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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
31890262213 | __author__ = 'Advik-B' # advik.b@gmail.com
import os
import sys
from fnmatch import fnmatch
# Third party modules
from send2trash import send2trash as delete
from termcolor import cprint
DEL = False
try:
cwd = sys.argv[1]
except IndexError:
cwd = os.getcwd()
if_allowed_files = os.path.isfile(os.path.join(cw... | Advik-B/GitHub-Utils | cleanup.py | cleanup.py | py | 2,264 | python | en | code | 3 | github-code | 1 | [
{
"api_name": "sys.argv",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "os.getcwd",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 1... |
39996367304 | import numpy as np
import pandas as pd
from sklearn.svm import LinearSVC
from sklearn.feature_extraction.text import TfidfTransformer, CountVectorizer
from sklearn.pipeline import Pipeline
from sklearn.model_selection import GridSearchCV
train_labels = pd.read_csv('../resources/train_labels.csv', names=['label'], head... | mokleit/text-classification-scikit | src/main/svm/find_best_svm_estimator.py | find_best_svm_estimator.py | py | 1,137 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sklearn.pipeline.Pipeli... |
16706436069 | import argparse
import ConfigParser
import cStringIO
import gzip
import logging
import json
import os
import sys
import traceback
import urllib
from boto.s3.connection import S3Connection
from boto.s3.key import Key
def _init_config():
conf_parser = argparse.ArgumentParser(
description="Downloads a file from a ... | zacharyozer/curlitos | curlitos.py | curlitos.py | py | 4,486 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "ConfigParser.SafeConfigParser",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": ... |
27496332734 |
import re
import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
if __name__ == "__main__":
test_string = "+375 (29) 299-00-00"
match = re.search(r"^\+\d{1,3}\s\(\d{2}\)\s\d{3}\-\d{2}\-\d{2}$", test_string)
if match:
logger.info(f"Found {match.group()}")
... | akinfina-ulyana/lesson | lesson_10/classwork_01.py | classwork_01.py | py | 369 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "logging.basicConfig",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "re.search",
... |
71571428834 | import heapq
import sys
from typing import (
Generic,
Iterable,
Iterator,
List,
NamedTuple,
Optional,
Set,
Tuple,
TypeVar,
)
from termcolor import cprint
from aoc.utils import Coord2D, Grid
H = TypeVar(
"H",
# technically can be anything comparible but obviously python's t... | Lexicality/advent-of-code | src/aoc/y2021/day15.py | day15.py | py | 4,908 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "typing.TypeVar",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "typing.TypeVar",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "typing.Generic",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_... |
36427808018 | from win32com.client import Dispatch
from tkinter import *
import tkinter as tk
from PIL import Image
from PIL import ImageTk
import os
import re
import random
from threading import Thread
import pythoncom
import time
stu_path = "名单.txt" # 学生名单路径
def speaker(str):
"""
语音播报
:param str: 需要播放语音的文字
"""
... | huangguifeng/callroll | rollcall.py | rollcall.py | py | 5,577 | python | zh | code | 1 | github-code | 1 | [
{
"api_name": "win32com.client.Dispatch",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "PIL.Image.open",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 34,
"usage_type": "name"
},
{
"api_name": "PIL.ImageTk.PhotoIm... |
22824109486 | r'''
Module with all structures for defining rings with operators.
Let `\sigma: R \rightarrow R` be an additive homomorphism, i.e., for all elements `r,s \in R`,
the map satisfies `\sigma(r+s) = \sigma(r) + \sigma(s)`. We define the *ring* `R` *with operator*
`\sigma` as the pair `(R, \sigma)`.
S... | Antonio-JP/dalgebra | dalgebra/ring_w_operator.py | ring_w_operator.py | py | 54,589 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "sage.categories.all.Rings.__classcall__",
"line_number": 155,
"usage_type": "call"
},
{
"api_name": "sage.categories.all.Rings",
"line_number": 155,
"usage_type": "argument"
},
{
"api_name": "sage.categories.all.CommutativeRings.__classcall__",
"line_number": 1... |
23787043311 | import torch as th
import pandas as pd
import numpy as np
import dgl
from bipartite_graph import BipartiteGraph
#######################
# user-item Subgraph Extraction
#######################
def map_newid(df, col):
old_ids = df[col]
old_id_uniq = old_ids.unique()
id_dict = {old: new for new, old in e... | venzino-han/graph-transfer | dataset.py | dataset.py | py | 7,605 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "numpy.array",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "torch.zeros",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "torch.int32",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "torch.arange",
"line_num... |
8877029762 | """
FILE: kernelregression.py
LAST MODIFIED: 24-12-2015
DESCRIPTION: Module for Gaussian kernel regression
===============================================================================
This file is part of GIAS2. (https://bitbucket.org/jangle/gias2)
This Source Code Form is subject to the terms of the Mozilla Publ... | musculoskeletal/gias2 | src/gias2/learning/kernelregression.py | kernelregression.py | py | 5,059 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numpy.sqrt",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "numpy.pi",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "numpy.exp",
"line_numb... |
72689147554 | #coding: utf-8
__author__ = "Lário dos Santos Diniz"
from django.contrib import admin
from .models import (RPGSystem)
class RPGSystemAdmin(admin.ModelAdmin):
list_display = ['name', 'description', 'site']
search_fields = ['name', 'description', 'site']
admin.site.register(RPGSystem, RPGSystemAdmin) | lariodiniz/minhaMesaRPG | api/admin.py | admin.py | py | 314 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.contrib.admin.ModelAdmin",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "django.contrib.admin.site.register",
"line_number": 14,
"usage_type": "call"
},... |
44370675825 | # Import required libraries
import pandas as pd
from sqlalchemy import create_engine
# Load data from source into a Pandas dataframe
df = pd.read_csv('source_data.csv')
# Perform data transformation and cleaning
df = df.dropna()
df['column_name'] = df['column_name'].str.upper()
# Load data into a SQL database
engine... | Kripadhn/DataIntegration | DI-Alogorithms/Data Integration/DataIntegration.py | DataIntegration.py | py | 906 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.create_engine",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pandas.read_sql_query",
"line_number": 21,
"usage_type": "call"
}
] |
71835741475 | import random
import sys
import numpy
import torch
import pygad
import pygad.torchga
from nn import create_ga, create_network
import math
class Gym:
def __init__(self, w, h, left_ai, right_ai):
self.turn_i = 0
self.w = w
self.h = h
self.left_ai = left_ai
self.right_ai = r... | enchantinggg4/pytorch_experiment | src/mygym.py | mygym.py | py | 9,940 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "random.randint",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 71,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_num... |
38523258836 | import csv
import models
from operator import attrgetter
import statistics
def filter_data(columns, row):
ENERGYSTARScore = row[columns.index('ENERGYSTARScore')]
if ENERGYSTARScore == '':
return False
YearBuilt = row[columns.index('YearBuilt')]
if int(YearBuilt) < 1920:
return False
... | the-non-binary-tree/ada_data_challenge_c15 | utils.py | utils.py | py | 9,974 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "csv.reader",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "models.Building",
"line_number": 70,
"usage_type": "call"
},
{
"api_name": "statistics.median",
"line_number": 144,
"usage_type": "call"
},
{
"api_name": "csv.reader",
"line_... |
3408800450 | import serial
import matplotlib
matplotlib.use('TkAgg') # MUST BE CALLED BEFORE IMPORTING plt
from matplotlib import pyplot as plt
import queue
import threading
import animation
import seaborn as sns
import numpy as np
import time
class ArduinoReader(threading.Thread):
def __init__(self, stop_event, sig, serport):... | saintnever/dualring_py | stream.py | stream.py | py | 2,949 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "matplotlib.use",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "threading.Thread",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "threading.Thread.__init__",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "threadi... |
10913773933 | from flask import Flask, render_template, request
import pandas as pd
import numpy as np
app = Flask(__name__)
# Reading dataset in global scope
df = pd.read_csv("winequalityN.csv")
# This is the home page
@app.route("/")
def home():
return render_template("home.html")
# This is the page where we will load the d... | ayushraina2028/basic-machine | app.py | app.py | py | 18,393 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "flask.render_template",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "flask.request.method"... |
31855918986 | import requests
import re
import random
import time
from bs4 import BeautifulSoup
import bs4
from fake_useragent import UserAgent
ua = UserAgent()
books = []
discounts = []
cookie = {
"bid": "6183e2a207286",
"_gcl_au": "1.1.1678734493.1636033188",
"cid": "kypss95053",
"pd": "B4MPDFMstRRagO9wOXmP3pNPoI... | jeff-901/bookstore | data/crawl.py | crawl.py | py | 6,009 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "fake_useragent.UserAgent",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "requests.get",
... |
42615079781 | import numpy as np
import glob
import sklearn.covariance as Covariance
def get_covariance_object(X, load=True):
if load:
covarianceDict = np.load('./profiles/covarianceDict.npy', allow_pickle=True)[()]
cov_object, mean, std = covarianceDict['cov_object'], covarianceDict['mean'], covarianceDict['std... | scarpma/SSM_segmentation_3DSlicer_module | compute_profiles_covariance.py | compute_profiles_covariance.py | py | 2,053 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "numpy.load",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sklearn.covariance.OAS",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "sklearn.covariance",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "numpy.save",
... |
38979638858 | from django.core.management.base import BaseCommand, CommandError
from django.core.exceptions import FieldDoesNotExist, FieldError
from django.conf import settings
import requests
from dbproducts.models import Category, Product
from dbproducts.related_functions import symbol_removal
class Command(BaseCommand):
"... | guillaumecarru/Pur_Beurre_Website | dbproducts/management/commands/populate_db.py | populate_db.py | py | 5,396 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.core.management.base.BaseCommand",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "django.conf.settings.PROD_CATEGORIES",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "django.conf.settings",
"line_number": 32,
"usage_type":... |
24522787900 | """Copied from cpython to ensure compatibility"""
import io
from typing import Any, Callable, Dict
BUFFER_SIZE = io.DEFAULT_BUFFER_SIZE # Compressed data read chunk size
class BaseStream(io.BufferedIOBase):
"""Mode-checking helper functions."""
def _check_not_closed(self):
if self.closed:
... | synodriver/python-bz3 | bz3/compression.py | compression.py | py | 5,403 | python | en | code | 5 | github-code | 1 | [
{
"api_name": "io.DEFAULT_BUFFER_SIZE",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "io.BufferedIOBase",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "io.UnsupportedOperation",
"line_number": 17,
"usage_type": "call"
},
{
"api_name... |
3262515470 | #!/usr/bin/env python3
import secrets
import sys
import subprocess
import argparse
import headerStruct
def calculateSizeOfTheImage(lastVirtAddr, size, SectAlignment):
mult = int((size-1) / SectAlignment) + 1
return lastVirtAddr + (SectAlignment * mult)
def generateKey(arch):
# init values
wordlength... | idrirap/projectEthHack | packer.py | packer.py | py | 13,046 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "secrets.token_bytes",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "secrets.token_bytes",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "subprocess.run",
"line_number": 67,
"usage_type": "call"
},
{
"api_name": "subprocess.run... |
19681624663 | from PIL import Image, ImageFilter
img = Image.open('./astro.jpg')
# filtered_img = img.filter(ImageFilter.BLUR) # Blurs the image
# filtered_img = img.filter(ImageFilter.SMOOTH) # Smooth the image
# filtered_img = img.filter(ImageFilter.SHARPEN) # Sharpens the image
# filtered_img = img.convert('L') # converts t... | Yeshwanth37/ImageProcessing | Image.py | Image.py | py | 687 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "PIL.Image.open",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 3,
"usage_type": "name"
}
] |
26237350861 | import logging
from datetime import datetime, timedelta
from typing import Dict, Optional
from synthetic.user.profile_data_update import ProfileDataUpdate
from synthetic.utils.time_utils import total_difference_seconds
logger = logging.getLogger(__name__)
class BaseVariableManager:
"""Responsible for managing a... | benshi-ai/open-synthetic-data-generator | src/synthetic/managers/base_manager.py | base_manager.py | py | 2,574 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "typing.Dict",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "datetime.datetime",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "datetime.datetime",
... |
6363891788 | from dataclasses import dataclass, field
from typing import Any, Iterable, List, Dict
from config import SUBJECT_PATTERNS, DAYS
@dataclass(kw_only=True)
class Pattern:
subject_type: str
classes: int
duration: int
required_rooms: List[Any] = field(init=False, default_factory=list)
def add_rooms(se... | oneku16/UCA-schedule-generator | brute_force_2/subject/pattern.py | pattern.py | py | 726 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "typing.List",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "typing.Any",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "dataclasses.field",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "typing.Iterable",
"line_... |
5142368170 | import sklearn
from sklearn.utils import shuffle
from sklearn.neighbors import KNeighborsClassifier
import pandas as pd
import numpy as np
from sklearn import linear_model, preprocessing
data = pd.read_csv("car.data")
print(data.head())
le = preprocessing.LabelEncoder()
buying = le.fit_transform(list(data[... | Laudkyle/my-python-projects | Python Scripts/machine learning 1/knn.py | knn.py | py | 1,408 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.LabelEncoder",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing",
"line_number": 11,
"usage_type": "name"
},
{
"api_name"... |
8362112734 | # ---------------------------
# Problem 2
# Given an array of integers, return a new array such that each element at index i of the new array is the
# product of all the numbers in the original array except the one at i.
#
# For example, if our input was [1, 2, 3, 4, 5], the expected output would be [120, 60, 40, 30, 2... | dmallory42/daily-coding-problem-solutions | problem_002.py | problem_002.py | py | 1,104 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "functools.reduce",
"line_number": 23,
"usage_type": "call"
}
] |
72966759394 | import json
import requests
import sys
import glance_check.exception as exc
class GlanceCheck:
def __init__(self, creds=None, imageid=None, os_image_url=None,
cacert=None, verbose=False):
self.__imageid = imageid
self.__image_url = os_image_url
self.__auth_url = creds['o... | ArdanaCLM/glance-check | glance_check/check.py | check.py | py | 4,530 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sys.stderr.write",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "sys.stderr",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "json.dumps",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line... |
74152867874 | import gym
import time
env = gym.make('CartPole-v0')
env.reset()
for step in range(1000):
env.render() # rendering the environment at each step
env.step(env.action_space.sample()) # feed the env with random actions that exist in all possible actions
time.sleep(0.1)
| Aslanfmh65/open_ai_project | practice.py | practice.py | py | 281 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "gym.make",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 10,
"usage_type": "call"
}
] |
1168928910 | import cv2
import keras
camera = cv2.VideoCapture(0)
haar = cv2.CascadeClassifier('cascades/haarcascade_frontalface_alt2.xml')
model = keras.models.load_model('gender/InceptionResNetV2/weights/inception_gender.h5')
model.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
while True:
... | imdeepmind/age-gender-prediction | detect.py | detect.py | py | 1,388 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "cv2.CascadeClassifier",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "keras.models.load_model",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "keras.mod... |
41131109007 | #Standard
import numpy as np
import cv2
import os
import copy
from PIL import Image, ImageFilter
import time
#Local files
from Utilities import make_directory, align_image, get_from_directory, save_to_directory, numericalSort
from HOG_functions import process_HOG_image, get_HOG_image
import JetsonYolo
#SCIPY and SKl... | ChrisLochhead/PhDSummerProject | PhDSummerProject/Programs/image_processing/ImageProcessor.py | ImageProcessor.py | py | 14,887 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cv2.cvtColor",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_BGR2YCrCb",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "cv2.equalizeHist",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "cv2.cvtColor",... |
25654546309 | import uvicorn
from fastapi import FastAPI, Request, status
from fastapi.openapi.utils import get_openapi
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from fastapi.exceptions import RequestValidationError
from app.v1.routers.facts import v1_router
from config import NA... | DucNgn/Dog-Facts-API-v2 | app/main.py | main.py | py | 1,763 | python | en | code | 6 | github-code | 1 | [
{
"api_name": "app.v1.routers.facts.openapi_schema",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "app.v1.routers.facts",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "app.v1.routers.facts.openapi_schema",
"line_number": 17,
"usage_type": "att... |
33845405230 | #-*- coding: utf-8 -*-
import pyqtgraph as pg
from DateAxis import DateAxis
from TableModel import TableModel
from PyQt4.QtGui import *
from PyQt4 import uic
class LogView(QTableView):
def __init__(self, graphicLayout, layoutRow = 0, layoutCol = 0):
super().__init__()
self.view = graphi... | turlvo/KuKuLogAnalyzer | LogView.py | LogView.py | py | 3,684 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "DateAxis.DateAxis",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pyqtgraph.TextItem",
"line_number": 85,
"usage_type": "call"
},
{
"api_name": "pyqtgraph.ScatterPlotItem",
"line_number": 109,
"usage_type": "call"
},
{
"api_name": "pyqtg... |
7420566826 | from django.contrib.auth import get_user_model
from django.test import TestCase
from posts.models import Group, Post
User = get_user_model()
class TestGroupModel(TestCase):
@classmethod
def setUpTestData(cls):
cls.group = Group.objects.create(
title="Тестовый Заголовок",
slug... | VaSeWS/hw05_final | yatube/posts/tests/test_models.py | test_models.py | py | 2,456 | python | ru | code | 0 | github-code | 1 | [
{
"api_name": "django.contrib.auth.get_user_model",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.test.TestCase",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "posts.models.Group.objects.create",
"line_number": 12,
"usage_type": "call"
},
... |
8803458348 | from typing import Union
import requests as r
from requests_toolbelt.multipart.encoder import MultipartEncoder
class PetFriends:
def __init__(self):
self.base_url = 'https://petfriends1.herokuapp.com/'
def get_api_key(self, email: str, password: str):
"""Метод получения ключа API"... | 313109116/Unit_19.7 | api.py | api.py | py | 2,661 | python | ru | code | 0 | github-code | 1 | [
{
"api_name": "requests.get",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "requests_toolbelt.multipart.encoder.MultipartEncoder",
"line_number": 33,
"usage_type": "call"
},
{
"ap... |
1603872328 | """
trainvalsplit.py is a script that splits an MS COCO formatted dataset into train and val partitions.
For sample usage, run from command line:
Example:
python trainvalsplit.py --help
"""
import random
from pathlib import Path
from typing import Any, List, Tuple
import numpy as np
from .class_dist import CocoC... | GiscardBiamby/cocobetter | PythonAPI/pycocotools/helpers/splits.py | splits.py | py | 4,977 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "typing.List",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "numpy.ceil",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "numpy.random.seed",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_num... |
21513980032 | import json
from scrapy import Selector
import requests
import re
headers = {
"content-type": "application/x-www-form-urlencoded",
"sec-ch-ua-mobile": "?0",
"x-requested-with": "XMLHttpRequest",
'User-Agent': 'Mozilla/5.0 (Linux; Android 5.0; SM-G900P Build/LRX21T) AppleWebKit/537.36 (KHTML, like Geck... | petr777/pp | flask_app/vk_app/posts.py | posts.py | py | 1,845 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "re.search",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 36,
"usage_ty... |
45290876502 | # -*- coding: utf-8 -*-
import re
import markdown
from markdown.treeprocessors import Treeprocessor
from tina.front.templatetags.functions import resolve
class TargetBlankLinkExtension(markdown.Extension):
"""An extension that add target="_blank" to all external links."""
def extendMarkdown(self, md):
... | phamhongnhung2501/Taiga.Tina | fwork-backend/tina/mdrender/extensions/target_link.py | target_link.py | py | 879 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "markdown.Extension",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "markdown.treeprocessors.Treeprocessor",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "tina.front.templatetags.functions.resolve",
"line_number": 22,
"usage_type"... |
2760383933 | # This file contains the main class to run the model
import os
import math
from tensorflow.keras.callbacks import LambdaCallback
import numpy as np
import time
import matplotlib.pyplot as plt
# generate samples and save as a plot and save the model
def summarize_performance(step, g_model, c_model, dataset, n_samples=1... | AKI-maggie/thesis | main.py | main.py | py | 6,229 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.subplot",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "... |
12158969726 | from unittest import TestCase, mock
from matplotlib import animation, pyplot as plt
from src.chinese_checkers.game.ChineseCheckersGame import ChineseCheckersGame
from src.chinese_checkers.simulation.GameSimulationAnimation import GameSimulationAnimation
from src.chinese_checkers.simulation.GameSimulation import GameS... | dakotacolorado/ChineseCheckersGameEngine | tests/chinese_checkers/simulation/test_GameSimulationAnimation.py | test_GameSimulationAnimation.py | py | 2,113 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "unittest.TestCase",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "unittest.mock.MagicMock",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "unittest.mock",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "src.chinese_c... |
4752374660 | import os
import openai
openai.api_key = ""
def get_completion(prompt, model="gpt-3.5-turbo"):
messages = [{"role": "user", "content": prompt}]
response = openai.ChatCompletion.create(
model=model,
messages=messages,
temperature=0,
)
return response.choices[0].message["content... | yeonieheoo/MemoryCompanion | ML4H_LLM/case90.py | case90.py | py | 2,539 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "openai.api_key",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "openai.ChatCompletion.create",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "openai.ChatCompletion",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name... |
14920841148 | """
> Extremely Simple Image file format <
>------------------------------------------------------------------------------------------<
> Designed for databending or glitching
> Has very little fancy features that could cause problems with decoding
> Decoder is desi... | AlexPoulsen/esi | esi_to_png.py | esi_to_png.py | py | 5,823 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "re.sub",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "struct.pack",
"line_number": 62,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 68,
"usage_type": "call"
},
{
"api_name": "math.floor",
"line_number": 69,
"us... |
11101974490 | #!/usr/bin/env python
import json
import csv
import re
import math
from pprint import pprint
CURRENT_SOURCE_PATTERN = re.compile('^i', re.I)
INDUCTOR_PATTERN = re.compile('^l', re.I)
PULSE_PATTERN = re.compile('^pulse', re.I)
POSITION_PATTERN = re.compile(r'\An|_n', re.I)
TIME_PATTERN = re.compile(r'^\.tran', re.I)
... | tshaffe1/noisemapper | noisemapper.py | noisemapper.py | py | 11,790 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "re.compile",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "re.I",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "re.compile",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "re.I",
"line_number": 10,
"usag... |
27393973025 | # --- Bibliothèques utilisées ---
from functools import partial
import tkinter as tk
from random import seed
from random import randint
# --- Préparation du jeu ---
def diff_size(diff):
"""
sert à déterminer le nombre de cases du jeu
entrées : diff (difficulté) avec trois valeurs possib... | Claripouet/demineur | démineur_final.py | démineur_final.py | py | 10,371 | python | fr | code | 0 | github-code | 1 | [
{
"api_name": "random.seed",
"line_number": 60,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "tkinter.Button",
"line_number": 139,
"usage_type": "call"
},
{
"api_name": "functools.partial",
"l... |
32087619445 | import uiautomator2 as u2
import pytest
import allure
@allure.feature("测试首页")#类的主要测试部分
#@allure.environment(app_package='com.mobile.fm')# 具体Environment参数可自行设置
# @allure.environment(app_activity='com.mobile.fm.activity')
# @allure.environment(device_name='aad464')
# @allure.environment(platform_name='Android')
class ... | luoqingfu/u2demo | testcase/test_demo.py | test_demo.py | py | 2,173 | python | zh | code | 0 | github-code | 1 | [
{
"api_name": "uiautomator2.connect",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "allure.story",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "allure.severity",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "allure.step",
"... |
16805089134 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
a_dataframe = pd.DataFrame(
{'name':['Alice','Bob','Charles'],
'age':[25, 23, 34],
'gender':['female','male','male']})
print(a_dataframe)
# new_dataframe = pd.DataFrame(np.arange(16).reshape((4,4)),
# ... | OceanicSix/Python_program | Study/external/pand/pandas_example.py | pandas_example.py | py | 973 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "pandas.DataFrame",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.legend",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "matplotlib... |
1293373601 | import random
import itertools
from fp.fp import FreeProxy
import requests
from itemloaders.processors import TakeFirst, MapCompose
proxies_list = FreeProxy().get_proxy_list()
print(type(proxies_list))
proxy = itertools.cycle(proxies_list)
# pr = random.choice(proxies)
def set_proxy(proxy):
_proxy = next(proxy)
... | navneet37/BusinessScrapy | testproxy.py | testproxy.py | py | 589 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "fp.fp.FreeProxy",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "itertools.cycle",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 20,
"usage_type": "call"
}
] |
28941505818 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
from tex import Tex
from PIL import Image
if __name__ == '__main__':
for root, dirs, files in os.walk('PackedContent'):
for f in files:
if os.path.splitext(f)[1].lower() == '.tex':
name = os.path.join(root, f)
... | noword/EXAPUNKS-Localize | images/import_imgs.py | import_imgs.py | py | 1,256 | python | en | code | 32 | github-code | 1 | [
{
"api_name": "os.walk",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path.splitext",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number"... |
647601614 | import json
import re
from konlpy.tag import Twitter
from collections import Counter
import pytagcloud
import webbrowser
import matplotlib
import matplotlib.pyplot as plt
from matplotlib import font_manager, rc
def showGraph(wordInfo) :
font_location = "C:\Windows\Fonts\malgun.ttf"
font_name = font_manager.Fo... | Gyeo1/Project | Iot-인공지능-빅데이터(크롤링,워드클라우드)/2.워드클라우드.py | 2.워드클라우드.py | py | 1,933 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "matplotlib.font_manager.FontProperties",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "matplotlib.font_manager",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "matplotlib.rc",
"line_number": 15,
"usage_type": "call"
},
{
"api_... |
15405751223 | #!/usr/bin/env python3
"""
https://adventofcode.com/2021/day/21
"""
import collections
import itertools
import aoc
PUZZLE = aoc.Puzzle(day=21, year=2021)
def solve_b(positions):
"""Solve puzzle part b"""
rolls = collections.Counter(
sum(rolls)
for rolls in itertools.product(range(1, 4), repe... | trosine/advent-of-code | 2021/day21.py | day21.py | py | 1,970 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "aoc.Puzzle",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "collections.Counter",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "itertools.product",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "collections.defaultd... |
24645452076 | """
This module should contain your main project pipeline(s).
Whilst the pipeline may change during the analysis phases, any more stable pipeline should be implemented here so
that it can be reused and easily reproduced.
"""
# This must be set in the beggining because in model_util, we import it
logger_name = "FCRN-BI... | aleksei-mashlakov/fcrn-bidding | src/fcrn_bidding/pipeline.py | pipeline.py | py | 3,112 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "proxy.Proxy",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "threading.Thread",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "schedule.every",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "schedule.every",
"lin... |
43464527814 | import easyocr
import cv2
import matplotlib.pyplot as plt
import re
import unidecode
from datetime import datetime
import numpy as np
import math
import os
import json
from difflib import SequenceMatcher
from itertools import combinations
READER = easyocr.Reader(['vi'])
json_path = "data/vn_administrative_location.j... | tungedng2710/TonEKYC | utils/ocr_utils.py | ocr_utils.py | py | 5,405 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "easyocr.Reader",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 24,... |
33776237261 | # # Notation: Draw Supported Notations of Explicit Converter
import mechkit
import networkx as nx
import matplotlib.pyplot as plt
plot_options = dict(
node_color="yellow",
node_size=2000,
width=2,
arrows=True,
font_size=10,
font_color="black",
)
converter = mechkit.notation.ExplicitConverter(... | JulianKarlBauer/mechkit | docs/source/notebooks/06.py | 06.py | py | 551 | python | en | code | 14 | github-code | 1 | [
{
"api_name": "mechkit.notation.ExplicitConverter",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "mechkit.notation",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "networkx.spring_layout",
"line_number": 20,
"usage_type": "call"
},
{
"a... |
33501639542 | import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.optim import Optimizer
import scipy.io
from Bayesian_DL.BPINN.VI.src.utils import log_gaussian_loss, gaussian, get_kl_Gaussian_divergence
from torch.utils.tensorboard... | SoloChe/BPINN | VI/KdV_identification.py | KdV_identification.py | py | 13,494 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "torch.cuda.is_available",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "Bayesian_DL.BPINN.VI.src.model.BBP_Model_PINN",
"line_number": 20,
"usage_type": "name"
},
{
... |
5237933206 | import numpy as np
import matplotlib.pyplot as plt
class Agent:
def __init__(self, bandit, exploration_rate):
self.bandit = bandit
self.exploration_rate = exploration_rate
self.cur_estimates = self.first_estimates()
self.all_estimates = [[self.cur_estimates[i]] for i in range(len(se... | Oppac/RL | simple_bandit.py | simple_bandit.py | py | 1,735 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.random.normal",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "numpy.random.random",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "numpy.rando... |
71349302755 | """
"""
import datetime as dt
import requests
import time
import pandas as pd
import streamlit as st
def app():
asset_contract_address = st.sidebar.text_input("Contract Address")
start_dt_input = st.sidebar.date_input(label='Start Date')
end_dt_input = st.sidebar.date_input(label='End Date')
def get... | alhedlund/al_nft_data_app | pages/collections.py | collections.py | py | 2,310 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "streamlit.sidebar.text_input",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "streamlit.sidebar",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "streamlit.sidebar.date_input",
"line_number": 13,
"usage_type": "call"
},
{
"... |
16190520974 | # coding: utf-8
"""
Производственный календарь.
"""
import json
import os
import datetime
import requests
WORKING_TYPE_WORK = 0
WORKING_TYPE_HOLIDAY = 2
WORKING_TYPE_SHORT = 3
DEFAULT_CACHE_PATH = '/tmp/basicdata_calend.json'
def is_working_time(date_time, use_cache=False, cache_path=DEFAULT_CACHE_PATH):
except... | telminov/sw-python-utils | swutils/prod_calendar.py | prod_calendar.py | py | 2,802 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "requests.get",
"line_number": 66,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 72,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 77,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
"line_number": ... |
4496867704 | import requests
import argparse
from datetime import datetime
PXLA_ENDPOINT = "https://pixe.la/v1/users"
USERNAME = "stamnoob"
PWD = "m0n0mlkiaple0n"
HEADER = {"X-USER-TOKEN": PWD}
def arg_parser() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Post a coding hours pixel in the pixela \"code-... | stzanos95/python-projects | Habit-Tracker/main.py | main.py | py | 2,221 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "argparse.Namespace",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "requests.post",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "request... |
72703642915 | import math
import random
import sys
import importlib
#========================change variables here to modify scenario========================
path_to_folder = "C:\\Users\\LJMU\\Documents\\Felix\\OpenMATB_ScenarioCreator"
path_to_folder = "C:\\Users\\felix\\Desktop\\LJMU\\Scripts\\Python\\OpenMATB_ScenarioCreator"
#... | Zebrakopf/OpenMATB_ScenarioCreator | create_scenario.py | create_scenario.py | py | 9,599 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sys.argv",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number... |
4490266612 | # My_Picture Predict
import numpy as np
import matplotlib.pyplot as plt
import cv2
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.models import load_model
model = load_model('../data/h5/k67_img.h5')
pred_datagen = ImageDataGenerator(rescale=1./255)
pred_data = pred_datagen... | Taerimmm/ML | keras2/keras67_4_my_result.py | keras67_4_my_result.py | py | 1,145 | python | en | code | 3 | github-code | 1 | [
{
"api_name": "tensorflow.keras.models.load_model",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras.preprocessing.image.ImageDataGenerator",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.imshow",
"line_number": 22,
"... |
19294404545 | from statsmodels.tsa.holtwinters import ExponentialSmoothing
from dateutil.relativedelta import relativedelta
import pandas as pd
def predict_next_12_months(data):
pred = pd.DataFrame()
start_and_finish = [max(pd.to_datetime(data.columns, format = "%Y-%m")) + relativedelta(months=(x*11)+1) for x in range(2)]
... | nizarcan/CapacityPlanningDSS-SD | backend/predictor.py | predictor.py | py | 1,444 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.DataFrame",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pandas.to_datetime",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "dateutil.relativedelta.relativedelta",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": ... |
36916798983 | # Módulos
from datetime import date
# Declaração de variáveis
pessoa = dict()
# Entrada de dados da pessoa
pessoa['nome'] = str(input('Nome: '))
nasc = int(input('Ano de nascimento: '))
pessoa['idade'] = date.today().year - nasc
ctps = int(input('Carteira de Trabalho (0 se não possui): '))
if ctps !=... | Henrique-Botelho/ExerciciosDePython-Curso-em-Video | Exercícios Aula 19/Ex. 092.py | Ex. 092.py | py | 636 | python | pt | code | 0 | github-code | 1 | [
{
"api_name": "datetime.date.today",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "datetime.date",
"line_number": 12,
"usage_type": "name"
}
] |
71730627235 | from gui.visual.player import Player
from gui.visual.entity import Entity
import glm
import OpenGL.GL as gl
from gui.visual.camera import Camera
from gui.visual.staticShader import StaticShader
from gui.visual.entityRenderer import EntityRenderer
from gui.visual.skyboxRenderer import SkyboxRenderer
from gui.visual.worl... | Mimikkk/2023-amib | src/libs/framspy/gui/visual/masterRenderer.py | masterRenderer.py | py | 3,138 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "gui.visual.staticShader.StaticShader",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "gui.visual.entityRenderer.EntityRenderer",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "gui.visual.skyboxRenderer.SkyboxRenderer",
"line_number": 24,
... |
2558854509 | import sqlite3
connection=sqlite3.connect("RUGIPP_REGISTRI.db")
crsr=connection.cursor()
class Registar_Geodeta:
def __init__(self,JMBG,ime,prezime,strucna_sprema,broj_strucnog,red_licence):
self.JMBG=JMBG
self.ime=ime
self.prezime=prezime
self.sprema=strucna_sprema
self.st... | SarajlicS/Zavrsni_Rad | Registar_Geodeta.py | Registar_Geodeta.py | py | 4,781 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sqlite3.connect",
"line_number": 2,
"usage_type": "call"
}
] |
34459058884 | import os, sys
from typing import Union, List
import numpy as np
import pandas as pd
from sklearn.preprocessing import scale
import torch
import torch.nn as nn
from torch.utils.data import Dataset
def load_data(data_path):
name = ["train", "test"]
columns = [f"V{i}" for i in range(1, 31)]
val_columns = ... | doyooni303/UnsupervisedAnomalyDetection_VAE | src/build_datset.py | build_datset.py | py | 1,789 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "pandas.read_csv",
"line... |
26074240113 | import json
from flask import Flask, redirect, request, render_template
from oauth2client.client import flow_from_clientsecrets
from config import GOOGLE_CLIENT_SECRETS_JSON, REGISTERED_CREDENTIALS_JSON
server_uri = 'http://localhost:5000'
app = Flask(__name__)
flow = flow_from_clientsecrets(
GOOGLE_CLIENT_SECR... | sk364/inbox-cleaner | server.py | server.py | py | 1,740 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "oauth2client.client.flow_from_clientsecrets",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "config.GOOGLE_CLIENT_SECRETS_JSON",
"line_number": 12,
"usage_type": "argument"
... |
27286970033 | import numpy as np
import pandas as pd
import pytest
from cleanlab.datalab.internal.issue_manager import IssueManager
from cleanlab.datalab.internal.issue_manager_factory import REGISTRY, register
class TestCustomIssueManager:
@pytest.mark.parametrize(
"score",
[0, 0.5, 1],
ids=["zero", "... | cleanlab/cleanlab | tests/datalab/test_issue_manager.py | test_issue_manager.py | py | 1,931 | python | en | code | 7,004 | github-code | 1 | [
{
"api_name": "pandas.DataFrame",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pandas.testing.assert_frame_equal",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "pandas.testing",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name":... |
26781812415 | import re
import nltk
import pandas as pd
from textblob import TextBlob
def lemmatize_with_postag(sentence):
'''
https://www.machinelearningplus.com/nlp/lemmatization-examples-python/
'''
sent = TextBlob(sentence)
tag_dict = {"J": 'a',
"N": 'n',
"V": 'v',
... | SamEdwardes/sentiment-cdn-election | src/twitter_analysis.py | twitter_analysis.py | py | 6,996 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "textblob.TextBlob",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "textblob.TextBlob",
"line_number"... |
22119528446 | import numpy as np
import cv2
def load_image(path_img):
return cv2.imread(path_img)
def bgr2hsv(img):
return cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
def setRangeColor(hsv, lower_color, upper_color):
return cv2.inRange(hsv, lower_color, upper_color)
def contours_img(mask):
contours,_ = cv2.... | opsun1/code | color_detection.py | color_detection.py | py | 3,063 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cv2.imread",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "cv2.cvtColor",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_BGR2HSV",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "cv2.inRange",
"line_n... |
43199229342 | import bpy
from bpy.props import BoolProperty, EnumProperty
from bpy_extras.view3d_utils import region_2d_to_location_3d, region_2d_to_origin_3d, region_2d_to_vector_3d
from mathutils import Vector
from .. utils.registration import get_addon, get_prefs
from .. utils.tools import get_active_tool
from .. utils.object imp... | AtixCG/Universal-3D-Shortcuts | Blender/With Addons/scripts/addons/MACHIN3tools/operators/mirror.py | mirror.py | py | 28,604 | python | en | code | 38 | github-code | 1 | [
{
"api_name": "bpy.types",
"line_number": 79,
"usage_type": "attribute"
},
{
"api_name": "bpy.props.BoolProperty",
"line_number": 84,
"usage_type": "call"
},
{
"api_name": "bpy.props.BoolProperty",
"line_number": 85,
"usage_type": "call"
},
{
"api_name": "bpy.prop... |
39101218782 | # type: ignore
import json
fin = open("secrets.json")
raw_data = fin.read()
#print(raw_data)
environ_data = json.loads(raw_data)
def load(os, db):
for i in environ_data:
os.environ[i] = environ_data[i]
| py660/PyChat-Self-Deploy | shh.py | shh.py | py | 216 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "json.loads",
"line_number": 7,
"usage_type": "call"
}
] |
25497213504 | import abc
import logging
import random
import numpy as np
import pandas as pd
EVALUATION_CRITERIA = 'Accuracy'
def _new_func(optimization, t, theta=1.0, record=None, gamma=1):
third_term = np.sqrt(2 * np.log(t) / optimization.count)
forth_term = np.sqrt(1 / theta * third_term)
second_term = np.sqrt(1 /... | pineconebean/automl_lab | bandit/model_selection.py | model_selection.py | py | 11,212 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.sqrt",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.log",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.sqrt",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.sqrt",
"line_number": 14,
... |
70561841635 |
import tensorflow.keras.backend as K
import matplotlib.pyplot as plt
from tensorflow.keras.callbacks import Callback
class LRFinder(Callback):
#adjuted callback from Lucas Anders at: https://github.com/LucasAnders1/LearningRateFinder/blob/master/lr_finder_callback.py
#adjusted to geometrically increase by ste... | valentinocc/Keras_cifar10 | custom_callbacks.py | custom_callbacks.py | py | 5,315 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "tensorflow.keras.callbacks.Callback",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "tensorflow.keras.backend.set_value",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras.backend",
"line_number": 42,
"usage_type": "name"
... |
36783915591 | import numpy as np
import matplotlib.pyplot as plt
import higra as hg
import torch
from tqdm import tqdm
#=========================================
#= Helper Functions =
#=========================================
def get_centroids(X, high_dim_clusters,K,device="cpu",dim=2):
index_sets = [np.a... | hci-unihd/DTAE | loss.py | loss.py | py | 3,853 | python | en | code | 6 | github-code | 1 | [
{
"api_name": "numpy.argwhere",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "torch.zeros",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "torch.mean",
"line_number... |
25608601191 | import json
with open( "Task2.json","r+")as f:
data=json.load(f)
def group_of_decade(movies):
dic={}
list1=[]
for i in movies:
m=int(i)%10
decade=int(i)-m
if decade not in list1:
list1.append(decade)
list1.sort()
for i in list1:
dic[i]=[]
for i in ... | Subhkirti/PYTHON | WEB SCRAPPING/TASK3.py | TASK3.py | py | 666 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "json.load",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 22,
"usage_type": "call"
}
] |
21532212683 | # -*- coding: utf-8 -*-
import scrapy
from protectoras_scrap.models.Pet import Pet
class ProtectoraLugoSpider(scrapy.Spider):
name = 'protectora_lugo_spider'
allowed_domains = ['www.protectoralugo.org']
base_url = 'http://www.protectoralugo.org/'
start_urls = ['http://www.protectoralugo.org/templates/j... | SaulEiros/protectoras-scraper | protectoras_scrap/spiders/protectora_lugo_spider.py | protectora_lugo_spider.py | py | 1,447 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "scrapy.Spider",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "scrapy.Request",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "scrapy.Request",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "scrapy.Request",
... |
264166147 | """django_obj 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-ba... | zhouf1234/django_obj | django_obj/urls.py | urls.py | py | 1,554 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.urls.path",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.urls.include",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "django.urls.inc... |
73426657635 | from time import sleep
import requests
def parsing_data(token_key, repos_list):
url = "https://api.github.com/repos/{}/{}"
headers = {
"Accept": "application/vnd.github.v3+json",
"Authorization": "token {}".format(token_key), # 此处的XXX代表上面的token
"X-OAuth-Scopes": "repo"
}
urls =... | freedanfan/delete_gitlab_repositories | delete_gitlab_repositories.py | delete_gitlab_repositories.py | py | 1,191 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "requests.delete",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 25,
"usage_type": "call"
}
] |
41440456232 | from collections import deque
from time import sleep
def append_one(num):
return int(str(num) + '1')
def solution(num, target):
queue = deque()
queue.append([num, 0])
while(queue):
cur_num, cur_cnt = queue.popleft()
if cur_num == target:
return cur_cnt + 1
... | aszxvcb/TIL | BOJ/boj16953.py | boj16953.py | py | 738 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "collections.deque",
"line_number": 8,
"usage_type": "call"
}
] |
31326029236 | # -*- coding: utf-8 -*-
### Import libraries ###
import numpy as np
import pandas as pd
from pandas import Grouper
import matplotlib.pyplot as plt
import seaborn as sns
color = sns.color_palette()
sns.set_style(style="darkgrid")
from data_utils import most_reviewed_products
from pathlib import Path
from ... | avivace/reviews-sentiment | scripts/data_exploration.py | data_exploration.py | py | 14,076 | python | en | code | 25 | github-code | 1 | [
{
"api_name": "seaborn.color_palette",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "seaborn.set_style",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matplotlib.rcParams",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "matplotli... |
2396932646 | import pathlib
# directories
DATA_DIR = pathlib.Path(__file__).resolve().parent.parent / "data"
RESOURCE_DIR = pathlib.Path(__file__).resolve().parent.parent / "resources"
MODEL_DIR = RESOURCE_DIR / "checkpoints"
WSD_DIR = DATA_DIR / "wsd_corpora"
TRAIN_DIR = DATA_DIR / "train"
DEV_DIR = DATA_DIR / "dev"
MAPPING_DIR =... | Riccorl/elmo-wsd | elmo-wsd/constants.py | constants.py | py | 1,683 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "pathlib.Path",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 5,
"usage_type": "call"
}
] |
73268716835 | import json
test_list =\
[{"Title":"Harry Potter", "DVD":"T", "Form":"C", "Genre":"Fantasy", "Date":"2003", "Alt Title 1":"", "Alt Title 2":"", "Count":1, \
"Director":"Jon","Writer":"Rowling", "Language":"English", "Date Watched":"2019", "Spec":""}, \
{"Title":"Transformers", "DVD":"F", "Form":"B", "Genre... | Leeoku/MovieDatabase | main.py | main.py | py | 789 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "json.dumps",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 17,
"usage_type": "call"
}
] |
74329843233 | import numpy as np
from sympy import Matrix
import string
import random
dim = 2 #n차원 행렬
cipher = string.ascii_uppercase
def main():
mode = input("Select Encrypt or Decrypt:")
if mode == 'Encrypt':
encrypt()
elif mode == 'Decrypt':
decrypt()
def encrypt():
key = np.matrix([[1, 2], [2, 5]... | jeongyoonlee2015/Ciphers | Theoretical/hillCipher.py | hillCipher.py | py | 1,602 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "string.ascii_uppercase",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "numpy.matrix",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "numpy.matrix",... |
30632192338 | import argparse
import json
import os
import platform
import PySide6 as RefMod
import PyInstaller.__main__
from mapclient.core.provenance import reproducibility_info
from mapclient.settings.definitions import APPLICATION_NAME, FROZEN_PROVENANCE_INFO_FILE
# Set Python optimisations on.
os.environ['PYTHONOPTIMIZE'] ... | MusculoskeletalAtlasProject/mapclient | res/pyinstaller/create_application.py | create_application.py | py | 3,596 | python | en | code | 19 | github-code | 1 | [
{
"api_name": "os.environ",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "mapclient.settings.defin... |
2113231979 | from __future__ import division
from __future__ import print_function
import numpy as np
import gzip
import re
import datetime
import calendar
import time
import glob
from copy import deepcopy
import warnings
import sys
import os
import codecs
from .tools import unix2date, date2unix, limitMaInidces, quantile
from .to... | maahn/IMProToo | IMProToo/core.py | core.py | py | 135,069 | python | en | code | 19 | github-code | 1 | [
{
"api_name": "importlib.metadata.version",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "importlib.metadata.PackageNotFoundError",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "pkg_resources.get_distribution",
"line_number": 35,
"usage_type": "cal... |
2524008345 | import matplotlib.pyplot as plt
import cv2
import os, glob
import numpy as np
import matplotlib._png as png
from moviepy.editor import VideoFileClip
#%matplotlib inline
#%config InlineBackend.figure_format = 'retina'
def show_images(images, cmap=None):
cols = 2
rows = (len(images) + 1) // cols
plt.figur... | ghazalsaf/mobNavigation | road_detect_hls.py | road_detect_hls.py | py | 10,716 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.subplot",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "... |
538148120 | import streamlit as st
import datetime
import requests
import json
import pandas as pd
import time
page = st.sidebar.selectbox('chose your page', ['users', 'checkin', 'checkout'])
if page == 'users':
st.title('ユーザー登録画面')
with st.form(key='user'):
username: str = st.text_input('ユーザー名', max_chars=12)
... | terotero57/tes | app.py | app.py | py | 7,125 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "streamlit.sidebar.selectbox",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "streamlit.sidebar",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "streamlit.title",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "stre... |
70508257953 | import itertools
#taking input
k=int(input())
a=list(map(int,input().split()))
#generating prime numbers
soe=[True]*(100000)
for i in range(2,100000):
if soe[i]==True:
j=i+i
while j<100000:
soe[j]=False
j+=i
#storing prime numbers whith in given input
p=[i for i in range(2,le... | jay8299/practice_cp | python_prac/smarttraining_infytq.py | smarttraining_infytq.py | py | 572 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "itertools.combinations",
"line_number": 18,
"usage_type": "call"
}
] |
9907501422 | #!/usr/bin/env python3
import sys
import re
import sqlite3
import codecs
season_length = 14
def __grab(term, lines):
for line in lines:
if term in line:
return line
def __get_line(term, lines):
num = 0
for line in lines:
num = num+1
if term in line:
retur... | phantom-voltage/mortician | scripts/cdda.py | cdda.py | py | 5,313 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sqlite3.connect",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 88,
"usage_type": "call"
},
{
"api_name": "re.findall",
"line_number": 119,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 156,
... |
35219965731 | from ast import main
import collections
from statistics import mean
import numpy as np
import random
from collections import defaultdict
import matplotlib.pyplot as plt
class MonteCarlo():
def __init__(self, gamma):
self.actions = [(-1,0), (0,1), (1,0), (0,-1)] # up, right, down, left
self.arrows ... | saurabhbajaj123/Reinforcement-Learning-Algorithms-1 | HW4/submission/HW4.py | HW4.py | py | 20,952 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.array",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "collections.defaultdict",
"li... |
74112978272 | from commands.Command import Command
import discord
import asyncio
class Cat(Command):
def __init__(self):
super().__init__(
{
'name': 'cat',
'description': 'extracts the text content of your file',
'argc': 1
}
)
async de... | luccanunes/code-runner-bot | commands/Cat.py | Cat.py | py | 1,045 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "commands.Command.Command",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "discord.Message",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "discord.Embed",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "discord.Co... |
1443567060 | # -*- coding: utf-8 -*-
"""
Created on Wed Feb 9 12:39:55 2022
@author: pkinn
"""
def cvTrain(model, features, targets, nSplits, nEpochs, batchSz, initWts):
from sklearn.model_selection import KFold
import numpy as np
kf = KFold(n_splits = nSplits, shuffle = True)
fn = 1
# Define per-fold score co... | Tessier-Lab-UMich/Emi_Pareto_Opt_ML | cvTrain.py | cvTrain.py | py | 1,305 | python | en | code | 14 | github-code | 1 | [
{
"api_name": "sklearn.model_selection.KFold",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 15,
"usage_type": "call"
}
] |
36170270181 | from abc import ABCMeta, abstractmethod
from bisect import bisect_right
from typing import Any, Dict, Iterable, List, Optional, Tuple
from volatility3.framework import exceptions, interfaces
from volatility3.framework.configuration import requirements
from volatility3.framework.layers import linear
class NonLinearly... | volatilityfoundation/volatility3 | volatility3/framework/layers/segmented.py | segmented.py | py | 6,939 | python | en | code | 1,879 | github-code | 1 | [
{
"api_name": "volatility3.framework.interfaces.layers",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "volatility3.framework.interfaces",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "abc.ABCMeta",
"line_number": 11,
"usage_type": "name"
},
... |
34529095803 | import copy
import re
from knack.log import get_logger
from azdev.utilities import get_name_index
logger = get_logger(__name__)
_LOADER_CLS_RE = re.compile('.*azure/cli/command_modules/(?P<module>[^/]*)/__init__.*')
def filter_modules(command_loader, help_file_entries, modules=None, include_whl_extensions=False... | Azure/azure-cli-dev-tools | azdev/operations/linter/util.py | util.py | py | 4,677 | python | en | code | 71 | github-code | 1 | [
{
"api_name": "knack.log.get_logger",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "copy.copy",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "azdev.utilities.get_name_ind... |
25922177105 | from swift.common.swob import wsgify, HTTPInternalServerError, HTTPException
from swift.common.utils import get_logger
from zion.handlers import ProxyHandler
from zion.handlers import ComputeHandler
from zion.handlers import ObjectHandler
from zion.handlers.base import NotFunctionRequest
from distutils.util import strt... | JosepSampe/storage-functions | Engine/swift/middleware/zion/function_handler.py | function_handler.py | py | 4,342 | python | en | code | 11 | github-code | 1 | [
{
"api_name": "swift.common.utils.get_logger",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "redis.ConnectionPool",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "zion.handlers.ProxyHandler",
"line_number": 38,
"usage_type": "name"
},
{
"api... |
8243965245 | import numpy as np
import random
import matplotlib.pyplot as plt
import pickle
class Dataset:
def __init__(self):
self.index = 0
self.obs = []
self.classes = []
self.num_obs = 0
self.num_classes = 0
self.indices = []
def __iter__(self):
return self
... | moritzlangenberg/SCaML6 | network.py | network.py | py | 13,504 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "random.shuffle",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "random.shuffle",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "numpy.float32",
"line_... |
21358312248 | __author__ = ["fkiraly"]
from sktime.tests import test_all_estimators
def pytest_addoption(parser):
"""Pytest command line parser options adder."""
parser.addoption(
"--matrixdesign",
default=False,
help="sub-sample estimators in tests by os/version matrix partition design",
)
d... | orgTestCodacy11KRepos110MB/repo-5089-sktime | conftest.py | conftest.py | py | 499 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sktime.tests.test_all_estimators.MATRIXDESIGN",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "sktime.tests.test_all_estimators",
"line_number": 18,
"usage_type": "name"
}
] |
72184037154 | import tqdm
import torch
import csv
import os
import os.path as osp
import random
import json
import h5py
import time
from collections import defaultdict
if __name__ == '__main__':
from MiniImageNet import MiniImageNetDataset, TransformedImageLoader, h5load
from base import MultiProcessImageLoader
else:
f... | alecwangcq/Prototypical-network | dataloader/MiniImageNetMAML.py | MiniImageNetMAML.py | py | 7,428 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "random.randrange",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "MiniImageNet.MiniImageNetDataset",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "random.shuffle",
"line_number": 73,
"usage_type": "call"
},
{
"api_name": "torc... |
2724354165 | from graphviz import Digraph
import pandas as pd
import numpy as np
import glob
import os
#Associa cada cor na planilha a um par (cor de fundo,cor da fonte) do Graphviz
colors = {'Amarelo':('yellow','black'),'Azul':('blue','white'),'Branco':('white','black'),
'Cinza':('grey','black'),'Marrom':('brown'... | lcoandrade/relationshipdiagram | diagrama_relacoes.py | diagrama_relacoes.py | py | 7,035 | python | pt | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_excel",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "numpy.nan",
"line_number": 34,
"usage_type": "attribute"
},
{
"api_name": "graphviz.Digraph",
"line_number": 70,
"usage_type": "call"
},
{
"api_name": "glob.glob",
"li... |
4348600276 | from pyspark.sql import SparkSession
from pyspark.ml.feature import MinMaxScaler
from pyspark.ml.linalg import Vectors
spark = SparkSession.builder.appName('normalization').getOrCreate()
spark.sparkContext.setLogLevel("WARN")
print("### spark starting ###")
records = [
(1, Vectors.dense([10.0, 10000.00, 1.0]),),... | yuyatinnefeld/spark | python/pyspark/ml_transformation/normalization.py | normalization.py | py | 793 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pyspark.sql.SparkSession.builder.appName",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pyspark.sql.SparkSession.builder",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "pyspark.sql.SparkSession",
"line_number": 5,
"usage_type": "... |
15166107096 | import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import os
all_models = pd.read_csv('model_results.csv')
all_models['Accuracy'] = all_models['target_response']
folder = 'accuracy_plots'
mymax = all_models.query('Task == "Different"').groupby(
['c', 'Representation', 'Category', 'Subcateg... | crasanders/vision | plot_model_accuracy.py | plot_model_accuracy.py | py | 3,031 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "seaborn.catplot",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.savefig",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "matplotlib.p... |
73033768993 | # -*- coding: utf-8 -*-
'''
The AWS Cloud Module
====================
The AWS cloud module is used to interact with the Amazon Web Services system.
This module has been replaced by the EC2 cloud module, and is no longer
supported. The documentation shown here is for reference only; it is highly
recommended to change ... | shineforever/ops | salt/salt/cloud/clouds/botocore_aws.py | botocore_aws.py | py | 7,499 | python | en | code | 9 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 60,
"usage_type": "call"
},
{
"api_name": "salt.cloud.clouds.libcloud_aws.__opts__",
"line_number": 83,
"usage_type": "attribute"
},
{
"api_name": "salt.cloud.clouds.libcloud_aws",
"line_number": 83,
"usage_type": "name"
... |
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