuda.forward(x_in, q, t, mi, sigma, strategy, torch.Tensor([training]).to(sigma))
else:
x_out = ana_logistic.forward(x_in, q, t, mi, sigma, strategy, training)
return x_out
@staticmethod
def backward(ctx, grad_in):
x_in, q, t, mi, sigma = ctx.saved_tensors
if use_ana_cuda_kernels and grad_in.is_cuda:
grad_out = ana_logistic_cuda.backward(grad_in, x_in, q, t, mi, sigma)
else:
grad_out = ana_logistic.backward(grad_in, x_in, q, t, mi, sigma)
return grad_out, None, None, None, None, None, None
| 35.703226
| 116
| 0.681424
| 821
| 5,534
| 4.390987
| 0.170524
| 0.02663
| 0.031068
| 0.038835
| 0.711234
| 0.711234
| 0.711234
| 0.711234
| 0.711234
| 0.711234
| 0
| 0.002813
| 0.229129
| 5,534
| 154
| 117
| 35.935065
| 0.842241
| 0.281894
| 0
| 0.571429
| 0
| 0
| 0.011134
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.095238
| false
| 0
| 0.083333
| 0
| 0.321429
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
067cebdfc9dcae4a06bb6cf0f4db2aa7ff753a88
| 56
|
py
|
Python
|
duckt/__init__.py
|
monomonedula/duckt
|
531c2f5e877ba0411d403fbb31de2fd8323ba143
|
[
"MIT"
] | null | null | null |
duckt/__init__.py
|
monomonedula/duckt
|
531c2f5e877ba0411d403fbb31de2fd8323ba143
|
[
"MIT"
] | null | null | null |
duckt/__init__.py
|
monomonedula/duckt
|
531c2f5e877ba0411d403fbb31de2fd8323ba143
|
[
"MIT"
] | null | null | null |
from duckt.duck_traverse import Duck, DuckGet, DuckCall
| 28
| 55
| 0.839286
| 8
| 56
| 5.75
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.107143
| 56
| 1
| 56
| 56
| 0.92
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
0685c65c096475b8dbc26de34f93406d5d89a8c2
| 55
|
py
|
Python
|
parallelpandas/__init__.py
|
gameduell/parallelpandas
|
967fba7a37247897001dbe0c065820ef511acb12
|
[
"MIT"
] | 1
|
2016-05-26T07:58:58.000Z
|
2016-05-26T07:58:58.000Z
|
parallelpandas/__init__.py
|
gameduell/parallelpandas
|
967fba7a37247897001dbe0c065820ef511acb12
|
[
"MIT"
] | null | null | null |
parallelpandas/__init__.py
|
gameduell/parallelpandas
|
967fba7a37247897001dbe0c065820ef511acb12
|
[
"MIT"
] | null | null | null |
from parallelpandas.mp_impl import apply, groupby_apply
| 55
| 55
| 0.890909
| 8
| 55
| 5.875
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.072727
| 55
| 1
| 55
| 55
| 0.921569
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
06a059415e21ccd4fe155a3dfb6785b8720492aa
| 862
|
py
|
Python
|
tests/test_provider_Ouest_France_ldap.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 507
|
2017-07-26T02:58:38.000Z
|
2022-01-21T12:35:13.000Z
|
tests/test_provider_Ouest_France_ldap.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 135
|
2017-07-20T12:01:59.000Z
|
2021-10-04T22:25:40.000Z
|
tests/test_provider_Ouest_France_ldap.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 81
|
2018-02-20T17:55:28.000Z
|
2022-01-31T07:08:40.000Z
|
# tests/test_provider_Ouest-France_ldap.py
# Automatically generated by tools/makecode.py (24-Sep-2021 15:20:59 UTC)
def test_provider_import():
import terrascript.provider.Ouest_France.ldap
def test_resource_import():
from terrascript.resource.Ouest_France.ldap import ldap_group
def test_datasource_import():
from terrascript.data.Ouest_France.ldap import ldap_group
from terrascript.data.Ouest_France.ldap import ldap_user
# TODO: Shortcut imports without namespace for official and supported providers.
# TODO: This has to be moved into a required_providers block.
# def test_version_source():
#
# import terrascript.provider.Ouest_France.ldap
#
# t = terrascript.provider.Ouest_France.ldap.ldap()
# s = str(t)
#
# assert 'https://github.com/Ouest-France/terraform-provider-ldap' in s
# assert '0.7.2' in s
| 27.806452
| 80
| 0.756381
| 123
| 862
| 5.130081
| 0.495935
| 0.139461
| 0.166403
| 0.1458
| 0.375594
| 0.321712
| 0.139461
| 0.139461
| 0
| 0
| 0
| 0.020492
| 0.150812
| 862
| 30
| 81
| 28.733333
| 0.84153
| 0.580046
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0.033333
| 0
| 1
| 0.428571
| true
| 0
| 1
| 0
| 1.428571
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
06b20e01ddbf2d8fb4b1691f35dfdfcc3e165b25
| 34
|
py
|
Python
|
xpctl/backends/__init__.py
|
mead-ml/xpctl
|
75fcb195e66519b545ddd7aeb2d7476624c20c46
|
[
"Apache-2.0"
] | 3
|
2019-07-11T17:05:25.000Z
|
2020-11-19T08:11:31.000Z
|
xpctl/backends/__init__.py
|
mead-ml/xpctl
|
75fcb195e66519b545ddd7aeb2d7476624c20c46
|
[
"Apache-2.0"
] | 4
|
2019-06-28T01:07:42.000Z
|
2020-07-24T15:12:57.000Z
|
xpctl/backends/__init__.py
|
mead-ml/xpctl
|
75fcb195e66519b545ddd7aeb2d7476624c20c46
|
[
"Apache-2.0"
] | 2
|
2019-06-27T19:10:05.000Z
|
2019-08-15T20:15:49.000Z
|
from xpctl.backends.core import *
| 17
| 33
| 0.794118
| 5
| 34
| 5.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 34
| 1
| 34
| 34
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
23785931bfc8daf0f5dd7ce67a31adfefbdedcb7
| 68
|
py
|
Python
|
django_twitter_photo_api/app_settings.py
|
softformance/django-twitter-photo-api
|
0475d6a061e10643c90959253e557f0016ae9ade
|
[
"MIT"
] | null | null | null |
django_twitter_photo_api/app_settings.py
|
softformance/django-twitter-photo-api
|
0475d6a061e10643c90959253e557f0016ae9ade
|
[
"MIT"
] | null | null | null |
django_twitter_photo_api/app_settings.py
|
softformance/django-twitter-photo-api
|
0475d6a061e10643c90959253e557f0016ae9ade
|
[
"MIT"
] | null | null | null |
from django.conf import settings
#Insert here your settings const.
| 17
| 33
| 0.808824
| 10
| 68
| 5.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.147059
| 68
| 3
| 34
| 22.666667
| 0.948276
| 0.470588
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
88be6ec0f8d74d96e6c083c46bb2bf15df512104
| 146
|
py
|
Python
|
apps/assignments/urls.py
|
Ev1dentSnow/ArtemisAPI_django
|
ca7ef0ccc97114f2c5439b7b1bbc0e635facf020
|
[
"MIT"
] | null | null | null |
apps/assignments/urls.py
|
Ev1dentSnow/ArtemisAPI_django
|
ca7ef0ccc97114f2c5439b7b1bbc0e635facf020
|
[
"MIT"
] | null | null | null |
apps/assignments/urls.py
|
Ev1dentSnow/ArtemisAPI_django
|
ca7ef0ccc97114f2c5439b7b1bbc0e635facf020
|
[
"MIT"
] | null | null | null |
from django.urls import path
import apps.assignments.views
urlpatterns = [
path('', apps.assignments.views.AssignmentsListView.as_view()),
]
| 20.857143
| 67
| 0.760274
| 17
| 146
| 6.470588
| 0.705882
| 0.272727
| 0.363636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116438
| 146
| 7
| 68
| 20.857143
| 0.852713
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
88c0c029cd46635263b5277c561fefa6a5ed34f2
| 316
|
py
|
Python
|
project_checker/checker/project/__init__.py
|
zuzannnaobajtek/github-cmake-project-checker
|
1406c2247bbbecb490bc5000c7fa521b9bf96ec0
|
[
"MIT"
] | 1
|
2017-05-17T21:21:54.000Z
|
2017-05-17T21:21:54.000Z
|
project_checker/checker/project/__init__.py
|
zuzannnaobajtek/github-cmake-project-checker
|
1406c2247bbbecb490bc5000c7fa521b9bf96ec0
|
[
"MIT"
] | 13
|
2018-03-28T15:36:17.000Z
|
2018-04-25T16:44:00.000Z
|
project_checker/checker/project/__init__.py
|
zuzannnaobajtek/github-cmake-project-checker
|
1406c2247bbbecb490bc5000c7fa521b9bf96ec0
|
[
"MIT"
] | 15
|
2017-05-31T11:44:20.000Z
|
2018-04-19T15:03:35.000Z
|
from project_checker.checker.project.studentproject import StudentProject
from project_checker.checker.project.config import Deadlines
from project_checker.checker.project.config import Groups
from project_checker.checker.project.config import ProjectOwners
from project_checker.checker.project.config import Config
| 52.666667
| 73
| 0.889241
| 40
| 316
| 6.9
| 0.225
| 0.199275
| 0.326087
| 0.452899
| 0.753623
| 0.637681
| 0.637681
| 0
| 0
| 0
| 0
| 0
| 0.063291
| 316
| 5
| 74
| 63.2
| 0.932432
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
cc5bc567e11a9ab8a19ff7b613471ad5086649cb
| 5,955
|
py
|
Python
|
exercises/concept/meltdown-mitigation/conditionals_test.py
|
ee7/python
|
3d61bacbd87e45dc7209620523ae13628e5a2fd8
|
[
"MIT"
] | null | null | null |
exercises/concept/meltdown-mitigation/conditionals_test.py
|
ee7/python
|
3d61bacbd87e45dc7209620523ae13628e5a2fd8
|
[
"MIT"
] | 11
|
2021-05-12T06:08:19.000Z
|
2022-03-02T12:10:44.000Z
|
exercises/concept/meltdown-mitigation/conditionals_test.py
|
ee7/python
|
3d61bacbd87e45dc7209620523ae13628e5a2fd8
|
[
"MIT"
] | null | null | null |
# unit test here
import unittest
import pytest
from conditionals import (is_criticality_balanced,
reactor_efficency,
fail_safe
)
class TestConditionals(unittest.TestCase):
# Checking the first condition using assertTrue and assertFalse
# The values for arguments is not final and should be considered as placeholders
# More test-cases required for full testing
@pytest.mark.task(taskno=1)
def test_is_criticality_balanced_set1(self):
self.assertTrue(is_criticality_balanced(
temperature=750, neutrons_emitted=650), msg="Expected True but returned False")
@pytest.mark.task(taskno=1)
def test_is_criticality_balanced_set2(self):
self.assertTrue(is_criticality_balanced(
temperature=799, neutrons_emitted=501), msg="Expected True but returned False")
@pytest.mark.task(taskno=1)
def test_is_criticality_balanced_set3(self):
self.assertTrue(
is_criticality_balanced(temperature=500, neutrons_emitted=600), msg="Expected True but returned False"
)
@pytest.mark.task(taskno=1)
def test_is_criticality_balanced_set4(self):
self.assertFalse(
is_criticality_balanced(temperature=800, neutrons_emitted=500), msg="Expected False but returned True"
)
# End of first functions testing
# Test case for reactor_efficency()
# Checking the second condition using assertEqual
# The values for arguments is not final and should be considered as placeholders
# More test-cases required for full testing
# need to add more info to messages
# Need to verify if f-string based errors allowed
@pytest.mark.task(taskno=2)
def test_reactor_efficency_set1(self):
test_return = reactor_efficency(
voltage=100, current=50, theoretical_max_power=5000)
self.assertEqual(
test_return, 'green', msg=f"Expected green but returned {test_return}"
)
@pytest.mark.task(taskno=2)
def test_reactor_efficency_set2(self):
test_return = reactor_efficency(
voltage=100, current=30, theoretical_max_power=5000)
self.assertEqual(
test_return, 'orange', msg=f"Expected orange but returned {test_return}"
)
@pytest.mark.task(taskno=2)
def test_reactor_efficency_set3(self):
test_return = reactor_efficency(
voltage=100, current=28, theoretical_max_power=5000)
self.assertEqual(
test_return, 'red', msg=f"Expected red but returned {test_return}"
)
@pytest.mark.task(taskno=2)
def test_reactor_efficency_set4(self):
test_return = reactor_efficency(
voltage=100, current=10, theoretical_max_power=5000)
self.assertEqual(
test_return, 'black', msg=f"Expected black but returned {test_return}"
)
# End of second function testing
# Test case for fail_safe()
# Checking the third condition using assertEqual
# The values for arguments is not final and should be considered as placeholders
# More test-cases required for full testing
# need to add more info to messages
# Need to verify if f-string based errors allowed
@pytest.mark.task(taskno=3)
def test_fail_safe_set1(self):
test_return = fail_safe(
temperature=100, neutrons_produced_per_second=18, threshold=5000)
self.assertEqual(
test_return, 'LOW', msg=f"Expected LOW but returned {test_return}"
)
@pytest.mark.task(taskno=3)
def test_fail_safe_set2(self):
test_return = fail_safe(
temperature=100, neutrons_produced_per_second=12, threshold=4000)
self.assertEqual(
test_return, 'LOW', msg=f"Expected LOW but returned {test_return}"
)
@pytest.mark.task(taskno=3)
def test_fail_safe_set3(self):
test_return = fail_safe(
temperature=100, neutrons_produced_per_second=10, threshold=3000)
self.assertEqual(
test_return, 'LOW', msg=f"Expected LOW but returned {test_return}"
)
@pytest.mark.task(taskno=3)
def test_fail_safe_set4(self):
test_return = fail_safe(
temperature=100, neutrons_produced_per_second=55, threshold=5000)
self.assertEqual(
test_return, 'NORMAL', msg=f"Expected NORMAL but returned {test_return}"
)
@pytest.mark.task(taskno=3)
def test_fail_safe_set5(self):
test_return = fail_safe(
temperature=100, neutrons_produced_per_second=45, threshold=5000)
self.assertEqual(
test_return, 'NORMAL', msg=f"Expected NORMAL but returned {test_return}"
)
@pytest.mark.task(taskno=3)
def test_fail_safe_set6(self):
test_return = fail_safe(
temperature=100, neutrons_produced_per_second=50, threshold=5000)
self.assertEqual(
test_return, 'NORMAL', msg=f"Expected NORMAL but returned {test_return}"
)
@pytest.mark.task(taskno=3)
def test_fail_safe_set7(self):
test_return = fail_safe(
temperature=1000, neutrons_produced_per_second=35, threshold=5000)
self.assertEqual(
test_return, 'DANGER', msg=f"Expected DANGER but returned {test_return}"
)
@pytest.mark.task(taskno=3)
def test_fail_safe_set8(self):
test_return = fail_safe(
temperature=1000, neutrons_produced_per_second=30, threshold=5000)
self.assertEqual(
test_return, 'DANGER', msg=f"Expected DANGER but returned {test_return}"
)
@pytest.mark.task(taskno=3)
def test_fail_safe_set9(self):
test_return = fail_safe(
temperature=1000, neutrons_produced_per_second=25, threshold=5000)
self.assertEqual(
test_return, 'DANGER', msg=f"Expected DANGER but returned {test_return}"
)
| 36.310976
| 114
| 0.67204
| 742
| 5,955
| 5.177898
| 0.168464
| 0.10151
| 0.061947
| 0.088496
| 0.812598
| 0.812598
| 0.809214
| 0.770172
| 0.671265
| 0.660854
| 0
| 0.039573
| 0.244668
| 5,955
| 163
| 115
| 36.533742
| 0.814584
| 0.138203
| 0
| 0.465517
| 0
| 0
| 0.1416
| 0
| 0
| 0
| 0
| 0
| 0.146552
| 1
| 0.146552
| false
| 0
| 0.025862
| 0
| 0.181034
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
ccc80086782835d3c5b364ed48a98d66d280135b
| 114
|
py
|
Python
|
module/generic/admin.py
|
pavanmaganti9/django_app
|
c13172053a09960d9cb3594bc8cdf2352e5bd655
|
[
"bzip2-1.0.6"
] | null | null | null |
module/generic/admin.py
|
pavanmaganti9/django_app
|
c13172053a09960d9cb3594bc8cdf2352e5bd655
|
[
"bzip2-1.0.6"
] | null | null | null |
module/generic/admin.py
|
pavanmaganti9/django_app
|
c13172053a09960d9cb3594bc8cdf2352e5bd655
|
[
"bzip2-1.0.6"
] | null | null | null |
from django.contrib import admin
# Register your models here.
from .models import crud
admin.site.register(crud)
| 19
| 32
| 0.798246
| 17
| 114
| 5.352941
| 0.647059
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131579
| 114
| 6
| 33
| 19
| 0.919192
| 0.22807
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
ccd4cbbedd04ba41bf9e3ad8aca7d568280253dd
| 69
|
py
|
Python
|
src/options/__init__.py
|
joacocruz6/RevisadorTareas
|
3c1c27eca93bb144cedbbcfcf35cd100344320a5
|
[
"MIT"
] | 1
|
2019-05-04T06:23:35.000Z
|
2019-05-04T06:23:35.000Z
|
src/options/__init__.py
|
joacocruz6/HomeworkMarker
|
3c1c27eca93bb144cedbbcfcf35cd100344320a5
|
[
"MIT"
] | null | null | null |
src/options/__init__.py
|
joacocruz6/HomeworkMarker
|
3c1c27eca93bb144cedbbcfcf35cd100344320a5
|
[
"MIT"
] | null | null | null |
from .TestCase import TestCase
from .TesterOptions import TestOptions
| 34.5
| 38
| 0.869565
| 8
| 69
| 7.5
| 0.625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.101449
| 69
| 2
| 38
| 34.5
| 0.967742
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
4e002fca034701d420865a3534ee4181398c24e0
| 139
|
py
|
Python
|
ml/vision/datasets/__init__.py
|
necla-ml/ML-Vision
|
66229b29fc0f67c75dbe6304cdb8c5e93fe0bacf
|
[
"BSD-3-Clause"
] | 1
|
2021-08-04T12:33:25.000Z
|
2021-08-04T12:33:25.000Z
|
ml/vision/datasets/__init__.py
|
necla-ml/ML-Vision
|
66229b29fc0f67c75dbe6304cdb8c5e93fe0bacf
|
[
"BSD-3-Clause"
] | 1
|
2021-11-02T21:29:44.000Z
|
2021-12-02T15:49:17.000Z
|
ml/vision/datasets/__init__.py
|
necla-ml/ML-Vision
|
66229b29fc0f67c75dbe6304cdb8c5e93fe0bacf
|
[
"BSD-3-Clause"
] | null | null | null |
from torchvision.datasets import *
from .flickr import Flickr30kEntities
from .widerperson import WiderPerson
from .sku110k import SKU110K
| 27.8
| 37
| 0.848921
| 16
| 139
| 7.375
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.065041
| 0.115108
| 139
| 4
| 38
| 34.75
| 0.894309
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
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