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
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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2024-11-18T21:37:17.538803+00:00 | 1,484,829,872,000 | 551fa06a42d24adf128db7a451b33f85834a6b50 | 3 | {
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"MIT"
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"extension": "py",
"fi... | 3.453125 | stackv2 | from pygame.rect import Rect
from settings import *
import pygame
class Hero:
def __init__(self, x, y, w, h):
''' The hero constructor function '''
self.rect = Rect(x, y, w, h)
self.dx = 0
self.dy = 9
self.ddy = 0
self.bouncy = False
self.update_gravity = Tru... | 117 | 31.88 | 70 | 16 | 854 | python | [] | 0 | true | |
2024-11-18T21:37:18.141230+00:00 | 1,590,627,118,000 | 46024eeb876c1db0456967c7b4661c0a174944a1 | 3 | {
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"directory_id": "4c7a8a2a4ef8e4220810e6aa411f1c8b6b628bad",
"extension": "py",
"fi... | 3.0625 | stackv2 | # references:
# https://github.com/weigq/3d_pose_baseline_pytorch/blob/master/src/model.py
# https://github.com/una-dinosauria/3d-pose-baseline/blob/master/src/linear_model.py
import torch.nn as nn
def init_weights(module):
"""Initialize weights of the baseline linear model.
Our initialization scheme is dif... | 118 | 29.36 | 96 | 12 | 866 | python | [] | 0 | true | |
2024-11-18T21:37:18.228114+00:00 | 1,609,258,648,000 | 21973e19746e56207c0a7ced99cd7c1a1224a1d8 | 3 | {
"blob_id": "21973e19746e56207c0a7ced99cd7c1a1224a1d8",
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"MIT"
],
"directory_id": "48dc7d6bbe4d525ab7c0860ab1b8673030f87961",
"extension": "py",
"fi... | 2.84375 | stackv2 | import random as rand
import numpy as np
import names
from math import floor
class Identifiers:
MRN = 0
LastName = ""
FirstName = ""
Service = ""
Room = ""
def __init__(self, MRN=0, LastName="", FirstName="", Service="", Room="", random = False):
services = "ICU, ER, ERHD, 2NS1, 2N... | 36 | 28.72 | 94 | 15 | 267 | python | [] | 0 | true | |
2024-11-18T21:37:18.295167+00:00 | 1,539,811,001,000 | d526b754b6ecb8737a58000e9064fe0e961c9656 | 3 | {
"blob_id": "d526b754b6ecb8737a58000e9064fe0e961c9656",
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"MIT"
],
"directory_id": "3e90ace00c0ca5e6c00b40659ddb416555cd826d",
"extension": "py",
"fi... | 2.59375 | stackv2 | import numpy as np
from keras.layers import Input, Dense, Conv2D, MaxPooling2D, Reshape, Flatten, UpSampling2D
from keras.models import Model
from scipy import stats
batch_size = 32
sidelen = 96
original_shape = (batch_size, 1, sidelen, sidelen)
latent_dim = 16
intermediate_dim = 256
x = Input(batch_shape=original_sh... | 75 | 32 | 91 | 11 | 765 | python | [] | 0 | true | |
2024-11-18T21:37:18.851073+00:00 | 1,591,905,373,000 | 7fa31a05b476bd1032565eb43a6a1374822a7d65 | 2 | {
"blob_id": "7fa31a05b476bd1032565eb43a6a1374822a7d65",
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"Apache-2.0"
],
"directory_id": "d86cec4595089c4ac3be1280ae8afab9b546e5ee",
"extension": "py"... | 2.328125 | stackv2 | import os
import sys
import numpy as np
import torch
import torch.utils.data
from sklearn.utils import shuffle
EXTENSION = '.pt'
########################################################################################################################
class DataSet(torch.utils.data.Dataset):
def __init__(self, ... | 246 | 37.89 | 120 | 24 | 2,186 | python | [] | 0 | true | |
2024-11-18T21:37:18.979561+00:00 | 1,610,264,007,000 | 2e24ac40ada26f32499d361209b44b8d5990ade0 | 4 | {
"blob_id": "2e24ac40ada26f32499d361209b44b8d5990ade0",
"branch_name": "refs/heads/main",
"committer_date": 1610264007000,
"content_id": "92437c69db48076cbf3743912583e027e4e59472",
"detected_licenses": [
"ISC",
"BSD-2-Clause"
],
"directory_id": "11fcf01e933ce5f170a0fe382c6dbefbe51e85df",
"exten... | 3.59375 | stackv2 | """
Implement `ipv4_address`, which should return true if given object is an IPv4 address - four numbers (0-255) separated by dots.
It should only accept addresses in canonical representation, so no leading `0`s, spaces etc.
"""
def ipv4_address(address):
ip_range = [str(x) for x in range(0, 256)]
if not addr... | 16 | 29.25 | 127 | 12 | 121 | python | [] | 0 | true | |
2024-11-18T21:37:19.208390+00:00 | 1,407,157,005,000 | d7d53e363356e2b9173164960522f9b5723d7ff8 | 2 | {
"blob_id": "d7d53e363356e2b9173164960522f9b5723d7ff8",
"branch_name": "refs/heads/master",
"committer_date": 1407157005000,
"content_id": "5ef0d661a6ce7f959d3987330434be2398813f3b",
"detected_licenses": [
"MIT"
],
"directory_id": "e9bf6aa4464d992735e4f39b31aa287b75ad3df1",
"extension": "py",
"fi... | 2.34375 | stackv2 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
# vim:fenc=utf-8
#
# Copyright © 2014 uralbash <root@uralbash.ru>
#
# Distributed under terms of the MIT license.
"""
SQLAlchemy events extension
"""
from sqlalchemy import and_, case, select
from sqlalchemy.sql import func
def _insert_subtree(table, connection, node_si... | 304 | 33.49 | 132 | 22 | 2,368 | python | [] | 0 | true | |
2024-11-18T21:37:19.307867+00:00 | 1,531,559,460,000 | 366e45515db66a77e1c6677d9429500b1141ec5b | 2 | {
"blob_id": "366e45515db66a77e1c6677d9429500b1141ec5b",
"branch_name": "refs/heads/master",
"committer_date": 1531559460000,
"content_id": "5de1c25321f754bbdd6debcaf98e08bfd40beb08",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "f1c7b5c627b1fea93134a6c30c79584d14427d88",
"extension": "p... | 2.328125 | stackv2 | """
新闻点赞模块
AUTH:
DATE:
"""
from django import db
from django.http.response import HttpResponse, JsonResponse
from django.views.decorators.http import require_GET, require_POST
from myApps.models import NewsLiked
from myApps.untils.wrapper_set import is_login_api
def hello_news_liked(request):
return HttpRespons... | 105 | 24.53 | 82 | 15 | 718 | python | [] | 0 | true | |
2024-11-18T21:37:19.366760+00:00 | 1,544,882,533,000 | 54ca85617e24ae17f9b46302dfa4010c1086a62d | 3 | {
"blob_id": "54ca85617e24ae17f9b46302dfa4010c1086a62d",
"branch_name": "refs/heads/master",
"committer_date": 1544882533000,
"content_id": "5eb0e9c0f021f627f0c3c169f6c8afbf9f596563",
"detected_licenses": [
"MIT"
],
"directory_id": "665bf4d744b1b1b7c1bb33b739971704ad3bd1a4",
"extension": "py",
"fi... | 2.53125 | stackv2 | from client_lex import LexResponse, to_validate_text
from client_comprehend import detect_keyphrases
from esclient import TextfileDocument, ImagefileDocument
from config import ES_HOST, ES_PORT, AWS_DEFAULT_REGION
import json
def validate_slots(slots : dict) -> dict:
""" Validate slots
Arguments:
sl... | 191 | 29.06 | 130 | 19 | 1,229 | python | [] | 0 | true | |
2024-11-18T21:37:19.667647+00:00 | 1,572,688,875,000 | b7640d022e910b9ad731605e14fa23e4baa54383 | 3 | {
"blob_id": "b7640d022e910b9ad731605e14fa23e4baa54383",
"branch_name": "refs/heads/master",
"committer_date": 1572688875000,
"content_id": "59e79136425ce696299ecc589717f9bc13152169",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "f1dfe2f9cd6d418badeaae6e452cc257d743ee79",
"extension": "py"... | 2.75 | stackv2 | from scipy.optimize import curve_fit
from scipy import signal
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from scipy.interpolate import interp1d
import os
from qutip import *
def lorentzian_func(f, A, f_r, Q, c):
return A*(f_r/Q)/((f_r/Q)**2 + 4*(f-f_r)**2)**0.5 + c
def lin_func(x, a,... | 262 | 29.32 | 118 | 15 | 2,078 | python | [] | 0 | true | |
2024-11-18T21:37:19.770973+00:00 | 1,503,419,141,000 | b11d9dfab62ff2f6dcd00c835f31b310ae081b6e | 3 | {
"blob_id": "b11d9dfab62ff2f6dcd00c835f31b310ae081b6e",
"branch_name": "refs/heads/master",
"committer_date": 1503419141000,
"content_id": "1744cd876077ebaca4647f20350a4fa329fdca62",
"detected_licenses": [
"MIT"
],
"directory_id": "23bcea76cd1c4be72d20623060ffaec8efbef2fb",
"extension": "py",
"fi... | 3.375 | stackv2 | """
Plucking (deep) keys/paths safely from python collections has never been easier.
"""
from __future__ import absolute_import
import re
import operator
from copy import deepcopy
from itertools import chain
from .compat import basestring
from .structural import pluckable
__all__ = ["pluck", "plucks", "pluckable", "... | 187 | 28.25 | 88 | 17 | 1,340 | python | [] | 0 | true | |
2024-11-18T21:37:19.815584+00:00 | 1,563,304,823,000 | fca1fc0c2c14a8162d291539f38af800ee60312f | 3 | {
"blob_id": "fca1fc0c2c14a8162d291539f38af800ee60312f",
"branch_name": "refs/heads/master",
"committer_date": 1563304823000,
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"detected_licenses": [
"MIT"
],
"directory_id": "693836f3d544b3a5a0bef74c70cf7404668b52d0",
"extension": "py",
"fi... | 2.75 | stackv2 | '''Python 3 script to compress, archive and upload data files to AWS
S3. Usage:
python3 archive-upload.py <path to configuration file>
Requires Python 3.6+ due to use of F-strings. Also see requirements.txt for
list of non-standard-library packages required.
'''
import sys
import time
from pathlib import Path, Pur... | 170 | 38.75 | 112 | 24 | 1,475 | python | [] | 0 | true | |
2024-11-18T21:37:19.942173+00:00 | 1,522,241,483,000 | c4a0e704253c68575f8b15eecc51ce8dee4fc48f | 3 | {
"blob_id": "c4a0e704253c68575f8b15eecc51ce8dee4fc48f",
"branch_name": "refs/heads/master",
"committer_date": 1522241483000,
"content_id": "69b793aa3955e27061b71e618f2204fa5db7e0e1",
"detected_licenses": [
"MIT"
],
"directory_id": "fe6df0924dfb04a39e7faf6861065b8b1bffeb41",
"extension": "py",
"fi... | 2.765625 | stackv2 | from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf
# one layer neural network, 92% accurency
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
x = tf.placeholder(tf.float32, [None, 784])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
logits = tf.matmu... | 26 | 41.85 | 97 | 11 | 322 | python | [] | 0 | true | |
2024-11-18T21:37:20.078913+00:00 | 1,557,864,774,000 | 2a2eaf67b8fecf4316517242c490575b0e2126dc | 2 | {
"blob_id": "2a2eaf67b8fecf4316517242c490575b0e2126dc",
"branch_name": "refs/heads/master",
"committer_date": 1557864774000,
"content_id": "6df9aad73fd4a1c219a20cbe24d1953294fa50bd",
"detected_licenses": [
"MIT"
],
"directory_id": "42503d8b477ec09edeb1dd209ad6af8ed4cd5670",
"extension": "py",
"fi... | 2.5 | stackv2 | from __future__ import print_function, division
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import trapz
import multiprocessing as mp
import h5py
def airy_func(wavelength, cos_th, d, F):
Q = (2. * F / np.pi)**2
airy = 1.0 / (1.0 + Q * np.sin(np.pi * 2.e6 * d * cos_th / wavelength)**... | 178 | 36.81 | 109 | 18 | 2,023 | python | [] | 0 | true | |
2024-11-18T21:37:21.135050+00:00 | 1,588,612,176,000 | 86354c86ef1d6b37cf30a796f1e5c6cf2e9b0e34 | 3 | {
"blob_id": "86354c86ef1d6b37cf30a796f1e5c6cf2e9b0e34",
"branch_name": "refs/heads/master",
"committer_date": 1588612176000,
"content_id": "90a1470bb5edff55578736437d45b6946a581998",
"detected_licenses": [
"MIT"
],
"directory_id": "e72b612154ad590890c2fe959e2dbeb08d239487",
"extension": "py",
"fi... | 2.515625 | stackv2 | """Figure out who needs to work on their docs!"""
import glob
import os
import numpy as np
import shutil
# Module-author keys
authors = {'distres': 'Russell Deitrick',
'thermint': 'Peter Driscoll',
'radheat': 'Rory Barnes',
'vplanet': 'Rory Barnes',
'poise': 'Russell Deitric... | 161 | 30.29 | 79 | 15 | 1,395 | python | [] | 0 | true | |
2024-11-18T21:37:21.317635+00:00 | 1,576,430,195,000 | 5f8401955da30ca83ea496d0eb026da310b546f9 | 3 | {
"blob_id": "5f8401955da30ca83ea496d0eb026da310b546f9",
"branch_name": "refs/heads/master",
"committer_date": 1576430195000,
"content_id": "33defc8e0b7f39eb7cf611e2965a14103e9bac18",
"detected_licenses": [
"MIT"
],
"directory_id": "c090c0b4fe5e7633abc51bf8c30e386c0c969978",
"extension": "py",
"fi... | 2.6875 | stackv2 | import os, logging, copy, re
from datetime import datetime
from multiprocessing import cpu_count
import numpy as np
from bokeh.models import HoverTool
from bokeh.palettes import brewer
log = logging.getLogger("dashmd")
# number of workers for calculations
max_workers = cpu_count()
log.debug(f"Detected {max_workers} ... | 215 | 30.5 | 126 | 15 | 1,881 | python | [] | 0 | true | |
2024-11-18T21:37:21.598391+00:00 | 1,675,259,014,000 | b518be61945e40d80bbfd492ea63c15c15df8091 | 4 | {
"blob_id": "b518be61945e40d80bbfd492ea63c15c15df8091",
"branch_name": "refs/heads/main",
"committer_date": 1675259014000,
"content_id": "75f1adcb17d5ae0cf4cd87fcfe2fae94bdc8e994",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "ea36821eb38a6474ac9e5644f18b4cee78cf73ed",
"extension": "py",
... | 3.984375 | stackv2 | from progressbar import ProgressBar
class ProgressBarWrapper:
"""
Class for the progress bar.
It indicates the number of the tested problems, the number of all the problems to test and the elapsed time of the execution.
The main functions are:
- Create an instance of the progress bar;
... | 38 | 26.18 | 129 | 11 | 207 | python | [] | 0 | true | |
2024-11-18T21:37:21.709787+00:00 | 1,550,014,387,000 | b6bed8c60bca4fc464e4b47135481151f0e4eb1d | 2 | {
"blob_id": "b6bed8c60bca4fc464e4b47135481151f0e4eb1d",
"branch_name": "refs/heads/master",
"committer_date": 1550014387000,
"content_id": "a49cd58af04ae2ae7b147807e1ffb2c14e5327bd",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "5ce9e8b0b4f047f6c99d40c58c8672c05f88abdc",
"extension": "py"... | 2.421875 | stackv2 | #!/usr/bin/env python
from __future__ import print_function
import json
import logging
import os
import shutil
import sys
import uuid
import crnn
# how many times to run for each split
runs = 10
# logging
logging.basicConfig(format='%(asctime)s %(process)s %(levelname)-8s %(message)s', stream=sys.stdout)
log = lo... | 56 | 36.02 | 109 | 16 | 533 | python | [] | 0 | true | |
2024-11-18T21:37:21.960037+00:00 | 1,545,475,951,000 | 7f4860cb38f14fea37eb683e9ec46f7c9ab05cb5 | 3 | {
"blob_id": "7f4860cb38f14fea37eb683e9ec46f7c9ab05cb5",
"branch_name": "refs/heads/master",
"committer_date": 1545475951000,
"content_id": "a5deadf11c496efbfa4366f324e50d0a60f2b9b0",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "9ff338e8c62b890bf86cad0365b6206fbc4bcf06",
"extension": "py"... | 2.734375 | stackv2 | from scapy.all import *
import sys
ip_list = ""
ports_list = []
def detect_ip(packet):
if 'IP' in packet:
global ip_list
ip_src = packet['IP'].src
if ip_src not in ip_list:
ip_list += " " + ip_src
return ip_list
def detect_ports(packet):
global ports_list
if... | 133 | 29.46 | 74 | 20 | 995 | python | [] | 0 | true | |
2024-11-18T21:37:22.005378+00:00 | 1,619,639,009,000 | 56230209e3cf0f17c3641c32020990fe75ba25f6 | 3 | {
"blob_id": "56230209e3cf0f17c3641c32020990fe75ba25f6",
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"committer_date": 1619639009000,
"content_id": "f98c8d3335b150489e47ad4107f7f7daf80cde12",
"detected_licenses": [
"MIT"
],
"directory_id": "6e143e844b66f9e0da053723ca1aedf1ba1e5e19",
"extension": "py",
"file... | 2.625 | stackv2 | import mysql.connector
from dotenv import load_dotenv
load_dotenv()
import os
from google.cloud import storage
import numpy as np
from sklearn import manifold
from sklearn.metrics import pairwise_distances
from sklearn import decomposition
import ssl
ssl._create_default_https_context = ssl._create_unverified_cont... | 183 | 28.85 | 124 | 18 | 1,449 | python | [] | 0 | true | |
2024-11-18T21:37:22.235661+00:00 | 1,632,733,435,000 | 2218bebd12ef97c380351d88599d9d9cb11e2319 | 2 | {
"blob_id": "2218bebd12ef97c380351d88599d9d9cb11e2319",
"branch_name": "refs/heads/master",
"committer_date": 1632733435000,
"content_id": "451cf54b8c8efba4a33f6bc774f964c211c0c484",
"detected_licenses": [
"MIT"
],
"directory_id": "eec0a30a367ba8745b36e92c58dd0223342d48a5",
"extension": "py",
"fi... | 2.3125 | stackv2 | from django.db import models
from django.contrib.auth.models import User
from cloudinary.models import CloudinaryField
# Create your models here.
class Neighbourhood(models.Model):
hood = models.CharField(max_length = 100)
location = models.CharField(max_length = 100)
pic = CloudinaryField('image')
de... | 63 | 31.43 | 83 | 11 | 445 | python | [] | 0 | true | |
2024-11-18T21:37:22.298729+00:00 | 1,628,873,642,000 | ec8cff158b1bf0050aa60b516d96e17d96023135 | 3 | {
"blob_id": "ec8cff158b1bf0050aa60b516d96e17d96023135",
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"committer_date": 1628873642000,
"content_id": "24faea049ddf0098b255f3876c0f813619718a73",
"detected_licenses": [
"MIT"
],
"directory_id": "c8f3ffe64cae77e734ea011ff3cd5dce3e81f2d5",
"extension": "py",
"file... | 3.09375 | stackv2 | import smbus
from time import sleep
class MXL90614():
# Based on the following source-code
# github.com/sightsdev/PyMLX90614/blob/master/mlx90614.py
#
# More details on MLX90614 datasheet on section 8.4 (SMBus)
BUS = 1 # /dev/i2c-1 is bus=1
ADDRESS = 0x5a # MXL90614 slave address is... | 49 | 25.02 | 79 | 15 | 406 | python | [] | 0 | true | |
2024-11-18T21:37:23.078843+00:00 | 1,587,765,824,000 | 747149f14c42643ac8fc516c5591a6c5c70f89f3 | 3 | {
"blob_id": "747149f14c42643ac8fc516c5591a6c5c70f89f3",
"branch_name": "refs/heads/master",
"committer_date": 1587765824000,
"content_id": "dadc08d1560d392eb74d36db4515dd10bac7547a",
"detected_licenses": [
"MIT"
],
"directory_id": "67ba2428edc8880dd493c6b25b3d3cc73e2edaa5",
"extension": "py",
"fi... | 3.140625 | stackv2 | from uuid import uuid4
class User:
id = None
name = None
game_id = None
money = 8
power = 8
def __init__(self, name, incoming_id = None):
if incoming_id is not None:
self.id = incoming_id
else:
self.id = str(uuid4())
self.name = name
self... | 38 | 24.21 | 49 | 15 | 234 | python | [] | 0 | true | |
2024-11-18T21:37:23.130081+00:00 | 1,633,465,310,000 | 064577fbfb95f286834e47b8455649ba394eaf9d | 3 | {
"blob_id": "064577fbfb95f286834e47b8455649ba394eaf9d",
"branch_name": "refs/heads/main",
"committer_date": 1633465310000,
"content_id": "381bddabe06ddcd09a1e10d688b42c746b414d9b",
"detected_licenses": [
"MIT"
],
"directory_id": "c516530ceaf94f6c441de6d0a40dcf1fdd502d6b",
"extension": "py",
"file... | 3 | stackv2 | """
Kubernetes Port-Forward Go-Edition For Python
"""
__version__ = "0.2.5"
import contextlib
import time
from typing import Generator
from pathlib import Path
import _portforward
class PortforwardError(Exception):
"""Will be raised when something went wrong while the port-forward process."""
@contextlib.con... | 102 | 25.08 | 82 | 11 | 652 | python | [] | 0 | true | |
2024-11-18T21:37:23.302279+00:00 | 1,425,498,561,000 | e70d4f5725a607f7e8dd827bdba77159551ac304 | 3 | {
"blob_id": "e70d4f5725a607f7e8dd827bdba77159551ac304",
"branch_name": "refs/heads/master",
"committer_date": 1425498561000,
"content_id": "9ad02435717ebfa23462abb56e2aecd1914d39ce",
"detected_licenses": [
"MIT"
],
"directory_id": "3e94fa33186279185c66a0eb3110803267012064",
"extension": "py",
"fi... | 3.1875 | stackv2 | """
SciptEx.py
This is a command line script which allows someone to run a list of python
scripts. It's main purpose is for running student submitted scripts all
at once with the same arguments. It uses JSON config file(s) to store the
interactive and commandline arguments which the scripts need to be tested
with.It l... | 119 | 38.92 | 152 | 17 | 1,120 | python | [] | 0 | true | |
2024-11-18T21:37:23.390060+00:00 | 1,456,229,089,000 | eb478e68e5a0e1b711e881c7937599e2f2d477a2 | 3 | {
"blob_id": "eb478e68e5a0e1b711e881c7937599e2f2d477a2",
"branch_name": "refs/heads/master",
"committer_date": 1456230111000,
"content_id": "ad204a5ddde451d2e1cc3fc7e722b924d83d219a",
"detected_licenses": [
"MIT"
],
"directory_id": "0897eafcb9a9fb0c991c965f735e156aa80d307f",
"extension": "py",
"fi... | 2.546875 | stackv2 | import click
from itertools import tee
from .formats import read, write
from .matcher import matcher
DEFAULT_OUTPUT_FORMAT = 'json'
def get_options(all_options, *names):
return {k: v for k, v in all_options.items() if k in names}
@click.command()
@click.argument('source', type=click.File('rb'))
@click.option('... | 62 | 36.65 | 79 | 17 | 540 | python | [] | 0 | true | |
2024-11-18T21:37:23.505045+00:00 | 1,574,525,108,000 | fde57f8d73d91ebb7772b8cdfa87834e8351c0d6 | 4 | {
"blob_id": "fde57f8d73d91ebb7772b8cdfa87834e8351c0d6",
"branch_name": "refs/heads/master",
"committer_date": 1574525108000,
"content_id": "78d95c1ed8270e59b036522aca65e8d6e7ba48dd",
"detected_licenses": [
"MIT"
],
"directory_id": "b97b4e660acfb88102e5ca3c6232e55e51b40dec",
"extension": "py",
"fi... | 3.640625 | stackv2 | """
This is templates for common data structures and algorithms.
Frequently used in my leetcode practices.
"""
"""
Binary search
"""
nums, target
left, right = 0, len(nums) - 1
while left + 1 < right:
mid = (left + right) // 2
# might need modification to fit the problem.
if nums[mid] < target:
... | 356 | 20.42 | 85 | 16 | 1,987 | python | [] | 0 | true | |
2024-11-18T21:37:23.764419+00:00 | 1,599,141,798,000 | 8549fb67771db47abaf48b5571e497c79088951e | 2 | {
"blob_id": "8549fb67771db47abaf48b5571e497c79088951e",
"branch_name": "refs/heads/master",
"committer_date": 1599141798000,
"content_id": "dd01c0b89f0bd64104b0a6007ac5fd8bc0390d84",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "8f50c262f89d3dc4f15f2f67eb76e686b8f808f5",
"extension": "py"... | 2.390625 | stackv2 | # Copyright (C) 2002-2020 CERN for the benefit of the ATLAS collaboration
from __future__ import print_function
import six
""" EI classes"""
def cmp(x, y):
return (x > y) - (x < y)
class IOV(object):
_iovs={}
_cached={}
def __init__(self):
pass
def cmpBN(self,a,b):
# compare... | 133 | 25.54 | 104 | 15 | 875 | python | [] | 0 | true | |
2024-11-18T21:37:23.989137+00:00 | 1,544,029,407,000 | 93665350100022a925f07419ffe193fed53ccf29 | 2 | {
"blob_id": "93665350100022a925f07419ffe193fed53ccf29",
"branch_name": "refs/heads/master",
"committer_date": 1544029407000,
"content_id": "729d0446921a89121079bca870d9ec2c0998025e",
"detected_licenses": [
"MIT"
],
"directory_id": "ee1147b9ea9fcd32f22435f01c15b57a3f01c23e",
"extension": "py",
"fi... | 2.453125 | stackv2 | """CLI commands."""
import asyncio
import json
import click
import aiohttp
@click.group()
def commands():
"""Click group."""
@commands.command()
@click.option('--stop', '-S', type=int, default=None, required=1,
help="Stop ID of the stop you want information from.")
@click.option('--destination', '... | 49 | 31.86 | 72 | 15 | 324 | python | [] | 0 | true | |
2024-11-18T21:37:24.525529+00:00 | 1,636,894,460,000 | 0ce54058fbbdb0c973ec591131197aa22a2c06f3 | 3 | {
"blob_id": "0ce54058fbbdb0c973ec591131197aa22a2c06f3",
"branch_name": "refs/heads/master",
"committer_date": 1636894460000,
"content_id": "cb313870e73f0097c3850ed48e1ecff11840b8cb",
"detected_licenses": [
"MIT"
],
"directory_id": "3852e8a0a212fee97aa6aeef0d1c92237ca0cc8e",
"extension": "py",
"fi... | 3.203125 | stackv2 | # Methods used only for testing purposes #
from dbfread import DBF
from tabulate import tabulate
def print_table(path, amount):
table = DBF(path, load=True)
if amount <= 0:
amount = len(table.records)
fields = table.field_names
for i in range(amount):
record = table.records[i].valu... | 64 | 22.05 | 70 | 17 | 344 | python | [] | 0 | true | |
2024-11-18T21:37:24.691246+00:00 | 1,644,446,753,000 | 13c4f99c5f256bc397ac8fb0b1209d49d38b29a3 | 3 | {
"blob_id": "13c4f99c5f256bc397ac8fb0b1209d49d38b29a3",
"branch_name": "refs/heads/master",
"committer_date": 1644446753000,
"content_id": "439f6bedb8d6187c27b234d355e5b306606fd1a2",
"detected_licenses": [
"MIT"
],
"directory_id": "cbb7de48045e1b38c901c1d51ca1ee8f300178cc",
"extension": "py",
"fi... | 2.6875 | stackv2 | """Queenbee MetaData class.
This object provides metadata information for a package.
The specification is designed based on openapi info object:
https://swagger.io/specification/#infoObject
"""
from typing import List
from pydantic import Field, constr, AnyUrl
from .basemodel import BaseModel
class Maintainer(Bas... | 102 | 22.22 | 88 | 11 | 521 | python | [] | 0 | true | |
2024-11-18T21:37:25.006976+00:00 | 1,632,546,710,000 | b16a8fa4629a6140944bb706287e2be4201bbbcb | 3 | {
"blob_id": "b16a8fa4629a6140944bb706287e2be4201bbbcb",
"branch_name": "refs/heads/master",
"committer_date": 1632546710000,
"content_id": "0f6b99793472b4e33b502ca4c6e0a559cfcc0074",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "cdb1d297e596a705ffeb2c13cbf7e4c7986f3d9b",
"extension": "p... | 2.546875 | stackv2 | from operator import attrgetter
import click
from . import VERSION_STR, ExchangeRates, Banks
@click.group()
@click.version_option(version=VERSION_STR)
def entry_point():
"""Tools to query Bank of Russia."""
@entry_point.command()
@click.option('-c', '--currency', help='Currency to get info (e.g. USD, 840)')
@... | 64 | 23.34 | 83 | 15 | 404 | python | [] | 0 | true | |
2024-11-18T21:37:25.191146+00:00 | 1,684,402,651,000 | 571301c91faabcebd13b65bc543926bfc340e361 | 3 | {
"blob_id": "571301c91faabcebd13b65bc543926bfc340e361",
"branch_name": "refs/heads/master",
"committer_date": 1684403273000,
"content_id": "4fec73f97454fe743b14df8169df12a9cb3d09b2",
"detected_licenses": [
"MIT"
],
"directory_id": "f05bb251caa53af9823143aac78e8728c1ca1544",
"extension": "py",
"fi... | 3.046875 | stackv2 | # Copyright (c) 2020-2023, Matthew Broadway
# License: MIT License
from __future__ import annotations
from abc import ABC, abstractmethod, ABCMeta
from typing import Optional, Iterable
from ezdxf.addons.drawing.config import Configuration
from ezdxf.addons.drawing.properties import Properties, BackendProperties
from e... | 202 | 34.23 | 91 | 17 | 1,478 | python | [] | 0 | true | |
2024-11-18T21:37:25.251224+00:00 | 1,652,969,620,000 | c3eca9e66125cf146b12c3dff656b8cf74dc4549 | 3 | {
"blob_id": "c3eca9e66125cf146b12c3dff656b8cf74dc4549",
"branch_name": "refs/heads/master",
"committer_date": 1652969620000,
"content_id": "8fedf68c35ddf2d9658bff76ac5ab7d8410efcea",
"detected_licenses": [
"MIT"
],
"directory_id": "423244213eca7573f36157d08c94f95ce22968a5",
"extension": "py",
"fi... | 3 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Written by Lucas Sinclair and Paul Rougieux.
JRC Biomass Project.
Unit D1 Bioeconomy.
"""
# Built-in modules #
# Internal modules #
from forest_puller import module_dir
# First party modules #
from plumbing.cache import property_cached
# Third party modules #
imp... | 84 | 28.75 | 82 | 13 | 569 | python | [] | 0 | true | |
2024-11-18T21:37:25.390310+00:00 | 1,630,313,895,000 | f07231349f6c41992d3a4810e93e3465ec2303f9 | 3 | {
"blob_id": "f07231349f6c41992d3a4810e93e3465ec2303f9",
"branch_name": "refs/heads/main",
"committer_date": 1630313895000,
"content_id": "765907e5f463d213d504002e16922828c0716ddc",
"detected_licenses": [
"MIT"
],
"directory_id": "307913cc54df02a68a2dbff5f8853c7a1d2ecfd6",
"extension": "py",
"file... | 2.71875 | stackv2 | import numpy as np
import cv2
import argparse
from PIL import Image
import time
import os
from ocr.text_reader import OCR_Reader
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--img_path", help="path of the image",
required=True, type=str)
parser.add_argument(... | 55 | 24.44 | 74 | 13 | 349 | python | [] | 0 | true | |
2024-11-18T21:37:25.510000+00:00 | 1,638,987,768,000 | b173f434d0ae66e89bc0fa2e6ab70a7ed0012ad3 | 3 | {
"blob_id": "b173f434d0ae66e89bc0fa2e6ab70a7ed0012ad3",
"branch_name": "refs/heads/master",
"committer_date": 1638987768000,
"content_id": "bba1debfead895570b28c6f4f1511ac94546093d",
"detected_licenses": [
"BSD-3-Clause-LBNL",
"BSD-3-Clause"
],
"directory_id": "b2a8d0186a27083fa316b6deacc04b95a5d... | 3.40625 | stackv2 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from abc import ABC, abstractmethod
import numpy as np
from graphdot.codegen.cpptool import cpptype
from graphdot.util.pretty_tuple import pretty_tuple
class StartingProbability(ABC):
'''Assigns non-negative starting probabilities to each node of a graph.
Note tha... | 140 | 26.06 | 79 | 15 | 842 | python | [] | 0 | true | |
2024-11-18T21:37:25.804798+00:00 | 1,488,513,599,000 | c4add4252e73c16b9cf39da3b2489f2447c7efa4 | 2 | {
"blob_id": "c4add4252e73c16b9cf39da3b2489f2447c7efa4",
"branch_name": "refs/heads/master",
"committer_date": 1488513599000,
"content_id": "ab3a720dc3924268cf338b90d48758c3a263641e",
"detected_licenses": [
"MIT"
],
"directory_id": "03eec1770693b425eb85d5816c3f1b7b5e37d0f7",
"extension": "py",
"fi... | 2.453125 | stackv2 | #!/usr/bin/env python
"""
RS 2017/03/01: Simple target class to read in and hold JLA data
This reads in data files on type Ia supernova light curves from
"Improved cosmological constraints from a joint analysis
of the SDSS-II and SNLS supernova samples",
M. Betoule et al., A&A 568, A22 (2014).
I cal... | 156 | 40.85 | 79 | 16 | 1,782 | python | [] | 0 | true | |
2024-11-18T21:37:26.107802+00:00 | 1,516,022,787,000 | f388bede5f692ccd74ed53bc777aa1dba714a27b | 3 | {
"blob_id": "f388bede5f692ccd74ed53bc777aa1dba714a27b",
"branch_name": "refs/heads/master",
"committer_date": 1516022787000,
"content_id": "f149cac6784d33cd3f98c0ec242726f6f07e367e",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "ca8ac4c5a17f9d2b60d23a24279f46f8c83db032",
"extension": "py"... | 2.515625 | stackv2 | import abc as _abc
import sys as _sys
import threading as _threading
import time as _time
import logging as _logging
from six.moves import queue as _queue
from .queueing import Types, Entry
logger = _logging.getLogger(__name__)
class SkipEntry(Exception):
"""Exception to notify pipeline system to skip a partic... | 498 | 30.94 | 79 | 20 | 3,375 | python | [] | 0 | true | |
2024-11-18T21:37:30.033758+00:00 | 1,591,124,956,000 | f77ca32dfda49d411c075262580e81ba132893c3 | 4 | {
"blob_id": "f77ca32dfda49d411c075262580e81ba132893c3",
"branch_name": "refs/heads/master",
"committer_date": 1591124956000,
"content_id": "be33df4f0ce7376b46f2b50e2e14b31a5cb129f0",
"detected_licenses": [
"MIT"
],
"directory_id": "af7cf208a1e5c31569a6f587b91040e62716c133",
"extension": "py",
"fi... | 3.546875 | stackv2 | import random
numbers = ['Ace', '2', '3', '4', '5', '6', '7', '8',
'9', '10', 'Page', 'Knight', 'Queen', 'King']
group = ['Fool', 'Magician', 'High Priestess', 'Empress', 'Emperor', 'Hierophant', 'Lovers', 'Chariot', 'Strength', 'Hermit',
'Wheel of Fortune', 'Justice', 'Hanged Man', 'Death', 'Temp... | 144 | 34.78 | 139 | 22 | 1,181 | python | [] | 0 | true | |
2024-11-18T21:37:30.084459+00:00 | 1,631,439,332,000 | fbea9563b8f0cda9fb8dad5e4671780d2dcae9c9 | 3 | {
"blob_id": "fbea9563b8f0cda9fb8dad5e4671780d2dcae9c9",
"branch_name": "refs/heads/main",
"committer_date": 1631439332000,
"content_id": "62fd0e6e0b6f834a9663a27ea50d3a3529f84722",
"detected_licenses": [
"MIT"
],
"directory_id": "51ac0608921a5996d7dbee7547137b8c37d860a9",
"extension": "py",
"file... | 2.65625 | stackv2 | # Start Date: 3/9/2021
# Finished Date: 3/9/2021
# Author: Lucifer 14
# App Name: Chat App (Multi Client)
# Version: CLI Version 1.0
# Type: Server
import socket
import random
import threading
connection_list=[]
# generates random portnumber for client
def random_port_generator(address):
result_of_check = 0
... | 93 | 37.31 | 120 | 18 | 857 | python | [] | 0 | true | |
2024-11-18T21:37:30.133231+00:00 | 1,623,487,809,000 | 7267f28da0a6ff60fb357d0eecbaf974bf1dbf93 | 2 | {
"blob_id": "7267f28da0a6ff60fb357d0eecbaf974bf1dbf93",
"branch_name": "refs/heads/main",
"committer_date": 1623487809000,
"content_id": "15223e10a82c9baa8bf11e43911b3a8293f5a35b",
"detected_licenses": [
"MIT"
],
"directory_id": "eee8d4d870b20f607621de8f6806fa452543ec26",
"extension": "py",
"file... | 2.390625 | stackv2 | from scrapy.loader import ItemLoader
from .items import EquityItem
from itemloaders.processors import TakeFirst, MapCompose
def strip_vnd_to_int(text):
return int(text.replace(" VND", "").replace(",", ""))
def strip_sec_to_int(text):
return int(text.replace(" Securites", "").replace(",", ""))
class EquityLoa... | 17 | 32.47 | 63 | 12 | 135 | python | [] | 0 | true | |
2024-11-18T21:37:30.252540+00:00 | 1,623,872,635,000 | 7ff6c366197281b05563a0645b462a32612b98a5 | 3 | {
"blob_id": "7ff6c366197281b05563a0645b462a32612b98a5",
"branch_name": "refs/heads/master",
"committer_date": 1623872635000,
"content_id": "5fb1f5a2b3e922422966b3749da7b4eaa080ae69",
"detected_licenses": [
"MIT"
],
"directory_id": "0b0c9e0b2aaeaad345daa209238956fef2bd39d2",
"extension": "py",
"fi... | 2.515625 | stackv2 | import os
import math
import argparse
import pickle
from shutil import copyfile
from typing import Tuple
import pandas as pd
import numpy as np
import yaml
def load_model(model_filename, labels_filename):
with open(model_filename, 'rb') as f:
model = pickle.load(f)
with open(labels_filename, 'rb') as... | 115 | 34.16 | 111 | 16 | 1,048 | python | [] | 0 | true | |
2024-11-18T21:37:30.354729+00:00 | 1,666,317,371,000 | 7e6413d430f991ebb6040e5b9248c7dcd2493979 | 2 | {
"blob_id": "7e6413d430f991ebb6040e5b9248c7dcd2493979",
"branch_name": "refs/heads/master",
"committer_date": 1666317371000,
"content_id": "0dfc74484247208b066b8d82fe1024c636bf8c9f",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "de3ecaec375e8754002b8503e35f714fbbe8b3fb",
"extension": "py"... | 2.46875 | stackv2 | import requests
import logging
import copy
from .game_poco import EshopGame
from .eshop_costants import check_nsuid
import os
EU_GET_GAMES_URL = os.getenv(
'EU_GET_GAMES_URL', 'https://search.nintendo-europe.com/{locale}/select')
EU_GAME_CHECK_CODE = os.getenv('EU_GAME_CHECK_CODE', '70010000000184')
logger = logg... | 95 | 28.71 | 84 | 19 | 668 | python | [] | 0 | true | |
2024-11-18T21:37:30.775360+00:00 | 1,684,405,927,000 | eb18e168767a06b34775d99e5215888c70074698 | 3 | {
"blob_id": "eb18e168767a06b34775d99e5215888c70074698",
"branch_name": "refs/heads/main",
"committer_date": 1684405927000,
"content_id": "f8fb118e900008eeb1eea83e3c91b7c89027e4d3",
"detected_licenses": [
"MIT"
],
"directory_id": "c54ca055363bd7fd097e0b28a76fd16f487fa8b2",
"extension": "py",
"file... | 2.53125 | stackv2 | from django.db import models
from django.contrib.auth.models import User
from django.urls import reverse #Used to generate URLs by reversing the URL patterns
# Create your models here.
class BlogAuthor(models.Model):
user= models.OneToOneField(User,on_delete=models.SET_NULL, null= True)
bio= models.CharFiel... | 63 | 33.94 | 95 | 14 | 470 | python | [] | 0 | true | |
2024-11-18T21:37:30.836626+00:00 | 1,634,536,339,000 | fb5e4926430f9ea04301fefc22fb0e2455a0973d | 3 | {
"blob_id": "fb5e4926430f9ea04301fefc22fb0e2455a0973d",
"branch_name": "refs/heads/master",
"committer_date": 1634536339000,
"content_id": "b259a24cee86a35667b0e48494bf26d824b0d140",
"detected_licenses": [
"MIT"
],
"directory_id": "8dcbe0e9e194371b6a25c736bc70fc8a05265aed",
"extension": "py",
"fi... | 3.125 | stackv2 | class NonEmployeeException(Exception):
"""
Raised if it is likely that the given profile is somehow not actually a valid employee with a job title
Ex: User's 'job title' is 'Student'
"""
class EmailError(Exception):
"""
Raised if email data cannot be accessed
"""
class Employee:
"""
... | 28 | 32.89 | 111 | 14 | 210 | python | [] | 0 | true | |
2024-11-18T21:37:30.972999+00:00 | 1,649,476,535,000 | 43ef4efae314f37e046372e9ccd18c7cc4ab3930 | 3 | {
"blob_id": "43ef4efae314f37e046372e9ccd18c7cc4ab3930",
"branch_name": "refs/heads/master",
"committer_date": 1649476535000,
"content_id": "e827417e3cdacd58b3c6563a869501b75d47f11b",
"detected_licenses": [
"MIT"
],
"directory_id": "1f1a91a3e2bd5fb78a252f44327ab9d923783f80",
"extension": "py",
"fi... | 2.953125 | stackv2 | # -*- coding: utf-8 -*-
# @Time : 2019/4/4 9:21
# @Author : Alan
# @Email : xiezhengwen2013@163.com
# @File : sentenceSimilarity.py
# @Software: PyCharm
import gc
import tqdm
import numpy as np
from gensim import corpora, models, similarities
from sentence import Sentence
from collections import defaultdict
... | 122 | 27.2 | 107 | 14 | 897 | python | [] | 0 | true | |
2024-11-18T21:37:31.110880+00:00 | 1,595,588,037,000 | 7135776234943087d5fd41a1fd53fb0c2cf3a8f7 | 2 | {
"blob_id": "7135776234943087d5fd41a1fd53fb0c2cf3a8f7",
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"content_id": "f32e81b47f274647b3191cf706617019d744eccc",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "42c6356db85ac5bb83b3434a4a445b92736eb9c9",
"extension": "py"... | 2.484375 | stackv2 | import os
from fog05 import FIMAPI
from fog05_sdk.interfaces.FDU import FDU
import sys
import time
import json
DESC_FOLDER = './descriptors'
descs = {
'gw':'gw.json',
'ap':'vap.json',
'zenoh':'zenoh.json',
'server':'teleop-server.json',
'gui':'gui.json',
'motors':'motors.json',
'client':... | 88 | 19.99 | 62 | 13 | 510 | python | [] | 0 | true | |
2024-11-18T21:37:31.597448+00:00 | 1,647,903,567,000 | 9e643d4708d64982ed8f4f06f07740c92c65beae | 2 | {
"blob_id": "9e643d4708d64982ed8f4f06f07740c92c65beae",
"branch_name": "refs/heads/master",
"committer_date": 1647903567000,
"content_id": "9fcaf27a9d7eb331b1139f46cefcebdce6d428dd",
"detected_licenses": [
"MIT"
],
"directory_id": "817478a20813b1703d9727c0e61fe140cf6a5061",
"extension": "py",
"fi... | 2.359375 | stackv2 | import os.path as osp
from PIL import Image
import random
from torch.utils.data import Dataset
from torchvision import transforms
import numpy as np
import h5py
class OpenMIC_Data(Dataset):
def __init__(self, setname, data_path):
data = None
lb = -1
all_labels = []
for i in range(l... | 62 | 28.39 | 77 | 18 | 391 | python | [] | 0 | true | |
2024-11-18T21:37:31.675759+00:00 | 1,527,060,155,000 | eea9ed7010b3b6b09e17de11a46c519a95a2c24b | 3 | {
"blob_id": "eea9ed7010b3b6b09e17de11a46c519a95a2c24b",
"branch_name": "refs/heads/master",
"committer_date": 1527060155000,
"content_id": "3b47887029afa97caea800005df87df2eb02568f",
"detected_licenses": [
"MIT"
],
"directory_id": "f1e24cc954c0abdb46e136327db0ca8ee1c6a14c",
"extension": "py",
"fi... | 3.140625 | stackv2 | # -*- coding=utf-8 -*-
from __future__ import absolute_import, print_function, unicode_literals
# base implementation of Chain of Responsibility Pattern
class DefaultHandler(object):
def __init__(self, successor=None):
self.__successor = successor
def handler(self, event):
if self.__succes... | 63 | 26.11 | 111 | 18 | 390 | python | [] | 0 | true | |
2024-11-18T21:37:31.737634+00:00 | 1,548,273,649,000 | aa46e46137e399ee885a0afda05a73c7b7393162 | 3 | {
"blob_id": "aa46e46137e399ee885a0afda05a73c7b7393162",
"branch_name": "refs/heads/master",
"committer_date": 1548273649000,
"content_id": "345e913d4bb5f37ee2ebdabc8a52c21ea81dcef7",
"detected_licenses": [
"MIT"
],
"directory_id": "de3c035f725b54bf4785f8e526ba9b99bf9a23e4",
"extension": "py",
"fi... | 2.734375 | stackv2 | import pandas as pd
DB_PATH = '/Users/yienxu/Desktop/Dropbox/Python/STAT479/Unihan/Unihan_DictionaryLikeData.txt'
SAVE_PATH = '/Users/yienxu/Desktop/Dropbox/Python/STAT479/counts.csv'
if __name__ == '__main__':
df = pd.read_csv(DB_PATH, encoding='UTF-8', delim_whitespace=True, comment='#',
na... | 20 | 35.1 | 93 | 15 | 213 | python | [] | 0 | true | |
2024-11-18T21:37:34.050833+00:00 | 1,534,329,127,000 | 7c705635de8a5f3ca58737b10a6e86bc518854a7 | 4 | {
"blob_id": "7c705635de8a5f3ca58737b10a6e86bc518854a7",
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"committer_date": 1534329127000,
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"detected_licenses": [
"MIT"
],
"directory_id": "1ac33c5ffc06fe8fc8ae9e5fe4ad47d123bbcc5b",
"extension": "py",
"fi... | 3.953125 | stackv2 | #!/usr/bin/python
# -*- coding: utf-8 -*-
'''
1723. Sandro's Book
Time limit: 0.5 second
Memory limit: 64 MB
[Description]
It's been quite a number of years since Lich Sandro retired. Sometimes in the
evenings, when he feels especially lonely, he takes a book that was presented
to him by his student magicians on the ... | 69 | 29.19 | 79 | 14 | 530 | python | [] | 0 | true | |
2024-11-18T21:37:34.190591+00:00 | 1,618,052,566,000 | 6a8bc6826a880465e235c4071095c47b2708784e | 3 | {
"blob_id": "6a8bc6826a880465e235c4071095c47b2708784e",
"branch_name": "refs/heads/main",
"committer_date": 1618052566000,
"content_id": "bc6f2ef810477f99657f251ddee0e6ebdabd0566",
"detected_licenses": [
"MIT"
],
"directory_id": "ae95d07deb432cc4b02449c03b67dd20ac36f465",
"extension": "py",
"file... | 2.546875 | stackv2 | import time
import ssl
import asyncio
import aiohttp
import click
from .model import URLStatus
from .kafka import Producer
# https://stackoverflow.com/a/57017274/482899
async def fetch(session: aiohttp.ClientSession, url: str, kafka_producer: Producer) -> URLStatus:
start = time.time_ns()
async with session.... | 46 | 35.72 | 97 | 17 | 386 | python | [] | 0 | true | |
2024-11-18T21:37:34.456439+00:00 | 1,477,057,321,000 | 0a3cfbd6a657c727a64f5bddcc2439fc1fbc9675 | 2 | {
"blob_id": "0a3cfbd6a657c727a64f5bddcc2439fc1fbc9675",
"branch_name": "refs/heads/master",
"committer_date": 1477057321000,
"content_id": "49ce733fc950cbae2471a417cac47ae41ec5beca",
"detected_licenses": [
"MIT"
],
"directory_id": "684403f73a0d54054d71c310c80323e5f9e362cd",
"extension": "py",
"fi... | 2.359375 | stackv2 | import os
from datetime import datetime
from werkzeug.http import http_date
from werkzeug.wsgi import wrap_file
def application(environ, start_response):
"""
Small WSGI application as helper for development.
Always send the index.html without any caching. This is only used for
Crossbar's built-in w... | 29 | 30.07 | 73 | 11 | 210 | python | [] | 0 | true | |
2024-11-18T21:37:34.520287+00:00 | 1,616,362,760,000 | ed14040f00e664f52f33887f6f5723da5f1bb973 | 3 | {
"blob_id": "ed14040f00e664f52f33887f6f5723da5f1bb973",
"branch_name": "refs/heads/master",
"committer_date": 1616362760000,
"content_id": "77538f44a2382e024e2392f834d3ed6c46d5547f",
"detected_licenses": [
"MIT"
],
"directory_id": "dbfbb9198b9e2428b5c46e21eb82eb93038621ed",
"extension": "py",
"fi... | 2.578125 | stackv2 | from numpy.linalg import inv
import numpy as np
import cv2
class EstimateTranslation:
def __init__(self):
self.WINDOW_SIZE = 25
def estimateAllTranslation(self, startXs, startYs, img1, img2):
I = cv2.cvtColor(img1, cv2.COLOR_RGB2GRAY)
I = cv2.GaussianBlur(I, (5, 5), 0.2)
Iy, ... | 105 | 33.84 | 122 | 15 | 1,157 | python | [] | 0 | true | |
2024-11-18T21:37:34.579033+00:00 | 1,625,149,000,000 | 861d013a5e6c38b80918e12338e9461d1cd106e4 | 3 | {
"blob_id": "861d013a5e6c38b80918e12338e9461d1cd106e4",
"branch_name": "refs/heads/main",
"committer_date": 1625149000000,
"content_id": "467b9c78ee88b4376f0402de5c73e17584875e4e",
"detected_licenses": [
"MIT"
],
"directory_id": "d5b9b8d67bd46c5fabfac6fc08763570ea0001c8",
"extension": "py",
"file... | 2.53125 | stackv2 | import paho.mqtt.client as mqtt
class Mqtt_Client(mqtt.Client):
USERNAME = "ENTER_USERNAME_HERE"
PASSWORD = "ENTER_PASSWORD_HERE"
BROKER_IP = "ENTER_BROKER_IP_HERE"
BROKER_PORT = 1883
TOPIC = "ENTER_MQTT_TOPIC_HERE"
def __init__(self, motor, app):
super().__init__()
self.mo... | 33 | 29.09 | 72 | 14 | 245 | python | [] | 0 | true | |
2024-11-18T21:37:34.874428+00:00 | 1,525,333,539,000 | a0f3a23185a1a610248968af28993034975670e7 | 2 | {
"blob_id": "a0f3a23185a1a610248968af28993034975670e7",
"branch_name": "refs/heads/master",
"committer_date": 1525333539000,
"content_id": "510b5f9a06949a5a06dc6a2e9125bb4cf0474c90",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "13c984cd2177368940446d6f51d43b32c278a592",
"extension": "py"... | 2.359375 | stackv2 | import numpy as np
import random
import keras
from keras.models import load_model, Sequential, Model
from keras.layers.convolutional import Convolution2D
from keras.optimizers import Adam
from keras.layers.core import Activation, Dropout, Flatten, Dense
from keras.layers import merge, Input
from keras import backend as... | 149 | 48.63 | 134 | 18 | 1,796 | python | [] | 0 | true | |
2024-11-18T21:37:36.144473+00:00 | 1,589,174,053,000 | dc0dda357c7de6569bbb53cd46944fc5c0df2c93 | 3 | {
"blob_id": "dc0dda357c7de6569bbb53cd46944fc5c0df2c93",
"branch_name": "refs/heads/master",
"committer_date": 1589174053000,
"content_id": "d3c38cf4282e745e212107990cb2850cba2fe9cd",
"detected_licenses": [
"MIT"
],
"directory_id": "ed33b0adc3e3b9143eba9dc9a349a3df0309f8d3",
"extension": "py",
"fi... | 2.703125 | stackv2 | # -*- coding: utf-8 -*-
"""
Mocks for the CircleCLI API library tests.
"""
from httmock import response, urlmatch
NETLOC = r'(.*\.)?[^.]+\.com$'
HEADERS = {'content-type': 'application/json'}
GET = 'get'
DELETE = 'delete'
class Resource:
""" A CircleCli resource.
:param path: The file path to the resourc... | 69 | 24.74 | 78 | 13 | 466 | python | [] | 0 | true | |
2024-11-18T21:37:36.355657+00:00 | 1,557,455,548,000 | 10b06696060731dd46128d08a796784b4c4886a8 | 3 | {
"blob_id": "10b06696060731dd46128d08a796784b4c4886a8",
"branch_name": "refs/heads/master",
"committer_date": 1557455548000,
"content_id": "0250af74d9aaa77650eaf36fe17a7bf7e4f87853",
"detected_licenses": [
"MIT"
],
"directory_id": "3c517ff94e7687858adf48e2bb7bcf4609d0674f",
"extension": "py",
"fi... | 3.421875 | stackv2 | #!/usr/bin/env python
from __future__ import annotations
import math
from typing import Union, Tuple
NumericType = Union[float, int]
AngleType = Union[float, int, 'RadianAngle']
VectorType = Union['Vector', 'PolarVector']
class Vector(tuple):
def __new__(cls, x: float, y: float):
if type(x) == int:
... | 166 | 33.57 | 104 | 15 | 1,597 | python | [] | 0 | true | |
2024-11-18T21:37:36.416998+00:00 | 1,519,962,650,000 | 154e18746a03d3d7209b7605cc464b710a8aa3e2 | 3 | {
"blob_id": "154e18746a03d3d7209b7605cc464b710a8aa3e2",
"branch_name": "refs/heads/master",
"committer_date": 1519962650000,
"content_id": "42708bd833a7dbe0c24134ac93f88769124a2fe4",
"detected_licenses": [
"MIT"
],
"directory_id": "1421d61938dafd86bf8195d0e24acb454e10ddb4",
"extension": "py",
"fi... | 2.96875 | stackv2 | import numpy as np
import pandas as pd
import math
import logging
import json
from scipy import signal
import sys
logging.basicConfig(filename="hrm.log",
format='%(asctime)s %(message)s',
datefmt='%m/%d/%Y %I:%M:%S %p')
class hrm:
def __init__(self, csvdata):
self... | 247 | 40.18 | 79 | 22 | 2,228 | python | [] | 0 | true | |
2024-11-18T21:37:36.537856+00:00 | 1,609,687,478,000 | 49d806b117e61a3194651a75884292110f54c01f | 3 | {
"blob_id": "49d806b117e61a3194651a75884292110f54c01f",
"branch_name": "refs/heads/master",
"committer_date": 1609687478000,
"content_id": "6d58ef85ffa5dd6729e466fd4933fae2b80446aa",
"detected_licenses": [
"MIT"
],
"directory_id": "17906411536000327b79008e2b3d4e12c40f0109",
"extension": "py",
"fi... | 3.40625 | stackv2 | import numpy as np
from _data import DataSets
from _math import ActivationFunctions, MathUtils
from _plot import PlotUtils
class Adaline:
def __init__(self, n, g, e):
self.n = n # learning rate
self.g = g # activation function
self.e = e # error variation tolerance
self.plot_data_x... | 76 | 29.3 | 75 | 20 | 626 | python | [] | 0 | true | |
2024-11-18T21:37:36.714190+00:00 | 1,546,412,517,000 | b31a952ef40d0fa9ad26ac9adfa4eef905942389 | 3 | {
"blob_id": "b31a952ef40d0fa9ad26ac9adfa4eef905942389",
"branch_name": "refs/heads/master",
"committer_date": 1546412517000,
"content_id": "10f565dfebc72ee60e583832afcc81f4be37d558",
"detected_licenses": [
"MIT"
],
"directory_id": "6874e4593fbabeca685976e3b4c96aaf32680a96",
"extension": "py",
"fi... | 2.53125 | stackv2 | import functools
import sfs.log_utils as log
import sfs.events as events
def cli_command(command_key):
"""Decorator for registering and logging CLI commands"""
def _decorator(fn):
@functools.wraps(fn)
@events.subscriber(events.command_key(command_key), unique=True)
def wrapper(args):... | 25 | 25.8 | 85 | 16 | 132 | python | [] | 0 | true | |
2024-11-18T21:37:40.388296+00:00 | 1,585,160,915,000 | e59c674b5f2b1c6352f5cd9486ac0933875a62c4 | 4 | {
"blob_id": "e59c674b5f2b1c6352f5cd9486ac0933875a62c4",
"branch_name": "refs/heads/master",
"committer_date": 1585160915000,
"content_id": "b7b7ff4605f8f020eb38ba2268be5441e180c263",
"detected_licenses": [
"MIT"
],
"directory_id": "d79cf0cd5d144abcc4376d9c041315e696742458",
"extension": "py",
"fi... | 3.765625 | stackv2 | def usuario_escolhe_jogada(n, m):
if n<=0:
pass
else:
aux = True # Varialvel para criar um laco
while aux: # Laco
escolha = int(input("Quantas peças você vai tirar? "))
if (escolha <= m)and (escolha>0): # Validando a entrada do usuario
aux = False... | 98 | 38.56 | 152 | 19 | 1,121 | python | [] | 0 | true | |
2024-11-18T21:37:40.841030+00:00 | 1,479,053,523,000 | 051c65f193e88e1887e2677443128b64ff87eb19 | 3 | {
"blob_id": "051c65f193e88e1887e2677443128b64ff87eb19",
"branch_name": "refs/heads/master",
"committer_date": 1479053523000,
"content_id": "92b9e0d9af07158dfce74b444aff4af8c27541d2",
"detected_licenses": [
"MIT"
],
"directory_id": "454c2b7188e0518371c5fccfe83e121220bfd34e",
"extension": "py",
"fi... | 2.640625 | stackv2 | import os
from argparse import ArgumentParser
import h5py
import numpy as np
from ncp.preprocessing import held_out
HDF5_DATASETS = ['Representation', 'Labels', 'Targets', 'RegressionMask']
def offline_preproc_activitynet(filename, newfile, hdf5_datasets=HDF5_DATASETS,
ratio=0.45):
... | 65 | 34.09 | 79 | 15 | 536 | python | [] | 0 | true | |
2024-11-18T21:37:41.021465+00:00 | 1,692,307,321,000 | 78d31a3fd266f089c9702d8fe7a838f1c9136179 | 2 | {
"blob_id": "78d31a3fd266f089c9702d8fe7a838f1c9136179",
"branch_name": "refs/heads/master",
"committer_date": 1692307321000,
"content_id": "37a65a96d1337be8a199376e606e0e0264c15e4a",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "6af90d24f1f081c1f1046346dc1c7cdb98bcaddb",
"extension": "py"... | 2.3125 | stackv2 | '''
Virtual target capture tasks where cursors are controlled by physical
motion interfaces such as joysticks
'''
import numpy as np
from scipy.spatial.transform import Rotation as R
from riglib.experiment import traits
from .target_graphics import *
from .target_capture_task import ScreenTargetCapture, ScreenReachAn... | 257 | 35.98 | 159 | 16 | 2,715 | python | [] | 0 | true | |
2024-11-18T21:37:41.145156+00:00 | 1,405,445,467,000 | 3ce8166b9bda4139e8b72711bc67c91923587d4f | 3 | {
"blob_id": "3ce8166b9bda4139e8b72711bc67c91923587d4f",
"branch_name": "refs/heads/master",
"committer_date": 1405445467000,
"content_id": "f4a6b1db21700be9375b5c09f322357fe00bf1c2",
"detected_licenses": [
"MIT"
],
"directory_id": "554cef0e84bd1f9ee80a44b3b7b33c49c4e36748",
"extension": "py",
"fi... | 2.703125 | stackv2 | #!/usr/bin/env python
'''
clean_visible maintains byte position of all visible text in an HTML (or
XML) document and removes all of parts that are not visible in a web
browser. This allows taggers to operate on the visible-only text and
any standoff annotation can refer to the original byte positions.
This software i... | 233 | 35.77 | 98 | 19 | 1,944 | python | [] | 0 | true | |
2024-11-18T21:37:41.206252+00:00 | 1,529,553,458,000 | c218beb88996088c20bf9eeef495fc05eaf8a15c | 2 | {
"blob_id": "c218beb88996088c20bf9eeef495fc05eaf8a15c",
"branch_name": "refs/heads/master",
"committer_date": 1529553458000,
"content_id": "340261ff737dda8b2466c8d89962cc41473714f8",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "5cc70ba3ae9187b9d82810204c308862113036b7",
"extension": "py"... | 2.4375 | stackv2 | import argparse
import os
# only support bieo
# PROBLEM = ["E-problem", "B-problem", "I-problem"]
# TREATMENT = ["E-treatment", "B-treatment", "I-treatment"]
# TEST = ["I-test", "B-test", "E-test"]
PROBLEM = ["B-problem"]
TREATMENT = ["B-treatment"]
TEST = ["B-test"]
def main(fname):
# fname = "../dev.eval"
... | 91 | 28.74 | 80 | 19 | 625 | python | [] | 0 | true | |
2024-11-18T21:37:42.106883+00:00 | 1,602,176,008,000 | b5a821ed285499b2c807c052a4e00c2a093ac3b3 | 2 | {
"blob_id": "b5a821ed285499b2c807c052a4e00c2a093ac3b3",
"branch_name": "refs/heads/master",
"committer_date": 1602176008000,
"content_id": "5a01e21958c867a11429e44cffb9bcb12555ebee",
"detected_licenses": [
"MIT"
],
"directory_id": "2dd335bb79f1c1c42cfbf2f76277fa1422752aa4",
"extension": "py",
"fi... | 2.40625 | stackv2 | from flask import Flask, jsonify, request
from flask_cors import CORS
from gevent.pywsgi import WSGIServer
import argparse
import multiprocessing as mp
import os
from solver import Solver
# Declare a flask app
app = Flask(__name__)
# Enable CORS
cors = CORS(app)
# Global variables
# Constants
PORT = 5000
# Pla... | 106 | 33.81 | 105 | 12 | 902 | python | [] | 0 | true | |
2024-11-18T21:37:42.214602+00:00 | 1,585,131,763,000 | a7c66838775271c23e803c04bfb88b43a4ca751b | 3 | {
"blob_id": "a7c66838775271c23e803c04bfb88b43a4ca751b",
"branch_name": "refs/heads/master",
"committer_date": 1585131763000,
"content_id": "dcf2f121d7d10bf4db56ea57e6e7bd98bb03190c",
"detected_licenses": [
"MIT"
],
"directory_id": "62cacaf4e9ce1bae426784882905e8aabf7dc521",
"extension": "py",
"fi... | 2.921875 | stackv2 | from fake_useragent import UserAgent
from requests_html import HTMLSession
import requests_html
from time import sleep
import traceback
from random import random
session = HTMLSession()
ua = UserAgent()
def fetch(url: str) -> requests_html.HTML:
tries = 6
while tries:
request = session.get(url,... | 54 | 20.89 | 93 | 14 | 302 | python | [] | 0 | true | |
2024-11-18T21:37:42.327653+00:00 | 1,589,211,473,000 | 4eefb4987f1b7556b00776780dd48e0424989594 | 3 | {
"blob_id": "4eefb4987f1b7556b00776780dd48e0424989594",
"branch_name": "refs/heads/master",
"committer_date": 1589211473000,
"content_id": "4cbcf70b7a219ad9ae7b30f09f329612c1814ba1",
"detected_licenses": [
"MIT"
],
"directory_id": "af86d25d86c12832715168da41fdb56ae83d1002",
"extension": "py",
"fi... | 2.875 | stackv2 | #!/usr/bin/env python3
"""
Author : Tania Chakraborty (taniac101)
Date : 2020-04-26
Purpose: Parsing SwissProt records
"""
import argparse
import os
import sys
from Bio import SeqIO
# --------------------------------------------------
def get_args():
"""Get command-line arguments"""
parser = argparse.Argum... | 73 | 32.49 | 74 | 18 | 481 | python | [] | 0 | true | |
2024-11-18T21:37:42.374946+00:00 | 1,658,413,343,000 | 40fbdecb9e3c6ad8c1766cb4576666b358eb06b1 | 2 | {
"blob_id": "40fbdecb9e3c6ad8c1766cb4576666b358eb06b1",
"branch_name": "refs/heads/master",
"committer_date": 1658413343000,
"content_id": "96878c862091adea8ee76d588aeab61ee226cd5c",
"detected_licenses": [
"MIT"
],
"directory_id": "76f9436dc1d4e9689005a025217aade455c9b9cd",
"extension": "py",
"fi... | 2.359375 | stackv2 | # -*- coding: utf-8 -*-
__author__ = 'S.I. Mimilakis'
__copyright__ = 'Fraunhofer IDMT'
# imports
import torch
from nn_modules import sk_iter as sk
bce_logitloss_func = torch.nn.BCEWithLogitsLoss()
bce_func = torch.nn.BCELoss()
_eps = 1e-24
def neg_snr(x, xhat):
res_val = -10. * torch.log10(torch.norm(x, 2.).po... | 60 | 26.43 | 116 | 21 | 617 | python | [] | 0 | true | |
2024-11-18T21:37:42.517545+00:00 | 1,648,756,313,000 | ecec55e6183143eb09a8fa8c74372951f40f4678 | 4 | {
"blob_id": "ecec55e6183143eb09a8fa8c74372951f40f4678",
"branch_name": "refs/heads/master",
"committer_date": 1648756313000,
"content_id": "431b8fbed0248d6e6403cabfad93a78119d668e9",
"detected_licenses": [
"MIT"
],
"directory_id": "70e8175d2011026dd6e07bf14a1fb7d89cc2a71c",
"extension": "py",
"fi... | 3.5 | stackv2 | """
Compress lists of integers to range objects
Do you have a list of integers? Do you want to know what ranges of consecutive
values the list covers? Do you need to solve a `gaps and islands
<https://stackoverflow.com/tags/gaps-and-islands/info>`_ problem outside of
SQL? Maybe you have a list of dates and need to ... | 242 | 35.91 | 83 | 24 | 2,272 | python | [] | 0 | true | |
2024-11-18T21:37:42.658925+00:00 | 1,597,131,299,000 | 96675bf56f03f94d14c12791b137ad867aefec2b | 2 | {
"blob_id": "96675bf56f03f94d14c12791b137ad867aefec2b",
"branch_name": "refs/heads/master",
"committer_date": 1597131299000,
"content_id": "7d1fd50aaa2442536583a30bc20784b2ae0e6a62",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "81579ecd0678d652bbb57ff97529631fcfb74b12",
"extension": "p... | 2.40625 | stackv2 | import os
import zipfile
from collections import Counter
from django.core.management.base import BaseCommand, CommandError
from corehq.apps.dump_reload.couch.load import (
CouchDataLoader,
DomainLoader,
ToggleLoader,
)
from corehq.apps.dump_reload.exceptions import DataExistsException
from corehq.apps.dum... | 97 | 45.62 | 114 | 16 | 915 | python | [] | 0 | true | |
2024-11-18T21:37:42.906422+00:00 | 1,505,936,826,000 | 9635f21a9e4b5806fba49a7f7aa85f36a1b58348 | 3 | {
"blob_id": "9635f21a9e4b5806fba49a7f7aa85f36a1b58348",
"branch_name": "refs/heads/master",
"committer_date": 1505936826000,
"content_id": "294f36ce32803a4cbf49baf95701749a6e550f8f",
"detected_licenses": [
"MIT"
],
"directory_id": "802e19352540c7261589b8a917f2152ca1f336c1",
"extension": "py",
"fi... | 2.546875 | stackv2 | import feedparser
from datetime import datetime
import time
import socket
from threading import Thread
import json
import os
from cl_email import CL_Email
from cl_post import CL_Post
from log import Logging
def CheckNotityInterval(notification_intervals):
for notify_time, notify_sent_flag in notification_interva... | 215 | 34.7 | 129 | 21 | 1,744 | python | [] | 0 | true | |
2024-11-18T21:37:42.961551+00:00 | 1,592,495,243,000 | a8d96b8a2e5f6ea7f0d4312d04f529c2fe81e8ee | 3 | {
"blob_id": "a8d96b8a2e5f6ea7f0d4312d04f529c2fe81e8ee",
"branch_name": "refs/heads/master",
"committer_date": 1592495243000,
"content_id": "f37222a7e0a7bb148a80996cd16cbbea10393f21",
"detected_licenses": [
"Apache-2.0",
"MIT"
],
"directory_id": "9be3096da9c98d900e4467514946a0fa8e4a7594",
"exten... | 2.671875 | stackv2 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import unicodedata
import collections
import random
from matplotlib.pyplot import imshow
from PIL import Image, ImageDraw, ImageFont
from pathlib import Path
import PIL
get_ipython().run_line_magic('matplotlib', 'inline')
PIL.PILLOW_VERSION
# In[2]:
RUS_LETTERS ... | 120 | 19.03 | 88 | 14 | 830 | python | [] | 0 | true | |
2024-11-18T21:37:43.079387+00:00 | 1,560,729,294,000 | 7230765f90cf0740224bf06d49daa32e512290c0 | 3 | {
"blob_id": "7230765f90cf0740224bf06d49daa32e512290c0",
"branch_name": "refs/heads/master",
"committer_date": 1560729294000,
"content_id": "01b453c16c59a2aa90bbeeb54a4438679fa087cc",
"detected_licenses": [
"MIT"
],
"directory_id": "d75bddaef84cd4d6bdf7a0e5ecc8ac141ebb2ef1",
"extension": "py",
"fi... | 2.828125 | stackv2 | import sqlite3
import pandas as pd
initial_money = 100000
conn=sqlite3.connect("database.db")
cur=conn.cursor()
cur.execute("DROP TABLE IF EXISTS User;")
cur.execute("DROP TABLE IF EXISTS Super_user;")
cur.execute("DROP TABLE IF EXISTS Stock;")
cur.execute("DROP TABLE IF EXISTS Stock_price;")
conn.commit()
cur.execu... | 24 | 34.71 | 93 | 9 | 203 | python | [] | 0 | true | |
2024-11-18T21:37:43.681110+00:00 | 1,586,882,713,000 | f2492c3e1cbf30815a98ca8fad7b22c7daa1e45b | 3 | {
"blob_id": "f2492c3e1cbf30815a98ca8fad7b22c7daa1e45b",
"branch_name": "refs/heads/master",
"committer_date": 1586882713000,
"content_id": "8283fb7aa7ebcf7474ef2245090cae5d85f2e105",
"detected_licenses": [
"MIT"
],
"directory_id": "5b495c14d81a1ffb441a0b8589978a324b395116",
"extension": "py",
"fi... | 3.421875 | stackv2 | import csv
import logging
import os
class DataExporter:
"""
Dataset creator in CSV format where data set is in form of the following structure
Format:
{
'Red Country': {
'Orange Table': {
'x': ['Day1', 'Day2', ..., 'Day8'],
'y': [8, 7, ..., 1]
... | 68 | 35.31 | 122 | 20 | 536 | python | [] | 0 | true | |
2024-11-18T21:37:43.861745+00:00 | 1,565,272,886,000 | 38ef7703ed5dc964cec93a4780af53cd00d6dc4e | 3 | {
"blob_id": "38ef7703ed5dc964cec93a4780af53cd00d6dc4e",
"branch_name": "refs/heads/master",
"committer_date": 1565272886000,
"content_id": "fd9c4c3513d2c7585a0d6c621ed8faf552ebf2f4",
"detected_licenses": [
"MIT"
],
"directory_id": "e86d743a93e61aebd60e65ab0f0570bc67d5f2ee",
"extension": "py",
"fi... | 2.875 | stackv2 | import numpy as np
###Best-fit parameters:
params=[2,79,0.00153,0.01,0.1976,0.7902,0.2010]
def runmodel(t_max,moi,params,s=1,H=1000):
tlist=[]
datalist=[]
###Parameters
r_max=params[0]
x_max=params[1]
Gamma_a=params[2]
Gamma_ar=params[3]
Gamma_x_a=params[4]
Gamma_x_ar=params[5]
Gamma_r=params[6]
###Stoch... | 125 | 23.14 | 149 | 25 | 1,071 | python | [] | 0 | true | |
2024-11-18T21:37:43.914635+00:00 | 1,547,840,012,000 | 786d25cd6ef3257ee7e31b741ad4c95a609fb79f | 3 | {
"blob_id": "786d25cd6ef3257ee7e31b741ad4c95a609fb79f",
"branch_name": "refs/heads/master",
"committer_date": 1547840012000,
"content_id": "42133fb94005636398c7ca264046dd1cbca8010f",
"detected_licenses": [
"MIT"
],
"directory_id": "f1183482e47167a9020046c061a53b88179193ec",
"extension": "py",
"fi... | 2.875 | stackv2 | """
Extracts medication information from the validation cohort.
"""
import collections
import feather
import pandas as pd
from click import *
from logging import *
COLUMNS = collections.OrderedDict(
[('ID', 'subject_id'), ('TIMEFRAME', 'visit_id'),
('IAS', 'medication_joint_injections'), ('NSAID', 'medicati... | 75 | 19.35 | 76 | 15 | 372 | python | [] | 0 | true | |
2024-11-18T21:37:44.396584+00:00 | 1,617,164,330,000 | 34e49115d08ca6ba5623a7de4d21da106dbc7c10 | 3 | {
"blob_id": "34e49115d08ca6ba5623a7de4d21da106dbc7c10",
"branch_name": "refs/heads/main",
"committer_date": 1617164330000,
"content_id": "8fdef91350e4ad21fff908cf2ebd254790a95085",
"detected_licenses": [
"MIT"
],
"directory_id": "b7ec2b940664e9a7175e53008d61dc704af49247",
"extension": "py",
"file... | 2.515625 | stackv2 | ########################################################
## constants.py - A module to load constants
########################################################
## Author: Jeremiah White
## License: MIT License
## Version: 1.0.1
## Email: jeremiah.white@gmail.com
########################################################
... | 51 | 39.02 | 78 | 13 | 467 | python | [] | 0 | true | |
2024-11-18T21:37:44.509317+00:00 | 1,588,755,503,000 | 3c9b1ccb9f01efed0d34a518b7bb2b7d1e3fc7b5 | 3 | {
"blob_id": "3c9b1ccb9f01efed0d34a518b7bb2b7d1e3fc7b5",
"branch_name": "refs/heads/master",
"committer_date": 1588755503000,
"content_id": "c21e689f3600b73e20134fd3db028c1e43f49cde",
"detected_licenses": [
"MIT"
],
"directory_id": "75fbe38c66b756704a0f0ba01fbbd0a4725536a5",
"extension": "py",
"fi... | 2.65625 | stackv2 | # -*- coding: utf-8 -*-
"""
Created on Sat May 2 10:47:12 2020
@author: max
"""
from bs4 import BeautifulSoup
import requests
import re
class Menu():
def __init__(self,URL='http://www.99kubo.tv'):
html = requests.get(URL).text
self.soup = BeautifulSoup(html, 'lxml')
self.URL=URL
... | 53 | 33.53 | 179 | 20 | 485 | python | [] | 0 | true | |
2024-11-18T21:37:44.731778+00:00 | 1,606,773,549,000 | ce9a9ca8dc27a0bab0b5de7b3fd84382e61742a8 | 2 | {
"blob_id": "ce9a9ca8dc27a0bab0b5de7b3fd84382e61742a8",
"branch_name": "refs/heads/master",
"committer_date": 1606773549000,
"content_id": "f9f8157bd9a832c313aaaffacee4ec8fb954024b",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "411d9653cf8c7e0137ebbd9b7806edf602b0975b",
"extension": "py"... | 2.484375 | stackv2 | import sys
from django.contrib.auth.models import User
from django.core.management.base import BaseCommand
from django.db import IntegrityError
from Harvest.utils import get_logger
logger = get_logger(__name__)
class Command(BaseCommand):
help = "Create a superuser with a given username and password"
_type... | 32 | 31.06 | 78 | 18 | 197 | python | [] | 0 | true | |
2024-11-18T21:37:44.824871+00:00 | 1,518,051,887,000 | 553cf16303cc423b3987c5da79b263a3f393c403 | 3 | {
"blob_id": "553cf16303cc423b3987c5da79b263a3f393c403",
"branch_name": "refs/heads/master",
"committer_date": 1518051887000,
"content_id": "5ef88b52f1634408f0a92eeffbca6b99abbf8743",
"detected_licenses": [
"MIT"
],
"directory_id": "49a676cd3a0b92cb07c9ff846ae77c41c893f03f",
"extension": "py",
"fi... | 2.515625 | stackv2 | import nmslib
import numpy as np
import scipy as sp
from sklearn.neighbors import NearestNeighbors
def knn(data, k=50, method='sklearn', verbose=False, **kwargs):
assert method in ('sklearn', 'nmslib'), 'No such knn method'
if method == 'sklearn':
return __knn_sklearn(data, k, verbose=verbose)
el... | 60 | 26.63 | 72 | 11 | 455 | python | [] | 0 | true | |
2024-11-18T21:37:45.545076+00:00 | 1,624,481,966,000 | 2b7e86e1417fba7929522048af4b47f4a16690aa | 3 | {
"blob_id": "2b7e86e1417fba7929522048af4b47f4a16690aa",
"branch_name": "refs/heads/main",
"committer_date": 1624481966000,
"content_id": "3a80f55bb62f84054469c2e98a4411551e31df69",
"detected_licenses": [
"MIT"
],
"directory_id": "e1a299fec115855889a2066a11257a7948cc725a",
"extension": "py",
"file... | 2.84375 | stackv2 | import os
import PySimpleGUI as sg
from tkinter import Event
from typing import ValuesView
import janelas
import manipulador_modulo
sg.theme("DarkGrey8")
win_esc_arq = janelas.make_win_esc_arq()
event, values = win_esc_arq.read()
if event == "Inserir":
arquivo_dir = values["Input_Arq"]
if os.path.isfile(a... | 97 | 30.37 | 119 | 18 | 625 | python | [] | 0 | true | |
2024-11-18T21:37:45.626615+00:00 | 1,462,397,881,000 | 740bf5d45ccf478ee44822eaa6362a75acd8f08e | 3 | {
"blob_id": "740bf5d45ccf478ee44822eaa6362a75acd8f08e",
"branch_name": "refs/heads/master",
"committer_date": 1462397881000,
"content_id": "495dad05f2cd314b6bb894bbfc9aeded16da82e1",
"detected_licenses": [
"MIT"
],
"directory_id": "6a112fd667d411043bae71dbbfd296c642ffe376",
"extension": "py",
"fi... | 2.515625 | stackv2 | import os
import re
import socket
class IRC(object):
def __init__(self):
self.host = None
self.port = None
self.username = None
self.password = None
self.channel = None
self.connection = socket.socket()
def connect(self, host, port):
self.host = host
... | 125 | 26.61 | 78 | 18 | 831 | python | [] | 0 | true | |
2024-11-18T21:37:45.685387+00:00 | 1,415,224,381,000 | ab692087fb7100a9a47824bfb1506bbe83cd2c01 | 3 | {
"blob_id": "ab692087fb7100a9a47824bfb1506bbe83cd2c01",
"branch_name": "refs/heads/master",
"committer_date": 1415224381000,
"content_id": "9c06921dc9cd8b84513309ac8a152605f24dee91",
"detected_licenses": [
"MIT"
],
"directory_id": "40dbdfc840d31966d681e238391b7ed257735ac3",
"extension": "py",
"fi... | 2.75 | stackv2 | # coding: utf-8
import csv
import pandas as pd
import numpy as np
# TR sehir kodlari
tr = dict()
with open('plaka.tsv') as plakalar:
for plaka in plakalar:
il, kod = plaka.split('\t')
tr[il.decode('utf8').strip()] = kod.strip()
# GSKD datasi: Tuik Nisan 2014 raporu, Ek 5 (sayfa 57)
# http://www.tu... | 52 | 30 | 160 | 20 | 593 | python | [] | 0 | true | |
2024-11-18T21:37:45.746217+00:00 | 1,637,237,732,000 | 395041d4f1f9ad770055192788e9df31fbd36584 | 3 | {
"blob_id": "395041d4f1f9ad770055192788e9df31fbd36584",
"branch_name": "refs/heads/master",
"committer_date": 1637237732000,
"content_id": "db8e7845e85ecd708cce73f13d51bbc8dc13a786",
"detected_licenses": [
"MIT"
],
"directory_id": "9c2a1ff832aa3b41f0fbe3e4c6a8d48b1f2f80fd",
"extension": "py",
"fi... | 2.5625 | stackv2 | #!/usr/bin/env python
import sys
import pandas as pd
import pysam
import click
import pairtools
import pyximport
pyximport.install()
from seq_mismatches import get_mismatches_c
CONTEXT_SETTINGS = dict(help_option_names=["-h", "--help"])
@click.command(context_settings=CONTEXT_SETTINGS)
@click.argument("PAIRSAM_PA... | 161 | 29.34 | 89 | 17 | 1,448 | python | [] | 0 | true | |
2024-11-18T21:37:45.864486+00:00 | 1,622,537,975,000 | 0e3b9a5fb69314d3c03bfd01d00b3465463800cb | 2 | {
"blob_id": "0e3b9a5fb69314d3c03bfd01d00b3465463800cb",
"branch_name": "refs/heads/master",
"committer_date": 1622537975000,
"content_id": "9f22dcb0a7380114ffa708bbbb9d17cd3092cbb2",
"detected_licenses": [
"MIT"
],
"directory_id": "b7b7ac86e4d45ca23a211caee5588361e05e8bcf",
"extension": "py",
"fi... | 2.328125 | stackv2 | from lib.common import rsa,logrecord
from config import app
#接口返回验证签名
def checkDataSign(data):
buff = []
for k in data:
if k != "sign" and data[k] != "" and not (isinstance(data[k],dict) or isinstance(data[k],list)):
buff.append(f'{k}={data[k]}')
sbuff=sorted(buff)
tmpStr = '&'.join(... | 16 | 35.31 | 104 | 14 | 177 | python | [] | 0 | true | |
2024-11-18T21:37:46.107833+00:00 | 1,597,842,331,000 | 84ac9998fe5f3adf4428836bae21e65551455575 | 3 | {
"blob_id": "84ac9998fe5f3adf4428836bae21e65551455575",
"branch_name": "refs/heads/master",
"committer_date": 1597842331000,
"content_id": "e59079890ea2598d8abb33c5e271309c11dfc2a8",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "566573be0a9b782c7f9d04f71fe840de2accd40e",
"extension": "py"... | 2.859375 | stackv2 | # Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | 189 | 30.93 | 88 | 15 | 1,729 | python | [] | 0 | true | |
2024-11-18T21:37:46.237486+00:00 | 1,492,324,190,000 | f0fb9730678dbdd40b476f363ab1f763e075766d | 3 | {
"blob_id": "f0fb9730678dbdd40b476f363ab1f763e075766d",
"branch_name": "refs/heads/master",
"committer_date": 1492324190000,
"content_id": "eff12c6fad4c13d5cad34a507a10bc11fa67a098",
"detected_licenses": [
"MIT"
],
"directory_id": "aba488d4ad374c0a8b6fb37a9c56a8504dc2cf5e",
"extension": "py",
"fi... | 2.65625 | stackv2 | import os.path
from flask import Flask, request, render_template
from flask.ext.pymongo import PyMongo
from yahoo_finance import Share
from twitter_scrape import TwitterScraper
import feedparser
app = Flask(__name__, static_url_path='')
mongo = PyMongo(app)
def root_dir():
return os.path.abspath(os.path.dirname(... | 81 | 28.47 | 107 | 18 | 592 | python | [] | 0 | true | |
2024-11-18T21:37:46.302503+00:00 | 1,277,279,654,000 | 9a9fcadef86b2713de5f0be473685d62859c1fe7 | 3 | {
"blob_id": "9a9fcadef86b2713de5f0be473685d62859c1fe7",
"branch_name": "refs/heads/master",
"committer_date": 1277279654000,
"content_id": "46079add76d5f1d76e94b032665b8abfb735a64a",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "560828627d27d5776c9d3b969f93792eeaa30971",
"extension": "p... | 2.671875 | stackv2 | """
Utils of Django Flickrsets application.
"""
import datetime
import re
import dateutil.parser
import dateutil.tz
import httplib2
from django.utils import simplejson
from django.utils.encoding import force_unicode
DEFAULT_HTTP_HEADERS = {
"User-Agent": "Django Flickrsets/0.1",
}
DATETIME_STRING_RE = ("(?P<year... | 65 | 25.72 | 79 | 17 | 437 | python | [] | 0 | true | |
2024-11-18T21:37:46.352959+00:00 | 1,623,447,184,000 | de02e44da0baf09e4992ff72f2992f7fa265cb92 | 2 | {
"blob_id": "de02e44da0baf09e4992ff72f2992f7fa265cb92",
"branch_name": "refs/heads/main",
"committer_date": 1623447184000,
"content_id": "d1a78f35ebd3f2687344ac0e7baa26fa575f899f",
"detected_licenses": [
"MIT"
],
"directory_id": "1a775a01341a17da07f520b2e28166b0aeda801e",
"extension": "py",
"file... | 2.4375 | stackv2 | # Copyright (c) 2021 Moneysocket Developers
# Distributed under the MIT software license, see the accompanying
# file LICENSE or http://www.opensource.org/licenses/mit-license.php
VERSION_MAJOR = 0 # pre-specification protocol v0
VERSION_MINOR = 99 # implementing v1, but still WIP
VERSION_PATCH = 99 # implementing v1... | 48 | 34.12 | 68 | 13 | 400 | python | [] | 0 | true | |
2024-11-18T21:37:46.459173+00:00 | 1,619,400,921,000 | d4de008bb358ecdcf91cf65a466ae44f7a1aaf17 | 3 | {
"blob_id": "d4de008bb358ecdcf91cf65a466ae44f7a1aaf17",
"branch_name": "refs/heads/master",
"committer_date": 1619400921000,
"content_id": "5b8010a6c51593a785ff04022c04981a8278b405",
"detected_licenses": [
"MIT"
],
"directory_id": "66963410dd4f79a8e0bf4ba272e984c35c6af441",
"extension": "py",
"fi... | 2.5625 | stackv2 | # !curl -O https://storage.googleapis.com/nasbench/nasbench_only108.tfrecord
# !git clone https://github.com/google-research/nasbench
# !pip install ./nasbench
# Initialize the NASBench object which parses the raw data into memory (this
# should only be run once as it takes up to a few minutes).
import tensorflow.comp... | 214 | 30.88 | 86 | 16 | 1,947 | python | [] | 0 | true | |
2024-11-18T21:37:46.528127+00:00 | 1,584,615,830,000 | b2f36d7fbd98975176ff4f72970497b42a5f6eea | 2 | {
"blob_id": "b2f36d7fbd98975176ff4f72970497b42a5f6eea",
"branch_name": "refs/heads/master",
"committer_date": 1584615830000,
"content_id": "0585e125d7f49fa1abc1875b53b8be62220262ca",
"detected_licenses": [
"MIT"
],
"directory_id": "2bb45ce4940e092082d8ee28503e843862befc0a",
"extension": "py",
"fi... | 2.328125 | stackv2 | from flask_sqlalchemy import SQLAlchemy
from flask_migrate import Migrate, upgrade
from flask import current_app
from sqlalchemy import MetaData
from multiprocessing import Lock
from sqlalchemy import create_engine
from .utils import get_metadata_from_parent
DB = SQLAlchemy()
MIGRATE = Migrate()
lock = Lock()
def g... | 38 | 25.89 | 73 | 14 | 200 | python | [] | 0 | true | |
2024-11-18T21:37:46.587287+00:00 | 1,635,337,745,000 | 1cd9381d3fc93ae4141c33dc558f53d99e37ab8f | 2 | {
"blob_id": "1cd9381d3fc93ae4141c33dc558f53d99e37ab8f",
"branch_name": "refs/heads/main",
"committer_date": 1635337745000,
"content_id": "c368df8196b3325a5c06070953fe4e0e43e5fb9e",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "fb6e7922df3da2e9cdc37a00150d6d7663e907ff",
"extension": "py",
... | 2.46875 | stackv2 | # Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from .base_modifier import BaseWeaponModifier, BasePrefixModifier
class BaseHitModifier(BaseWeaponModifier):
level = ... | 75 | 17.85 | 65 | 10 | 328 | python | [] | 0 | true | |
2024-11-18T21:37:49.818323+00:00 | 1,511,363,738,000 | ddbe7837c27118b5be93e0b8872c6aec4d1c6b27 | 2 | {
"blob_id": "ddbe7837c27118b5be93e0b8872c6aec4d1c6b27",
"branch_name": "refs/heads/master",
"committer_date": 1511363738000,
"content_id": "6a683c7ebf21c2d1425e13d944a39f2b24468128",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "2c4bee7d73d02dbdbf8d0c491c731cf2f6c1fcb0",
"extension": "py"... | 2.328125 | stackv2 | from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import os
kaggleRoot = '/home/mattmcd/Work/Projects/PyCharm/PyAnalysis/Kaggle/'
kaggleComp = 'CouponPurchasePrediction/'
os.chdir(kaggleRoot + kaggleComp + 'working')
__author__ = 'mattmcd'
def get_all_data():
... | 86 | 38.29 | 141 | 17 | 929 | python | [] | 0 | true | |
2024-11-18T21:37:50.058327+00:00 | 1,605,076,598,000 | bf3c21006eab0cd259ec7e71dbda757c307bbe66 | 3 | {
"blob_id": "bf3c21006eab0cd259ec7e71dbda757c307bbe66",
"branch_name": "refs/heads/master",
"committer_date": 1605076598000,
"content_id": "d87fc0abc0fb8a69d13d892043d66d399cb8b468",
"detected_licenses": [
"MIT"
],
"directory_id": "c10c732c7b038d7140fbc5e58fa0a00202b7903c",
"extension": "py",
"fi... | 2.640625 | stackv2 | import gym
from cell_place_gym.envs import geom
from gym.envs.classic_control import rendering
from cell_place_gym.native.acp_primes import *
from cell_place_gym.native.acp_placement import *
from cell_place_gym.native.acp_state import *
from gym.envs.classic_control.rendering import make_circle, LineWidth
cl... | 196 | 32.16 | 99 | 16 | 1,723 | python | [] | 0 | true | |
2024-11-18T21:37:50.776858+00:00 | 1,614,550,805,000 | 6a4c09f013ed89d0e9c9c51dba1e8d056092293e | 4 | {
"blob_id": "6a4c09f013ed89d0e9c9c51dba1e8d056092293e",
"branch_name": "refs/heads/main",
"committer_date": 1614550805000,
"content_id": "6b6b601ab71eca88c53f71bb2c0c7505ab59b50e",
"detected_licenses": [
"MIT"
],
"directory_id": "b268bd8b1b9a37c5ba738b227aceadac2fa2ae6f",
"extension": "py",
"file... | 3.5 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
BE523 Biosystems Analysis & Design
HW3 - Problem 3. Exercise 2 Penicillin in intestine and plasma
https://mathinsight.org/penicillin_clearance_model_exercises
Created on Sat Jan 23 21:29:34 2021
@author: eduardo
"""
import numpy as np
import matplotlib.pyplot as plt
... | 34 | 30.71 | 67 | 11 | 355 | python | [] | 0 | true | |
2024-11-18T21:37:50.935506+00:00 | 1,589,785,804,000 | 27737d5ae8e6dd08875e89e8185663aaedec7e4b | 2 | {
"blob_id": "27737d5ae8e6dd08875e89e8185663aaedec7e4b",
"branch_name": "refs/heads/master",
"committer_date": 1589785804000,
"content_id": "987ac7f995d34b4864ca923054127ef0aedfe1ae",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "8b34f2e78377d1dd7baefcf851844b77dc322579",
"extension": "py"... | 2.5 | stackv2 | '''/*---------------------------------------------------------------------------------------------
* Copyright (c) VituTech. All rights reserved.
* Licensed under the Apache License 2.0. See License.txt in the project root for license information.
*------------------------------------------------------------------... | 287 | 36.51 | 120 | 19 | 3,129 | python | [] | 0 | true | |
2024-11-18T21:37:51.053918+00:00 | 1,623,148,126,000 | 66225e61be119fd9bef39ef2d29fded159d31db7 | 4 | {
"blob_id": "66225e61be119fd9bef39ef2d29fded159d31db7",
"branch_name": "refs/heads/master",
"committer_date": 1623148126000,
"content_id": "76cf1d9de64ba7c8da674d3b0de0a086eee6db06",
"detected_licenses": [
"MIT"
],
"directory_id": "db0f8db6f22f511e84e5c8de7139afb6de2ba2fd",
"extension": "py",
"fi... | 4.125 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jun 3 13:53:12 2021
Assume s is a string of lower case characters.
Write a program that counts up the number of vowels contained in the string s.
Valid vowels are: 'a', 'e', 'i', 'o', and 'u'.
For example, if s = 'azcbobobegghakl', your program shou... | 20 | 26.6 | 79 | 12 | 195 | python | [] | 0 | true | |
2024-11-18T21:37:51.349637+00:00 | 1,608,482,762,000 | a9155ce7e54e731feac9d117815cdb5c0d59cbca | 3 | {
"blob_id": "a9155ce7e54e731feac9d117815cdb5c0d59cbca",
"branch_name": "refs/heads/main",
"committer_date": 1608482762000,
"content_id": "f751c634a9d50106d1954cacfe7e08c5dfe5bb74",
"detected_licenses": [
"MIT"
],
"directory_id": "d2bdba69891ce231bf7c0c3ed0f16ee7755b2174",
"extension": "py",
"file... | 3.09375 | stackv2 | from tkinter import ttk
import tkinter as tk
from tkinter import *
import tkinter.scrolledtext as tkscrolled
# pip install pillow
from PIL import ImageTk, Image
class base:
#esto es un constructor
def __init__(self, window):
self.wind = window #guarda la ventana que tiene como parametro
self.... | 69 | 35.07 | 92 | 13 | 674 | python | [] | 0 | true |
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