added stringdate 2024-11-18 17:59:49 2024-11-19 03:44:43 | created int64 0 2,086B | id stringlengths 40 40 | int_score int64 2 5 | metadata dict | score float64 2.31 5.5 | source stringclasses 1
value | text stringlengths 258 23.4k | num_lines int64 16 649 | avg_line_length float64 15 61 | max_line_length int64 31 179 | ast_depth int64 8 40 | length int64 101 3.8k | lang stringclasses 1
value | sast_codeql_findings stringlengths 2 265k | sast_codeql_findings_count int64 0 45 | sast_codeql_success bool 1
class | sast_codeql_error stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2024-11-18T20:48:13.763592+00:00 | 1,578,126,095,000 | ee0ed0abe88cff35ba113e95541ae91d735643e4 | 2 | {
"blob_id": "ee0ed0abe88cff35ba113e95541ae91d735643e4",
"branch_name": "refs/heads/master",
"committer_date": 1578126095000,
"content_id": "608a8bc7880752ea123e09514ab6a15dd15848d0",
"detected_licenses": [
"MIT"
],
"directory_id": "db9bfa96f739f1a699377e3c05f1c0783d7b0927",
"extension": "py",
"fi... | 2.421875 | stackv2 | import os
import codecs
import sys
from shutil import rmtree
from setuptools import setup, find_packages, Command
here = os.path.abspath(os.path.dirname(__file__))
# Utility function to read the README file.
# Used for the long_description. It's nice, because now 1) we have a top level
# README file and 2) it's ea... | 69 | 27.2 | 79 | 14 | 447 | python | [] | 0 | true | |
2024-11-18T20:48:13.841016+00:00 | 1,599,140,775,000 | e84e6f6110f1975279605bae2f332f34c9ed5800 | 3 | {
"blob_id": "e84e6f6110f1975279605bae2f332f34c9ed5800",
"branch_name": "refs/heads/master",
"committer_date": 1599140775000,
"content_id": "e04dae4718d524d217847b640a6350229a0d4ea6",
"detected_licenses": [
"MIT"
],
"directory_id": "942d19049ff1620a85102cc2b9ad4439f28487b9",
"extension": "py",
"fi... | 2.546875 | stackv2 | import new
from monocle.stack.eventloop import queue_task
from monocle.callback import Callback
def next_tick():
cb = Callback()
cb(None)
return cb
def immediate(val):
cb = Callback()
cb(val)
return cb
def delayed(seconds, val):
cb = Callback()
queue_task(seconds, cb, val)
ret... | 44 | 17.64 | 57 | 14 | 205 | python | [] | 0 | true | |
2024-11-18T20:48:13.901693+00:00 | 1,589,434,531,000 | 1723a340e95faf5909ab8ade084224b35356bb6c | 2 | {
"blob_id": "1723a340e95faf5909ab8ade084224b35356bb6c",
"branch_name": "refs/heads/master",
"committer_date": 1589434531000,
"content_id": "e15208358d8f3be83850e04136d866bc553cfeee",
"detected_licenses": [
"MIT"
],
"directory_id": "21bc3b8fc76ca5af2870bf7f62a22b43fab3b4f8",
"extension": "py",
"fi... | 2.484375 | stackv2 | from typing import Dict, Any, Optional
import re
from atcodertools.codegen.code_style_config import CodeStyleConfig
from atcodertools.fmtprediction.models.format import Pattern, SingularPattern, ParallelPattern, TwoDimensionalPattern, \
Format
from atcodertools.fmtprediction.models.type import Type
from atcodertoo... | 388 | 44.99 | 120 | 25 | 3,127 | python | [] | 0 | true | |
2024-11-18T20:48:14.022724+00:00 | 1,691,758,963,000 | 669ca3385a01e28a89cf03716a4b45c00d03c712 | 4 | {
"blob_id": "669ca3385a01e28a89cf03716a4b45c00d03c712",
"branch_name": "refs/heads/master",
"committer_date": 1691758963000,
"content_id": "8406abb0718113d6e367f8e70422644220b14e34",
"detected_licenses": [
"MIT"
],
"directory_id": "751d837b8a4445877bb2f0d1e97ce41cd39ce1bd",
"extension": "py",
"fi... | 4.4375 | stackv2 | #!/usr/bin/env python
"""
Challenge
So, um, it seems that, while we have plenty of challenges that work with square numbers or numbers of other shapes, we don't have one that simply asks:
Given an integer n (where n>=0) as input return a truthy value if n is a perfect square or a falsey value if not.
Rules
You may ... | 47 | 24.13 | 152 | 10 | 332 | python | [] | 0 | true | |
2024-11-18T20:48:14.208961+00:00 | 1,630,098,373,000 | b49e8e8889cd5444edcce2728ef75bf904e989a9 | 2 | {
"blob_id": "b49e8e8889cd5444edcce2728ef75bf904e989a9",
"branch_name": "refs/heads/main",
"committer_date": 1630098373000,
"content_id": "d701818d70d36f314bbf61c2798d9c72ae93e34a",
"detected_licenses": [
"MIT"
],
"directory_id": "7343b74ea3d783ddf43816e207671c3324ae841b",
"extension": "py",
"file... | 2.453125 | stackv2 | from .ping import Ping
def init_app(app):
"""
I'm using init_app to call the app.load_extension function because if I just call the setup
function directly, the extension name would not be added to the __extensions attribute of the app.
"""
app.load_extension(__name__)
def setup(app):
module... | 20 | 23.25 | 102 | 10 | 113 | python | [] | 0 | true | |
2024-11-18T20:48:14.526932+00:00 | 1,692,365,125,000 | 317198ef9d9b866d97ce62fb0d81b4b341f1edd2 | 3 | {
"blob_id": "317198ef9d9b866d97ce62fb0d81b4b341f1edd2",
"branch_name": "refs/heads/master",
"committer_date": 1692365125000,
"content_id": "7212cb66957e5a5e9126f4cb364c4955d4c97d7b",
"detected_licenses": [
"BSD-2-Clause"
],
"directory_id": "fe5d16cef63488c5ef3f73be54a0981243288d1d",
"extension": "p... | 3.171875 | stackv2 | #!/usr/bin/env python
"""
Checker for repeated tokens
~~~~~~~~~~~~~~~~~~~~~~~~~~~
Helper script to find suspicious lexers which produce the same token
repeatedly, i.e. for example:
.. code::
'd' Text
'a' Text
't' Text
'a' Text
... | 78 | 29.05 | 79 | 13 | 505 | python | [] | 0 | true | |
2024-11-18T20:48:15.050884+00:00 | 1,606,420,219,000 | b4780df87fef3012376512efda3a5dfc297cd1d5 | 4 | {
"blob_id": "b4780df87fef3012376512efda3a5dfc297cd1d5",
"branch_name": "refs/heads/main",
"committer_date": 1606420219000,
"content_id": "2363a1fefe6f667ffed06e66bc59751693404c2c",
"detected_licenses": [
"MIT"
],
"directory_id": "9834875740c6fa5218dd26a75b12a8fbc2ed39d2",
"extension": "py",
"file... | 4.4375 | stackv2 | '''
String = cadeira de caracter = frase
Para cada caracter é denominado um indice começado em 0, sendo
o espaço é contado
maiusculo e diferenciado de minusculo
'''
frase='Teste para a video aula'
print(frase[9])
#ira ate o indice 12, o final é sempre -1
print(frase[9:15])
# imprime pulando de 2 em 2
print(frase[9:2... | 79 | 22.65 | 81 | 9 | 581 | python | [] | 0 | true | |
2024-11-18T20:48:15.170765+00:00 | 1,615,321,907,000 | 031d5690811f5547c32f86396aead5fcff9f5336 | 4 | {
"blob_id": "031d5690811f5547c32f86396aead5fcff9f5336",
"branch_name": "refs/heads/main",
"committer_date": 1615321907000,
"content_id": "7d9ace8b14bebdbfb88fd52a709113b97c75ce65",
"detected_licenses": [
"MIT"
],
"directory_id": "8c9c3e0290d711769aa49fe74efddd71364e2d8a",
"extension": "py",
"file... | 4.34375 | stackv2 | n = int(input('Digite um número inteiro: '))
maior = menor = n
contador = 1
continuar = str(input('Deseja continuar? (S/N): '))
while continuar in 'Ss':
n1 = int(input('Digite um número inteiro: '))
n += n1
contador += 1
continuar = str(input('Deseja continuar? (S/N): '))
if n1 > maior:
maio... | 17 | 32.82 | 71 | 11 | 168 | python | [] | 0 | true | |
2024-11-18T20:48:15.213224+00:00 | 1,597,078,699,000 | eb6c8ec581c9fd64a97b183a4753c1705b20252e | 3 | {
"blob_id": "eb6c8ec581c9fd64a97b183a4753c1705b20252e",
"branch_name": "refs/heads/master",
"committer_date": 1597078699000,
"content_id": "9e9d4625c30bf3b002bc686e06b55bac2dcf34ad",
"detected_licenses": [
"MIT"
],
"directory_id": "c7e4ac2dabeb251858756e44b9a0f309ada05fb0",
"extension": "py",
"fi... | 3.15625 | stackv2 | '''
author: Anmol Durgapal || @slothfulwave612
A Python module for plotting radar-chart.
The radar-chart theme is inspired from @Statsbomb.
'''
## import necessary packages/modules
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
from . import utils
def plot_radar(ranges, p... | 349 | 34.17 | 155 | 18 | 3,065 | python | [] | 0 | true | |
2024-11-18T20:48:15.270582+00:00 | 1,606,469,576,000 | 47b7a18570c895d6f1538b3769778a96fd830dc6 | 4 | {
"blob_id": "47b7a18570c895d6f1538b3769778a96fd830dc6",
"branch_name": "refs/heads/main",
"committer_date": 1606469576000,
"content_id": "30009b32d0d01e0e83139c3d03b7195d5dea2818",
"detected_licenses": [
"MIT"
],
"directory_id": "f219b8c35d2c5e2a6a50fd529a5a952f7230e3e6",
"extension": "py",
"file... | 3.890625 | stackv2 | import random
from consts import *
class Game(object):
def __init__(self, length=GAME_LENGTH):
self.length = length
self.initial = []
self.turns = 0
self.is_won = False
self.is_ended = False
# process the initial state of colors
while len(self.initial) < sel... | 72 | 31.29 | 111 | 16 | 524 | python | [] | 0 | true | |
2024-11-18T20:48:15.427121+00:00 | 1,620,723,556,000 | bc10d8fa683766f0e436da4aa3c8ff5dca4808f1 | 3 | {
"blob_id": "bc10d8fa683766f0e436da4aa3c8ff5dca4808f1",
"branch_name": "refs/heads/master",
"committer_date": 1620723556000,
"content_id": "2c69bb84c201cc69513e3add759ccc2b8008379f",
"detected_licenses": [
"MIT"
],
"directory_id": "62096e1511805b49fb8027fb31e55a51ce6e599b",
"extension": "py",
"fi... | 3 | stackv2 | import random
from typing import Dict, List, Union, Tuple
from pypokerengine.utils.card_utils import estimate_hole_card_win_rate, gen_cards
from pypokerengine.players import BasePokerPlayer
NB_SIMULATION = 1000
class BaselinePlayer(BasePokerPlayer):
"""
Documentation for callback arguments given here:
h... | 91 | 43.27 | 125 | 17 | 867 | python | [] | 0 | true | |
2024-11-18T20:48:15.554800+00:00 | 1,588,050,274,000 | d7bf9963039149ced723adbaf4d0d72dd7a14bad | 2 | {
"blob_id": "d7bf9963039149ced723adbaf4d0d72dd7a14bad",
"branch_name": "refs/heads/master",
"committer_date": 1588050274000,
"content_id": "faa834cb80f3bbf808757c4149d9aad501d3288e",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "04eeda7d8ab415eb68921eb35ca310efdcad2180",
"extension": "py"... | 2.484375 | stackv2 | from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from config import DATABASE_URI
from models import Base, CVE, CPE, Junction
class Database:
def __init__(self):
self.engine = create_engine(DATABASE_URI)
self.connection = self.engine.connect()
self.Session = ses... | 42 | 26.6 | 53 | 12 | 240 | python | [] | 0 | true | |
2024-11-18T20:48:15.604429+00:00 | 1,546,137,507,000 | 9ed7e8635d5a8f3b2f7b0a27ac0f693c63a144a5 | 3 | {
"blob_id": "9ed7e8635d5a8f3b2f7b0a27ac0f693c63a144a5",
"branch_name": "refs/heads/master",
"committer_date": 1546137507000,
"content_id": "f71b599c49ef3382050c2d01eff0c192906c1d7b",
"detected_licenses": [
"MIT"
],
"directory_id": "553952885882cecd83680aaebc0d28b1aa1d32fe",
"extension": "py",
"fi... | 3 | stackv2 | """
The player's AI code
Functions here are called by clock.py to run the AI code
"""
import random
import math
from clientLogic.logging import logPrint
from clientLogic import clientData, commands
def onConnect():
"""
Called when the player initially connects to the server but before the tank first spaw... | 56 | 27.21 | 92 | 17 | 367 | python | [] | 0 | true | |
2024-11-18T20:48:15.719384+00:00 | 1,381,272,885,000 | b76e76cc40a1b062f0bdc347856fb9dbb2b50321 | 3 | {
"blob_id": "b76e76cc40a1b062f0bdc347856fb9dbb2b50321",
"branch_name": "refs/heads/master",
"committer_date": 1381272885000,
"content_id": "0a867ba4a357b1e368f889b9903c3c0336c582fc",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "fa01f015df46f02a748a475c45146d3ed69be5be",
"extension": "py"... | 2.59375 | stackv2 | from xml.dom import minidom
import html5lib
import symboltypes
import flags
import linkify
def GenerateHtmlDocs(namespace_map):
for filepath, document in GenerateDocuments(namespace_map):
content = document.documentElement.toxml('utf-8')
yield filepath, content
def GenerateDocuments(namespace_map):
for ... | 291 | 29.6 | 83 | 15 | 1,985 | python | [] | 0 | true | |
2024-11-18T20:48:15.782866+00:00 | 1,435,497,628,000 | 69c8d7607e793e0c36344b1360e8c5d6a6c48bf0 | 3 | {
"blob_id": "69c8d7607e793e0c36344b1360e8c5d6a6c48bf0",
"branch_name": "refs/heads/master",
"committer_date": 1435497628000,
"content_id": "3dd7797815f7935b1da433f6e41f5070a1284fab",
"detected_licenses": [
"MIT"
],
"directory_id": "a09a8cd9e52918c587b55a5c0587330f6b00e244",
"extension": "py",
"fi... | 2.8125 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def _collect_edges(graph):
from itertools import product
result = []
for (u, v) in product(range(len(graph)), range(len(graph))):
if graph[u][v] != 0:
result.append((u, v))
return result
def _detect_nwc_for_src(graph):
if len(gr... | 150 | 27.65 | 79 | 19 | 1,315 | python | [] | 0 | true | |
2024-11-18T20:48:15.954551+00:00 | 1,613,645,886,000 | f05706e475c266189ffd8f94499a3f3251859c1d | 3 | {
"blob_id": "f05706e475c266189ffd8f94499a3f3251859c1d",
"branch_name": "refs/heads/master",
"committer_date": 1613645886000,
"content_id": "a7a0838db8deac46bfcb2530484a83ee47ff7099",
"detected_licenses": [
"MIT"
],
"directory_id": "fe72c322c894a4212edb576f8e826c54dfbc5490",
"extension": "py",
"fi... | 2.625 | stackv2 | # asyncio version
# The MIT License (MIT)
#
# Copyright (c) 2016, 2017 Robert Hammelrath (basic driver)
# 2016 Peter Hinch (asyncio extension)
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# ... | 176 | 41.01 | 105 | 21 | 1,958 | python | [] | 0 | true | |
2024-11-18T20:48:16.319868+00:00 | 1,685,468,889,000 | bb42dffff228071752c3ae699460db6bb065454e | 4 | {
"blob_id": "bb42dffff228071752c3ae699460db6bb065454e",
"branch_name": "refs/heads/master",
"committer_date": 1685468889000,
"content_id": "43ee1d4b0f5fd09b8583052db30dee40c388a21c",
"detected_licenses": [
"MIT"
],
"directory_id": "9e1f60a867f66b1f4e4fc84fa4252c581e5e1a36",
"extension": "py",
"fi... | 4.03125 | stackv2 | """Clean Code in Python - Chapter 6: Descriptors
> A Pythonic Implementation
"""
class HistoryTracedAttribute:
"""Trace the values of this attribute into another one given by the name at
``trace_attribute_name``.
"""
def __init__(self, trace_attribute_name: str) -> None:
self.trace_attribut... | 85 | 28.28 | 79 | 13 | 577 | python | [] | 0 | true | |
2024-11-18T20:48:16.369205+00:00 | 1,630,409,346,000 | 1c84b42379b83d7111a86f83512561654894268d | 3 | {
"blob_id": "1c84b42379b83d7111a86f83512561654894268d",
"branch_name": "refs/heads/master",
"committer_date": 1630409346000,
"content_id": "1e6f97adac7ed842e97eeddb23e22199fdf8e06b",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "2cd54a665f5387947550f24168e3e133d938800b",
"extension": "py"... | 2.75 | stackv2 | import numpy as np
import gym
import matplotlib.pyplot as plt
import seaborn as sns
import os, time
import threading
sns.set()
ep_rewards = []
def run_episodes(env, number_episodes, max_steps):
for episode in range(number_episodes):
obs = env.reset()
ep_score = 0
for t in range(max_steps... | 52 | 25.21 | 115 | 14 | 342 | python | [] | 0 | true | |
2024-11-18T20:48:16.419174+00:00 | 1,598,184,895,000 | 36b87a72365d94b5bfa89e963edcf93f413a44eb | 3 | {
"blob_id": "36b87a72365d94b5bfa89e963edcf93f413a44eb",
"branch_name": "refs/heads/master",
"committer_date": 1598184895000,
"content_id": "243ee4496ee2e597ac8eeb4b367c02ebdc967f3d",
"detected_licenses": [
"MIT"
],
"directory_id": "d09b06ab29e7bd1acb4ab544ccc8573560c37e58",
"extension": "py",
"fi... | 2.765625 | stackv2 | from find_landings import all_landings
import numpy as np
from direct_keys import *
import time
from figures import piece_weight, find_figure
from digit import get_field
import keyboard
FIELD_SIZE = [20, 10]
class AI:
def __init__(self, play_safe):
self.play_safe = play_safe
self.start_time = tim... | 288 | 34.65 | 129 | 20 | 2,646 | python | [] | 0 | true | |
2024-11-18T20:48:16.935169+00:00 | 1,421,257,246,000 | 05db36c7f8770199d339d33c3318e65793ceb2e3 | 3 | {
"blob_id": "05db36c7f8770199d339d33c3318e65793ceb2e3",
"branch_name": "refs/heads/master",
"committer_date": 1421257246000,
"content_id": "dc0d7b417641df65cf32bdb75d1c81ca0e4005c5",
"detected_licenses": [
"MIT"
],
"directory_id": "e20ed90b9be7a0bcdc1603929d65b2375a224bf6",
"extension": "py",
"fi... | 2.5625 | stackv2 | from netapp.netapp_object import NetAppObject
class SystemImagePackageAttributes(NetAppObject):
"""
These attributes provide details about the software packages
available on the system.
When returned as part of the output, all elements of this typedef
are reported, unless limited by a set of desire... | 65 | 29.83 | 89 | 13 | 446 | python | [] | 0 | true | |
2024-11-18T20:48:17.162805+00:00 | 1,508,909,596,000 | 55f1789b2faa99731f180bd770defbad490d1188 | 3 | {
"blob_id": "55f1789b2faa99731f180bd770defbad490d1188",
"branch_name": "refs/heads/master",
"committer_date": 1508909596000,
"content_id": "d2ec3c32bd4159034b29639bd5d12a9aa59c4b76",
"detected_licenses": [
"MIT"
],
"directory_id": "eabbc9604e7454c25c542450e89ea397f137b8ae",
"extension": "py",
"fi... | 3.4375 | stackv2 | from zope.interface import Interface, Attribute
class IStudent(Interface):
"""
Интерфейс компонент, представляющих студентов
"""
name = Attribute("Имя студента")
code = Attribute("Номер зачетки")
group = Attribute("Группа, к которой приписан студент или None")
def add_to_group(group):
... | 49 | 18.8 | 68 | 9 | 223 | python | [] | 0 | true | |
2024-11-18T20:48:17.214254+00:00 | 1,644,337,681,000 | 2c9934c01ecea5ef6840b059708b5ee8d4a55d1f | 3 | {
"blob_id": "2c9934c01ecea5ef6840b059708b5ee8d4a55d1f",
"branch_name": "refs/heads/master",
"committer_date": 1644388851000,
"content_id": "2721f9a146814ca07bb8ad470ac98f943b5413f1",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "b39b31269db70d72d57959feaa0b063eb2b37e12",
"extension": "py"... | 2.90625 | stackv2 | from app.util.log import get_logger
from app.util.ordered_set_queue import OrderedSetQueue
from app.util.safe_thread import SafeThread
from app.master.slave import SlaveMarkedForShutdownError
class SlaveAllocator(object):
"""
The SlaveAllocator class is responsible for allocating slaves to prepared builds.
... | 69 | 40.7 | 114 | 16 | 542 | python | [] | 0 | true | |
2024-11-18T20:48:17.307807+00:00 | 1,693,347,563,000 | f6bd573d871655223faa2f99276f2b4ec5043dae | 3 | {
"blob_id": "f6bd573d871655223faa2f99276f2b4ec5043dae",
"branch_name": "refs/heads/master",
"committer_date": 1693347563000,
"content_id": "32f3fc92097ddb3bcda1f08da125af7cfe9a36ea",
"detected_licenses": [
"Apache-2.0",
"MIT"
],
"directory_id": "c085f61a0f9da8ccd2f56ab9142799a4dcfd1052",
"exten... | 3.03125 | stackv2 | from functools import total_ordering
from .base import PydeckType
@total_ordering
class Function(PydeckType):
"""Indicate a function type with arguments and set already in pydeck
Parameters
----------
name : str
Function name
**kwargs
arguments and value of each argument to be s... | 34 | 20.97 | 83 | 12 | 173 | python | [] | 0 | true | |
2024-11-18T20:48:17.355613+00:00 | 1,526,596,684,000 | 8f02c58cc927da28edc6dfa1cd2f1e715f027a61 | 3 | {
"blob_id": "8f02c58cc927da28edc6dfa1cd2f1e715f027a61",
"branch_name": "refs/heads/master",
"committer_date": 1526596684000,
"content_id": "b631b8bfb8e823aa046621de4836f200a1e8cebd",
"detected_licenses": [
"MIT"
],
"directory_id": "f203fbdb0e3d1be3c5d43e78faeada6b2c15cd34",
"extension": "py",
"fi... | 2.96875 | stackv2 | """
Script plots the multi-observational data set mean to demonstrate changing
moving averages (# of months)
Notes
-----
Author : Zachary Labe
Date : 10 May 2018
"""
### Import modules
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import nclcmaps as ncm
import datetime
import cmocean
... | 143 | 29.32 | 83 | 13 | 1,154 | python | [] | 0 | true | |
2024-11-18T20:48:17.404862+00:00 | 1,583,793,809,000 | 6f2a3ec9eb2df1b702abdb7373268d0600f69fa6 | 2 | {
"blob_id": "6f2a3ec9eb2df1b702abdb7373268d0600f69fa6",
"branch_name": "refs/heads/master",
"committer_date": 1583793809000,
"content_id": "72fcafe7ebe80bfe9e47699eab467e703dd2ac7b",
"detected_licenses": [
"MIT"
],
"directory_id": "9bb22edc4cd39c5d4d689a13abff0fc9ed66af9f",
"extension": "py",
"fi... | 2.453125 | stackv2 | import csv
import datetime as dt
import requests
from discord.ext import commands
from typing import List
import asyncio
import logging
import os
import discord
import src.utils as utils
from src.plotting import plot_csv
from src.database import db
logger = logging.getLogger("covid-19")
class AutoUpdater(commands.... | 128 | 38.3 | 161 | 20 | 1,098 | python | [] | 0 | true | |
2024-11-18T20:48:17.489714+00:00 | 1,457,928,896,000 | 11b75ccb3fdedf546c5aea49970fcd65798049b5 | 4 | {
"blob_id": "11b75ccb3fdedf546c5aea49970fcd65798049b5",
"branch_name": "refs/heads/master",
"committer_date": 1457928896000,
"content_id": "d59da32090e652aeedc6e1836709c4b457507d8e",
"detected_licenses": [
"MIT"
],
"directory_id": "f3fb929efff8168a89ffb09a25c5f20136ea6b11",
"extension": "py",
"fi... | 4.375 | stackv2 | """
An Armstrong number is an n-digit number that is equal to the sum of the n'th
powers of its digits. Determine if the input numbers are Armstrong numbers.
INPUT SAMPLE:
Your program should accept as its first argument a path to a filename. Each
line in this file has a positive integer. E.g.
6
153
351
OUTPUT SAMP... | 46 | 20.28 | 77 | 14 | 234 | python | [] | 0 | true | |
2024-11-18T20:48:17.535616+00:00 | 1,629,306,016,000 | a1516e9d5a77b650e40d3e8c1162f518f248a693 | 2 | {
"blob_id": "a1516e9d5a77b650e40d3e8c1162f518f248a693",
"branch_name": "refs/heads/master",
"committer_date": 1629306016000,
"content_id": "49fdabe443258b9e2783ba587387c058e69cdb05",
"detected_licenses": [
"MIT"
],
"directory_id": "3570814e010ca1fdb146fe9eaa1ea9e014da9a94",
"extension": "py",
"fi... | 2.40625 | stackv2 | # Compute ODT mean and rms velocity profiles. Plot results versus DNS.
# Run as: python3 stats.py case_name
# Values are in wall units (y+, u+).
# Scaling is done in the input file (not explicitly here).
import numpy as np
import glob as gb
import yaml
import sys
import matplotlib
matplotlib.use('PDF')
import m... | 171 | 29.49 | 105 | 11 | 1,838 | python | [] | 0 | true | |
2024-11-18T20:48:17.779831+00:00 | 1,634,167,704,000 | 73b55d8af88df0b178f8b4c8d4426bbc7e44776d | 3 | {
"blob_id": "73b55d8af88df0b178f8b4c8d4426bbc7e44776d",
"branch_name": "refs/heads/master",
"committer_date": 1634167704000,
"content_id": "5528dd631aed0326f54fdb35c6de8dedca91053b",
"detected_licenses": [
"MIT"
],
"directory_id": "2f017d3059c4215062bb3a3e7cf24e7d571b512d",
"extension": "py",
"fi... | 2.921875 | stackv2 | from PySDDP.dessem.script.templates.ilstri import IlstriTemplate
import numpy as np
from typing import IO
import os
COMENTARIO = '&'
class Ilstri(IlstriTemplate):
"""
Classe que contem todos os elementos comuns a qualquer versao do arquivo Ils_tri do Dessem.
Esta classe tem como intuito fornecer duck ty... | 86 | 31.81 | 118 | 22 | 619 | python | [] | 0 | true | |
2024-11-18T20:48:18.323081+00:00 | 1,601,955,335,000 | 93d2fe242712401523fe1819fc7ee1695ea6a35a | 3 | {
"blob_id": "93d2fe242712401523fe1819fc7ee1695ea6a35a",
"branch_name": "refs/heads/main",
"committer_date": 1601955335000,
"content_id": "ed27291c76f9a7a7aa28725b7b77cbbf0d7de67b",
"detected_licenses": [
"BSD-2-Clause"
],
"directory_id": "5c3c62a159ae267ceb75ac24c5f59d4b211ad514",
"extension": "py"... | 2.96875 | stackv2 | import numpy as np
from .shape import check, check_value
def pluralize(noun, count):
return noun if count == 1 else "{}s".format(noun)
def raise_dimension_error(*input_values):
messages = [
"{} {}".format(input_value.ndim, pluralize("dimension", input_value.ndim))
for input_value in input_va... | 73 | 29.55 | 86 | 17 | 601 | python | [] | 0 | true | |
2024-11-18T20:48:18.389713+00:00 | 1,576,018,589,000 | 3a927ce08958163ce6c0c37139decd4f70a98c33 | 3 | {
"blob_id": "3a927ce08958163ce6c0c37139decd4f70a98c33",
"branch_name": "refs/heads/master",
"committer_date": 1576018589000,
"content_id": "e11278eaed2eead73192c1ad6cb4b3afd2c03f26",
"detected_licenses": [
"MIT"
],
"directory_id": "eec5f55d93148c6d7483a5fa86bcb58fa68ed610",
"extension": "py",
"fi... | 2.875 | stackv2 | from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
import EncypData
import json
class WebAutomated():
def __init__(self):
#call the driver to run the webapp
self.driver = webdriver.Chrome("C:\Program Files (x86)\Google\Chrome\Application\chromedriver_win32\chr... | 103 | 31.18 | 158 | 14 | 741 | python | [] | 0 | true | |
2024-11-18T20:48:19.514107+00:00 | 1,542,884,002,000 | e4ffcd64cae18e88d45bf4649a2d4b1e07dae1f8 | 3 | {
"blob_id": "e4ffcd64cae18e88d45bf4649a2d4b1e07dae1f8",
"branch_name": "refs/heads/master",
"committer_date": 1542884002000,
"content_id": "bd77488b6fed555d3375f3b415817b1b8922a2e1",
"detected_licenses": [
"MIT"
],
"directory_id": "1c924ea9b89ed514d3eab6cff6eed30da2fa07e1",
"extension": "py",
"fi... | 2.5625 | stackv2 | import subprocess, os, itertools, time
from mpi4py import MPI as pyMPI
from fill_mesh import fill_mesh
import numpy as np
from dolfin import (Mesh, mpi_comm_world, mpi_comm_self, MeshPartitioning)
def msh_read(msh_file):
'''Get nodes and 3-cells from msh_file'''
assert os.path.splitext(msh_file)[1] == '.msh'... | 95 | 29.48 | 83 | 18 | 783 | python | [] | 0 | true | |
2024-11-18T20:48:20.227172+00:00 | 1,557,363,234,000 | ab4ec73aa2e7c24ec260bc842bb723eaac148eac | 3 | {
"blob_id": "ab4ec73aa2e7c24ec260bc842bb723eaac148eac",
"branch_name": "refs/heads/master",
"committer_date": 1557363234000,
"content_id": "f099e2b02dfe77921cb7b41853e9e20ac1b4b338",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "1e75cec574ed3399751dcf5eedd9fd6ffe903c5a",
"extension": "p... | 2.9375 | stackv2 | import os
import torch
import random
from collections import Counter
class Dictionary(object):
def __init__(self):
self.word2idx = {}
self.idx2word = []
self.counter = Counter()
self.total = 0
def add_word(self, word):
if word not in self.word2idx:
self.id... | 75 | 28.03 | 67 | 15 | 484 | python | [] | 0 | true | |
2024-11-18T20:48:20.342116+00:00 | 1,601,553,746,000 | 71e82378b10d2f92e24de4db9b8582cb36c3b628 | 3 | {
"blob_id": "71e82378b10d2f92e24de4db9b8582cb36c3b628",
"branch_name": "refs/heads/master",
"committer_date": 1601553746000,
"content_id": "1abd2e0e675674252bef3ce03a5058722bf82678",
"detected_licenses": [
"MIT"
],
"directory_id": "fed304f2033a738670793cb70f5098e37df34118",
"extension": "py",
"fi... | 2.6875 | stackv2 | import os.path
import classify_numbers
import extract_grid
import extract_numbers
import sudoku_solver
image_path = str(input("Enter the image file path"))
# if os.path.exists("Output_Images"):
# os.rmdir("Output_Images")
if os.path.exists(image_path):
sudoku_image = extract_grid.SudokuImage(image_path)
else:... | 33 | 31.58 | 80 | 9 | 216 | python | [] | 0 | true | |
2024-11-18T20:48:20.459223+00:00 | 1,566,439,625,000 | 463755bb07a195f47cb3be0029d84f270127d2d8 | 2 | {
"blob_id": "463755bb07a195f47cb3be0029d84f270127d2d8",
"branch_name": "refs/heads/master",
"committer_date": 1566439625000,
"content_id": "33a40bf4b6e8834b2cb35104b16eed47b7924cd2",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "7cc6addf6bbeb6368205196fea3d44feba975bcc",
"extension": "py"... | 2.3125 | stackv2 | import sys
sys.path.append("..")
from SyntheticFunctions import *
from SlidingWindow import *
from Laplacian import *
from CSMSSMTools import *
import matplotlib.pyplot as plt
from PulseExperiments import *
from CircularCoordinates import *
import glob
import os
from sys import exit
PREFIX = "temp"
if __name__ == '_... | 45 | 25.44 | 65 | 13 | 407 | python | [] | 0 | true | |
2024-11-18T20:48:20.522459+00:00 | 1,475,763,867,000 | 7aba203ca65dc4a55bd6be9c831d0d154792f6eb | 3 | {
"blob_id": "7aba203ca65dc4a55bd6be9c831d0d154792f6eb",
"branch_name": "refs/heads/master",
"committer_date": 1475763867000,
"content_id": "337f0306455e8bacd8c1f4b446b85673c659b066",
"detected_licenses": [
"MIT"
],
"directory_id": "d490c6408851678b4346ca6ec8dc08d3547b88d3",
"extension": "py",
"fi... | 2.5625 | stackv2 | from flask import Flask, render_template, request, redirect,session,Markup
from random import randint
from datetime import datetime, date, time
app = Flask(__name__)
app.secret_key = "Dan"
@app.route('/',methods=['GET','POST'])
def index():
if not session.has_key('log'):
session['log'] = []
if not sess... | 44 | 32.68 | 80 | 15 | 398 | python | [{"finding_id": "codeql_py/flask-debug_802f01f1d1071e61_8550d253", "tool_name": "codeql", "rule_id": "py/flask-debug", "finding_type": "problem", "severity": "medium", "confidence": "high", "message": "A Flask app appears to be run in debug mode. This may allow an attacker to run arbitrary code through the debugger.", ... | 1 | true | |
2024-11-18T20:48:20.622947+00:00 | 1,562,332,915,000 | 7dd03e5831768a972f63540df5ab5b194889f138 | 3 | {
"blob_id": "7dd03e5831768a972f63540df5ab5b194889f138",
"branch_name": "refs/heads/master",
"committer_date": 1562332915000,
"content_id": "7f4aadf182f5951a1439f8b60ac0664fe2896ab2",
"detected_licenses": [
"MIT"
],
"directory_id": "ec1de82b189c3b12ad6943f5995e294aebb281db",
"extension": "py",
"fi... | 3.15625 | stackv2 | import requests
from .parser import createResultArray
baseURL = "https://news.ycombinator.com/"
# all the functions below take number of pages as optional parameter.
# Default value is 1 ie., a single page is fetched. Valid range is 1 - 5
# The first page is fetched regardless of the argument passed
def getArticles(... | 50 | 40.72 | 103 | 14 | 478 | python | [] | 0 | true | |
2024-11-18T20:48:21.031114+00:00 | 1,616,449,407,000 | b9faf9508138c607caf24b0d0aeb3b43bda9d1ed | 3 | {
"blob_id": "b9faf9508138c607caf24b0d0aeb3b43bda9d1ed",
"branch_name": "refs/heads/master",
"committer_date": 1616449407000,
"content_id": "6cc063e5eb6bcc4b8068a441c1550d8b8728e86a",
"detected_licenses": [
"MIT"
],
"directory_id": "9491ec2a6ee861b4fb68065ec14c81c10806d746",
"extension": "py",
"fi... | 2.859375 | stackv2 | # -*- coding: utf-8 -*-
"""Negative sampling algorithm based on the work of of Bordes *et al.*."""
from typing import Collection, Optional, Tuple
import torch
from .negative_sampler import NegativeSampler
from ..triples import TriplesFactory
__all__ = [
'BasicNegativeSampler',
]
LOOKUP = {'h': 0, 'r': 1, 't':... | 110 | 41.29 | 119 | 18 | 1,079 | python | [] | 0 | true | |
2024-11-18T20:48:21.262405+00:00 | 1,573,993,469,000 | 2418a660d913b106300b3c23e0bec1d7cdb83c5c | 2 | {
"blob_id": "2418a660d913b106300b3c23e0bec1d7cdb83c5c",
"branch_name": "refs/heads/master",
"committer_date": 1573993469000,
"content_id": "35830786ba81ad8f47054c1ff5872da1826b9386",
"detected_licenses": [
"MIT"
],
"directory_id": "cd270da569019f43ae4a980cdc3c1307d712a672",
"extension": "py",
"fi... | 2.453125 | stackv2 | # -*- coding: utf-8 -*-
"""
Created on Sun Oct 27 15:10:52 2019
@author: Wentao
"""
import requests
import pandas as pd
from time import time
from multiprocessing import Pool
import os
import traceback
#from bs4 import BeautifulSoup
#url = 'https://api.github.com/repos/hashicorp/terraform/stargazers?page=2'
def star... | 255 | 33.38 | 144 | 19 | 2,214 | python | [] | 0 | true | |
2024-11-18T20:48:21.319326+00:00 | 1,418,959,639,000 | 6c9223e83594c65bbb24a28f7cef745181c66482 | 2 | {
"blob_id": "6c9223e83594c65bbb24a28f7cef745181c66482",
"branch_name": "refs/heads/master",
"committer_date": 1418959639000,
"content_id": "63bff7d28ed7b1a582b0d8658c3e8a3c88f06f7a",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "6e2333d1aeea4805fe465d3e768bbd6af1abd898",
"extension": "py"... | 2.328125 | stackv2 | from ansi2html import Ansi2HTMLConverter
from flask import current_app
from werkzeug.utils import escape
from changes.api.serializer import Serializer, register
from changes.models.log import LogChunk
@register(LogChunk)
class LogChunkSerializer(Serializer):
def serialize(self, instance, attrs):
conv = ... | 28 | 29.43 | 93 | 15 | 166 | python | [] | 0 | true | |
2024-11-18T20:48:21.422521+00:00 | 1,690,111,694,000 | 61692dfa3979d09e9c5598ab19463037efdec684 | 5 | {
"blob_id": "61692dfa3979d09e9c5598ab19463037efdec684",
"branch_name": "refs/heads/main",
"committer_date": 1690111694000,
"content_id": "0c4df71af153197dbc6aba1dc583c45a92a89f4a",
"detected_licenses": [
"MIT"
],
"directory_id": "f41a47376d9a0cf69114d8050f7d69c2100c4974",
"extension": "py",
"file... | 4.9375 | stackv2 | """
For a given positive integer n determine
if it can be represented as
a sum of two Fibonacci numbers (possibly equal).
Example
For n = 1, the output should be
fibonacciSimpleSum2(n) = true.
Explanation: 1 = 0 + 1 = F0 + F1.
For n = 11, the output should be
fibonacciSimpleSum2(n) = true.
Explanation: 11 = 3 + ... | 71 | 17.97 | 48 | 12 | 464 | python | [] | 0 | true | |
2024-11-18T20:48:22.521386+00:00 | 1,580,906,793,000 | c7a4a0837d01b9d16d5183824e983308a3b7601a | 2 | {
"blob_id": "c7a4a0837d01b9d16d5183824e983308a3b7601a",
"branch_name": "refs/heads/master",
"committer_date": 1580906793000,
"content_id": "eef24aaadc42c88da9505999cb982100f21ad829",
"detected_licenses": [
"MIT"
],
"directory_id": "6527dbc1a07cb0c214f3b8efa76258a709ff7458",
"extension": "py",
"fi... | 2.3125 | stackv2 | """
Handle the email *forward* and *reply*. phase. There are 3 actors:
- website: who sends emails to alias@sl.co address
- SL email handler (this script)
- user personal email: to be protected. Should never leak to website.
This script makes sure that in the forward phase, the email that is forwarded to user personal... | 397 | 34.56 | 136 | 22 | 2,838 | python | [] | 0 | true | |
2024-11-18T20:48:22.624183+00:00 | 1,693,052,794,000 | 86075fd2940dd024cd40a677a07e565544ba4f3e | 3 | {
"blob_id": "86075fd2940dd024cd40a677a07e565544ba4f3e",
"branch_name": "refs/heads/master",
"committer_date": 1693052794000,
"content_id": "593b818bc08cbfe3b4c9f973f8dfa56ef74031c7",
"detected_licenses": [
"MIT"
],
"directory_id": "ccf975c869d2bda9929262986574a1560a887872",
"extension": "py",
"fi... | 2.515625 | stackv2 | import copy
import numpy as np
import open3d as o3
import transforms3d as t3d
def estimate_normals(pcd, params):
pcd.estimate_normals(search_param=params)
pcd.orient_normals_to_align_with_direction()
def prepare_source_and_target_rigid_3d(source_filename,
noise_amp=0.0... | 55 | 40.16 | 104 | 15 | 534 | python | [] | 0 | true | |
2024-11-18T20:48:22.760663+00:00 | 1,435,578,712,000 | 3595df34a91f0a72fff1a27e84c1230c04c04c46 | 3 | {
"blob_id": "3595df34a91f0a72fff1a27e84c1230c04c04c46",
"branch_name": "refs/heads/master",
"committer_date": 1435578712000,
"content_id": "944491f7e107da42590ff491a7c1b9b77a015b48",
"detected_licenses": [
"MIT"
],
"directory_id": "08e65159ee9629668f894a245093dde6cd168ce9",
"extension": "py",
"fi... | 2.8125 | stackv2 | """
a script that will remove all the unwanted installed willie modules
from site.sitepackages()
"""
import os, site, sys
from errno import EACCES
whitelist = ["__init__", "admin", "reload"]
def rm_rf(site_packages_dir):
path = "%s/willie/modules/" % site_packages_dir
deleted = 0
if os.path.isdir(path):
... | 38 | 29.55 | 67 | 17 | 258 | python | [] | 0 | true | |
2024-11-18T20:48:22.812262+00:00 | 1,594,897,783,000 | 5647633ee6d66d41482204447b944dc8b80fa389 | 3 | {
"blob_id": "5647633ee6d66d41482204447b944dc8b80fa389",
"branch_name": "refs/heads/master",
"committer_date": 1594897783000,
"content_id": "c37e793aa276512f931ff747ea40598b9d110865",
"detected_licenses": [
"MIT"
],
"directory_id": "bafd4a10f9d8a6da63a98ac47007e45d3f3e53bb",
"extension": "py",
"fi... | 3.125 | stackv2 | import datetime as dt
import numpy as np
import pandas_datareader.data as wb
import matplotlib.pyplot as plt
from scipy.stats import norm
StockList = ['ADBE','CSCO','IBM','NVDA','MSFT','HPQ']
StartDay = dt.datetime(2019, 1, 1)
EndDay = dt.datetime(2019, 12, 31)
StockData = wb.DataReader(StockList, 'yahoo',StartDay,... | 51 | 27.1 | 79 | 8 | 527 | python | [] | 0 | true | |
2024-11-18T20:48:22.935956+00:00 | 1,602,906,356,000 | a89fd5c5f67ea7fca175180872e61ab815f65059 | 3 | {
"blob_id": "a89fd5c5f67ea7fca175180872e61ab815f65059",
"branch_name": "refs/heads/main",
"committer_date": 1602906356000,
"content_id": "cdaf67d0d447505ba4911d21daafaa089438bce8",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "59eb2ba876ab4b9c5ff94b113b861a90acb2959e",
"extension": "py",
... | 3.078125 | stackv2 | """Ghose Filter
This runs a Ghose filter for drug-likeliness. Ghose filter filters molecules
by Molecular weight (MW), the number of atoms, and the logP value.
The upper bound of MW is relaxed from 480Da to 500Da. This is
less restrictive and works in conjunction with Lipinski. This is also
to retro-match AutoGrow 3.1.... | 110 | 35.23 | 92 | 12 | 1,080 | python | [] | 0 | true | |
2024-11-18T20:48:23.050056+00:00 | 1,607,940,269,000 | a57e4902ce2e228af738b26fcfee9e0957dabdec | 3 | {
"blob_id": "a57e4902ce2e228af738b26fcfee9e0957dabdec",
"branch_name": "refs/heads/master",
"committer_date": 1607940269000,
"content_id": "f1f0c401cbac2ca064f32bdcc0178f23cd2c8071",
"detected_licenses": [
"MIT"
],
"directory_id": "e943cae50ba6c46a84870d1b3f1f0f9569aeea7d",
"extension": "py",
"fi... | 3.3125 | stackv2 | from typing import Dict, Generic, TypeVar, Union
import json
V = TypeVar("V")
class ConfigClass(Generic[V]):
"""
A lot of config usually exists as JSON objects, when parsed in Python,
it results in a dict being generated which can be accessed as dict['key']
However, this looks less cleaner than writi... | 38 | 35.68 | 113 | 14 | 320 | python | [] | 0 | true | |
2024-11-18T20:48:23.114940+00:00 | 1,631,796,538,000 | 136879e54dc75479725137993e6f3ff9327831b9 | 2 | {
"blob_id": "136879e54dc75479725137993e6f3ff9327831b9",
"branch_name": "refs/heads/main",
"committer_date": 1631796538000,
"content_id": "afc70ba6197f904484129df98f636fffb85b5c34",
"detected_licenses": [
"MIT"
],
"directory_id": "4c849a36b15478c18be38631a9a3a036b9184733",
"extension": "py",
"file... | 2.359375 | stackv2 | from dataset import make_dataset, Dataloader
from model.model_utils import get_net
from early_stop import EarlyStopping
from options import opt
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch.utils.tensorboard import SummaryWriter
from torch.autograd import Variable
from tqdm import tqdm
import torch... | 160 | 32.53 | 109 | 15 | 1,259 | python | [] | 0 | true | |
2024-11-18T20:48:23.156114+00:00 | 1,421,854,138,000 | 70c0f31783242b0415341c57df0b87e1dedeed01 | 3 | {
"blob_id": "70c0f31783242b0415341c57df0b87e1dedeed01",
"branch_name": "refs/heads/master",
"committer_date": 1421854138000,
"content_id": "b5184a72455a4eff76ac41f86936bf9cbcb2293e",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "2a5d8501b0dc06d36a06571beac69630fbf6b33c",
"extension": "py"... | 3.4375 | stackv2 | # Completed version of the Mortar Spark tutorial script.
# To follow the tutorial go to https://help.mortardata.com/technologies/spark/spark_tutorial
import string
import json
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
from pyspark import Spa... | 72 | 37.89 | 110 | 14 | 671 | python | [] | 0 | true | |
2024-11-18T20:48:23.237225+00:00 | 1,526,272,186,000 | 48d525122015b720d80638fed6d10b836eb910df | 3 | {
"blob_id": "48d525122015b720d80638fed6d10b836eb910df",
"branch_name": "refs/heads/master",
"committer_date": 1526272186000,
"content_id": "40b14edadc9ab9a8b2d80dae5fa43254ae1f4201",
"detected_licenses": [
"MIT"
],
"directory_id": "166ca3fb2d774a3fe681e45afedd0e02c1c53130",
"extension": "py",
"fi... | 3.34375 | stackv2 | from trie import Node, Trie
testTrie = Trie()
#test cannot find string in empty Trie
fail = testTrie.find('anything')
print('expect None for empty match =', fail)
#test add da, dad
testTrie.insert('da')
testTrie.insert('dad')
print('expect None for d: ', testTrie.find('d'))
print('expect da for da: ', testTrie.fin... | 20 | 26.65 | 52 | 8 | 157 | python | [] | 0 | true | |
2024-11-18T20:48:23.300036+00:00 | 1,660,829,837,000 | bfb242ad2ff7dd725682382cef21a57a9b999710 | 3 | {
"blob_id": "bfb242ad2ff7dd725682382cef21a57a9b999710",
"branch_name": "refs/heads/master",
"committer_date": 1660829837000,
"content_id": "9d87962c5d4306fcc96511d1596d4420365c5b25",
"detected_licenses": [
"MIT"
],
"directory_id": "a06ac5090ede57c73cb05a6e20430893715983ee",
"extension": "py",
"fi... | 2.609375 | stackv2 | from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Type, TypeVar, Union
from urllib.parse import urlparse
ArgumentsType = Dict[str, Union[str, bool, int]]
class ExchangeType(Enum):
topic = "topic"
direct = "direct"
fanout = "fanout"
@dataclass(frozen... | 63 | 26.7 | 78 | 16 | 410 | python | [] | 0 | true | |
2024-11-18T20:48:23.362451+00:00 | 1,692,558,045,000 | 14fb1cf6fdaa99e9e50be8b41c235378d750c5e2 | 3 | {
"blob_id": "14fb1cf6fdaa99e9e50be8b41c235378d750c5e2",
"branch_name": "refs/heads/main",
"committer_date": 1692558045000,
"content_id": "be2368cfc62a1e9b66fe2c79832aff424fff2979",
"detected_licenses": [
"MIT"
],
"directory_id": "518bf342bc4138982af3e2724e75f1d9ca3ba56c",
"extension": "py",
"file... | 3.203125 | stackv2 | class Solution:
def reverseEvenLengthGroups(self, head: Optional[ListNode]) -> Optional[ListNode]:
# Prev -> (head -> ... -> tail) -> next -> ...
dummy = ListNode(0, head)
prev = dummy
tail = head
next = head.next
groupLength = 1
def getTailAndLength(head: Optional[ListNode], groupLength:... | 44 | 25.57 | 103 | 15 | 295 | python | [] | 0 | true | |
2024-11-18T20:48:23.480460+00:00 | 1,473,013,723,000 | 381b6a21411b9fcf7093f8137d9d2125409dc062 | 3 | {
"blob_id": "381b6a21411b9fcf7093f8137d9d2125409dc062",
"branch_name": "refs/heads/master",
"committer_date": 1473013723000,
"content_id": "99e2c0d483c05c27055ca153859b2b7e227635e6",
"detected_licenses": [
"MIT"
],
"directory_id": "226b56fb4b8cb4c11e235bebba72f3e803d58e2d",
"extension": "py",
"fi... | 2.609375 | stackv2 | import tensorflow as tf
from colorbot import tf_util, constants
class Encoder(object):
def __init__(self, hidden_size, vocab_size):
cell = tf.nn.rnn_cell.GRUCell(hidden_size)
state_size = cell.state_size
output_w = tf_util.weights([state_size, constants.COLOR_SIZE])
output_b = tf_... | 48 | 28.71 | 75 | 14 | 329 | python | [] | 0 | true | |
2024-11-18T20:48:23.527025+00:00 | 1,357,341,515,000 | 12c9e704b25a4b14b1b921e869ab9465246ff4ea | 3 | {
"blob_id": "12c9e704b25a4b14b1b921e869ab9465246ff4ea",
"branch_name": "refs/heads/master",
"committer_date": 1357341515000,
"content_id": "17863b41c14305cd11e58cece2094edbb3848e3c",
"detected_licenses": [
"MIT"
],
"directory_id": "ddf01aae79897eebc3e8e46bc26e772585e8fcc0",
"extension": "py",
"fi... | 2.78125 | stackv2 | """
wifi.py
Christopher Lee, Ashima Research, 2013
lee@ashimaresearch.COM
This module provides and XBee WiFi (802.11) API library
"""
import struct
from xbee.base import XBeeBase
class XBeeWifi(XBeeBase):
"""
Implements the XBee-WiFi API.
Commands may be sent to a device by instansiating this class w... | 142 | 52.11 | 103 | 14 | 1,627 | python | [] | 0 | true | |
2024-11-18T20:48:23.680800+00:00 | 1,629,304,891,000 | 88fa871a3c7a7051e1dc241163ffa0822f48171c | 4 | {
"blob_id": "88fa871a3c7a7051e1dc241163ffa0822f48171c",
"branch_name": "refs/heads/main",
"committer_date": 1629304891000,
"content_id": "187797c71434d81fe356afcca198e67951671036",
"detected_licenses": [
"Unlicense"
],
"directory_id": "6df9b291a49609c802b0e0b33f6561cdf92c73c5",
"extension": "py",
... | 3.546875 | stackv2 | ## kstrikis' solution for project euler problem 5
## released under The Unlicense
## What is the smallest positive number that is evenly divisible by all of the numbers from 1 to 20?
## the answer will be the product of all primes less than 20 times
## any repeated factors (e.g. 16 = 2*2*2*2 and 9 = 3*3)
## for 1 to 20... | 19 | 31.32 | 100 | 9 | 201 | python | [] | 0 | true | |
2024-11-18T20:48:24.068733+00:00 | 1,425,326,912,000 | 7aa7c1dbb1b069ebd30e2dfaa658872dd2cabf88 | 2 | {
"blob_id": "7aa7c1dbb1b069ebd30e2dfaa658872dd2cabf88",
"branch_name": "refs/heads/master",
"committer_date": 1425326912000,
"content_id": "be404ba24cbde9a76d3226aba1e2394cd421668b",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "0a25ea42bd8aff27c939b7de9d9a8ea036b0c66f",
"extension": "py"... | 2.46875 | stackv2 | # Copyright (C) 2013-2014 Computer Sciences Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 60 | 38.33 | 128 | 16 | 495 | python | [] | 0 | true | |
2024-11-18T20:48:24.244185+00:00 | 1,626,863,532,000 | c1b400683d0c248ad6b15ac12c3831e2b32e658a | 3 | {
"blob_id": "c1b400683d0c248ad6b15ac12c3831e2b32e658a",
"branch_name": "refs/heads/master",
"committer_date": 1626863532000,
"content_id": "3aa01357bf60022494d3197c59bd183e24ce3680",
"detected_licenses": [
"MIT"
],
"directory_id": "3bc654990bea5acc2c1160c848271f5a4ec4e4cb",
"extension": "py",
"fi... | 2.953125 | stackv2 | import math
import numpy as np
from prepare_dataset import epoch_sep
import tensorflow.keras.backend as K
import tensorflow_datasets as tfds
import tensorflow as tf
class DataGenerator(tf.keras.utils.Sequence):
def __init__(self, dataset_path, batch_size=1):
'Initialization'
self.batch_size = batc... | 80 | 45.08 | 144 | 17 | 880 | python | [] | 0 | true | |
2024-11-18T20:48:24.344353+00:00 | 1,689,850,979,000 | cd1be11a2308ab217327a7d361138cb7f6c25106 | 3 | {
"blob_id": "cd1be11a2308ab217327a7d361138cb7f6c25106",
"branch_name": "refs/heads/master",
"committer_date": 1689850979000,
"content_id": "549ea7b5f4a4087445fd948e97015a809ec5488b",
"detected_licenses": [
"MIT"
],
"directory_id": "81e6b06b63ab06bcef6a86a91f17aa4a91ceac0a",
"extension": "py",
"fi... | 2.609375 | stackv2 | import sys
from external import align_warp, reslice, softmean, slicer, convert
def align_reslice(anatomy_image, reference_image):
anatomy_header = anatomy_image[:-3] + "hdr"
reference_header = reference_image[:-3] + "hdr"
warp = align_warp(anatomy_image, anatomy_header,
reference_imag... | 25 | 33.96 | 68 | 10 | 207 | python | [] | 0 | true | |
2024-11-18T20:48:24.465349+00:00 | 1,443,938,519,000 | 0713f3a5f9ce44cbc05cd5bc1d1640cfeff85ea3 | 3 | {
"blob_id": "0713f3a5f9ce44cbc05cd5bc1d1640cfeff85ea3",
"branch_name": "refs/heads/master",
"committer_date": 1443938519000,
"content_id": "54f9702d0aa2337b0c4cabafd1e337d6fb1e5230",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "9c72f4923b5c9537385620ee0bd5b41d872333f9",
"extension": "py"... | 3.234375 | stackv2 | from abc import ABCMeta, abstractmethod
import random
import math
from ggplot import *
import pandas as pd
from board_base import BoardBase
class Board(BoardBase):
def __init__(self):
self.limit = 8
self.board = [[None for y in xrange(self.limit)] for x in xrange(self.limit)]
for ... | 123 | 33.02 | 109 | 21 | 1,003 | python | [] | 0 | true | |
2024-11-18T20:48:24.837378+00:00 | 1,468,640,562,000 | 2d089b2d4ddcc9fed5046eb1ecda2a1f98994e77 | 3 | {
"blob_id": "2d089b2d4ddcc9fed5046eb1ecda2a1f98994e77",
"branch_name": "refs/heads/master",
"committer_date": 1468640562000,
"content_id": "85c98011cc919eadf93a5ac6690a2a0cf0f60c65",
"detected_licenses": [
"MIT"
],
"directory_id": "af291d70499553e7fd0b435183117814479f403a",
"extension": "py",
"fi... | 2.6875 | stackv2 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import argparse
import collections
import fnmatch
import os
import pkg_resources
import subprocess
import sys
import pathspec
import yaml
#Python2 support
try:
from autolint.runners import Runner
except ImportError:
from .runners import Runner
__conf_file__ = ".... | 407 | 35.96 | 79 | 21 | 3,013 | python | [] | 0 | true | |
2024-11-18T20:48:24.894480+00:00 | 1,639,681,726,000 | 68a4282b7355f5b0af34712559f145f0ded8064e | 2 | {
"blob_id": "68a4282b7355f5b0af34712559f145f0ded8064e",
"branch_name": "refs/heads/master",
"committer_date": 1639681726000,
"content_id": "aa98210d19a59a48d1d6f27af321962f49363a38",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "25768ca580e72e3b890a4dc66a0bf028308d3711",
"extension": "py"... | 2.5 | stackv2 | from typing import Dict
from typing import Optional
from argparse import ArgumentParser
from rkd.api.contract import ExecutionContext
from ...formatting import development_formatting
from ...exception import MissingDeploymentConfigurationError
from .base import BaseDeploymentTask
class SSHTask(BaseDeploymentTask):
... | 93 | 33.82 | 116 | 15 | 716 | python | [] | 0 | true | |
2024-11-18T20:48:24.941576+00:00 | 1,486,771,566,000 | 9888d5a9ea5c491102f6de50a8b448333e69fbe4 | 4 | {
"blob_id": "9888d5a9ea5c491102f6de50a8b448333e69fbe4",
"branch_name": "refs/heads/master",
"committer_date": 1486771566000,
"content_id": "84ac1c9e5da0ff909e8f1b8f4b78654fe6db2a41",
"detected_licenses": [
"MIT"
],
"directory_id": "c115917f23adc7bc252c81848bb5eb84df6e4ac0",
"extension": "py",
"fi... | 3.78125 | stackv2 | ## 1. Counting in Python ##
import sqlite3
conn = sqlite3.connect('factbook.db')
facts = conn.cursor().execute('select * from facts;').fetchall()
print(facts)
facts_count = len(facts)
## 2. Counting in SQL ##
conn = sqlite3.connect("factbook.db")
birth_rate_count = conn.cursor().execute('select count(birth_rate) fro... | 68 | 34.51 | 128 | 10 | 607 | python | [] | 0 | true | |
2024-11-18T20:48:25.155242+00:00 | 1,513,450,527,000 | c18ed2acc1bf562c1a78a2827913048b6ff36b52 | 3 | {
"blob_id": "c18ed2acc1bf562c1a78a2827913048b6ff36b52",
"branch_name": "refs/heads/master",
"committer_date": 1513450527000,
"content_id": "7e005755ff199b295ebf583ff4370c2650c5f0e9",
"detected_licenses": [
"MIT"
],
"directory_id": "a37dce61efb6280c72335fb50ff4bf412ee65c89",
"extension": "py",
"fi... | 2.546875 | stackv2 | import numpy as np
import manga_elines as mel
class BPT(object):
'''
compute BPT classes
'''
labels = ['None', 'SF', 'Li(N)ER', 'AGN', 'Comp.']
class_labels = dict(enumerate(labels))
class_numbers = {v: k for k, v in class_labels.items()}
lines = ['Hb-4862', 'Ha-6564', 'OIII-5008', 'NII-65... | 51 | 27.76 | 69 | 14 | 473 | python | [] | 0 | true | |
2024-11-18T20:48:25.294990+00:00 | 1,564,765,803,000 | 23460459628658d52bd4ab6ae5e98aa6eb91fa21 | 3 | {
"blob_id": "23460459628658d52bd4ab6ae5e98aa6eb91fa21",
"branch_name": "refs/heads/master",
"committer_date": 1564765803000,
"content_id": "41f5e56beac71ec1c7fd9093747a2ce71096f5c3",
"detected_licenses": [
"MIT"
],
"directory_id": "87453de1749efae79272df3744b1fc7d92927737",
"extension": "py",
"fi... | 3 | stackv2 | # Because main is always too cluttered...
import json
import requests
import argparse
from colorama import Fore, Back, Style, init
# The secret sauce behind the personality of this program
def inform(msg):
print('{}{}{}{}'.format(Style.BRIGHT, Back.BLACK, Fore.MAGENTA, msg))
# Just a simple abstraction of readin... | 47 | 37.4 | 131 | 12 | 422 | python | [] | 0 | true | |
2024-11-18T20:48:25.452442+00:00 | 1,690,045,657,000 | d97afd9e7615365da6f8c39ee66a7e26a8639f2a | 2 | {
"blob_id": "d97afd9e7615365da6f8c39ee66a7e26a8639f2a",
"branch_name": "refs/heads/master",
"committer_date": 1690045657000,
"content_id": "7b5ca44769f06b1aea3cdb178d454286fb051be7",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "518c7e2514194f5c4ebe8f52a53730e447637339",
"extension": "py"... | 2.421875 | stackv2 | import datetime
from gpxpy.geo import Location
from raw_instr_data import RawInstrData
class DestInfo:
def __init__(self):
self.wpt = None # Destination waypoint
self.org_wpt = None # Origin waypoint
self.flw_wpt = None # Waypoint following the destination
self.dtw = None # D... | 77 | 29.61 | 118 | 9 | 598 | python | [] | 0 | true | |
2024-11-18T20:48:25.978396+00:00 | 1,520,533,550,000 | 1084dd07bb2e539bbc399ee55673d50016c7f95f | 3 | {
"blob_id": "1084dd07bb2e539bbc399ee55673d50016c7f95f",
"branch_name": "refs/heads/master",
"committer_date": 1520533550000,
"content_id": "1dd4a1f772ed6975369c971f18864dd8ccda06d3",
"detected_licenses": [
"MIT"
],
"directory_id": "bab947f0a75277b9e81e420d6e020e82e2c92410",
"extension": "py",
"fi... | 2.71875 | stackv2 | import calendar
import requests
import datetime
from core.abstract.input import ExternalDataSource, EnergyData, Device
class SmireAPI(ExternalDataSource):
def __init__(self, usr: str, pwd: str, site: str):
"""
Blue Saphire Smire API. https://test.smire.bluesafire.io
:param usr: Username... | 62 | 31.65 | 96 | 14 | 482 | python | [] | 0 | true | |
2024-11-18T20:48:26.042816+00:00 | 1,590,296,028,000 | dadcdd42c357b7159b102f54c252d498ce43e3cd | 3 | {
"blob_id": "dadcdd42c357b7159b102f54c252d498ce43e3cd",
"branch_name": "refs/heads/master",
"committer_date": 1590296028000,
"content_id": "9c762cf65815568c78f0eafde880d03be096dba4",
"detected_licenses": [
"MIT"
],
"directory_id": "f1e540140594bf5a003a154f217ca9bc0d6f4374",
"extension": "py",
"fi... | 2.75 | stackv2 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn import decomposition
#df.to_csv('iris.csv')
from sklearn.preprocessing import StandardScaler
from sklearn import metrics
from sklearn.svm import SVC # 'rbf'
import time as t
from sklearn.model_selection import train_test_split
... | 70 | 37.9 | 81 | 12 | 735 | python | [] | 0 | true | |
2024-11-18T20:48:26.092585+00:00 | 1,692,107,265,000 | 22d552bc8abc2b1f02a3ec85e89982e8f2d33ed1 | 3 | {
"blob_id": "22d552bc8abc2b1f02a3ec85e89982e8f2d33ed1",
"branch_name": "refs/heads/master",
"committer_date": 1692107265000,
"content_id": "1088e3e5af7d3a263fc30b683cca69e8e0eb64c3",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "23fb7793e9d94e56714b618faacc4e85db8d74f9",
"extension": "p... | 3.046875 | stackv2 | r"""
For information about polarised and magnetic scattering, see
the :ref:`magnetism` documentation.
Definition
----------
The 1D scattering intensity is calculated in the following way (Guinier, 1955)
.. math::
I(q) = \frac{\text{scale}}{V} \cdot \left[
3V(\Delta\rho) \cdot \frac{\sin(qr) - qr\cos(qr)... | 184 | 43.23 | 84 | 10 | 3,224 | python | [] | 0 | true | |
2024-11-18T20:48:26.731253+00:00 | 1,661,450,284,000 | 1ffad46ae660b2982f60c2a6f32f256689981012 | 3 | {
"blob_id": "1ffad46ae660b2982f60c2a6f32f256689981012",
"branch_name": "refs/heads/master",
"committer_date": 1661450284000,
"content_id": "841ca3d8cb8d089271fd7f83e31f7fa6e5da297a",
"detected_licenses": [
"MIT"
],
"directory_id": "a2f3597364f5b6fb6fc9786f4efd837a0a293e88",
"extension": "py",
"fi... | 2.671875 | stackv2 | #
# author: Jungtaek Kim (jtkim@postech.ac.kr)
# last updated: February 4, 2022
#
"""It is utilities for Bayesian optimization."""
import numpy as np
try:
from scipydirect import minimize as directminimize
except: # pragma: no cover
directminimize = None
try:
import cma
except: # pragma: no cover
cma =... | 318 | 30.62 | 97 | 15 | 2,493 | python | [] | 0 | true | |
2024-11-18T20:48:26.896686+00:00 | 1,691,676,412,000 | 95a70c2170157ab7c8959dc0da4284788900385b | 4 | {
"blob_id": "95a70c2170157ab7c8959dc0da4284788900385b",
"branch_name": "refs/heads/master",
"committer_date": 1691676412000,
"content_id": "d908b636a76452250b7926d456339bce1bc54fcc",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "e59a07b832669f55b91f314903344b97f49b227b",
"extension": "py"... | 3.71875 | stackv2 | """
Exact Berk-Jones statistics for goodness-of-fit testing.
This code includes computation of the M_n, M_n^+ and M_n^- statistics.
See paper for details: http://arxiv.org/abs/1311.3190
To use this code, you must install the Python language interpreter and then install the NumPy and SciPy packages.
Alternatively, you... | 71 | 41.23 | 175 | 10 | 778 | python | [] | 0 | true | |
2024-11-18T20:48:27.216170+00:00 | 1,692,307,499,000 | 4d6e8c1c37b428604c3bbb9c4a2151f611ee87cb | 2 | {
"blob_id": "4d6e8c1c37b428604c3bbb9c4a2151f611ee87cb",
"branch_name": "refs/heads/master",
"committer_date": 1692307499000,
"content_id": "552dea37f94b0323b76719c5fe8226c13ad52c45",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "2ae0b8d95d439ccfd55ea7933ad4a2994ad0f6c5",
"extension": "py"... | 2.46875 | stackv2 | # Copyright (C) 2018-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import networkx as nx
from openvino.tools.mo.ops.gather import Gather
from openvino.tools.mo.ops.transpose import Transpose
from openvino.tools.mo.front.common.partial_infer.utils import int64_array
from openvino.tools.mo.graph.graph im... | 244 | 52.89 | 119 | 17 | 3,012 | python | [] | 0 | true | |
2024-11-18T20:48:27.347134+00:00 | 1,502,843,523,000 | 52af7a8ed1c945d8eea90b01f476e960e30905d6 | 3 | {
"blob_id": "52af7a8ed1c945d8eea90b01f476e960e30905d6",
"branch_name": "refs/heads/master",
"committer_date": 1502843523000,
"content_id": "b90805ecd45466670142dfbefe9857f0ecc43b43",
"detected_licenses": [
"MIT"
],
"directory_id": "0abdc6869b473ad55cfd5788d0401cad0e4ea3c9",
"extension": "py",
"fi... | 2.5625 | stackv2 | import azurerm
import json
import sys
Summary = False
def print_region_quota(region):
print(region + ':')
quota = azurerm.get_compute_usage(access_token, subscription_id, region)
if Summary == False:
print(json.dumps(quota, sort_keys=False, indent=2, separators=(',', ': ')))
try:
for r... | 50 | 27.8 | 108 | 20 | 336 | python | [] | 0 | true | |
2024-11-18T20:48:27.477325+00:00 | 1,528,670,183,000 | cd771e702ed8e5c8eb4d0f7df6fb9a33121eb571 | 3 | {
"blob_id": "cd771e702ed8e5c8eb4d0f7df6fb9a33121eb571",
"branch_name": "refs/heads/master",
"committer_date": 1528670183000,
"content_id": "fee83a1fa107fbc67d715fbcb9f8a9086f7311e3",
"detected_licenses": [
"CC0-1.0"
],
"directory_id": "c09f6d45b59e9b759757984eadb4db762fa2bf4b",
"extension": "py",
... | 2.65625 | stackv2 | import pandas as pd
import numpy as np
import datetime as dt
import matplotlib.pyplot as plt
import seaborn as sns
import datetime
from sklearn.cross_validation import train_test_split
from sklearn.cross_validation import cross_val_score
from sklearn.metrics import roc_curve, auc
from sklearn import metrics
pd.option... | 167 | 29.38 | 101 | 11 | 1,196 | python | [] | 0 | true | |
2024-11-18T20:48:27.870199+00:00 | 1,668,627,057,000 | d4acc1a0de68a5f966cb9604bd729be3b60292d2 | 3 | {
"blob_id": "d4acc1a0de68a5f966cb9604bd729be3b60292d2",
"branch_name": "refs/heads/master",
"committer_date": 1668627057000,
"content_id": "61d021467e7bf220233e9957ac8c51ce3a4f2586",
"detected_licenses": [
"MIT"
],
"directory_id": "f25d5f95844ea005ef7809348489e42de4ea75c9",
"extension": "py",
"fi... | 2.625 | stackv2 | from typing import Type
from jivago.lang.annotations import Override
from jivago.serialization.deserialization_strategy import DeserializationStrategy
from jivago.wsgi.invocation.incorrect_attribute_type_exception import IncorrectAttributeTypeException
class ListDeserializationStrategy(DeserializationStrategy):
... | 18 | 33.78 | 101 | 12 | 121 | python | [] | 0 | true | |
2024-11-18T20:48:27.985505+00:00 | 1,573,148,949,000 | b274ab6e3ca3ed3d1dbf7a2f93f4cd53136a37ba | 3 | {
"blob_id": "b274ab6e3ca3ed3d1dbf7a2f93f4cd53136a37ba",
"branch_name": "refs/heads/master",
"committer_date": 1573148949000,
"content_id": "258601702c97b43c984a103ba03091c929368293",
"detected_licenses": [
"MIT"
],
"directory_id": "308ff3931781ba97355e610f20356f7df5a684bc",
"extension": "py",
"fi... | 2.921875 | stackv2 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
tunacell package
============
filters/trees.py module
~~~~~~~~~~~~~~~~~~~~~~~~~~
Classes to filter trees.
"""
import numpy as np
import warnings
from tunacell.filters.main import FilterGeneral, bounded, intersect
class FilterTree(FilterGeneral):
"General class... | 75 | 25.37 | 76 | 17 | 431 | python | [] | 0 | true | |
2024-11-18T20:48:28.038055+00:00 | 1,663,245,489,000 | 89945b39787506c27e90918c4fdae63211b62f20 | 3 | {
"blob_id": "89945b39787506c27e90918c4fdae63211b62f20",
"branch_name": "refs/heads/master",
"committer_date": 1663245489000,
"content_id": "fbe3a2bf7f061c96a2939d4eceb8b27757c40cdd",
"detected_licenses": [
"MIT"
],
"directory_id": "b4f49e5039ab6691bd8871668867939d6d881a6f",
"extension": "py",
"fi... | 2.578125 | stackv2 | import numpy as np
import torch.nn as nn
"""
The code is:
Copyright (c) 2018 Erik Linder-Norén
Licensed under MIT
(https://github.com/eriklindernoren/PyTorch-GAN/blob/master/LICENSE)
"""
class Generator(nn.Module):
def __init__(self, opt):
super().__init__()
self.img_shape = (opt.channels, opt.i... | 84 | 27.2 | 68 | 17 | 604 | python | [] | 0 | true | |
2024-11-18T20:48:28.086572+00:00 | 1,580,365,842,000 | 04c05f2c24b2feb447ce73e477e5f859dc8fb829 | 2 | {
"blob_id": "04c05f2c24b2feb447ce73e477e5f859dc8fb829",
"branch_name": "refs/heads/master",
"committer_date": 1580365842000,
"content_id": "7141054e7993250c54989cb11eb02ce32923e380",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "7b8bb9e6359b181865d39af68547dacbef8e6b36",
"extension": "py"... | 2.3125 | stackv2 | # -*- coding: utf-8 -*-
"""
Created on Thu Dec 19 16:48:40 2019
@author: SUPERMAN
"""
import cv2
import numpy as np
import os
#path =
fol= ['training', 'testing', 'validation']
classes = ['forehand_openstands','forehand_volley','forehead_slice','kick_service','slice_service', 'smash']
for path in fol:
for clss i... | 30 | 19.8 | 108 | 15 | 185 | python | [] | 0 | true | |
2024-11-18T20:48:28.145394+00:00 | 1,487,584,423,000 | 018e0f5a494b3da3deb31acfbf39ed1ef05bcb5a | 3 | {
"blob_id": "018e0f5a494b3da3deb31acfbf39ed1ef05bcb5a",
"branch_name": "refs/heads/master",
"committer_date": 1487584423000,
"content_id": "8c2a8313377b097a8d2b5d787d0a913227f89402",
"detected_licenses": [
"MIT"
],
"directory_id": "24981a0d2bc1833826959e315eeeef511cb6209b",
"extension": "py",
"fi... | 2.578125 | stackv2 | import numpy
import pyopencl as cl
from simple_gene import SimpleGene
class ShufflerChromosome:
# ShufflerChromosome - a chromosome contains a list of Genes.
# __genes - an ordered list of Genes
# __name - name of the chromosome
# dna - an listed of Gene's dna
# dna_total_length - sum of the lengh... | 240 | 43.35 | 98 | 16 | 2,212 | python | [] | 0 | true | |
2024-11-18T20:48:28.225247+00:00 | 1,691,588,353,000 | 0ad9cf0feffe0cb9b3440fa38c1b9fc846e1f072 | 3 | {
"blob_id": "0ad9cf0feffe0cb9b3440fa38c1b9fc846e1f072",
"branch_name": "refs/heads/main",
"committer_date": 1691588353000,
"content_id": "94cddc32a1c356325834d3dd3801c705f3538790",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "ee8a7d7e502c1152cc80906c698b0a64b8f2c17a",
"extension": "py"... | 3.078125 | stackv2 | """Cement core config module."""
import os
from abc import abstractmethod
from ..core.interface import Interface
from ..core.handler import Handler
from ..utils.fs import abspath
from ..utils.misc import minimal_logger
LOG = minimal_logger(__name__)
class ConfigInterface(Interface):
"""
This class defines ... | 228 | 26.4 | 79 | 14 | 1,287 | python | [] | 0 | true | |
2024-11-18T20:48:28.321762+00:00 | 1,629,052,445,000 | 88758cea0bbeab817dc88eb5f7b47154cd755386 | 3 | {
"blob_id": "88758cea0bbeab817dc88eb5f7b47154cd755386",
"branch_name": "refs/heads/main",
"committer_date": 1629052445000,
"content_id": "edfe38f3c9008f929f5770f576fb22ac19ca3bec",
"detected_licenses": [
"MIT"
],
"directory_id": "5bc9bc81d84059b4c7f13b59450399e1b35af506",
"extension": "py",
"file... | 2.703125 | stackv2 | try: import pipeline.detector as dt
except: import TCTracker.pipeline.detector as dt
try: import pipeline.classifier as cl
except: import TCTracker.pipeline.classifier as cl
try: from TCTracker.data.dataset import COCOInputDataset
except: from TCTracker.data.dataset import COCOInputDataset
try: from data.dataset impo... | 88 | 48.05 | 175 | 21 | 962 | python | [] | 0 | true | |
2024-11-18T20:48:28.588265+00:00 | 1,525,663,480,000 | 5ff5741278cb39bc71411172d908d4cf8270469e | 2 | {
"blob_id": "5ff5741278cb39bc71411172d908d4cf8270469e",
"branch_name": "refs/heads/master",
"committer_date": 1525663480000,
"content_id": "40ad4d1024b4c0f1ecc6edef18ed5fdea5d9e01f",
"detected_licenses": [
"MIT"
],
"directory_id": "1296506a42321c3737ca53f3dbde7e611d5601e1",
"extension": "py",
"fi... | 2.46875 | stackv2 | #!/usr/bin/env python3
import sys
import os
import numpy
import scipy.stats
import matplotlib
matplotlib.use("Agg")
import pylab
import seaborn
seaborn.set(context="paper", style="white", palette="deep")
#nonrandom
data=[numpy.loadtxt("learningON/trial"+str(i+1)+"/time_explore.csv", delimiter=",")[:,1] for i in range... | 55 | 32.96 | 123 | 13 | 591 | python | [] | 0 | true | |
2024-11-18T20:48:28.723385+00:00 | 1,641,036,951,000 | 31d855550f078f955c0ca6bcb8901686fb76b803 | 3 | {
"blob_id": "31d855550f078f955c0ca6bcb8901686fb76b803",
"branch_name": "refs/heads/master",
"committer_date": 1641036951000,
"content_id": "26c7e11b9663e6c6773925cde350b6ad393bb1ba",
"detected_licenses": [
"MIT"
],
"directory_id": "c40045b23a2580447f237c23cd9fe8a986aae41a",
"extension": "py",
"fi... | 2.875 | stackv2 | #!/usr/bin/env python3
# coding=utf-8
import argparse
import logging
import logging.config
import os
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
def start_and_end_time_orca(test_path):
'''Determine the start and end call of orcas in the acoustic sample'''
i = 1
dur = 0
... | 58 | 25.4 | 79 | 16 | 397 | python | [] | 0 | true | |
2024-11-18T20:48:28.875795+00:00 | 1,600,137,049,000 | d69c3800577513f6ff27a65be34db38c01d11de3 | 3 | {
"blob_id": "d69c3800577513f6ff27a65be34db38c01d11de3",
"branch_name": "refs/heads/master",
"committer_date": 1600137049000,
"content_id": "61007795dd6e04242ba850d3a303c05369b87388",
"detected_licenses": [
"MIT"
],
"directory_id": "52b5beb1d7e09017ae4e85fc179e1bb8326e74e8",
"extension": "py",
"fi... | 2.6875 | stackv2 | import numpy as np
import matplotlib.pyplot as plt
import all_paths as ap
import engformat as ef
def create():
data = np.loadtxt(ap.MODULE_DATA_PATH + 'basic_raw_data.csv', skiprows=1, delimiter=',').T
x = data[0]
y = data[1]
ps = np.polyfit(x, y, deg=2)
y_fit = ps[0] * x ** 2 + ps[1] * x + ps[2]... | 33 | 36.64 | 99 | 11 | 414 | python | [] | 0 | true | |
2024-11-18T20:48:29.009640+00:00 | 1,622,640,754,000 | 6a13a18f38b9c29a89647854dde515eb74102f98 | 3 | {
"blob_id": "6a13a18f38b9c29a89647854dde515eb74102f98",
"branch_name": "refs/heads/main",
"committer_date": 1622640754000,
"content_id": "0a19399283be5e4e062386a04723def499e6cb98",
"detected_licenses": [
"MIT"
],
"directory_id": "9a634078fb23524a38563835a2b2ff28647b26e0",
"extension": "py",
"file... | 3.203125 | stackv2 | import turtle
import os
colors = ["red", "purple", "blue", "green", "orange", "yellow"]
def spiral(t, size):
for i in range(size):
t.pencolor(colors[i % 6])
t.width(i/100 + 1)
t.forward(i)
t.left(59)
def draw(size, save = False, filename = None):
window = turtle.Screen()
w... | 25 | 25.6 | 72 | 12 | 190 | python | [] | 0 | true | |
2024-11-18T20:48:29.084551+00:00 | 1,636,145,170,000 | 4b51a7b76bf92f8670aab6f39627ed03f3945887 | 3 | {
"blob_id": "4b51a7b76bf92f8670aab6f39627ed03f3945887",
"branch_name": "refs/heads/master",
"committer_date": 1636145170000,
"content_id": "2118a891dabd91b78236f327ebebe174303ffb5f",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "4053b0c49d7974cc20e9f8fa5ce9190e0a253668",
"extension": "py"... | 2.765625 | stackv2 | from ..imports import *
from ..predictor import Predictor
from .preprocessor import TextPreprocessor, TransformersPreprocessor, detect_text_format
from .. import utils as U
class TextPredictor(Predictor):
"""
```
predicts text classes
```
"""
def __init__(self, model, preproc, batch_size=U.DEF... | 228 | 46.23 | 168 | 19 | 2,271 | python | [] | 0 | true | |
2024-11-18T20:48:29.554300+00:00 | 1,552,338,156,000 | 849d34b63490a4705d82f4e49d2074e715b686a5 | 2 | {
"blob_id": "849d34b63490a4705d82f4e49d2074e715b686a5",
"branch_name": "refs/heads/master",
"committer_date": 1552338156000,
"content_id": "30dea573091eb42e545d416051aa4869371c735a",
"detected_licenses": [],
"directory_id": "f7ca8a7507d885e37d405c99ed19818f7ffe5e11",
"extension": "py",
"filename": "sto... | 2.40625 | stackv2 | from flask import jsonify, request
from ..model import StoryLine
from . import api
from .. import db
@api.route('/story_lines', methods=['POST'])
def create_story_line():
story_line = StoryLine(
position=request.json.get('position'),
story_id=request.json.get('story_id')
)
# story_line.int... | 30 | 25.93 | 51 | 13 | 193 | python | [] | 0 | true | |
2024-11-18T20:48:29.605702+00:00 | 1,678,137,174,000 | 77f0d6bc1a4ef56336d14c6cfca328b8ec261a23 | 4 | {
"blob_id": "77f0d6bc1a4ef56336d14c6cfca328b8ec261a23",
"branch_name": "refs/heads/master",
"committer_date": 1678137174000,
"content_id": "df7b9adadcc785995bc80751d874c059f3ac62be",
"detected_licenses": [
"MIT"
],
"directory_id": "2e7aaf5367b9555554ae22338b9184c616e3f69e",
"extension": "py",
"fi... | 3.734375 | stackv2 | import math
import time
def triangle(n):
return int(n * (n + 1) / 2.0)
def divisors(n):
lowers = [i for i in range(1, math.ceil(math.sqrt(n)) + 1) if n % i == 0]
uppers = [int(n / low) for low in reversed(lowers)]
return len(set(lowers + uppers))
def divisor_count(stop):
i = 1
while True:
... | 34 | 24.18 | 77 | 15 | 265 | python | [] | 0 | true | |
2024-11-18T20:48:30.022648+00:00 | 1,561,620,622,000 | 9be802d461389ca1b1143be341984a37ca3e5454 | 3 | {
"blob_id": "9be802d461389ca1b1143be341984a37ca3e5454",
"branch_name": "refs/heads/master",
"committer_date": 1561620622000,
"content_id": "18ff6c2d1b58bc923f4f3ea518d12b8142109eb9",
"detected_licenses": [
"MIT"
],
"directory_id": "0bdd797b3e95429e03108152cacfbb26069f1d76",
"extension": "py",
"fi... | 2.8125 | stackv2 | class Solution:
def maxProfitAssignment(self, difficulty, profit, worker):
"""
:type difficulty: List[int]
:type profit: List[int]
:type worker: List[int]
:rtype: int
"""
def findKey(lis, key):
left, right = 0, len(lis)-1
while left < r... | 37 | 31.38 | 62 | 18 | 287 | python | [] | 0 | true | |
2024-11-18T20:48:30.197163+00:00 | 1,591,900,993,000 | d1ef215bfc03c0268a8a218138985bb427594bc8 | 3 | {
"blob_id": "d1ef215bfc03c0268a8a218138985bb427594bc8",
"branch_name": "refs/heads/master",
"committer_date": 1591901486000,
"content_id": "bfaed749264f3911719a646d4bf17e011108f517",
"detected_licenses": [
"MIT"
],
"directory_id": "2ccd9dad942b7afe6e8c8cabdf48146e3169d5b7",
"extension": "py",
"fi... | 2.59375 | stackv2 | import tensorflow as tf
import numpy as np
class AutoEncoder(tf.keras.layers.Layer):
def __init__(self, units, l2_const=1e-4, share_weights=False):
super().__init__()
self.units = units
self.l2_const = l2_const
self.share_weights = share_weights
def build(self, input_shape):
... | 148 | 39.33 | 126 | 18 | 1,290 | python | [] | 0 | true | |
2024-11-18T20:48:30.242593+00:00 | 1,593,882,917,000 | c14474b6562d69ab43d3ca4f16b52a0ca41601be | 3 | {
"blob_id": "c14474b6562d69ab43d3ca4f16b52a0ca41601be",
"branch_name": "refs/heads/master",
"committer_date": 1593882917000,
"content_id": "4d500efe29be0d887b0b2cb7f17310e9d411bf66",
"detected_licenses": [
"MIT"
],
"directory_id": "1c5d40cde2248e643b354b199374192218b2e731",
"extension": "py",
"fi... | 3.1875 | stackv2 | import pygame
class Board:
def __init__(self, board_x, board_y, block_size, colors, font, font_size, board_offset):
self.board_x = board_x
self.board_y = board_y
self.block_size = block_size
self.right_border = (self.board_x + 4) * self.block_size
self.left_border = board_... | 180 | 37.51 | 134 | 21 | 1,670 | python | [] | 0 | true | |
2024-11-18T20:48:30.295046+00:00 | 1,617,098,203,000 | 3d7c097fb2873e1246b5689a09e651f27cf6032b | 3 | {
"blob_id": "3d7c097fb2873e1246b5689a09e651f27cf6032b",
"branch_name": "refs/heads/master",
"committer_date": 1617098203000,
"content_id": "e2cd4bbd9137bf1a6a0e55d6359898a45b7fbdfe",
"detected_licenses": [
"MIT"
],
"directory_id": "3b4cd52a75859d57054127e644212fa0bcd5bb73",
"extension": "py",
"fi... | 2.640625 | stackv2 | import numpy as np
import torch
from concorde.tsp import TSPSolver
import collections as C
def solve_batch_graphs(batch, first_cities, tmp_name='tmpname'):
def create_concorde_file_xy_coord(arr, name="route", template=''):
n_cities = arr.shape[0]
assert len(arr.shape) == 2
# space delim... | 58 | 35.71 | 145 | 18 | 532 | python | [] | 0 | true | |
2024-11-18T20:48:30.402286+00:00 | 1,505,295,246,000 | 4c4a0534b5fe22a0bc109d8227bf08a351e687fc | 3 | {
"blob_id": "4c4a0534b5fe22a0bc109d8227bf08a351e687fc",
"branch_name": "refs/heads/master",
"committer_date": 1505295246000,
"content_id": "53b5259562e5ec416d943077b9a5e9080c654bc4",
"detected_licenses": [
"MIT"
],
"directory_id": "ad035abbfd2470215b0cfc5884105e90c02d8c99",
"extension": "py",
"fi... | 2.96875 | stackv2 | import os
import pickle
import numpy as np
from sklearn.preprocessing import LabelBinarizer
from utils import Cifar10, unpickle
preprocessed_data_path = "preprocessed-cifar10-data"
lb = LabelBinarizer()
lb.fit(range(Cifar10.num_classes))
if not os.path.exists(preprocessed_data_path):
os.makedirs(preprocessed_da... | 128 | 34.44 | 110 | 17 | 940 | python | [] | 0 | true | |
2024-11-18T20:48:30.486758+00:00 | 1,607,650,454,000 | 985327b4c42aa78d8d3dad62d8025486c04c2683 | 3 | {
"blob_id": "985327b4c42aa78d8d3dad62d8025486c04c2683",
"branch_name": "refs/heads/master",
"committer_date": 1607650454000,
"content_id": "98a2f75a62954deeefd9bd01bcd32ad19f4bd15c",
"detected_licenses": [
"MIT"
],
"directory_id": "fb748834fe2f16e360a4de6b89dca84b148ae2fa",
"extension": "py",
"fi... | 2.6875 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Python example script showing Cisco Secure Workload (Tetration).
Copyright (c) 2020 Cisco and/or its affiliates.
This software is licensed to you under the terms of the Cisco Sample
Code License, Version 1.1 (the "License"). You may obtain a copy of the
License at
... | 97 | 34.15 | 114 | 14 | 691 | python | [] | 0 | true | |
2024-11-18T20:48:30.769335+00:00 | 1,498,926,991,000 | b59b80267b7e47ad227019d42bd9f027d4c80fa7 | 2 | {
"blob_id": "b59b80267b7e47ad227019d42bd9f027d4c80fa7",
"branch_name": "refs/heads/master",
"committer_date": 1498926991000,
"content_id": "1889a0b384251fda31dcb6bb8cbaf91db7dec181",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "a916ea8c4619f8ccf218e26453b56cd8d586cebb",
"extension": "py"... | 2.375 | stackv2 | from baseline.pytorch.torchy import *
class TaggerModel(nn.Module):
def save(self, outname):
torch.save(self, outname)
def create_loss(self):
return SequenceCriterion(len(self.labels))
@staticmethod
def load(dirname, base):
name = '%s/%s.model' % (dirname, base)
retur... | 108 | 35.84 | 117 | 17 | 1,096 | python | [] | 0 | true | |
2024-11-18T20:48:30.945807+00:00 | 1,657,910,712,000 | 4695abfb967c3a1d16ce368f52c6309aae8c5f53 | 3 | {
"blob_id": "4695abfb967c3a1d16ce368f52c6309aae8c5f53",
"branch_name": "refs/heads/master",
"committer_date": 1657910712000,
"content_id": "632a3dd387924ffd091ca3b9b0fc0d2ac009f3ac",
"detected_licenses": [
"MIT"
],
"directory_id": "6661b4d8aa95cd4125c368f7a70c529fcc10bd45",
"extension": "py",
"fi... | 2.953125 | stackv2 | # Generally useful functions. Uses cgs units unless specified otherwise.
import math
import sys
import numpy as np
from scipy.interpolate import interp1d
### physical constants
Lsun = 3.839e33 # solar luminosity in erg/s
G = 6.674e-8 # gravitational constant in cm**3 g**-1 s**-2
Msun = 1.989e33 # mass of the sun in gr... | 279 | 36.47 | 163 | 17 | 3,745 | python | [] | 0 | true | |
2024-11-18T20:48:31.152886+00:00 | 1,614,283,968,000 | 288f7e191492b0a47b6a53abe14a328f1390c346 | 2 | {
"blob_id": "288f7e191492b0a47b6a53abe14a328f1390c346",
"branch_name": "refs/heads/main",
"committer_date": 1614283968000,
"content_id": "e8b3845279f8a28774c7b5e9762a29e960842616",
"detected_licenses": [
"MIT"
],
"directory_id": "9ed7ba12d6c337d15e213c53d6d57cbe83d85756",
"extension": "py",
"file... | 2.375 | stackv2 | import cbprocharts
import json
import getpass
config_file = "./config.json"
with open('config.json') as file:
api_config = json.load(file)
passphrase = getpass.getpass()
charter = cbprocharts.ProCharter(
api_config["api_key"], api_config["api_secret"], passphrase)
balance = cbprocharts.Balance(charter)
bala... | 19 | 21.84 | 64 | 9 | 107 | python | [] | 0 | true | |
2024-11-18T20:48:31.328633+00:00 | 1,585,784,439,000 | 95a51f3fc00fcde3184629be9b84617f1f224a04 | 2 | {
"blob_id": "95a51f3fc00fcde3184629be9b84617f1f224a04",
"branch_name": "refs/heads/master",
"committer_date": 1585784439000,
"content_id": "1375aaaab803742e0f411f451e94bdcfa4225430",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "7013b5ec3be23891411d9979525af551c984ec10",
"extension": "p... | 2.375 | stackv2 | #! /usr/bin/env python
#
# Copyright (C) 2016 Rich Lewis <rl403@cam.ac.uk>
# License: 3-clause BSD
"""
# skchem.features.descriptors.charge
Charge descriptors for scikit-chem.
"""
from collections import OrderedDict
import numpy as np
from rdkit.Chem import rdPartialCharges
from .caching import cache
from .fundame... | 353 | 23.44 | 85 | 16 | 1,992 | python | [] | 0 | true | |
2024-11-18T20:48:32.687273+00:00 | 1,632,679,968,000 | 25993fddcb6f19cbd66823ce29f96314ff3d09a9 | 3 | {
"blob_id": "25993fddcb6f19cbd66823ce29f96314ff3d09a9",
"branch_name": "refs/heads/main",
"committer_date": 1632679968000,
"content_id": "bc9eeec13dafdde4c8b6defee704e56e5f5079b3",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "63f0ca44a91c1c4eed7eb2b255b9431c54ad931e",
"extension": "py",
... | 2.984375 | stackv2 | """
Distance measures that can be used for various torch.tensor operations
"""
import torch
import numpy as np
import torch.nn.functional as F
from torch.distributions import Categorical
from torch.autograd import Variable
from scipy.spatial.distance import cosine
def get_predict_token_vector(pred, target, k=10, s=1,... | 101 | 32.62 | 105 | 17 | 996 | python | [] | 0 | true | |
2024-11-18T20:48:32.817705+00:00 | 1,559,273,002,000 | bd4e8529d137e4df206ba63a069f4525b9e1587f | 3 | {
"blob_id": "bd4e8529d137e4df206ba63a069f4525b9e1587f",
"branch_name": "refs/heads/master",
"committer_date": 1559273002000,
"content_id": "88325d8db67f52eabc93ab0af13f8535230a4b4e",
"detected_licenses": [
"MIT"
],
"directory_id": "b3b104acc91e26c14d8d1d3211f5e7a6094041a5",
"extension": "py",
"fi... | 2.90625 | stackv2 | """
This script gives a simple example on that how to train an Recurrent Neural Networks (RNN).
Author:
Hailiang Zhao
"""
import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
import argparse
from src.utils.global_settings import remove_avx_warning
remove_avx_warni... | 81 | 45.75 | 106 | 14 | 881 | python | [] | 0 | true | |
2024-11-18T20:48:32.875015+00:00 | 1,655,846,464,000 | c3ad7a5a5955e9112e9858032a432de66948dd54 | 2 | {
"blob_id": "c3ad7a5a5955e9112e9858032a432de66948dd54",
"branch_name": "refs/heads/master",
"committer_date": 1655846464000,
"content_id": "7ba9b37e16373d3d19250da35a72dc15130350fd",
"detected_licenses": [
"MIT"
],
"directory_id": "33e5e4b883671f7f40a48e6e0a4b544b3f8f839a",
"extension": "py",
"fi... | 2.328125 | stackv2 | #!/usr/bin/env python
import json
import logging
import os
import shutil
import subprocess
import tempfile
from astropy.io import fits
from astropy.io.ascii import SExtractor as SexToAstropy
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class Executable(object):
def __init__(self,... | 222 | 29.59 | 91 | 18 | 1,721 | python | [] | 0 | true | |
2024-11-18T20:48:33.094032+00:00 | 1,621,835,523,000 | aa661dd9b4fb41247df931755de7a9efab8d099a | 3 | {
"blob_id": "aa661dd9b4fb41247df931755de7a9efab8d099a",
"branch_name": "refs/heads/main",
"committer_date": 1621835523000,
"content_id": "7549ea5ba5a2fcf8d2725d7badeee037a34ed5ff",
"detected_licenses": [
"MIT"
],
"directory_id": "e6bd5bdd18961ad1f310fab33c5f287cd1eac346",
"extension": "py",
"file... | 3.34375 | stackv2 | # Gesture Recognizer
from tkinter import Tk, Canvas, Label, Button
from pickle import load, dump
from tkinter.simpledialog import askstring
from math import floor
defaultDir = 'CursiveRec Files/defaultGestures.pkl'
customDir = 'CursiveRec Files/customGestures.pkl'
uiFont = ("Segoe UI Light", 14)
displayFont = ("Segoe ... | 201 | 42.14 | 120 | 22 | 2,315 | python | [] | 0 | true |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.