seq_id string | text string | repo_name string | sub_path string | file_name string | file_ext string | file_size_in_byte int64 | program_lang string | lang string | doc_type string | stars int64 | dataset string | pt string | api list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
12506646901 | # GUI and Image Processing Modules
import PySimpleGUI as sg
import io
import os
from PIL import Image
# Prediction
from tensorflow.keras.applications.resnet50 import ResNet50, preprocess_input, decode_predictions
from tensorflow.keras.preprocessing import image
import numpy as np
import matplotlib.pyplot as ... | gabrielbrosula/ResNet_GUI | resnet_gui.py | resnet_gui.py | py | 8,810 | python | en | code | 5 | github-code | 21 | [
{
"api_name": "matplotlib.use",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras.applications.resnet50.ResNet50",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras.preprocessing.image.load_img",
"line_number": 40,
"usage_... |
36606722823 | """
University of Liege
ELEN0062 - Introduction to machine learning
Project 1 - Classification algorithms
"""
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Only py3 / so that 2 / 3 = 0.66..
from __future__ import division
# Only py3 string encoding
from __future__ import unicode_literals
# Only py3 print
from __fut... | nDerroitte/ML1 | logistic_regression.py | logistic_regression.py | py | 8,605 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "sklearn.base.BaseEstimator",
"line_number": 33,
"usage_type": "name"
},
{
"api_name": "sklearn.base.ClassifierMixin",
"line_number": 33,
"usage_type": "name"
},
{
"api_name": "numpy.asarray",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": ... |
44295420621 | from flask import Blueprint, request, render_template, session, redirect, flash
from weather_util import get_weather
import db_sqlite.user_dao as udao
import datetime
screening_output = Blueprint('screening_output', __name__, static_folder='../static')
@screening_output.route('/output', methods=['GET', 'POST'])
def s... | cbj1847/Projects | 건강검진데이터분석/screening_bp/screening_output.py | screening_output.py | py | 824 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "flask.Blueprint",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "flask.request.method",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "flask.request",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "flask.render_t... |
44708499790 | """empty message
Revision ID: 11007796e0ef
Revises: 8650d3d6ee2f
Create Date: 2018-04-05 17:49:46.465148
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = '11007796e0ef'
down_revision = '8650d3d6ee2f'
branch_labels = None
depends_on = None
def upgrade():
# #... | anasyusef/ECA-Project | migrations/versions/11007796e0ef_.py | 11007796e0ef_.py | py | 651 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "alembic.op.add_column",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "alembic.op",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "sqlalchemy.Column",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.Boolean... |
902990272 | import requests
import json
headers = {
"Accept": "*/*",
"User-Agent": "httpp://rest-tool.com"
}
class RequestHandler():
def __init__(self, url, method="GET", headers=headers, payload=""):
self.url = url
self.method = method
self.headers = headers
self.payload = payload ... | sumeetmathpati/rest-test | request_handler.py | request_handler.py | py | 746 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "requests.request",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 23,
"usage_type": "call"
}
] |
15703295032 | import os
import shutil
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdm
import biomorph_mutation.utils as utils
# Set seed (for reproducibility)
np.random.seed(4321)
# Create output folders
if os.path.isdir('biomorphs'):
shutil.rmtree('biomorphs')
os.mkdir('biomorphs')
# Initialize gen... | sgalella/BiomorphMutation | biomorph_mutation/__main__.py | __main__.py | py | 975 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "numpy.random.seed",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "os.path.isdir",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path",
"line... |
25923021987 | from django.shortcuts import render
import requests
from ff_espn_api import League
# Create your views here.
# import pdb; pdb.set_trace()
# 1246423
# 1625692
def home(request):
return render(request, 'create.html')
def league_view(request):
idLeague1 = request.GET.get('leagueid1')
idLeague2 = request.GE... | Kyle-Howard/fantasy_fb | fantasy_fb/views.py | views.py | py | 3,048 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "django.shortcuts.render",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "ff_espn_api.League",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "ff_espn_api.League",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "django.... |
17275973942 | #Realizar en python el codigo fuente necesario para implementar una lista enlazada que permita
#almacenar alineaciones de jugadores de futbol para un equipo cualquiera(nombre y numero de camiseta)
#en un orden cualquiera, para posteriormente imprimirlos en orden secuencial segun su numero de camiseta
#Importar libre... | AFuentes1/Lenguajes-de-programacion- | Diagnostico Lenguajes/Diagnostico Lenguajes Python/Diagnostico.py | Diagnostico.py | py | 1,136 | python | es | code | 0 | github-code | 21 | [
{
"api_name": "collections.deque",
"line_number": 18,
"usage_type": "call"
}
] |
73042165813 | import numpy as np
import chainer
import chainer.functions as F
import chainer.links as L
from chainer.links.model.vision.vgg import VGG16Layers
from lib.bbox_transform import bbox_transform_inv
from lib.bbox_transform import clip_boxes
from lib.nms_cpu import nms_cpu as nms
from lib.proposal_target_layer import Propo... | LiuFang816/SALSTM_py_data | python/yuyu2172_chainer-cv/chainer-cv-master/examples/detection/faster_rcnn/faster_rcnn.py | faster_rcnn.py | py | 5,791 | python | en | code | 9 | github-code | 21 | [
{
"api_name": "chainer.Chain",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "chainer.links.model.vision.vgg.VGG16Layers",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "lib.rpn.RPN",
"line_number": 28,
"usage_type": "call"
},
{
"api_nam... |
22192131776 |
# coding: utf-8
import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import load_breast_cancer
from sklearn.preprocessing import scale
import matplotlib.pyplot as plt
import seaborn as sns
#Reading breast_cancer dataset
X_Actual, Y_Actual = load_breast_cancer(True)
#Taking fisrt 500 samples for t... | sonusinghrajput11/Machine-Learning | ML Algorithm Implementation Using Python/logistic_regression_vectorization.py | logistic_regression_vectorization.py | py | 2,260 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "sklearn.datasets.load_breast_cancer",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.scale",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.scale",
"line_number": 18,
"usage_type": "call"
}... |
71993383733 | from selenium import webdriver
import time
driver = webdriver.Chrome()
url = "https://www.justdial.com/Madanapalle/Mobile-Shops/nct-11216691"
driver.get(url)
time.sleep(5)
shop_names_html = driver.find_elements_by_css_selector(".lng_cont_name")
all_shop_names = []
for shop_name_html in shop_names_html:
print(sho... | ashrithssreddy/adhoc_codes | eyewear_data_scraping/code_2.py | code_2.py | py | 964 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "selenium.webdriver.Chrome",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "time.sleep",
"line_number": 7,
"usage_type": "call"
}
] |
33130917249 | import bge
import csv
import math
from config import custom_dir
from csv import DictReader
# DEBUGGING
DEBUG=False
print("(Debugging is set to", DEBUG, ")\n")
def debug_print(*args):
"""Function that set the debugging mode On (True) or Off (False)"""
if DEBUG:
print(*args)
scene = bge.logic.... | savysok/diploma | scripts/load_block.py | load_block.py | py | 5,461 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "bge.logic.getCurrentScene",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "bge.logic",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "bge.logic.getCurrentController",
"line_number": 34,
"usage_type": "call"
},
{
"api_name"... |
4500230514 | #!use\bin\python3
import kivy
#for app or software
kivy.require('1.9.0')
from kivy.app import App
from random import randint
from kivy.core.window import Window
from kivy.uix.image import Image, AsyncImage
#numbre of colors
n_of_colors = 255
#random color
color = randint(0, n_of_colors)
#create color windo... | madocoin/kivypython3 | image.py | image.py | py | 1,283 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "kivy.require",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "kivy.core.window.Window.clearcolor",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "ki... |
70309790454 | """
Pair Plot
=========
_gallery_category: Inference Diagnostics
"""
import matplotlib.pyplot as plt
import arviz as az
az.style.use("arviz-doc")
data = az.load_arviz_data("centered_eight")
coords = {"school": ["Choate", "Deerfield"]}
az.plot_pair(
data,
var_names=["theta", "mu", "tau"],
coords=coords,
... | arviz-devs/arviz | examples/matplotlib/mpl_plot_pair.py | mpl_plot_pair.py | py | 373 | python | en | code | 1,461 | github-code | 21 | [
{
"api_name": "arviz.style.use",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "arviz.style",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "arviz.load_arviz_data",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "arviz.plot_pai... |
32949587123 | from Functions import range_check, digit_check, clear_screen
# requests used for api requests
import requests
# json used for converting the api request into dictionary
import json
# random used for generates random numbers
from random import randrange
# add_score uses for updating the user score to score.txt
from Scor... | shahar5/wog | CurrencyRouletteGame.py | CurrencyRouletteGame.py | py | 3,465 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "Functions.clear_screen",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "random.randrange",
... |
16935600260 | #!/usr/bin/env python3
import ssh_func
import make_archive
import applybackup
import yaml
import sys
import time
import datetime
import os.path
import pathlib
#definition du config.yaml et utilisation des information dedans pour utilisé les variables
def read_yaml(file):
with open(file) as f:
return yaml.safe_load(... | Immomix/P6 | main.py | main.py | py | 1,181 | python | fr | code | 0 | github-code | 21 | [
{
"api_name": "yaml.safe_load",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number... |
13721695866 | # Import necessary modules and functions
import numpy as np
import pandas as pd
import gradio as gr
from utils import demo_actions
import utils.constants as consts
# Create the main Gradio interface
with gr.Blocks(theme='soft') as demo:
gr.Markdown("# Otimizador de Molas Pocket")
# Step 1: Molejo
# Creat... | FelipeMAssis/OtimizadorPocketPublic | app.py | app.py | py | 19,849 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "gradio.Blocks",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "gradio.Markdown",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "gradio.Accordion",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "gradio.Markdown",
... |
35865165060 | import requests
import time
import json
TOKEN = '73eaea320bdc0d3299faa475c196cfea1c4df9da4c6d291633f9fe8f83c08c4de2a3abf89fbc3ed8a44e1'
class User:
def __init__(self, token):
self.token = token
def get_user_id(self, user):
try:
params = {
'access_token': self.toke... | shattl2000/Netology | Python_course/Part 1/Diploma/hiding_groups_vk.py | hiding_groups_vk.py | py | 3,610 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "requests.get",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 60,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": ... |
37138853330 | import zlib
from base64 import b64encode, b64decode
# Compressing
def compress(input_file, output_file):
data = open(input_file, 'r').read()
data_bytes = bytes(data, 'utf-8')
compressed_data = b64encode(zlib.compress(data_bytes, 9))
decoded_data = compressed_data.decode('utf-8')
compressed_file = ... | jeniferss/PythonStudies | files/compress-decode/compress-decompress.py | compress-decompress.py | py | 828 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "base64.b64encode",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "zlib.compress",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "zlib.decompress",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "base64.b64decode",
"... |
6016763656 | import matplotlib
from matplotlib import pyplot as plt
matplotlib.rcParams['figure.figsize'] = [9, 6]
import tensorflow as tf
x = tf.linspace(-2, 2, 256)
x = tf.cast(x, tf.float32)
def f(x):
y = x**2 + 2*x - 5
return y
y = f(x) + tf.random.normal(shape=[256], mean=0, stddev=1)
#plt.plot(x.numpy(), y.numpy(), '... | Martin-Paez/Python | Proyecto 12 - IA/model.py | model.py | py | 4,835 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "matplotlib.rcParams",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.linspace",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "tensorflow.cast",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "tensorflow.... |
38749437031 | import requests
from selectorlib import Extractor
class Temperature:
"""
Temperature is scraped from timeanddate.com/weather
"""
headers = {
'pragma': 'no-cache',
'cache-control': 'no-cache',
'dnt': '1',
'upgrade-insecure-requests': '1',
'user-agent': 'Mozilla/5... | PetaGb/CalorieCalculator | Temperature.py | Temperature.py | py | 1,206 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "requests.get",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "selectorlib.Extractor.from_yaml_file",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "selectorlib.Extractor",
"line_number": 28,
"usage_type": "name"
}
] |
15269489497 | # -*- coding: utf-8 -*-
############ Variables ############
'''
main_url = url main page of the site
main_page = content of the main page
main_categories[] = list of categories displayed in the main page
main_url_categories[] = list of URLs associated of each main categories
category_page_url = URL of one category
pro... | LeChat76/Projet2OC | script_monolithique.py | script_monolithique.py | py | 9,032 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "requests.get",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 86,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"... |
34693320533 | import subprocess
import logging
import argparse
import csv
from threading import Thread, Lock
import multiprocessing
import sys
import bisect
from copy import deepcopy
try:
#python3
from queue import Queue
except:
#python 2
from Queue import Queue
def main(args=None):
# Construct the argument par... | lwaeijen/cnn-mapping-tool | cnn_implementer/tools/reuse_distance.py | reuse_distance.py | py | 6,941 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "argparse.ArgumentTypeError",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "logging.ERROR",
"line_number": 33,
"usage_type": "attribute"
},
{
"api_name": ... |
11862144418 | import urllib.request
from bs4 import BeautifulSoup
import os
# Assigning the wiki link to link
Link = "https://www.fantasypros.com/nfl/reports/leaders/qb.php?year=2016"
# Opens the URL
getLink=urllib.request.urlopen(Link)
f = open('gameleaders_in_2016.txt', 'w+')
# Converts to HTML
soup = BeautifulSoup(getLink, "h... | sairamtorlikonda/python_deeplearning | labs/lab1/source/5.py | 5.py | py | 1,002 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "urllib.request.request.urlopen",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "urllib.request.request",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "urllib.request",
"line_number": 10,
"usage_type": "name"
},
{
"api_nam... |
16181127716 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import sg2im.box_utils as box_utils
from sg2im.graph import GraphTripleConv, GraphTripleConvNet
from sg2im.crn import RefinementNetwork
from sg2im.layout import boxes_to_layout, masks_to_layout
from sg2im.layers import build_mlp
class Sg2... | google/sg2im | sg2im/model.py | model.py | py | 8,337 | python | en | code | 1,275 | github-code | 21 | [
{
"api_name": "torch.nn.Module",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "torch.nn.Embedding",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line... |
14546578983 | # -*- coding: utf-8 -*-
import itertools as it
with open('tsp.txt', 'r') as f:
n_vertices = int(f.readline())
vertices = [(float(i.split(' ')[0]), float(i.split(' ')[1])) for i in f.read().split('\n')[:-1]]
def euclidean_dist(tuple_0, tuple_1):
return(((tuple_0[0] - tuple_1[0])**2 + (tuple_0[1] - tuple_1[... | elikschultz/coursera_algorithms | course_4/tsp.py | tsp.py | py | 1,355 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "itertools.combinations",
"line_number": 27,
"usage_type": "call"
}
] |
7847470141 | from rest_framework import generics
from accounts.serializers import (
RegisterSerializer,
EmailVerifiSerializer,
LoginSerializer,
LogoutSerializer
)
from django.http import HttpResponse, HttpResponseRedirect
from rest_framework import permissions
from rest_framework.response import Response
from rest_f... | Krzyzaku21/project_amber | app/accounts/views/views.py | views.py | py | 7,118 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "rest_framework.generics.GenericAPIView",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.generics",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "accounts.serializers.RegisterSerializer",
"line_number": 31,
"usage_t... |
2122423759 | from configparser import ConfigParser
from kafka import KafkaProducer
import json
def config_file_setup():
config_file = "config.ini"
config = ConfigParser()
config.read(config_file)
return config
def get_threshold_from_config():
config = config_file_setup()
threshold = int(config.get("thre... | InonBr/BE_currency_exchange_monitor | monitor_service/src/logic.py | logic.py | py | 1,287 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "configparser.ConfigParser",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "kafka.KafkaProducer",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "kafka.KafkaProducer",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "kafk... |
19738163139 | """
given
A_i ∈ ℝ^(m_i × n)
b_i ∈ ℝ^m_i
`x₀` ∈ ℝ^n
min_(x ∈ ℝ^n) ∑_i ‖A_i x + b_i‖ + (1/2)‖x-`x₀`‖²
"""
import numpy as np
import scipy
import scipy.linalg
from scipy import sparse
from scipy.integrate import quad
from scipy.optimize import minimize
class convex_optimization_276ResultType:
def __init__( sel... | iheartla/Iheartla.github.io | evaluation/static/gallery_res/Convex Optimization page 276/convex_optimization_276.py | convex_optimization_276.py | py | 1,414 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "numpy.asarray",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "numpy.asarray",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "numpy.asarray",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "numpy.float64",
"line_n... |
17636915370 | import numpy as np
import matplotlib.pyplot as plt
import time
calculation_unit = 20
WIN = "1"
LOOSE = "-1"
while True:
print("start")
results = []
win_dicts = {}
loose_dicts = {}
with open('result.txt', 'r') as f:
for row in f:
results.append(row.strip())
... | yohe-kitamura/pysc2-experiment | result_graph.py | result_graph.py | py | 1,171 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "matplotlib.pyplot.plot",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 35,
"usage_type": "name"
},
{
"api_name": "numpy.array",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplo... |
72907710454 | # Compatibility imports
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
# from .base_multi_gpus import MultiGPUBaseModel as BaseModel
from .base import BaseModel
import tensorflow as tf
from tensorflow.python.layers import core as layers_core
from six.mo... | Kyoto-University-Speech-and-Audio/speech-to-dialog-act | src/models/da/seq2seq.py | seq2seq.py | py | 10,083 | python | en | code | 4 | github-code | 21 | [
{
"api_name": "base.BaseModel",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "tensorflow.contrib.seq2seq.BeamSearchDecoder",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "tensorflow.contrib",
"line_number": 30,
"usage_type": "attribute"
},
{
... |
26622820100 |
import os
import torch
import cv2
import copy
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print("Using {} device ...".format(device.type))
# from ICSNet import create_model, detect_image_iris
# icsnet = create_model("ICSNet/model.pth", device)
from PSNet import load_model_and... | chgex/PSNet | demo/detect_eye_images.py | detect_eye_images.py | py | 1,585 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "torch.device",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "PSNet.load_model_an... |
42488803252 | import matplotlib.pyplot as plt
import sys
from matplotlib.pyplot import *
import matplotlib
import numpy as np
style=['b:*','r:s','c:p']
prectage = [0.001, 0.01, 0.1, 1.0]
lprectage = np.log10(prectage)
snli_bert = [52.5, 78.1, 86.7, 91.0]
snli_mtl = [82.1, 85.2, 88.4, 91.5]
scitail_bert = [51.... | bernaljg/N-aryRels | SciREX/scirex_dataset/release_data/scirex_tex/1901.11504v2.Multi_Task_Deep_Neural_Networks_for_Natural_Language_Understanding/fig/draw.py | draw.py | py | 1,516 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "numpy.log10",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.ylabel",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "matplotlib.pypl... |
31600355844 | from django.contrib import admin
from django.utils.safestring import mark_safe
from storage.models import (
Storage,
Image,
Box,
Booking,
Discount,
Invoice,
Lead,
UnlockQR,
)
@admin.register(Storage)
class StorageAdmin(admin.ModelAdmin):
list_display = (
'city',
'a... | mavel-x/SelfStorage | storage/admin.py | admin.py | py | 2,216 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "django.contrib.admin.ModelAdmin",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "django.utils.safestring.mark_safe",
"line_number": 29,
"usage_type": "call"
}... |
32177293505 | from __future__ import annotations
"""
Most of this code was taken from
https://github.com/data-engineering-collective/plateau
https://github.com/data-engineering-collective/plateau/blob/d4c4522f5a829d43e3368fc82e1568c91fa352f3/plateau/core/common_metadata.py
and adapted to this project
under the original license
... | dask-contrib/dask-deltatable | dask_deltatable/_schema.py | _schema.py | py | 13,508 | python | en | code | 34 | github-code | 21 | [
{
"api_name": "logging.getLogger",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "pyarrow.Schema",
"line_number": 54,
"usage_type": "attribute"
},
{
"api_name": "pyarrow.Schema",
"line_number": 62,
"usage_type": "attribute"
},
{
"api_name": "pyarrow.Tim... |
28502823361 | # 827. Making A Large Island
# Hard
# You are given an n x n binary matrix grid. You are allowed to change
# at most one 0 to be 1.
# Return the size of the largest island in grid after applying this
# operation.
# An island is a 4-directionally connected group of 1s.
# Example 1:
# Input: grid = [[1,0],[0,1]]
# Ou... | DmitryVlaznev/leetcode | 827-making-a-large-island.py | 827-making-a-large-island.py | py | 3,032 | python | en | code | 2 | github-code | 21 | [
{
"api_name": "typing.List",
"line_number": 41,
"usage_type": "name"
},
{
"api_name": "collections.defaultdict",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "utils.checkValue",
"line_number": 94,
"usage_type": "call"
},
{
"api_name": "utils.checkValue... |
10575358883 | #-*- coding: utf-8 -*-
from netaddr import IPAddress, IPNetwork
class RFC3046:
"""
"""
def __init__(self, data):
"""
"""
self._agent_remote_id = []
self._agent_circuit_id = []
self.agent_remote_id = self.agent_circuit_id = []
self.empty = True
... | ialx/isdhcplib | isdhcplib/type_rfc.py | type_rfc.py | py | 4,158 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "netaddr.IPNetwork",
"line_number": 132,
"usage_type": "call"
},
{
"api_name": "netaddr.IPNetwork",
"line_number": 133,
"usage_type": "call"
},
{
"api_name": "netaddr.IPAddress",
"line_number": 133,
"usage_type": "call"
}
] |
9395489825 | import copy, traceback
from datetime import datetime
from utils import *
import utils
# import FeatureOntology
# usage: to output rules list, run:
# python Rules.py > rules.txt
from LogicOperation import CheckPrefix as LogicOperation_CheckPrefix
from LogicOperation import SeparateOrBlocks as LogicOperation_Sepa... | lingvisa/ParserOC | src/Rules.py | Rules.py | py | 106,238 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "copy.deepcopy",
"line_number": 129,
"usage_type": "call"
},
{
"api_name": "copy.deepcopy",
"line_number": 192,
"usage_type": "call"
},
{
"api_name": "utils.DBCon.cursor",
"line_number": 354,
"usage_type": "call"
},
{
"api_name": "utils.DBCon",
"... |
43717732440 | # coding: utf-8
import requests,re,fitz,json,base64
from lxml import etree
from bs4 import BeautifulSoup
import os.path
'''
# 将PDF转化为图片
pdfPath pdf文件的路径
imgPath 图像要保存的文件夹
zoom_x x方向的缩放系数
zoom_y y方向的缩放系数
rotation_angle 旋转角度
'''
#PDF转图片
def pdf_image(pdfPath, imgPath, zoom_x, zoom_y, rotation_angle):
... | TheHai-shao/TheHai-shao | 爬虫1.py | 爬虫1.py | py | 6,845 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "fitz.open",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "fitz.Matrix",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "base64.b64encode",
"line_numbe... |
71989315253 | import unittest
import logging
from netsquid import BellIndex
from netsquid.components import INSTR_INIT
from netsquid.qubits import ketstates
import netsquid.qubits.qubitapi as qapi
from netsquid_trappedions.ion_trap import IonTrap
from netsquid_trappedions.programs import IonTrapSwapProgram, ion_trap_meas_z, ion_tra... | AshritVerma/netsquid-trappedions | test_programs.py | test_programs.py | py | 3,843 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "unittest.TestCase",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "netsquid.sim_reset",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "netsquid.qubits.qformalism.set_qstate_formalism",
"line_number": 20,
"usage_type": "call"
},
... |
35370331661 | """Module implementing the basic network that performs prototypical classification"""
import torch
import torch.nn as nn
import torch.nn.functional as func
import networks
import utils
class ResNet18Proto(nn.Module):
"""Class definition for the ResNet-18 backbone for the model"""
def __init__(self, pret... | aivaslab/toybox_da | src/proto_network.py | proto_network.py | py | 8,069 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "torch.nn.Module",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "networks.ResNet18Backbone",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "torch.nn.Iden... |
1997632051 | # -*- coding: utf-8 -*-
import requests
import traceback
import logging
import time
import json
import hmac
import base64
import random
import datetime
#娱乐中心 玩游戏3GB
#测试时 服务器返回400 无法使用
#若能够解决 希望能提交pr谢谢
def main(*i):
client = i[0]
username = i[1]
#获取jwt 用于验证
cookiesdata = client.cookies.get_dict()
... | LxDebug/UnicomPlus | TaskList/GameProduc.py | GameProduc.py | py | 7,886 | python | en | code | 46 | github-code | 21 | [
{
"api_name": "time.sleep",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "logging.info",
"line_number": 59,
"usage_type": "call"
},
{
"api_name": "logging.info",
"line_number": 6... |
73036771893 | #!/usr/bin/env python
"""
Script to show the contents of a JSON file
"""
import pdb
try:
ustr = unicode
except NameError:
ustr = str
def parser(options=None):
import argparse
# Parse
parser = argparse.ArgumentParser(
description='Show contents of a JSON file, assuming one of several for... | LiuFang816/SALSTM_py_data | python/pyigm_pyigm/pyigm-master/pyigm/scripts/pyigm_showjson.py | pyigm_showjson.py | py | 1,458 | python | en | code | 9 | github-code | 21 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "linetools.utils.loadjson",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "linetools.utils",
"line_number": 33,
"usage_type": "name"
},
{
"api_name": "pyig... |
75213105973 | #!/usr/bin/python3
"""module uses State model to list states"""
import sys
from model_state import Base, State
from sqlalchemy import (create_engine)
from sqlalchemy.orm import sessionmaker
if __name__ == "__main__":
uname = sys.argv[1]
pswd = sys.argv[2]
dname = sys.argv[3]
conn_str = 'mysql+mysqldb:... | cmiltone/alx-higher_level_programming | 0x0F-python-object_relational_mapping/13-model_state_delete_a.py | 13-model_state_delete_a.py | py | 676 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "sys.argv",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "sqlalchemy.create_engine",
... |
1453541891 | import requests
from geopy.distance import geodesic # 执行API调用并储存响应
import pandas as pd
def count_dis(lat, long, lat1, long1):
result = geodesic((long, lat), (long1, lat1)).km
print(round(result, 2))
def test():
long_c = 120.73056
lat_c = 31.270745
data = []
for i in range(0, 15):
fo... | nexusme/leetcode_try | LeetCode/.idea/coordinatesRange.py | coordinatesRange.py | py | 1,832 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "geopy.distance.geodesic",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 46,
"usage_type": "call"
}
] |
37493615743 | import time
import base64
import os
import shutil
import subprocess
def b64tofile(bs64img,id):
t = time.time()
imgdata = base64.b64decode(bs64img)
timenow = str(int(round(t * 1000)))
filename = timenow+'.jpg'
try:
with open('img/'+id+'/'+filename, 'wb+') as destination:
... | winterpink/ocr4hwt | backend/srtphouduan/ocr/imghandler.py | imghandler.py | py | 1,461 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "time.time",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "base64.b64decode",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "base64.b64decode",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "os.path.exists",
"line_... |
32035127007 | from django.shortcuts import render
import requests
from django.http import HttpResponse
def my_view(request):
# ...
# Return a "created" (201) response code.
return HttpResponse(status=201)
# Create your views here.
def index(request):
r=requests.get('http://api.mediastack.com/v1/news?access_key=API... | karandesai24/NEWSAPP-django | newsapp/views.py | views.py | py | 750 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "django.http.HttpResponse",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.render",
"line_number": 27,
"usage_type": "call"
}
] |
37945221011 | import sys
import collections
input = sys.stdin.readline
n ,k = map(int, input().split())
queue= collections.deque()
arr = []
visted = [0] * (k+1)
for i in range(0, n):
m = int(input().strip())
queue.append(m)
arr.append(m)
level = 0
check = True
while queue :
if check == False :
break
... | loveminpic/K-Jungle | Week3/2294.py | 2294.py | py | 872 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "sys.stdin",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "collections.deque",
"line_number": 7,
"usage_type": "call"
}
] |
374749671 | import os;os.system('cls')
import tkinter as tk
from tkinter.messagebox import showinfo
window = tk.Tk()
window.geometry("300x180")
window.resizable(False,False)
###Get the alarm time from the user
Format = [
"12",
"24"
]
Form = tk.StringVar(window)
Form.set(Format[0])
hrformat=tk.OptionMenu(window,Form,*Format)
Hour =... | kamachisundaram/Python_Codes | python-alarmClock/AlarmClock.py | AlarmClock.py | py | 2,534 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "os.system",
"line_number": 1,
"usage_type": "call"
},
{
"api_name": "tkinter.Tk",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "tkinter.StringVar",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "tkinter.OptionMenu",
"line_n... |
10781870012 | from urllib.request import *
import json
import pandas as pd
import numpy as np
with urlopen("https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol=NSE:SBIN&interval=1min&outputsize=full&apikey=08AXPZ0UQEVKUSD8") as response:
source = response.read()
finalData={} # This should contain our final o... | webclinic017/Trading-Application | historical data.py | historical data.py | py | 5,122 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "numpy.nan",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "json.loads",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame.from_dict",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame... |
21772281957 | import logging
from datetime import datetime, timedelta
from enum import Enum
from threading import Thread, Event
from typing import List
from .adapter import SpiderEventAdapter
from ..spider import BaseSpider, SpiderFactory
from ..source import EventsSource, ClassroomSource, Classroom, Building
from .settings import ... | manu0466/BookingBot | src/booking/scheduler/Scheduler.py | Scheduler.py | py | 5,798 | python | en | code | 5 | github-code | 21 | [
{
"api_name": "enum.Enum",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "threading.Thread",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "source.EventsSource",
"line_number": 35,
"usage_type": "name"
},
{
"api_name": "source.ClassroomSource... |
12642241725 | import pygame as pg
from pygame import gfxdraw
import noise
import math
import settings
import numpy as np
import terrain_utils
from PIL import Image, ImageDraw
WIDTH = 1000
HEIGHT = 1000
ZOOM = 10
DETAIL_LEVEL = 10
pg.init()
screen = pg.display.set_mode((WIDTH, HEIGHT))
image = Image.new(mode = "RGB", size = (WIDT... | TheLightmare/perlin_noise | terrain.py | terrain.py | py | 3,416 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "pygame.init",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pygame.display.set_mode",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pygame.display",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image.new... |
5535893964 | import numpy as np
import matplotlib.pyplot as plt
# This is a new file
class SpikePlot:
def __init__(self):
self.x = None
self.y = None
def plot(self, *args):
max_len = 0
num_waveforms = len(args)
waveforms = []
for arg in args:
# if not isi... | totinos/SNN-Simulator | snn_sim/sim/spike_plot.py | spike_plot.py | py | 1,662 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "numpy.repeat",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "numpy.append",
"line_numbe... |
25564748868 | # Odnos ukupnoog stanovništva i prekršaja po regiji
import os
from datetime import datetime
from pyspark import SparkContext, SparkConf
from pyspark.sql import SparkSession
from pyspark.sql.functions import *
from pyspark.sql.types import *
def quiet_logs(sc):
logger = sc._jvm.org.apache.log4j
logger... | cinc98/ASVSP | batch/primeri/primer9.py | primer9.py | py | 1,467 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "pyspark.SparkConf",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pyspark.SparkContext",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pyspark.sql.SparkSession",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "os.en... |
2675592845 | #!/usr/bin/env python3
import uproot
import uproot3
import numpy as np
import pandas as pd
import sys
import track_reconstruction_old as tr
def Create_tracks(Profiling):
root_file = '/home/ecal/Documents/scripts/Analysis/Data/10h/data_0000.root'
Tname = 'board_57'
br_list_data = ['n_hits', 'tofpet_id', '... | demetriougreo/Ecal2022 | Analyse/Track_reconstruction/track_file_creation_old.py | track_file_creation_old.py | py | 2,570 | python | en | code | 3 | github-code | 21 | [
{
"api_name": "uproot.open",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame.from_dict",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "numpy.em... |
38660631891 | ### - character.py - ###
"""
Date de la création du fichier : 04/07/2017
Date de la dernière édition du fichier : 19/02/2018
"""
### import ###
import pygame
from pygame.locals import *
from game import Event
class Character :
def __init__(self, hauteurPersonnage, vitessePerso, fenetre) :
... | JordanCourne/Jet-Pack-Game | character.py | character.py | py | 6,343 | python | fr | code | 0 | github-code | 21 | [
{
"api_name": "pygame.image.load",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pygame.image",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "pygame.transform.smoothscale",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pyga... |
30637548350 | """
Solution for 1186. Maximum Subarray Sum with One Deletion1186. Maximum Subarray Sum with One Deletion
https://leetcode.com/problems/maximum-subarray-sum-with-one-deletion/
"""
from typing import List
class Solution:
"""
Runtime: 368 ms, faster than 22.87% of Python3 online submissions for Maximum Subarray ... | KKosukeee/CodingQuestions | LeetCode/1186_maximum_subarray_sum_with One_deletion.py | 1186_maximum_subarray_sum_with One_deletion.py | py | 2,453 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "typing.List",
"line_number": 12,
"usage_type": "name"
}
] |
9560682814 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
from sklearn.preprocessing import MinMaxScaler
from torch.utils.data import DataLoader, Dataset
from models import *
df = pd.read_csv("../data/demandData.csv")
df = df.drop("Unnamed: 0", axis=1)
df = df.drop("tar... | TahaBinhuraib/energy_datascience | src/demand_prediction.py | demand_prediction.py | py | 3,970 | python | en | code | 3 | github-code | 21 | [
{
"api_name": "pandas.read_csv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "torch.device",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
... |
14437233084 | import requests
import os
import json
import pymongo
import time
import datetime
from influxdb import InfluxDBClient
time.sleep(5)
INFLUX_HOST = os.environ['INFLUX_HOST']
MONGO_HOST = os.environ['MONGO_HOST']
influxdb_client = InfluxDBClient(host=INFLUX_HOST, port=8086)
influxdb_client.create_database('vega_history'... | bitcoinbill0/vega-protocol-explorer | collector/app.py | app.py | py | 2,950 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "time.sleep",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "influxdb.InfluxDBClient",
... |
43708707490 | from gc import callbacks
import numpy as np
from scipy.interpolate import RectBivariateSpline, UnivariateSpline
from datasets import get_exp_info
import pdf
from callbacks import ValidationCheckCallback, UpdateMultipliersCallback
import tensorflow as tf
from tensorflow.keras.layers import Input, Lambda
from tensorflo... | andrey-jpm/prometheus | src/fitter.py | fitter.py | py | 13,552 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "tensorflow.keras.optimizers.RMSprop",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.keras.optimizers",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "tensorflow.keras.optimizers.Adam",
"line_number": 20,
"usage_type": ... |
6174543096 | from django.apps import AppConfig
from django.utils.translation import gettext_lazy as _
print("*** loading nanoc app")
class PluginApp(AppConfig):
name = "pretalx_nanoc_exporter"
verbose_name = "Pretalx exporter for nanoc (FOSDEM)"
class PretalxPluginMeta:
name = _("Pretalx exporter for nanoc (F... | FOSDEM/pretalx-integration | pretalx-nanoc-yaml-exporter/pretalx_nanoc_exporter/apps.py | apps.py | py | 617 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "django.apps.AppConfig",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "django.utils.translation.gettext_lazy",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "django.utils.translation.gettext_lazy",
"line_number": 13,
"usage_type": "call... |
536908172 | import logging
import json
import jsonschema
from jsonschema import validate
def assert_status_code(response, expected_code):
assert response.status_code == expected_code, f"An unexpected status code was received.\n" \
f"Expected: {expected_code}, but {response.st... | lgonzalez95/Python-API-Testing | src/utilities/AssertionUtility.py | AssertionUtility.py | py | 1,366 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "jsonschema.validate",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "jsonschema.exceptions",
"line_number": 20,
"usage_type": "attribute"
}
] |
41476486312 | import sqlite3
conn = sqlite3.connect('emaildb.sqlite')
cur = conn.cursor()
cur.execute('DROP TABLE IF EXISTS domains')
cur.execute('DROP TABLE IF EXISTS counts')
cur.execute('''
CREATE TABLE counts (org TEXT, count INTEGER)''')
f=open("mbox.txt", "r")
for line in f:
if not line.startswith('From: '): contin... | dancoder-engineer/Python-Homeworks | 01 - Homeworks/07 - SQL/SQLite.py | SQLite.py | py | 663 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "sqlite3.connect",
"line_number": 3,
"usage_type": "call"
}
] |
8141201916 | import time
import json
import numpy as np
import pandas as pd
import spotipy
from spotipy.oauth2 import SpotifyClientCredentials
import apikey
json_file = open('setting.json', 'r')
setting = json.load(json_file)
def main():
ccm = SpotifyClientCredentials(client_id = apikey.my_id, client_secret = ... | feruworld/anisong_bpm | 02_make_playlist.py | 02_make_playlist.py | py | 1,820 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "json.load",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "spotipy.oauth2.SpotifyClientCredentials",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "apikey.my_id",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "a... |
28801924457 | import sys
import io
_INPUT = """\
4
0 3 1 4
1 0 5 9
2 6 0 5
3 5 8 0
"""
sys.stdin = io.StringIO(_INPUT)
# 巡回セールスマン問題
# 全ての地点を訪れるための最小の労力を調べる
# DP[S][v] := 集合の全体のうちの部分集合Sの順列の中で、vが末項となるもののうち、最も最適なもののコスト
import sys
import math
N = int(sys.stdin.readline())
dp = [[math.inf for _ in [0] * N] for _ in [0] * (2**N)]
cos... | Satjopg/atcoder | typical_algorithm/003.py | 003.py | py | 554 | python | ja | code | 0 | github-code | 21 | [
{
"api_name": "sys.stdin",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "io.StringIO",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "sys.stdin.readline",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "sys.stdin",
"line_n... |
1917249565 | from sqlalchemy import Column, String, create_engine, Table, MetaData, Column, Integer
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base
from urllib.parse import quote_plus
dbuser = 'sa'
dbpwd = 'test@local'
dbhost = 'localhost'
dbname = 'test'
db_uri = "mssql+pymssql://{}... | akimisen/kawaii | test.py | test.py | py | 733 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "urllib.parse.quote_plus",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.create_engine",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.MetaData",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "... |
39913316647 | from collections import Counter, defaultdict
import operator
import math
import pandas as pd
import scipy
from tqdm import tqdm_notebook
def add_time_rank_to_dataframe(df):
# Set mails with absurd dates to date before any real mail
min_date_string = '1998-12-20 00:00:01'
correct_prefix = [c... | GeoffNN/ALTEGRADEnron | src/recencytools.py | recencytools.py | py | 8,231 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "pandas.to_datetime",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "tqdm.tqdm_notebook",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "collections.Counter",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "operator.it... |
11157859556 | from copy import copy
import numpy as np
from sklearn.preprocessing import StandardScaler, MinMaxScaler
from itertools import compress
from typing import Union
import pandas as pd
from typing import List
from nexa_preprocessing.normalization.methods import select_scaler
from nexa_preprocessing.normalization.check_l... | timlac/nexa-preprocessing | nexa_preprocessing/normalization/low_level.py | low_level.py | py | 2,986 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "typing.List",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "typing.Union",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "numpy.ndarray",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "pandas.DataFrame",
"l... |
24761288910 | import os
import sys
from pyspark.ml.feature import OneHotEncoder,StringIndexer,VectorAssembler,StandardScaler
from pyspark.ml.pipeline import Pipeline
from churn_predication.config.spark_manager import spark
from churn_predication.exception import ChurnException
from churn_predication.logger import logging
from pyspar... | hdesai0436/Telco-Churn | churn_predication/component/data_tranformation.py | data_tranformation.py | py | 5,145 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "churn_predication.entity.config_entity.DataTransformationConfig",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "churn_predication.entity.config_entity.DataValidationConfig",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "churn_predication.ent... |
25786135868 | from __future__ import absolute_import
import base64
import hmac
import hashlib
from six import text_type, b, PY3
from libthumbor.url import unsafe_url, plain_image_url
class CryptoURL(object):
'''Class responsible for generating encrypted URLs for thumbor'''
def __init__(self, key):
'''
I... | kivicode/EuroBot_2019 | Python/ColorDetector/venv/lib/python3.6/site-packages/libthumbor/crypto.py | crypto.py | py | 1,496 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "six.text_type",
"line_number": 24,
"usage_type": "argument"
},
{
"api_name": "hmac.new",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "six.b",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "hashlib.sha1",
"line_number": 28... |
37345751816 | #processes bagfile and runs optimization on each separated trajectory
#Schmittle
#romesc
import argparse
import rosbag
import math
import numpy as np
import tf.transformations
import librhc.utils as utils
import rhctensor
import librhc.types as types
import matplotlib.pyplot as plt
import os
CROP_SQUARE_SZ = 200
de... | romesco/correctiveFB_utils | ros_util/process_rosbag.py | process_rosbag.py | py | 7,466 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "tf.transformations.transformations.euler_from_quaternion",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "tf.transformations.transformations",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "tf.transformations",
"line_number": 21,
... |
41892984485 | # modified from https://github.com/ZhuangLab/storm-analysis/blob/master/storm_analysis/sa_utilities/read_tagged_spot_file.py
import sys
import struct
import google.protobuf.internal.decoder as decoder
import TSFProto_pb2
if (len(sys.argv)<2):
print("usage: <tsf file>")
exit()
tsf_file_path = sys.argv[1]
if l... | imodpasteur/TaggedSpot2CSV | TaggedSpot2CSV.py | TaggedSpot2CSV.py | py | 2,831 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "sys.argv",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number"... |
41754336416 | import argparse
import os
import sys
import logging
import yaml
import dotenv
from taggedlist import TaggedLists, AnnotatedResults
def main():
has_dotenv = True if os.environ.get('DOTENV') != None else False
dotenv.load_dotenv(os.environ.get('DOTENV','.env'), verbose = has_dotenv, override = has_dotenv)
p... | matgoebl/taggedlistbrowser-cloud | src/taggedlist/__main__.py | __main__.py | py | 3,586 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "os.environ.get",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "dotenv.load_dotenv",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.environ.get",
... |
13415678775 | from copy import deepcopy
from functools import cached_property
import vigorish.database as db
from vigorish.constants import TEAM_ID_MAP
from vigorish.data.metrics.pitch_stats import PitchStatsMetrics
from vigorish.data.metrics.pitch_stats.player_pitch_stat_metrics import PlayerPitchStatsMetrics
from vigorish.data.me... | a-luna/vigorish | src/vigorish/data/metrics/pitch_stats/pitch_stats_metrics_factory.py | pitch_stats_metrics_factory.py | py | 4,417 | python | en | code | 2 | github-code | 21 | [
{
"api_name": "vigorish.data.metrics.pitch_stats.player_pitch_stat_metrics.PlayerPitchStatsMetrics",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "vigorish.data.metrics.pitch_stats.team_pitch_stat_metrics.TeamPitchStatsMetrics",
"line_number": 15,
"usage_type": "name"
},
... |
8044528788 | """
Test fixtures and utilities for creating and using CRS repositories
"""
from pathlib import Path
from typing import Any, Callable, Iterable, NamedTuple, Union
import pytest
from typing_extensions import Literal
from ..bpt import BPTWrapper
from .fixtures import TempPathFactory
from .fs import TempCloner
from .ht... | vector-of-bool/bpt | tools/bpt_ci/testing/repo.py | repo.py | py | 3,333 | python | en | code | 292 | github-code | 21 | [
{
"api_name": "pathlib.Path",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "bpt.BPTWrapper",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "typing.Union",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "pathlib.Path",
"line_num... |
28502320331 | # 394. Decode String
# Given an encoded string, return its decoded string.
# The encoding rule is: k[encoded_string], where the encoded_string
# inside the square brackets is being repeated exactly k times. Note
# that k is guaranteed to be a positive integer.
# You may assume that the input string is always valid; ... | DmitryVlaznev/leetcode | 394-decode-string.py | 394-decode-string.py | py | 2,800 | python | en | code | 2 | github-code | 21 | [
{
"api_name": "utils.checkValue",
"line_number": 78,
"usage_type": "call"
},
{
"api_name": "utils.checkValue",
"line_number": 79,
"usage_type": "call"
},
{
"api_name": "utils.checkValue",
"line_number": 80,
"usage_type": "call"
},
{
"api_name": "utils.checkValue",... |
32875776131 | import unittest
from choconaga1874 import solve
from itertools import permutations
class Test(unittest.TestCase):
def test_no_crash(self):
n = 8
for lst in permutations(range(1,n+1)):
solve(list(lst))
if __name__ == '__main__':
unittest.main() | yeardream-high6/coding_test | 곽치영/백준/나동빈 강사님 - 유형별 문제풀이/01 기본 자료구조/01-3 1874 스택 수열/test1874.py | test1874.py | py | 281 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "unittest.TestCase",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "itertools.permutations",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "choconaga1874.solve",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "unitte... |
24292919736 | import requests
from bs4 import BeautifulSoup
import logging
fmt = "%(asctime)s [%(levelname)s]: %(message)s"
logging.basicConfig(level=logging.INFO, format=fmt)
url = "https://www.nike.com/cz/w/muzi-obuv-nik1zy7ok"
logging.info("Scraping: ")
r = requests.get(url)
logging.info("DONE")
if r.status_code != 200:
lo... | MasnaKaczucha/scraper | main.py | main.py | py | 1,588 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "logging.basicConfig",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "logging.info",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "requests.get",
"l... |
23170665006 | """Add sync columns
Revision ID: d063cab9613d
Revises: 117f1504ed6c
Create Date: 2023-04-20 16:07:28.600462
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = 'd063cab9613d'
down_revision = '117f1504ed6c'
branch_labels = None
depends_on = None
def upgrade() -> N... | David1906/Xandra | alembic/versions/d063cab9613d_add_sync_columns.py | d063cab9613d_add_sync_columns.py | py | 1,060 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "alembic.op.add_column",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "alembic.op",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "sqlalchemy.Column",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.Boolean... |
5606530674 | import numpy as np
from pydrake.all import JacobianWrtVariable
from pydrake.multibody.tree import Frame
from dataclasses import dataclass
# Global variables for gait timing
LEFT_STANCE = 0
RIGHT_STANCE = 1
STANCE_DURATION = 0.2
def get_fsm(t: float) -> int:
if np.fmod(t, 2 * STANCE_DURATION) > STANCE_D... | git-dhruv/Hop-Skip-and-Jump | src/utils.py | utils.py | py | 3,917 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "numpy.fmod",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.fmod",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pydrake.multibody.tree.Frame",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "numpy.ndarray",
... |
32785249561 | #!/usr/bin/env python3
import PIL.Image
import os
from pathlib import Path
ASCII_CHARS = ['@', '#', 'S', '%', '?', '*', '+', ';', ':', ',', '.']
def resize_image(image, new_width):
width, height = image.size
ratio = height / width
new_height = int(new_width * ratio)
resized_image = image.resize((ne... | alanwsmith/ascii-art.alanwsmith.com | scripts/converter/convert.py | convert.py | py | 1,083 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "PIL.Image.Image.open",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "PIL.Image.Image",
"line_number": 33,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image",
"line_number": 33,
"usage_type": "name"
}
] |
42218140834 | import selenium
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.common.by import By
from time import sleep
from selenium.webdriver.firefox.options import Options
from tqdm import tqdm
options = Options()
options.headless = False
webdriver = webdriver.Firefox(opt... | koljapluemer/inspirationbot | webscraper/wiki_singer_songwriter.py | wiki_singer_songwriter.py | py | 2,181 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "selenium.webdriver.firefox.options.Options",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "selenium.webdriver.Firefox",
"line_number": 13,
"usage_type": "call"
},
... |
26324561066 | import cv2
import numpy as np
import time
import os
import openpyxl
import pyautogui
import pytesseract
from PIL import Image as im
import pyautogui as pg
import easygui
pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"
time.sleep(2)
print("STARTED")
def takeSS(mode)... | MusadiqPasha/Sudoko-Solver | sudokosolver.py | sudokosolver.py | py | 7,532 | python | en | code | 3 | github-code | 21 | [
{
"api_name": "pytesseract.pytesseract",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "time.sleep",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pyautogui.screenshot",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "pyautogu... |
37129085941 | import csv
import pandas as pd
import matplotlib.pyplot as plt
Montezuma_DQN = pd.read_csv('csv/MontezumaRevenge-v0_DQN.csv')
Montezuma_DoubleDQN = pd.read_csv('csv/MontezumaRevenge-v0_DoubleDQN.csv')
Montezuma_DuelingDQN = pd.read_csv('csv/MontezumaRevenge-v0_DuelingDQN.csv')
DQN_STEP = Montezuma_DQN['Step'].tolist(... | twelcone/CS211_Assignment02 | break_montezuma.py | break_montezuma.py | py | 1,783 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "pandas.read_csv",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.rcPara... |
10083303911 | import streamlit as st
from langchain.vectorstores import VectorStore
from langchain.embeddings.openai import OpenAIEmbeddings
_extension_map = {}
def _extension(*ext):
def decorator(f):
for e in ext:
_extension_map[e] = f
return f
return decorator
@_extension("txt")
def load_txt(d... | amwaters/LangChainTemplate | Source/packages/utils/files.py | files.py | py | 1,477 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "langchain.vectorstores.VectorStore",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "langchain.document_loaders.TextLoader",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "langchain.vectorstores.VectorStore",
"line_number": 20,
"usage_t... |
16925652642 | import socketio
import re
import time
# define the countdown func.
from utiles import get_current_active_user, User , Depends, AuthJWT, users_collection, role_collection, retrieve_roles
room_number = 0
room_dict = {}
names_list = []
players = []
player = {}
messages = []
messages_dict = {}
history = {}
clients = []... | Mokhles-Abdelmonem/socket-io-app-fastapi-react | server/sockets.py | sockets.py | py | 31,020 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "socketio.AsyncServer",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "socketio.ASGIApp",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "utiles.users_collection.find_one",
"line_number": 102,
"usage_type": "call"
},
{
"api_name"... |
28502212731 | # 323. Number of Connected Components in an Undirected Graph
# Medium
# You have a graph of n nodes. You are given an integer n and an array
# edges where edges[i] = [ai, bi] indicates that there is an edge
# between ai and bi in the graph.
# Return the number of connected components in the graph.
# Example 1:
# In... | DmitryVlaznev/leetcode | 323-number-of-connected-components-in-an-undirected-graph.py | 323-number-of-connected-components-in-an-undirected-graph.py | py | 1,169 | python | en | code | 2 | github-code | 21 | [
{
"api_name": "typing.List",
"line_number": 31,
"usage_type": "name"
}
] |
32287069630 | import subprocess
import os
import time
import sys
from django.conf import settings
def makeFile(name, code, extension):
name = name.replace(" ", "_")
name = settings.SUBMISSION_ROOT+name+"."+extension
with open(name, 'w') as f:
code = code.replace("\r", "")
f.write(code)
return name
... | dnhirapara/Online-IDE | IDEApp/runCode.py | runCode.py | py | 1,184 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "django.conf.settings.SUBMISSION_ROOT",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "django.conf.settings",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "subprocess.run",
"line_number": 19,
"usage_type": "call"
},
{
"api... |
31052956983 | import tkinter as tk
import customtkinter
import time
import os
import sys
from PIL import Image, ImageTk
import others
from serial_interface import write_to_computer as write
class Window:
padding = 3
button_size = 50
def __init__(self, edit):
self.converter = LatexToImage()
self.edit = ed... | CyrilGremaud3141/LaTeX_Keyboard_Software | code_of_raspberry_pi/gui.py | gui.py | py | 3,699 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "customtkinter.set_appearance_mode",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "customtkinter.set_default_color_theme",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "customtkinter.CTk",
"line_number": 19,
"usage_type": "call"
},
... |
9232475824 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jun 9 17:02:35 2020
@author: Broth
"""
import requests
from bs4 import BeautifulSoup
import pandas as pd
import numpy as np
def article_scraper(url):
'''
Function that scrapes the article title, author, and text from input url
'''
#tr... | Ben-Roth-MS-DS/Masters-Capstone | scraping/azcapitoltimes.py | azcapitoltimes.py | py | 5,138 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "requests.get",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "numpy.nan",
"line_number": 38,
"usage_type": "attribute"
},
{
"api_name": "pandas.DataFrame",
... |
47171071144 | #Criando uma tabela arrow a partir de uma lista de dicionarios
import pyarrow as pa
dados = [{"nome": "João", 'idade':25}, {"nome": "Maria", 'Idade': 30}, {"nome": "Thiago", "Idade": 33}]
tabela = pa.Table.from_pandas(pd.Dataframe(dados))
#Escrevendo e lendo uma tabela arrow de/para um arquivo
dados = {"nomes":["João... | demetriusengdados/ScikitLearn-e-Tensorflow-main | pyarrow.py | pyarrow.py | py | 1,531 | python | pt | code | 0 | github-code | 21 | [
{
"api_name": "pyarrow.Table.from_pandas",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pyarrow.Table",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "pyarrow.Table.from_pandas",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "p... |
31276476979 | import pandas as pd
import numpy as np
import os
from sklearn.covariance import EmpiricalCovariance
from pyRMT import clipped, optimalShrinkage
from tqdm import tqdm
from CollectTicker import collect_ticker
from TAQQuotesReader import TAQQuotesReader
data_path = 'C:\\Users\\Admin\\PycharmProjects\\Algo-HW_3\\data\\quo... | WeiYuan01070/Algo-HW_3 | TAQ_rolling.py | TAQ_rolling.py | py | 5,156 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "pyRMT.clipped",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "sklearn.covariance.EmpiricalCovariance",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "pyRMT.optimalShrinkage",
"line_number": 32,
"usage_type": "call"
},
{
"api_n... |
18572225857 | import random
import time
from selenium.common.exceptions import NoSuchElementException
from selenium.webdriver import ActionChains
from selenium.webdriver.common.by import By
from Pages.OrderPage import OrderPage
class Base:
def __init__(self, driver):
self.driver = driver
self.checkout = Orde... | TienThuong/Test-Final-Project | Test/BaseTest.py | BaseTest.py | py | 3,530 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "Pages.OrderPage.OrderPage",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver.common.by.By.XPATH",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "selenium.webdriver.common.by.By",
"line_number": 22,
"usage_type": "... |
2098130451 | import os
import numpy as np
from PIL import Image
import random
import glob
def main():
path = '/Users/bytedance/Documents/data/test_tmp/result'
out_path = '/Users/bytedance/Documents/data/test_tmp/tmp'
data_list = [item for item in glob.glob(path + '/*.png') if 'mask' not in item]
n_total = len(data_... | xiaozhoushi/my_script | matplotlib/seg_show.py | seg_show.py | py | 1,544 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "glob.glob",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path.basename",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image.open",
"line_nu... |
42538987981 | import json
import os
import tqdm
import _jsonnet
from seq2struct import datasets
from seq2struct.utils import registry
def compute_metrics(config_path, config_args, section, inferred_path,logdir=None, evaluate_beams_individually=False):
if config_args:
config = json.loads(_jsonnet.evaluate_file(config_p... | rshin/seq2struct | seq2struct/utils/evaluation.py | evaluation.py | py | 2,197 | python | en | code | 22 | github-code | 21 | [
{
"api_name": "json.loads",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "_jsonnet.evaluate_file",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "_jsonnet.evaluate_file",... |
41911612736 | import re
from nltk.stem import PorterStemmer
import nltk
nltk.download('punkt')
from nltk.tokenize import word_tokenize
stopwords_english = []
sentences_clean = []
def __init__():
with open('src/Stopword-List.txt', 'r') as f:
stopWord = f.readline()
while stopWord:
stopw... | AhmedAshraf982/PyBoolSearch | src/utils.py | utils.py | py | 1,422 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "nltk.download",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "nltk.stem.PorterStemmer",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "nltk.tokenize.word_tokeni... |
41784281405 | """Script to evaluate the experiment for figure1. This is done by plotting the proportion of
easy examples against the inverse kl divergence and classification performance."""
from pathlib import Path
from typing import List
import numpy as np
import pandas as pd
import plotnine as pn
from application.constants imp... | HLasse/data-centric-synthetic-data | src/application/figure1/evaluate_figure1.py | evaluate_figure1.py | py | 10,141 | python | en | code | 1 | github-code | 21 | [
{
"api_name": "pathlib.Path",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "application.figure1.run_figure1_exp.POCExperiment",
"line_number": 20,
"usage_type": "name"
},
{
"api_na... |
41388633606 | import numpy as np
import os
from datetime import datetime
from auxiliary import epsilonize
from DemonModel import RACTION_SET, FEATURES, INITIALSTATE, \
action_value, daction_value, \
get_actions, is_terminal, take_action
os.chdir(os.path.dirname(os.path.abspath(__file__))... | BibarelUsedFly/reinforcement-learning | non tabular/Controller.py | Controller.py | py | 5,843 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "os.chdir",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number... |
42183456063 | import os
import itertools
import numba as nb
from math import sqrt
import numpy as np
import pandas as pd
@nb.jit(nopython=True)
def searchsorted(arr, x, N=-1):
"""N is length of arr
"""
if N == -1:
N = len(arr)
L = 0
R = N - 1
done = False
eq = False
m = (L + R) // 2
wh... | timothydmorton/isochrones | isochrones/interp.py | interp.py | py | 20,283 | python | en | code | 112 | github-code | 21 | [
{
"api_name": "numba.jit",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "numba.uint32",
"line_number": 42,
"usage_type": "attribute"
},
{
"api_name": "numpy.zeros",
"line_numbe... |
70749945653 | #!/usr/bin/env python3
"""
This model uses LSTM and Attention to predict the
ratings and category of a business review
"""
import torch
import torch.nn as tnn
import torch.nn.functional as F
from torch.nn.utils.rnn import pad_packed_sequence, pack_padded_sequence
import torch.optim as toptim
from torchtext.vocab impo... | ivan-pua/business-review-prediction | lstm_attention_model.py | lstm_attention_model.py | py | 8,506 | python | en | code | 0 | github-code | 21 | [
{
"api_name": "nltk.download",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords.words",
"line_number": 53,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopword... |
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