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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
144645119 | # -*- coding: utf-8 -*-
from flask import request
from flask_restful import Resource, reqparse
from .notification import CREATED, UPDATED, PATCHED, REMOVED
import rest.timeservice as timeservice
from util.patch import patch, PatchConflict
import model
_NOTIFICATION_ARG = "notifications"
_API_ARG = "api"
_MODEL_ARG = ... | null | server/rest/tag.py | tag.py | py | 3,666 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "flask_restful.Resource",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "rest.timeservice.time_service",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "rest.timeservice",
"line_number": 27,
"usage_type": "name"
},
{
"api_na... |
317208988 | import os
import json
from data.preprocess_data import preprocess_data
import pandas as pd
import numpy as np
from copy import copy
'''
This file contains the functions that are used universally in the live deployments, usually for the generation of processed data.
'''
#creates the split dates array which rolls f... | null | code/utils/general_functions.py | general_functions.py | py | 11,118 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.exit",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "os.exit",
"line_number": 119,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 130,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 130,
... |
33537019 |
# !mkdir dst; for l in `cat best_model.txt`; do f=`echo $l|tr ',' '_'|cut -d '_' -f1-5`; for file in `find checkpoints/ -name $f*`; do cp $file dst/; done; done
import os
import pickle
import numpy as np
import statistics as st
from sklearn.metrics import mean_squared_error
from scipy.stats import pearsonr
from sc... | null | .ipynb_checkpoints/sent_analyze-checkpoint.py | sent_analyze-checkpoint.py | py | 5,030 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.path.join",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 3... |
371827357 | import os
import pydub
from docx import Document
# Imports the Google Cloud client library
from google.cloud import storage
from google.cloud import speech
from google.cloud.speech import enums
from google.cloud.speech import types
file_name = 'a'
# flacに変換
sound = pydub.AudioSegment.from_file('sound/' + file_name +... | null | sptotx.py | sptotx.py | py | 1,620 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pydub.AudioSegment.from_file",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pydub.AudioSegment",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "... |
50051373 | import cv2 as cv
import numpy as np
def bliateralFilter(image):
dst = cv.bilateralFilter(image,0,100,15)
cv.imshow("bliateralFilter",dst)
def pyrMeanShiftFilter(image):
dst = cv.pyrMeanShiftFiltering(image,10,50)
cv.imshow("pyrMeanShiftFilter",dst)
src = cv.imread("D:/opencv/head.jpg")
cv.imshow("h... | null | test/tutorial_8.py | tutorial_8.py | py | 418 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "cv2.bilateralFilter",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "cv2.pyrMeanShiftFiltering",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
... |
587526595 | '''
Created on 15 Apr 2020
@author: si
'''
import json
import os
from ayeaye.connectors.base import DataConnector, AccessMode
from ayeaye.pinnate import Pinnate
class JsonConnector(DataConnector):
engine_type = 'json://'
def __init__(self, *args, **kwargs):
"""
Single JSON file loaded into ... | null | ayeaye/connectors/json_connector.py | json_connector.py | py | 4,260 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "ayeaye.connectors.base.DataConnector",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "ayeaye.connectors.base.AccessMode.READ",
"line_number": 78,
"usage_type": "attribute"
},
{
"api_name": "ayeaye.connectors.base.AccessMode",
"line_number": 78,
"... |
348244176 | from django.core.management.base import BaseCommand, CommandError
from ImagePicker.views import *
import sys
class Command(BaseCommand):
help = 'deletes duplicate zone codes'
def handle(self, *args, **options):
#mapPoints = MapPoint.objects.all()
mapPoints = MapPoint.objects.filter(pk=69997)
... | null | streetviewInterface/mySite/ImagePicker/management/commands/deleteDuplicateZoneCodes.py | deleteDuplicateZoneCodes.py | py | 627 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.core.management.base.BaseCommand",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "sys.exit",
"line_number": 19,
"usage_type": "call"
}
] |
632510581 | #Exercise 9
#Authors: Janice Love and Melissa Stephens
#Load data and import packages
import numpy
import pandas
from scipy.optimize import minimize
from scipy.stats import norm
from scipy.stats import chi2
from plotnine import *
#need to read-in/populate dataframe with existing data
MyDataFrame=pandas.read_csv("Mmar... | null | Q2_Excercise09.py | Q2_Excercise09.py | py | 1,784 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_csv",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "scipy.stats.norm",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "scipy.optimize.minimize",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "numpy.arange... |
471975885 | from django.conf.urls.defaults import *
from data import views
# Uncomment the next two lines to enable the admin:
from django.contrib import admin
admin.autodiscover()
urlpatterns = patterns('',
('^$', views.hello),
(r'^test/$',views.qr),
(r'^time/plus/(\d{1,2})/$', views.hours_ahead),
(r'^choice/([a-z]+)/$',view... | null | urls.py | urls.py | py | 625 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.contrib.admin.autodiscover",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "django.contrib.admin",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "data.views.hello",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_nam... |
95899387 | # Crash Course Text Project 1 - 15th Iteration:
''' - Repopulating the fleet
- Speeding up the bullets
files updated:
game_functions.py
alien_invasion.py
settings.py
- Repopulating the fleet: When the fleet is destroyed - a new one appears.
- Speeding up bullets due to the am... | null | Python_Crash_Course_text/Crash_Course_Text_Projects/15_ver_Project_01/alien_invasion.py | alien_invasion.py | py | 1,318 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pygame.init",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "settings.Settings",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "pygame.display.set_mode",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "pygame.display"... |
117844676 | # -*- coding: utf-8 -*-
from PyQt5.QtCore import QCoreApplication, pyqtSlot
from PyQt5.QtWidgets import QApplication, QDialog,QMainWindow
from PyQt5 import QtGui
from UI.SCRIPT.Readpage_Script import Ui_Read_Window
from UI.Theme.Journal_Content_Layout import layout
import requests
from bs4 import Beauti... | null | Core/Outliner_Journal.py | Outliner_Journal.py | py | 2,262 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "UI.Theme.Styles.Black_white",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "UI.Theme.Styles.White_Black",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "UI.Theme.Styles.Sleep_Red",
"line_number": 15,
"usage_type": "name"
},
{
... |
446009484 | import numpy as np
from sklearn import svm, datasets
from sklearn.cross_validation import train_test_split
from sklearn.multiclass import OneVsRestClassifier
from sklearn_evaluation import ClassifierEvaluator
# Import some data to play with
iris = datasets.load_iris()
X = iris.data
y = iris.target
# Add noisy featur... | null | examples/generate_report.py | generate_report.py | py | 1,492 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sklearn.datasets.load_iris",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "sklearn.datasets",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "numpy.random.RandomState",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "nu... |
553055567 | import pygame
import globals
class Enemy(pygame.sprite.Sprite):
def __init__(self, color, pos, player):
super().__init__()
self.color = color
self.image = pygame.Surface([20, 20])
self.image.fill(color)
self.image.set_colorkey((255, 255, 255))
self.rect = self.i... | null | entities/enemy.py | enemy.py | py | 928 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pygame.sprite",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "pygame.Surface",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pygame.math.Vector2",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "pygame.math",
... |
410849924 | from datetime import datetime as dt
from time import time
import requests
from common_components.orderbook import OrderBook
import numpy as np
class CoinbaseOrderBook(OrderBook):
def __init__(self, sym):
super(CoinbaseOrderBook, self).__init__(sym, 'coinbase')
self.sequence = 0
def _get_book... | null | coinbase_connector/coinbase_orderbook.py | coinbase_orderbook.py | py | 5,111 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "common_components.orderbook.OrderBook",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "time.time",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "time.time... |
77417560 | import collections
from math import sqrt
import sys
import numpy as np
def calculate_diagonal(m):
result = 1
for i in range(min(len(m), len(m[0]))):
if m[i][i] != 0:
result = result * m[i][i]
return result
def multiset_equal(x, y):
first_set = collections.Counter(x... | null | functions.py | functions.py | py | 1,744 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "collections.Counter",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "collections.Counter",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "sys.maxsize",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "numpy.array"... |
180070608 | import numpy as np
import matplotlib.pyplot as plt
from math import sin, pi
import scipy.signal as signal
def heterodyne(stageName, t, p, rfreq, ifreq, fs_rf, fs_if, aa_cut, plots=True):
# Stage 1: RF-IF1
# Design/build AA filter
IF1osc = rfreq - ifreq
IF1AAcutoff = aa_cut
digcut = IF1AAcutoff/fs_r... | null | Radar/RFGenerator.py | RFGenerator.py | py | 2,992 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "scipy.signal.firwin",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "scipy.signal",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "numpy.zeros",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "math.sin",
"line_num... |
166562011 | import json
SPEED_OUTPUT_PATH = "./output/speed_meta.json"
FACE_OUTPUT_PATH = "./output/face_meta.json"
HAND_OUTPUT_PATH = "./output/hand_meta.json"
class MetaCollector:
def __init__(self):
self._frame_number = 0
self._data = []
self._hands = {'left_hand': [], 'right_hand': []}
def p... | null | project/solution/meta_collector.py | meta_collector.py | py | 2,340 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "json.dump",
"line_number": 65,
"usage_type": "call"
}
] |
258103828 | from scrapy.spider import BaseSpider
from scrapy.selector import HtmlXPathSelector
from scrapy.http import Request
from product_spiders.items import Product, ProductLoaderWithNameStrip as ProductLoader
from urlparse import urljoin as urljoin_rfc
from scrapy.utils.response import get_base_url
from product_spiders.... | null | e-commerce/CompetitorMonitor/product_spiders/spiders/qatesting2/alexanderandjames_com.py | alexanderandjames_com.py | py | 8,058 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "scrapy.spider.BaseSpider",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "scrapy.xlib.pydispatch.dispatcher.connect",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "scrapy.xlib.pydispatch.dispatcher",
"line_number": 28,
"usage_type": "... |
457582573 | __author__ = 'YaelSegal & TzeviyaFuchs'
# VGG model was taken from Yossi Adi
import torch.nn as nn
import torch.nn.functional as F
import torch
def _make_layers(cfg, kernel=3):
layers = []
in_channels = 1
for x in cfg:
if x == 'M':
layers += [nn.MaxPool2d(kernel_size=2, stride=2)]
... | null | model_speech_yolo.py | model_speech_yolo.py | py | 5,782 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "torch.nn.MaxPool2d",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv2d",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_numb... |
397261697 | import numpy as np
import pandas as pd
from tensorflow.keras.models import Sequential, Model, load_model
from tensorflow.keras.layers import Dense, LSTM, Conv1D, Input, Flatten, MaxPooling1D, Dropout, Reshape, SimpleRNN, LSTM, LeakyReLU, GRU, Conv2D, MaxPool2D, BatchNormalization, Activation
from tensorflow.keras.c... | null | dacon/solar/py/ff.py | ff.py | py | 10,950 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_csv",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "pandas.concat",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "numpy.cos",
"line_n... |
421702277 | # -*- coding: utf-8 -*-
"""
Created on Sun Aug 23 00:38:00 2020
@author: BT
"""
'''
In semantic segmentation, each pixel is classified according to the class of the object it
belongs to (e.g., road, car, pedestrian, building, etc.), as shown in Figure 14-26. Note
that different objects of the same class are not disti... | null | DL/14_DeepCVusingCNN/10_semantic_segmentation.py | 10_semantic_segmentation.py | py | 8,226 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "tensorflow.reduce_min",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "tensorflow.reduce_max",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "sklearn.datasets.load_sample_image",
"line_number": 53,
"usage_type": "call"
},
{
"ap... |
619274547 | #!/usr/bin/env python
"""Application that calculates the domain architecture of each gene and
outputs them in a simple text-based format.
"""
from __future__ import print_function
from collections import defaultdict
import operator
import sys
import re
from gfam.assignment import AssignmentOverlapChecker
from gfam.ass... | null | gfam/scripts/find_domain_arch.py | find_domain_arch.py | py | 23,183 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "gfam.scripts.CommandLineApp",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "gfam.utils.redirected",
"line_number": 125,
"usage_type": "call"
},
{
"api_name": "gfam.assignment.AssignmentOverlapChecker.max_overlap",
"line_number": 135,
"usage_type... |
469951562 | import numpy as np
import pandas as pd
from random import randint
import random
import argparse
import time
import itertools, collections
import networkx as nx
import matplotlib.pyplot as plt
# Patent Cit. dataset with 7515023 Triangles and Fraction of closed triangles 0.02343 -- 16518948 edges
# Adolescent health dat... | null | min_data_streams/main.py | main.py | py | 5,481 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "networkx.from_edgelist",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "networkx.triangles",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "mat... |
585031671 | import torch
import torch.nn as nn
import numpy as np
from torch.utils.data import Dataset, DataLoader
import torch.nn.functional as F
import torch.optim as optim
from tqdm.notebook import tqdm
import math
import copy
import random
#-----------------------------------------Model Definition----------------------------... | null | hw4&5/kq4ff-stackedlstm-rnnlm.py | kq4ff-stackedlstm-rnnlm.py | py | 7,343 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "torch.nn.Module",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "torch.nn.Embedding",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line... |
158122452 | import json
import os
from PyQt5.QtWidgets import QLabel, QWidget, QPushButton, QFormLayout, QLineEdit, QHBoxLayout, QVBoxLayout
from PyQt5.QtGui import QIntValidator
from PyQt5.QtCore import pyqtSignal, Qt
from fitness_tracker.database_wrapper import DatabaseWrapper
class UpdateLiftsForRepsWindow(QWidget):
change_l... | null | fitness_tracker/notes/compound_exercises/update_lifts_for_reps_window.py | update_lifts_for_reps_window.py | py | 8,504 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "PyQt5.QtWidgets.QWidget",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "PyQt5.QtCore.pyqtSignal",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtCore.pyqtSignal",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": ... |
312034555 | # Copyright 2018 Iguazio
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, softwa... | null | mlrun/runtimes/base.py | base.py | py | 39,958 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "model.ModelObj",
"line_number": 56,
"usage_type": "name"
},
{
"api_name": "model.ModelObj",
"line_number": 62,
"usage_type": "name"
},
{
"api_name": "model.ModelObj",
"line_number": 70,
"usage_type": "name"
},
{
"api_name": "model.ModelObj",
"li... |
457624286 | from django.shortcuts import render
from django.contrib.auth.decorators import login_required
from catalog.models.country import Country
@login_required
def countries(request):
"""
Страница списка стран
:param request:
:return:
"""
countries = Country.objects.all
template = 'user/country_... | null | catalog/views/user_views/lists/country_list.py | country_list.py | py | 451 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "catalog.models.country.Country.objects",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "catalog.models.country.Country",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "django.shortcuts.render",
"line_number": 19,
"usage_type": "ca... |
346418181 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import datetime
from django.utils.timezone import utc
class Migration(migrations.Migration):
dependencies = [
('blog', '0001_initial'),
]
operations = [
migrations.CreateModel(
... | null | blog/migrations/0002_auto_20150510_2004.py | 0002_auto_20150510_2004.py | py | 1,242 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.db.migrations.Migration",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "django.db.migrations",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "django.db.migrations.CreateModel",
"line_number": 16,
"usage_type": "call"
},
... |
640558266 | import numpy as np
def str_to_list(string):
#print(string)
#string= string[1:-1]
listt= string.split(", ")
listt2=[]
for i in range(0,len(listt)):
#print(listt[i])
#listt2.append(float(listt[i][1:-1]))
listt2.append(float(listt[i]))
return listt2
def get_data_bumps(filename1, data_with_labels):
file1... | null | randomForestClassifier.py | randomForestClassifier.py | py | 3,003 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sklearn.__version__",
"line_number": 73,
"usage_type": "attribute"
},
{
"api_name": "numpy.array",
"line_number": 110,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 111,
"usage_type": "call"
},
{
"api_name": "sklearn.utils.shuf... |
643199375 | # stmfile generator
from PIL import Image
import numpy as np
import cv2
from itertools import product
# meta settings
NOCONVERT = False
NOMOVIE = False
filepath = "./10square_stripe05.stm"
# settings
width = 10
height = 10
frame = 100
fps = 10
total_time = frame / fps
current_max = 0.5
# making arrays... | null | util/stmgenerater/stmgenerater.py | stmgenerater.py | py | 2,637 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "numpy.zeros",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "numpy.full",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "numpy.copy",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "numpy.copy",
"line_number": 34,... |
201035224 | import sys, os
import pygame as pg
import numpy as np
from pygame.locals import *
from PyQt5.QtWidgets import QMainWindow, QApplication, QWidget, QFrame, QAction, QPushButton, QTabWidget, QVBoxLayout, QToolBar, QListWidget, QOpenGLWidget
from PyQt5.QtGui import QIcon, QCursor, QMouseEvent, QPixmap
from PyQt5.QtOpenGL i... | null | gui/Gui2.py | Gui2.py | py | 10,032 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "PyQt5.QtWidgets.QMainWindow",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "PyQt5.QtGui.QIcon",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets.QWidget",
"line_number": 43,
"usage_type": "name"
},
{
"api_name": ... |
134170742 | __author__ = 'Fabian'
import zipfile
class ModFile():
def __init__(self, path):
self.path = path
def check(self):
try:
zip = zipfile.ZipFile(self.path)
zip.testzip()
files = zip.namelist()
info = False
for file in files:
... | null | FactorioManager/ModFile.py | ModFile.py | py | 668 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "zipfile.ZipFile",
"line_number": 10,
"usage_type": "call"
}
] |
484568761 | # По данной непустой строке s длины не более 104, состоящей из строчных букв латинского алфавита,
# постройте оптимальный беспрефиксный код. В первой строке выведите количество различных букв k,
# встречающихся в строке, и размер получившейся закодированной строки.
# В следующих k строках запишите коды букв в формате "... | null | Greedy_algorithms/Huffman/Huffman_1.py | Huffman_1.py | py | 4,139 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "collections.Counter",
"line_number": 93,
"usage_type": "call"
}
] |
354119698 | __author__ = 'iacopo'
from flask import request
from flask.ext.restful import Resource
from flask.ext.restful import marshal_with
from flask.ext.restful import reqparse
from sqlalchemy.exc import IntegrityError
from sqlalchemy.orm.exc import NoResultFound
from dao.ide_usage import IdeUsage
from dao.discipline_member ... | null | src/api/resources.py | resources.py | py | 2,197 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "flask.ext.restful.Resource",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "flask.ext.restful.reqparse.RequestParser",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "flask.ext.restful.reqparse",
"line_number": 21,
"usage_type": "name"
... |
452718791 | import ast
import os
import json
import binascii
import astor
class ConstantParam(object):
def __init__(self, node):
self.node = node
def get_name(self):
for target in self.node.targets:
if isinstance(target, ast.Name):
return target.id
def set_value(self, val... | null | docker/comagic-web/configure/configurator.py | configurator.py | py | 5,869 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "ast.Name",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "ast.Dict",
"line_number": 26,
"usage_type": "attribute"
},
{
"api_name": "ast.Str",
"line_number": 35,
"usage_type": "attribute"
},
{
"api_name": "ast.Str",
"line_number":... |
188294844 | import argparse
import collections
import logging
import os
from utils.misc import intervals_genomic_sort_order, parse_interval
logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s')
def parse_args():
p = argparse.ArgumentParser(description="Combine repeat regions .bed files")
... | null | docker/base-scripts/simulate/combine_repeat_regions_bed_files.py | combine_repeat_regions_bed_files.py | py | 3,329 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.basicConfig",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.path.b... |
363378016 | import json
import requests
__author__ = 'Kozo Nishida'
__email__ = 'knishida@riken.jp'
__version__ = '0.0.1'
__license__ = 'MIT'
def escher2cyelements(escher_json_url):
r = requests.get(escher_json_url)
data = json.loads(r.content)
escher_nodes = data[1]['nodes']
# escher_edges =
cyelements = {}
... | null | escher2cyjs.py | escher2cyjs.py | py | 1,225 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "requests.get",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 44,
"usage_type": "call"
}
] |
327286289 | # import modules
import os
import requests
import telegram
import time
from datetime import datetime
from wallets_dict import wallets
from config import limit, transactions, contract, looptime, my_token, filename, api_key
def get_OPQ_prices():
request_ETH = requests.get(
'https://api.kucoin.com/v1/open/ti... | null | signals_blockchain.py | signals_blockchain.py | py | 6,463 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "requests.get",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_numbe... |
470860205 | import numpy as np
import json
def read_layer(data, json_index) -> np.ndarray:
size_in = int(data[json_index]['size_in'])
size_out = int(data[json_index]['size_out'])
weights = data[json_index]['weights']
matrix = np.zeros([size_in, size_out])
for x in data[json_index]['weights']:
for y in ... | null | neural_network.py | neural_network.py | py | 1,285 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "numpy.zeros",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.ndarray",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "json.load",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numpy.dot",
"line_number":... |
319870563 | from typing import Generator
import requests
from bs4 import BeautifulSoup
def get_category_link(category_name: str)-> str:
page = requests.get('http://books.toscrape.com/')
soup = BeautifulSoup(page.content, 'html.parser')
for link in soup.find_all('a'):
if category_name == link.text.strip():
... | null | main.py | main.py | py | 1,469 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "requests.get",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"li... |
650050928 | from uuid import uuid4
import tornado
from .board import Board
class PlayerValueError(ValueError):
pass
class MoveValueError(ValueError):
pass
class Game:
MAX_PLAYERS = 2
STATE_MATCHMAKING = 'matchmaking'
STATE_IN_PROGRESS = 'in_progress'
STATE_FINISHED = 'finished'
def __init__(sel... | null | solution/api/tictactoe/engine/game.py | game.py | py | 1,741 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "uuid.uuid4",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "board.Board",
"line_number": 26,
"usage_type": "call"
}
] |
303921844 | from flask import Blueprint ,render_template,request
from flask_login import login_required, current_user
from .models import Upload
views = Blueprint('views', __name__)
@views.route('/', methods=['GET', 'POST'])
@login_required
def home():
if request.method == 'POST':
note = request.form.get(... | null | Flask web app/Website/views.py | views.py | py | 711 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "flask.Blueprint",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "flask.request.method",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "flask.request",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "flask.request.... |
83528832 | from django.shortcuts import render
from django.http import HttpResponseRedirect, HttpResponseBadRequest, HttpResponse
from django.urls import reverse
from .models import Squawk
# Create your views here.
def index(request):
if(request.method == 'POST'):
post_text = request.POST['post_text']
if(l... | null | squawkerApp/views.py | views.py | py | 678 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.http.HttpResponseBadRequest",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "models.Squawk",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "django.http.HttpResponseRedirect",
"line_number": 18,
"usage_type": "call"
},
{
... |
94270874 | import json
import sys
import os
from collections import OrderedDict
right_answers_path = sys.argv[1]
right_answers = os.path.join(right_answers_path, 'right_answers.json')
# right_answers = os.path.join(right_answers_path, 'overcome.json')
print("found right answers:", right_answers)
with open("/data2/ymeng/dolphin1... | null | scripts/auto_correct.py | auto_correct.py | py | 819 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sys.argv",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "json.load",
"line_number": 1... |
565764513 | import traceback, logging
import json
from web.conf.return_conf import *
from web.lib.request_api import Request_api
from django.http import HttpResponse, HttpResponseServerError
class insert_new_bok_report():
logger = logging.getLogger('web')
logger_access = logging.getLogger('access')
def __init__(self, reque... | null | web/htdocs/ajax/insert_new_bok_report.py | insert_new_bok_report.py | py | 2,793 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.getLogger",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "web.lib.request_api.Request_api",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "dj... |
101717945 | author = 'Simon Kohl, Paul Jaeger, June 2017'
from abc import abstractmethod
from collections import OrderedDict
from copy import deepcopy
import lasagne
import cPickle
from lasagne.layers import get_output, get_all_params, get_all_layers
from lasagne.objectives import categorical_crossentropy
from lasagne.updates imp... | null | DeepTrainerUtils/AbstractClassificationNet.py | AbstractClassificationNet.py | py | 6,081 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "abc.abstractmethod",
"line_number": 31,
"usage_type": "name"
},
{
"api_name": "collections.OrderedDict",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "theano.tensor.tensor4",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "thea... |
129461879 | #!/usr/bin/env python3
# -*- coding:utf-8 -*-
u"""
Created by ygidtu@gmail.com at 2018.11.25
Collect input fq.gz files, and assign SE PE output prefix to it
"""
import configparser as cp
import glob
import json
import os
import re
from itertools import chain
def __check_directory__(in_dir):
U"""
check whethe... | null | src/collect_fq.py | collect_fq.py | py | 5,305 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.path.exists",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "os.makedirs",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_n... |
355204796 | from meta_mb.utils.networks.mlp import create_rnn
from meta_mb.policies.distributions.discrete import Discrete
from meta_mb.policies.base import Policy
from meta_mb.utils import Serializable
from meta_mb.utils.utils import remove_scope_from_name
from meta_mb.logger import logger
import tensorflow as tf
import tensorfl... | null | meta-mb-internal/meta_mb/policies/discrete_rnn_with_cnn.py | discrete_rnn_with_cnn.py | py | 15,835 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "meta_mb.policies.base.Policy",
"line_number": 35,
"usage_type": "name"
},
{
"api_name": "meta_mb.utils.Serializable.quick_init",
"line_number": 56,
"usage_type": "call"
},
{
"api_name": "meta_mb.utils.Serializable",
"line_number": 56,
"usage_type": "name"
... |
480225370 |
from reportlab.platypus import Paragraph, Table, TableStyle
from reportlab.lib.units import inch
from reportlab.lib import colors
from PDFAttachment import PDFAttachment
from taa.services.docusign.service import BasePDFDoc
from utils import style, bold_style2, NumberedCanvas, create_attachment_header
class Addition... | null | taa/services/docusign/documents/additional_replacement_policies.py | additional_replacement_policies.py | py | 4,001 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "PDFAttachment.PDFAttachment",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "taa.services.docusign.service.BasePDFDoc.__init__",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "taa.services.docusign.service.BasePDFDoc",
"line_number": 13,
... |
258495896 | import networkx as nx
from math import cos, sin, pi
from algorithms import a_start, dijkstra
def get_attr_val(G, node, attribute):
if node in G.nodes:
return G.nodes[node][attribute]
def remove_node_util(G, node):
if node in G.nodes:
G.remove_node(node)
def add_node_util(G, node):
if... | null | functions.py | functions.py | py | 1,448 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "math.cos",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "math.pi",
"line_number": 40,
"usage_type": "name"
},
{
"api_name": "math.sin",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "math.sin",
"line_number": 41,
"usag... |
543228044 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import logging
import os
import re
from collections import OrderedDict, defaultdict
from datetime import datetime
from pprint import pprint
import tqdm
import yaml
from geopy.extra.rate_limiter import RateLimiter
from geopy.geocoders import Nominatim
from ranking.managem... | null | ranking/management/modules/neerc_ifmo_school.py | neerc_ifmo_school.py | py | 9,728 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.getLogger",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "ranking.management.modules.common.BaseModule",
"line_number": 22,
"usage_type": "name"
},
{
"... |
639771259 | #!/usr/bin/python3
# -*- coding: utf-8 -*-
""" configuration module for gstatic: it includes the routines to modify work of application"""
import os
import sys
import tempfile
import datetime
from sgglobals import *
from configparser import ConfigParser
#
#
class CaseConfigParser(ConfigParser):
"""subclassing necessa... | null | sgconf.py | sgconf.py | py | 8,496 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "configparser.ConfigParser",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "os.path.join",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 38,
"usage_type": "attribute"
},
{
"api_name": "os.path.exists",
... |
17204822 | #!/usr/bin/env python
# Traces
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
from opentelemetry.instrumentation.flask import FlaskInstrumentor
from opentelemetry.exporter.jaeger.thrift import JaegerExporter
from opentel... | null | sender/main.py | main.py | py | 2,266 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "opentelemetry.exporter.jaeger.thrift.JaegerExporter",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "opentelemetry.trace.set_tracer_provider",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "opentelemetry.trace",
"line_number": 32,
"usa... |
624234264 | # -*- encoding: utf-8 -*-
import numpy as np
def loadDataSet(fileName):
numFeat = len(open(fileName).readline().split('\t')) - 1
dataMat = []
labelMat = []
fr = open(fileName)
for line in fr.readlines():
lineArr = []
curLine = line.strip().split('\t')
for i in range(numFeat... | null | 02.机器学习实战/08.线性回归/codes/regression.py | regression.py | py | 8,930 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "numpy.mat",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "numpy.mat",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "numpy.linalg.det",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "numpy.linalg",
"line_number"... |
636424397 | from music21 import *
import numpy as np
import os
import torch
import time
import random
from torch import nn
from torch import optim
import torch.utils.data as Data
from torch.autograd import Variable
from imblearn.over_sampling import RandomOverSampler
device = torch.device("cuda:0" if torch.cuda.is_available() el... | null | generation_frommodel.py | generation_frommodel.py | py | 4,990 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "torch.device",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "torch.nn.Module"... |
547981540 | '''
Maria Cioffi, Cole Conte, Andrew Kirna
httpserver.py
Last Edited: Mon Nov 30 2015
Revised from a sample Python Server from Xiannong Meng,
which was in turn revised from the code segments:
http://stackoverflow.com/questions/23264569/python-3-x-basehttpserver-or-http-server
and
https://wiki.python.org/moin/BaseHttpSe... | null | httpserver.py | httpserver.py | py | 5,928 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "http.server.BaseHTTPRequestHandler",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "os.getcwd",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "os.open",... |
200321826 | # -*- coding: cp932 -*-
import time
import sys
from sys import platform as _platform
from datetime import datetime, date, timedelta
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.common.by import By
from sele... | null | tc_common.py | tc_common.py | py | 11,328 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.INFO",
"line_number": 31,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "logging.Formatter",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "selenium.webdri... |
337975908 | # -*- coding:utf-8 -*-
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import create_engine
from bottle.ext import sqlalchemy as bs
Model = declarative_base()
plugin = None
create_session = None
def init(app):
global plugin, create_session
eng... | null | wa/database.py | database.py | py | 597 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sqlalchemy.ext.declarative.declarative_base",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.create_engine",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.orm.sessionmaker",
"line_number": 17,
"usage_type": "call"... |
138503523 | # The MIT License (MIT)
#
# Copyright (c) 2015 Philippe Proulx <eepp.ca>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to us... | null | lttngc/model.py | model.py | py | 6,808 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "enum.Enum",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "enum.unique",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "enum.Enum",
"line_number": 37,
"usage_type": "attribute"
},
{
"api_name": "enum.unique",
"lin... |
308943387 | # 给你一个整数数组 coins 表示不同面额的硬币，另给一个整数 amount 表示总金额。
#
# 请你计算并返回可以凑成总金额的硬币组合数。如果任何硬币组合都无法凑出总金额，返回 0 。
#
# 假设每一种面额的硬币有无限个。
#
# 题目数据保证结果符合 32 位带符号整数。
#
#
#
#
#
#
# 示例 1：
#
#
# 输入：amount = 5, coins = [1, 2, 5]
# 输出：4
# 解释：有四种方式可以凑成总金额：
# 5=5
# 5=2+2+1
# 5=2+1+1+1
# 5=1+1+1+1+1
#
#
# 示例 2：
#
#
#... | null | [518]零钱兑换 II.py | [518]零钱兑换 II.py | py | 1,900 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "typing.List",
"line_number": 56,
"usage_type": "name"
}
] |
149618261 | from django.conf.urls import url
from django.contrib.auth.decorators import login_required
from django.views.generic.edit import UpdateView, DeleteView
from django.views.generic import DetailView
from .models import Photo, Album
from .views import PHOTO_FORM_FIELDS, ALBUM_FORM_FIELDS
from .views import PhotoCreate, Al... | null | imager_images/urls.py | urls.py | py | 2,329 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.conf.urls.url",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "django.contrib.auth.decorators.login_required",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "views.LibraryView.as_view",
"line_number": 13,
"usage_type": "call"
... |
415607032 | # -*- coding: utf-8 -*-
# 3rd party library
try:
from urllib.parse import urljoin
from urllib.parse import urlencode
import urllib.request as urlrequest
except ImportError:
from urlparse import urljoin
from urllib import urlencode
import urllib2 as urlrequest
import json
import time
class Sl... | null | slackweb/slackweb.py | slackweb.py | py | 1,511 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "urllib2.build_opener",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "urllib2.HTTPHandler",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "urllib.urlencode"... |
498041910 | try:
import argparse
except ImportError:
print("Please check if module 'argparse' is installed")
quit()
parser = argparse.ArgumentParser()
parser.add_argument('--tab', type=argparse.FileType('r'), required=True)
parser.add_argument('--out', type=str)
args = parser.parse_args()
def table_parsi... | null | NeuroPep_fasta_prep.py | NeuroPep_fasta_prep.py | py | 1,403 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "argparse.FileType",
"line_number": 8,
"usage_type": "call"
}
] |
29144765 | import pysam
import pandas as pd
import os
def depth_combine(samples, bed, batch_out, name_list):
bed_df = pd.read_csv(bed, header = None, sep = '\t')
try:
df = pd.DataFrame({'chr': bed_df[0],
'start': bed_df[1],
'end': bed_df[2],
... | null | src/depth.py | depth.py | py | 1,221 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_csv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
... |
126000740 | from bottomup_cluster import *
import matplotlib.pyplot as plt
X = np.loadtxt("s1.txt")
c = AggloClustering(X[0:5000, :])
clusters = c.cluster(15, linkage="average")
LABEL_COLOR_MAP = ['b','g','r','c','m','y','k']
[plt.scatter(cluster[:, 0], cluster[:, 1], c=LABEL_COLOR_MAP[i], marker='+') for i, cluster in enumerate... | null | bottom up clustering/main.py | main.py | py | 1,223 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "matplotlib.pyplot.scatter",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.scatter",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "m... |
93056293 | import psycopg2
import pandas as pd
host = 'localhost'
dbname = 'audioforma'
user = 'postgres'
conn = psycopg2.connect(f"host={host} dbname={dbname} user={user}")
cur = conn.cursor()
songs = pd.read_csv('songs.csv').iterrows()
for idx, s in songs:
cur.execute(
'''
INSERT INTO song
(song_t... | null | static/data/import_csv.py | import_csv.py | py | 562 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "psycopg2.connect",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 11,
"usage_type": "call"
}
] |
645709859 | import pyupbit
import numpy as np
import time
from datetime import datetime
import pandas as pd
start_time = datetime.now()
tickers = pyupbit.get_tickers(fiat="KRW")
start_day = datetime(2021,8,10)
today = datetime.now()
days = days = (today-start_day).days
################################################ Function ... | null | Backtest_bol.py | Backtest_bol.py | py | 3,736 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "datetime.datetime.now",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "pyupbit.get_tickers",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "datetime.dat... |
196233136 | from bs4 import BeautifulSoup
import requests as req
class NetworkClass(object):
def __init__(self):
pass
def get_correct_url(self, url, source):
if url[0] == "/" and source[len(source)-1] != "/" or url[0] != "/" and source[len(source) - 1] == "/":
return source + url
elif ... | null | app/NetworkClass.py | NetworkClass.py | py | 1,339 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "requests.get",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 34,
"usage_type": "call"
}
] |
622119111 | import logging
import time
import requests
from urllib.parse import urlencode
class RequestManager(object):
"""Manager of external requests."""
def __init__(
self, request_timeout=30, max_retries=5, retry_interval=0, log=None
):
"""
Instance configuration.
Args:
... | null | feed_test_api/utils/request.py | request.py | py | 3,491 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.getLogger",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 60,
"usage_type": "attribute"
},
{
"api_name": "requests.post",
"line_number": 62,
"usage_type": "attribute"
},
{
"api_name": "requests.put",... |
375025873 | import os
from flask import Flask
def create_app(test_config=None):
# create and configure the app
app = Flask(__name__, instance_relative_config=True)
app.config.from_mapping(
SECRET_KEY='dev',
)
if test_config is None:
# load the instance config, if it exists, when not testing
... | null | awesome_site/__init__.py | __init__.py | py | 880 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "flask.Flask",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.makedirs",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 30,
... |
471122063 | import pyglet
from random import random
class Stars:
def __init__(self):
self.stars = []
for i in range(200):
z = random()
self.stars.append([int(random()*self.window.width*z), int(random()*self.window.height*z), z])
def drawstars(self):
starbatch =... | null | stars.py | stars.py | py | 754 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "random.random",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "random.random",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pyglet.graphics.Batch",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pyglet.graphics",
... |
482071496 | __author__ = 'liuwei'
from gensim.models import Word2Vec
import logging
from Common import Common
from nltk.corpus import stopwords
import nltk.data
import numpy as np
import os
class Word_2_Vec(object):
'''word to vec, to get the distuibuted representation of the word'''
def __init__(self, train, test, unla... | null | Word_2_Vec.py | Word_2_Vec.py | py | 2,649 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.path.exists",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "gensim.models.Word2Vec.load",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "gensim.models... |
356676373 | import pandas as pd
import pandasql
# 默认读取第一个表单，直接默认读取到这个Excel的第一个表单
df = pd.read_excel('D:\\TAL\\考勤自动化\\2019年秋季教师请假汇总-更新2019.10.27-赵哲面授.xlsx', sheet_name='面授10.27')
df.columns = [
'a1',
'classid',
'a3',
'a4',
'a5',
'teacherid',
'teacher',
'学期',
'年部',
'年级',
'年份',
'学科',
... | null | tal/excel/postpone.py | postpone.py | py | 1,822 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_excel",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pandasql.sqldf",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "openpyxl.load_workbook",
"line_number": 56,
"usage_type": "call"
}
] |
175840373 | # -*- coding: utf-8 -*-
"""
Created on Sat Apr 4 15:49:50 2020
@author: pietertpt
"""
import RPi.GPIO as GPIO
import os
from time import sleep
from http.server import BaseHTTPRequestHandler, HTTPServer
host_name = '192.168.2.200' # Change this to your Raspberry Pi IP address
host_port = 8000
class MyServer(BaseHT... | null | simple_webserver2.py | simple_webserver2.py | py | 4,888 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "http.server.BaseHTTPRequestHandler",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "RPi.GPIO.setmode",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "RPi.GPIO",
"line_number": 35,
"usage_type": "name"
},
{
"api_name": "RPi.GPIO... |
116507634 | # -*- coding: utf-8 -*-
#
# Copyright (C) 2006-2009 Edgewall Software
# All rights reserved.
#
# This software is licensed as described in the file COPYING, which
# you should have received as part of this distribution. The terms
# are also available at http://genshi.edgewall.org/wiki/License.
#
# This software consist... | null | genshi/template/directives.py | directives.py | py | 27,622 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "genshi.template.eval.Expression",
"line_number": 110,
"usage_type": "call"
},
{
"api_name": "genshi.template.base.TemplateSyntaxError",
"line_number": 115,
"usage_type": "call"
},
{
"api_name": "six.add_metaclass",
"line_number": 39,
"usage_type": "call"
... |
470548402 | import os, fnmatch
import netCDF4 as nc
import numpy as np
from time import time
from scDataset import scDataset
#from IPython import embed
def gethourlyfiles(prefix, days, grid):
files = []
for day in days:
dirname = os.path.join(prefix, day)
for item in os.listdir(dirname):
if fn... | null | scDataset/test_scDataset.py | test_scDataset.py | py | 3,401 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.path.join",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "os.listdir",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "fnmatch.fnmatchcase",
"line_... |
57896764 | from copy import copy
from django.core.exceptions import ImproperlyConfigured
from django.forms import ModelForm, ModelChoiceField, ModelMultipleChoiceField
from types import StringTypes
from django.db.models import Model
from .bundle import Bundle
def model_to_dict(bundle, resource):
data = {}
for name, fie... | null | tastypie/validation.py | validation.py | py | 3,958 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "bundle.Bundle",
"line_number": 16,
"usage_type": "argument"
},
{
"api_name": "django.core.exceptions.ImproperlyConfigured",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "django.db.models.Model",
"line_number": 65,
"usage_type": "argument"
},
... |
521559504 | from __future__ import print_function, division
import warnings
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import get_backend
from matplotlib.widgets import Slider
__all__ = ["echelle", "plot_echelle", "interact_echelle"]
def echelle(freq, power, dnu, offset=0.0):
if len(freq) != len(p... | null | echelle/echelle.py | echelle.py | py | 5,047 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "numpy.intersect1d",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "numpy.where",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "numpy.median",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_n... |
516345078 | #!/usr/bin/python3
"""Places file
"""
from api.v1.views import app_views
from flask import jsonify, abort, request
from models import storage
from models.state import State
from models.city import City
from models.place import Place
@app_views.route("/cities/<city_id>/places", methods=['GET', 'POST'])
def places(city... | null | api/v1/views/places.py | places.py | py | 2,210 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "models.storage.get",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "models.storage",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "flask.abort",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "flask.request.method",
... |
650962179 | import torch
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader, Sampler
import numpy as np
import random
from typing import Sized, Iterator, List
class Experience:
def __init__(self, dvae):
self.dvae = dvae
self.frames = []
self.encoded_frames = []
self.rewar... | null | utils/experience.py | experience.py | py | 4,624 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "torch.tensor",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "torch.tensor",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "numpy.stack",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "torch.stack",
"line_number"... |
274409183 | import pygame
from paddle import Paddle
from ball import Ball
from random import randint
pygame.init()
black = (0, 0, 0)
white = (255, 255, 255)
screen = pygame.display.set_mode((600, 400))
pygame.display.set_caption("Pong")
leftPoints = 0
rightPoints = 0
scoredict = {
0: 'zero.png',
1: 'one.png',
2: '... | null | wontrun.py | wontrun.py | py | 5,196 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pygame.init",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pygame.display.set_mode",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pygame.display",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "pygame.display... |
609332472 | from tqdm import tqdm
countries_set = set()
for line in open('./chapter09/country.txt', 'r').readlines():
if len(line) > 2:
countries_set.add(line.strip())
with open('./chapter09/corpus81.txt', 'w') as f:
for line in tqdm(open('./chapter09/corpus.txt', 'r')):
for country in countries_set:
... | null | wanghongfei/chapter09/knock81.py | knock81.py | py | 405 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "tqdm.tqdm",
"line_number": 9,
"usage_type": "call"
}
] |
120749197 | import pdb
import pyfits
import numpy as np
import matplotlib.cm as cmp
import matplotlib.pyplot as py
from matplotlib import rc
from astropysics.spec import *
from coaddSpectra import sigclip_coadd
rc('text', usetex = True)
rc('font', family = 'serif')
rc('font', size = 20)
hdu = pyfits.open('/Users/khamren/M31_Re... | null | Plots/Coadds/mstar_ladder.py | mstar_ladder.py | py | 1,928 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "matplotlib.rc",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matplotlib.rc",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "matplotlib.rc",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pyfits.open",
"line_num... |
437272340 | from ctypes import cdll, Structure, POINTER, c_char_p, c_void_p, c_uint, c_bool, c_ulong, c_int
from clang import CXUnsavedFile, CXCompletionChunkKind, CXCursorKind
from sys import platform as _platform
import os
import re
# It's not who I am underneath,
# but what I do that defines me.
class Batman():
def __init__(... | null | cc.py | cc.py | py | 13,589 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "clang.CXCursorKind.FIELD_DECL",
"line_number": 29,
"usage_type": "attribute"
},
{
"api_name": "clang.CXCursorKind",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "clang.CXCursorKind.FUNCTION_TEMPLATE",
"line_number": 31,
"usage_type": "attribute"... |
130523726 | import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.ticker as mticker
import mpl_finance
import pandas as pd
import matplotlib.dates as mdates
import os
def plot_indicators(filename = '', coin = ''):
if not filename:
dataset = pd.read_csv('data\minute\price_surge_YOYOBNB.csv... | null | breakout_finder/plot.py | plot.py | py | 3,531 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_csv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "matplotlib.p... |
425399776 | # TensorFlow and tf.keras
import tensorflow as tf
from tensorflow import keras
# Helper libraries
import numpy as np
import matplotlib.pyplot as plt
print(tf.__version__)
# Import MNIST Dataset
fashion_mnist = tf.keras.datasets.fashion_mnist
(train_images, train_labels), (test_images, test_labels) = fashion_mnist.l... | null | src/test_model.py | test_model.py | py | 2,468 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "tensorflow.__version__",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.keras",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 28,
"usage_type": "call"
},
{
"api_nam... |
2070584 | """ Openface classification """
import cv2
import numpy as np
np.set_printoptions(precision=2)
import pandas as pd
from models.model_openface import aligndlib2 as aligndlib
import os
import random
import shutil
import openface
import openface.helper
from openface.data import iterImgs
import argparse
from subprocess im... | null | models/model_openface/model_classify.py | model_classify.py | py | 9,037 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "numpy.set_printoptions",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "warnings.filterwarnings",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "os.path... |
643171623 | import os
import torch, torchvision
import urllib.request
import numpy as np
import pandas as pd
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import Dataset
import matplotlib.pyplot as plt
def download_images():
""" Download players' face images. """
#... | null | utils.py | utils.py | py | 2,376 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_csv",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "urllib.request.request.URLopener",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "urllib.request.request",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_... |
542381356 | from app.main import main
from app import db
from flask import render_template, flash, redirect, url_for, request, current_app, g, jsonify
from flask_login import login_user, logout_user, current_user, login_required
from .forms import LoginForm, RegistrationForm, EditProfileForm, PostForm, SearchForm, MessageForm
from... | null | app/main/views.py | views.py | py | 11,349 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "flask_login.current_user.is_authenticated",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "flask_login.current_user",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "flask_login.current_user.last_seen",
"line_number": 14,
"usage_ty... |
187989106 | import os
from collections import Counter
import importlib,sys
import numpy as np
base_dir = 'DATA'
train_dir = os.path.join(base_dir, 'traindata.txt')#训练集
test_dir = os.path.join(base_dir, 'testdata.txt')#测试集
val_dir = os.path.join(base_dir, 'devdata.txt')#验证集
vocab_dir = os.path.join(base_dir, 'vocab.txt')#词汇表
stopw... | null | Dataload.py | Dataload.py | py | 4,723 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.path.join",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 8,
... |
57638771 | import os
import pandas as pd
from src.preprocess import PreprocessData
from sklearn import model_selection
TRAIN = os.environ.get("TRAINING_DATA")
TEST = os.environ.get("TEST_DATA")
df_train = pd.read_csv(TRAIN)
df_test = pd.read_csv(TEST)
preprocessor = PreprocessData(model = "xgboost",
... | null | tabulardata/src/load_data.py | load_data.py | py | 867 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.environ.get",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "os.environ.get",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_num... |
218821346 | """
Module for all related to registries endpoint.
"""
from __future__ import absolute_import
import logging
from flask import Blueprint
from flask_restplus import Resource
from flask_restplus import Api
import pyba.library as lib
REGISTRIES = Blueprint('registries', __name__)
API = Api(REGISTRIES)
@API.route("/r... | null | pyba/blueprints/registries.py | registries.py | py | 1,273 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "flask.Blueprint",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "flask_restplus.Api",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "flask_restplus.Resource",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "pyba.libra... |
452173791 | import pandas as pd
import numpy as np
from collections import defaultdict
def load_user_data():
user_dataset = pd.read_csv("u.data",sep = "\t",header=None)
user_dataset.columns = ["UserID","MovieID","Rating","Datetime"]
user_dataset["Datetime"] = pd.to_datetime(user_dataset["Datetime"])
print("user_da... | null | apriori/main.py | main.py | py | 1,828 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_csv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pandas.to_datetime",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "collections.defaultdict",
"line_number": 33,
"usage_type": "call"
}
] |
510251273 | """
Module for holding and exporting file metadata as JSON documents.
"""
from __future__ import division
import hashlib
import json
import logging
import math
from pyhull.convex_hull import qconvex
class Properties(object):
"""
A class to hold, manipulate, and export geospatial metadata at file level.
"... | null | python/src/ceda_di/metadata/product.py | product.py | py | 8,303 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.getLogger",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "hashlib.sha1",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "pyhull.convex_hull.qconvex",
"line_number": 115,
"usage_type": "call"
},
{
"api_name": "math.ceil"... |
80864909 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.autograd as autograd
class Decoder(nn.Module):
def __init__(self, vocab_size, hidden_dim, embed_dim, output_dim, n_layers=1):
super(Decoder, self).__init__()
self.n_layers = n_layers
self.hidden_dim = hidden_d... | null | decoder.py | decoder.py | py | 1,019 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "torch.nn.Module",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "torch.nn.Embedding",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_n... |
389519822 | import datetime
import json
import requests
def main():
file = open('/Users/lyj/Downloads/coinget_pk', 'w')
size = 0
for i in range(1, 10000):
r = requests.get(
'https://coinget.vip/api/index/listNewDrawnPeriod?pageNo=' + str(i) + '&pageSize=99&zoneList=3')
resJson = json.loa... | null | script/spider.py | spider.py | py | 1,122 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "requests.get",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.utcfromtimestamp",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "datetime.d... |
369902371 | from django.http import Http404
from django.shortcuts import get_object_or_404
from dataworkspace.apps.datasets.models import DataSet
from dataworkspace.apps.datasets.constants import DataSetType
def find_dataset(dataset_uuid, user):
dataset = get_object_or_404(DataSet.objects.live(), id=dataset_uuid)
if us... | null | dataworkspace/dataworkspace/apps/datasets/utils.py | utils.py | py | 917 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.shortcuts.get_object_or_404",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "dataworkspace.apps.datasets.models.DataSet.objects.live",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "dataworkspace.apps.datasets.models.DataSet.objects",
... |
379153695 |
#Bayesian Neural Network
import numpy as np
import numpy.random as npr
import tensorflow as tf
import random
import math
from os.path import expanduser
home = expanduser("~")
import time
import pickle
from utils import log_normal3
class BNN(object):
def __init__(self, network_architecture, act_func, batch_s... | null | BVAE/BVAE_3jul2017/BNN.py | BNN.py | py | 4,624 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.path.expanduser",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "tensorflow.Variable",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "tensorflow.random_normal",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "tenso... |
49506620 | #!/usr/bin/python
import requests
from PIL import Image
import sys
from datetime import datetime
import CredentialManager
#######################################################################
# Written by Ryan D'souza
#
# Takes a link, calls PDFLayer's API to get a PDF representation
# Of the text at that link
#
... | null | Python/TextPDF.py | TextPDF.py | py | 2,133 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "CredentialManager.get_value",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "CredentialManager.get_value",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 35,
"usage_type": "attribute"
},
{
"api_name": ... |
174619031 | from datetime import datetime
import pymysql.cursors
class cal:
"""Đây là class tính phí"""
total = ""
def __init__(self,con,dnhan,dtra,idkm,idlphong,idti):
self.con = con
self.dnhan = dnhan
self.dtra = dtra
self.idkm = idkm
self.idlphong = idlphong
self.idti... | null | assitant/calucate.py | calucate.py | py | 1,840 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "datetime.datetime.strptime",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "datetime.datetime.strptime",
"line_number": 18,
"usage_type": "call"
},
{
"api_name"... |
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