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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
8bff289fee0564050c0fdeb1e26fa1cfcdb3e115
| 76
|
py
|
Python
|
lesson_tasks/lesson4/num2.1.py
|
NikaEgorova/goiteens-python3-egorova
|
809059abf3464cbe4f0f116e52ce53534a0ca5ba
|
[
"MIT"
] | null | null | null |
lesson_tasks/lesson4/num2.1.py
|
NikaEgorova/goiteens-python3-egorova
|
809059abf3464cbe4f0f116e52ce53534a0ca5ba
|
[
"MIT"
] | null | null | null |
lesson_tasks/lesson4/num2.1.py
|
NikaEgorova/goiteens-python3-egorova
|
809059abf3464cbe4f0f116e52ce53534a0ca5ba
|
[
"MIT"
] | null | null | null |
boy_have = ['pen', 'pencil', 'rubber', 'candy', 'gum']
print(len(boy_have))
| 25.333333
| 54
| 0.618421
| 11
| 76
| 4.090909
| 0.818182
| 0.311111
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.105263
| 76
| 2
| 55
| 38
| 0.661765
| 0
| 0
| 0
| 0
| 0
| 0.302632
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 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
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
e30aa212e5938a3204c29d100994a0bdee74978d
| 236
|
py
|
Python
|
server/budgettrackerbackend/budgets/admin.py
|
gmulz/budget-tracker-2
|
0abc144d50420875853e89080ec5cac27cc256a4
|
[
"MIT"
] | null | null | null |
server/budgettrackerbackend/budgets/admin.py
|
gmulz/budget-tracker-2
|
0abc144d50420875853e89080ec5cac27cc256a4
|
[
"MIT"
] | null | null | null |
server/budgettrackerbackend/budgets/admin.py
|
gmulz/budget-tracker-2
|
0abc144d50420875853e89080ec5cac27cc256a4
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
# Register your models here.
from .models import Transaction, Category, User, Income
admin.site.register(Transaction)
admin.site.register(Category)
admin.site.register(User)
admin.site.register(Income)
| 26.222222
| 55
| 0.813559
| 32
| 236
| 6
| 0.4375
| 0.1875
| 0.354167
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.088983
| 236
| 9
| 56
| 26.222222
| 0.893023
| 0.110169
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 0
| 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
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
e30b9ed6b2134e7304c1832161c85928883543a9
| 10,873
|
py
|
Python
|
DatabaseOperation.py
|
Must-Student/Must-ExchangeRoom
|
f506eab36f39a4dafa3071aae2814e5a101a8a56
|
[
"Apache-2.0"
] | 1
|
2020-09-04T09:47:29.000Z
|
2020-09-04T09:47:29.000Z
|
DatabaseOperation.py
|
Must-Student/Must-ExchangeRoom
|
f506eab36f39a4dafa3071aae2814e5a101a8a56
|
[
"Apache-2.0"
] | 2
|
2020-09-04T09:40:33.000Z
|
2020-09-14T10:52:53.000Z
|
DatabaseOperation.py
|
Must-Student/Must-ExchangeRoom
|
f506eab36f39a4dafa3071aae2814e5a101a8a56
|
[
"Apache-2.0"
] | 2
|
2021-05-13T03:00:12.000Z
|
2021-05-17T09:19:20.000Z
|
#!/usr/bin/env python3
# coding:utf-8
import pymysql
import hashlib
def md5(password):
password=password.encode(encoding='utf-8')
hashedPassword=hashlib.md5()
hashedPassword.update(password)
return (hashedPassword.hexdigest())
sqlservername='servernamehere'
sqluser='usernamehere'
sqlpasswd='passwordhere'
sqldatabase='databasenamehere'
def CheckIfUserExist(emailaddress):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = 'select EmailAddress from ' + sqldatabase + '.AccountInfo where EmailAddress =' + "'" + emailaddress + "'"
check.execute(sql)
temp=check.fetchone()
temp= list(str(temp).replace('(', '').replace(')', '').replace("'", "").split(','))
if temp[0]==emailaddress:
return 0
else:
return 1
def adduser(EmailAddress,UserName,ContactInfo,PassWord,IsVerified,Sex,Address,Model,IdealAddress,IdealModel,Note):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = "insert into ExchangeRoom.AccountInfo (EmailAddress,UserName,ContactInfo,PassWord,IsVerified,Md5,Sex,Address,Model,IdealAddress,IdealModel,Note,AssociateEmail,MyDeal) VALUES (" + "'" + EmailAddress + "'" + ","+"'" + UserName + "'" + ","+"'" + ContactInfo + "'" + ","+"'" + PassWord + "'" + ","+"'" + IsVerified + "'" + ","+"'" + str(md5(PassWord))+'2020' + "'" + ","+ "'" + Sex + "'"+ ","+"'" + Address + "'" + ","+"'" + Model + "'" + ","+"'" + IdealAddress + "'" + ","+"'" + IdealModel + "'" + ","+"'" + Note + "'"+ ","+"'" + EmailAddress + "'"+ ","+"'" + '0' + "'" + ")"
check.execute(sql)
db.commit()
#SecSql="insert into ExchangeRoom.AccountInfo (Address,Model,IdealAddress,IdealModel,Note,AssociateEmail) VALUES ("+"'" + Address + "'" + ","+"'" + Model + "'" + ","+"'" + IdealAddress + "'" + ","+"'" + IdealModel + "'" + ","+"'" + Note + "'"+ ","+"'" + EmailAddress + "'" + ")"
#check.execute(SecSql)
#db.commit()
db.close()
return 1
def CheckVerifyCode(VerifyCode,EmailAddress):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = 'select IsVerified from ' + sqldatabase + '.AccountInfo where EmailAddress =' + "'" + EmailAddress + "'"
check.execute(sql)
a = check.fetchone()
a = list(str(a).replace('(', '').replace(')', '').replace("'", "").split(','))
if a[0] == VerifyCode:
return 1
else:
return 0
def UpdateIsVerified(EmailAddress,VerifyCode):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql='update '+sqldatabase+'.AccountInfo set IsVerified='+VerifyCode+' where EmailAddress='+ "'" +EmailAddress+ "'"
check.execute(sql)
db.commit()
db.close()
return 1
def ReadMd5(EmailAddress):
try:
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = 'select Md5 from ' + sqldatabase + '.AccountInfo where EmailAddress =' + "'" + str(EmailAddress) + "'"
# print(sql)
check.execute(sql)
a = check.fetchone()
a = list(str(a).replace('(', '').replace(')', '').replace("'", "").split(','))
# print(a)
if a[0] is not None:
return a[0]
else:
return 0
except:
return 0
def CheckEmailAddressPassWord(EmailAddress,PassWord):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = 'select PassWord from ' + sqldatabase + '.AccountInfo where EmailAddress =' + "'" + EmailAddress + "'"
check.execute(sql)
a = check.fetchone()
a = list(str(a).replace('(', '').replace(')', '').replace("'", "").split(','))
if a[0] == PassWord:
return 1
else:
return 0
def ReturnAllData(Sex):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = "select UserName, Sex, Address, Model, ContactInfo, Note,IdealAddress, IdealModel, MyDeal from ExchangeRoom.AccountInfo where Sex="+"'"+Sex+"'"
check.execute(sql)
a = check.fetchall()
#print(a)
return a
def ReturnSexFromEmail(EmailAddress):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = "select Sex from ExchangeRoom.AccountInfo where EmailAddress="+"'"+EmailAddress+"'"
check.execute(sql)
a = check.fetchone()
return a[0]
def ReturnInfoFromSexAndModel(Sex,Model):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = "select UserName, Sex, Address, Model, ContactInfo, Note,IdealAddress, IdealModel, MyDeal from ExchangeRoom.AccountInfo where Sex="+"'"+Sex+"'"+" and Model="+"'"+Model+"'"
check.execute(sql)
a = check.fetchall()
# print(a)
return a
def ReturnInfoFromSexAndAddress(Sex,Address):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = "select UserName, Sex, Address, Model, ContactInfo, Note,IdealAddress, IdealModel, MyDeal from ExchangeRoom.AccountInfo where Sex=" + "'" + Sex + "'" + " and Address=" + "'" + Address + "'"
check.execute(sql)
a = check.fetchall()
# print(a)
return a
def ReturnInfoFromSexAndAddressAndModel(Sex,Address,Model):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = "select UserName, Sex, Address, Model, ContactInfo, Note,IdealAddress, IdealModel, MyDeal from ExchangeRoom.AccountInfo where Sex=" + "'" + Sex + "'" + " and Address=" + "'" + Address + "'"+ " and Model=" + "'" + Model + "'"
check.execute(sql)
a = check.fetchall()
# print(a)
return a
def ReturnInfoFromSexIdealAddressIdealModel(Sex,IdealAddress,IdealModel,Address,Model):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql=''
if IdealModel=='0':
if IdealAddress=='0':
sql="select EmailAddress, UserName, Sex, Address, Model, ContactInfo, Note,MyDeal from ExchangeRoom.AccountInfo where Sex=" + "'" + Sex + "'" + " and (IdealAddress='0' or IdealAddress=" + "'" + Address + "')"+ " and (IdealModel='0' or IdealModel=" + "'" + Model + "')"
else:
sql = "select EmailAddress, UserName, Sex, Address, Model, ContactInfo, Note,MyDeal from ExchangeRoom.AccountInfo where Sex=" + "'" + Sex + "'" + " and Address=" + "'" + IdealAddress + "'" + + " and (IdealAddress='0' or IdealAddress='" + "'" + Address + "')" + " and (IdealModel='0' or IdealModel=" + "'" + Model + "')"
else:
if IdealAddress=='0':
sql = "select EmailAddress, UserName, Sex, Address, Model, ContactInfo, Note,MyDeal from ExchangeRoom.AccountInfo where Sex=" + "'" + Sex + "'" + " and Model=" + "'" + IdealModel + "'" + " and (IdealAddress='0' or IdealAddress=" + "'" + Address + "')" + " and (IdealModel='0' or IdealModel=" + "'" + Model + "')"
else:
sql = "select EmailAddress, UserName, Sex, Address, Model, ContactInfo, Note,MyDeal from ExchangeRoom.AccountInfo where Sex=" + "'" + Sex + "'" + " and Address=" + "'" + IdealAddress + "'" + " and Model=" + "'" + IdealModel + "'" + " and (IdealAddress='0' or IdealAddress=" + "'" + Address + "')" + " and (IdealModel='0' or IdealModel=" + "'" + Model + "')"
#print(sql)
check.execute(sql)
a = check.fetchall()
# print(a)
return a
def ReturnEmailAddressIsVerified(EmailAddress):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = "select IsVerified from ExchangeRoom.AccountInfo where EmailAddress=" + "'" + EmailAddress + "'"
try :
check.execute(sql)
a=check.fetchone()
if a[0]=='1':
return 1
else:
return 0
except:
return 0
def ReturnInfoFromEmailAddress(EmailAddress):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = "select UserName, Sex, Address, Model, ContactInfo, Note,IdealAddress, IdealModel, MyDeal from ExchangeRoom.AccountInfo where EmailAddress=" + "'" + EmailAddress + "'"
check.execute(sql)
a = check.fetchone()
# print(a)
return a
def CheckEmailAddressAlreadyExist(EmailAddress):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = "select EmailAddress from ExchangeRoom.AccountInfo where EmailAddress=" + "'" + EmailAddress + "'"
try:
check.execute(sql)
a = check.fetchone()
print(a)
if a[0]==EmailAddress:
return 1
if a[0]=='':
return 0
except:
return 0
def UpdateUserInfo(UserName,ContactInfo,Address,Model,IdealAddress,IdealModel,Note,EmailAddress):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql='update '+sqldatabase+'.AccountInfo set Username='+"'"+UserName+"',"+' ContactInfo='+"'"+ContactInfo+"',"+' Address='+"'"+Address+"',"+' Model='+"'"+Model+"',"+' IdealAddress='+"'"+IdealAddress+"',"+' IdealModel='+"'"+IdealModel+"',"+' Note='+"'"+Note+"'"+' where EmailAddress='+"'"+EmailAddress+"';"
print(sql)
check.execute(sql)
db.commit()
db.close()
return 1
def UpdateBackupEmailAddressByEmailAddress(BackupEmailAddress,EmailAddress,IsVerified):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = 'update ' + sqldatabase + '.AccountInfo set BackupEmailAddress=' + "'" + BackupEmailAddress + "'," +' IsVerified='+ "'" + IsVerified + "'"+' where EmailAddress=' + "'" + EmailAddress + "'"
print(sql)
check.execute(sql)
db.commit()
db.close()
return 1
def CheckBackupEmailAddressByEmailAddress(EmailAddress):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = 'select BackupEmailAddress from ExchangeRoom.AccountInfo where EmailAddress=' + "'" + EmailAddress + "'"
print(sql)
check.execute(sql)
a = check.fetchone()
print(a)
db.commit()
db.close()
if (a[0]=='') or (str(a[0])=='None'):
return 0
else:
return 1
def DeleteUser(EmailAddress):
db = pymysql.connect(sqlservername, sqluser, sqlpasswd, sqldatabase)
check = db.cursor()
sql = 'delete from ExchangeRoom.AccountInfo where EmailAddress='+"'" + EmailAddress + "'"
print(sql)
check.execute(sql)
a = check.fetchone()
print(a)
db.commit()
db.close()
return 1
| 44.744856
| 583
| 0.611515
| 1,032
| 10,873
| 6.442829
| 0.096899
| 0.036096
| 0.045721
| 0.08287
| 0.791698
| 0.75079
| 0.685817
| 0.672733
| 0.670928
| 0.657994
| 0
| 0.006816
| 0.217419
| 10,873
| 242
| 584
| 44.929752
| 0.774592
| 0
| 0
| 0.684729
| 0
| 0.049261
| 0.266536
| 0.04789
| 0.108374
| 0
| 0
| 0
| 0
| 0
| null | null | 0.147783
| 0.009852
| null | null | 0.034483
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
e33c465c53389e53fd469e737e4105c56dbb3912
| 231
|
py
|
Python
|
backend/django/admins/models.py
|
IndiaCFG2/team-19
|
219adab32d3a4999a553ac3fcae0e1b2f3c3b13d
|
[
"MIT"
] | null | null | null |
backend/django/admins/models.py
|
IndiaCFG2/team-19
|
219adab32d3a4999a553ac3fcae0e1b2f3c3b13d
|
[
"MIT"
] | null | null | null |
backend/django/admins/models.py
|
IndiaCFG2/team-19
|
219adab32d3a4999a553ac3fcae0e1b2f3c3b13d
|
[
"MIT"
] | null | null | null |
from django.db import models
# Create your models here.
class PolicyCreation(models.Model):
policyname= models.CharField(max_length=100)
description= models.TextField()
def __str__(self):
return self.policyname
| 28.875
| 48
| 0.744589
| 28
| 231
| 5.964286
| 0.785714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015625
| 0.168831
| 231
| 8
| 49
| 28.875
| 0.854167
| 0.103896
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.166667
| 0.166667
| 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
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
e34e6dbb0cdad1f396a51ab5f503e71890d35d56
| 35
|
py
|
Python
|
PycharmProjects/CursoStrings/main.py
|
FeFSRibeiro/learning-python
|
4f642aa7e1c6523f5209f83ece7e974bfb3ef24e
|
[
"Apache-2.0"
] | null | null | null |
PycharmProjects/CursoStrings/main.py
|
FeFSRibeiro/learning-python
|
4f642aa7e1c6523f5209f83ece7e974bfb3ef24e
|
[
"Apache-2.0"
] | null | null | null |
PycharmProjects/CursoStrings/main.py
|
FeFSRibeiro/learning-python
|
4f642aa7e1c6523f5209f83ece7e974bfb3ef24e
|
[
"Apache-2.0"
] | null | null | null |
meuNome = "Fernanda"
print(meuNome)
| 17.5
| 20
| 0.771429
| 4
| 35
| 6.75
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.085714
| 35
| 2
| 21
| 17.5
| 0.84375
| 0
| 0
| 0
| 0
| 0
| 0.222222
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 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
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
e35fe7ad03cb66bc09be1a8ae5111606cb2a8d95
| 88
|
py
|
Python
|
src/fintrist_ds/listening.py
|
tristanbrown/fintrist
|
38875e4f2c3ab4db31195c798c4262a2f51e4a22
|
[
"MIT"
] | null | null | null |
src/fintrist_ds/listening.py
|
tristanbrown/fintrist
|
38875e4f2c3ab4db31195c798c4262a2f51e4a22
|
[
"MIT"
] | null | null | null |
src/fintrist_ds/listening.py
|
tristanbrown/fintrist
|
38875e4f2c3ab4db31195c798c4262a2f51e4a22
|
[
"MIT"
] | 1
|
2022-01-21T21:10:38.000Z
|
2022-01-21T21:10:38.000Z
|
"""Module that creates the listener app receiving run commands from the scheduler."""
| 22
| 85
| 0.761364
| 12
| 88
| 5.583333
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.159091
| 88
| 3
| 86
| 29.333333
| 0.905405
| 0.897727
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 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
| 4
|
e36a2a31524f79a33ba549723e1ac367a821a936
| 144
|
py
|
Python
|
ca_on_peel/people.py
|
djac/scrapers-ca
|
2e16a85ff8a05ea49031a11ede66fa452631f8da
|
[
"MIT"
] | null | null | null |
ca_on_peel/people.py
|
djac/scrapers-ca
|
2e16a85ff8a05ea49031a11ede66fa452631f8da
|
[
"MIT"
] | null | null | null |
ca_on_peel/people.py
|
djac/scrapers-ca
|
2e16a85ff8a05ea49031a11ede66fa452631f8da
|
[
"MIT"
] | null | null | null |
from utils import CSVScraper
class PeelPersonScraper(CSVScraper):
csv_url = 'http://opendata.peelregion.ca/media/33531/wards1418_csv.csv'
| 24
| 75
| 0.791667
| 18
| 144
| 6.222222
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.069767
| 0.104167
| 144
| 5
| 76
| 28.8
| 0.79845
| 0
| 0
| 0
| 0
| 0
| 0.409722
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
8b4bed9e646dcdc11367200583a021a03786197c
| 477
|
py
|
Python
|
app/main/errors.py
|
Forec/cloud-monitor
|
79037d7372bf3ff499562fab351fc35433c6e2f5
|
[
"0BSD"
] | 6
|
2017-03-18T09:45:55.000Z
|
2018-05-31T07:05:51.000Z
|
app/main/errors.py
|
Forec/cloud-monitor
|
79037d7372bf3ff499562fab351fc35433c6e2f5
|
[
"0BSD"
] | null | null | null |
app/main/errors.py
|
Forec/cloud-monitor
|
79037d7372bf3ff499562fab351fc35433c6e2f5
|
[
"0BSD"
] | 2
|
2017-01-22T10:01:54.000Z
|
2018-04-13T00:02:14.000Z
|
# 作者:Forec
# 最后修改时间:2017-01-01
# 邮箱:forec@bupt.edu.cn
# 关于此文件:包含了应用处理错误的视图函数
from . import main
from flask import render_template
# 处理 403 错误入口
@main.app_errorhandler(403)
def forbidden(e):
return render_template('error/403.html'), 403
# 处理 404 错误入口
@main.app_errorhandler(404)
def page_not_found(e):
return render_template('error/404.html'), 404
# 处理 500 错误入口
@main.app_errorhandler(500)
def internal_server_error(e):
return render_template('error/500.html'), 500
| 21.681818
| 49
| 0.754717
| 76
| 477
| 4.592105
| 0.460526
| 0.160458
| 0.094556
| 0.197708
| 0.223496
| 0
| 0
| 0
| 0
| 0
| 0
| 0.105012
| 0.121593
| 477
| 22
| 50
| 21.681818
| 0.727924
| 0.218029
| 0
| 0
| 0
| 0
| 0.114754
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.272727
| false
| 0
| 0.181818
| 0.272727
| 0.727273
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
8b5cd05a44122284ad0cd99e62ec5f12b165a744
| 581
|
py
|
Python
|
creme/conftest.py
|
Leo-VK/creme
|
0b02df4f4c826368747ee91946efca1a7e8653a6
|
[
"BSD-3-Clause"
] | 23
|
2020-11-21T22:09:24.000Z
|
2022-03-21T22:33:07.000Z
|
creme/conftest.py
|
53X/creme
|
3b397d6aafdfad48dbb36813c90ed3fd1844fc30
|
[
"BSD-3-Clause"
] | null | null | null |
creme/conftest.py
|
53X/creme
|
3b397d6aafdfad48dbb36813c90ed3fd1844fc30
|
[
"BSD-3-Clause"
] | 1
|
2021-04-25T16:24:43.000Z
|
2021-04-25T16:24:43.000Z
|
collect_ignore = []
try:
import sklearn
except ImportError:
collect_ignore.append('compat/sklearn.py')
collect_ignore.append('compat/test_sklearn.py')
try:
import sqlalchemy
except ImportError:
collect_ignore.append('stream/iter_sql.py')
collect_ignore.append('stream/test_sql.py')
try:
import surprise
except ImportError:
collect_ignore.append('reco/surprise.py')
try:
import torch
except ImportError:
collect_ignore.append('compat/pytorch.py')
try:
import vaex
except ImportError:
collect_ignore.append('stream/iter_vaex.py')
| 20.034483
| 51
| 0.741824
| 73
| 581
| 5.739726
| 0.273973
| 0.24821
| 0.317422
| 0.357995
| 0.505967
| 0.420048
| 0.21957
| 0
| 0
| 0
| 0
| 0
| 0.151463
| 581
| 28
| 52
| 20.75
| 0.849899
| 0
| 0
| 0.434783
| 0
| 0
| 0.218589
| 0.037866
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.434783
| 0
| 0.434783
| 0
| 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
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
8b97642d848a0656cd9cebd2a8634db13f714e58
| 257
|
py
|
Python
|
crossbaker/test/test_baker.py
|
josephkirk/MeshBaker
|
e4f75193074cc92d12f953d6cad3a2a599f63ead
|
[
"MIT"
] | null | null | null |
crossbaker/test/test_baker.py
|
josephkirk/MeshBaker
|
e4f75193074cc92d12f953d6cad3a2a599f63ead
|
[
"MIT"
] | 5
|
2018-10-09T02:43:14.000Z
|
2018-10-12T13:00:09.000Z
|
crossbaker/test/test_baker.py
|
josephkirk/CrossBaker
|
e4f75193074cc92d12f953d6cad3a2a599f63ead
|
[
"MIT"
] | null | null | null |
import pytest
def test_run_current_baker():
import crossbaker
print("exec {} baker using arguments: {}".format(
crossbaker.bakers.current().path, crossbaker.bakers.current().mod.get()))
crossbaker.bakers.current().run()
assert False
| 32.125
| 81
| 0.700389
| 30
| 257
| 5.9
| 0.633333
| 0.271186
| 0.389831
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.159533
| 257
| 8
| 82
| 32.125
| 0.819444
| 0
| 0
| 0
| 0
| 0
| 0.127907
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 1
| 0.142857
| true
| 0
| 0.285714
| 0
| 0.428571
| 0.142857
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
8ba496ad06e25f0777fc9b65483bb79a5e4dc21f
| 2,624
|
py
|
Python
|
python/test/test_exchange_datetime_functions.py
|
alexandru-porcescu/ccxt
|
438276f2c476ae24e7cede3cf9c192caababedfa
|
[
"MIT"
] | null | null | null |
python/test/test_exchange_datetime_functions.py
|
alexandru-porcescu/ccxt
|
438276f2c476ae24e7cede3cf9c192caababedfa
|
[
"MIT"
] | null | null | null |
python/test/test_exchange_datetime_functions.py
|
alexandru-porcescu/ccxt
|
438276f2c476ae24e7cede3cf9c192caababedfa
|
[
"MIT"
] | null | null | null |
from unittest import TestCase
import os
import sys
# ------------------------------------------------------------------------------
root = os.path.dirname(os.path.abspath(__file__))
sys.path.append(root)
# ------------------------------------------------------------------------------
import ccxt # noqa: E402
# ------------------------------------------------------------------------------
exchange = ccxt.Exchange()
class TestExchange(TestCase):
def test_iso8601(self):
self.assertEqual(exchange.iso8601(714862627000), '1992-08-26T20:57:07.000Z')
self.assertEqual(exchange.iso8601(0), '1970-01-01T00:00:00.000Z')
self.assertEqual(exchange.iso8601(None), None)
self.assertEqual(exchange.iso8601(), None)
self.assertEqual(exchange.iso8601(-1), None)
self.assertEqual(exchange.iso8601({}), None)
self.assertEqual(exchange.iso8601(''), None)
self.assertEqual(exchange.iso8601('a'), None)
self.assertEqual(exchange.iso8601([]), None)
self.assertEqual(exchange.iso8601([1]), None)
def test_parse_date(self):
self.assertEqual(exchange.parse_date('1996-04-26 00:00:00'), 830476800000)
self.assertEqual(exchange.parse_date('1996-04-26T01:23:47.000Z'), 830481827000)
self.assertEqual(exchange.parse_date('1996-13-13 00:00:00'), None)
self.assertEqual(exchange.parse_date('Sun, 18 Mar 2012 05:50:34 GMT'), 1332049834000)
self.assertEqual(exchange.parse_date('GMT'), None)
self.assertEqual(exchange.parse_date('42 GMT'), None)
self.assertEqual(exchange.parse_date(None), None)
self.assertEqual(exchange.parse_date(), None)
self.assertEqual(exchange.parse_date(1), None)
self.assertEqual(exchange.parse_date({}), None)
self.assertEqual(exchange.parse_date([]), None)
self.assertEqual(exchange.parse_date([1]), None)
def test_parse8601(self):
self.assertEqual(exchange.parse8601('1986-04-26T01:23:47.000Z'), 514862627000)
self.assertEqual(exchange.parse8601('1986-14-26T23:01:47.000Z'), None)
self.assertEqual(exchange.parse8601('1986-04-26T25:71:47.000Z'), None)
self.assertEqual(exchange.parse8601(None), None)
self.assertEqual(exchange.parse8601(), None)
self.assertEqual(exchange.parse8601(''), None)
self.assertEqual(exchange.parse8601('1'), None)
self.assertEqual(exchange.parse8601(1), None)
self.assertEqual(exchange.parse8601({}), None)
self.assertEqual(exchange.parse8601([]), None)
self.assertEqual(exchange.parse8601([1]), None)
| 39.757576
| 93
| 0.621951
| 290
| 2,624
| 5.558621
| 0.227586
| 0.307072
| 0.470844
| 0.401985
| 0.754963
| 0.651985
| 0.577543
| 0.427419
| 0.427419
| 0.427419
| 0
| 0.138676
| 0.153582
| 2,624
| 65
| 94
| 40.369231
| 0.587123
| 0.094131
| 0
| 0
| 0
| 0
| 0.093592
| 0.060708
| 0
| 0
| 0
| 0
| 0.75
| 1
| 0.068182
| false
| 0
| 0.090909
| 0
| 0.181818
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
8baf4e589eaa2e9c9659dfc53151f926bb544501
| 3,489
|
py
|
Python
|
pyramid_request_log/tests/test_config.py
|
MoiTux/pyramid-request-log
|
31852bbf09e4f416f93c7720ecd9eca8cfe32d38
|
[
"MIT"
] | 1
|
2017-08-07T10:22:16.000Z
|
2017-08-07T10:22:16.000Z
|
pyramid_request_log/tests/test_config.py
|
MoiTux/pyramid-request-log
|
31852bbf09e4f416f93c7720ecd9eca8cfe32d38
|
[
"MIT"
] | null | null | null |
pyramid_request_log/tests/test_config.py
|
MoiTux/pyramid-request-log
|
31852bbf09e4f416f93c7720ecd9eca8cfe32d38
|
[
"MIT"
] | null | null | null |
from __future__ import absolute_import
from unittest import TestCase
from pyramid.config import Configurator
from testfixtures import log_capture
from .. import config, request_log
class TestConfig(TestCase):
def tearDown(self):
request_log.unlog_pattern = None
request_log.authenticated_id = ''
@log_capture()
def test_no_conf(self, log):
config.includeme(Configurator())
log.check(
(
'pyramid_request_log.config',
'WARNING',
'No pyramid_request_log.pattern found in settings',
),
)
self.assertIsNone(request_log.unlog_pattern)
self.assertEqual(request_log.authenticated_id, '')
@log_capture()
def test_conf(self, log):
conf = Configurator()
conf.registry.settings.update({
'pyramid_request_log.pattern': '\npassword',
'pyramid_request_log.ignore_route': '\n/monitoring',
'pyramid_request_log.authenticated_id': 'me',
})
config.includeme(conf)
log.check(
(
'pyramid_request_log.config',
'INFO',
"Pyramid-Request-Log will ignore keys: ['password']",
),
(
'pyramid_request_log.config',
'INFO',
"Pyramid-Request-Log will ignore routes: ['/monitoring']",
),
)
self.assertEqual(request_log.unlog_pattern.pattern, '(password)')
self.assertEqual(request_log.unlog_route.pattern, '(/monitoring)')
self.assertEqual(request_log.authenticated_id, 'me')
@log_capture()
def test_conf_list(self, log):
conf = Configurator()
conf.registry.settings.update({
'pyramid_request_log.pattern': '\npassword\npwd',
'pyramid_request_log.ignore_route': '\n^/api.*\n/v5$',
'pyramid_request_log.authenticated_id': 'me',
})
config.includeme(conf)
log.check(
(
'pyramid_request_log.config',
'INFO',
"Pyramid-Request-Log will ignore keys: ['password', 'pwd']",
),
(
'pyramid_request_log.config',
'INFO',
"Pyramid-Request-Log will ignore routes: ['^/api.*', '/v5$']",
),
)
self.assertEqual(request_log.unlog_pattern.pattern, '(password)|(pwd)')
self.assertEqual(request_log.unlog_route.pattern, '(^/api.*)|(/v5$)')
self.assertEqual(request_log.authenticated_id, 'me')
@log_capture()
def test_conf_empty(self, log):
conf = Configurator()
conf.registry.settings.update({
'pyramid_request_log.pattern': '',
'pyramid_request_log.ignore_route': '',
'pyramid_request_log.authenticated_id': 'me',
})
config.includeme(conf)
log.check(
(
'pyramid_request_log.config',
'INFO',
('Pyramid-Request-Log will ignore no key: '
'variable define but empty'),
),
(
'pyramid_request_log.config',
'INFO',
('Pyramid-Request-Log will ignore no route: '
'variable define but empty'),
),
)
self.assertIsNone(request_log.unlog_pattern)
self.assertEqual(request_log.authenticated_id, 'me')
| 33.228571
| 79
| 0.554887
| 330
| 3,489
| 5.618182
| 0.172727
| 0.194175
| 0.210895
| 0.107875
| 0.790723
| 0.762675
| 0.709277
| 0.662891
| 0.574973
| 0.574973
| 0
| 0.001278
| 0.327028
| 3,489
| 104
| 80
| 33.548077
| 0.78833
| 0
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0
| 4
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8bb05361144f612ccb4e9cb29d313110c2b194cf
| 15,584
|
py
|
Python
|
src/loanforms/models.py
|
Deepak27004/carecoop
|
01229c1f9d1c89e595d7f4ca62a07e780522118b
|
[
"MIT"
] | null | null | null |
src/loanforms/models.py
|
Deepak27004/carecoop
|
01229c1f9d1c89e595d7f4ca62a07e780522118b
|
[
"MIT"
] | null | null | null |
src/loanforms/models.py
|
Deepak27004/carecoop
|
01229c1f9d1c89e595d7f4ca62a07e780522118b
|
[
"MIT"
] | 5
|
2017-11-06T14:15:19.000Z
|
2020-10-02T14:51:37.000Z
|
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models
from django.utils.translation import ugettext_lazy as _
# Create your models here.
"""
This model represents the Revised Member Organisations Loan Form child
under Loan Forms
"""
# class PersonalInformation(models.Model):
# # B. PERSONAL INFORMATION (to be filled by loan applicant)
# name = models.CharField(_("1. Members Name"),max_length=255, null=True, blank=True)
# organisation = models.CharField(_("2. Member's Organisation"),max_length=255, null=True, blank=True)
# member_number = models.CharField(_("3. Member's Number"),max_length=255, null=True, blank=True)
# employee_number = models.CharField(_("4. Employee Number"),max_length=255, null=True, blank=True)
# email_address = models.CharField(_("5. Email Address"),max_length=255, null=True, blank=True)
# telephone = models.CharField(_("6. Contact telephone No."),max_length=255, null=True, blank=True)
# physical_address = models.CharField(_("7. Physical Address"),max_length=255, null=True, blank=True)
# postal_address = models.CharField(_("8. Postal Address"),max_length=255, null=True, blank=True)
# length_of_membership = models.CharField(_("9. Length of Membership"),max_length=255, null=True, blank=True)
# nrc_number = models.CharField(_("10. NRC No."),max_length=255, null=True, blank=True)
# created = models.DateTimeField(auto_now_add=True)
# class Meta:
# ordering = ['-created']
# verbose_name = 'PERSONAL INFORMATION'
# verbose_name_plural = 'PERSONAL INFORMATIONS'
# def __unicode__(self):
# return self.name
# class LoanApplication(models.Model):
# # C. LOAN APPLICATION (to be filled by loan applicant)
# amount_applied_for = models.CharField(_("1. Amount Applied for (K)"),max_length=255, null=True, blank=True)
# amount_in_words = models.CharField(_("2. Amount in Words (K)"),max_length=255, null=True, blank=True)
# period_repayment = models.CharField(_("3. Period of Repayment (months)"),max_length=255, null=True, blank=True)
# purposes_for_the_loan = models.CharField(_("4. Purpose for the Loan"),max_length=255, null=True, blank=True)
# created = models.DateTimeField(auto_now_add=True)
# class Meta:
# ordering = ['-created']
# verbose_name = 'LOAN APPLICATION'
# verbose_name_plural = 'LOAN APPLICATIONS'
# def __unicode__(self):
# return self.amount_applied_for
# class LoanPaymentShareContribution(models.Model):
# # D. LOAN REPAYMENT/SHARE CONTRIBUTION (to be filled in by Coop Loans Officer)
# period_of_repayment = models.CharField(_("1. Period of Repayment (months)"),max_length=255, null=True, blank=True)
# monthly_principal_deduction = models.CharField(_("2. Monthly Principal Deduction (K)"),max_length=255, null=True, blank=True)
# monthly_interest_deduction = models.CharField(_("3. Monthly Interest Deduction (K)"),max_length=255, null=True, blank=True)
# monthly_share_contribution = models.CharField(_("4. Monthly Share Contribution(K)"),max_length=255, null=True, blank=True)
# total_care_coop_deduction = models.CharField(_("5. Total Care Coop Deduction (K)"),max_length=255, null=True, blank=True)
# created = models.DateTimeField(auto_now_add=True)
# class Meta:
# ordering = ['-created']
# verbose_name = 'LOANPAYMENTSHARECONTRIBUTION'
# verbose_name_plural = 'LOANPAYMENTSHARECONTRIBUTIONS'
# def __unicode__(self):
# return self.period_repayment
# class OutStandingLoans(models.Model):
# # E. OUTSTANDING LOANS (to be filled by care coop loans officer)
# premium_loan_amount = models.CharField(_("Premium Loan Amount (K)"),max_length=255, null=True, blank=True)
# premium_balance = models.CharField(_("Premium Balance (K)"),max_length=255, null=True, blank=True)
# premium_monthly_repayment = models.CharField(_("Premium Monthly repayment (K)"),max_length=255, null=True, blank=True)
# ordinary_loan_amount = models.CharField(_("Ordinary Loan Amount (K)"),max_length=255, null=True, blank=True)
# ordinary_balance = models.CharField(_("Ordinary Balance (K)"),max_length=255, null=True, blank=True)
# ordinary_monthly_repayment = models.CharField(_("Ordinary Monthly repayment (K)"),max_length=255, null=True, blank=True)
# rental_plus_loan_amount = models.CharField(_("Rental Plus Loan Amount (K)"),max_length=255, null=True, blank=True)
# rental_plus_balance = models.CharField(_("Rental Plus Balance (K)"),max_length=255, null=True, blank=True)
# rental_plus_monthly_repayment = models.CharField(_("Rental Plus Monthly repayment (K)"),max_length=255, null=True, blank=True)
# education_loan_amount = models.CharField(_("Education Loan Amount (K)"),max_length=255, null=True, blank=True)
# education_balance = models.CharField(_("Education Balance (K)"),max_length=255, null=True, blank=True)
# education_monthly_repayment = models.CharField(_("Education Monthly repayment (K)"),max_length=255, null=True, blank=True)
# emergency_loan_amount = models.CharField(_("Emergeny Loan Amount (K)"),max_length=255, null=True, blank=True)
# emergency_balance = models.CharField(_("Emergeny Balance (K)"),max_length=255, null=True, blank=True)
# emergency_monthly_repayment = models.CharField(_("Emergeny Monthly repayment (K)"),max_length=255, null=True, blank=True)
# family_holiday_loan_amount = models.CharField(_("Family Holiday Loan Amount (K)"),max_length=255, null=True, blank=True)
# family_holiday_balance = models.CharField(_("Family Holiday Balance (K)"),max_length=255, null=True, blank=True)
# family_holiday_monthly_repayment = models.CharField(_("Family Holiday Monthly repayment (K)"),max_length=255, null=True, blank=True)
# commodity_loan_amount = models.CharField(_("Commodity Loan Amount (K)"),max_length=255, null=True, blank=True)
# commodity_balance = models.CharField(_("Commodity Balance (K)"),max_length=255, null=True, blank=True)
# commodity_monthly_repayment = models.CharField(_("Commodity Monthly repayment (K)"),max_length=255, null=True, blank=True)
# building_loan_amount = models.CharField(_("Building Loan Amount (K)"),max_length=255, null=True, blank=True)
# building_balance = models.CharField(_("Building Balance (K)"),max_length=255, null=True, blank=True)
# building_monthly_repayment = models.CharField(_("Building Monthly repayment (K)"),max_length=255, null=True, blank=True)
# land_purchase_loan_amount = models.CharField(_("Land Purchase Loan Amount (K)"),max_length=255, null=True, blank=True)
# land_purchase_balance = models.CharField(_("Land Purchase Balance (K)"),max_length=255, null=True, blank=True)
# land_purchase_monthly_repayment = models.CharField(_("Land Purchase Monthly repayment (K)"),max_length=255, null=True, blank=True)
# care_coop_land_loan_amount = models.CharField(_("Care Coop Land Loan Amount (K)"),max_length=255, null=True, blank=True)
# care_coop_land_balance = models.CharField(_("Care Coop Land Balance (K)"),max_length=255, null=True, blank=True)
# care_coop_land_monthly_repayment = models.CharField(_("Care Coop Land Monthly repayment (K)"),max_length=255, null=True, blank=True)
# vehicle_loan_amount = models.CharField(_("Vehicle Loan Amount (K)"),max_length=255, null=True, blank=True)
# vehicle_balance = models.CharField(_("Vehicle Balance (K)"),max_length=255, null=True, blank=True)
# vehicle_monthly_repayment = models.CharField(_("Vehicle Monthly repayment (K)"),max_length=255, null=True, blank=True)
# vehicle_insurance_loan_amount = models.CharField(_("Vehicle Insurance Loan Amount (K)"),max_length=255, null=True, blank=True)
# vehicle_insurance_balance = models.CharField(_("Vehicle Insurance Balance (K)"),max_length=255, null=True, blank=True)
# vehicle_insurance_monthly_repayment = models.CharField(_("Vehicle Insurance Monthly repayment (K)"),max_length=255, null=True, blank=True)
# share_financing_loan_amount = models.CharField(_("Share Financing Loan Amount (K)"),max_length=255, null=True, blank=True)
# share_financing_balance = models.CharField(_("Share Financing Balance (K)"),max_length=255, null=True, blank=True)
# share_financing_monthly_repayment = models.CharField(_("Share Financing Monthly repayment (K)"),max_length=255, null=True, blank=True)
# home_improvement_loan_amount = models.CharField(_("Home Improvement Loan Amount (K)"),max_length=255, null=True, blank=True)
# home_improvement_balance = models.CharField(_("Home Improvement Balance (K)"),max_length=255, null=True, blank=True)
# home_improvement_monthly_repayment = models.CharField(_("Home Improvement Monthly repayment (K)"),max_length=255, null=True, blank=True)
# name_loans_officer = models.CharField(_("Name(loans officer)"),max_length=255, null=True, blank=True)
# signature = models.BooleanField(_("Signature"),default=False)
# text = models.TextField(_("Text"), null=True,blank=True)
# date = models.DateTimeField(auto_now_add=False)
# created = models.DateTimeField(auto_now_add=True)
# class Meta:
# ordering = ['-created']
# verbose_name = 'OUT STANDING LOAN'
# verbose_name_plural = 'OUT STANDING LOANS'
# def __unicode__(self):
# return self.premium_loan_amount
# class Security(models.Model):
# # F.SECURITY
# total_shares = models.CharField(_("1. Total Shares (K)"),max_length=255, null=True, blank=True)
# terminal_benefits_accured = models.CharField(_("2. Terminal Benefits Accrued (K)"),max_length=255, null=True, blank=True)
# total = models.CharField(_("3. Total (K)"),max_length=255, null=True, blank=True)
# signaturea = models.BooleanField(_("Signature"),default=False)
# signatureb = models.BooleanField(_("Signature"),default=False)
# datea = models.DateTimeField(auto_now_add=False)
# dateb = models.DateTimeField(auto_now_add=False)
# created = models.DateTimeField(auto_now_add=True)
# class Meta:
# ordering = ['-created']
# verbose_name = 'SECURITY'
# verbose_name_plural = 'SECURITIES'
# def __unicode__(self):
# return self.total_shares
# class Declaration(models.Model):
# # G. DECLARATION(to be filled by applicant)
# applicant_name = models.CharField(_("Applicant name"),max_length=255, null=True, blank=True)
# datea = models.DateTimeField(auto_now_add=False)
# signature = models.BooleanField(_("Signature"),default=False)
# dateb = models.DateTimeField(auto_now_add=False)
# bank_name = models.CharField(_("Bank Name"),max_length=255, null=True, blank=True)
# account_no = models.CharField(_("Account No"),max_length=255, null=True, blank=True)
# branch = models.CharField(_("Branch"),max_length=255, null=True, blank=True)
# cheque = models.BooleanField(_("Signature"),default=False)
# bank_transfer = models.BooleanField(_("Signature"),default=False)
# created = models.DateTimeField(auto_now_add=True)
# class Meta:
# ordering = ['-created']
# verbose_name = 'DECLARATION'
# verbose_name_plural = 'DECLARATIONS'
# def __unicode__(self):
# return self.applicant_name
# class ReviewedByCoOperativeManager(models.Model):
# # H.REVIEWED BY COOPERATE GENERAL MANAGER/FINANCE CORDINATOR
# name = models.CharField(_("NAME"),max_length=255, null=True, blank=True)
# date = models.DateTimeField(auto_now_add=False)
# signature = models.BooleanField(_("Signature"),default=False)
# created = models.DateTimeField(auto_now_add=True)
# class Meta:
# ordering = ['-created']
# verbose_name = 'REVIEWED BY CO OPERATIVE MANAGER'
# verbose_name_plural = 'REVIEWED BY CO OPERATIVE MANAGERS'
# def __unicode__(self):
# return self.name
# class LoanAnalysisAndApprovalByLoans(models.Model):
# # I. LOAN ANALYSIS AND APPROVAL BY LOANS COMMITTEEE
# comments = models.TextField(_("Comments"), null=True,blank=True)
# chair_person_name = models.CharField(_("Chair Person Name"),max_length=255, null=True, blank=True)
# chair_person_signature = models.CharField(_("Chair Person Sign"),max_length=255, null=True, blank=True)
# chair_person_date = models.DateTimeField(auto_now_add=False)
# Treasurer_name = models.CharField(_("Treasurer Name"),max_length=255, null=True, blank=True)
# Treasurer_signature = models.CharField(_("Treasurer Sign"),max_length=255, null=True, blank=True)
# Treasurer_date = models.CharField(_("Treasurer Date"),max_length=255, null=True, blank=True)
# committee_member_name = models.CharField(_("Committee Member Name"),max_length=255, null=True, blank=True)
# committee_member_signature = models.CharField(_("Committee Member Sign"),max_length=255, null=True, blank=True)
# committee_member_date = models.CharField(_("Committee Member Date"),max_length=255, null=True, blank=True)
# created = models.DateTimeField(auto_now_add=True)
# class Meta:
# ordering = ['-created']
# verbose_name = 'LOAN ANALYSIS AND APPROVAL BY LOAN'
# verbose_name_plural = 'LOAN ANALYSIS AND APPROVAL BY LOANS'
# def __unicode__(self):
# return self.comments
# class NameSignatureDate(models.Model):
# # J. BOARD RESOLUTION (Applicable to loans of above K10000)
# name = models.CharField(_("Name"),max_length=255, null=True, blank=True)
# signature = models.CharField(_("Signature"),max_length=255, null=True, blank=True)
# date = models.CharField(_("Date"),max_length=255, null=True, blank=True)
# created = models.DateTimeField(auto_now_add=True)
# class Meta:
# ordering = ['-created']
# verbose_name = 'NAME SIGNATURE DATE'
# verbose_name_plural = 'NAME SIGNATURE DATES'
# def __unicode__(self):
# return self.name
# class SuccessStories(models.Model):
#
# message = models.TextField(null=True, blank=True)
# name = models.CharField(_('Name of Member'),max_length=255, null=True, blank=True)
# carecoopnumber = models.CharField(_('CareCoop Number'),max_legnth=255, null=True, blank=True)
#
# #Start contact numbers
# home = models.CharField(_('Home'),max_length=255, null=True, blank=True)
# cell = models.CharField(_('Cell'),max_length=255, null=True, blank=True)
# work = models.CharField(_('Work'),max_length=255, null=True, blank=True)
#
# #End contact numbers
# #Direct debit mandate Start
# barclays = models.BooleanField(_('Barclays Bank Zambia Plc'))
# firstalliance = models.BooleanField(_('First Alliance Bank Ltd'))
# stanbic = models.BooleanField(_('Stanbic Bank (Z) Ltd'))
# cavmont = models.BooleanField(_('Cavmont Capital Bank Ltd'))
# indo = models.BooleanField(_('Indo Bank Zambia Ltd'))
# standard = models.BooleanField(_('Standard Chartered Bank Plc'))
# investtrust = models.BooleanField(_('Investrust Mechant Bank Plc'))
# zanaco = models.BooleanField(_('Zambia National Commercial Bank Plc'))
# finance = models.BooleanField(_('Finance Bank (Z) Ltd'))
# citybank = models.BooleanField(_('Citybank (Z) Ltd'))
# others = models.BooleanField(_('Others'),max_length=255, null=True, blank=True)
#
# #Direct debit mandate end
# tomanager = models.BooleanField(_('To The Manager:'),max_length=255, null=True, blank=True)
# bankaddress = models.BooleanField(_('Address'),max_length=255, null=True, blank=True)
# postcode = models.BooleanField(_('Post Code'),max_length=255, null=True, blank=True)
# bankshortcode = models.BooleanField(_('Bank Short Code'),max_length=255, null=True, blank=True)
# accnumber = models.BooleanField(_('Account Number'),max_length=255, null=True, blank=True)
# amount = models.BooleanField(_('Amount K:'),max_length=50, null=True, blank=True)
# effect = models.DateTimeField(auto_now_add=False)
# payday = models.DateTimeField(auto_now_add=False)
#
# class meta:
# ordering = ['-created']
# verbose_name = ('Approval Form')
# verbose_name_plural = ('Approval Forms')
#
# def __unicode__(self):
# return self.carecoopnumber
| 53.553265
| 141
| 0.748781
| 2,040
| 15,584
| 5.489706
| 0.119118
| 0.068578
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| 0.541834
| 0.492723
| 0.463524
| 0.424502
| 0.355746
| 0.284579
| 0
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| 0.109728
| 15,584
| 291
| 142
| 53.553265
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0
| 4
|
8bdfc4a377c12d257b322de2f571e622d7fccf45
| 214
|
py
|
Python
|
handlers/users/__init__.py
|
KotDath/game_jams_bot
|
6abb8af3160a1f34d2511ae76ccdb9c77eff23dc
|
[
"MIT"
] | null | null | null |
handlers/users/__init__.py
|
KotDath/game_jams_bot
|
6abb8af3160a1f34d2511ae76ccdb9c77eff23dc
|
[
"MIT"
] | null | null | null |
handlers/users/__init__.py
|
KotDath/game_jams_bot
|
6abb8af3160a1f34d2511ae76ccdb9c77eff23dc
|
[
"MIT"
] | null | null | null |
from aiogram import Dispatcher
from aiogram.dispatcher.filters import CommandStart, CommandHelp
from .start import bot_start
def setup(dp: Dispatcher):
dp.register_message_handler(bot_start, CommandStart())
| 23.777778
| 64
| 0.817757
| 27
| 214
| 6.333333
| 0.555556
| 0.128655
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| 0.116822
| 214
| 8
| 65
| 26.75
| 0.904762
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| 1
| 0
|
0
| 4
|
47826436d8ffd606c38fb5fa14f7f2f960821c34
| 139
|
py
|
Python
|
Resume/education/urls.py
|
flame4ost/Django-Resume-Creative
|
6f713f22eb77bf742330c5a0b3b93dcb10bb29d2
|
[
"MIT"
] | null | null | null |
Resume/education/urls.py
|
flame4ost/Django-Resume-Creative
|
6f713f22eb77bf742330c5a0b3b93dcb10bb29d2
|
[
"MIT"
] | 4
|
2020-02-11T21:47:30.000Z
|
2021-06-10T17:24:50.000Z
|
Resume/education/urls.py
|
flame4ost/Django-Resume-Creative
|
6f713f22eb77bf742330c5a0b3b93dcb10bb29d2
|
[
"MIT"
] | null | null | null |
from django.urls import path
from . import views
app_name = 'education'
urlpatterns = [
path('', views.education, name='education')
]
| 17.375
| 47
| 0.705036
| 17
| 139
| 5.705882
| 0.588235
| 0.268041
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| 139
| 8
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| 17.375
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| 1
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| 0
| 0
|
0
| 4
|
478b8753a829f7978d764902bb3b27f46dd786a8
| 132
|
py
|
Python
|
async_service/typing.py
|
cburgdorf/async-service
|
04bbca368b0dfdeb87e8f9ff871ffb23a27b01ee
|
[
"MIT"
] | null | null | null |
async_service/typing.py
|
cburgdorf/async-service
|
04bbca368b0dfdeb87e8f9ff871ffb23a27b01ee
|
[
"MIT"
] | null | null | null |
async_service/typing.py
|
cburgdorf/async-service
|
04bbca368b0dfdeb87e8f9ff871ffb23a27b01ee
|
[
"MIT"
] | null | null | null |
from types import TracebackType
from typing import Tuple, Type
EXC_INFO = Tuple[Type[BaseException], BaseException, TracebackType]
| 26.4
| 67
| 0.825758
| 16
| 132
| 6.75
| 0.625
| 0.166667
| 0
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| 0
| 0
| 0
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| 0
| 0
| 0.113636
| 132
| 4
| 68
| 33
| 0.923077
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| false
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
47c38a33c076bd09d7bbd14cd5779de11805e6c7
| 3,319
|
py
|
Python
|
Results/reformat_prediction_patch.py
|
varnerlab/Reduced_EMT_Model
|
48cda4ef98cfcf539f8b38def68d64722a2db8be
|
[
"MIT"
] | 1
|
2019-03-08T09:09:22.000Z
|
2019-03-08T09:09:22.000Z
|
Results/reformat_prediction_patch.py
|
varnerlab/Reduced_EMT_Model
|
48cda4ef98cfcf539f8b38def68d64722a2db8be
|
[
"MIT"
] | null | null | null |
Results/reformat_prediction_patch.py
|
varnerlab/Reduced_EMT_Model
|
48cda4ef98cfcf539f8b38def68d64722a2db8be
|
[
"MIT"
] | null | null | null |
# take linear julia list of lists and convert to julia array format
execfile('../pyprgs/in_out_line.py')
execfile('../pyprgs/in_out_csv.py')
dat1 = lin.reader("../poets/results_poets/cross_validation/EC1.dat")
dat2 = lin.reader("../poets/results_poets/cross_validation/EC2.dat")
dat3 = lin.reader("../poets/results_poets/cross_validation/EC3.dat")
dat4 = lin.reader("../poets/results_poets/cross_validation/EC4.dat")
dat5 = lin.reader("../poets/results_poets/cross_validation/EC5.dat")
dat6 = lin.reader("../poets/results_poets/cross_validation/EC6.dat")
dat7 = lin.reader("../poets/results_poets/cross_validation/EC7.dat")
dat8 = lin.reader("../poets/results_poets/cross_validation/EC8.dat")
dat9 = lin.reader("../poets/results_poets/cross_validation/EC9.dat")
dat10 = lin.reader("../poets/results_poets/cross_validation/EC10.dat")
dat11 = lin.reader("../poets/results_poets/cross_validation/EC11.dat")
# map X1 (size e.g. 772) to x1 within x2 from X2 (size 11)
def julia_listlist_to_array(dat):
dat_new = [[],[],[],[],[],[],[],[],[],[],[]] # number of objectives (x2space)
counter = 0
for LINE in dat:
if LINE.count('[') == 1:
counter = 0
dat_new[counter].append(LINE.replace('[','').replace(']',''))
counter = counter + 1
outlines = []
for LIST in dat_new:
outlines.append('\t'.join(LIST))
return outlines
outlines = julia_listlist_to_array(dat1)
lin.writer("../poets/results_poets/cross_validation/EC1_jl_array.dat",outlines)
outlines = julia_listlist_to_array(dat2)
lin.writer("../poets/results_poets/cross_validation/EC2_jl_array.dat",outlines)
outlines = julia_listlist_to_array(dat3)
lin.writer("../poets/results_poets/cross_validation/EC3_jl_array.dat",outlines)
outlines = julia_listlist_to_array(dat4)
lin.writer("../poets/results_poets/cross_validation/EC4_jl_array.dat",outlines)
outlines = julia_listlist_to_array(dat5)
lin.writer("../poets/results_poets/cross_validation/EC5_jl_array.dat",outlines)
outlines = julia_listlist_to_array(dat6)
lin.writer("../poets/results_poets/cross_validation/EC6_jl_array.dat",outlines)
outlines = julia_listlist_to_array(dat7)
lin.writer("../poets/results_poets/cross_validation/EC7_jl_array.dat",outlines)
outlines = julia_listlist_to_array(dat8)
lin.writer("../poets/results_poets/cross_validation/EC8_jl_array.dat",outlines)
outlines = julia_listlist_to_array(dat9)
lin.writer("../poets/results_poets/cross_validation/EC9_jl_array.dat",outlines)
outlines = julia_listlist_to_array(dat10)
lin.writer("../poets/results_poets/cross_validation/EC10_jl_array.dat",outlines)
outlines = julia_listlist_to_array(dat11)
lin.writer("../poets/results_poets/cross_validation/EC11_jl_array.dat",outlines)
# need to reformat random as well
datr = lin.reader("../poets/results_poets/random_set/EC.dat")
outlines = julia_listlist_to_array(datr)
lin.writer("../poets/results_poets/random_set/EC_jl_array.dat",outlines)
datrf = lin.reader("../poets/results_poets/random_set/EC_full.dat")
outlines = julia_listlist_to_array(datrf)
lin.writer("../poets/results_poets/random_set/EC_full_jl_array.dat",outlines)
#for line in dat:
# dat_new.append([float(string.replace('[' ,'').replace(']','')) for string in line])
#datx = lin.reader("../poets/results_poets/cross_validation/fold_pop_obj_1/EC.dat")
| 43.671053
| 89
| 0.756553
| 486
| 3,319
| 4.888889
| 0.191358
| 0.136364
| 0.193182
| 0.212963
| 0.726852
| 0.726852
| 0.656145
| 0.255892
| 0.193603
| 0
| 0
| 0.021974
| 0.08135
| 3,319
| 75
| 90
| 44.253333
| 0.757297
| 0.111781
| 0
| 0.037736
| 0
| 0
| 0.469005
| 0.467302
| 0
| 0
| 0
| 0
| 0
| 1
| 0.018868
| false
| 0
| 0
| 0
| 0.037736
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
47db51e9523923bd84aa6b38ae26db66c39ba234
| 1,811
|
py
|
Python
|
templatealchemy_driver/file.py
|
cadithealth/templatealchemy
|
a098aff22a6bcdd693e5ebea51155b96356d3178
|
[
"MIT"
] | 1
|
2019-10-06T23:49:58.000Z
|
2019-10-06T23:49:58.000Z
|
templatealchemy_driver/file.py
|
cadithealth/templatealchemy
|
a098aff22a6bcdd693e5ebea51155b96356d3178
|
[
"MIT"
] | null | null | null |
templatealchemy_driver/file.py
|
cadithealth/templatealchemy
|
a098aff22a6bcdd693e5ebea51155b96356d3178
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
#------------------------------------------------------------------------------
# file: $Id$
# lib: templatealchemy_driver.file
# auth: Philip J Grabner <grabner@cadit.com>
# date: 2013/07/03
# copy: (C) Copyright 2013 Cadit Health Inc., All Rights Reserved.
#------------------------------------------------------------------------------
import os
from templatealchemy import api, util
#------------------------------------------------------------------------------
def loadSource(spec=None):
return FileSource(spec)
#------------------------------------------------------------------------------
class FileSource(api.Source):
#----------------------------------------------------------------------------
def getSource(self, name):
if name is None:
return self
return FileSource(self.spec + '/' + name)
#----------------------------------------------------------------------------
def getFormats(self):
path, base = os.path.split(self.spec)
base += '.'
return [
cur[len(base):]
for cur in os.listdir(path)
if cur.startswith(base) and os.path.isfile(os.path.join(path, cur))]
#----------------------------------------------------------------------------
def get(self, format):
# todo: what about file descriptor clean-up?...
if format:
format = '.' + format
return open(self.spec + format, 'rb')
#----------------------------------------------------------------------------
def getRelated(self, name):
if name.startswith('/'):
return open(name, 'rb')
return open(os.path.dirname(self.spec) + '/' + name, 'rb')
#------------------------------------------------------------------------------
# end of $Id$
#------------------------------------------------------------------------------
| 35.509804
| 79
| 0.355052
| 141
| 1,811
| 4.553191
| 0.503546
| 0.049844
| 0.031153
| 0.043614
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008244
| 0.12921
| 1,811
| 50
| 80
| 36.22
| 0.398859
| 0.563777
| 0
| 0
| 0
| 0
| 0.014267
| 0
| 0
| 0
| 0
| 0.02
| 0
| 1
| 0.208333
| false
| 0
| 0.083333
| 0.041667
| 0.625
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
9a171b27694b6a0eb32eb5bf4a181de5af95cc26
| 215
|
py
|
Python
|
xicidailiSpider/run_spider.py
|
xzlmark/webspider
|
133c620c65aa45abea1718b0dada09618c2115bf
|
[
"Apache-2.0"
] | 3
|
2020-04-09T02:35:26.000Z
|
2021-02-27T17:00:21.000Z
|
xicidailiSpider/run_spider.py
|
colorworlds/webspider
|
133c620c65aa45abea1718b0dada09618c2115bf
|
[
"Apache-2.0"
] | null | null | null |
xicidailiSpider/run_spider.py
|
colorworlds/webspider
|
133c620c65aa45abea1718b0dada09618c2115bf
|
[
"Apache-2.0"
] | 1
|
2020-04-09T02:35:08.000Z
|
2020-04-09T02:35:08.000Z
|
# 运行爬虫文件,在pychram里面运行,要注意这个文件的位置,是位于scrapy,cfg一个目录下
# 第一中方式,必须加split()
from scrapy import cmdline
# cmdline.execute('scrapy crawl xicidaili'.split())
# 第二种是用os模块来实行
import os
os.system('scrapy crawl xicidaili ')
| 21.5
| 51
| 0.781395
| 25
| 215
| 6.72
| 0.72
| 0.130952
| 0.238095
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106977
| 215
| 10
| 52
| 21.5
| 0.875
| 0.6
| 0
| 0
| 0
| 0
| 0.292683
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 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
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
9a399f1a01562ea08168931d524893ca67c3d4c3
| 128
|
py
|
Python
|
compilador/tests/router_solver.py
|
Nombre-Pendiente/Super-Compi
|
3f2a8e0219b04863fbf78d03aba782d235ccb11a
|
[
"MIT"
] | 6
|
2021-05-20T16:01:45.000Z
|
2021-05-27T18:48:57.000Z
|
compilador/tests/router_solver.py
|
Nombre-Pendiente/Super-Compi
|
3f2a8e0219b04863fbf78d03aba782d235ccb11a
|
[
"MIT"
] | 1
|
2021-05-18T14:44:04.000Z
|
2021-05-18T14:44:04.000Z
|
compilador/tests/router_solver.py
|
Nombre-Pendiente/Super-Compi
|
3f2a8e0219b04863fbf78d03aba782d235ccb11a
|
[
"MIT"
] | null | null | null |
import sys
import os
route = os.getcwd().replace("/compilador/tests", "").replace("/compilador", "")
sys.path.insert(1, route)
| 21.333333
| 79
| 0.6875
| 17
| 128
| 5.176471
| 0.647059
| 0.386364
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008621
| 0.09375
| 128
| 5
| 80
| 25.6
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0.21875
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 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
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
7be02423e251c988c361568ecac87d496a247b35
| 202
|
py
|
Python
|
test/lib/systestlib.py
|
arista-eosplus/eapictl
|
38917722dd61224f044f30daf21f8120cdf034fa
|
[
"BSD-3-Clause"
] | 2
|
2017-08-24T04:41:07.000Z
|
2020-02-27T00:14:11.000Z
|
test/lib/systestlib.py
|
arista-eosplus/eapictl
|
38917722dd61224f044f30daf21f8120cdf034fa
|
[
"BSD-3-Clause"
] | 1
|
2015-04-14T18:06:19.000Z
|
2017-04-26T13:45:31.000Z
|
test/lib/systestlib.py
|
arista-eosplus/eapictl
|
38917722dd61224f044f30daf21f8120cdf034fa
|
[
"BSD-3-Clause"
] | null | null | null |
import os
HERE = os.path.abspath(os.path.dirname(__file__))
def fixtures_path():
return os.path.join(HERE, '../fixtures')
def get_fixture(name):
return os.path.join(fixtures_path(), name)
| 15.538462
| 49
| 0.69802
| 30
| 202
| 4.466667
| 0.466667
| 0.179104
| 0.179104
| 0.238806
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.143564
| 202
| 12
| 50
| 16.833333
| 0.774566
| 0
| 0
| 0
| 0
| 0
| 0.055276
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.166667
| 0.333333
| 0.833333
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
d0172e75df20ac530a640cf59eb77f0f195f46b9
| 156
|
py
|
Python
|
django_timecode/test/models.py
|
jaumeba/django-timecode
|
8f4afcde8e0f86a2a385cbbc4704a90652077202
|
[
"BSD-3-Clause"
] | 3
|
2015-02-05T09:56:48.000Z
|
2020-01-07T17:05:59.000Z
|
django_timecode/test/models.py
|
jaumeba/django-timecode
|
8f4afcde8e0f86a2a385cbbc4704a90652077202
|
[
"BSD-3-Clause"
] | 1
|
2015-01-20T17:19:58.000Z
|
2015-02-05T10:33:51.000Z
|
django_timecode/test/models.py
|
jaumeba/django-timecode
|
8f4afcde8e0f86a2a385cbbc4704a90652077202
|
[
"BSD-3-Clause"
] | 5
|
2015-01-01T00:07:06.000Z
|
2022-01-22T01:37:25.000Z
|
from timecode.fields import TimecodeField
from django.db import models
class TestModel(models.Model):
timecode = TimecodeField(blank=True, null=True)
| 22.285714
| 51
| 0.794872
| 20
| 156
| 6.2
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128205
| 156
| 6
| 52
| 26
| 0.911765
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
d0264b9704ddf1719f307d41ccfa8d9de99666f4
| 446
|
py
|
Python
|
opponent_app/views/__init__.py
|
Alpaca00/alpaca_web
|
1db33978f774addbe456f750ffadf32d2f223610
|
[
"MIT"
] | 4
|
2021-09-14T07:36:27.000Z
|
2021-09-18T15:10:24.000Z
|
opponent_app/views/__init__.py
|
Alpaca00/alpaca_web
|
1db33978f774addbe456f750ffadf32d2f223610
|
[
"MIT"
] | 1
|
2021-12-14T20:32:29.000Z
|
2021-12-15T13:28:29.000Z
|
opponent_app/views/__init__.py
|
Alpaca00/squash-opponent
|
1db33978f774addbe456f750ffadf32d2f223610
|
[
"MIT"
] | null | null | null |
from .product import product_app
from .gallery import gallery_app
from .video_gallery import video_app
from .cart import cart_app
from .order import order_app
from .login import login_app
from .register import register_app
from .support import support_app
from .user_account import user_account_app
from .home import home_app, admin
from .about import about_app
from .finder import finder_app
from .password_recovery import recovery_password_app
| 31.857143
| 52
| 0.849776
| 71
| 446
| 5.084507
| 0.267606
| 0.213296
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.118834
| 446
| 13
| 53
| 34.307692
| 0.918575
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.076923
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 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
| 0
| 1
| 1
| 1
| 0
| 0
| 0
|
0
| 4
|
d0288f25da385c8b59b083433144a72b1161c85f
| 114
|
py
|
Python
|
mailbot/exceptions.py
|
alseageo/mailbot
|
642200dce8b34cfcce6276d76952b9454155f8b3
|
[
"BSD-3-Clause"
] | 13
|
2015-07-15T19:28:09.000Z
|
2021-11-04T23:50:13.000Z
|
mailbot/exceptions.py
|
alseageo/mailbot
|
642200dce8b34cfcce6276d76952b9454155f8b3
|
[
"BSD-3-Clause"
] | 7
|
2015-04-26T07:11:29.000Z
|
2019-11-19T12:54:12.000Z
|
mailbot/exceptions.py
|
alseageo/mailbot
|
642200dce8b34cfcce6276d76952b9454155f8b3
|
[
"BSD-3-Clause"
] | 12
|
2015-04-25T17:48:57.000Z
|
2021-07-11T14:28:34.000Z
|
# -*- coding: utf-8 -*-
class RegisterException(Exception):
"""Exception raised on a registration error."""
| 19
| 51
| 0.666667
| 12
| 114
| 6.333333
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.010526
| 0.166667
| 114
| 5
| 52
| 22.8
| 0.789474
| 0.561404
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 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
| 0
| 0
| 1
| 0
|
0
| 4
|
d03eec5a7b0c3cdcae3328e20449cb6c4ef66b7a
| 361
|
py
|
Python
|
wealthbot/ria/views/changeProfile.py
|
jliev/wealthbot_chatterbot
|
f6681da8e5f833990ccd321e166994f31253353f
|
[
"MIT"
] | 1
|
2019-04-22T07:20:31.000Z
|
2019-04-22T07:20:31.000Z
|
wealthbot/ria/views/changeProfile.py
|
jliev/wealthbot_chatterbot
|
f6681da8e5f833990ccd321e166994f31253353f
|
[
"MIT"
] | null | null | null |
wealthbot/ria/views/changeProfile.py
|
jliev/wealthbot_chatterbot
|
f6681da8e5f833990ccd321e166994f31253353f
|
[
"MIT"
] | null | null | null |
from django.http import HttpResponse
from django.contrib.auth.decorators import login_required
@login_required
def changeProfileIndex(request, tab='company_profile'):
return HttpResponse('Not implemented yet, please come back later!')
@login_required
def profile(request, tab='profile'):
return HttpResponse('Not implemented yet, please come back later!')
| 32.818182
| 68
| 0.808864
| 46
| 361
| 6.26087
| 0.521739
| 0.135417
| 0.111111
| 0.194444
| 0.423611
| 0.423611
| 0.423611
| 0.423611
| 0.423611
| 0.423611
| 0
| 0
| 0.102493
| 361
| 11
| 69
| 32.818182
| 0.888889
| 0
| 0
| 0.5
| 0
| 0
| 0.303867
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0.25
| 0.75
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
d04dd3b917cf51581535a74e0f55a25209ad9eed
| 132
|
gyp
|
Python
|
binding.gyp
|
pash2048/hetrodo-node-cursor-napi
|
96566cb1696e7094285424ab21d30270032f2267
|
[
"MIT"
] | 1
|
2022-01-27T11:23:54.000Z
|
2022-01-27T11:23:54.000Z
|
binding.gyp
|
pash2048/hetrodo-node-cursor-napi
|
96566cb1696e7094285424ab21d30270032f2267
|
[
"MIT"
] | null | null | null |
binding.gyp
|
pash2048/hetrodo-node-cursor-napi
|
96566cb1696e7094285424ab21d30270032f2267
|
[
"MIT"
] | 1
|
2022-01-27T12:58:40.000Z
|
2022-01-27T12:58:40.000Z
|
{
"targets": [
{
"target_name": "node-cursor",
"sources": [ "node-cursor.cc" ]
}
]
}
| 16.5
| 43
| 0.356061
| 9
| 132
| 5.111111
| 0.777778
| 0.434783
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.454545
| 132
| 8
| 44
| 16.5
| 0.638889
| 0
| 0
| 0
| 0
| 0
| 0.37594
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
d050178ec9d61ca2ba12f401515b69366b9f5379
| 2,080
|
py
|
Python
|
software/cl_reachy/cl_reachy/model/body_state.py
|
wisehackermonkey/CoLab-Reachy
|
538f3e6d6f43f87cdf2c91e97229b20a7fb490a9
|
[
"CC0-1.0"
] | 3
|
2021-03-28T19:43:57.000Z
|
2021-12-19T04:42:02.000Z
|
software/cl_reachy/cl_reachy/model/body_state.py
|
wisehackermonkey/CoLab-Reachy
|
538f3e6d6f43f87cdf2c91e97229b20a7fb490a9
|
[
"CC0-1.0"
] | 7
|
2020-09-23T00:33:53.000Z
|
2021-08-11T03:15:43.000Z
|
software/cl_reachy/cl_reachy/model/body_state.py
|
wisehackermonkey/CoLab-Reachy
|
538f3e6d6f43f87cdf2c91e97229b20a7fb490a9
|
[
"CC0-1.0"
] | 1
|
2021-01-21T02:32:15.000Z
|
2021-01-21T02:32:15.000Z
|
import json
from collections import namedtuple
from json import JSONEncoder
from .common import DataModelBase
class DynamixelState(DataModelBase):
def __init__(self, name, present_position, compliant):
# TODO - some properties should stay local to the view but other
# properties should be in the model with the controller
self.name = name
self.present_position = present_position
self.compliant = compliant
@staticmethod
def decoder(msgDict):
return namedtuple(LogMessage.__name__, msgDict.keys())(*msgDict.values())
@staticmethod
def from_json(msgJson):
return json.loads(msgJson, object_hook=HeadState.decoder)
class HeadState(DataModelBase):
def __init__(self, left_antenna_state, right_antenna_state):
self.left_antenna_state = left_antenna_state
self.right_antenna_state = right_antenna_state
@staticmethod
def decoder(msgDict):
return namedtuple(HeadState.__name__, msgDict.keys())(*msgDict.values())
@staticmethod
def from_json(msgJson):
return json.loads(msgJson, object_hook=HeadState.decoder)
class OrbitaState(DataModelBase):
def __init__(self):
# TODO
pass
@staticmethod
def decoder(msgDict):
return namedtuple(OrbitaState.__name__, msgDict.keys())(*msgDict.values())
@staticmethod
def from_json(msgJson):
return json.loads(msgJson, object_hook=OrbitaState.decoder)
class RightArmState(DataModelBase):
def __init__(self, shoulder_pitch_state, shoulder_roll_state, arm_yaw_state, elbow_pitch_state):
# TODO
self.shoulder_pitch_state = shoulder_pitch_state
self.shoulder_roll_state = shoulder_roll_state
self.arm_yaw_state = arm_yaw_state
self.elbow_pitch_state = elbow_pitch_state
@staticmethod
def decoder(msgDict):
return namedtuple(RightArmState.__name__, msgDict.keys())(*msgDict.values())
@staticmethod
def from_json(msgJson):
return json.loads(msgJson, object_hook=RightArmState.decoder)
| 33.548387
| 100
| 0.720673
| 236
| 2,080
| 6.016949
| 0.245763
| 0.084507
| 0.056338
| 0.067606
| 0.496479
| 0.416901
| 0.353521
| 0.283099
| 0.283099
| 0.283099
| 0
| 0
| 0.2
| 2,080
| 62
| 101
| 33.548387
| 0.853365
| 0.063942
| 0
| 0.391304
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.016129
| 0
| 1
| 0.26087
| false
| 0.021739
| 0.086957
| 0.173913
| 0.608696
| 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
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
d051b20b4d9c639a564d6399a6bb116b76d2b690
| 78
|
py
|
Python
|
pyrolite/extensions/__init__.py
|
JustinGOSSES/pyrolite
|
21eb5b28d9295625241b73b820fc8892b00fc6b0
|
[
"BSD-3-Clause"
] | 1
|
2020-03-13T07:11:47.000Z
|
2020-03-13T07:11:47.000Z
|
pyrolite/extensions/__init__.py
|
JustinGOSSES/pyrolite
|
21eb5b28d9295625241b73b820fc8892b00fc6b0
|
[
"BSD-3-Clause"
] | null | null | null |
pyrolite/extensions/__init__.py
|
JustinGOSSES/pyrolite
|
21eb5b28d9295625241b73b820fc8892b00fc6b0
|
[
"BSD-3-Clause"
] | null | null | null |
"""
A stub module to house pyrolite extensions,
where they are installed.
"""
| 15.6
| 43
| 0.730769
| 11
| 78
| 5.181818
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 78
| 4
| 44
| 19.5
| 0.876923
| 0.884615
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 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
| 4
|
d0746ce95bc2021f11879c7cd47d76342d9046b2
| 188
|
py
|
Python
|
devstat/__main__.py
|
prashantdivate/devstat
|
22238b0dd322e8b3c17b58f15d1ac2325c0f4d28
|
[
"MIT"
] | null | null | null |
devstat/__main__.py
|
prashantdivate/devstat
|
22238b0dd322e8b3c17b58f15d1ac2325c0f4d28
|
[
"MIT"
] | null | null | null |
devstat/__main__.py
|
prashantdivate/devstat
|
22238b0dd322e8b3c17b58f15d1ac2325c0f4d28
|
[
"MIT"
] | null | null | null |
#
# Python tool to fetch Linux system information
# Author - diwateprashant44@gmail.com
# Tested with Python3 on Ubuntu 16.04
#
import subprocess
subprocess.call(['sh','./devstat.sh'])
| 20.888889
| 47
| 0.739362
| 25
| 188
| 5.56
| 0.92
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.043478
| 0.143617
| 188
| 9
| 48
| 20.888889
| 0.819876
| 0.62766
| 0
| 0
| 0
| 0
| 0.21875
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 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
| 0
| 0
|
0
| 4
|
d077e19e923096067361c2e528bae24db52bf56d
| 196
|
py
|
Python
|
holobot/discord/sdk/components/__init__.py
|
rexor12/holobot
|
89b7b416403d13ccfeee117ef942426b08d3651d
|
[
"MIT"
] | 1
|
2021-05-24T00:17:46.000Z
|
2021-05-24T00:17:46.000Z
|
holobot/discord/sdk/components/__init__.py
|
rexor12/holobot
|
89b7b416403d13ccfeee117ef942426b08d3651d
|
[
"MIT"
] | 41
|
2021-03-24T22:50:09.000Z
|
2021-12-17T12:15:13.000Z
|
holobot/discord/sdk/components/__init__.py
|
rexor12/holobot
|
89b7b416403d13ccfeee117ef942426b08d3651d
|
[
"MIT"
] | null | null | null |
from .button import Button
from .combo_box import ComboBox
from .combo_box_item import ComboBoxItem
from .component import Component
from .pager import Pager
from .stack_layout import StackLayout
| 28
| 40
| 0.846939
| 28
| 196
| 5.785714
| 0.464286
| 0.111111
| 0.148148
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.122449
| 196
| 6
| 41
| 32.666667
| 0.94186
| 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
| 0
| 0
|
0
| 4
|
d0784a1d9bc89cedae056927e21cdd8d202e5459
| 258
|
py
|
Python
|
data_structures/stacks_and_queues/stack/node.py
|
michaelsklepowich/data_structures_and_algorithms
|
0e44be7789db8e361a01f300fc399c8b29cd9970
|
[
"MIT"
] | null | null | null |
data_structures/stacks_and_queues/stack/node.py
|
michaelsklepowich/data_structures_and_algorithms
|
0e44be7789db8e361a01f300fc399c8b29cd9970
|
[
"MIT"
] | null | null | null |
data_structures/stacks_and_queues/stack/node.py
|
michaelsklepowich/data_structures_and_algorithms
|
0e44be7789db8e361a01f300fc399c8b29cd9970
|
[
"MIT"
] | null | null | null |
class Node:
def __init__(self, value, _next=None):
self._value = value
self._next = _next
def __str__(self):
return f'{self._value}'
def __repr__(self):
return f'<Node | Val: {self._value} | Next: {self._next}>'
| 23.454545
| 66
| 0.581395
| 33
| 258
| 3.969697
| 0.393939
| 0.274809
| 0.198473
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.27907
| 258
| 10
| 67
| 25.8
| 0.704301
| 0
| 0
| 0
| 0
| 0
| 0.236434
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.375
| false
| 0
| 0
| 0.25
| 0.75
| 0
| 0
| 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
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 4
|
d093462a5dd90024700b280c1c05a2b840baf803
| 16
|
py
|
Python
|
gloomsim/__init__.py
|
AlanTolan/gloomsim
|
5414c7a8aaba0dc3b1c99d1b21e4a6232b1fc365
|
[
"MIT"
] | null | null | null |
gloomsim/__init__.py
|
AlanTolan/gloomsim
|
5414c7a8aaba0dc3b1c99d1b21e4a6232b1fc365
|
[
"MIT"
] | null | null | null |
gloomsim/__init__.py
|
AlanTolan/gloomsim
|
5414c7a8aaba0dc3b1c99d1b21e4a6232b1fc365
|
[
"MIT"
] | null | null | null |
# empty so far
| 5.333333
| 14
| 0.625
| 3
| 16
| 3.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.3125
| 16
| 2
| 15
| 8
| 0.909091
| 0.75
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
d0a82a14f7beb42bb587ee1e4ffcccc8a0deb4b8
| 390
|
py
|
Python
|
examples/utils/app.py
|
pichatelli/simple-settings
|
b0cb539a13581107effc674c823703e990e3463c
|
[
"MIT"
] | 213
|
2015-05-13T21:29:35.000Z
|
2022-02-24T12:56:00.000Z
|
examples/utils/app.py
|
pichatelli/simple-settings
|
b0cb539a13581107effc674c823703e990e3463c
|
[
"MIT"
] | 248
|
2015-05-13T23:32:16.000Z
|
2022-02-02T21:41:30.000Z
|
examples/utils/app.py
|
pichatelli/simple-settings
|
b0cb539a13581107effc674c823703e990e3463c
|
[
"MIT"
] | 39
|
2015-05-18T21:29:42.000Z
|
2022-03-26T16:27:46.000Z
|
from simple_settings import settings
from simple_settings.utils import settings_stub
# Stub examples
with settings_stub(SOME_SETTING='foo'):
assert settings.SOME_SETTING == 'foo'
assert settings.SOME_SETTING == 'bar'
@settings_stub(SOME_SETTING='foo')
def get_some_setting():
return settings.SOME_SETTING
assert get_some_setting() == 'foo'
assert settings.SOME_SETTING == 'bar'
| 24.375
| 47
| 0.782051
| 53
| 390
| 5.471698
| 0.301887
| 0.303448
| 0.193103
| 0.206897
| 0.517241
| 0.386207
| 0.386207
| 0.289655
| 0
| 0
| 0
| 0
| 0.117949
| 390
| 15
| 48
| 26
| 0.843023
| 0.033333
| 0
| 0.2
| 0
| 0
| 0.048
| 0
| 0
| 0
| 0
| 0
| 0.4
| 1
| 0.1
| true
| 0
| 0.2
| 0.1
| 0.4
| 0
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
d0ab3e8ed68efcd720ef84554774ee101be57e3b
| 68
|
py
|
Python
|
tonguetwister/xformat/info.py
|
lham/tonguetwister
|
ae8cd1555782f2e551a5d4156d8d247e08e354e1
|
[
"MIT"
] | 4
|
2021-03-06T19:26:27.000Z
|
2022-02-07T16:00:01.000Z
|
tonguetwister/xformat/info.py
|
lham/tonguetwister
|
ae8cd1555782f2e551a5d4156d8d247e08e354e1
|
[
"MIT"
] | null | null | null |
tonguetwister/xformat/info.py
|
lham/tonguetwister
|
ae8cd1555782f2e551a5d4156d8d247e08e354e1
|
[
"MIT"
] | null | null | null |
from dataclasses import dataclass
@dataclass
class Info:
pass
| 9.714286
| 33
| 0.764706
| 8
| 68
| 6.5
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.205882
| 68
| 6
| 34
| 11.333333
| 0.962963
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.25
| 0.25
| 0
| 0.5
| 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
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
d0d88acae48bf1ff854a50d2dcd9dec3b1137290
| 87
|
py
|
Python
|
Ethica/ethicaEnv/ethicaProject/Ethica/apps.py
|
oconnalla/ethicaApp
|
88fef16b70a0d8e2c5f43af6afd3e6bef43ff683
|
[
"MIT"
] | null | null | null |
Ethica/ethicaEnv/ethicaProject/Ethica/apps.py
|
oconnalla/ethicaApp
|
88fef16b70a0d8e2c5f43af6afd3e6bef43ff683
|
[
"MIT"
] | null | null | null |
Ethica/ethicaEnv/ethicaProject/Ethica/apps.py
|
oconnalla/ethicaApp
|
88fef16b70a0d8e2c5f43af6afd3e6bef43ff683
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class EthicaConfig(AppConfig):
name = 'Ethica'
| 14.5
| 33
| 0.747126
| 10
| 87
| 6.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.172414
| 87
| 5
| 34
| 17.4
| 0.902778
| 0
| 0
| 0
| 0
| 0
| 0.068966
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
d0fd6a9a61fe55ec05bbd4f274abbec45815b826
| 1,804
|
py
|
Python
|
migrations/versions/5cb851130ebb_.py
|
isabella232/comport
|
117123862415261095a917ed7f2037c1f986b474
|
[
"BSD-3-Clause"
] | 35
|
2015-11-14T18:32:45.000Z
|
2022-01-23T15:15:05.000Z
|
migrations/versions/5cb851130ebb_.py
|
codeforamerica/comport
|
117123862415261095a917ed7f2037c1f986b474
|
[
"BSD-3-Clause"
] | 119
|
2015-11-20T22:45:34.000Z
|
2022-02-10T23:02:36.000Z
|
migrations/versions/5cb851130ebb_.py
|
isabella232/comport
|
117123862415261095a917ed7f2037c1f986b474
|
[
"BSD-3-Clause"
] | 19
|
2015-11-20T20:41:52.000Z
|
2022-01-26T04:12:34.000Z
|
"""add officer age & years of service to SRPD incidents
Revision ID: 5cb851130ebb
Revises: c5e276c0d67f
Create Date: 2017-02-02 16:31:22.915785
"""
# revision identifiers, used by Alembic.
revision = '5cb851130ebb'
down_revision = 'c5e276c0d67f'
from alembic import op
import sqlalchemy as sa
def upgrade():
op.add_column('citizen_complaints_srpd', sa.Column('officer_age', sa.String(length=255), nullable=True))
op.add_column('citizen_complaints_srpd', sa.Column('officer_years_of_service', sa.String(length=255), nullable=True))
op.add_column('officer_involved_shootings_srpd', sa.Column('officer_age', sa.String(length=255), nullable=True))
op.add_column('officer_involved_shootings_srpd', sa.Column('officer_years_of_service', sa.String(length=255), nullable=True))
op.add_column('pursuits_srpd', sa.Column('officer_age', sa.String(length=255), nullable=True))
op.add_column('pursuits_srpd', sa.Column('officer_years_of_service', sa.String(length=255), nullable=True))
op.add_column('use_of_force_incidents_srpd', sa.Column('officer_age', sa.String(length=255), nullable=True))
op.add_column('use_of_force_incidents_srpd', sa.Column('officer_years_of_service', sa.String(length=255), nullable=True))
def downgrade():
op.drop_column('use_of_force_incidents_srpd', 'officer_years_of_service')
op.drop_column('use_of_force_incidents_srpd', 'officer_age')
op.drop_column('pursuits_srpd', 'officer_years_of_service')
op.drop_column('pursuits_srpd', 'officer_age')
op.drop_column('officer_involved_shootings_srpd', 'officer_years_of_service')
op.drop_column('officer_involved_shootings_srpd', 'officer_age')
op.drop_column('citizen_complaints_srpd', 'officer_years_of_service')
op.drop_column('citizen_complaints_srpd', 'officer_age')
| 50.111111
| 129
| 0.777716
| 261
| 1,804
| 5.034483
| 0.191571
| 0.118721
| 0.09589
| 0.115677
| 0.807458
| 0.807458
| 0.770928
| 0.727549
| 0.578387
| 0.480213
| 0
| 0.043876
| 0.090355
| 1,804
| 35
| 130
| 51.542857
| 0.756856
| 0.100333
| 0
| 0
| 0
| 0
| 0.421053
| 0.319505
| 0
| 0
| 0
| 0
| 0
| 1
| 0.090909
| false
| 0
| 0.090909
| 0
| 0.181818
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 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
| 4
|
ef7cdd1cc15633a00b0952c05fd01587b507d10f
| 140
|
py
|
Python
|
BarcodeRead/BarcodeRead/urls.py
|
fd239/DynamSoftBarcodeReaderPython
|
99f23add83067972f4d603ea2d064f725c66ceae
|
[
"MIT"
] | null | null | null |
BarcodeRead/BarcodeRead/urls.py
|
fd239/DynamSoftBarcodeReaderPython
|
99f23add83067972f4d603ea2d064f725c66ceae
|
[
"MIT"
] | 5
|
2021-03-19T11:59:23.000Z
|
2022-02-10T10:37:30.000Z
|
BarcodeRead/BarcodeRead/urls.py
|
fd239/DynamSoft_Barcode_Reader
|
99f23add83067972f4d603ea2d064f725c66ceae
|
[
"MIT"
] | null | null | null |
from django.urls import path
from . import views
urlpatterns = [
path('api/v1/get_barcode/', views.get_barcode, name='get_barcode')
]
| 17.5
| 70
| 0.721429
| 20
| 140
| 4.9
| 0.6
| 0.306122
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008403
| 0.15
| 140
| 7
| 71
| 20
| 0.815126
| 0
| 0
| 0
| 0
| 0
| 0.215827
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 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
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ef853111855e3500f6f62c806ed320fcfa149533
| 370
|
py
|
Python
|
demo/transcrypt/simple-packages/src/spam.py
|
ericsnowcurrently/pyweb
|
08b3ef62409922f03c82080070873d4d49802c4d
|
[
"BSD-3-Clause"
] | 3
|
2018-10-28T06:11:54.000Z
|
2020-04-07T19:40:58.000Z
|
demo/transcrypt/simple-packages/src/spam.py
|
ericsnowcurrently/pyweb
|
08b3ef62409922f03c82080070873d4d49802c4d
|
[
"BSD-3-Clause"
] | 1
|
2018-08-28T15:01:29.000Z
|
2018-08-28T17:19:11.000Z
|
demo/transcrypt/simple-packages/src/spam.py
|
ericsnowcurrently/pyweb
|
08b3ef62409922f03c82080070873d4d49802c4d
|
[
"BSD-3-Clause"
] | null | null | null |
# spam.py
import org
import org.python
import org.python.pypi
import org.python.pypi.myproject
import org.python.pypi.myproject.spam
def fail():
raise Exception('oops!')
print(__name__)
print()
now, menu = org.python.pypi.myproject.spam.get_menu()
print(f'menu at {now}s:')
for index, item in enumerate(menu, 1):
print(f' {index}: {item}')
print()
fail()
| 15.416667
| 53
| 0.705405
| 58
| 370
| 4.413793
| 0.448276
| 0.175781
| 0.234375
| 0.222656
| 0.335938
| 0
| 0
| 0
| 0
| 0
| 0
| 0.003135
| 0.137838
| 370
| 23
| 54
| 16.086957
| 0.799373
| 0.018919
| 0
| 0.133333
| 0
| 0
| 0.099723
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.066667
| true
| 0
| 0.333333
| 0
| 0.4
| 0.333333
| 0
| 0
| 0
| 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
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ef8f890ecaa6580bfa9a5121d7900b54ad858e04
| 1,191
|
py
|
Python
|
site/public/courses/CS-1.2/src/PlaylistLinkedList-StarterCode/Playlist.py
|
KitsuneNoctus/makeschool
|
5eec1a18146abf70bb78b4ee3d301f6a43c9ede4
|
[
"MIT"
] | 1
|
2021-08-24T20:22:19.000Z
|
2021-08-24T20:22:19.000Z
|
site/public/courses/CS-1.2/src/PlaylistLinkedList-StarterCode/Playlist.py
|
KitsuneNoctus/makeschool
|
5eec1a18146abf70bb78b4ee3d301f6a43c9ede4
|
[
"MIT"
] | null | null | null |
site/public/courses/CS-1.2/src/PlaylistLinkedList-StarterCode/Playlist.py
|
KitsuneNoctus/makeschool
|
5eec1a18146abf70bb78b4ee3d301f6a43c9ede4
|
[
"MIT"
] | null | null | null |
from Song import Song
class Playlist:
def __init__(self):
self.__first_song = None
# TODO: Create a method called add_song that creates a Song object and adds it to the playlist. This method has one parameter called title.
def add_song(self, title):
pass
# TODO: Create a method called find_song that searches for whether a song exits in the playlist and returns its index.
# The method has one parameters, title, which is the title of the song to be searched for. If the song is found, return its index. Otherwise, return -1.
def find_song(self, title):
pass
# TODO: Create a method called remove_song that removes a song from the playlist. This method takes one parameter, title, which is the song that should be removed.
def remove_song(self, title):
pass
# TODO: Create a method called length, which returns the number of songs in the playlist.
def length(self):
pass
# TODO: Create a method called print_songs that prints a numbered list of the songs in the playlist.
# Example:
# 1. Song Title 1
# 2. Song Title 2
# 3. Song Title 3
def print_songs(self):
pass
| 25.891304
| 167
| 0.690176
| 188
| 1,191
| 4.292553
| 0.345745
| 0.061958
| 0.068154
| 0.105328
| 0.210657
| 0.182156
| 0.148699
| 0.148699
| 0.148699
| 0
| 0
| 0.007928
| 0.258606
| 1,191
| 45
| 168
| 26.466667
| 0.906002
| 0.68178
| 0
| 0.357143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.022222
| 0
| 1
| 0.428571
| false
| 0.357143
| 0.071429
| 0
| 0.571429
| 0.071429
| 0
| 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
| 1
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
efcb89d48267d895c368785754802065fc2bb923
| 656
|
py
|
Python
|
nlpblock/layer/__init__.py
|
graykode/nlpblock
|
d7cd9e6d7a0ee401b8fecdbbf3a0ac60bdb3c0d7
|
[
"MIT"
] | 3
|
2019-02-27T13:41:26.000Z
|
2021-05-13T07:02:39.000Z
|
nlpblock/layer/__init__.py
|
graykode/nlpblock
|
d7cd9e6d7a0ee401b8fecdbbf3a0ac60bdb3c0d7
|
[
"MIT"
] | null | null | null |
nlpblock/layer/__init__.py
|
graykode/nlpblock
|
d7cd9e6d7a0ee401b8fecdbbf3a0ac60bdb3c0d7
|
[
"MIT"
] | 3
|
2019-03-02T02:19:46.000Z
|
2021-10-03T18:46:52.000Z
|
from nlpblock.layer import RNN
from nlpblock.layer.GRU import GRU
from nlpblock.layer.LSTM import LSTM
from nlpblock.layer.Attention import Attention
from nlpblock.layer.AttentionOne import AttentionOne
from nlpblock.layer.AttentionTwo import AttentionTwo
from nlpblock.layer.AttentionTwo import AttentionTwo
from nlpblock.layer.SelfAttnEncoder import SelfAttnEncoder
from nlpblock.layer.SelfAttnEncoderLayer import SelfAttnEncoderLayer
from nlpblock.layer.PosEncoding import PosEncoding
__all__ = [
'RNN', 'LSTM', 'GRU',
'Attention',
'AttentionOne',
'AttentionTwo',
'SelfAttnEncoder',
'SelfAttnEncoderLayer',
'PosEncoding',
]
| 31.238095
| 68
| 0.800305
| 69
| 656
| 7.550725
| 0.202899
| 0.230326
| 0.326296
| 0.111324
| 0.213052
| 0.213052
| 0.213052
| 0.213052
| 0.213052
| 0
| 0
| 0
| 0.125
| 656
| 21
| 69
| 31.238095
| 0.907666
| 0
| 0
| 0.105263
| 0
| 0
| 0.135464
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.526316
| 0
| 0.526316
| 0
| 0
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
560060903494a8a67cd0b561ec6aca32d85e3cb4
| 39
|
py
|
Python
|
neural-navigation-with-lstm/MARCO/nltk_contrib/mit/rspeer/parser/__init__.py
|
ronaldahmed/SLAM-for-ugv
|
52e3241b8b737a0cfe5682c0aa87ec8c27d6a33d
|
[
"MIT"
] | 14
|
2016-04-03T19:25:13.000Z
|
2022-01-05T07:03:07.000Z
|
neural-navigation-with-lstm/MARCO/nltk_contrib/mit/rspeer/parser/__init__.py
|
ronaldahmed/SLAM-for-ugv
|
52e3241b8b737a0cfe5682c0aa87ec8c27d6a33d
|
[
"MIT"
] | null | null | null |
neural-navigation-with-lstm/MARCO/nltk_contrib/mit/rspeer/parser/__init__.py
|
ronaldahmed/SLAM-for-ugv
|
52e3241b8b737a0cfe5682c0aa87ec8c27d6a33d
|
[
"MIT"
] | 5
|
2018-06-21T12:58:58.000Z
|
2020-02-15T05:33:39.000Z
|
"""
A feature-based chart parser.
"""
| 7.8
| 29
| 0.615385
| 5
| 39
| 4.8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.179487
| 39
| 4
| 30
| 9.75
| 0.75
| 0.74359
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
4bca2512823f794cae2079f246c89954c1a88b92
| 26,442
|
py
|
Python
|
crossdomain/model/models.py
|
INK-USC/ConNet
|
adb299f160556004561df302c19578200bd3835b
|
[
"MIT"
] | 11
|
2019-11-13T13:33:30.000Z
|
2022-03-27T13:16:19.000Z
|
crossdomain/model/models.py
|
INK-USC/ConNet
|
adb299f160556004561df302c19578200bd3835b
|
[
"MIT"
] | null | null | null |
crossdomain/model/models.py
|
INK-USC/ConNet
|
adb299f160556004561df302c19578200bd3835b
|
[
"MIT"
] | 2
|
2020-05-27T15:17:58.000Z
|
2020-07-09T08:57:21.000Z
|
import torch
import torch.nn as nn
from torch.nn import Parameter
import numpy as np
import model.crf as crf
# Single-task model with MLP
class STM_MLP(nn.Module):
def __init__(self, args):
super(STM_MLP, self).__init__()
self.mlp = nn.Linear(5000, args['mlp_hid'])
self.cla = nn.Linear(args['mlp_hid'], 1)
self.dropout = nn.Dropout(p=args['dropout'])
self.sigmoid = nn.Sigmoid()
def forward(self, data_input):
mlp_out = self.dropout(self.mlp(data_input))
cla = self.sigmoid(self.cla(mlp_out)).squeeze(1)
return cla
# CN_MLP model
class CN_MLP(nn.Module):
def __init__(self, args):
super(CN_MLP, self).__init__()
self.args = args
self.mlp = nn.Linear(5000, args['mlp_hid'])
self.CM = nn.Parameter(torch.Tensor(args['num_tasks'], args['mlp_hid'], args['mlp_hid']))
nn.init.xavier_normal_(self.CM)
self.attn = nn.Parameter(torch.Tensor(args['mlp_hid'], args['num_tasks']))
nn.init.xavier_normal_(self.attn)
self.cla = nn.Linear(args['mlp_hid'], 1)
self.dropout = nn.Dropout(p=args['dropout'])
self.sigmoid = nn.Sigmoid()
self.softmax = nn.Softmax(dim=1)
# switch to extraction training
def extraction_phase(self):
self.attn.requires_grad = False
self.mlp.weight.requires_grad = True
self.CM.requires_grad = True
self.cla.weight.requires_grad = True
# switch to aggregation training
def aggregation_phase(self):
self.attn.requires_grad = True
if not self.args['fine_tune']:
self.mlp.weight.requires_grad = False
self.CM.requires_grad = False
self.cla.weight.requires_grad = False
def forward(self, data_input, task_ids):
# process the input and return lstm output
# data_input: batch_size * 5000
mlp_out = self.dropout(self.mlp(data_input))
# aggregation phase
if task_ids == None:
task_attn = mlp_out.mm(self.attn)
batch_size = mlp_out.shape[0]
consensus = (self.softmax(task_attn).unsqueeze(-1).unsqueeze(-1) * torch.unsqueeze(self.CM, 0).repeat(batch_size,1,1,1)).sum(1)
# extraction phase
else:
consensus = self.CM[task_ids]
mlp_out_1 = self.dropout(mlp_out.unsqueeze(1).bmm(consensus)).squeeze(1)
cla = self.sigmoid(self.cla(mlp_out_1)).squeeze(1)
return cla
# base class for all models: take input data, return lstm output
class Base_Model(nn.Module):
def __init__(self, args, emb):
super(Base_Model, self).__init__()
self.args = args
# embeddings, lstms
if self.args['char_rnn']:
self.char_emb = nn.Embedding.from_pretrained(Parameter(torch.FloatTensor(emb[0])), freeze=False if args['fine_tune_char_emb'] else True)
self.char_lstm = nn.LSTM(self.char_emb.weight.shape[1], args['char_rnn_hid'], args['char_rnn_layers'], bidirectional=True, batch_first=True)
if self.args['word_rnn']:
self.word_emb = nn.Embedding.from_pretrained(Parameter(torch.FloatTensor(emb[1])), freeze=False if args['fine_tune_word_emb'] else True)
word_rnn_input_dim = self.word_emb.weight.shape[1]
if self.args['char_rnn']:
word_rnn_input_dim += 2 * args['char_rnn_hid']
self.word_lstm = nn.LSTM(word_rnn_input_dim, args['word_rnn_hid'], args['word_rnn_layers'], bidirectional=True, batch_first=True)
self.dropout = nn.Dropout(p=args['dropout'])
self.softmax = nn.Softmax(dim=1)
def forward(self, data_input):
# process the input and return lstm output
# chars (data_input[0]): batch_size * char_seq_len * char_emb_dim
# words (data_input[1]): batch_size * word_seq_len * word_emb_dim
if self.args['char_rnn']:
chars, char_start, char_end = data_input[0]
batch_size = chars.shape[0]
char_emb_out = self.dropout(self.char_emb(chars))
char_lstm_out = self.dropout(self.char_lstm(char_emb_out)[0])
if self.args['word_rnn']:
char_lstm_out_f = char_lstm_out[:,:,:self.args['char_rnn_hid']]
char_lstm_out_b = char_lstm_out[:,:,self.args['char_rnn_hid']:]
word_max_len = np.array(char_start).shape[1]
idx = [[ii for i in range(word_max_len)] for ii in range(batch_size)]
word_rep_f = char_lstm_out_f[[idx,char_end]]
word_rep_b = char_lstm_out_b[[idx,char_start]]
word_rep = torch.cat((word_rep_f, word_rep_b), dim=2)
if self.args['word_rnn']:
words = data_input[1]
batch_size = words.shape[0]
word_emb_out = self.dropout(self.word_emb(words))
if self.args['char_rnn']:
mask = words != self.args['pad_word_idx']
word_rep = word_rep * mask.float().unsqueeze(-1)
word_out = torch.cat((word_emb_out, word_rep), dim=2)
else:
word_out = word_emb_out
lstm_out = self.dropout(self.word_lstm(word_out)[0])
return lstm_out
# Single-task model
class STM(Base_Model):
def __init__(self, args, emb):
super(STM, self).__init__(args, emb)
self.crf = crf.Orig_CRF_S(args['word_rnn_hid'], args['tagset_size'])
def forward(self, data_input):
lstm_out = super(STM, self).forward(data_input)
crf_out = self.crf(lstm_out)
return crf_out
# Multi-task model
class MTM(Base_Model):
def __init__(self, args, emb):
super(MTM, self).__init__(args, emb)
self.crf_list = crf.List_Orig_CRF_S(args['word_rnn_hid'], args['tagset_size'], args['num_tasks'])
def forward(self, data_input, task_ids):
lstm_out = super(MTM, self).forward(data_input)
crf_out = self.crf_list(lstm_out, task_ids)
return crf_out
# Peng et al, 2016
class Peng_2016(Base_Model):
def __init__(self, args, emb, method):
assert method in ['domain_mask', 'domain_trans']
super(Peng_2016, self).__init__(args, emb)
self.method = method
if self.method == 'domain_mask':
self.domain_width = int(self.args['word_rnn_hid'] / (self.args['num_tasks']+1))
self.shared_width = args['word_rnn_hid'] - self.domain_width * self.args['num_tasks']
else:
self.trans_mat = nn.Parameter(torch.Tensor(self.args['num_tasks'], args['word_rnn_hid']*2, args['word_rnn_hid']*2))
nn.init.xavier_normal_(self.trans_mat)
self.crf = crf.Orig_CRF_S(args['word_rnn_hid'], args['tagset_size'])
def forward(self, data_input, task_id):
lstm_out = super(Peng_2016, self).forward(data_input)
if self.method == 'domain_mask':
domain_mask = np.zeros(self.args['word_rnn_hid']*2)
domain_mask[:self.shared_width] = 1
domain_mask[self.args['word_rnn_hid']:(self.args['word_rnn_hid']+self.shared_width)] = 1
domain_mask[(self.shared_width+self.domain_width*task_id):(self.shared_width+self.domain_width*(task_id+1))] = 1
domain_mask[(self.args['word_rnn_hid']+self.shared_width+self.domain_width*task_id):(self.args['word_rnn_hid']+self.shared_width+self.domain_width*(task_id+1))] = 1
domain_mask = torch.tensor(domain_mask)
if self.args['cuda']:
domain_mask = domain_mask.cuda()
crf_input = lstm_out * domain_mask.float().unsqueeze(0).unsqueeze(0)
crf_out = self.crf(crf_input)
else:
batch_size = lstm_out.shape[0]
batch_trans_mat = self.trans_mat[task_id].unsqueeze(0).repeat(batch_size, 1, 1)
crf_input = torch.bmm(lstm_out, batch_trans_mat)
crf_out = self.crf(crf_input)
return crf_out
# Crowd-Add
class Crowd_add(Base_Model):
def __init__(self, args, emb):
super(Crowd_add, self).__init__(args, emb)
self.crowd_vecs = nn.Parameter(torch.Tensor(args['num_tasks'], args['tagset_size']))
nn.init.xavier_normal_(self.crowd_vecs)
self.crf = crf.Crowd_add_CRF_S(args['word_rnn_hid'], args['tagset_size'])
def forward(self, data_input, task_ids):
lstm_out = super(Crowd_add, self).forward(data_input)
batch_size = lstm_out.shape[0]
if task_ids:
crowd_rep = self.crowd_vecs[task_ids]
else:
crowd_rep = self.crowd_vecs.mean(0).unsqueeze(0).repeat(batch_size, 1)
crf_out = self.crf(lstm_out, crowd_rep)
return crf_out
# Crowd-Add
class Crowd_add_MLP(nn.Module):
def __init__(self, args):
super(Crowd_add_MLP, self).__init__()
self.mlp = nn.Linear(5000, args['mlp_hid'])
self.crowd_vecs = nn.Parameter(torch.Tensor(args['num_tasks'], args['mlp_hid']))
nn.init.xavier_normal_(self.crowd_vecs)
self.cla = nn.Linear(args['mlp_hid'], 1)
self.dropout = nn.Dropout(p=args['dropout'])
self.sigmoid = nn.Sigmoid()
def forward(self, data_input, task_ids):
mlp_out = self.dropout(self.mlp(data_input))
batch_size = mlp_out.shape[0]
if task_ids:
crowd_rep = self.crowd_vecs[task_ids]
else:
crowd_rep = self.crowd_vecs.mean(0).unsqueeze(0).repeat(batch_size, 1)
mlp_out_ = mlp_out + crowd_rep
cla = self.sigmoid(self.cla(mlp_out)).squeeze(1)
return cla
# Crowd-Add
class Crowd_cat(Base_Model):
def __init__(self, args, emb):
super(Crowd_cat, self).__init__(args, emb)
self.crowd_vecs = nn.Parameter(torch.Tensor(args['num_tasks'], 50))
nn.init.xavier_normal_(self.crowd_vecs)
self.crf = crf.Orig_CRF_S(args['word_rnn_hid']+25, args['tagset_size'])
def forward(self, data_input, task_ids):
lstm_out = super(Crowd_cat, self).forward(data_input)
batch_size = lstm_out.shape[0]
if task_ids:
crowd_rep = self.crowd_vecs[task_ids]
else:
crowd_rep = self.crowd_vecs.mean(0).unsqueeze(0).repeat(batch_size, 1)
lstm_out_ = torch.cat((lstm_out, crowd_rep.unsqueeze(1).repeat(1,lstm_out.shape[1],1)), 2)
crf_out = self.crf(lstm_out_)
return crf_out
# Crowd-Add
class Crowd_cat_MLP(nn.Module):
def __init__(self, args):
super(Crowd_cat_MLP, self).__init__()
self.mlp = nn.Linear(5000, args['mlp_hid'])
self.crowd_vecs = nn.Parameter(torch.Tensor(args['num_tasks'], 50))
nn.init.xavier_normal_(self.crowd_vecs)
self.cla = nn.Linear(args['mlp_hid']+50, 1)
self.dropout = nn.Dropout(p=args['dropout'])
self.sigmoid = nn.Sigmoid()
def forward(self, data_input, task_ids):
mlp_out = self.dropout(self.mlp(data_input))
batch_size = mlp_out.shape[0]
if task_ids:
crowd_rep = self.crowd_vecs[task_ids]
else:
crowd_rep = self.crowd_vecs.mean(0).unsqueeze(0).repeat(batch_size, 1)
mlp_out_ = torch.cat((mlp_out, crowd_rep), 1)
cla = self.sigmoid(self.cla(mlp_out_)).squeeze(1)
return cla
# base class for two-phase training Consensus Network
class Base_CN(Base_Model):
def __init__(self, args, emb):
super(Base_CN, self).__init__(args, emb)
# attention layer
self.attn = nn.Parameter(torch.Tensor(args['word_rnn_hid']*2, args['num_tasks']))
nn.init.xavier_normal_(self.attn)
# switch to extraction training
def extraction_phase(self):
self.attn.requires_grad = False
if self.args['char_rnn']:
if self.args['fine_tune_char_emb']:
self.char_emb.weight.requires_grad = True
for param in self.char_lstm.parameters():
param.requires_grad = True
if self.args['word_rnn']:
if self.args['fine_tune_word_emb']:
self.word_emb.weight.requires_grad = True
for param in self.word_lstm.parameters():
param.requires_grad = True
# switch to aggregation training
def aggregation_phase(self):
self.attn.requires_grad = True
if not self.args['fine_tune']:
if self.args['char_rnn']:
self.char_emb.weight.requires_grad = False
for param in self.char_lstm.parameters():
param.requires_grad = False
if self.args['word_rnn']:
self.word_emb.weight.requires_grad = False
for param in self.word_lstm.parameters():
param.requires_grad = False
def forward(self, data_input, sent_end):
# sent_end: batch_size or None (in extraction phase)
lstm_out = super(Base_CN, self).forward(data_input)
batch_size = lstm_out.shape[0]
# compute attention output for aggregation phase
if sent_end:
lstm_out_f = lstm_out[:,:,:int(lstm_out.shape[2]/2)]
lstm_out_b = lstm_out[:,:,int(lstm_out.shape[2]/2):]
f_sent_rep = lstm_out_f[[range(batch_size),sent_end]]
b_sent_rep = lstm_out_b[[range(batch_size),[0]*batch_size]]
sent_rep = torch.cat((f_sent_rep, b_sent_rep), dim=1)
task_attn = sent_rep.mm(self.attn)
return lstm_out, task_attn
else:
return lstm_out
# Two-phase training Consensus Network
class CN_2(Base_CN):
def __init__(self, args, emb):
super(CN_2, self).__init__(args, emb)
self.crf = crf.CN_CRF_S(args['word_rnn_hid'], args['tagset_size'])
# consensus matrices
self.CM = nn.Parameter(torch.Tensor(args['num_tasks'], args['tagset_size'], args['tagset_size']))
nn.init.xavier_normal_(self.CM)
def extraction_phase(self):
super(CN_2, self).extraction_phase()
self.CM.requires_grad = True
self.crf.extraction_phase()
def aggregation_phase(self):
super(CN_2, self).aggregation_phase()
if not self.args['fine_tune']:
self.CM.requires_grad = False
self.crf.aggregation_phase()
def forward(self, data_input, sent_end, task_ids):
# aggregation phase
if task_ids == None:
lstm_out, task_attn = super(CN_2, self).forward(data_input, sent_end)
batch_size = lstm_out.shape[0]
consensus = (self.softmax(task_attn).unsqueeze(-1).unsqueeze(-1) * torch.unsqueeze(self.CM, 0).repeat(batch_size,1,1,1)).sum(1)
# extraction phase
else:
lstm_out = super(CN_2, self).forward(data_input, None)
consensus = self.CM[task_ids]
crf_out = self.crf(lstm_out, consensus)
return crf_out
# Flexible Consensus Network (two linear mappings, both task-specific)
class FCN_2(Base_CN):
def __init__(self, args, emb):
super(FCN_2, self).__init__(args, emb)
self.crf = crf.FCN_CRF_S(args['word_rnn_hid'], args['tagset_size'])
# consensus matrices
self.CM1 = nn.Parameter(torch.Tensor(args['num_tasks'], args['tagset_size'], args['cm_dim']))
self.CM2 = nn.Parameter(torch.Tensor(args['num_tasks'], args['cm_dim'], args['tagset_size']))
nn.init.xavier_normal_(self.CM1)
nn.init.xavier_normal_(self.CM2)
def extraction_phase(self):
super(FCN_2, self).extraction_phase()
self.CM1.requires_grad = True
self.CM2.requires_grad = True
self.crf.extraction_phase()
def aggregation_phase(self):
super(FCN_2, self).aggregation_phase()
if not self.args['fine_tune']:
self.CM1.requires_grad = False
self.CM2.requires_grad = False
self.crf.aggregation_phase()
def forward(self, data_input, sent_end, task_ids):
# aggregation phase
if task_ids == None:
lstm_out, task_attn = super(FCN_2, self).forward(data_input, sent_end)
batch_size = lstm_out.shape[0]
consensus1 = (self.softmax(task_attn).unsqueeze(-1).unsqueeze(-1) * torch.unsqueeze(self.CM1, 0).repeat(batch_size,1,1,1)).sum(1)
consensus2 = (self.softmax(task_attn).unsqueeze(-1).unsqueeze(-1) * torch.unsqueeze(self.CM2, 0).repeat(batch_size,1,1,1)).sum(1)
# extraction phase
else:
lstm_out = super(FCN_2, self).forward(data_input, None)
consensus1 = self.CM1[task_ids]
consensus2 = self.CM2[task_ids]
crf_out = self.crf(lstm_out, consensus1, consensus2)
return crf_out
# More Flexible Consensus Network v2 (first mapping shared, second mapping task-specific)
class FCN_2_v2(Base_CN):
def __init__(self, args, emb):
super(FCN_2_v2, self).__init__(args, emb)
self.crf = crf.FCN_CRF_S(args['word_rnn_hid'], args['tagset_size'])
# consensus matrices
self.CM1 = nn.Parameter(torch.Tensor(args['tagset_size'], args['cm_dim']))
self.CM2 = nn.Parameter(torch.Tensor(args['num_tasks'], args['cm_dim'], args['tagset_size']))
nn.init.xavier_normal_(self.CM1)
nn.init.xavier_normal_(self.CM2)
def extraction_phase(self):
super(FCN_2_v2, self).extraction_phase()
self.CM1.requires_grad = True
self.CM2.requires_grad = True
self.crf.extraction_phase()
def aggregation_phase(self):
super(FCN_2_v2, self).aggregation_phase()
if not self.args['fine_tune']:
self.CM1.requires_grad = False
self.CM2.requires_grad = False
self.crf.aggregation_phase()
def forward(self, data_input, sent_end, task_ids):
# aggregation phase
if task_ids == None:
lstm_out, task_attn = super(FCN_2_v2, self).forward(data_input, sent_end)
batch_size = lstm_out.shape[0]
consensus2 = (self.softmax(task_attn).unsqueeze(-1).unsqueeze(-1) * torch.unsqueeze(self.CM2, 0).repeat(batch_size,1,1,1)).sum(1)
# extraction phase
else:
lstm_out = super(FCN_2_v2, self).forward(data_input, None)
batch_size = lstm_out.shape[0]
consensus2 = self.CM2[task_ids]
# first consensus is shared
consensus1 = self.CM1.unsqueeze(0).repeat(batch_size, 1, 1)
crf_out = self.crf(lstm_out, consensus1, consensus2)
return crf_out
# Base class for adversarial training Consensus Network
class Base_ADV_CN(Base_CN):
def __init__(self, args, emb):
super(Base_ADV_CN, self).__init__(args, emb)
# classifier (for adversarial training)
self.cla = nn.Linear(args['word_rnn_hid']*2, args['num_tasks'])
nn.init.xavier_normal_(self.cla.weight)
def extraction_phase(self):
super(Base_ADV_CN, self).extraction_phase()
self.cla.weight.requires_grad = False
def aggregation_phase(self):
super(Base_ADV_CN, self).aggregation_phase()
self.cla.weight.requires_grad = False
def train_cla_phase(self):
self.cla.weight.requires_grad = True
self.attn.requires_grad = False
if self.args['char_rnn']:
self.char_emb.weight.requires_grad = False
for param in self.char_lstm.parameters():
param.requires_grad = False
if self.args['word_rnn']:
self.word_emb.weight.requires_grad = False
for param in self.word_lstm.parameters():
param.requires_grad = False
def adv_phase(self):
self.cla.weight.requires_grad = False
self.attn.requires_grad = False
if self.args['char_rnn']:
self.char_emb.weight.requires_grad = False
for param in self.char_lstm.parameters():
param.requires_grad = True
if self.args['word_rnn']:
self.word_emb.weight.requires_grad = False
for param in self.word_lstm.parameters():
param.requires_grad = True
def forward(self, data_input, sent_end, model_name):
# aggregation phase
if model_name == 'adv_cn-agg':
lstm_out, task_attn = super(Base_ADV_CN, self).forward(data_input, sent_end)
return lstm_out, task_attn
# extraction phase
elif model_name == 'adv_cn-ext':
lstm_out = super(Base_ADV_CN, self).forward(data_input, None)
return lstm_out
# training classifier phase or adversarial training phase
elif model_name in ['adv_cn-adv', 'adv_cn-train_cla']:
lstm_out = super(Base_ADV_CN, self).forward(data_input, None)
batch_size = lstm_out.shape[0]
lstm_out_f = lstm_out[:,:,:self.args['word_rnn_hid']]
lstm_out_b = lstm_out[:,:,self.args['word_rnn_hid']:]
f_sent_rep = lstm_out_f[[range(batch_size),sent_end]]
b_sent_rep = lstm_out_b[[range(batch_size),[0]*batch_size]]
sent_rep = torch.cat((f_sent_rep, b_sent_rep), dim=1)
cla_out = self.cla(sent_rep)
return cla_out
class ADV_CN(Base_ADV_CN):
def __init__(self, args, emb):
super(ADV_CN, self).__init__(args, emb)
self.crf = crf.CN_CRF_S(args['word_rnn_hid'], args['tagset_size'])
# consensus matrices
self.CM = nn.Parameter(torch.Tensor(args['num_tasks'], args['tagset_size'], args['tagset_size']))
nn.init.xavier_normal_(self.CM)
def extraction_phase(self):
super(ADV_CN, self).extraction_phase()
self.CM.requires_grad = True
self.crf.extraction_phase()
def aggregation_phase(self):
super(ADV_CN, self).aggregation_phase()
if self.args['fine_tune']:
self.CM.requires_grad = True
self.crf.extraction_phase()
else:
self.CM.requires_grad = False
self.crf.aggregation_phase()
def train_cla_phase(self):
super(ADV_CN, self).train_cla_phase()
self.CM.requires_grad = False
self.crf.aggregation_phase()
def adv_phase(self):
super(ADV_CN, self).adv_phase()
self.CM.requires_grad = False
self.crf.aggregation_phase()
def forward(self, data_input, sent_end, task_ids, model_name):
if model_name == 'adv_cn-agg':
lstm_out, task_attn = super(ADV_CN, self).forward(data_input, sent_end, model_name)
batch_size = lstm_out.shape[0]
consensus = (self.softmax(task_attn).unsqueeze(-1).unsqueeze(-1) * torch.unsqueeze(self.CM, 0).repeat(batch_size,1,1,1)).sum(1)
crf_out = self.crf(lstm_out, consensus)
return crf_out
elif model_name == 'adv_cn-ext':
lstm_out = super(ADV_CN, self).forward(data_input, None, model_name)
consensus = self.CM[task_ids]
crf_out = self.crf(lstm_out, consensus)
return crf_out
elif model_name in ['adv_cn-adv', 'adv_cn-train_cla']:
cla_out = super(ADV_CN, self).forward(data_input, sent_end, model_name)
return cla_out
class ADV_FCN_v2(Base_ADV_CN):
def __init__(self, args, emb):
super(ADV_FCN_v2, self).__init__(args, emb)
self.crf = crf.FCN_CRF_S(args['word_rnn_hid'], args['tagset_size'])
# consensus matrices
self.CM1 = nn.Parameter(torch.Tensor(args['tagset_size'], args['cm_dim']))
self.CM2 = nn.Parameter(torch.Tensor(args['num_tasks'], args['cm_dim'], args['tagset_size']))
nn.init.xavier_normal_(self.CM1)
nn.init.xavier_normal_(self.CM2)
def extraction_phase(self):
super(ADV_FCN_v2, self).extraction_phase()
self.CM1.requires_grad = True
self.CM2.requires_grad = True
self.crf.extraction_phase()
def aggregation_phase(self):
super(ADV_FCN_v2, self).aggregation_phase()
if self.args['fine_tune']:
self.CM1.requires_grad = True
self.CM2.requires_grad = True
self.crf.extraction_phase()
else:
self.CM1.requires_grad = False
self.CM2.requires_grad = False
self.crf.aggregation_phase()
def train_cla_phase(self):
super(ADV_FCN_v2, self).train_cla_phase()
self.CM1.requires_grad = False
self.CM2.requires_grad = False
self.crf.aggregation_phase()
def adv_phase(self):
super(ADV_FCN_v2, self).adv_phase()
self.CM1.requires_grad = False
self.CM2.requires_grad = False
self.crf.aggregation_phase()
def forward(self, data_input, sent_end, task_ids, model_name):
if model_name == 'adv_cn-agg':
lstm_out, task_attn = super(ADV_FCN_v2, self).forward(data_input, sent_end, model_name)
batch_size = lstm_out.shape[0]
consensus1 = self.CM1.unsqueeze(0).repeat(batch_size, 1, 1)
consensus2 = (self.softmax(task_attn).unsqueeze(-1).unsqueeze(-1) * torch.unsqueeze(self.CM2, 0).repeat(batch_size,1,1,1)).sum(1)
crf_out = self.crf(lstm_out, consensus1, consensus2)
return crf_out
elif model_name == 'adv_cn-ext':
lstm_out = super(ADV_FCN_v2, self).forward(data_input, None, model_name)
batch_size = lstm_out.shape[0]
consensus1 = self.CM1.unsqueeze(0).repeat(batch_size, 1, 1)
consensus2 = self.CM2[task_ids]
crf_out = self.crf(lstm_out, consensus1, consensus2)
return crf_out
elif model_name in ['adv_cn-adv', 'adv_cn-train_cla']:
cla_out = super(ADV_FCN_v2, self).forward(data_input, sent_end, model_name)
return cla_out
| 38.942563
| 176
| 0.611754
| 3,617
| 26,442
| 4.173348
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app/callbacks/__init__.py
|
oldcryptogeek/coinjerk-btcp
|
76d16b6c890bf1caa155ff07bca162526db08fc7
|
[
"MIT"
] | 8
|
2020-09-22T03:40:31.000Z
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2021-04-17T15:17:03.000Z
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app/callbacks/__init__.py
|
Zaxounette/coinjerk-btcp
|
76d16b6c890bf1caa155ff07bca162526db08fc7
|
[
"MIT"
] | 5
|
2021-01-10T23:36:12.000Z
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2022-02-19T06:46:18.000Z
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app/callbacks/__init__.py
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Zaxounette/coinjerk-btcp
|
76d16b6c890bf1caa155ff07bca162526db08fc7
|
[
"MIT"
] | 2
|
2021-01-03T23:36:39.000Z
|
2021-02-13T15:45:09.000Z
|
from flask import Blueprint
from flask_cors import CORS
callbacks = Blueprint('callbacks', __name__)
CORS(callbacks)
from app.callbacks import routes # noqa: F401 E402
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py
|
Python
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WAFNinja/ninja/__init__.py
|
pretech86/carbontoolkit
|
60bc3cafe0314cb60752ed165b4a419a0a7f81be
|
[
"MIT"
] | 7
|
2020-02-29T01:09:22.000Z
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2022-02-17T03:37:46.000Z
|
WAFNinja/ninja/__init__.py
|
amrm121/carbontoolkit
|
60bc3cafe0314cb60752ed165b4a419a0a7f81be
|
[
"MIT"
] | null | null | null |
WAFNinja/ninja/__init__.py
|
amrm121/carbontoolkit
|
60bc3cafe0314cb60752ed165b4a419a0a7f81be
|
[
"MIT"
] | 2
|
2020-01-28T07:34:30.000Z
|
2020-03-01T12:04:43.000Z
|
__author__ = "Acer"
__date__ = "$14.07.2015 15:44:44$"
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4bfba430e4b37bf54efe229e82c50060710c29d9
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|
py
|
Python
|
geoapyfr/admin/__init__.py
|
hadrilec/geoapyfr
|
555b42c83f2f100bbd19a6ef5c42743873fcf3a7
|
[
"MIT"
] | 1
|
2021-08-11T21:45:39.000Z
|
2021-08-11T21:45:39.000Z
|
geoapyfr/admin/__init__.py
|
hadrilec/geoapyfr
|
555b42c83f2f100bbd19a6ef5c42743873fcf3a7
|
[
"MIT"
] | null | null | null |
geoapyfr/admin/__init__.py
|
hadrilec/geoapyfr
|
555b42c83f2f100bbd19a6ef5c42743873fcf3a7
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from .get_departement import get_departement
from .get_region import get_region
from .get_commune import get_commune
__all__ = ['get_departement', 'get_region', 'get_commune']
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0
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ef0e12f9343dd65e63489dadbf2ca309b6fbeec8
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|
py
|
Python
|
espressodb/notifications/templatetags/__init__.py
|
remram44/espressodb
|
5aad7222ab81c0f1694b51171e5d197dbcc8a65f
|
[
"BSD-3-Clause"
] | 8
|
2019-12-10T04:30:01.000Z
|
2020-10-30T09:40:22.000Z
|
espressodb/notifications/templatetags/__init__.py
|
remram44/espressodb
|
5aad7222ab81c0f1694b51171e5d197dbcc8a65f
|
[
"BSD-3-Clause"
] | 41
|
2019-10-23T00:26:25.000Z
|
2021-10-21T07:55:57.000Z
|
espressodb/notifications/templatetags/__init__.py
|
remram44/espressodb
|
5aad7222ab81c0f1694b51171e5d197dbcc8a65f
|
[
"BSD-3-Clause"
] | 3
|
2020-01-09T21:29:09.000Z
|
2021-03-14T22:20:52.000Z
|
"""Templatetags for the notifications module.
"""
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0
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ef37a1c7faf5c51f2b230b0f5a73aacf3c8553a3
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|
py
|
Python
|
src/bpp/admin/wydawnictwo_zwarte_autor.py
|
iplweb/django-bpp
|
85f183a99d8d5027ae4772efac1e4a9f21675849
|
[
"BSD-3-Clause"
] | 1
|
2017-04-27T19:50:02.000Z
|
2017-04-27T19:50:02.000Z
|
src/bpp/admin/wydawnictwo_zwarte_autor.py
|
mpasternak/django-bpp
|
434338821d5ad1aaee598f6327151aba0af66f5e
|
[
"BSD-3-Clause"
] | 41
|
2019-11-07T00:07:02.000Z
|
2022-02-27T22:09:39.000Z
|
src/bpp/admin/wydawnictwo_zwarte_autor.py
|
iplweb/bpp
|
f027415cc3faf1ca79082bf7bacd4be35b1a6fdf
|
[
"BSD-3-Clause"
] | null | null | null |
# -*- encoding: utf-8 -*-
from django.contrib import admin
from bpp.admin.wydawnictwo_autor_base import Wydawnictwo_Autor_Base
from bpp.models import Wydawnictwo_Zwarte, Wydawnictwo_Zwarte_Autor
@admin.register(Wydawnictwo_Zwarte_Autor)
class Wydawnictwo_Zwarte_Autor_Admin(Wydawnictwo_Autor_Base):
klasa_autora = Wydawnictwo_Zwarte_Autor
base_rekord_class = Wydawnictwo_Zwarte
change_list_template = "admin/bpp/wydawnictwo_zwarte_autor/change_list.html"
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0
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ef38a4c47aeadb017fac152be2fea5d802912d94
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py
|
Python
|
resources.py
|
AlexanderPretel/colector
|
980a2c4f9e5c7ff1d6f12675a9c6868f7fb8cdfe
|
[
"MIT"
] | null | null | null |
resources.py
|
AlexanderPretel/colector
|
980a2c4f9e5c7ff1d6f12675a9c6868f7fb8cdfe
|
[
"MIT"
] | null | null | null |
resources.py
|
AlexanderPretel/colector
|
980a2c4f9e5c7ff1d6f12675a9c6868f7fb8cdfe
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.12.8)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
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qt_resource_name = b"\
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"
qt_resource_struct_v1 = b"\
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qt_resource_struct_v2 = b"\
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"
qt_version = [int(v) for v in QtCore.qVersion().split('.')]
if qt_version < [5, 8, 0]:
rcc_version = 1
qt_resource_struct = qt_resource_struct_v1
else:
rcc_version = 2
qt_resource_struct = qt_resource_struct_v2
def qInitResources():
QtCore.qRegisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
| 65.240891
| 103
| 0.727247
| 52,440
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| 3.004024
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| 0
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| 216,665
| 3,320
| 104
| 65.260542
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| 1
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| null | 1
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ef4a0960c5b953b840c2ca563441b25172a05db8
| 212
|
py
|
Python
|
tests/e2e_tests/test_gylm/__init__.py
|
rudolfspetrovs/benchml
|
896673f387a6bb9b185664ddd54f569a1ba54e51
|
[
"Apache-2.0"
] | 3
|
2021-08-12T13:25:31.000Z
|
2022-03-21T21:30:22.000Z
|
tests/e2e_tests/test_gylm/__init__.py
|
rudolfspetrovs/benchml
|
896673f387a6bb9b185664ddd54f569a1ba54e51
|
[
"Apache-2.0"
] | 5
|
2020-12-08T08:59:41.000Z
|
2022-01-22T06:46:09.000Z
|
tests/e2e_tests/test_gylm/__init__.py
|
rudolfspetrovs/benchml
|
896673f387a6bb9b185664ddd54f569a1ba54e51
|
[
"Apache-2.0"
] | 1
|
2021-06-25T11:07:32.000Z
|
2021-06-25T11:07:32.000Z
|
import os
from benchml.test import TestMock
class TestGylm(TestMock):
model_regex = ["bmol_gylm_standard_int_krr"]
data_dir = ("..", "test_data", "molecular_tiny")
path = os.path.dirname(__file__)
| 21.2
| 52
| 0.712264
| 28
| 212
| 4.964286
| 0.785714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.160377
| 212
| 9
| 53
| 23.555556
| 0.780899
| 0
| 0
| 0
| 0
| 0
| 0.240566
| 0.122642
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
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| 1
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| 0
| null | 0
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| 0
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| 0
| 0
| 0
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| null | 0
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| 0
| 0
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| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
ef67c745bf3e12a2139d99c76796d6dbed132650
| 133
|
py
|
Python
|
store/context_processor.py
|
kenkennie/Ecommerce-website-with-django
|
50a4a0f3e6f8b57773df0599c0578988cbb3f342
|
[
"MIT"
] | 2
|
2021-08-11T09:38:45.000Z
|
2022-02-24T19:26:18.000Z
|
store/context_processor.py
|
kenkennie/Ecommerce-website-with-django
|
50a4a0f3e6f8b57773df0599c0578988cbb3f342
|
[
"MIT"
] | null | null | null |
store/context_processor.py
|
kenkennie/Ecommerce-website-with-django
|
50a4a0f3e6f8b57773df0599c0578988cbb3f342
|
[
"MIT"
] | null | null | null |
from .models import Category
def categories (request):
return {
'categories':Category.objects.all()
}
| 14.777778
| 43
| 0.586466
| 12
| 133
| 6.5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.315789
| 133
| 9
| 44
| 14.777778
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0.074627
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.2
| 0.2
| 0.6
| 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
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
322e8564e8c7304a604e72dfb2c085834b7e6ba1
| 3,030
|
py
|
Python
|
core/REST_permissions.py
|
gcnoopy/YaraGuardian
|
aa5f7ea1bada193ef1f2355b0446dfc78aa9d0f7
|
[
"Apache-2.0"
] | 178
|
2017-07-31T08:29:04.000Z
|
2022-03-29T08:03:05.000Z
|
core/REST_permissions.py
|
fr0gger/YaraGuardian
|
56c7339f816114ee0c350fa08afd4f6742c9b7b7
|
[
"Apache-2.0"
] | 31
|
2017-08-02T19:19:02.000Z
|
2019-10-11T17:56:39.000Z
|
core/REST_permissions.py
|
fr0gger/YaraGuardian
|
56c7339f816114ee0c350fa08afd4f6742c9b7b7
|
[
"Apache-2.0"
] | 51
|
2017-07-28T22:31:51.000Z
|
2021-07-28T09:06:49.000Z
|
from rest_framework import permissions
from rest_framework.permissions import BasePermission
from django.core.exceptions import ObjectDoesNotExist
from django.contrib.auth.models import Group
def group_owner(request):
group_name = request.resolver_match.kwargs.get('group_name')
try:
group = Group.objects.get(name=group_name)
except ObjectDoesNotExist:
pass
else:
if request.user == group.groupmeta.owner:
return True
return False
def group_admin(request):
group_name = request.resolver_match.kwargs.get('group_name')
try:
group = Group.objects.get(name=group_name)
except ObjectDoesNotExist:
pass
else:
if request.user == group.groupmeta.owner:
return True
elif request.user in group.groupmeta.admins.all():
return True
return False
def group_member(request):
group_name = request.resolver_match.kwargs.get('group_name')
if request.user.groups.filter(name=group_name).exists():
return True
return False
class IsGroupMember(BasePermission):
def has_permission(self, request, view):
return group_member(request)
class IsGroupMemberOrPublicReadOnly(BasePermission):
def has_permission(self, request, view):
if group_member(request):
return True
elif request.method in permissions.SAFE_METHODS:
return True
return False
class IsGroupAdmin(BasePermission):
def has_permission(self, request, view):
if group_member(request) and group_admin(request):
return True
return False
class IsGroupAdminOrMemberReadOnly(BasePermission):
def has_permission(self, request, view):
if group_member(request):
if group_admin(request):
return True
elif request.method in permissions.SAFE_METHODS:
return True
return False
class IsGroupAdminOrMemberAddMethod(BasePermission):
def has_permission(self, request, view):
if group_member(request):
if group_admin(request):
return True
elif request.method == 'POST':
return True
return False
class IsGroupOwner(BasePermission):
def has_permission(self, request, view):
if group_member(request) and group_owner(request):
return True
return False
class IsGroupOwnerOrMemberReadOnly(BasePermission):
def has_permission(self, request, view):
if group_member(request):
if group_owner(request):
return True
elif request.method in permissions.SAFE_METHODS:
return True
return False
class IsGroupOwnerOrPublicReadOnly(BasePermission):
def has_permission(self, request, view):
if group_member(request) and group_owner(request):
return True
elif request.method in permissions.SAFE_METHODS:
return True
return False
| 24.047619
| 64
| 0.664026
| 328
| 3,030
| 6.003049
| 0.182927
| 0.08126
| 0.08126
| 0.106653
| 0.752158
| 0.72321
| 0.673946
| 0.651092
| 0.651092
| 0.651092
| 0
| 0
| 0.267987
| 3,030
| 125
| 65
| 24.24
| 0.887737
| 0
| 0
| 0.743902
| 0
| 0
| 0.011221
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.134146
| false
| 0.02439
| 0.04878
| 0.012195
| 0.609756
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
3230c385bedbf8860ccc53f0828d397d96aec236
| 120
|
py
|
Python
|
scratch.py
|
GavinGuan95/Generative-VQA
|
0912e3a2426809ef4d4eb40bae667b31c2269161
|
[
"MIT"
] | 1
|
2021-06-08T02:55:16.000Z
|
2021-06-08T02:55:16.000Z
|
scratch.py
|
puzzlecollector/Generative-VQA
|
0912e3a2426809ef4d4eb40bae667b31c2269161
|
[
"MIT"
] | 1
|
2021-06-21T04:05:26.000Z
|
2021-06-21T04:05:26.000Z
|
scratch.py
|
puzzlecollector/Generative-VQA
|
0912e3a2426809ef4d4eb40bae667b31c2269161
|
[
"MIT"
] | 1
|
2021-06-08T02:31:59.000Z
|
2021-06-08T02:31:59.000Z
|
import pickle
temp = pickle.load(open("./cache/vqa2_nonimdb_boxes10-100ada_train2014visualprecomp.pkl", 'rb'))
print(1)
| 30
| 96
| 0.791667
| 16
| 120
| 5.75
| 0.9375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.097345
| 0.058333
| 120
| 4
| 97
| 30
| 0.716814
| 0
| 0
| 0
| 0
| 0
| 0.528926
| 0.512397
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0.333333
| 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
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
32676b7bc654a3bac37c896c1ed209aa1f5839e4
| 87
|
py
|
Python
|
myexam/apps.py
|
PrinceSingh-123/solutiontube-2020
|
01b756a7e1cf78d112c58a7ac52906255bcb252c
|
[
"MIT"
] | null | null | null |
myexam/apps.py
|
PrinceSingh-123/solutiontube-2020
|
01b756a7e1cf78d112c58a7ac52906255bcb252c
|
[
"MIT"
] | 9
|
2019-10-21T18:46:11.000Z
|
2022-03-11T23:43:59.000Z
|
ExamModule/myexam/apps.py
|
neopentane/exam-module
|
95d8bc33836afcb760b777dc9a945fde4ed2749e
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class MyexamConfig(AppConfig):
name = 'myexam'
| 14.5
| 33
| 0.747126
| 10
| 87
| 6.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.172414
| 87
| 5
| 34
| 17.4
| 0.902778
| 0
| 0
| 0
| 0
| 0
| 0.068966
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
32ac40ebe6847594191c1af3b78d1e219142432b
| 763
|
py
|
Python
|
sciengdox/tests/test_constants.py
|
gbingersoll/sciengdox
|
01d953e0b0cfdf1022c2b06ca1e7f83801edd39b
|
[
"MIT"
] | 5
|
2020-12-09T09:04:35.000Z
|
2022-01-17T10:44:30.000Z
|
sciengdox/tests/test_constants.py
|
gbingersoll/sciengdox
|
01d953e0b0cfdf1022c2b06ca1e7f83801edd39b
|
[
"MIT"
] | 13
|
2020-05-27T22:45:13.000Z
|
2022-03-01T21:45:31.000Z
|
sciengdox/tests/test_constants.py
|
gbingersoll/sciengdox
|
01d953e0b0cfdf1022c2b06ca1e7f83801edd39b
|
[
"MIT"
] | null | null | null |
from pytest import approx
from sciengdox.units import ureg
import sciengdox.constants as constants
def test_c0_has_correct_units_and_value():
assert constants.c0.m == approx(299792458)
assert constants.c0.u == ureg.parse_units('m / s')
def test_planck_constant_has_correct_units_and_value():
assert constants.h.m == approx(6.62607004e-34, abs=1e-40)
assert constants.h.u == ureg.parse_units('m^2 kg / s')
def test_proton_mass_has_correct_units_and_value():
assert constants.proton_mass.m == approx(1.6726219e-27, abs=1e-34)
assert constants.proton_mass.u == ureg.parse_units('kg')
def test_g_has_correct_units_and_value():
assert constants.g.m == approx(9.80665, abs=1e-6)
assert constants.g.u == ureg.parse_units('m/s^2')
| 31.791667
| 70
| 0.747051
| 126
| 763
| 4.269841
| 0.325397
| 0.223048
| 0.111524
| 0.133829
| 0.375465
| 0.345725
| 0.282528
| 0
| 0
| 0
| 0
| 0.073906
| 0.131062
| 763
| 23
| 71
| 33.173913
| 0.737557
| 0
| 0
| 0
| 0
| 0
| 0.028834
| 0
| 0
| 0
| 0
| 0
| 0.533333
| 1
| 0.266667
| true
| 0
| 0.2
| 0
| 0.466667
| 0
| 0
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
32c5af759d39a1d7bbf22c5fb2f80da126d716c9
| 92
|
py
|
Python
|
Dicts.py
|
maiconloure/Learning_Python
|
2999508909ace5f8ca0708cdea93b82abaaeafb2
|
[
"MIT"
] | null | null | null |
Dicts.py
|
maiconloure/Learning_Python
|
2999508909ace5f8ca0708cdea93b82abaaeafb2
|
[
"MIT"
] | null | null | null |
Dicts.py
|
maiconloure/Learning_Python
|
2999508909ace5f8ca0708cdea93b82abaaeafb2
|
[
"MIT"
] | null | null | null |
# How to merge two dicts
x = {'a': 1, 'b': 2}
y = {'c': 3, 'd': 4}
z = {**x, **y}
print(z)
| 13.142857
| 24
| 0.402174
| 20
| 92
| 1.85
| 0.85
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 0.26087
| 92
| 7
| 25
| 13.142857
| 0.485294
| 0.23913
| 0
| 0
| 0
| 0
| 0.057971
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
086357cb68b6e0a417fa1261145bfbf209f1cb7b
| 565
|
py
|
Python
|
TrekBot2_WS/build/nav_core/catkin_generated/pkg.develspace.context.pc.py
|
Rafcin/RescueRoboticsLHMV
|
d3dc63e6c16a040b16170f143556ef358018b7da
|
[
"Unlicense"
] | 1
|
2018-10-04T14:37:00.000Z
|
2018-10-04T14:37:00.000Z
|
TrekBot2_WS/build/nav_core/catkin_generated/pkg.develspace.context.pc.py
|
Rafcin/TrekBot
|
d3dc63e6c16a040b16170f143556ef358018b7da
|
[
"Unlicense"
] | null | null | null |
TrekBot2_WS/build/nav_core/catkin_generated/pkg.develspace.context.pc.py
|
Rafcin/TrekBot
|
d3dc63e6c16a040b16170f143556ef358018b7da
|
[
"Unlicense"
] | null | null | null |
# generated from catkin/cmake/template/pkg.context.pc.in
CATKIN_PACKAGE_PREFIX = ""
PROJECT_PKG_CONFIG_INCLUDE_DIRS = "/xavier_ssd/TrekBot/TrekBot2_WS/src/navigation/nav_core/include".split(';') if "/xavier_ssd/TrekBot/TrekBot2_WS/src/navigation/nav_core/include" != "" else []
PROJECT_CATKIN_DEPENDS = "std_msgs;geometry_msgs;tf2_ros;costmap_2d".replace(';', ' ')
PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else []
PROJECT_NAME = "nav_core"
PROJECT_SPACE_DIR = "/xavier_ssd/TrekBot/TrekBot2_WS/devel/.private/nav_core"
PROJECT_VERSION = "1.16.2"
| 62.777778
| 193
| 0.769912
| 81
| 565
| 5
| 0.580247
| 0.069136
| 0.118519
| 0.177778
| 0.325926
| 0.261728
| 0.261728
| 0.261728
| 0.261728
| 0.261728
| 0
| 0.01711
| 0.069027
| 565
| 8
| 194
| 70.625
| 0.752852
| 0.095575
| 0
| 0
| 1
| 0
| 0.471513
| 0.436149
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
087ccac95a49ff68a0ddd7937b0a72a129bd15cf
| 23
|
py
|
Python
|
piccolo/__init__.py
|
ariebovenberg/piccolo
|
2d70ba95e661e92bf1b1ea0335d1636da32cd544
|
[
"MIT"
] | null | null | null |
piccolo/__init__.py
|
ariebovenberg/piccolo
|
2d70ba95e661e92bf1b1ea0335d1636da32cd544
|
[
"MIT"
] | null | null | null |
piccolo/__init__.py
|
ariebovenberg/piccolo
|
2d70ba95e661e92bf1b1ea0335d1636da32cd544
|
[
"MIT"
] | null | null | null |
__VERSION__ = "0.69.1"
| 11.5
| 22
| 0.652174
| 4
| 23
| 2.75
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 0.130435
| 23
| 1
| 23
| 23
| 0.35
| 0
| 0
| 0
| 0
| 0
| 0.26087
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
08800f7b74f9c390b68177d5376ed1c65d995082
| 33
|
py
|
Python
|
zhaquirks/aurora/__init__.py
|
WolfRevo/zha-device-handlers
|
0fa4ca1c03c611be0cf2c38c4fec2a197e3dd1d3
|
[
"Apache-2.0"
] | 213
|
2020-04-16T10:48:31.000Z
|
2022-03-30T20:48:07.000Z
|
zhaquirks/aurora/__init__.py
|
WolfRevo/zha-device-handlers
|
0fa4ca1c03c611be0cf2c38c4fec2a197e3dd1d3
|
[
"Apache-2.0"
] | 1,088
|
2020-04-03T13:23:29.000Z
|
2022-03-31T23:55:03.000Z
|
zhaquirks/aurora/__init__.py
|
WolfRevo/zha-device-handlers
|
0fa4ca1c03c611be0cf2c38c4fec2a197e3dd1d3
|
[
"Apache-2.0"
] | 280
|
2020-04-24T08:44:27.000Z
|
2022-03-31T12:58:04.000Z
|
"""Module for Aurora devices."""
| 16.5
| 32
| 0.666667
| 4
| 33
| 5.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.121212
| 33
| 1
| 33
| 33
| 0.758621
| 0.787879
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
088ff8d45a2c1c33e46f3b92885928d389cc0ba7
| 345
|
py
|
Python
|
integration_tests/tc/test_river_list.py
|
aiqa/geo-docker-django
|
87dbb841ce79d43222b7a03f708b142dc4de36de
|
[
"MIT"
] | 1
|
2020-08-26T17:59:26.000Z
|
2020-08-26T17:59:26.000Z
|
integration_tests/tc/test_river_list.py
|
aiqa/geo-docker-django
|
87dbb841ce79d43222b7a03f708b142dc4de36de
|
[
"MIT"
] | 12
|
2020-06-06T00:56:38.000Z
|
2022-02-19T00:17:10.000Z
|
integration_tests/tc/test_river_list.py
|
aiqa/geo-docker-django
|
87dbb841ce79d43222b7a03f708b142dc4de36de
|
[
"MIT"
] | 1
|
2022-03-16T14:00:24.000Z
|
2022-03-16T14:00:24.000Z
|
import pytest
import requests
from .. import endpoints
class TestRiverList:
"""Test for River"""
def test_river_list(self, sample_river):
"""River List"""
river_list_response = requests.get(endpoints.river_list)
assert river_list_response.status_code == 200
assert len(river_list_response.json()) > 0
| 23
| 64
| 0.692754
| 43
| 345
| 5.302326
| 0.534884
| 0.236842
| 0.223684
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.014706
| 0.211594
| 345
| 14
| 65
| 24.642857
| 0.823529
| 0.072464
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0.125
| false
| 0
| 0.375
| 0
| 0.625
| 0
| 0
| 0
| 0
| null | 1
| 1
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| 0
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| 0
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| 0
| 0
| 0
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| 0
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| 0
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| null | 0
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| 0
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| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
08ba03bf3e02042ad3ef2287ac77e4faaf990212
| 20
|
py
|
Python
|
datasketch/version.py
|
tallamjr/datasketch
|
7229f48cdaa0f49d36f5904d447bdbd11a6b65a5
|
[
"MIT"
] | null | null | null |
datasketch/version.py
|
tallamjr/datasketch
|
7229f48cdaa0f49d36f5904d447bdbd11a6b65a5
|
[
"MIT"
] | null | null | null |
datasketch/version.py
|
tallamjr/datasketch
|
7229f48cdaa0f49d36f5904d447bdbd11a6b65a5
|
[
"MIT"
] | null | null | null |
__version__="1.5.4"
| 10
| 19
| 0.7
| 4
| 20
| 2.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 0.05
| 20
| 1
| 20
| 20
| 0.368421
| 0
| 0
| 0
| 0
| 0
| 0.25
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
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| 1
| 1
| 0
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| 0
| 0
| 0
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| 0
| 0
| 0
| 1
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| 1
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
08bffa915740793c608db2d739bc213b812187d2
| 1,199
|
py
|
Python
|
docbook/core/migrations/0002_auto_20211113_1310.py
|
dhruvs19/docbook
|
cacff9e014c88fe7f1cee197dac53ec78ee4342e
|
[
"MIT"
] | null | null | null |
docbook/core/migrations/0002_auto_20211113_1310.py
|
dhruvs19/docbook
|
cacff9e014c88fe7f1cee197dac53ec78ee4342e
|
[
"MIT"
] | null | null | null |
docbook/core/migrations/0002_auto_20211113_1310.py
|
dhruvs19/docbook
|
cacff9e014c88fe7f1cee197dac53ec78ee4342e
|
[
"MIT"
] | null | null | null |
# Generated by Django 3.1.4 on 2021-11-13 07:40
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('core', '0001_initial'),
]
operations = [
migrations.RemoveField(
model_name='docprofile',
name='address2',
),
migrations.RemoveField(
model_name='docprofile',
name='blood_type',
),
migrations.RemoveField(
model_name='docprofile',
name='city',
),
migrations.RemoveField(
model_name='docprofile',
name='clinical_employment',
),
migrations.RemoveField(
model_name='docprofile',
name='height',
),
migrations.RemoveField(
model_name='docprofile',
name='photo_id',
),
migrations.RemoveField(
model_name='docprofile',
name='right_to_sell',
),
migrations.RemoveField(
model_name='docprofile',
name='state',
),
migrations.RemoveField(
model_name='docprofile',
name='weight',
),
]
| 23.98
| 47
| 0.514595
| 94
| 1,199
| 6.404255
| 0.43617
| 0.313953
| 0.388704
| 0.448505
| 0.657807
| 0.657807
| 0
| 0
| 0
| 0
| 0
| 0.026667
| 0.374479
| 1,199
| 49
| 48
| 24.469388
| 0.776
| 0.037531
| 0
| 0.627907
| 1
| 0
| 0.16059
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.023256
| 0
| 0.093023
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3e9f8aa76094e2591b6fc186634688d9d85b6627
| 181
|
py
|
Python
|
src/garage/torch/value_functions/__init__.py
|
bainro/garage
|
c5afbb19524792d9bbad9b9741f45e1d48ddca3d
|
[
"MIT"
] | null | null | null |
src/garage/torch/value_functions/__init__.py
|
bainro/garage
|
c5afbb19524792d9bbad9b9741f45e1d48ddca3d
|
[
"MIT"
] | null | null | null |
src/garage/torch/value_functions/__init__.py
|
bainro/garage
|
c5afbb19524792d9bbad9b9741f45e1d48ddca3d
|
[
"MIT"
] | null | null | null |
"""Value functions which use PyTorch."""
from garage.torch.value_functions.gaussian_mlp_value_function import \
GaussianMLPValueFunction
__all__ = ['GaussianMLPValueFunction']
| 30.166667
| 70
| 0.812155
| 18
| 181
| 7.722222
| 0.777778
| 0.201439
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.099448
| 181
| 5
| 71
| 36.2
| 0.852761
| 0.187845
| 0
| 0
| 0
| 0
| 0.170213
| 0.170213
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 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
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
3ebdd68d685ff8c2dce951e730f76155081c3d2b
| 2,285
|
py
|
Python
|
mainApp/migrations/0006_auto_20200815_1617.py
|
asanka9/youtubeAdmin
|
3848027dfd5cf6493eeab9c50a9be9e2fb634b28
|
[
"Apache-2.0"
] | null | null | null |
mainApp/migrations/0006_auto_20200815_1617.py
|
asanka9/youtubeAdmin
|
3848027dfd5cf6493eeab9c50a9be9e2fb634b28
|
[
"Apache-2.0"
] | null | null | null |
mainApp/migrations/0006_auto_20200815_1617.py
|
asanka9/youtubeAdmin
|
3848027dfd5cf6493eeab9c50a9be9e2fb634b28
|
[
"Apache-2.0"
] | null | null | null |
# Generated by Django 3.0.5 on 2020-08-15 10:47
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('mainApp', '0005_auto_20200815_1522'),
]
operations = [
migrations.CreateModel(
name='Completed',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('project_name', models.CharField(max_length=128)),
('lesson_name', models.CharField(max_length=128)),
('sublesson_name', models.CharField(max_length=128)),
],
),
migrations.AlterField(
model_name='lessons',
name='name',
field=models.CharField(max_length=128),
),
migrations.AlterField(
model_name='lessons',
name='project_name',
field=models.CharField(max_length=128),
),
migrations.AlterField(
model_name='projects',
name='name',
field=models.CharField(max_length=128, unique=True),
),
migrations.AlterField(
model_name='sublessons',
name='lesson_name',
field=models.CharField(max_length=128),
),
migrations.AlterField(
model_name='sublessons',
name='name',
field=models.CharField(max_length=256),
),
migrations.AlterField(
model_name='sublessons',
name='project_name',
field=models.CharField(max_length=128),
),
migrations.AlterField(
model_name='videolessons',
name='chanel',
field=models.CharField(max_length=128),
),
migrations.AlterField(
model_name='videolessons',
name='lesson_name',
field=models.CharField(max_length=128),
),
migrations.AlterField(
model_name='videolessons',
name='project_name',
field=models.CharField(max_length=128),
),
migrations.AlterField(
model_name='videolessons',
name='sublesson_name',
field=models.CharField(max_length=128),
),
]
| 31.30137
| 114
| 0.551422
| 207
| 2,285
| 5.903382
| 0.270531
| 0.159574
| 0.191489
| 0.255319
| 0.737316
| 0.737316
| 0.611293
| 0.551555
| 0.518822
| 0.518822
| 0
| 0.045812
| 0.331291
| 2,285
| 72
| 115
| 31.736111
| 0.753927
| 0.019694
| 0
| 0.69697
| 1
| 0
| 0.120643
| 0.010277
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.015152
| 0
| 0.060606
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3ec4a912c7729c2243be4a0e5d3716283dad99a6
| 58
|
py
|
Python
|
src/video_effect_star_war_like.py
|
GoyalYatin/Youtube-Downloader
|
1bcd129361998bbf7bac5131c63d81f7a70ad682
|
[
"MIT"
] | null | null | null |
src/video_effect_star_war_like.py
|
GoyalYatin/Youtube-Downloader
|
1bcd129361998bbf7bac5131c63d81f7a70ad682
|
[
"MIT"
] | null | null | null |
src/video_effect_star_war_like.py
|
GoyalYatin/Youtube-Downloader
|
1bcd129361998bbf7bac5131c63d81f7a70ad682
|
[
"MIT"
] | null | null | null |
# https://zulko.github.io/moviepy/examples/star_worms.html
| 58
| 58
| 0.810345
| 9
| 58
| 5.111111
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0.017241
| 58
| 1
| 58
| 58
| 0.807018
| 0.965517
| 0
| null | 0
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| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
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| null | 0
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| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3ec71580f1cff18e705ed0b95ba3ab6fe741ed01
| 80
|
py
|
Python
|
creds.py
|
bit-git/psirt_checker
|
9c7f669152362d46c2df4058121c61f24e3ea77d
|
[
"MIT"
] | null | null | null |
creds.py
|
bit-git/psirt_checker
|
9c7f669152362d46c2df4058121c61f24e3ea77d
|
[
"MIT"
] | null | null | null |
creds.py
|
bit-git/psirt_checker
|
9c7f669152362d46c2df4058121c61f24e3ea77d
|
[
"MIT"
] | null | null | null |
CLIENT_ID = "mxxgwertsps7ry9zsdkk7r3"
CLIENT_SECRET = "adqB3jegsvbYbJfcx27As5au"
| 40
| 42
| 0.8625
| 6
| 80
| 11.166667
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106667
| 0.0625
| 80
| 2
| 42
| 40
| 0.786667
| 0
| 0
| 0
| 0
| 0
| 0.580247
| 0.580247
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
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| 0
| 0
| 0
| 1
| 0
| 1
| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3ec8a28d78821fd2a97260247922b30635b1173e
| 141
|
py
|
Python
|
15/lattice_paths.py
|
redfast00/euler
|
98fc49a1fcb8b49415cc4384952a6447378bd4f4
|
[
"MIT"
] | null | null | null |
15/lattice_paths.py
|
redfast00/euler
|
98fc49a1fcb8b49415cc4384952a6447378bd4f4
|
[
"MIT"
] | null | null | null |
15/lattice_paths.py
|
redfast00/euler
|
98fc49a1fcb8b49415cc4384952a6447378bd4f4
|
[
"MIT"
] | null | null | null |
from math import factorial
def choose(n, k):
return factorial(n)//(factorial(n-k)*factorial(k))
size = 20
print(choose(2*size, size))
| 15.666667
| 54
| 0.687943
| 23
| 141
| 4.217391
| 0.565217
| 0.041237
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025
| 0.148936
| 141
| 8
| 55
| 17.625
| 0.783333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.2
| 0.2
| 0.6
| 0.2
| 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
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
3ed7da49212e06607df687659fce7027f1882382
| 53
|
py
|
Python
|
run.py
|
ChittiVersion/Lichess-bot
|
69dff24138f38b55b433bd6aed54cf64b7e1edc3
|
[
"BSD-3-Clause"
] | null | null | null |
run.py
|
ChittiVersion/Lichess-bot
|
69dff24138f38b55b433bd6aed54cf64b7e1edc3
|
[
"BSD-3-Clause"
] | null | null | null |
run.py
|
ChittiVersion/Lichess-bot
|
69dff24138f38b55b433bd6aed54cf64b7e1edc3
|
[
"BSD-3-Clause"
] | null | null | null |
import os
os.system("python3 lichess-bot.py -u")
| 13.25
| 39
| 0.679245
| 9
| 53
| 4
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.022727
| 0.169811
| 53
| 3
| 40
| 17.666667
| 0.795455
| 0
| 0
| 0
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
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| 1
| 0
| 0
| null | 0
| 0
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| 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
| 4
|
41090218e9c998aefadc550da81ecb54c7e53fe5
| 176
|
py
|
Python
|
mayan/apps/authentication/utils.py
|
bonitobonita24/Mayan-EDMS
|
7845fe0e1e83c81f5d227a16116397a3d3883b85
|
[
"Apache-2.0"
] | 343
|
2015-01-05T14:19:35.000Z
|
2018-12-10T19:07:48.000Z
|
mayan/apps/authentication/utils.py
|
bonitobonita24/Mayan-EDMS
|
7845fe0e1e83c81f5d227a16116397a3d3883b85
|
[
"Apache-2.0"
] | 191
|
2015-01-03T00:48:19.000Z
|
2018-11-30T09:10:25.000Z
|
mayan/apps/authentication/utils.py
|
bonitobonita24/Mayan-EDMS
|
7845fe0e1e83c81f5d227a16116397a3d3883b85
|
[
"Apache-2.0"
] | 114
|
2015-01-08T20:21:05.000Z
|
2018-12-10T19:07:53.000Z
|
def get_context_user(context):
if 'user' in context:
return context['user']
elif 'request' in context:
return getattr(context['request'], 'user', None)
| 29.333333
| 56
| 0.642045
| 22
| 176
| 5.045455
| 0.5
| 0.198198
| 0.27027
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.227273
| 176
| 5
| 57
| 35.2
| 0.816176
| 0
| 0
| 0
| 0
| 0
| 0.147727
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 0
| 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
| 0
| 0
| 1
| 0
|
0
| 4
|
411d9c7a24403f91eefc625d1a586be7613d8e94
| 21
|
py
|
Python
|
tmonitor/notify/__init__.py
|
cahorn/tmonitor
|
696425b602887cc99fcb0e15b17ef8d16d2e1cd3
|
[
"WTFPL"
] | null | null | null |
tmonitor/notify/__init__.py
|
cahorn/tmonitor
|
696425b602887cc99fcb0e15b17ef8d16d2e1cd3
|
[
"WTFPL"
] | null | null | null |
tmonitor/notify/__init__.py
|
cahorn/tmonitor
|
696425b602887cc99fcb0e15b17ef8d16d2e1cd3
|
[
"WTFPL"
] | null | null | null |
__all__ = ['email']
| 7
| 19
| 0.571429
| 2
| 21
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.190476
| 21
| 2
| 20
| 10.5
| 0.470588
| 0
| 0
| 0
| 0
| 0
| 0.25
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
412cfd39f31c9dfd7643eb2429700dfd829ce3de
| 27
|
py
|
Python
|
packages/tar.py
|
bratsche/bockbuild
|
04d583550aa8e067f84dcc081be61fd1a78d71e3
|
[
"MIT"
] | null | null | null |
packages/tar.py
|
bratsche/bockbuild
|
04d583550aa8e067f84dcc081be61fd1a78d71e3
|
[
"MIT"
] | null | null | null |
packages/tar.py
|
bratsche/bockbuild
|
04d583550aa8e067f84dcc081be61fd1a78d71e3
|
[
"MIT"
] | null | null | null |
GnuPackage ('tar', '1.26')
| 13.5
| 26
| 0.592593
| 4
| 27
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 0.111111
| 27
| 1
| 27
| 27
| 0.541667
| 0
| 0
| 0
| 0
| 0
| 0.259259
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 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
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
f5b459e458902454e37a122367a6b4b69712c8f5
| 127
|
py
|
Python
|
atividades/ex010.py
|
leonardoarthur/PythonAtividades
|
9bb2b6e1d7788d99276730de5f199cb0e9ab782f
|
[
"MIT"
] | 1
|
2021-05-02T09:03:27.000Z
|
2021-05-02T09:03:27.000Z
|
atividades/ex010.py
|
leonardoarthur/PythonAtividades
|
9bb2b6e1d7788d99276730de5f199cb0e9ab782f
|
[
"MIT"
] | null | null | null |
atividades/ex010.py
|
leonardoarthur/PythonAtividades
|
9bb2b6e1d7788d99276730de5f199cb0e9ab782f
|
[
"MIT"
] | null | null | null |
r = float(input('Seja bem vindo, quanto dinheiro(em reais) você tem?'))
print('Seu saldo em dólares é: {:.2f}'.format(r/5.57))
| 42.333333
| 71
| 0.677165
| 23
| 127
| 3.73913
| 0.913043
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.036036
| 0.125984
| 127
| 2
| 72
| 63.5
| 0.738739
| 0
| 0
| 0
| 0
| 0
| 0.637795
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
f5bf8f189fd0c6e80e7928561cd3e637a38903e5
| 440
|
py
|
Python
|
versions.py
|
yoavram/mamba
|
c0fae9cc05d0fda493c144186bebfa518bcec9cd
|
[
"MIT"
] | 1
|
2018-09-20T20:27:30.000Z
|
2018-09-20T20:27:30.000Z
|
versions.py
|
yoavram/mamba
|
c0fae9cc05d0fda493c144186bebfa518bcec9cd
|
[
"MIT"
] | null | null | null |
versions.py
|
yoavram/mamba
|
c0fae9cc05d0fda493c144186bebfa518bcec9cd
|
[
"MIT"
] | null | null | null |
def print_underscore_version(module):
print module.__name__, module.__version__
def print_double_version(module):
print module.__name__, module.version.version
import os
import logging
import json
import numpy
import pandas
import scipy
import cython
print_underscore_version(logging)
print_underscore_version(json)
print_double_version(scipy)
print_double_version(pandas)
print_double_version(numpy)
a = os.system("cython --version")
| 22
| 46
| 0.843182
| 60
| 440
| 5.75
| 0.283333
| 0.127536
| 0.208696
| 0.13913
| 0.237681
| 0.237681
| 0.237681
| 0
| 0
| 0
| 0
| 0
| 0.086364
| 440
| 20
| 47
| 22
| 0.858209
| 0
| 0
| 0
| 0
| 0
| 0.036281
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.411765
| null | null | 0.529412
| 0
| 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
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 1
|
0
| 4
|
f5c4b606808d4ddfdd3998b4bf9d561172774caf
| 6,767
|
py
|
Python
|
config/config.py
|
guopeiming/NNTranSegmentor
|
4496932bfb93f64de0d0c07236c1dd523e6577c3
|
[
"Apache-2.0"
] | null | null | null |
config/config.py
|
guopeiming/NNTranSegmentor
|
4496932bfb93f64de0d0c07236c1dd523e6577c3
|
[
"Apache-2.0"
] | null | null | null |
config/config.py
|
guopeiming/NNTranSegmentor
|
4496932bfb93f64de0d0c07236c1dd523e6577c3
|
[
"Apache-2.0"
] | null | null | null |
# @Author : guopeiming
# @Contact : guopeiming2016@{qq, gmail, 163}.com
from config import Constants
from configparser import ConfigParser
class MyConf(ConfigParser):
"""
MyConf
"""
def __init__(self, config_file, *args, **kwargs):
super(MyConf, self).__init__(*args, **kwargs)
self.read(filenames=config_file, encoding='utf-8')
def __str__(self):
res = ""
for sect in self.sections():
res = res + '[' + sect + ']\n'
for k, v in self.items(sect):
res = res + k + ' : ' + v + '\n'
res += '\n'
return res
@property
def char_min_fre(self):
return self.getint('Preprocess', 'char_min_fre')
@property
def word_min_fre(self):
return self.getint('Preprocess', 'word_min_fre')
@property
def bichar_min_fre(self):
return self.getint('Preprocess', 'bichar_min_fre')
@property
def data_path(self):
return self.get('Data', 'data_path')
@property
def dict_data_path(self):
return self.get('Data', 'dict_data_path')
@property
def logits_path(self):
return self.get('Data', 'logits_path')
@property
def cache_3gram_path(self):
return self.get('Data', 'cache_3gram_path')
@property
def pretrained_embed_char(self):
return self.getboolean('Embed', 'pretrained_embed_char')
@property
def pretrained_embed_bichar(self):
return self.getboolean('Embed', 'pretrained_embed_bichar')
@property
def char_gen_oov_uniform(self):
return self.getfloat('Embed', 'char_gen_oov_uniform')
@property
def bichar_gen_oov_uniform(self):
return self.getfloat('Embed', 'bichar_gen_oov_uniform')
@property
def pretrained_char_embed_file(self):
return self.get('Embed', 'pretrained_char_embed_file')
@property
def pretrained_bichar_embed_file(self):
return self.get('Embed', 'pretrained_bichar_embed_file')
@property
def char_gen_oov_mode(self):
return self.get('Embed', 'char_gen_oov_mode')
@property
def bichar_gen_oov_mode(self):
return self.get('Embed', 'bichar_gen_oov_mode')
@property
def seed(self):
return self.getint('Train', 'seed')
@property
def use_cuda(self):
return self.getboolean('Train', 'use_cuda')
@property
def cuda_id(self):
return self.getint('Train', 'cuda_id')
@property
def distillLambda(self):
return self.getfloat('Train', 'distillLambda')
@property
def batch_size(self):
return self.getint('Train', 'batch_size')
@property
def shuffle(self):
return self.getboolean('Train', 'shuffle')
@property
def num_workers(self):
return self.getint('Train', 'num_workers')
@property
def drop_last(self):
return self.getboolean('Train', 'drop_last')
@property
def epoch(self):
return self.getint('Train', 'epoch')
@property
def accumulation_steps(self):
return self.getint('Train', 'accumulation_steps')
@property
def logInterval(self):
return self.getint('Train', 'logInterval')
@property
def valInterval(self):
return self.getint('Train', 'valInterval')
@property
def visuParaInterval(self):
return self.getint('Train', 'visuParaInterval')
@property
def saveInterval(self):
return self.getint('Train', 'saveInterval')
@property
def save_path(self):
return self.get('Train', 'save_path')
@property
def visual_logger_path(self):
return self.get('Train', 'visual_logger_path')
@property
def is_stack(self):
return self.getboolean('Model', 'is_stack')
@property
def char_embed_dim(self):
return self.getint('Model', 'char_embed_dim')
@property
def char_embed_dim_no_static(self):
return self.getint('Model', 'char_embed_dim_no_static')
@property
def bichar_embed_dim(self):
return self.getint('Model', 'bichar_embed_dim')
@property
def bichar_embed_dim_no_static(self):
return self.getint('Model', 'bichar_embed_dim_no_static')
@property
def dropout_embed(self):
return self.getfloat('Model', 'dropout_embed')
@property
def char_embed_max_norm(self):
num = self.getfloat('Model', 'char_embed_max_norm')
assert num >= 0., 'Char_max_norm must greater than 0.0'
return None if abs(num - 0.) < Constants.EPSILON else num
@property
def bichar_embed_max_norm(self):
num = self.getfloat('Model', 'bichar_embed_max_norm')
assert num >= 0., 'Word_max_norm must greater than 0.0'
return None if abs(num - 0.) < Constants.EPSILON else num
@property
def encoder_embed_dim(self):
return self.getint('Model', 'encoder_embed_dim')
@property
def dropout_encoder_embed(self):
return self.getfloat('Model', 'dropout_encoder_embed')
@property
def encoder_lstm_hid_size(self):
return self.getint('Model', 'encoder_lstm_hid_size')
@property
def dropout_encoder_hid(self):
return self.getfloat('Model', 'dropout_encoder_hid')
@property
def subword_lstm_hid_size(self):
return self.getint('Model', 'subword_lstm_hid_size')
@property
def word_lstm_hid_size(self):
return self.getint('Model', 'word_lstm_hid_size')
@property
def freeze_bert(self):
return self.getboolean('Model', 'freeze_bert')
@property
def freeze_bert_layers(self):
return self.getint('Model', 'freeze_bert_layers')
@property
def opti_name(self):
return self.get('Optimizer', 'name')
@property
def learning_rate(self):
return self.getfloat('Optimizer', 'learning_rate')
@property
def fine_tune_lr(self):
return self.getfloat('Optimizer', 'fine_tune_lr')
@property
def weight_decay(self):
return self.getfloat('Optimizer', 'weight_decay')
@property
def clip_grad(self):
return self.getboolean('Optimizer', 'clip_grad')
@property
def clip_grad_max_norm(self):
return self.getfloat('Optimizer', 'clip_grad_max_norm')
@property
def warmup_steps(self):
return self.getint('Optimizer', 'warmup_steps')
@property
def lr_decay_factor(self):
return self.getfloat('Optimizer', 'lr_decay_factor')
@property
def momentum(self):
return self.getfloat('Optimizer', 'momentum')
@property
def dampening(self):
return self.getfloat('Optimizer', 'dampening')
@property
def nesterov(self):
return self.getboolean('Optimizer', 'nesterov')
| 26.127413
| 66
| 0.64386
| 819
| 6,767
| 5.072039
| 0.155067
| 0.153587
| 0.188734
| 0.110737
| 0.567886
| 0.330043
| 0.282378
| 0.179104
| 0.056813
| 0.037073
| 0
| 0.00348
| 0.235703
| 6,767
| 258
| 67
| 26.228682
| 0.799691
| 0.011083
| 0
| 0.3125
| 0
| 0
| 0.190441
| 0.038058
| 0
| 0
| 0
| 0
| 0.010417
| 1
| 0.3125
| false
| 0
| 0.010417
| 0.291667
| 0.635417
| 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
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
f5c8def9a514f38c73e138fc07a2d2a1eff2793e
| 223
|
py
|
Python
|
api/accounts/urls.py
|
hawzie197/pyllama
|
20e1fd1d6edcbb164f190684fb96fdff00f6a701
|
[
"BSD-3-Clause"
] | 4
|
2019-10-21T04:27:04.000Z
|
2019-11-17T04:08:39.000Z
|
api/accounts/urls.py
|
hawzie197/llama-api
|
20e1fd1d6edcbb164f190684fb96fdff00f6a701
|
[
"BSD-3-Clause"
] | 32
|
2019-10-21T01:44:57.000Z
|
2022-02-18T13:07:50.000Z
|
api/accounts/urls.py
|
hawzie197/llama-api
|
20e1fd1d6edcbb164f190684fb96fdff00f6a701
|
[
"BSD-3-Clause"
] | null | null | null |
from django.urls import path
from api.accounts.views import UserViewSet, GroupViewSet
urlpatterns = [
path("users/", UserViewSet.as_view({"get": "list"})),
path("groups/", GroupViewSet.as_view({"get": "list"})),
]
| 27.875
| 59
| 0.690583
| 27
| 223
| 5.62963
| 0.62963
| 0.078947
| 0.118421
| 0.171053
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125561
| 223
| 7
| 60
| 31.857143
| 0.779487
| 0
| 0
| 0
| 0
| 0
| 0.121076
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 0
| 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
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
f5dbebac24366e4fcdc3233c1713042aad5364fa
| 372
|
py
|
Python
|
test/imported.py
|
jerseyshawn/cf-python-client
|
f59f13b723fb30a2128dd0e0f072d28c0416b054
|
[
"Apache-2.0"
] | null | null | null |
test/imported.py
|
jerseyshawn/cf-python-client
|
f59f13b723fb30a2128dd0e0f072d28c0416b054
|
[
"Apache-2.0"
] | null | null | null |
test/imported.py
|
jerseyshawn/cf-python-client
|
f59f13b723fb30a2128dd0e0f072d28c0416b054
|
[
"Apache-2.0"
] | null | null | null |
import sys
if sys.version_info.major == 2:
from mock import patch, call, MagicMock
from httplib import SEE_OTHER, CREATED, NO_CONTENT
elif sys.version_info.major == 3:
from unittest.mock import patch, call, MagicMock
from http.client import SEE_OTHER, CREATED, NO_CONTENT
else:
raise ImportError('Invalid major version: %d' % sys.version_info.major)
| 31
| 75
| 0.747312
| 55
| 372
| 4.927273
| 0.509091
| 0.110701
| 0.154982
| 0.210332
| 0.457565
| 0.457565
| 0
| 0
| 0
| 0
| 0
| 0.006494
| 0.172043
| 372
| 12
| 75
| 31
| 0.873377
| 0
| 0
| 0
| 0
| 0
| 0.067024
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 1
| 0
|
0
| 4
|
de1e4c0ceeefabf40dbb4720316197784bb5c90a
| 30
|
py
|
Python
|
data/studio21_generated/introductory/3963/starter_code.py
|
vijaykumawat256/Prompt-Summarization
|
614f5911e2acd2933440d909de2b4f86653dc214
|
[
"Apache-2.0"
] | null | null | null |
data/studio21_generated/introductory/3963/starter_code.py
|
vijaykumawat256/Prompt-Summarization
|
614f5911e2acd2933440d909de2b4f86653dc214
|
[
"Apache-2.0"
] | null | null | null |
data/studio21_generated/introductory/3963/starter_code.py
|
vijaykumawat256/Prompt-Summarization
|
614f5911e2acd2933440d909de2b4f86653dc214
|
[
"Apache-2.0"
] | null | null | null |
def amicable_numbers(n1,n2):
| 15
| 28
| 0.766667
| 5
| 30
| 4.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.074074
| 0.1
| 30
| 2
| 29
| 15
| 0.740741
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
de21d16099b68da6aa9ac816708be55e80b3443b
| 153
|
py
|
Python
|
bilangan_ganjil_genap.py
|
ardian-sh/menghitung-2-buah-bilangan-awal-dan-akhir-ganjil-genap
|
56b730428bac56572abda461ef2052414419fdea
|
[
"Unlicense"
] | null | null | null |
bilangan_ganjil_genap.py
|
ardian-sh/menghitung-2-buah-bilangan-awal-dan-akhir-ganjil-genap
|
56b730428bac56572abda461ef2052414419fdea
|
[
"Unlicense"
] | null | null | null |
bilangan_ganjil_genap.py
|
ardian-sh/menghitung-2-buah-bilangan-awal-dan-akhir-ganjil-genap
|
56b730428bac56572abda461ef2052414419fdea
|
[
"Unlicense"
] | null | null | null |
even = int(input("total even number : "))
print(even, "first even number : ",end="")
for i in range(2,even*2,2):
print (i,end=", ")
print(even*2)
| 30.6
| 43
| 0.594771
| 26
| 153
| 3.5
| 0.5
| 0.21978
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.032
| 0.183007
| 153
| 5
| 44
| 30.6
| 0.696
| 0
| 0
| 0
| 0
| 0
| 0.28
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.6
| 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
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
de392080af43c2b219fc46fed9183872a8165b8b
| 94
|
py
|
Python
|
Init.py
|
Athanaze/Battery-Pack-Workbench
|
d3a32281cb6f1d1c7cc8f7e2977fb6cfe77f91a8
|
[
"MIT"
] | 2
|
2021-08-08T01:14:57.000Z
|
2022-03-14T13:14:39.000Z
|
Init.py
|
Athanaze/Battery-Pack-Workbench
|
d3a32281cb6f1d1c7cc8f7e2977fb6cfe77f91a8
|
[
"MIT"
] | 1
|
2021-03-06T16:28:02.000Z
|
2021-03-06T16:50:35.000Z
|
Init.py
|
Athanaze/Battery-Pack-Workbench
|
d3a32281cb6f1d1c7cc8f7e2977fb6cfe77f91a8
|
[
"MIT"
] | null | null | null |
"""FreeCAD init script of the Battery pack module"""
# Not sure what I am supposed to put here
| 47
| 52
| 0.744681
| 17
| 94
| 4.117647
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.180851
| 94
| 2
| 53
| 47
| 0.909091
| 0.925532
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
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| 0
| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
de4876f79a2c41accf5e5f6f50dd3e40f314141d
| 236
|
py
|
Python
|
Codewars/8kyu/switch-slash-case-bug-fixing-number-6/Python/solution1.py
|
RevansChen/online-judge
|
ad1b07fee7bd3c49418becccda904e17505f3018
|
[
"MIT"
] | 7
|
2017-09-20T16:40:39.000Z
|
2021-08-31T18:15:08.000Z
|
Codewars/8kyu/switch-slash-case-bug-fixing-number-6/Python/solution1.py
|
RevansChen/online-judge
|
ad1b07fee7bd3c49418becccda904e17505f3018
|
[
"MIT"
] | null | null | null |
Codewars/8kyu/switch-slash-case-bug-fixing-number-6/Python/solution1.py
|
RevansChen/online-judge
|
ad1b07fee7bd3c49418becccda904e17505f3018
|
[
"MIT"
] | null | null | null |
# Python - 2.7.6
eval_object = lambda v: {
'+': v['a'] + v['b'],
'-': v['a'] - v['b'],
'/': v['a'] / v['b'],
'*': v['a'] * v['b'],
'%': v['a'] % v['b'],
'**': v['a'] ** v['b']
}.get(v['operation'], 0)
| 21.454545
| 27
| 0.275424
| 36
| 236
| 1.777778
| 0.361111
| 0.1875
| 0.28125
| 0.375
| 0.375
| 0.375
| 0.375
| 0.375
| 0.375
| 0.375
| 0
| 0.024096
| 0.29661
| 236
| 10
| 28
| 23.6
| 0.361446
| 0.059322
| 0
| 0
| 0
| 0
| 0.127273
| 0
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| 0
| 0
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| 0
| 1
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| false
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
de635a38e95fdb96849694518e4b00885211166d
| 77
|
py
|
Python
|
triad/constants.py
|
kvnkho/triad
|
371a5e84945b2203f1108598b8e67136414589a3
|
[
"Apache-2.0"
] | 6
|
2020-10-04T23:01:33.000Z
|
2021-11-08T11:46:39.000Z
|
triad/constants.py
|
kvnkho/triad
|
371a5e84945b2203f1108598b8e67136414589a3
|
[
"Apache-2.0"
] | 16
|
2020-09-28T21:58:08.000Z
|
2021-12-29T07:09:03.000Z
|
triad/constants.py
|
kvnkho/triad
|
371a5e84945b2203f1108598b8e67136414589a3
|
[
"Apache-2.0"
] | 1
|
2020-10-10T20:36:43.000Z
|
2020-10-10T20:36:43.000Z
|
FLOAT_NAN = float("nan")
FLOAT_INF = float("inf")
FLOAT_NINF = float("-inf")
| 19.25
| 26
| 0.675325
| 12
| 77
| 4.083333
| 0.333333
| 0.489796
| 0.530612
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116883
| 77
| 3
| 27
| 25.666667
| 0.720588
| 0
| 0
| 0
| 0
| 0
| 0.12987
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
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| 0
| 0
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| 0
| 0
| null | 1
| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
de6edf5ca016fd15d62490a71860f782c37a4699
| 159
|
py
|
Python
|
machine_sleeping/main.py
|
caveljan/machine-sleeping
|
eb51de96d17e94e4810da3be010a0e312a94327c
|
[
"MIT"
] | null | null | null |
machine_sleeping/main.py
|
caveljan/machine-sleeping
|
eb51de96d17e94e4810da3be010a0e312a94327c
|
[
"MIT"
] | null | null | null |
machine_sleeping/main.py
|
caveljan/machine-sleeping
|
eb51de96d17e94e4810da3be010a0e312a94327c
|
[
"MIT"
] | null | null | null |
# varia
class Sleep:
def NREM(self):
print('NREM')
def REM(self):
print('REM')
class Awake:
def act(self):
print('act')
| 12.230769
| 21
| 0.509434
| 20
| 159
| 4.05
| 0.5
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.339623
| 159
| 12
| 22
| 13.25
| 0.771429
| 0.031447
| 0
| 0
| 0
| 0
| 0.065789
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.375
| false
| 0
| 0
| 0
| 0.625
| 0.375
| 1
| 0
| 0
| null | 1
| 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
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
de8a6f6effa70c964bad6aeb4ff32a8ea67fa1cb
| 60
|
py
|
Python
|
mocks/lms/djangoapps/teams/__init__.py
|
ibm-skills-network/tahoe-lti
|
53308c947632a63fc343e176b177145ccfaeba8b
|
[
"MIT"
] | 4
|
2019-05-02T13:31:44.000Z
|
2021-03-12T23:02:47.000Z
|
mocks/lms/djangoapps/teams/__init__.py
|
ibm-skills-network/tahoe-lti
|
53308c947632a63fc343e176b177145ccfaeba8b
|
[
"MIT"
] | 9
|
2019-01-29T17:44:11.000Z
|
2022-03-14T10:42:06.000Z
|
mocks/lms/djangoapps/teams/__init__.py
|
ibm-skills-network/tahoe-lti
|
53308c947632a63fc343e176b177145ccfaeba8b
|
[
"MIT"
] | 6
|
2020-05-19T14:13:52.000Z
|
2021-10-29T19:51:45.000Z
|
"""
Mocks for the Open edX lms.djangoapps.teams module.
"""
| 15
| 51
| 0.7
| 9
| 60
| 4.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15
| 60
| 3
| 52
| 20
| 0.823529
| 0.85
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 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
| 4
|
de8a82ebdb68670b967e8d770b7adfb060d29b15
| 475
|
py
|
Python
|
batchflow/models/torch/blocks/__init__.py
|
analysiscenter/dataset
|
50a0607442bd2eb675c8f6a8d7bc5e9dbabe36c0
|
[
"Apache-2.0"
] | 101
|
2017-06-05T07:33:54.000Z
|
2018-10-28T04:55:23.000Z
|
batchflow/models/torch/blocks/__init__.py
|
analysiscenter/dataset
|
50a0607442bd2eb675c8f6a8d7bc5e9dbabe36c0
|
[
"Apache-2.0"
] | 23
|
2017-11-08T20:01:58.000Z
|
2018-07-15T09:08:02.000Z
|
batchflow/models/torch/blocks/__init__.py
|
analysiscenter/dataset
|
50a0607442bd2eb675c8f6a8d7bc5e9dbabe36c0
|
[
"Apache-2.0"
] | 23
|
2017-06-06T05:13:37.000Z
|
2018-11-01T14:33:38.000Z
|
""" Blocks: large parts that implement idea/named entity from popular articles. """
from .core import Block, DefaultBlock, Downsample, Upsample
from .named_blocks import VGGBlock, ResBlock, ResNeStBlock, DenseBlock, MBConvBlock, InvResBlock, ConvNeXtBlock
from .attention import SEBlock, SCSEBlock, SimpleSelfAttention, BAM, CBAM, FPA, SelectiveKernelConv, SplitAttentionConv
from .pyramid import PyramidPooling, ASPP, KSAC
from ..layers import Combine, Branch # convenience
| 67.857143
| 119
| 0.814737
| 52
| 475
| 7.423077
| 0.788462
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111579
| 475
| 6
| 120
| 79.166667
| 0.914692
| 0.187368
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 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
| 4
|
dec5945f9a6ed1b9670b29f1c9bcdb9713ec434e
| 47
|
py
|
Python
|
cntapp/__init__.py
|
rgaudin/edupi
|
97a1f482bd895660dfa0a88f1c91ac86d39d31f8
|
[
"MIT"
] | null | null | null |
cntapp/__init__.py
|
rgaudin/edupi
|
97a1f482bd895660dfa0a88f1c91ac86d39d31f8
|
[
"MIT"
] | null | null | null |
cntapp/__init__.py
|
rgaudin/edupi
|
97a1f482bd895660dfa0a88f1c91ac86d39d31f8
|
[
"MIT"
] | null | null | null |
default_app_config = 'cntapp.apps.CntappConfig'
| 47
| 47
| 0.851064
| 6
| 47
| 6.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.042553
| 47
| 1
| 47
| 47
| 0.844444
| 0
| 0
| 0
| 0
| 0
| 0.5
| 0.5
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 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
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
dee53b3c250d8c6b0a46955f69c9c5f619cb95b5
| 1,167
|
py
|
Python
|
pycatia/mec_mod_interfaces/factory.py
|
evereux/catia_python
|
08948585899b12587b0415ce3c9191a408b34897
|
[
"MIT"
] | 90
|
2019-02-21T10:05:28.000Z
|
2022-03-19T01:53:41.000Z
|
pycatia/mec_mod_interfaces/factory.py
|
Luanee/pycatia
|
ea5eef8178f73de12404561c00baf7a7ca30da59
|
[
"MIT"
] | 99
|
2019-05-21T08:29:12.000Z
|
2022-03-25T09:55:15.000Z
|
pycatia/mec_mod_interfaces/factory.py
|
Luanee/pycatia
|
ea5eef8178f73de12404561c00baf7a7ca30da59
|
[
"MIT"
] | 26
|
2019-04-04T06:31:36.000Z
|
2022-03-30T07:24:47.000Z
|
#! usr/bin/python3.6
"""
Module initially auto generated using V5Automation files from CATIA V5 R28 on 2020-06-11 12:40:47.360445
.. warning::
The notes denoted "CAA V5 Visual Basic Help" are to be used as reference only.
They are there as a guide as to how the visual basic / catscript functions work
and thus help debugging in pycatia.
"""
from pycatia.system_interfaces.any_object import AnyObject
class Factory(AnyObject):
"""
.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-06-11 12:40:47.360445)
| System.IUnknown
| System.IDispatch
| System.CATBaseUnknown
| System.CATBaseDispatch
| System.AnyObject
| Factory
|
| Abstract object gathering behaviours of all objects being a
| factory.
"""
def __init__(self, com_object):
super().__init__(com_object)
self.factory = com_object
def __repr__(self):
return f'Factory(name="{self.name}")'
| 29.175
| 108
| 0.556127
| 129
| 1,167
| 4.899225
| 0.627907
| 0.052215
| 0.025316
| 0.031646
| 0.126582
| 0.063291
| 0.063291
| 0
| 0
| 0
| 0
| 0.065129
| 0.368466
| 1,167
| 39
| 109
| 29.923077
| 0.792402
| 0.647815
| 0
| 0
| 1
| 0
| 0.09854
| 0.09854
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0.142857
| 0.142857
| 0.714286
| 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
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
7214b2ee6d5f847d40c175cd330db0ef9263718e
| 600
|
py
|
Python
|
14 - Data manipulation with Pandas/chapter 4 - Creating and Visualizing DataFrames/10 - CSV to DataFrame.py
|
Baidaly/datacamp-samples
|
09b3e253ec2c503df936298fedc3902413c987b0
|
[
"MIT"
] | null | null | null |
14 - Data manipulation with Pandas/chapter 4 - Creating and Visualizing DataFrames/10 - CSV to DataFrame.py
|
Baidaly/datacamp-samples
|
09b3e253ec2c503df936298fedc3902413c987b0
|
[
"MIT"
] | null | null | null |
14 - Data manipulation with Pandas/chapter 4 - Creating and Visualizing DataFrames/10 - CSV to DataFrame.py
|
Baidaly/datacamp-samples
|
09b3e253ec2c503df936298fedc3902413c987b0
|
[
"MIT"
] | null | null | null |
'''
You work for an airline, and your manager has asked you to do a competitive analysis and see how often passengers flying on other airlines are involuntarily bumped from their flights. You got a CSV file (airline_bumping.csv) from the Department of Transportation containing data on passengers that were involuntarily denied boarding in 2016 and 2017, but it doesn't have the exact numbers you want. In order to figure this out, you'll need to get the CSV into a pandas DataFrame and do some manipulation!
pandas is imported for you as pd. "airline_bumping.csv" is in your working directory.
'''
| 100
| 504
| 0.796667
| 103
| 600
| 4.621359
| 0.699029
| 0.058824
| 0.071429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.016
| 0.166667
| 600
| 5
| 505
| 120
| 0.936
| 0.985
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a0f7c3f2b5a5b6e332651d38c13f85b04a4a6356
| 169
|
py
|
Python
|
PDA/extra_assignments/10.1. Dicts_ Number of occurrences/solution/main.py
|
EMbeDS-education/StatsAndComputing20212022
|
971e418882b206a1b5606d15d222cef1a5a04834
|
[
"MIT"
] | 2
|
2022-02-24T09:35:15.000Z
|
2022-03-14T20:34:33.000Z
|
PDA/extra_assignments/10.1. Dicts_ Number of occurrences/solution/main.py
|
GeorgiosArg/StatsAndComputing20212022
|
798d39af6aa5ef5eef49d5d6f43191351e8a49f3
|
[
"MIT"
] | null | null | null |
PDA/extra_assignments/10.1. Dicts_ Number of occurrences/solution/main.py
|
GeorgiosArg/StatsAndComputing20212022
|
798d39af6aa5ef5eef49d5d6f43191351e8a49f3
|
[
"MIT"
] | 2
|
2022-03-15T21:40:35.000Z
|
2022-03-26T14:51:31.000Z
|
text = input().split()
times_seen = {}
for word in text:
if word not in times_seen:
times_seen[word] = 0
print(times_seen[word], end=' ')
times_seen[word] += 1
| 24.142857
| 34
| 0.650888
| 28
| 169
| 3.75
| 0.5
| 0.428571
| 0.371429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.014706
| 0.195266
| 169
| 7
| 35
| 24.142857
| 0.757353
| 0
| 0
| 0
| 0
| 0
| 0.005882
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
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| 0
| 0.142857
| 1
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| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
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| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
9d07af6c55ea5a5e36253ca85bba3d759ec14401
| 190
|
py
|
Python
|
featherhelper/__init__.py
|
kiwi0fruit/featherhelper
|
fb981a57e3a99535e3f8a51d5918687f07780f27
|
[
"MIT"
] | 3
|
2019-03-12T13:41:45.000Z
|
2020-10-12T14:29:09.000Z
|
featherhelper/__init__.py
|
kiwi0fruit/featherhelper
|
fb981a57e3a99535e3f8a51d5918687f07780f27
|
[
"MIT"
] | null | null | null |
featherhelper/__init__.py
|
kiwi0fruit/featherhelper
|
fb981a57e3a99535e3f8a51d5918687f07780f27
|
[
"MIT"
] | null | null | null |
from ._version import get_versions
__version__ = get_versions()['version']
del get_versions
from .feather_helper import (
setdir, name, push, pull,
FeatherHelperError as Err, exc
)
| 21.111111
| 39
| 0.752632
| 24
| 190
| 5.583333
| 0.666667
| 0.246269
| 0.268657
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.163158
| 190
| 8
| 40
| 23.75
| 0.842767
| 0
| 0
| 0
| 0
| 0
| 0.036842
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.285714
| 0
| 0.285714
| 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
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
9d0899ecdc42e2c944158215c5c44fba2bb03b53
| 1,281
|
py
|
Python
|
server/ahj_app/migrations/0012_auto_20210701_0345.py
|
reepoi/ahj-registry
|
d4498bccfe114b19acca4f931d29f30fbc65a803
|
[
"MIT"
] | null | null | null |
server/ahj_app/migrations/0012_auto_20210701_0345.py
|
reepoi/ahj-registry
|
d4498bccfe114b19acca4f931d29f30fbc65a803
|
[
"MIT"
] | null | null | null |
server/ahj_app/migrations/0012_auto_20210701_0345.py
|
reepoi/ahj-registry
|
d4498bccfe114b19acca4f931d29f30fbc65a803
|
[
"MIT"
] | null | null | null |
# Generated by Django 3.1.3 on 2021-07-01 03:45
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('ahj_app', '0011_auto_20210623_2231'),
]
operations = [
migrations.RemoveField(
model_name='historicaluser',
name='AcceptedEdits',
),
migrations.RemoveField(
model_name='historicaluser',
name='CommunityScore',
),
migrations.RemoveField(
model_name='historicaluser',
name='SubmittedEdits',
),
migrations.RemoveField(
model_name='user',
name='AcceptedEdits',
),
migrations.RemoveField(
model_name='user',
name='CommunityScore',
),
migrations.RemoveField(
model_name='user',
name='SubmittedEdits',
),
migrations.AddField(
model_name='historicaluser',
name='NumAPICalls',
field=models.IntegerField(db_column='NumAPICalls', default=0),
),
migrations.AddField(
model_name='user',
name='NumAPICalls',
field=models.IntegerField(db_column='NumAPICalls', default=0),
),
]
| 26.6875
| 74
| 0.550351
| 102
| 1,281
| 6.77451
| 0.401961
| 0.104197
| 0.22576
| 0.260492
| 0.639653
| 0.639653
| 0.188133
| 0.188133
| 0.188133
| 0.188133
| 0
| 0.038961
| 0.338798
| 1,281
| 47
| 75
| 27.255319
| 0.77686
| 0.035129
| 0
| 0.829268
| 1
| 0
| 0.184765
| 0.018639
| 0
| 0
| 0
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| 0
| 1
| 0
| false
| 0
| 0.02439
| 0
| 0.097561
| 0
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| null | 0
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| 0
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| 0
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| 1
| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
9d1c91cf59d0418c4e6b5c5008cef13528dae10a
| 634
|
py
|
Python
|
Problem Solving/Python Morsels/Circle/circle.py
|
Lockon2000/Practice
|
a51cb282c727a46a41ac2ce50ea1bd4be9bb4b88
|
[
"MIT"
] | null | null | null |
Problem Solving/Python Morsels/Circle/circle.py
|
Lockon2000/Practice
|
a51cb282c727a46a41ac2ce50ea1bd4be9bb4b88
|
[
"MIT"
] | null | null | null |
Problem Solving/Python Morsels/Circle/circle.py
|
Lockon2000/Practice
|
a51cb282c727a46a41ac2ce50ea1bd4be9bb4b88
|
[
"MIT"
] | null | null | null |
from math import pi
class Circle:
def __init__(self, radius=1):
self.radius = radius
@property
def radius(self):
return self.__radius
@radius.setter
def radius(self, radius):
if radius < 0:
raise ValueError("Radius cannot be negative")
else:
self.__radius = radius
@property
def diameter(self):
return 2*self.radius
@diameter.setter
def diameter(self, diameter):
self.radius = diameter/2
@property
def area(self):
return pi*self.radius**2
def __repr__(self):
return f"Circle({self.radius})"
| 19.8125
| 57
| 0.591483
| 75
| 634
| 4.84
| 0.36
| 0.247934
| 0.132231
| 0.132231
| 0.14876
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011468
| 0.312303
| 634
| 31
| 58
| 20.451613
| 0.821101
| 0
| 0
| 0.125
| 0
| 0
| 0.072555
| 0.033123
| 0
| 0
| 0
| 0
| 0
| 1
| 0.291667
| false
| 0
| 0.041667
| 0.166667
| 0.541667
| 0
| 0
| 0
| 0
| null | 1
| 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
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
9d31b6d0f8382ca3b5ba428039eac19e473bcf75
| 210
|
py
|
Python
|
demo.py
|
pramodsu/pyLingeling
|
a28b69c351ac16a27d804c7fd051cca6b7e8d1e5
|
[
"BSD-2-Clause"
] | 3
|
2020-07-09T12:03:49.000Z
|
2021-08-16T06:46:33.000Z
|
demo.py
|
pramodsu/pyLingeling
|
a28b69c351ac16a27d804c7fd051cca6b7e8d1e5
|
[
"BSD-2-Clause"
] | null | null | null |
demo.py
|
pramodsu/pyLingeling
|
a28b69c351ac16a27d804c7fd051cca6b7e8d1e5
|
[
"BSD-2-Clause"
] | 2
|
2020-09-27T06:42:30.000Z
|
2022-03-28T18:36:11.000Z
|
import lingeling
p = lingeling.lglinit()
lingeling.lgladd(p, 1)
lingeling.lgladd(p, -1)
lingeling.lgladd(p, 0)
lingeling.lglassume(p, -1)
assert lingeling.lglsat(p) == lingeling.LGL_SATISFIABLE
print("Done.")
| 21
| 55
| 0.752381
| 30
| 210
| 5.233333
| 0.466667
| 0.286624
| 0.305732
| 0.216561
| 0.318471
| 0.318471
| 0.318471
| 0
| 0
| 0
| 0
| 0.020942
| 0.090476
| 210
| 9
| 56
| 23.333333
| 0.801047
| 0
| 0
| 0
| 0
| 0
| 0.02381
| 0
| 0
| 0
| 0
| 0
| 0.125
| 1
| 0
| false
| 0
| 0.125
| 0
| 0.125
| 0.125
| 0
| 0
| 0
| null | 1
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
9d4e7525557fc7ec827b99fb8faa05b32e8716ff
| 489
|
py
|
Python
|
nitorch/metrics.py
|
ArneBinder/Pytorch-LRP
|
c17902138f1d560f1f5d38f401ac856e071a5800
|
[
"BSD-3-Clause"
] | 117
|
2019-03-19T08:47:03.000Z
|
2022-03-31T04:14:51.000Z
|
nitorch/metrics.py
|
ArneBinder/Pytorch-LRP
|
c17902138f1d560f1f5d38f401ac856e071a5800
|
[
"BSD-3-Clause"
] | 10
|
2019-09-15T14:59:43.000Z
|
2022-03-15T14:18:02.000Z
|
nitorch/metrics.py
|
ArneBinder/Pytorch-LRP
|
c17902138f1d560f1f5d38f401ac856e071a5800
|
[
"BSD-3-Clause"
] | 49
|
2019-03-19T08:47:03.000Z
|
2021-11-30T01:02:04.000Z
|
from sklearn.metrics import recall_score, roc_curve, auc
def specificity(y_true, y_pred):
return recall_score(y_true, y_pred, pos_label=0)
def sensitivity(y_true, y_pred):
return recall_score(y_true, y_pred, pos_label=1)
def balanced_accuracy(y_true, y_pred):
spec = specificity(y_true, y_pred)
sens = sensitivity(y_true, y_pred)
return (spec + sens) / 2
def auc_score(y_true, y_pred):
fpr, tpr, thresholds = roc_curve(y_true, y_pred)
return auc(fpr, tpr)
| 27.166667
| 56
| 0.730061
| 84
| 489
| 3.928571
| 0.333333
| 0.136364
| 0.163636
| 0.272727
| 0.578788
| 0.387879
| 0.272727
| 0.272727
| 0.272727
| 0.272727
| 0
| 0.007371
| 0.167689
| 489
| 18
| 57
| 27.166667
| 0.80344
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.083333
| 0.166667
| 0.75
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
c2052ef489dac2cb2f931e4c84458e0f49e2d431
| 59
|
py
|
Python
|
app/config.py
|
ontoligent-design/polo2
|
cfb76218708189064c95c493b351589296de51f7
|
[
"MIT"
] | 1
|
2018-07-02T13:31:44.000Z
|
2018-07-02T13:31:44.000Z
|
app/config.py
|
ontoligent-design/polo2
|
cfb76218708189064c95c493b351589296de51f7
|
[
"MIT"
] | null | null | null |
app/config.py
|
ontoligent-design/polo2
|
cfb76218708189064c95c493b351589296de51f7
|
[
"MIT"
] | 1
|
2021-06-18T16:09:18.000Z
|
2021-06-18T16:09:18.000Z
|
#PROJECTS_DIR = "/Users/rca2t1/Dropbox/CODE/polo2-test/PUB"
| 59
| 59
| 0.779661
| 9
| 59
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052632
| 0.033898
| 59
| 1
| 59
| 59
| 0.736842
| 0.983051
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 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
| 4
|
c21a0bd40da517ab182f5f6d1b6d8b0f9abd3dd8
| 4,335
|
py
|
Python
|
tests/test_inbound_client.py
|
Otoru/Genesis
|
389a1e270d1ca432f11f76602fbe8491f344672f
|
[
"MIT"
] | 5
|
2021-07-19T03:30:43.000Z
|
2022-03-10T03:03:54.000Z
|
tests/test_inbound_client.py
|
Otoru/Genesis
|
389a1e270d1ca432f11f76602fbe8491f344672f
|
[
"MIT"
] | 9
|
2021-07-19T03:36:06.000Z
|
2022-03-22T15:49:35.000Z
|
tests/test_inbound_client.py
|
Otoru/Genesis
|
389a1e270d1ca432f11f76602fbe8491f344672f
|
[
"MIT"
] | null | null | null |
import pytest
import asyncio
from textwrap import dedent
from genesis.exceptions import AuthenticationError
from genesis import Client
from environment import Freeswitch, Callback, EVENTS
@pytest.mark.asyncio
async def test_connect_without_freeswitch():
with pytest.raises(ConnectionRefusedError):
async with Client("0.0.0.0", 8021, "ClueCon"):
await asyncio.sleep(1)
@pytest.mark.asyncio
async def test_connect_with_freesswitch():
async with Freeswitch("0.0.0.0", 8021, "ClueCon"):
async with Client("0.0.0.0", 8021, "ClueCon") as client:
response = await client.send("uptime")
message = "The answer is not what we expected"
assert response["Reply-Text"] == "6943047", message
@pytest.mark.asyncio
async def test_connect_without_freeswitch_and_wrong_password():
with pytest.raises(AuthenticationError):
async with Freeswitch("0.0.0.0", 8021, "ClueCon"):
async with Client("0.0.0.0", 8021, "WrongPassword"):
await asyncio.sleep(1)
@pytest.mark.asyncio
async def test_send_api_command():
async with Freeswitch("0.0.0.0", 8021, "ClueCon"):
async with Client("0.0.0.0", 8021, "ClueCon") as client:
response = await client.send("api console loglevel")
message = "The answer is not what we expected"
expected = "+OK console log level set to DEBUG"
assert response["X-API-Reply-Text"] == expected, message
@pytest.mark.asyncio
async def test_send_api_command_with_large_reponse():
async with Freeswitch("0.0.0.0", 8021, "ClueCon"):
async with Client("0.0.0.0", 8021, "ClueCon") as client:
response = await client.send("api status")
message = "The answer is not what we expected"
expected = """UP 0 years, 80 days, 8 hours, 25 minutes, 5 seconds, 869 milliseconds, 87 microseconds
FreeSWITCH (Version 1.10.3-release git e52b1a8 2020-09-09 12:16:24Z 64bit) is ready
7653 session(s) since startup
0 session(s) - peak 2, last 5min 0
0 session(s) per Sec out of max 30, peak 14, last 5min 0
1000 session(s) max
min idle cpu 0.00/99.00
Current Stack Size/Max 240K/8192K"""
assert response["X-API-Reply-Text"] == expected, message
@pytest.mark.asyncio
async def test_event_handler_on_client():
handler = Callback()
assert not handler.is_called, "Control started with wrong value"
events = [EVENTS["HEARTBEAT"]]
async with Freeswitch("0.0.0.0", 8021, "ClueCon", events):
async with Client("0.0.0.0", 8021, "ClueCon") as client:
client.on("HEARTBEAT", handler)
await asyncio.sleep(0.001)
assert handler.is_called, "Event processing did not activate handler"
@pytest.mark.asyncio
async def test_wildcard_handler_on_client():
handler = Callback()
assert not handler.is_called, "Control started with wrong value"
events = [EVENTS["HEARTBEAT"]]
async with Freeswitch("0.0.0.0", 8021, "ClueCon", events):
async with Client("0.0.0.0", 8021, "ClueCon") as client:
client.on("*", handler)
await asyncio.sleep(0.001)
assert handler.is_called, "Event processing did not activate handler"
@pytest.mark.asyncio
async def test_event_handler_not_is_called_with_wrong_event():
handler = Callback()
assert not handler.is_called, "Control started with wrong value"
events = [EVENTS["HEARTBEAT"]]
async with Freeswitch("0.0.0.0", 8021, "ClueCon", events):
async with Client("0.0.0.0", 8021, "ClueCon") as client:
client.on("MESSAGE", handler)
await asyncio.sleep(0.001)
assert not handler.is_called, "Event processing did not activate handler"
@pytest.mark.asyncio
async def test_event_handler_is_called_with_all_events():
handler = Callback()
assert not handler.is_called, "Control started with wrong value"
events = [
EVENTS["MESSAGE"],
EVENTS["MESSAGE"],
EVENTS["MESSAGE"],
EVENTS["MESSAGE"],
]
async with Freeswitch("0.0.0.0", 8021, "ClueCon", events):
async with Client("0.0.0.0", 8021, "ClueCon") as client:
client.on("MESSAGE", handler)
await asyncio.sleep(0.001)
assert not handler.count == len(events), "Event processing did not activate handler"
| 33.604651
| 112
| 0.668973
| 601
| 4,335
| 4.740433
| 0.222962
| 0.036504
| 0.035802
| 0.023868
| 0.742015
| 0.742015
| 0.713233
| 0.708319
| 0.694279
| 0.606529
| 0
| 0.067409
| 0.212918
| 4,335
| 128
| 113
| 33.867188
| 0.767585
| 0
| 0
| 0.586957
| 0
| 0.021739
| 0.278201
| 0
| 0
| 0
| 0
| 0
| 0.119565
| 1
| 0
| false
| 0.021739
| 0.065217
| 0
| 0.065217
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 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
| 4
|
c226d0fb0b375ee06a4b7051d4b0626cda7e3ec0
| 160
|
py
|
Python
|
src/retrieval/retrieval_method.py
|
RahulRoyMattam/fever-baselines
|
8977ffd939dbdb17bf4f190d45f11dabb7755668
|
[
"Apache-2.0"
] | 71
|
2019-01-11T21:07:32.000Z
|
2021-07-10T17:59:33.000Z
|
src/retrieval/retrieval_method.py
|
RahulRoyMattam/fever-baselines
|
8977ffd939dbdb17bf4f190d45f11dabb7755668
|
[
"Apache-2.0"
] | 16
|
2018-04-10T16:00:49.000Z
|
2018-06-28T07:41:08.000Z
|
src/retrieval/retrieval_method.py
|
mithunpaul08/fever-baselines
|
7b2a8f9f9b599e5a00e503db06400fca655ad106
|
[
"Apache-2.0"
] | 21
|
2019-01-31T09:05:30.000Z
|
2021-05-26T10:37:13.000Z
|
class RetrievalMethod():
def __init__(self,db):
self.db = db
def get_sentences_for_claim(self,claim_text,include_text=False):
pass
| 14.545455
| 68
| 0.6625
| 21
| 160
| 4.619048
| 0.666667
| 0.123711
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.24375
| 160
| 10
| 69
| 16
| 0.801653
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0.2
| 0
| 0
| 0.6
| 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
| 0
| 1
| 0
|
0
| 4
|
c22a519a8aa5cfda4ea538b1a2f6e273ac094734
| 168
|
py
|
Python
|
mmrotate/core/visualization/__init__.py
|
liuyanyi/mmrotate
|
d80310aa2c4a67c877c62432cddee246d2a4dbcd
|
[
"Apache-2.0"
] | 449
|
2022-02-18T08:26:58.000Z
|
2022-03-31T11:58:32.000Z
|
mmrotate/core/visualization/__init__.py
|
liuyanyi/mmrotate
|
d80310aa2c4a67c877c62432cddee246d2a4dbcd
|
[
"Apache-2.0"
] | 162
|
2022-02-18T09:54:46.000Z
|
2022-03-31T15:40:46.000Z
|
mmrotate/core/visualization/__init__.py
|
liuyanyi/mmrotate
|
d80310aa2c4a67c877c62432cddee246d2a4dbcd
|
[
"Apache-2.0"
] | 98
|
2022-02-18T08:28:48.000Z
|
2022-03-31T08:52:11.000Z
|
# Copyright (c) OpenMMLab. All rights reserved.
from .image import imshow_det_rbboxes
from .palette import get_palette
__all__ = ['imshow_det_rbboxes', 'get_palette']
| 28
| 47
| 0.791667
| 23
| 168
| 5.347826
| 0.608696
| 0.146341
| 0.260163
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.119048
| 168
| 5
| 48
| 33.6
| 0.831081
| 0.267857
| 0
| 0
| 0
| 0
| 0.239669
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 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
| 4
|
c24dc5178d821ec2ce41b09336be1b6880117e86
| 663
|
py
|
Python
|
robots/catkin_ws/build/lilistbot/cmake/lilistbot-genmsg-context.py
|
sunzhon/Lilibot
|
8fc9e5e0beea87bd25743a9c28f9419dbbc7479c
|
[
"BSD-3-Clause"
] | 3
|
2020-12-06T08:46:45.000Z
|
2021-07-28T13:28:53.000Z
|
robots/catkin_ws/build/lilistbot/cmake/lilistbot-genmsg-context.py
|
sunzhon/Lilibot
|
8fc9e5e0beea87bd25743a9c28f9419dbbc7479c
|
[
"BSD-3-Clause"
] | 1
|
2020-10-03T07:25:14.000Z
|
2020-10-03T07:25:14.000Z
|
robots/catkin_ws/build/lilistbot/cmake/lilistbot-genmsg-context.py
|
sunzhon/Lilibot
|
8fc9e5e0beea87bd25743a9c28f9419dbbc7479c
|
[
"BSD-3-Clause"
] | 1
|
2021-07-21T07:45:51.000Z
|
2021-07-21T07:45:51.000Z
|
# generated from genmsg/cmake/pkg-genmsg.context.in
messages_str = "/home/suntao/workspace/gorobots/utils/real_robots/stbot/catkin_ws/src/lilistbot/msg/Jy901imu.msg"
services_str = ""
pkg_name = "lilistbot"
dependencies_str = "std_msgs"
langs = "gencpp;geneus;genlisp;gennodejs;genpy"
dep_include_paths_str = "lilistbot;/home/suntao/workspace/gorobots/utils/real_robots/stbot/catkin_ws/src/lilistbot/msg;std_msgs;/opt/ros/kinetic/share/std_msgs/cmake/../msg"
PYTHON_EXECUTABLE = "/home/suntao/.pyenv/shims/python"
package_has_static_sources = '' == 'TRUE'
genmsg_check_deps_script = "/opt/ros/kinetic/share/genmsg/cmake/../../../lib/genmsg/genmsg_check_deps.py"
| 55.25
| 173
| 0.793363
| 96
| 663
| 5.239583
| 0.572917
| 0.059642
| 0.075547
| 0.107356
| 0.27833
| 0.27833
| 0.27833
| 0.27833
| 0.27833
| 0.27833
| 0
| 0.004769
| 0.051282
| 663
| 11
| 174
| 60.272727
| 0.794913
| 0.073906
| 0
| 0
| 1
| 0.222222
| 0.668301
| 0.633987
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 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
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
dfaec5e7b55b1c59719e1279741eb6567b4536cf
| 230
|
py
|
Python
|
200116/Python/solution.py
|
ktaletsk/daily-problem
|
62ea445d499b8c5211eba635373102627e1d2710
|
[
"MIT"
] | 1
|
2020-01-20T20:31:44.000Z
|
2020-01-20T20:31:44.000Z
|
200116/Python/solution.py
|
ktaletsk/daily-problem
|
62ea445d499b8c5211eba635373102627e1d2710
|
[
"MIT"
] | null | null | null |
200116/Python/solution.py
|
ktaletsk/daily-problem
|
62ea445d499b8c5211eba635373102627e1d2710
|
[
"MIT"
] | null | null | null |
class Solution(object):
def findDisappearedNumbers(self, nums):
return list(set(range(1,len(nums)+1)) - set(nums))
nums = [4, 6, 2, 6, 7, 2, 1]
def test():
assert Solution().findDisappearedNumbers(nums) == [3, 5]
| 28.75
| 60
| 0.634783
| 33
| 230
| 4.424242
| 0.636364
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058511
| 0.182609
| 230
| 8
| 60
| 28.75
| 0.718085
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 1
| 0.333333
| false
| 0
| 0
| 0.166667
| 0.666667
| 0
| 0
| 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
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
dfb51ebd6774a36e8e4a139b511244c188fae903
| 89
|
py
|
Python
|
bedrift/apps.py
|
kristoea/daljeweb
|
cfbce1d1c023c5d91c3e06ee7c92d8ac2831795a
|
[
"MIT"
] | null | null | null |
bedrift/apps.py
|
kristoea/daljeweb
|
cfbce1d1c023c5d91c3e06ee7c92d8ac2831795a
|
[
"MIT"
] | null | null | null |
bedrift/apps.py
|
kristoea/daljeweb
|
cfbce1d1c023c5d91c3e06ee7c92d8ac2831795a
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class BedriftConfig(AppConfig):
name = 'bedrift'
| 14.833333
| 33
| 0.752809
| 10
| 89
| 6.7
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.168539
| 89
| 5
| 34
| 17.8
| 0.905405
| 0
| 0
| 0
| 0
| 0
| 0.078652
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
dfc98edb7bbf5097bb833e1cad985ced48dd17a7
| 193
|
py
|
Python
|
tasks/admin.py
|
wdy-exceedteam/celery-tasks
|
3a66ac6a391286dfe6aba223b11d649f3bbe8bcc
|
[
"MIT"
] | null | null | null |
tasks/admin.py
|
wdy-exceedteam/celery-tasks
|
3a66ac6a391286dfe6aba223b11d649f3bbe8bcc
|
[
"MIT"
] | null | null | null |
tasks/admin.py
|
wdy-exceedteam/celery-tasks
|
3a66ac6a391286dfe6aba223b11d649f3bbe8bcc
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import Task
@admin.register(Task)
class TaskAdmin(admin.ModelAdmin):
list_display = ('id', 'name', 'status_task', 'author', 'created_date')
| 21.444444
| 74
| 0.73057
| 25
| 193
| 5.52
| 0.76
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.129534
| 193
| 8
| 75
| 24.125
| 0.821429
| 0
| 0
| 0
| 0
| 0
| 0.181347
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.8
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
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