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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
7414775356 | from __future__ import unicode_literals, print_function, division
__author__ = "mozman <mozman@gmx.at>"
import os
import zipfile
import random
from datetime import datetime
from .xmlns import etree, CN
from .manifest import Manifest
from .compatibility import tobytes, bytes2unicode, is_bytes, is_zipfile
from .compati... | T0ha/ezodf | ezodf/filemanager.py | filemanager.py | py | 7,721 | python | en | code | 61 | github-code | 1 | [
{
"api_name": "datetime.datetime.now",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "zipfile.ZipInfo",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "zipfile.ZIP_D... |
23466715421 | #!/usr/bin/python3
from brownie import CallMeChallenge
from scripts.deploy import deploy
from scripts.helpful_scripts import get_account
from colorama import Fore
# * colours
green = Fore.GREEN
red = Fore.RED
blue = Fore.BLUE
magenta = Fore.MAGENTA
reset = Fore.RESET
def print_colour(target, solved=False):
if so... | Aviksaikat/Blockchain-CTF-Solutions | capturetheether/warmup/CallMe_DONE/scripts/hack.py | hack.py | py | 1,151 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "colorama.Fore.GREEN",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "colorama.Fore",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "colorama.Fore.RED",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "colorama.F... |
39906386971 | from sklearn.model_selection import train_test_split
import tensorflow as tf
import keras
import os
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
from os import listdir
from matplotlib import image
import random
from keras.utils import np_utils
from keras import callbacks
# batch_size = high... | jansowa/pneumonia-model | load_data.py | load_data.py | py | 4,145 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "tensorflow.io.gfile.glob",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "tensorflow.io",
"line_number": 34,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.io.gfile.glob",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "... |
40529127357 | import bpy
from bpy.types import NodeSocket
from . import ProkitekturaContainerNode
class ProkitekturaDemoAdvancedAttr(ProkitekturaContainerNode, bpy.types.Node): # make ProkitekturaNode the first super() in multiple inheritance
# Optional identifier string. If not explicitly defined, the python class na... | vvoovv/blosm-nodes | node/demoNode.py | demoNode.py | py | 4,620 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "bpy.types",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "bpy.props.BoolProperty",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "bpy.props",
"line_number": 51,
"usage_type": "attribute"
},
{
"api_name": "bpy.props.IntProp... |
16625738937 | """ GLPointCloudPlotItem.py - extension of pyqtgraph for plotting pointclouds
This file implements an extension of pyqtgraph for visualizing PointClouds.
Last update: 04/10/2013, Tadewos Somano(tadewos85@gmail.com)
"""
from OpenGL.GL import *
from pyqtgraph.opengl.GLGraphicsItem import GLGraphicsItem
__all__ =... | GeoDTN/Communication-Technologies-Multimedia | GLPointCloudPlotItem.py | GLPointCloudPlotItem.py | py | 2,544 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pyqtgraph.opengl.GLGraphicsItem.GLGraphicsItem",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "pyqtgraph.opengl.GLGraphicsItem.GLGraphicsItem.__init__",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "pyqtgraph.opengl.GLGraphicsItem.GLGraphics... |
4538885674 | # Helper functions for stochastic raytracer
import numpy as np
import pickle
import matplotlib.pyplot as plt
from scipy import interpolate
from sklearn import preprocessing
# Create a linear interpolant in each of the x, y, z directions
def create_interpolant(xyz, g):
fx = interpolate.RegularGridInterpo... | Bryden38/579_project_code | stochastic_raytracer_helper.py | stochastic_raytracer_helper.py | py | 7,495 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "scipy.interpolate.RegularGridInterpolator",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "scipy.interpolate",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "scipy.interpolate.RegularGridInterpolator",
"line_number": 12,
"usage_type": ... |
73910447714 | __author__ = 'Victor Olaya'
__date__ = 'August 2012'
__copyright__ = '(C) 2012, Victor Olaya'
# This will get replaced with a git SHA1 when you do a git archive
__revision__ = '$Format:%H$'
import os
import codecs
import datetime
from processing.tools.system import userFolder
from processing.core.ProcessingConfig im... | nextgis/nextgisqgis | python/plugins/processing/core/ProcessingLog.py | ProcessingLog.py | py | 4,717 | python | en | code | 27 | github-code | 1 | [
{
"api_name": "processing.tools.system.userFolder",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.sep",
"line_number": 29,
"usage_type": "attribute"
},
{
"api_name": "os.path.isfile",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "os.path... |
33402238582 | import functools
words=input().split()
def validate(word):
letters=[]
for i in word:
if i.upper() not in letters:
letters.append(i.upper())
if len(letters)>3:
return True
return False
if __name__=='__main__':
answer1=list(filter(validate, words))
print(list(map(lambda... | Bulka148/IsmagilovB_11105 | task004.py | task004.py | py | 472 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "functools.reduce",
"line_number": 15,
"usage_type": "call"
}
] |
17360106168 | from datetime import datetime
from sqlalchemy import Column
from sqlalchemy.sql.sqltypes import Integer, Text, Date, Boolean
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class Follower(Base):
__tablename__ = 'follower'
id = Column(Integer, primary_key=True)
name = C... | MickaelBergem/unfollower | models.py | models.py | py | 573 | python | en | code | 6 | github-code | 1 | [
{
"api_name": "sqlalchemy.ext.declarative.declarative_base",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.Column",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.sql.sqltypes.Integer",
"line_number": 13,
"usage_type": "argument... |
28416232124 | #!/usr/bin/env python2
# [Ordered Dictionary for Py2.4 « Python recipes « ActiveState Code]
# (http://code.activestate.com/recipes/576693/)
from collections import OrderedDict
od = OrderedDict()
od["a"] = 1
od["b"] = 2
od["c"] = 4
od["d"] = 5
del od["a"]
od["a"] = 3
for k, v in od.iteritems():
print("{},{}".fo... | 10sr/junks | python/ordereddict.py | ordereddict.py | py | 627 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "collections.OrderedDict",
"line_number": 8,
"usage_type": "call"
}
] |
13806395486 | """
Yo que se ya
"""
import argparse
import mido
import logging
from timeit import default_timer as timer
from video import Video
# from moviepy.editor import *
DEBUG = True
def print_d(msg):
if DEBUG:
print(msg)
def maxSymNotes(notes):
curr = max = 0
for note in notes:
if note[2] == 0... | nestor98/pymidi2vid | editor.py | editor.py | py | 12,213 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "mido.MidiTrack",
"line_number": 122,
"usage_type": "call"
},
{
"api_name": "mido.Message",
"line_number": 124,
"usage_type": "call"
},
{
"api_name": "mido.merge_tracks",
"line_number": 126,
"usage_type": "call"
},
{
"api_name": "timeit.default_timer... |
34573074614 | import os
from os import getenv
from dotenv import load_dotenv
if os.path.exists("local.env"):
load_dotenv("local.env")
API_ID = int(getenv("API_ID", "6435225")) #optional
API_HASH = getenv("API_HASH", "") #optional
SUDO_USERS = list(map(int, getenv("SUDO_USERS", "").split()))
OWNER_ID = int(getenv("OWNER_ID"))... | ITZ-ZAID/ZAID-USERBOT | config.py | config.py | py | 1,235 | python | en | code | 167 | github-code | 1 | [
{
"api_name": "os.path.exists",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "dotenv.load_dotenv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_num... |
26661499475 | # -*- coding: utf-8 -*-
from scrapy import Spider, Request, FormRequest
from MobaiSpider.items import MobaispiderItem
import numpy as np
import json
import time
class MobaiSpider(Spider):
name = 'mobai'
# allowed_domains = ['mobike.com']
# start_urls = ['http://mobike.com/']
url = "https://mwx.mobike.... | jllan/spiders_mess | MobaiSpider/MobaiSpider/spiders/mobai.py | mobai.py | py | 2,846 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "scrapy.Spider",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "numpy.arange",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "MobaiSpider.items.MobaispiderI... |
42447368963 | """ Preprocess the ISBI data set.
"""
__author__ = "Mike Pekala"
__copyright__ = "Copyright 2015, JHU/APL"
__license__ = "Apache 2.0"
import argparse, os.path
import numpy as np
from scipy.stats.mstats import mquantiles
import scipy.io
import emlib
def get_args():
"""Command line parameters for the 'deploy'... | iscoe/coca | Experiments/CcT/preprocess.py | preprocess.py | py | 3,303 | python | en | code | 6 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "os.path.path.isdir",
"line_number": 70,
"usage_type": "call"
},
{
"api_name": "os.path.path",
"line_number": 70,
"usage_type": "attribute"
},
{
"api_name": "os.path"... |
185545694 | import pickle
import struct
from pathlib import Path
from interact import interact as io
from utils import Path_utils
import samplelib.SampleHost
from samplelib import Sample
packed_faceset_filename = 'faceset.pak'
class PackedFaceset():
VERSION = 1
@staticmethod
def pack(samples_path):
sample... | jem0101/BigSwag-SQA2022-AUBURN | TestOrchestrator4ML-main/resources/Data/supervised/GITLAB_REPOS/bytehackr@DeepFaceLab/samplelib/PackedFaceset.py | PackedFaceset.py | py | 3,627 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "interact.interact.log_info",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "interact.interact",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "interact.interact.input_bool",
"line_number": 23,
"usage_type": "call"
},
{
"api_nam... |
6468869212 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import random
def coin():
return random.randrange(0,2)
def coins20():
X = []
for i in range(0,20):
X.append(coin())
return X
def mili():
E = []
for i in range(0,1000000):
E.append(coins20()... | Testosterol/Machine-Learning---Python-2 | Assign2.py | Assign2.py | py | 5,960 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "random.randrange",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "numpy.shape",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplo... |
39605975671 | import pygame as pg
from pygame.math import Vector2
from src.camera import Camera
from src.game_objects.abstract.tile import Tile
from src.game_objects.movable_tile import MovableTile
from src.game_objects.selection_box import SelectionBox
from src.game_objects.static_tile import StaticTile
from src.graphics import Sp... | tmcgroul/GPD-4X | src/game_core.py | game_core.py | py | 5,377 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "src.main_loop.MainLoop",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "src.settings.constants.CAPTION",
"line_number": 27,
"usage_type": "argument"
},
{
"api_name": "src.settings.constants.SCREEN_SIZE",
"line_number": 27,
"usage_type": "argument... |
244144573 | __author__ = 'nipunbatra'
import numpy as np
import pandas as pd
def read_df():
df = pd.read_csv("../data/input/main-data.csv",index_col=0)
dfc = df.copy()
df = df.drop(871)
df = df.drop(1169)
w=df[['aggregate_%d' %i for i in range(1,13)]]
df = df.ix[w[w>0].dropna().index]
feature... | nipunbatra/Gemello | code/create_df.py | create_df.py | py | 7,664 | python | en | code | 18 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "itertools.combinations",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "numpy.hstack",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "numpy.percentile",... |
17114049075 | from django.urls import reverse_lazy
from django.views.generic.edit import FormView
from forum.forms import ContactForm
class ContactView(FormView):
template_name = 'pages/contact.html'
form_class = ContactForm
success_url = reverse_lazy('forum:home')
def form_valid(self, form):
form.send_em... | Projectca-r/it | itacademy-django/forum/views/contact.py | contact.py | py | 366 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.views.generic.edit.FormView",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "forum.forms.ContactForm",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "django.urls.reverse_lazy",
"line_number": 10,
"usage_type": "call"
}
] |
1402617285 | from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtWidgets import QFileDialog, QMessageBox
from PyQt5.QtCore import QTimer
import sys
import time
import csv
import os
import winsound
from libs import Track, getShiftRPM, fuelSavingOptimiser, rollOut
from libs.IDDU import IDDUThread, IDDUItem
from libs.auxiliaries i... | MarcMatten/iDDU | gui/iDDUgui.py | iDDUgui.py | py | 78,820 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "libs.IDDU.IDDUThread",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "libs.IDDU.IDDUThread.__init__",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "libs.IDDU.IDDUThread",
"line_number": 29,
"usage_type": "name"
},
{
"api_name"... |
15427212046 | import random
import requests
from currency_converter import CurrencyConverter
from forex_python.converter import CurrencyRates
def get_guess_from_user():
while True:
try:
guess = float(input("Enter your guess for the value in ILS: "))
break
except ValueError:
pr... | Almonk777/WorldOfGame | CurrencyRouletteGame.py | CurrencyRouletteGame.py | py | 1,720 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "currency_converter.CurrencyConverter",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 37,
"usage_type": "call"
}
] |
39974834021 | from tensorflow import keras
import matplotlib.pyplot as plt
from sklearn.metrics import confusion_matrix
import seaborn as sns
import numpy as np
from custom_models import custom_model, old_model
from data_preprocessing import Preprocessing
from data_augmentation import DataAugmentation
from config import ... | AnaChikashua/Georgian-OCR | model/train_ocr.py | train_ocr.py | py | 1,997 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "config.ConstantConfig",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras.callbacks.EarlyStopping",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras.callbacks",
"line_number": 18,
"usage_type": "attribute"
... |
3477761372 | from flask import Flask, jsonify, request, make_response
import torch
from transformers import BertTokenizer, BertModel
from sklearn.metrics.pairwise import cosine_similarity
import numpy as np
import pandas as pd
app=Flask(__name__)
# @app.route('/<string:text1>/<string:text2>')
@app.route('/post_json',me... | daringsingh22/sementicsimilar | app.py | app.py | py | 1,487 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "flask.request.get_json",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "flask.request",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "transformers.BertToke... |
72827279715 | import sys
from collections import deque
dx = [1,-1,0,0]
dy = [0,0,1,-1]
n,m = map(int,sys.stdin.readline().split())
arr = []
for _ in range(m):
arr.append(list(sys.stdin.readline().strip()))
visit = [[int(1e9)]*n for _ in range(m)]
queue = deque([[0,0]])
visit[0][0] = 0
while queue:
x,y = queue.popleft()
... | clapans/Algorithm_Study | 박수근/all_code/1261.py | 1261.py | py | 767 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sys.stdin.readline",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sys.stdin",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "sys.stdin.readline",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sys.stdin",
"l... |
29062292111 | from question_model import Question
from data import question_data
from quiz_brain import QuizBrain
question_bank = []
for question in question_data:
question_bank.append(Question(question["text"], question["answer"]))
brain = QuizBrain(question_bank)
while brain.stillHasQuestions():
brain.next_question()
... | miklealex/PythonProjects | TrueFalseQuiz/main.py | main.py | py | 429 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "data.question_data",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "question_model.Question",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "quiz_brain.QuizBrain",
"line_number": 10,
"usage_type": "call"
}
] |
18061408079 | from pathlib import Path
from tensorflow.keras import layers
from tensorflow.keras import models
from tensorflow.keras import optimizers
from tensorflow.keras.preprocessing.image import ImageDataGenerator
import tensorflow as tf
from solve_cudnn_error import solve_cudnn_error
solve_cudnn_error()
base_dir = Path('cats... | enrongtsai/Horovod-practice | original_cat_dog.py | original_cat_dog.py | py | 3,594 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "solve_cudnn_error.solve_cudnn_error",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras.models.Sequential",
"line_number": 30,
"usage_type": "call"
},
{
... |
33711265867 | import pandas as pd
from dateutil import parser
import numpy as np
def load_data(_file, pct_split):
"""Load test and train data into a DataFrame
:return pd.DataFrame with ['test'/'train', features]"""
# load train and test data
data = pd.read_csv(_file)
# split into train and test using pct_spli... | braddeutsch/example_pipeline | btc_battle/data/make_dataset.py | make_dataset.py | py | 1,960 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pandas.to_datetime",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "datetime.timedelta",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "numpy.min",
... |
26112150368 | # This files contains your custom actions which can be used to run
# custom Python code.
#
# See this guide on how to implement these action:
# https://rasa.com/docs/rasa/custom-actions
# This is a simple example for a custom action which utters "Hello World!"
from typing import Any, Text, Dict, List
#
from rasa_sdk... | RupakBiswas-2304/covid-bot | actions/actions.py | actions.py | py | 2,360 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "rasa_sdk.Action",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "typing.Text",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "rasa_sdk.Tracker",
"line_number": 33,
"usage_type": "name"
},
{
"api_name": "typing.Dict",
"line_... |
11373411713 | # -*- coding: utf-8 -*-
"""Implementation of the Airfield class."""
import logging
import random
import math
import pygame
from airportgame.runway import Runway
from airportgame.utilities import vec2tuple, distance_between
class Airfield():
"""
Airfield that contains runways.
"""
FIELD_HEIGHT = 200... | soikkea/airportgame | airportgame/airfield.py | airfield.py | py | 8,706 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "pygame.Surface",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "random.randint",
... |
1270621755 | import requests
import pandas as pd
from alpha_vantage.timeseries import TimeSeries
import numpy as np
def sharpe_sortino_beta(ticker='TSLA', market_returns='SPY'):
try:
ts = TimeSeries(key='SWKZ23Y8HKIF4N4A', output_format='pandas')
data, meta_data = ts.get_daily_adjusted(ticker)
... | HudsonHurtig/TamuHack2023 | StockData.py | StockData.py | py | 1,756 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "alpha_vantage.timeseries.TimeSeries",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "requests.codes",
"line_number": 38,
"usage_type": "attribute"
}
] |
42654133120 | #!/usr/bin/env python3
# Written by Telekrex
import pygame
import sys
import os
os.environ['SDL_VIDEO_CENTERED'] = '1'
tps = 30
pygame.init()
pygame.display.set_caption('Color Calibrator')
monitor = (pygame.display.Info().current_w, pygame.display.Info().current_h)
clock = pygame.time.Clock()
void = pygame.display.set_... | telekrex/colorbase | source/colorbase.py | colorbase.py | py | 1,018 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "os.environ",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "pygame.init",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pygame.display.set_caption",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pygame.display",
... |
13223932657 | from reference_model.Lactose.LactoseCrystallizer import LactoseCrystallizer
from data.Data import Data, Batch
from domain.Domain import Domain
import numpy as np
import seaborn as sns
from data.Illustration import Illustration
import matplotlib.pyplot as plt
sns.set()
# Construct discretized domain object for hybrid m... | rfjoni/ParticleModel | reference_model/Lactose/demo.py | demo.py | py | 1,694 | python | en | code | 7 | github-code | 1 | [
{
"api_name": "seaborn.set",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "domain.Domain",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "domain.Domain.Domain",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "domain.Domain.add_axis"... |
24349296351 | import json
from pprint import pprint
import requests
import logbook
from log_book import init_logger
logger = logbook.Logger(__file__)
def main():
init_logger('movie-app.log')
logbook.info("Starting the omdb search app...")
logbook.debug("Getting user's input...")
movie_name = get_user_input()
... | pgmilenkov/100daysofcode-with-python-course | days/40-42-json-data/omdb_parse.py | omdb_parse.py | py | 1,714 | python | en | code | null | github-code | 1 | [
{
"api_name": "logbook.Logger",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "log_book.init_logger",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "logbook.info",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "logbook.debug",
"... |
33524555484 | from tkinter import *
from tkinter.ttk import *
from tkinter import scrolledtext
import os
import tkinter.filedialog as filedialog
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
# Implement the default Matplotlib key bindings.
from matplotlib.backend_bases import key_press_handler... | JonathanCauchon/LunaUtils | GUI.py | GUI.py | py | 11,420 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "os.getcwd",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "tkinter.filedialog.askopenfile",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "tkinter.filedialog",
"line_number": 46,
"usage_type": "name"
},
{
"api_name": "matplotli... |
19388016465 | from audioop import ratecv
from pathlib import Path
import tkinter as tk
from tkinter import ttk
from tkinter.filedialog import askopenfilename
import PIL.Image
import PIL.ImageTk
# Defining of global variables...
_MODULE_DIR = Path(__file__).resolve().parent
class GifAnimationWin(tk.Tk):
def __init__(
... | megacodist/a-bit-more-of-an-interest | Image/gif-animation.pyw | gif-animation.pyw | pyw | 4,641 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pathlib.Path",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "tkinter.Tk",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "pathlib.Path",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "PIL.Image.ImageTk",
"li... |
40639476449 | from pygame.locals import *
import numpy as np
import os
import pygame
import sys
import time
from source.core.game_objects.bomb.Bomb import Bomb
from source.core.game_objects.bomb.Fire import Fire
from source.core.game_objects.character.Cpu import Cpu
from source.core.ui.GameOver import GameOver
from source.core.ui.M... | asilvaigor/bomberboy | source/core/engine/Match.py | Match.py | py | 10,719 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "os.path.dirname",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 35,
"usage_type": "attribute"
},
{
"api_name": "os.path.realpath",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "pygame.font.Font",
... |
10461388653 | """
Модуль для работы с базой данных sqlite3.
"""
import sqlite3
from typing import Dict
import os
PATH = 'db'
DATABASE = 'db.sqlite3'
connect = sqlite3.connect(os.path.join(PATH, DATABASE))
cursor = connect.cursor()
def create_db() -> None:
"""
Создает базу данных и таблицы в ней,
если база и таблицы ... | darkus007/FlatScrapper | database/db_sqlite.py | db_sqlite.py | py | 2,466 | python | ru | code | 0 | github-code | 1 | [
{
"api_name": "sqlite3.connect",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "typing.Dict",
"line_num... |
41629028008 | from jira import JIRA
import pandas as pd
from datetime import datetime
import plotly
import plotly.graph_objs as go
import numpy as np
from ast import literal_eval
from IPython.display import display, HTML
pd.set_option('display.max_columns', 999)
plotly.offline.init_notebook_mode()
def product_closed_time(version)... | matthewjwall/youi-product-flow-metrics | scripts/metrics_okrs.py | metrics_okrs.py | py | 8,557 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.set_option",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "plotly.offline.init_notebook_mode",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "plotly.offline",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name"... |
26276689512 | import pandas as pd
import json
import dash
from dash import dcc,html, callback
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import plotly.express as px
import dash_bootstrap_components as dbc
import numpy as np
import pathlib
dash.register_page(__name__, path = '/', name="Accueil")
## D... | louislat/deployer | pages/pg0.py | pg0.py | py | 2,800 | python | fr | code | 0 | github-code | 1 | [
{
"api_name": "dash.register_page",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame.from_dict"... |
70427983394 | import pandas as pd
import matplotlib.pyplot as plt
import os
class CoefficientAnalyzer:
def __init__(self, data_file):
"""
Initialize the CoefficientAnalyzer class.
"""
# Load the data for all trials from the CSV
self.data = pd.read_csv(data_file)
def calculate_coeffic... | NolanTrem/phys1494 | experiment1/motion_analyzer.py | motion_analyzer.py | py | 4,688 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 72,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 72,
"usage_type": "name"
},
{
"api_name": "matplotlib... |
31589162522 | import itertools
from osgeo import ogr,osr
import shapely.geometry
# Convert Shapely type to OGR type
shapely_to_ogr_type = {
shapely.geometry.linestring.LineString: ogr.wkbLineString,
shapely.geometry.polygon.Polygon: ogr.wkbPolygon,
}
def to_datasource(shape):
"""Converts an in-memory Shapely object t... | pism/uafgi | uafgi/util/shapelyutil.py | shapelyutil.py | py | 1,095 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "shapely.geometry.geometry",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "shapely.geometry",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "shapely.geometry.geometry",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_n... |
73286444834 |
from koza.cli_runner import koza_app
from loguru import logger
source_name = "mimtitles"
row = koza_app.get_row(source_name)
map = koza_app.get_map(source_name)
###
# From OMIM
# An asterisk (*) before an entry number indicates a gene.
#
# A number symbol (#) before an entry number indicates that it is a descrip... | monarch-initiative/monarch-ingest | src/monarch_ingest/maps/mimtitles.py | mimtitles.py | py | 2,943 | python | en | code | 11 | github-code | 1 | [
{
"api_name": "koza.cli_runner.koza_app.get_row",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "koza.cli_runner.koza_app",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "koza.cli_runner.koza_app.get_map",
"line_number": 9,
"usage_type": "call"
},
... |
18042327734 | # -*- coding: utf-8 -*-
from django import forms
from ..models import Programacao
class ProgramacaoForm(forms.ModelForm):
class Meta:
model = Programacao
fields = (
'programa', 'data_inicio', 'data_fim'
)
def clean(self):
cleaned_data = super(ProgramacaoForm, self... | rbiassusi/grade_programacao | grade_programacao/radio/forms/programacaoform.py | programacaoform.py | py | 549 | python | pt | code | 0 | github-code | 1 | [
{
"api_name": "django.forms.ModelForm",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "django.forms",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "models.Programacao",
"line_number": 9,
"usage_type": "name"
}
] |
23270541963 | """
Detection Recipe - 12.0.4.17
References:
(1) 'Asteroseismic detection predictions: TESS' by Chaplin (2015)
(2) 'On the use of empirical bolometric corrections for stars' by Torres (2010)
(3) 'The amplitude of solar oscillations using stellar techniques' by Kjeldson (2008)
(4) 'An absolutely calibrated Teff sca... | Fill4/tess-yield | tess-yield/TASC_detection_recipe.py | TASC_detection_recipe.py | py | 22,339 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "warnings.simplefilter",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "numpy.log10",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "numpy.full",
"line_number": 59,
"usage_type": "call"
},
{
"api_name": "numpy.log10",
"line_... |
31379366652 | from bs4 import BeautifulSoup as bs
import csv
import requests
URL = 'https://kaktus.media/?lable=8&date=2022-10-15&order=time'
dict_with_news = {}
def get_html(url):
response = requests.get(url)
return response.text
def get_soup(html):
soup = bs(html, 'lxml')
return soup
def get_list_news():
... | 31nkmu/hackathon_bot_kaktus_media | parsing.py | parsing.py | py | 1,183 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "requests.get",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 15,
"usage_type": "call"
}
] |
17828467348 | from django.contrib import admin
from django.urls import path,include
from . import views
urlpatterns = [
path('admin/', admin.site.urls),
path('',views.index,name='Home'),
path('aboutus/',views.aboutus,name='aboutUs'),
path('product/<int:prodId>',views.prodDetails,name='prodDetails'),
path('emptyC... | aman1100/thcProject | thcProject/thcProducts/urls.py | urls.py | py | 421 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "django.urls.path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.contrib.admin.site",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "dja... |
5530540643 | import config
from db import db_config
from db import db_users
#from calendar import cal
from flask import Flask, render_template, request
from pymessager.message import Messager
client = Messager(config.facebook_access_token)
import os
import json
from msg_handlers import main_handler, notification_handler, responses... | kartikye/sch | run.py | run.py | py | 2,339 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pymessager.message.Messager",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "config.facebook_access_token",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "msg_handlers.responses",
"line_number": 15,
"usage_type": "name"
},
{
... |
25777861293 | import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.Utils import COMMASPACE, formatdate
# me == my email address
# you == recipient's email address
#assert type(to)==list
def send_mail(to,fro,sub,html,html_text=None):
#to = ['Chacha <sakhawat.sobhan@gmail.... | tanvirraj/hirenow | doc/generic_mail.py | generic_mail.py | py | 2,470 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "email.mime.multipart.MIMEMultipart",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "email.Utils.COMMASPACE.join",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "email.Utils.COMMASPACE",
"line_number": 18,
"usage_type": "name"
},
{
... |
18455156740 | #import libraries
from sklearn.model_selection import train_test_split
import numpy as np
from imblearn.over_sampling import SMOTE
from svm_constructdata import constructdata
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import RandomizedSearchCV
#generate data
features,labels = cons... | kksuresh25/Cancer-AI | Random Forest/rf_tunehyperparameters.py | rf_tunehyperparameters.py | py | 2,420 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "svm_constructdata.constructdata",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.train_test_split",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "sklearn.ensemble.RandomForestClassifier",
"line_number": 24,
"us... |
32437306078 | # Continuous cart pole using policy gradients (PG)
# Running this script does the trick!
import gym
import numpy as np
from gym import wrappers
# env = gym.make('InvertedPendulum-v1')
env = gym.make('Pendulum-v0')
# env = wrappers.Monitor(env, '/home/sid/ccp_pg', force=True)
def simulate(policy, steps, graphics=Fal... | geyang/reinforcement_learning_learning_notes | gym-sessions/ge-baselines/simple_vpg.py | simple_vpg.py | py | 3,296 | python | en | code | 3 | github-code | 1 | [
{
"api_name": "gym.make",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "numpy.random.randn",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 40,
"usage_type": "attribute"
},
{
"api_name": "numpy.append",
"line... |
10361363697 | import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator
## 1d example
# camera is at origin and looks right
# objects have position, importance, transparency
## Formulas
# extinction \mu(x) = \alpha_x
# optical_depth \tau(d_i) = \sum_j^i - \ln(1-\alpha... | BETuncay/demo-doo | example1d.py | example1d.py | py | 6,164 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.linspace",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.abs",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "numpy.linspace",
"line_numbe... |
5227372260 | # 移动止盈止损策略 赢损比自定义 默认1.5：1
import pymysql as sql
import pandas as pd
import requests as req
db = sql.connect(host="localhost", user="root", password="74110", database="quant-trade", port=3307,
autocommit=True)
sina_url = 'http://hq.sinajs.cn/list='
# 获取新浪财经的指定股票实时数据返回dateframe类型
#参考链接 https://www.jia... | ZHAOHUHU/quant-trade | com/quant/trade/zhao/tralling_stop.py | tralling_stop.py | py | 1,024 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pymysql.connect",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"... |
1747709397 | import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import numpy as np
# input
N=100
returns_input = np.array([0.04,0.06])
volas_input = np.array([0.06,0.10])
corr_input=0
def covariance(corr_c... | investeer-io/markowitz_bokeh | dashEfficientFrontierSlider.py | dashEfficientFrontierSlider.py | py | 2,474 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.array",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numpy.diag",
"line_number": 1... |
1101552482 | import torch
import torch.optim as optim
from torch.autograd import Variable
from torchvision import datasets, transforms
import os
import matplotlib.pyplot as plt
from autoencoder import Autoencoder
from gmmn import *
from constants import *
if not os.path.exists(root):
os.mkdir(root)
if not os.path.exists(mod... | Abhipanda4/GMMN-Pytorch | train.py | train.py | py | 3,369 | python | en | code | 13 | github-code | 1 | [
{
"api_name": "os.path.exists",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "os.mkdir",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path.exists",
"line_numbe... |
15278137621 |
# Hashmap + list
from collections import Counter
class FindSumPairs:
def __init__(self, nums1, nums2):
self.n1, self.n2 = Counter(nums1), Counter(nums2)
self.n = [i for i in nums2]
def add(self, index: int, val: int) -> None:
self.n2[self.n[index]] -= 1 # Remove the element from the ... | onyxolu/DSA | Bloomberg/Top 100/FindingPairsWithACertainSum.py | FindingPairsWithACertainSum.py | py | 827 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "collections.Counter",
"line_number": 8,
"usage_type": "call"
}
] |
569319840 | from rest_framework import serializers
# from departamentos.api.serializers import DepartamentoSerializer
# from municipios.api.serializers import MunicipioSerializer
from usuarios.models import Usuario
class UsuarioSerializer(serializers.ModelSerializer):
# municipio = MunicipioSerializer()
# departamento =... | OscarRuiz15/BackendTG | usuarios/api/serializers.py | serializers.py | py | 727 | python | es | code | 0 | github-code | 1 | [
{
"api_name": "rest_framework.serializers.ModelSerializer",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.serializers",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "usuarios.models.Usuario",
"line_number": 13,
"usage_type": "name... |
15238963233 | import json
import pickle
def getNumToTagsMap():
with open("./metadata/all_tags.cls") as fi:
taglist = map(lambda x: x[:-1], fi.readlines())
with open("./metadata/mappings.json") as fi:
mapping = json.loads(fi.read())
finalTag = list(map(lambda x: mapping[x], taglist))
return finalTa... | kyuyeonpooh/objects-that-sound | utils/util.py | util.py | py | 1,765 | python | en | code | 31 | github-code | 1 | [
{
"api_name": "json.loads",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pickle.dump",
"line_number": 53,
"usage_type": "call"
},
{
"api_name": "pickle.dump",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "pickle.load",
"line_number": 6... |
70107487715 | from django.urls import path
from . import views
urlpatterns = [
path('list_plants/', views.all_plants, name='list_plants'),
path('add_plant/', views.add_plant, name='add_plant'),
path('edit_plant/<int:plant_id>/', views.edit_plant, name='edit_plant'),
path('plant_detail/<int:location_id>/<int:pk>/... | Stephen-J-Whitaker/wild-carbon | plants/urls.py | urls.py | py | 1,029 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.urls.path",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
... |
19142088501 | from . import constants
def get_response(url: str, headers: dict = constants.DEFAULT_HEADERS):
try:
import requests as r
except ImportError:
raise "Not search a requests module."
response = r.get(url=url, headers=headers)
if response.status_code != 200:
raise "Not response co... | PavelKrivorotov/Test_Task_python_04_02_2023 | main/main/utils.py | utils.py | py | 773 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "requests.get",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "re.findall",
"line_number": 21,
"usage_type": "call"
}
] |
43645610632 | import pyspark
import pyspark.sql
from pyspark.sql import *
from pyspark.sql.functions import *
import json
import urllib
import argparse
conf = pyspark.SparkConf().setMaster("local[*]").setAll([
('spark.jars.packages', 'com.databricks:spark-xml_2.11:0.8.0'),
... | epfl-dlab/WikiPDA | PaperAndCode/TopicsExtractionPipeline/GetBeta.py | GetBeta.py | py | 1,797 | python | en | code | 10 | github-code | 1 | [
{
"api_name": "pyspark.SparkConf",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 25,
"usage_type": "call"
}
] |
27172359979 | from django import forms
from .models import Tag, Post
from django.core.exceptions import ValidationError
class PostForm(forms.ModelForm):
class Meta:
model = Post
fields = ['title', 'slug', 'body', 'tags']
widgets = {
'title': forms.TextInput(attrs={'class': 'form-con... | HolidayMan/pinkerblog | blog/engine/forms.py | forms.py | py | 2,745 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.forms.ModelForm",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "django.forms",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "models.Post",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "django.forms.TextIn... |
43687469628 | # -*- coding: utf-8 -*-
import os,sys,inspect
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parentdir = os.path.dirname(currentdir)
sys.path.insert(0,parentdir)
from PyQt4 import QtGui
from PyQt4 import QtCore
import os
import modules.filter as tableWidgetFilters
import modules.... | Doberm4n/POEStashJsonViewer | ui/main_layout.py | main_layout.py | py | 8,943 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.path.dirname",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "inspect.getfile",
"line... |
37413122640 | import torch
import torch.nn as nn
import torch.nn.functional as F
from model.octconv import *
import model.venconv as venconv
from model.median_pooling import median_pool_2d
class SNRom(nn.Module):
def __init__(self, in_channels=1, hide_channels=64, out_channels=1, kernel_size=3, alpha_in=0.5,
... | StephenYang190/SpeckleNoisePytorch | model/SNRom.py | SNRom.py | py | 4,128 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "torch.nn.Module",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "torch.nn.ModuleList",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_... |
15850354420 | import pandas as pd
from typing import Union, List, Optional, Tuple
from bokeh.io import output_notebook
from bokeh.resources import INLINE
from bokeh.plotting import figure, gridplot
from bokeh.plotting import show as _show
from pandas.api.types import is_string_dtype
from bokeh.palettes import Set1
output_notebook(I... | idiotekk/unknownlib | lib/unknownlib/plt/bk.py | bk.py | py | 2,990 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "bokeh.io.output_notebook",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "bokeh.resources.INLINE",
"line_number": 10,
"usage_type": "argument"
},
{
"api_name": "bokeh.palettes.Set1",
"line_number": 15,
"usage_type": "name"
},
{
"api_name"... |
70766232034 | from stable_baselines3 import A2C
from algos.PlaNet.planet import PlaNet
from algos.PlaNet.policies import DiscreteMPCPlanner
from algos.PlaNet.world_model import DreamerModel
import os
from buffers.chunk_buffer import ChunkReplayBuffer
from buffers.introspective_buffer import IntrospectiveChunkReplayBuffer
from algos... | GittiHab/mbrl-thesis-code | algos/setup.py | setup.py | py | 3,496 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "utils.total_timesteps",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "utils.total_timesteps",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "algos.PlaNet.world_model.DreamerModel.from_args",
"line_number": 32,
"usage_type": "call"
}... |
24154817598 | #!/usr/bin/env python
'''
Mizoo rename all your photos with a description of what is in them.
It uses Microsoft Computer Vision API's to describe what it sees on
the image and rename the file to that description.
By naming your photos with a description of the content you will
never have to dig up an old photo from y... | albertoqa/mizoo | mizoo/mizoo.py | mizoo.py | py | 3,866 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "json.dumps",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "http.client.HTTPSConnection",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "http.client",
"line_number": 43,
"usage_type": "attribute"
},
{
"api_name": "json.loads",
... |
39278591910 | import cv2
import numpy as np
import imutils
PATH_TEMPLATE_MSLOGO = r"C:\Users\ASUS\Desktop\Working\PROJECT\Mybotic Product\mySejahtera Scan\images\template images\mslogo.png"
PATH_TEMPLATE_TICKMARK = r"C:\Users\ASUS\Desktop\Working\PROJECT\Mybotic Product\mySejahtera Scan\images\template images\tickmark.png"
SIMILAR... | Awexander/mySejahtera-scanner | mysejahtera_scan_v1.py | mysejahtera_scan_v1.py | py | 3,056 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cv2.imread",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "cv2.cvtColor",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_BGR2GRAY",
"line_num... |
38933917008 | #!/usr/bin/env python
# encoding: utf-8
"""
@author: zzz_jq
@contact: zhuangjq@stu.xmu.edu.cn
@software: PyCharm
@file: data_process.py
@create: 2020/11/30 16:06
"""
import re
import os
from pathlib import Path
from tqdm import tqdm
import numpy as np
import pandas as pd
from sklearn.feature_extraction.text imp... | TsinghuaDatabaseGroup/AI4DBCode | Spark-Tuning/prediction_ml/spark_tuning/by_stage/ml_baselines/data_process_one_line.py | data_process_one_line.py | py | 3,683 | python | en | code | 56 | github-code | 1 | [
{
"api_name": "re.sub",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "sklearn.feature_extraction.text.TfidfVectorizer",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "tqdm.tqdm",
"line_number": 67,
"usage_type": "call"
},
{
"api_name": "nump... |
22039745744 | query_variables = {
"wallet": "tz1NqA15BLrMFZNsGWBwrq8XkcXfGyCpapU1",
"timestart": "2021-07-01",
"timeend": "2022-06-30"
}
buys_start = "2019-01-01"
currency = "AUD"
import json
import os
import datetime
import csv
import requests
# Prepare conversion rates
# Using the RBA exchange rates spreadsheet cleaned up... | mattebb/tezos-nft-tax-report | report.py | report.py | py | 8,757 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "csv.reader",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "datetime.timedelta",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "datetime.timedelta",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "requests.post",
... |
7409145188 | import pandas as pd
import numpy as np
import loaders as ld
import analytics as an
def cooc(opens,closes,costs=0.0001,cutoff=1,strength=10000,prec=2,ret=0,sw=0,inv=0):
k = opens.shape[1]-opens.isnull().sum(axis=1)
CO_ret = np.log(opens/closes.shift(1))
OC_ret = closes/opens-1
#OO_ret = np.log(opens/ope... | mlabedzki/Fortuna | strategies.py | strategies.py | py | 6,008 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.log",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.sign",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.minimum",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "numpy.maximum",
"line_number": ... |
19586982312 | import os, pathlib
from pydo import *
this_dir = pathlib.Path(__file__).parent
try:
from . import config
except ImportError:
log.error('Error: Project is not configured.')
exit(-1)
try:
jobs = int(os.environ['PYDOJOBS'], 10)
except Exception:
import multiprocessing
jobs = multiprocessing.cpu... | ali1234/rpi-ramdisk | __init__.py | __init__.py | py | 1,348 | python | en | code | 79 | github-code | 1 | [
{
"api_name": "pathlib.Path",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "multiprocessing.cpu_count",
"line_number": 17,
"usage_type": "call"
}
] |
17166477183 | # -*- coding: utf-8 -*-
"""
Created on Thu Jun 3 15:50:28 2021
@author: mozhenling
"""
import copy
import numpy as np
import scipy.io as scio
import matplotlib.pyplot as plt
from dbtpy.filters.afilter import filter_fun
from dbtpy.findexes.afindex import findex_fun
from dbtpy.findexes.sigto import sig_real_to_env
#--... | mozhenling/dbtree | dbtpy/funs/fun_diag.py | fun_diag.py | py | 18,106 | python | en | code | 4 | github-code | 1 | [
{
"api_name": "dbtpy.filters.afilter.filter_fun",
"line_number": 75,
"usage_type": "call"
},
{
"api_name": "dbtpy.findexes.sigto.sig_real_to_env",
"line_number": 77,
"usage_type": "call"
},
{
"api_name": "dbtpy.findexes.afindex.findex_fun",
"line_number": 79,
"usage_type"... |
41495665790 | import torch
import torch.nn as nn
class MASRModel(nn.Module):
def __init__(self, **config):
super().__init__()
self.config = config
@classmethod
def load(cls, path):
package = torch.load(path)
state_dict = package["state_dict"]
config = package["config"]
m... | nobody132/masr | models/base.py | base.py | py | 1,176 | python | en | code | 1,754 | github-code | 1 | [
{
"api_name": "torch.nn.Module",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "torch.load",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "trainable.TrainableModel",
... |
9293506322 | #this model aim to reduce number of rounds but will continue to use random method
import random
from datetime import datetime
start_time = datetime.now()
final_state = [1,2,3,4,5,6,7,8]
initial_state = [0,0,0,0,0,0,0,0]
#random initail state with different position of number
while 0 in initial_state:
rand = rand... | Tanisa124/AI-Practice | heuristic_lessRound.py | heuristic_lessRound.py | py | 2,058 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "datetime.datetime.now",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "random.randint",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "random.randint",... |
35465861402 | import itertools
import torch.nn as nn
import decoder
import encoder
import modules
from utils import MergeDict
class Model(nn.Module):
def __init__(self, sample_rate, vocab_size):
super().__init__()
self.spectra = modules.Spectrogram(sample_rate)
# self.encoder = encoder.Conv2dRNNEnco... | vshmyhlo/listen-attend-and-speell-pytorch | model.py | model.py | py | 2,131 | python | en | code | 11 | github-code | 1 | [
{
"api_name": "torch.nn.Module",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "modules.Spectrogram",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "encoder.Conv2dAtten... |
27981377485 | import requests
import json
import numpy as np
import time
import pandas as pd
from pymysql import connect
import csv
from custom_send_email import sendEmail
# 获取订单簿数据
class GetData(object):
'''
获取对应api bitmax数据，计算固定比例的数据，监控变化，发送邮件
'''
def __init__(self,url):
self.url = url
# self.da... | jackendoff/bilian_bitmax_data | BITMAX_jackendoff.py | BITMAX_jackendoff.py | py | 10,355 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "time.time",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.percentile",
"line_number... |
29598602871 | import numpy as np
import keras
# from keras.models import Sequential
from keras.models import *
from keras.layers import *
import random
from sklearn.model_selection import train_test_split
#this one will be used for normalization and standardization
from sklearn import preprocessing
import scipy.io as sio
# We us... | ell-hol/mpc-DL-controller | simulate_DL_controller.py | simulate_DL_controller.py | py | 16,307 | python | en | code | 61 | github-code | 1 | [
{
"api_name": "numpy.array",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "numpy.dot",
"line_number": 29... |
30296294545 | import serial
import sys
import time
def out_gpio(value):
f_val = open('/sys/class/gpio/gpio18/value', 'w')
f_val.write(value)
f_val.close()
# первый байт req - ожидаемая длина ответа
def make_request(req):
out_gpio('1')
port.write(req[1:])
time.sleep(0.004)
out_gpio('0')
while(port.inWaiting() == 0):
time.... | almarkov/quest | test.py | test.py | py | 651 | python | ru | code | 0 | github-code | 1 | [
{
"api_name": "time.sleep",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "sys.stdout.write",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "sys.stdout",
"line_number"... |
8707312288 | #----------------------------------------------------------------------
# Package Management
#----------------------------------------------------------------------
import os
import os.path as op
import textwrap
import argparse
import pandas as pd
import re
import zipfile
from tqdm import tqdm, trange
import hashlib
... | muscbridge/comprssr | comprssr.py | comprssr.py | py | 7,544 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "argparse.RawDescriptionHelpFormatter",
"line_number": 26,
"usage_type": "attribute"
},
{
"api_name": "textwrap.dedent",
"line_number": 27,
"usage_type": "call"
},
{
... |
24383408411 | """Script to gather IMDB keywords from 2013's top grossing movies."""
import sys
from os import path
import time
from business_logic.compare_prices import ComparePrices
import logging
from business_logic.logic import Logic
logger = logging.getLogger('ftpuploader')
hdlr = logging.FileHandler('ftplog.log')
formatter = lo... | life-of-pi-thon/crypto_carluccio | lukrative.py | lukrative.py | py | 1,077 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "logging.FileHandler",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "logging.Formatter",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
... |
19767607746 | """CSV操作
aws cliの初期設定
aws configure
設定の確認
~/.aws/
boto3 Client APIとResource API
Client API・・・リソースを操作する場合も参照系と同様に、対象のリソースIDを引数に加えてメソッドを実行する。
ex)
s3 = boto3.client('s3')
# バケット一覧を取得
s3.list_buckets()
obj = client.get_object(Bucket='test_bucket', Key='test.text')
print(obj['body'].read())
Resource API・・・リソースを操作する場合には対象の... | yoshikikasama/data_analytics | coding/boto3/tutorials/csv_from_s3.py | csv_from_s3.py | py | 6,116 | python | ja | code | 0 | github-code | 1 | [
{
"api_name": "boto3.client",
"line_number": 53,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 92,
"usage_type": "call"
},
{
"api_name": "io.TextIOWrapper",
"line_number": 108,
"usage_type": "call"
},
{
"api_name": "io.BytesIO",
"line_numb... |
39002643737 | import sqlite3
DbName = "./db/timing_plan.db"
class Cdb:
def __init__(self,dbName):
self.dbName = dbName #数据库名称
self.conn = None #文件与数据库的连接
self.cursor = None #文件与数据库的交互
self.__connect()
def __connect(self): #将数据库与文件连接
try:
self.conn = sqlite... | lx-dtbs/UI-base | sumo_liveUpdate_ui/DbBase.py | DbBase.py | py | 2,777 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "sqlite3.connect",
"line_number": 11,
"usage_type": "call"
}
] |
22184099208 | """
Simple `GIL` released demo.
"""
import threading
import requests
from ch01.tools import time_it
def simple_request() -> None:
"""Make a simple request"""
response = requests.get("https://www.google.com")
print(f"Response status code: {response.status_code}")
@time_it
def requests_no_threading() ->... | iplitharas/myasyncio | ch01/gil_released_demo.py | gil_released_demo.py | py | 700 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "requests.get",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "ch01.tools.time_it",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "threading.Thread",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "threading.Thread",
... |
70026443555 | import os
import datetime
import argparse
import sys
import shutil
def run():
parser = argparse.ArgumentParser(description="Delete files each period of time")
parser.add_argument("--dir_path", type=str, help="Path to the folder")
parser.add_argument("--period", type=int, help="Period of time in days")
a... | JassielMG/AutoCleanFolder | main.py | main.py | py | 1,778 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sys.stdout.write",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sys.stdout",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "datetime.date... |
14621398412 | import os
import tornado.web
from .Util import *
from .Core import *
class IndexHandler(tornado.web.RequestHandler):
def get(self):
self.render("index.html", people="skipper")
class LogIndexHandler(tornado.web.RequestHandler):
def get(self):
self.render("log/log_index.html")
class LogList... | daddvted/arch1ve | python_code/log2chart_tornado/engine/Handler.py | Handler.py | py | 3,264 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "tornado.web.web",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "tornado.web",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "tornado.web.web",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "tornado.web",
... |
72632864993 | import json
from flask import Flask, render_template, request, jsonify
from sklearn.svm import SVC
from sklearn.feature_extraction.text import CountVectorizer
app = Flask(__name__)
# Load the business guidelines from a JSON file
with open("business_guidelines.json", "r") as f:
guidelines_data = json.load... | Balakumarmd/Ideavalidator | app.py | app.py | py | 1,730 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sklearn.feature_extraction.text.CountVectorizer",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "... |
26358115895 | from __future__ import print_function, division
####################################################################
###### Copyright (c) 2022-2023 PGEDGE ##########
####################################################################
import argparse, sys, os, tempfile, json, subprocess, getpass... | pgEdge/nodectl | src/pgXX/config-pgXX.py | config-pgXX.py | py | 4,102 | python | en | code | 7 | github-code | 1 | [
{
"api_name": "os.getenv",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 15,
... |
43751970541 | #!/usr/bin/env python3
"""
Scraper for the 'The Flavor Bible'.
Created by Jon.
"""
import json
import os
import re
import sqlite3
import sys
import ebooklib
from ebooklib import epub
from bs4 import BeautifulSoup
latest_id = 0
def createTables(c):
c.execute('''CREATE TABLE ingredients(
id int... | tristanchu/FlavorFinder | dev/scraper.py | scraper.py | py | 11,938 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "re.search",
"line_number": 75,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 76,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
"line_number": 158,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 158,
... |
74407308832 | from fastapi import Depends, FastAPI
app = FastAPI()
"""
# Dependency injection: a function that abstracts logic and can be provided to
# other functions as dependency.
Whenever a new request arrives to a function that includes a dependency, fastAPI
runs the dependency function with the corresponding parameters, an... | jcaguirre89/learning-fastapi | another_app/dependency.py | dependency.py | py | 1,980 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "fastapi.FastAPI",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "fastapi.Depends",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "fastapi.Depends",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "fastapi.Depends",
... |
4832434614 | # Always prefer setuptools over distutils
from setuptools import setup, find_packages
# To use a consistent encoding
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
with open(path.join(here, 'README.rst'), encoding='utf-8') as f:
long_description = f.read()
setup(
name=... | csail-csg/pyverilator | setup.py | setup.py | py | 1,497 | python | en | code | 64 | github-code | 1 | [
{
"api_name": "os.path.abspath",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "os.path.dirname",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "codecs.open",
"line_number":... |
24402276077 | import os
import numpy as np
import pandas as pd
from catboost import CatBoost, Pool
import matplotlib.pylab as plt
from model import Model
from util import Util
class ModelCatBoost(Model):
def train(self, tr_x, tr_y, va_x=None, va_y=None):
# ハイパーパラメータの設定
params = dict(self.params)
cat_... | riron1206/lgb_tuning | src/model_catboost.py | model_catboost.py | py | 2,770 | python | ja | code | 0 | github-code | 1 | [
{
"api_name": "model.Model",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "catboost.Pool",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "catboost.Pool",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "catboost.CatBoost",
"line... |
25623285903 | """
Google Forms Interaction Module
This module provides functionalities to interact with Google Forms, specifically
to fetch responses from a designated form. The primary purpose is to retrieve
sign-up responses, which are then used in the main application for sending out
notifications.
Key Features:
- Authentic... | StevenWangler/snow_day_bot | google_functions/google_forms.py | google_forms.py | py | 4,128 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.path.path.exists",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "os.path.path",
"line_number": 39,
"usage_type": "attribute"
},
{
"api_name": "os.path",
"line_number": 39,
"usage_type": "name"
},
{
"api_name": "google.oauth2.credentia... |
16239780344 | import os
import sys
import PIL
import time
import random
import logging
import datetime
import os.path as osp
import torch
import torch.backends
import torch.nn as nn
import torch.backends.cudnn
import torch.distributed as dist
from utils.loss import OhemCELoss
from utils.utils import prepare_seed
from utils.utils i... | NoamRosenberg/autodeeplab | train_distributed.py | train_distributed.py | py | 8,976 | python | en | code | 306 | github-code | 1 | [
{
"api_name": "config_utils.re_train_autodeeplab.obtain_retrain_autodeeplab_args",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "torch.cuda.set_device",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 30,
"usage_type": "at... |
15616079630 | import multiprocessing as processing
from multiprocessing import pool,Process
import math
import numpy as np
import gzip
import pickle
import sys
from scipy import integrate
import time,random
import h5py
import threading
import os.path
import _pickle as cpickle
from scipy import spatial
from multiprocessing import Pro... | peraktong/Multi_thread_examples | 0327_calculate_density_Kd_tree_multi_process_doable_v1.py | 0327_calculate_density_Kd_tree_multi_process_doable_v1.py | py | 6,624 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "math.log10",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "numpy.inf",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "math.exp",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "numpy.inf",
"line_number": 28,... |
27836865388 | import regex as re
from bs4 import BeautifulSoup
import requests
import requests_futures
import aiohttp
import asyncio
from requests_futures.sessions import FuturesSession
import tree
import json
trees = []
valid_regex = r"^https?\:\/\/([\w\.]+)wikipedia.org\/wiki\/([\w]+\_?)+"
links = dict()
loop = asyncio.get_even... | LyudmilaTretyakova/testtask | script.py | script.py | py | 4,831 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "asyncio.get_event_loop",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "regex.split",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
... |
18161161348 | import pandas
from recordlinkage.preprocessing import clean
d = {'col1': ['marry - a', 'kudo::'], 'col2': ['nam vinh', 'okee-']}
df = pandas.DataFrame(data=d)
s = pandas.Series(df['col1'])
df['col1'] = clean(s)
print(df)
df['col1'][0] = "b"
print(df) | aduyphm/data-integration-20212 | DataHandle/test.py | test.py | py | 252 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.DataFrame",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pandas.Series",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "recordlinkage.preprocessing.clean",
"line_number": 7,
"usage_type": "call"
}
] |
16547812246 | import requests
import sys
import json
def post_predict(host:str):
'''
Sends an HTTP POST request to the /predict endpoint.
'''
proto = ''
if not host.startswith('http'):
proto = 'http://'
with open('manualtests/manual_predict_data.json', 'r') as f:
data = json.loads(f.read... | pugad/ml-golf-demo-app | manualtests/predict_manual.py | predict_manual.py | py | 667 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "json.loads",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 20,
"usage_type": "attribute"
}
] |
37639058519 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import re
import sys
import argparse
__author__ = 'menghao'
__mail__ = 'haomeng@genome.cn'
bindir = os.path.abspath(os.path.dirname(__file__))
pat1 = re.compile('^\s*$')
sys.path.append(bindir + '/../lib')
from common import parser_fasta
complement = {'A':'T','... | whenfree/Rosalind | Locating_Restriction_Sites/Locating_Restriction_Sites.py | Locating_Restriction_Sites.py | py | 1,287 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.path.abspath",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_n... |
17446433552 | """Tests for the config API."""
import unittest
from pygame_assets.exceptions import NoSuchConfigurationParameterError
from pygame_assets.configure import Config, ConfigMeta
from pygame_assets.configure import get_config, config_exists, remove_config
from pygame_assets.configure import get_environ_config, set_environ... | florimondmanca/pygame-assets | pygame_assets/tests/test_configure.py | test_configure.py | py | 6,870 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "unittest.TestCase",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "pygame_assets.configure.ConfigMeta.get_class_attributes",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "pygame_assets.configure.ConfigMeta",
"line_number": 25,
"u... |
6048712734 | from app.visual_detector.workers import (
FrameReaderThread, TowerDetectorThread, ComponentDetectorThread, DefectDetectorThread,
DefectTrackingThread, ResultsProcessorThread, TiltDetectorThread, DumperClassifierThread,
WoodCracksDetectorThread
)
from app.visual_detector.defect_detectors import (
TowerDe... | EvgeniiTitov/defect_detection | app/visual_detector/model.py | model.py | py | 11,192 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "typing.List",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "queue.Queue",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "queue.Queue",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "queue.Queue",
"line_number": ... |
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