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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
311887062 | import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
from sklearn.externals import joblib
import plotly.graph_objs as go
import feature_engineering as fe
import neural_network as nn
import random_forest as rf
from keras.models import load_model
... | null | app.py | app.py | py | 3,569 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "dash.Dash",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "dash_html_components.Div",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "dash_html_components.H1",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "dash_html_... |
588159900 | import torch
from transformers import BertModel
import argparse
import os
device = "cuda" if torch.cuda.is_available() else "cpu"
print("Using {} device".format(device))
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--save", default="model.pt")
args = parser.parse_args... | null | sagemaker-triton/benchmark/pytorch/workspace/pt_exporter.py | pt_exporter.py | py | 764 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "torch.cuda.is_available",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "transfo... |
511636603 | import os
import time
import json
import pandas as pd
import numpy as np
import gc
import datetime
from pandas.io.json import json_normalize
import itertools
import configparser
import warnings
import re
import sys
config = configparser.ConfigParser()
config.read('/home/melgazar9/Trading/TD/Scripts/Trading-Scripts/ES/... | null | Trading/scripts/Trading-Scripts/ES/ES_1min_concat-new-data.py | ES_1min_concat-new-data.py | py | 4,365 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "configparser.ConfigParser",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "warnings.filterwarnings",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "sys.exit... |
482948408 | import urllib2
from bs4 import BeautifulSoup
import random
def get_page(url):
data = None
try:
response = urllib2.urlopen(url)
data = response.read()
except urllib2.HTTPError as err:
pass
return data
def get_responses(url):
data = get_page(url)
links_list = []
if da... | null | modules/stackoverflow/so.py | so.py | py | 1,289 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "urllib2.urlopen",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "urllib2.HTTPError",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "random.randin... |
400326776 | # coding: utf8
# TP Régression linéaire - Outils statistiques
import csv # data.txt is a csv like file
import numpy as np
import matplotlib.pyplot as plt
# ********* #
# FONCTIONS #
# ********* #
# Fonction f(x) = ax + b
def lineaire(a, b, x):
return a * x + b
# Fonction de calcul de régression linéaire
def regre... | null | Licence 2/S4/Outils_statistiques/outilsStats/TP3/exo.py | exo.py | py | 2,780 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.average",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "numpy.average",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "numpy.average",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "numpy.average",
"line_n... |
431483399 | import numpy as np
import pandas as pd
import pickle
from collections import Counter
# cross_validation for training and testing set, neighbour bcoz we are doing kmeans neighbours
# VotingClassifier - because we are going to use many classifiers and vote for the best
# RandomForestClassifier is a type of classifier
fro... | null | simple_ml_with_indicators.py | simple_ml_with_indicators.py | py | 5,116 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pickle.load",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numpy.round",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.round",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "collections.Counter",
"line_n... |
488742189 | # August 30th 2016
# Testing how the pairwise histogram gets set up
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
data_1 = [0, 2, 1, 2, 1, 0, 1, 1, 1, 2]
data_2 = [2, 0, 0, 0, 1, 1, 0, 0, 2, 2]
j_dist, x, y = np.histogram2d(data_1, data_2, bins=[-0.5, 0.5, 1.5, 2.5])
# j_dist[a, b] is the... | null | examine_decoded_angle/2016_08_tuning_curve_angle_analyses/test_pairwise_hist.py | test_pairwise_hist.py | py | 680 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.histogram2d",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "matplotl... |
44627988 | from mpl_toolkits.mplot3d import Axes3D
from matplotlib.pyplot import *
from scipy.optimize import minimize
penalidade_interior = lambda x: f(x)+rp*sum([(-1/g(x) if g(x)<=(-C*(rp)**a) else -(2*(-C*(rp)**a)-g(x))/((-C*(rp)**a)**2)) for g in restricoes])
penalidade_exterior = lambda x: f(x)+rp*sum([max(0,g(x))**2 for g ... | null | Lista 3/Q4/util.py | util.py | py | 4,798 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "scipy.optimize.minimize",
"line_number": 92,
"usage_type": "call"
},
{
"api_name": "scipy.optimize.minimize",
"line_number": 113,
"usage_type": "call"
},
{
"api_name": "scipy.optimize.minimize",
"line_number": 151,
"usage_type": "call"
}
] |
538456535 | import logging
import yaml
with open("config.yaml", 'r', encoding='UTF-8') as ymlfile: cfg = yaml.load(ymlfile)
from HM_functions import get_request, set_request, find_device
# -------------------------------------------------------------------------
def fctTemperatur_Abfragen(Ort):
act_temp = 'empty'
msg = "D... | null | HM_temperature.py | HM_temperature.py | py | 2,771 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "yaml.load",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "HM_functions.find_device",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "HM_functions.get_request",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "HM_functio... |
528995212 | """yolowa URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based ... | null | Hackathon/yolowa/yolowa/urls.py | urls.py | py | 1,783 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.urls.path",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "django.contrib.admin.site",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "... |
513412573 | #!/usr/bin/env python
#coding=utf-8
#上面这条声明让程序在unix系统中可以通过./manage.py执行脚本
import os
COV = None
if os.environ.get('FLASK_COVERAGE'):
import coverage
COV = coverage.coverage(branch=True,include='app/*')
COV.start()
from app import create_app,db
from app.models import User,Role,Post,Permission,Follow,Comment
from fla... | null | manage.py | manage.py | py | 2,222 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.environ.get",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "coverage.coverage",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "app.create_app",
"l... |
256398516 | """Analysis script for the EEG project.
Notes
-----
- Baseline: -500 - 350
- All trials average (all subjects), or average of subject averages?
- Filter individual channels or single frequency estimate per subject?
"""
from os import listdir
from os.path import join as pjoin
import numpy as np
from scipy.signal impo... | null | scripts/fooof_eeg.py | fooof_eeg.py | py | 19,166 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.mean",
"line_number": 71,
"usage_type": "attribute"
},
{
"api_name": "os.listdir",
"line_number": 97,
"usage_type": "call"
},
{
"api_name": "fooof.data.FOOOFSettings",
"line_number": 102,
"usage_type": "call"
},
{
"api_name": "fooof.FOOOF",
... |
325203860 | """
日历相关函数
"""
from flask import Blueprint
cal_blueprint = Blueprint('cal', __name__)
from flask import request, session, redirect, url_for, render_template
from flask import current_app as app
from everyclass.commons import semester_to_string, semester_to_tuple
from everyclass.mysql_operations import get_classes_for_... | null | server/everyclass/cal.py | cal.py | py | 1,274 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Blueprint",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "flask.request.values.get",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "flask.request.values",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "fla... |
120192911 | #!/usr/bin/env python
################################################################################
# Libraries import
import sys
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
import numpy as np
import glob
########################################################################... | null | analysis/PlotPrefixes/prefixes_comb_ipv6_cdf.py | prefixes_comb_ipv6_cdf.py | py | 5,272 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "glob.glob1",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 47,
"usage_type": "name"
},
{
"api_name": "numpy.cumsum",
... |
208129123 | from django.core.management.base import BaseCommand, CommandError
from django.core.mail import send_mail
from ...models import OrderItem, VendorEmail
from django.template import Context
from django.template.loader import get_template
import datetime
class Command(BaseCommand):
def handle(self, *args, **options):... | null | orders/management/commands/sendemail.py | sendemail.py | py | 1,002 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.core.management.base.BaseCommand",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "datetime.date.today",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "datetime.date",
"line_number": 12,
"usage_type": "attribute"
},
{
"api... |
638265115 | import docker
# from docker.api.service import ServiceMode
from docker.types import SecretReference, ServiceMode
client = docker.DockerClient(base_url='unix://var/run/docker.sock')
image = 'aerospike/aerospike-server'
# network = 'aerospikenetwork'
# client.networks.create(network, internal=True)
mode = ServiceMode... | null | data/docker/database/aerospike/test_server/run_docker.py | run_docker.py | py | 840 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "docker.DockerClient",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "docker.types.ServiceMode",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "docker.types.SecretReference",
"line_number": 18,
"usage_type": "call"
}
] |
606421975 | #
# This file is part of Brazil Data Cube Collection Builder.
# Copyright (C) 2019-2020 INPE.
#
# Brazil Data Cube Collection Builder is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""Handle Sentinel Download interface."""
import o... | null | bdc_collection_builder/collections/sentinel1/download.py | download.py | py | 3,913 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.Response",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "os.makedirs",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.path",
"lin... |
437480628 | # construct Codon Markov Model
# Input: genbank file of Prokaryote in one folder
# Output: codon Markov Model of every input genebank
import argparse
import sys
import os
import numpy as np
np_load_old = np.load
np.load = lambda *a,**k: np_load_old(*a, allow_pickle=True, **k)
import pandas as pd
from Bio import SeqIO
i... | null | cmm_HoPhage_S.py | cmm_HoPhage_S.py | py | 5,271 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.load",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "numpy.load",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.getcwd",
... |
241332813 | import collections, itertools
import nltk.classify.util, nltk.metrics
import random
from sklearn import metrics
from sklearn.svm import SVC
from nltk.classify import NaiveBayesClassifier , DecisionTreeClassifier , MaxentClassifier
from nltk.classify import SklearnClassifier
from nltk.corpus import movie_reviews, stopw... | null | PA4/Baozhi_PA4_final.py | Baozhi_PA4_final.py | py | 4,641 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sklearn.metrics.precision_score",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "sklearn.metrics",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "sklearn.metrics.recall_score",
"line_number": 23,
"usage_type": "call"
},
{
"api_... |
103207020 | # uncompyle6 version 3.7.4
# Python bytecode 3.6 (3379)
# Decompiled from: Python 3.6.9 (default, Apr 18 2020, 01:56:04)
# [GCC 8.4.0]
# Embedded file name: C:\Users\R and L\Dropbox\Coding Notes and Programming\gcapi-python\gcapi\gcapi_client.py
# Compiled at: 2020-02-29 16:31:02
# Size of source mod 2**32: 7679 bytes... | null | pycfiles/gcapi-python-0.0.7.tar/gcapi_client.cpython-36.py | gcapi_client.cpython-36.py | py | 10,121 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.post",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "gcapi.gcapi_exception.GCapiException",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "request... |
277165358 | import os
from math import ceil
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from tensorflow.keras.datasets import mnist
import tensorflow.keras.backend as K
from Checkpoint import load_checkpoint
from Utils import make_noise, korea_time, save_summary, make_folders_for_model, save_initi... | null | MNIST/Complicated/WGAN/Model.py | Model.py | py | 11,577 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "Utils.make_folders_for_model",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "math.ceil",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras.utils.Progbar",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": ... |
393653374 | import pandas as pd
import torch
from torch import nn
from torch.nn import functional as F
from rebar import recurrence, profiling
import time
from boardlaw import cuda
class Optimal(nn.Module):
def __init__(self, features, n_models, n_layers):
super().__init__()
self.layers = nn.ModuleList([nn.Li... | null | experiments/parallel/multinet.py | multinet.py | py | 5,776 | python | en | code | null | code-starcoder2 | 76 | [
{
"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": 13,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_... |
620028624 | # Lukas - 24.05.18
# xmlrpc-client based on https://docs.python.org/3.1/library/xmlrpc.server.html and interface with TraitsUI. Script is written for Phython2
import xmlrpclib # Different in Python3
from traits.api import HasTraits, Button, Int, Float, String, Bool, Range, Enum
from traitsui.api import View, Item, H... | null | xmlrpc/sh_client/client.py | client.py | py | 4,306 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "threading.Thread",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "time.sleep",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "traits.api.HasTraits",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "traits.api.Float",
... |
565579244 | import os
from flask import Flask, request, make_response, jsonify
from flask_restful import Api
from flask_cors import CORS
import os
app = Flask(__name__)
api = Api(app)
CORS(app, resources={r"/api/*": {"origins": "*"}})
app.config['JSON_AS_ASCII'] = False
respE = {
"events":[
{
... | null | server/__init__.py | __init__.py | py | 1,401 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Flask",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "flask_restful.Api",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "flask_cors.CORS",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "flask.make_response",
... |
289078977 | import sys, inspect
import NovelParsers
import NovelDownloader
import TKWrapper
import threading
from multiprocessing.pool import ThreadPool
import uuid
class NovelGUI:
def __init__(self):
# Set download pool size (how many chapters to download at a time)
self.poolSize = ... | null | novel2ebook.py | novel2ebook.py | py | 10,382 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "TKWrapper.TKWrapper",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "inspect.getmembers",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "inspect.isclass",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "uuid.uuid... |
535358919 | # you can watch more on ' www.mllounge.com '
# Basic CNN project
from keras.models import Sequential
from keras.layers import Conv2D, MaxPool2D, Flatten, Dropout, Dense
from keras.optimizers import Adam, rmsprop
import numpy as np
import cv2
import serial
from PIL import Image
import time
import sys
class CnnModel()... | null | Basic Project/CNN - Distinguish language according to characters/CNN - Distinguish language according to characters.py | CNN - Distinguish language according to characters.py | py | 3,850 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.load",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.reshape",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numpy.reshape",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "keras.models.Sequential",
... |
296970072 |
import torch
import torch.nn as nn
def kld(mu1, std1, mu2, std2):
p = torch.distributions.Normal(mu1, std1)
q = torch.distributions.Normal(mu2, std2)
return torch.distributions.kl_divergence(p, q).mean()
class Encoder(nn.Module):
def __init__(self, inShape, muSize, sigSize, h = 300):
su... | null | experiment_2_face_tasks/vae.py | vae.py | py | 4,426 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "torch.distributions.Normal",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "torch.distributions",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "torch.distributions.Normal",
"line_number": 11,
"usage_type": "call"
},
{
"ap... |
647999621 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import njango.fields
class Migration(migrations.Migration):
dependencies = [
('core', '0003_budgethead_recurrent'),
('project', '0008_auto_20160630_2118'),
]
operations = [
m... | null | project/migrations/0009_exchangerate.py | 0009_exchangerate.py | py | 879 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.db.migrations.Migration",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "django.db.migrations",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "django.db.migrations.CreateModel",
"line_number": 16,
"usage_type": "call"
},
... |
72324595 | # Copyright (C) 2020 Zurich Instruments
#
# This software may be modified and distributed under the terms
# of the MIT license. See the LICENSE file for details.
import pytest
from hypothesis import given, strategies as st
import numpy as np
from .context import (
UHFQA,
UHFQA_AWG,
ReadoutChannel,
Dev... | null | tests/test_uhfqa.py | test_uhfqa.py | py | 10,989 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "context.uhfqa_logger.disable_logging",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "context.uhfqa_logger",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "context.UHFQA",
"line_number": 24,
"usage_type": "call"
},
{
"api_name"... |
80583926 | from django.test import TestCase
from topspots.services import get_lat_lng, get_nearby_airports,\
get_location_from_address, get_city_state
class TestGetLocationData(TestCase):
def test_lat_lng_returns_correct_lat_and_lng(self):
address = 'Sunnyside Park, Summit Street, KCMO, MO'
expected_la... | null | topspots/tests/test_services.py | test_services.py | py | 1,668 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.test.TestCase",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "topspots.services.get_lat_lng",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "topspots.services.get_city_state",
"line_number": 21,
"usage_type": "call"
},
{
... |
400873995 | import numpy as np
from pathlib import Path
from ray.util.joblib import register_ray
from numpy import load, save
from sklearn.pipeline import Pipeline
from sklearn.model_selection import train_test_split
from sklearn.model_selection import RepeatedKFold, cross_val_score
from sklearn.metrics import make_scorer
from xgb... | null | preprocessing/02_encoding.py | 02_encoding.py | py | 7,042 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.set_option",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "Transformers.RareLa... |
15453993 |
from random import randint, random
import math, sys, colorsys, threading
from math import pi, sin
#import direct.directbase.DirectStart
from direct.actor.Actor import Actor
from panda3d.core import Filename, CardMaker
#from direct.showbase.DirectObject import DirectObject
#from panda3d.core import *
from pa... | null | demo_artoolkit/ar_demo4.py | ar_demo4.py | py | 3,720 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "demobase.DemoBase",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "demobase.DemoBase.__init__",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "demobase.DemoBase",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name... |
328050314 | import json
import os
import functools
import decimal
import operator
from django.utils.dateparse import parse_datetime
from django.http import HttpResponse
from rest_framework import status
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.exceptions import Permi... | null | api/views/employee_views.py | employee_views.py | py | 18,294 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "rest_framework_jwt.settings.api_settings.JWT_DECODE_HANDLER",
"line_number": 31,
"usage_type": "attribute"
},
{
"api_name": "rest_framework_jwt.settings.api_settings",
"line_number": 31,
"usage_type": "name"
},
{
"api_name": "rest_framework_jwt.settings.api_setting... |
48829133 | import numpy as np
import math
import matplotlib.pyplot as plt
from matplotlib2tikz import save as tikz_save
from label_lines import *
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.spines['left'].set_position('zero')
ax.spines['bottom'].set_position('zero')
ax.spines['right'].set_color('none')
ax.spines['top'].... | null | Spring 2018/Calc IV/Project/graphs/haar.py | haar.py | py | 2,124 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "math.pi",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "numpy.linspace"... |
140470339 | """
weather_parser.py:
Parses and cleans json weather data from the Dark Sky API
WeatherRecordParser (cls): Parses an individual weather record
WeatherParser (cls): Wrapper for WeatherRecordParser; parses multiple records
WeatherCleaner (cls): Cleans and transforms parsed weather data
"""
import json... | null | lib/weather_parser.py | weather_parser.py | py | 9,519 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pendulum.from_timestamp",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "pandas.io.json.json_normalize",
"line_number": 91,
"usage_type": "call"
},
{
"api_name": "pandas.io.json.json_normalize",
"line_number": 103,
"usage_type": "call"
},
{
... |
537484239 | import sys
from django.db import models
from PIL import Image
from io import BytesIO
from django.core.files.uploadedfile import InMemoryUploadedFile
# Create your models here.
class upload(models.Model):
user=models.CharField(max_length=100)
image=models.ImageField(upload_to="photos/",default='/media/... | null | models.py | models.py | py | 1,000 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.db.models.Model",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "django.db.models",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "django.db.models.CharField",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "... |
460326543 | from random import randrange
from scipy import io
from PIL import Image, ImageDraw
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
class Dataset:
def __init__(self, filename):
mat = io.loadmat(filename)
self.examples = mat["examples"][0]
self.size = self.examples.size
... | null | DatasetImport.py | DatasetImport.py | py | 1,586 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "scipy.io.loadmat",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "scipy.io",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "random.randrange",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "matplotlib.image.imread",
... |
104660275 | from collections import Counter
from csv import writer
class PlayerExposures:
def __init__(self):
self.total_exposures = Counter({})
self.positional_exposures = {}
def bump_exposures(self, lineup):
for player in lineup:
if player in self.total_exposures:
se... | null | pydfs_lineup_optimizer/player_exposures.py | player_exposures.py | py | 2,666 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "collections.Counter",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "collections.Counter",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "csv.writer",
"line_number": 42,
"usage_type": "call"
}
] |
52537197 | # -*- coding:utf-8 -*-
import os
import time
from pathlib import Path
from .fs import read_json
from .fs import write_json
from .fs import mkdir
from .http import fetch
class Crawler(object):
u"""爬虫
Parameters
----------
timeout : int, optional, default=3
请求超时时间
timesleep : int, optiona... | null | nlptools/crawler.py | crawler.py | py | 6,777 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "fs.mkdir",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line_number": 164,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 169... |
395176504 | from os import path, mkdir, walk
# pip install Crypto
from Crypto.Cipher import AES
from Crypto.Hash import MD5
from base64 import b64encode, b64decode
from sys import version
if version[0] == 3:
raw_input = input
BLOCK_SIZE = 32
PADDING = '{'
pad = lambda s: s + (BLOCK_SIZE - len(s) % BLOCK_SIZE) * PADDING
Enco... | null | dox.py | dox.py | py | 2,350 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.version",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "base64.b64encode",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "base64.b64decode",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.path.isdir",
"lin... |
227795524 | from varglas.meshing import MeshGenerator, MeshRefiner, GetBasin
from varglas.data.data_factory import DataFactory
from varglas.io import DataInput, print_min_max
from pylab import *
from scipy.interpolate import interp2d
kappa = 1.0 # ice thickness to refine
#===... | null | antarctica/gen_basin_mesh.py | gen_basin_mesh.py | py | 2,836 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "varglas.data.data_factory.DataFactory.get_ant_measures",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "varglas.data.data_factory.DataFactory",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "varglas.data.data_factory.DataFactory.get_bedmap2",
... |
258800080 | """
Q503
Next Greater Element II
Medium
Given a circular array (the next element of the last element
is the first element of the array), print the Next Greater
Number for every element. The Next Greater Number of a
number x is the first greater number to its traversing-order
next in the array, which means you could se... | null | Q503.py | Q503.py | py | 1,335 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "typing.List",
"line_number": 20,
"usage_type": "name"
}
] |
342147849 | from django.conf.urls import url
from . import views
urlpatterns = [
url(r'^list/$', views.cveindex,name="list"), #DJango自动补充url /
url(r"^search/$",views.cvesearch),
url(r'^detail/(?P<id>.*)/$', views.cvedetail, name='detail'),
url(r'^cvedit/$', views.cvedit, name="cvedit"),
url(r'cveImagelUplo... | null | WikiList2/list/urls.py | urls.py | py | 568 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.conf.urls.url",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.co... |
230997476 | from django.test import TestCase
from django.test.simple import DjangoTestSuiteRunner
# custom test runner only sets up test DB if necessary.
class CustomTestSuiteRunner(DjangoTestSuiteRunner):
def run_tests(self, test_labels, extra_tests=None, **kwargs):
self.setup_test_environment()
suite = self.... | null | editorsnotes/testrunner.py | testrunner.py | py | 799 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.test.simple.DjangoTestSuiteRunner",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "django.test.TestCase",
"line_number": 11,
"usage_type": "argument"
}
] |
521999527 | from django.contrib import admin
from app.models import Todo
# Register your models here.
class TodoAdmin(admin.ModelAdmin):
list_display = (
"title",
"user",
"status",
'priority',
'updated_date',
'created_date',
)
list_filter = ("user", )
search_f... | null | app/admin.py | admin.py | py | 393 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.contrib.admin.ModelAdmin",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "django.contrib.admin.site.register",
"line_number": 17,
"usage_type": "call"
},... |
162104565 | """server URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.1/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based ... | null | webserver/server/main/urls.py | urls.py | py | 1,088 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.urls.path",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.urls.path",... |
124164151 | #!C:/Users/Anjana/Anaconda3/python.exe
# coding: utf-8
# In[1]:
'''
* Author : Anjana Tiha
* Course : Inform Retrieval/Web Search
* Course Instructor: Professor Visali Rus
* Semester : Fall 2017
* University : University of Memphis
* Project Name : Web Search Engine Implementat... | null | search_engine/search_engine_website/Obsolete/search_engine2.py | search_engine2.py | py | 33,707 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "queue.Queue",
"line_number": 75,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 79,
"usage_type": "call"
},
{
"api_name": "os.makedirs",
"line_number": 125,
"usage_type": "call"
},
{
"api_name": "errno.EEXIST",
"line_number": ... |
490320112 | import pandas as pd
import sqlalchemy as db
from sqlalchemy import Column, Float, Table, Integer, String
from sqlalchemy.ext.declarative import declarative_base
engine = db.create_engine('sqlite:///traindb.db', echo=True)
Base = declarative_base()
Base.metadata.reflect(engine)
def create_tb(table_name, column_names)... | null | Assignment 1/Database/Resources/Database_utilities.py | Database_utilities.py | py | 1,463 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sqlalchemy.create_engine",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.ext.declarative.declarative_base",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.Column",
"line_number": 15,
"usage_type": "call"
},
{
... |
631617206 | #!/usr/bin/env python3
"""
Author: Harsh Desai
Course: JHU EN.685 Data Science
Problem Set 2: Obtaining and Querying Data
Description: Excel file parser for Top 100 Contractors of
the U.S. federal goverment.
"""
import sqlite3
import os
import pandas as pd
import re
def parse_xlsx(excel_file):
# Starts parsing e... | null | ProblemSets/Problem_Set_2/contracts.py | contracts.py | py | 4,666 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.read_excel",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "re.search",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "pandas.Series",
"lin... |
357714408 | from setuptools import setup, find_packages
version = '0.4'
long_description = ('a package destined to be forgotten')
setup(name='themes.realestate_ecuador',
version=version,
description="Theme for Real Estate Agents",
long_description=long_description,
# Get more strings from
# http://... | null | pypi_install_script/themes.realestate_ecuador-0.4/setup.py | setup.py | py | 1,082 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "setuptools.setup",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "setuptools.find_packages",
"line_number": 21,
"usage_type": "call"
}
] |
430664575 | # -*- coding: utf-8 -*-
# @Author = moon
# @Create = 2018/4/28 14:35
# @File = baisi.py
# 用于爬取百思不得姐图片，可指定爬取页面
import requests,re,urllib.request
def getPic(page):
response = requests.get("http://www.budejie.com/pic/%s" % page)
html = response.text
reg = r'data-original="(.*?)"'
for i in re.findall(reg... | null | 百思不得姐/baisi.py | baisi.py | py | 560 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.get",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "re.findall",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "urllib.request.request.urlretrieve",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "urllib.req... |
60272334 | from keras.datasets import reuters
from keras import models
from keras import layers
import numpy as np
# 读取数据
(train_data, train_labels), (test_data, test_labels) = reuters.load_data(
path='/users/yu/desktop/keras__datasets/reuters.npz',
num_words=10000)
print(len(train_data))
# 数据向量化
def vectorize_sequenc... | null | ai2_mouple.py | ai2_mouple.py | py | 1,656 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "keras.datasets.reuters.load_data",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "keras.datasets.reuters",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "numpy.zeros",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "num... |
272602468 | """Audit
functions to simplify adding context and extra data to log messages destined for audit logs
"""
import logging
from hydrant.logserverhandler import LogServerHandler
EVENT_LOG_NAME = "hydrant_event_logger"
def audit_log_init(app):
log_server_handler = LogServerHandler(
jwt=app.config['LOGSERVER... | null | hydrant/audit.py | audit.py | py | 921 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "hydrant.logserverhandler.LogServerHandler",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 17,
"usage_type": "attribute"
},
{
"api... |
264579636 | import twitter
outfile = open("twitterFollowers.txt", 'w')
# Variables that contains the user credentials to access Twitter API
ACCESS_TOKEN = '824794440409706496-CGUoqhcZpfk4lOcblNVG1OuubwaCqZp'
ACCESS_SECRET = 'Mgd7wctkwI3nNUL6RHD4Cqjg9HVngccRrynoWfEsTUzlJ'
CONSUMER_KEY = '72haUMMgwOXNNGXXz4G0N7B9m'
CONSUMER_SECRET... | null | assignments/a4-solution/getFollowers.py | getFollowers.py | py | 1,165 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "twitter.Api",
"line_number": 10,
"usage_type": "call"
}
] |
205353916 | from alerta.models.alert import Alert
from alerta.webhooks import WebhookBase
import json
class DynatraceWebhook(WebhookBase):
def incoming(self, query_string, payload):
services = []
#serviceValue = payload['ImpactedEntities'][1]['entity'].split('-')[0]
#services.append(serviceValue)
... | null | webhooks/dynatrace/alerta_dynatrace.py | alerta_dynatrace.py | py | 1,047 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "alerta.webhooks.WebhookBase",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "alerta.models.alert.Alert",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 33,
"usage_type": "call"
}
] |
356862931 | #!/usr/bin/env python3
#
# Copyright 2017 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law ... | null | tools/plot_satisfaction.py | plot_satisfaction.py | py | 3,002 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.asarray",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "numpy.sum",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "simulation.static.user_satisfaction",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "simulatio... |
327967529 | # coding=utf-8
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import ast
import argparse
from math import ceil
import paddle
import numpy as np
import paddle.static
from paddlehub.module.module import moduleinfo, runnable, serving
from paddle.inf... | null | modules/image/object_detection/faster_rcnn_resnet50_coco2017/module.py | module.py | py | 8,513 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.join",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "processor.load_label_info",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "os.path.join",
... |
200973279 | #!/usr/local/bin/python2.7
from sys import exit, stdout, argv
from os import environ, system
environ['KERAS_BACKEND'] = 'tensorflow'
environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
environ["CUDA_VISIBLE_DEVICES"] = ""
import numpy as np
import utils
import signal
from keras.layers import Input, Dense, Dropout, concaten... | null | train/full/models/train_shallow_panda_5_decorr.py | train_shallow_panda_5_decorr.py | py | 3,703 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.environ",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "os.environ",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "os.environ",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "keras.backend.set_image_data_format",
... |
444566081 | import os
from fabric.api import cd, env, task, require, sudo, prefix, shell_env, run
from fabric.contrib.files import exists, upload_template
REPO_URL = 'https://github.com/pudo/nomenklatura.git'
PACKAGES = (
'git-core',
'nginx',
# 'npm',
'python-dev',
'python-virtualenv',
'supervisor',
)
@... | null | fabfile.py | fabfile.py | py | 3,461 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "fabric.api.env.user",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "fabric.api.env",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "fabric.api.env.hosts",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "fab... |
543145775 | import csv
import django
django.setup()
import website.alimentos as alimentos
def run(nomeArq):
with open(nomeArq, encoding='utf8') as csvfile:
reader = csv.reader(csvfile, delimiter=';')
for row in reader:
numero = int(row[0])
porcao = row[1]
descricao = row[2]
... | null | carregar_alimentos.py | carregar_alimentos.py | py | 2,681 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.setup",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "csv.reader",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "website.alimentos.Alimento",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "website.alimentos",
... |
198010386 | from flask import Flask
from app.routes import app
application = Flask(__name__)
application.config.from_object('config.ConfigDev')
application.register_blueprint(app)
if __name__ == '__main__':
application.debug = True
application.run(host="0.0.0.0",port=3000,debug=True) | null | application.py | application.py | py | 282 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Flask",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "app.routes.app",
"line_number": 6,
"usage_type": "argument"
}
] |
441252048 | import cv2
import numpy as np
from PIL import Image
from PIL.ExifTags import TAGS
import PIL.ExifTags
tImgNum=7
imgNames = []
for i in range(1,tImgNum+1):
imgNames.append("01 ("+str(i)+").JPG")
print(i)
imgList = [cv2.imread(fn) for fn in imgNames]
def get_field (exif,field) :
for (k,v) in exif.items():
if TAGS.ge... | null | HDR.py | HDR.py | py | 1,624 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "cv2.imread",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "PIL.ExifTags.TAGS.get",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "PIL.ExifTags.TAGS",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "PIL.Image.open",
... |
508303503 | import gc
import json
import sys
from time import sleep
from confluent_kafka import Consumer, KafkaError, KafkaException
from clickhouse import init_clickhouse_database, save_to_clickhouse
from config import settings
from models import Event
# kafka client init
conf = {
"bootstrap.servers": settings.kafka_hosts_... | null | etl/src/main.py | main.py | py | 1,723 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "config.settings.kafka_hosts_as_string",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "config.settings",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "config.settings.kafka_consumer_group",
"line_number": 15,
"usage_type": "attri... |
22564525 | import torch
from model import ModelSimple1
import const,utils
import numpy as np
from torch.autograd import Variable
import math
import scipy.stats
from sklearn.metrics import f1_score
from io import open
def cal_f1(targets,outputs):
outputs_bin = []
targets_bin = []
for i in xrange(len(outputs)):
... | null | eval.py | eval.py | py | 1,952 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sklearn.metrics.f1_score",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "torch.from_numpy",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "numpy.dot",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "math.sqrt",
"... |
339731834 | """The module for the Resource class.
Classes:
Resource
"""
from typing import List, Optional, Union
from rdflib import Namespace, URIRef
from modules.nampi_graph import Nampi_graph
from modules.node import Node
class Resource(Node):
"""A RDF resource resource with an individual uri and possibly a label."... | null | modules/resource.py | resource.py | py | 1,122 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "modules.node.Node",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "modules.nampi_graph.Nampi_graph",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "typ... |
30886225 | #!/usr/bin/env python3
import os
import argparse
import cv2
import numpy as np
import imutils
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True, help="path to input image for preprocessing")
ap.add_argument("-t", "--threshold", require... | null | MachineLearning/natural-language-processing/tesseract/preprocess.py | preprocess.py | py | 4,141 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "cv2.IMREAD_GRAYSCALE",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "imutils.... |
472821756 | from django.conf.urls import re_path
from django.urls import path
from django.contrib.auth.decorators import login_required
from django.views.decorators.csrf import csrf_exempt
from .views import (
AppointmentCreateView,
AppointmentDeleteView,
AppointmentDetailView,
AppointmentListView,
Appointment... | null | reminders/urls.py | urls.py | py | 1,358 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.urls.path",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "django.contrib.auth.decorators.login_required",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "views.AppointmentListView.as_view",
"line_number": 16,
"usage_type": "call... |
320203693 | import decimal
import logging
import ujson
from collections import defaultdict
import operator
import pandas as pd
from django.contrib.contenttypes.models import ContentType
from django.db import transaction
from django.db.models.query_utils import Q
from django.utils import timezone
from rest_framework import status,... | null | api/v1/goals/views.py | views.py | py | 29,720 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "decimal.getcontext",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "decimal.FloatOperation",
"line_number": 37,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "api.... |
184077974 | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 22 10:58:08 2016
@author: David
"""
from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
import pyx
from pyxgraph import PyXGraph, pyxcolorbar, pyxsave
def r_rescale(r, e0):
"""
Parameters
--... | null | Programme/imports/tov_functions.py | tov_functions.py | py | 12,062 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.zeros",
"line_number": 93,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 95,
"usage_type": "call"
},
{
"api_name": "numpy.pi",
"line_number": 95,
"usage_type": "attribute"
},
{
"api_name": "numpy.pi",
"line_number": 9... |
49844547 | from pathlib import Path
from soulstruct.base.events.core import convert_events as convert_events_base, compare_events as compare_events_base
from .emevd import EMEVD
from ..maps.constants import ALL_MAPS
def convert_events(
output_type,
output_directory,
input_type=None,
input_directory=None,
ma... | null | soulstruct/darksouls3/events/utilities.py | utilities.py | py | 2,121 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pathlib.Path",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "maps.constants",
"line_number": 31,
"usage_type": "name"
},
{
"api_name": "maps.constants",
"line_number": 32,
"usage_type": "name"
},
{
"api_name": "maps.constants.ALL_MAPS",
... |
552357671 | #! /usr/bin/env python
# coding: utf-8
"""Contains the parser class which allows to cut a sentence."""
import unicodedata
import config as const
from fuzzywuzzy import fuzz
class Parser:
"""The objects in this class are used to cut and clean sentences."""
def __init__(self):
"""Initialise the word... | null | grandpyapp/backend/parser.py | parser.py | py | 2,098 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "config.STOP_WORDS_GENERIQUE",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "config.STOP_WORD_ADDED",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "unicodedata.normalize",
"line_number": 24,
"usage_type": "call"
},
{
... |
625166324 |
#This program performs surface and volume rendering for a dataset.
import vtk
from vtk.util.numpy_support import vtk_to_numpy, numpy_to_vtk
import argparse
import numpy as np
#Gaussian filter
def gaussianFilter(image):
filter = vtk.vtkImageGaussianSmooth()
filter.SetInputConnection(image.GetOutp... | null | visualization_final_2.py | visualization_final_2.py | py | 16,481 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "vtk.vtkImageGaussianSmooth",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "vtk.vtkImageThreshold",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "vtk.vtkMarchingCubes",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": ... |
191385798 | #实例：
#中国大学排名爬虫
#定向爬虫
#输入URL排名，输出大学排名信息
import requests
from bs4 import BeautifulSoup
import bs4
def getHTMLText(url):
try:
r = requests.get(url, timeout=30);
r.raise_for_status()
r.encoding = r.apparent_encoding
return r.text
except:
return ""
def fillU... | null | UnivRanklist.py | UnivRanklist.py | py | 1,254 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.get",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "bs4.element",
"line_number": 21,
"usage_type": "attribute"
}
] |
304736819 | import numpy as np
import matplotlib.pyplot as plt
date, recordedWeather, conditions, high, low = np.loadtxt("RealWeatherData.csv", unpack=True, delimiter=',', dtype='str')
#part a: ratio of cloudy to clear days
def getRatioOfCloudyToClear(conditions):
daysClear = 0 #initialize daysClear to 0
for i in range (... | null | p6problem1/p6problem1.py | p6problem1.py | py | 3,684 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.loadtxt",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "numpy.where",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "numpy.amax",
"line_number": ... |
597603745 | import csv
import json
fr = open("data4030000-4035499.json")
fw = open("data.csv", "w", newline="")
csv_writer = csv.writer(fw)
json_fr = json.load(fr)
csv_writer.writerow(["maths","phy","chem","mech","bee","workshop","cgpa","sgpa"])
for student in json_fr:
marks = student['marks']
csv_writer.writerow(list(m... | null | jsontocsv.py | jsontocsv.py | py | 358 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "csv.writer",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 7,
"usage_type": "call"
}
] |
598851005 | #!/usr/bin/env python3
import os
import re
import yaml
script_path = os.path.dirname(os.path.abspath(__file__))
def_path = os.path.join(script_path, "definitions")
for fn in os.listdir(def_path):
print(f"processing {fn} ...")
with open(os.path.join(def_path, fn)) as f:
y = yaml.safe_load(f)
bn = os.path.s... | null | generate.py | generate.py | py | 1,009 | python | en | code | null | code-starcoder2 | 76 | [
{
"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": 8,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_nu... |
70154575 |
from sklearn.cluster import KMeans
from scipy.spatial.distance import cdist
import matplotlib.pyplot as plt
### ElbowMethod
distortions = []
K = range(1,10)
for k in K:
kmeanModel = KMeans(n_clusters=k)
kmeanModel.fit(X)
distortions.append(sum(np.min(cdist(X,kmeanModel.cluster_centers_, 'euclidean'), a... | null | English/Clustering.py | Clustering.py | py | 2,196 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sklearn.cluster.KMeans",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "scipy.spatial.distance.cdist",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.plot",
"line_number": 15,
"usage_type": "call"
},
{
"api_na... |
323633722 | from __future__ import unicode_literals
from django.shortcuts import render, redirect
from datetime import datetime
import random
def index(request):
if 'gold' not in request.session:
request.session['gold'] = 0
request.session['activities'] = []
context = {
"gold": request.session["gold"],
"activities": re... | null | PythonDjango - Week 6/ninja_gold/main/apps/ninja_gold/views.py | views.py | py | 1,566 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.shortcuts.render",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "rando... |
482110090 | '''
PyDenseCRF:
https://github.com/lucasb-eyer/pydensecrf
reference of opencv color histogram:
https://www.pyimagesearch.com/2014/07/14/3-ways-compare-histograms-using-opencv-python/
https://docs.opencv.org/3.3.1/dd/d0d/tutorial_py_2d_histogram.html
'''
import numpy as np
import pydensecrf.densecrf as dcrf
from pyde... | null | CRF_all_class_paral.py | CRF_all_class_paral.py | py | 18,449 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.max",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "numpy.exp",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "numpy.sum",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 67,
... |
44704960 | # ! /usr/bin/python
# -*- coding: utf-8 -*-
import time, struct, os
# from openpyxl import Workbook, load_workbook
from jinja2 import Environment, FileSystemLoader
log_config = {
}
def set_log_path():
# 日志函数辅助函数
fmt = '%Y%m%d%H%M%S'
value = time.localtime(int(time.time()))
dt = time.strftime(fmt, va... | null | utils.py | utils.py | py | 1,470 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "time.localtime",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "time.strftime",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "time.localtime",
"line_num... |
305185281 | from kivy.lang import Builder
from plyer import gps
from kivy.app import App
from kivy.properties import BooleanProperty, ListProperty, StringProperty
from kivy.clock import mainthread
from kivy.utils import platform
kv = '''
<ProviderToggleButton@ToggleButton>:
red: rgba('#8B0000')
black: rgba('#ffffff')
... | null | examples/gps/main.py | main.py | py | 4,803 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "kivy.app.App",
"line_number": 66,
"usage_type": "name"
},
{
"api_name": "kivy.properties.StringProperty",
"line_number": 67,
"usage_type": "call"
},
{
"api_name": "kivy.properties.StringProperty",
"line_number": 68,
"usage_type": "call"
},
{
"api_na... |
606643667 | #!/usr/lib/env python35
# for more information about matplotlib, see:
# http://matplotlib.org/users/pyplot_tutorial.html
import numpy as np
import matplotlib.pyplot as plt
if __name__=="__main__":
# Create some fake data
run1 = [1,2,3]
run2 = [2,4,5]
run3 = [1,10,2]
xpoints = [1,2,3]
run1_l... | null | Assignment/A2/grapher.py | grapher.py | py | 731 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "matplotlib.pyplot.plot",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.plot",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "matpl... |
639958166 | """Process EEG data from the EEGDev dataset, saving out PSDs from resting EEG data.
Notes
-----
- This script can / should be updated to save out FOOOF objects, rather than extracted slope data.
"""
import os
import csv
import mne
import numpy as np
from fooof import FOOOFGroup
from slf.core.db import SLFDB
from sl... | null | childmind/scripts/proc_dev_dat.py | proc_dev_dat.py | py | 7,974 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "mne.set_log_level",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "slf.core.db.SLFDB",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_number": 85,
"usage_type": "call"
},
{
"api_name": "csv.reader",
"l... |
515625333 | import csv
import time
import requests
from bs4 import BeautifulSoup
import re
import os
headers = {
'user-agent': 'Renty',
}
duplicate_count = 0
max_duplicate_count = 3
propertyData = []
class urlManager:
index = 0
base_url = "https://www.rightmove.co.uk/property-for-sale/find.html?locationIdentifier=... | null | main.py | main.py | py | 2,311 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.sep",
"line_number": 50,
"usage_type": "attribute"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"lin... |
47875336 | """wp_dj URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class... | null | wordpress_django_integration/wp_dj/urls.py | urls.py | py | 1,382 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.urls.path",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.contrib.admin.site",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "... |
100425580 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import math
from scipy.optimize import curve_fit
from scipy.optimize import minimize
from iminuit import Minuit
from pprint import pprint
#import median stack data + associated fitting results
from observationcode import *
#########################... | null | attenuationcode.py | attenuationcode.py | py | 3,639 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.genfromtxt",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.genfromtxt",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "matplotlib... |
454669234 | from flask import Flask
from flask import render_template
from flask import redirect
from flask import Blueprint
from flask import make_response
from flask import request
from flask import url_for
from flask import session
from flask import abort
import uuid
import yagmail
from models.user import User
from utils impo... | null | routes/login.py | login.py | py | 2,225 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Blueprint",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "flask.make_response",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "flask.render_template",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "flask.make_... |
70752505 | #!/usr/bin/env python
"""Tests the BME280 sensor"""
import time
import logging
from nanpy import BME280
from nanpy.serialmanager import SerialManager
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("BME280")
connection = SerialManager(sleep_after_connect=2)
connection.open()
sensor = BME280(conn... | null | nanpy/examples/bme280.py | bme280.py | py | 697 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.basicConfig",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "nanpy.serialm... |
72405103 | # uncompyle6 version 3.7.4
# Python bytecode 2.7 (62211)
# Decompiled from: Python 3.6.9 (default, Apr 18 2020, 01:56:04)
# [GCC 8.4.0]
# Embedded file name: paxmusica/model.py
# Compiled at: 2013-03-05 16:27:54
import os, fnmatch, id3reader
from flask import g
from os.path import join, isdir
import sqlite3
db_locatio... | null | pycfiles/paxmusica-0.0.3.tar/model.py | model.py | py | 5,618 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.g.cur.execute",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "flask.g.cur",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "flask.g",
"line_number": 24,
"usage_type": "name"
},
{
"api_name": "flask.g.cur.execute",
... |
349469483 | import pickle
from gensim.corpora import Dictionary
from gensim.models.ldamodel import LdaModel
from tqdm import tqdm
from utils import (
load_config,
prep_text,
)
config = load_config()
n = 100000
# Preprocessing text
print("Preprocessing text...")
data = []
for doc in tqdm(open(config["gigaword"], "r")):
... | null | scripts/train_lda_model.py | train_lda_model.py | py | 763 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "utils.load_config",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "tqdm.tqdm",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "utils.prep_text",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "gensim.corpora.Dictionary... |
602267276 | import openpyxl
from openpyxl.utils.cell import get_column_letter
def replace_nulls(filename):
wb = openpyxl.load_workbook(filename)
wb.sheetnames
sheet = wb["Sheet1"]
amountOfRows = sheet.max_row
amountOfColumns = sheet.max_column
for i in range(amountOfColumns):
for k in range(amountOfRows):
cell = str(... | null | file_processing/etls/excelswapper.py | excelswapper.py | py | 1,011 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "openpyxl.load_workbook",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "openpyxl.utils.cell.get_column_letter",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "openpyxl.utils.cell.get_column_letter",
"line_number": 17,
"usage_type": "cal... |
130031182 | # compare new / old versions of SNAP downscaled outputs
def open_raster( fn, band=1 ):
with rasterio.open( fn ) as rst:
arr = rst.read(1)
return arr
def compare_files( old, new ):
old = open_raster(old)
new = open_raster(new)
diff = (old-new)
return (np.min(diff),np.max(diff))
def wrap( x ):
old, new = x
r... | null | snap_scripts/downscaling_v2/compare_variable_output_versions.py | compare_variable_output_versions.py | py | 1,047 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "glob.glob",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 29,
"usage_type": "attribute"
},
{
"api_name": "multiprocessing.Pool",
"line_... |
477035934 | import urwid
class MsgInput(urwid.Edit):
signals = ['move-focus', 'send-msg']
def submitMsg(self):
urwid.emit_signal(self, 'send-msg', self.edit_text)
self.set_edit_text('')
def keypress(self, size, key):
if key == 'enter':
# send a message
self.submitMsg()
if key == 'up' and self.get_cursor_coord... | null | lib/ui/msg_input.py | msg_input.py | py | 610 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "urwid.Edit",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "urwid.emit_signal",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "urwid.emit_signal",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "urwid.ExitMainLoop"... |
20953072 | from datetime import datetime
from http.client import HTTPMessage
import io
import os
import unittest
from github3.session import AppInstallationTokenAuth
import mock
import responses
from cumulusci.core.exceptions import GithubException
from cumulusci.core import github
from cumulusci.core.github import get_github_a... | null | cumulusci/core/tests/test_github.py | test_github.py | py | 3,674 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "mock.Mock",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "http.client.HTTPMessage",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "io.BytesIO",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "unittest.TestCase",... |
22037612 | #!/usr/bin/python
""" Automation Framework to run tests
usage: autopsy.py [-h] --test-bed TEST_BED --log-file LOG_FILE --test-suite
TEST_SUITE [--run-tests RUN_TEST[,RUN_TEST,RUN_TEST]]
[--skip-tests SKIP_TEST[,SKIP_TEST,SKIP_TEST]] [-d]
"""
import os
import parser... | null | main/autopsy.py | autopsy.py | py | 15,134 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.chdir",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "os.path.realpath",
"line_nu... |
616891261 | import utils
# fetch data
data = utils.line_to_list('input_files/aoc_17.txt')
### START SOLUTION BODY ###
def get_neighbors(x, y, z, w):
return [(i, j, k, l) for i in range(x - 1, x + 2) for j in range(y - 1, y + 2) for k in range(z - 1, z + 2) for l in range(w - 1, w + 2) if not i == x or not j == y or not k ==... | null | 2020/day_17/part_b.py | part_b.py | py | 1,872 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "utils.line_to_list",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "utils.one_val_out",
"line_number": 58,
"usage_type": "call"
}
] |
309420754 | import sys
sys.path.insert(0, "..")
from opcua import Client
import time
from time import sleep
from pyo import *
import tkinter as tk
import threading
rootTk = tk.Tk()
canvas = tk.Canvas(rootTk, width=400, height=400, borderwidth=0, highlightthickness=0, bg="black")
canvas.grid()
fileName = 'alerts.log'
def _... | null | client-minimal-prueba.py | client-minimal-prueba.py | py | 5,581 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path.insert",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "tkinter.Tk",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "tkinter.Canvas",
"line_num... |
291539209 | from django.shortcuts import render
from myapp.models import Article, Categories
def index(request):
return render(request, 'index.html')
def contact(request):
# articles = Article.objects.get(title='Google IA beats Human')
# articles = Article.objects.filter(title='Google IA beats Human')
# articles = Article... | null | myapp/views.py | views.py | py | 1,003 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.shortcuts.render",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "myapp.models.Article.objects.all",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "myapp.models.Article.objects",
"line_number": 14,
"usage_type": "attribute"
},
... |
625785067 | from django.shortcuts import render
from django.http import HttpResponse
from gallery.models import Images, Themes
from django.template import loader
# Create your views here.
def index(request):
#latest_images = FileUpload.objects.order_by('-date_added')[:4]
images = Images.objects.all()
#background = Bac... | null | views.py | views.py | py | 706 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "gallery.models.Images.objects.all",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "gallery.models.Images.objects",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "gallery.models.Images",
"line_number": 9,
"usage_type": "name"
},
... |
112993623 | import numpy as np
import mdutils
import os
# Load a file not on the path
import runpy
fetcher = runpy.run_path('../notebook/fetcher.py')
fetch_difumo = fetcher['fetch_difumo']
dic = {64: "https://osf.io/pqu9r/download",
128: "https://osf.io/wjvd5/download",
256: "https://osf.io/3vrct/download",
... | null | scripts/create_each_dimension_md.py | create_each_dimension_md.py | py | 1,556 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "runpy.run_path",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "mdutils.MdUtils",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number... |
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