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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
43187154033 | '''
Created on June 3, 2021
Implementation of crawling the graph information of a certain fund portfolio
@author: jasonzheng (jasonccvx@outlook.com)
@version: 0.3.2
'''
import requests
import json
import matplotlib.pyplot as plt
import time
def get_json_of_graph_info(code):
"""
get the json string of the com... | jasonccvx/big-v | crawling/v_details_graph.py | v_details_graph.py | py | 4,484 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "requests.post",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 74,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 97,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",... |
74846508201 | from init import db
from flask import Blueprint, request
from models.format import Format, format_schema, formats_schema
from flask_jwt_extended import get_jwt_identity, jwt_required
from controllers.book_controller import authorise_admin
formats_bp = Blueprint('formats', __name__, url_prefix='/formats')
@formats_bp.... | zakaryjs/CA-T2A2-Webserver_API | controllers/format_controller.py | format_controller.py | py | 3,069 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "flask.Blueprint",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "init.db.select",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "models.format.Format",
"line_number": 12,
"usage_type": "argument"
},
{
"api_name": "init.db",
... |
71813889320 | #!/usr/bin/python3
# -*-coding:UTF-8-*-
import time
import argparse
import pickle
from model import *
from utils import *
from torch.utils.data import DataLoader
import logging
import torch
import os
from tqdm import tqdm
import datetime
import numpy as np
import random
from os.path import join
# CUDA_VISIBLE_DEVICES=1... | cyq002/ITR-GNN | generate_high_confidence_data.py | generate_high_confidence_data.py | py | 4,977 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "time.time",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "numpy.random.seed",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "random.seed",
"line... |
17640202590 | import hashlib
import asyncio
from . import message
from . import error
from . import interfaces
from . import numbers
def hashing_etag(request, response):
"""Helper function for render_get handlers that allows them to use ETags based
on the payload's hash value
Run this on your request and response befo... | ric1234/intelligent_refrigerator | userRpi/aiocoap/aiocoap/resource.py | resource.py | py | 10,899 | python | en | code | 2 | github-code | 18 | [
{
"api_name": "hashlib.sha1",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "asyncio.coroutine",
"line_number": 67,
"usage_type": "attribute"
},
{
"api_name": "asyncio.coroutine",
"line_number": 71,
"usage_type": "attribute"
},
{
"api_name": "asyncio.co... |
3306505237 | from pathlib import Path
current_wd = Path(__file__).resolve()
current_wd = current_wd.parent.parent
raw_data_path = current_wd / 'data/raw/SBAnational.csv'
split_dir = current_wd / 'data' / 'split'
split_train = split_dir / 'train_df.csv'
split_test = split_dir / 'test_df.csv'
split_test_y_true = split_dir / 'tes... | patrick-potocny/loan_prediction | loan_prediction/config.py | config.py | py | 535 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "pathlib.Path",
"line_number": 3,
"usage_type": "call"
}
] |
35619807603 | import numpy as np
from sklearn.neighbors import KDTree, KNeighborsClassifier
class TrustScore:
"""
Trust Score: a measure of classifier uncertainty based on nearest neighbors.
"""
def __init__(self, k=10, alpha=0.0, filtering="none", min_dist=1e-12):
"""
k and alpha are the tuning para... | google/TrustScore | trustscore/trustscore.py | trustscore.py | py | 4,341 | python | en | code | 169 | github-code | 18 | [
{
"api_name": "numpy.array",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "sklearn.neighbors.KDTree",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "numpy.percentile",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "numpy.wher... |
71131048359 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
data = pd.read_csv('1KGP.txt', delimiter=' ',header=None)
Y = data.iloc[:,3:]
labels = data.iloc[:,1].unique()
colors = ['b','g','r','c','m','y','k']
modes = Y.mode().iloc[0]
Y = (Y!=modes).astype(int)
pca = P... | fardinayar/SPR | HW4/4/f.py | f.py | py | 446 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "pandas.read_csv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sklearn.decomposition.PCA",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.scatter",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "ma... |
73297841639 | """
plots excel file uncertanties
"""
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.pyplot import figure
figure(figsize=(10,5))
data=pd.read_csv("/Users/kiern/OneDrive/Desktop/JAM22_PY.csv ")
plt.xlabel("Bin Number #",fontsize=14)
plt.ylabel("",fontsize=14)
plt.plo... | mnycz/Spring_2022_SULI | CSV_Plot.py | CSV_Plot.py | py | 1,003 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.xlabel",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matp... |
73871845800 | from rest_framework import serializers
from service.models.wedding_hall import Menu, MenuItem, WeddingHall
class MenuItemSerializers(serializers.ModelSerializer):
class Meta:
model = MenuItem
fields = ("name", "menu_id")
class MenuSerializers(serializers.ModelSerializer):
menu_items = MenuI... | yusuf88811/afarmilena | service/serializers/wedding_hall_serializers.py | wedding_hall_serializers.py | py | 4,134 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "rest_framework.serializers.ModelSerializer",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.serializers",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "service.models.wedding_hall.MenuItem",
"line_number": 8,
"usage_... |
9772073637 | import torch
import torch.nn.functional as F
import matplotlib.pyplot as plt
import copy
import nn
import shuffler
class NNTrainer:
def __init__(self, num_epochs, learning_rate, loss_function):
self.epochs = num_epochs
self.lr = learning_rate
self.loss_func = loss_function
def proces... | JunkyLove/Project_1 | trainer.py | trainer.py | py | 2,991 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "copy.deepcopy",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "torch.optim.Adam",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "torch.optim",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "shuffler.x_y_shuffler... |
44174168828 | from typing import Callable
import numpy as np
import copy
from functools import reduce
from configargparse import ArgumentParser
from random import randint
from datetime import datetime, timedelta
from board import Board
from solver import State
def main():
options = [
argument(
'--file',
... | SteveDraper/sudoku_gen | python/solve.py | solve.py | py | 3,585 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "functools.reduce",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "configargparse.ArgumentParser",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "board.Board",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "board.cell... |
13040730222 | """I/O module.
This module creates a File class that can fetch data and/or plot data.
Available classes are one of following:
File:
MCPDataFile;
TESConfigFile;
SPECParamFile;
ScanFileAPS29;
SCanFileSSRL13.
"""
__author__ = "Yizhi Fang"
__version__ = "2017.07.05"
import re
from os.path import joi... | Yizhi-Fang/data_analysis | file_loader.py | file_loader.py | py | 14,195 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "abc.ABCMeta",
"line_number": 37,
"usage_type": "name"
},
{
"api_name": "os.path.join",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "re.search",
"line_number": 60,
"usage_type": "call"
},
{
"api_name": "re.search",
"line_number": 62,... |
41642897835 | from typing import Tuple, Any, List
import pandas as pd
from sklearn.feature_selection import SelectKBest, f_regression
# vanilla feature selection
def select_features(
x_train: pd.DataFrame, y_train: pd.DataFrame,
x_test: pd.DataFrame, k: Any = "all"
) -> Tuple[pd.DataFrame, pd.DataFrame]:
# con... | AlexCawl/DataAnalysisLabs | labs/lab_3/util/regression.py | regression.py | py | 1,184 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "pandas.DataFrame",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "pandas.DataFrame",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "typing.Any",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "sklearn.feature... |
26507182432 | import pandas as pd
import json
dataset_path = "../data/accountData.json"
#transform json to dataframe
def transform_json_to_dataframe(dataset_path):
with open(dataset_path) as json_file:
data = json.load(json_file)
dataset = pd.DataFrame(data)
return dataset
data = transform_json_to_datafram... | soundbond-team/bond | scripts/cleaning_data.py | cleaning_data.py | py | 943 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "json.load",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 10,
"usage_type": "call"
}
] |
18031309683 | from django import forms
from library.models import Book
from django.forms import NumberInput
# LOCATION_CHOICES = [
# ('MG_ROAD', 'MG Road'),
# ('Karkhana', 'Karkhana'),
# ('Hitech_City', 'Hi-Tech City'),
# ]
# ISSUE_CHOICES = [
# ('available', 'Available'),
# ('issued', 'Issued')... | mayank-gubba/capstone_library_managment_system | crud_project/library/forms.py | forms.py | py | 993 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "django.forms.ModelForm",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "django.forms",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "django.forms.MultipleChoiceField",
"line_number": 29,
"usage_type": "call"
},
{
"api_nam... |
15485248896 | import requests, os, logging
from datetime import date
from urllib.parse import urlparse
def download_csv():
url = urlConstrutor()
try:
headers = {
'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.102 Safari/537.36'}
... | santhosh6328/bhavcopy | bhavcopy/bhavcopy/app/downloader.py | downloader.py | py | 1,315 | python | en | code | 1 | github-code | 18 | [
{
"api_name": "requests.get",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "urllib.parse.urlparse",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path.basename",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.path",
"li... |
7245964577 | #!/usr/bin/env python3
#By Marcus Chan
#Last Updated 2020-08-20
#Required Libraries: psycopg2
#Purpose:To create a conviennient wrapper for psycopg2 and create a few other functions to interact with observing things
# from the database
import psycopg2
class db_interactions:
""" This class will be ... | MKC-testcase/stock_extract | db_operations/PostgreSQL_analysis.py | PostgreSQL_analysis.py | py | 4,819 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "psycopg2.connect",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "psycopg2.connect",
"line_number": 99,
"usage_type": "call"
}
] |
26952840019 | import abc
from pathlib import Path
from typing import Dict, List, Optional, Union
import numpy as np
import pandas as pd
from brainstat.stats.SLM import SLM
from brainstat.stats.terms import FixedEffect
from nilearn.surface import Mesh
from clinica.utils.stream import cprint
from ._contrast import Contrast
from ._u... | aramis-lab/clinica | clinica/pipelines/statistics_surface/surfstat/models/_base.py | _base.py | py | 7,598 | python | en | code | 196 | github-code | 18 | [
{
"api_name": "pandas.DataFrame",
"line_number": 64,
"usage_type": "attribute"
},
{
"api_name": "typing.Optional",
"line_number": 67,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 68,
"usage_type": "name"
},
{
"api_name": "typing.Optional... |
74595230120 | import torch
from torch import nn
import torch.nn.functional as F
import errno
import hashlib
import os
import warnings
import re
import shutil
import sys
import tempfile
from tqdm import tqdm
from urllib.request import urlopen
from urllib.parse import urlparse # noqa: F401
def _download_url_to_file(url, dst, hash_p... | CanPeng123/FSCIL_ALICE | alice/model/model_factory.py | model_factory.py | py | 9,251 | python | en | code | 22 | github-code | 18 | [
{
"api_name": "urllib.request.urlopen",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 31,
"usage_type": "attribute"
},
{
"api_name": "tempfile.NamedTem... |
23530078640 | from collections import deque
from htm.bindings.regions.PyRegion import PyRegion
from .import extractList, asBool
class RawValues(PyRegion):
"""
RawValues is a simple region used to send raw scalar values into networks.
It accepts data using the command 'addDataToQueue' or through the function
addDa... | jgab3103/Jamie-Gabriel | Archived/Notebooks/jovyan/.local/lib/python3.8/site-packages/htm.core-2.1.15-py3.8-linux-x86_64.egg/htm/advanced/regions/RawValues.py | RawValues.py | py | 3,547 | python | en | code | 2 | github-code | 18 | [
{
"api_name": "htm.bindings.regions.PyRegion.PyRegion",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "collections.deque",
"line_number": 20,
"usage_type": "call"
}
] |
4526616769 | import sys
import gurobipy as gp
from gurobipy import GRB
import networkx as nx
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import math
import csv
import pandas as pd
import time
"""
Parameters:
G - edge list of original graph; dtype
r - root node
size - num... | dominicflocco/Graph_Pebbling | py/tree_opt_sym.py | tree_opt_sym.py | py | 12,572 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "matplotlib.use",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "gurobipy.Model",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "gurobipy.GRB.Param",
"line_number": 52,
"usage_type": "attribute"
},
{
"api_name": "gurobipy.GRB",
... |
73250170600 | # -*- coding: utf-8 -*-
"""
seen plugin: Traks user sightings in MUC.
"""
__author__ = "Petr Morávek (xificurk@gmail.com)"
__copyright__ = ["Copyright (C) 2007 Kevin Smith",
"Copyright (C) 2009-2011 Petr Morávek"]
__license__ = "GPL 3.0"
__version__ = "0.5.0"
import logging
import time
log = logg... | xificurk/keelsbot | plugins/seen.py | seen.py | py | 6,357 | python | en | code | 4 | github-code | 18 | [
{
"api_name": "logging.getLogger",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 66,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 73,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": ... |
41953315758 | from keras.models import Sequential, load_model
from keras.layers.core import Dense, Dropout, Flatten
from keras.layers.advanced_activations import LeakyReLU
from keras.layers.convolutional import Conv2D
from keras.preprocessing.image import ImageDataGenerator
from keras.layers.pooling import MaxPooling2D
from ke... | baptistepouthier/plancton | CNN/CNN.py | CNN.py | py | 5,686 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "keras.models.Sequential",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "keras.layers.convolutional.Conv2D",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "keras.layers.advanced_activations.LeakyReLU",
"line_number": 35,
"usage_type": ... |
32580158614 | import os
from sqlalchemy import Column, Integer, MetaData, String, Table, create_engine
from databases import Database
DATABASE_URI = os.getenv("DATABASE_URI")
engine = create_engine(DATABASE_URI)
metadata = MetaData()
authors = Table(
"authors",
metadata,
Column("id", Integer, primary_key=True),
Co... | Plaoo/library-microservices-example | author-service/app/api/db.py | db.py | py | 538 | python | en | code | 3 | github-code | 18 | [
{
"api_name": "os.getenv",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.create_engine",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.MetaData",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.Table"... |
43397689648 | import requests
from pprint import pprint
import json
token = '10796cf210796cf210796cf2b9100a74631107910796cf24f6a15c243a53fbe860107c9'
version = 5.92
domain = 'aquataz'
response = requests.get('https://api.vk.com/method/wall.get',
params={
'access_token' : token,
... | AntonSlivaev/Data_parsing | lesson_1/2_task.py | 2_task.py | py | 610 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "requests.get",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pprint.pprint",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 20,
"usage_type": "call"
}
] |
4162748545 | import numpy as np
import numpy.random as npr
import matplotlib.pyplot as plt
from sklearn.datasets import make_blobs
from sklearn.datasets import make_moons
from matplotlib.patches import Ellipse
from sklearn.mixture import GaussianMixture
#source: https://github.com/UBC-CS/cpsc340/blob/master/lectures/L8demo.ipynb
d... | MohamedAbdelsalam9/CIE417 | Tutorials/Lab8_Clustering/lab8_functions.py | lab8_functions.py | py | 2,952 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "numpy.any",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.scatter",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "numpy.any",
... |
39904670945 | import streamlit as st
import pandas as pd
import numpy as np
st.set_page_config(layout="wide")
st.title("Experiment Results using One-class SVM and Gaussian Mixture Model \
from Scikit-learn")
select_slide = st.sidebar.selectbox(
"Which slide would you like to navigate to?",
("One-class SVM", "Gaussian... | C190194/Streamlit_W7_OCSVM_GMM | slides.py | slides.py | py | 2,893 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "streamlit.set_page_config",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "streamlit.title",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "streamlit.sidebar.selectbox",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "s... |
27542888829 | #第 0014 题： 纯文本文件 student.txt为学生信息, 里面的内容（包括花括号）如下所示：
#{
# "1":["张三",150,120,100],
# "2":["李四",90,99,95],
# "3":["王五",60,66,68]
#}
#请将上述内容写到 student.xls 文件中，如下图所示：
import pandas as pd
import json
import win32api
filepath = "data/Student.txt"
f = open(filepath)
s = f.read()
s = json.loads(s)
df = pd.DataFrame(s)
df = df.... | ga0404/python_project | ex_0014/ex_0014.py | ex_0014.py | py | 562 | python | zh | code | 0 | github-code | 18 | [
{
"api_name": "json.loads",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "win32api.ShellExecute",
"line_number": 18,
"usage_type": "call"
}
] |
29681019110 | from bs4 import BeautifulSoup
import re
import sys
# Check if the start of a post claims it is reserved, then remove that line.
def joinPosts(posts):
return '<br>'.join([str(tag) for tag in posts])
args = sys.argv
html_doc = open(args[1],'rb')
text = html_doc.read().decode(errors='replace')
text.replace('\uFFFD',... | MarkovChainmail/dnd_3.5_library | scripts/bgparser.py | bgparser.py | py | 498 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "sys.argv",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 16,
"usage_type": "call"
}
] |
27930009415 | import collections
import sys
input = sys.stdin.readline
#sys.stdin = open('./input.txt')
n, m = map(int, input().split())
num_to_pokemon = collections.defaultdict(str)
pokemon_to_num = collections.defaultdict(int)
for i in range(1, n + 1):
input_pokemon = input().strip()
num_to_pokemon[i] = input_poke... | Yuha0123/Algorithm | BOJ/1620.py | 1620.py | py | 544 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "sys.stdin",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "collections.defaultdict",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "collections.defaultdict",
"line_number": 10,
"usage_type": "call"
}
] |
15317263848 | from collections import deque
di = [0,0,1,-1,1,-1,1,-1]
dj = [1,-1,0,0,1,-1,-1,1]
n, m = map(int,input().split())
a = [list(map(int,input().split())) for _ in range(n)]
def solve(x,y):
d = [[-1] * m for _ in range(n)]
d[x][y] = 0
q = deque()
q.append((x,y))
while q:
i, j = q.popleft()
... | cldud400/python-coding-test | 문제풀이/17086.py | 17086.py | py | 819 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "collections.deque",
"line_number": 11,
"usage_type": "call"
}
] |
33089612264 | from __future__ import absolute_import, print_function
from django.core import mail
from sentry.models import AuthProvider, OrganizationMember
from sentry.testutils import TestCase
from sentry.tasks.auth import email_missing_links, email_unlink_notifications
class EmailMissingLinksTest(TestCase):
def setUp(self... | fictional-tribble-2/getsentry--sentry | tests/sentry/tasks/test_auth.py | test_auth.py | py | 1,545 | python | en | code | 1 | github-code | 18 | [
{
"api_name": "sentry.testutils.TestCase",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "sentry.models.AuthProvider.objects.create",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "sentry.models.AuthProvider.objects",
"line_number": 15,
"usage_type":... |
72998975720 | # -*- coding: utf-8 -*-
import os
import warnings
from Marketingtool.common import path_leaf
warnings.filterwarnings("ignore", message=".*The 'nopython' keyword.*")
# warnings.simplefilter('ignore', category=NumbaDeprecationWarning)
# warnings.simplefilter('ignore', category=NumbaPendingDeprecationWarning)
import whis... | robertzengcn/Marketingtool | Marketingtool/modules/audioprocess.py | audioprocess.py | py | 2,053 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path.exists",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "os.path.isdir",
... |
32639548531 | import os.path
import serial
print(serial.__file__),
import pyrebase
from time import time, sleep
from datetime import datetime
config = { #firebase authentification
"apiKey": "AIzaSyDEfkwr7Zl5WucXFluMxB8VIlngUnp7aDM",
"authDomain": "smv-daq.firebaseapp.com",
"databaseURL": "https://smv-daq.firebaseio.com... | Bruin-SuperMileage/EV | daq/panda/test/testScript.py | testScript.py | py | 3,896 | python | en | code | 5 | github-code | 18 | [
{
"api_name": "serial.__file__",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "pyrebase.initialize_app",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "serial.Serial",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "time.time",... |
15784565363 | """
Created on Tue Jan 18 15:44:39 2022
Prepare depth-dependent in house sens. and spec. and EPI for cvessel detection (BOLD_mean.nii)
@author: apizz
"""
import os
import numpy as np
import nibabel as nb
import matplotlib.pyplot as plt
STUDY_PATH = "D:\\Pilot_Exp_VASO\\pilotAOM"
SUBJ = ['sub-02', 'sub-03', 'sub-04... | 27-apizzuti/AOM-VASO_project | VASO_analysis/archive/layers_TO_REMOVE/metrics/3_compute_depth_in_house_metrics.py | 3_compute_depth_in_house_metrics.py | py | 3,504 | python | en | code | 2 | github-code | 18 | [
{
"api_name": "os.path.join",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 26,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 2... |
5043884847 | from django.shortcuts import render
from django.http import HttpResponse
from .models import Post
posts = [
{
'author' : 'Jakub Kazimierski',
'title' : 'First post',
'content' : 'First tweet',
'date_posted' : 'January 28 2021',
},
{
'author' : 'Jaku... | Sibusiso-Mgidi/PythonPortfolio | Django/Django_blog/blog/views.py | views.py | py | 810 | python | en | code | null | github-code | 18 | [
{
"api_name": "models.Post.objects.all",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "models.Post.objects",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "models.Post",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "django.s... |
36519668920 | from random import choice, random, sample
import numpy as np
import networkx as nx
from BanditAlg.BanditAlgorithms import ArmBaseStruct
import datetime
class LinUCBUserStruct:
def __init__(self, featureDimension,lambda_, userID, RankoneInverse = False):
self.userID = userID
self.d = featureDimension
self.A = la... | HCDM/BanditLib | OnlineInfluenceMaximization/BanditAlg/DILinUCB.py | DILinUCB.py | py | 4,675 | python | en | code | 314 | github-code | 18 | [
{
"api_name": "numpy.identity",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.linalg.inv",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.linalg",
"line_... |
14458050873 | # Ahmed El Fekih
# aelfekih
# user interface + AI
from tkinter import *
from chess import Chess
import random
from tkinter import messagebox
LIGHTCOLOR = '#feffed'
## GUI
## User interface test
class mainMenu:
def __init__(self):
self.wnd = Tk()
self.wnd.title('Chess Game')
... | ahmed-el-fekih/chess-game | GUI+AI.py | GUI+AI.py | py | 19,677 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "chess.Chess",
"line_number": 42,
"usage_type": "name"
},
{
"api_name": "chess.Chess.__init__",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "chess.Chess",
"line_number": 44,
"usage_type": "name"
},
{
"api_name": "random.randint",
"li... |
34663254189 | import os
import click
import socket
import time
import ciphers, packet, mac
from sealed_object import SealedObject
from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
from cryptography.hazmat.primitives.serialization import load_der_private_key
from cryptography.hazmat.backends import default_... | diogom93/ssre | tut8/client.py | client.py | py | 3,128 | python | en | code | 1 | github-code | 18 | [
{
"api_name": "socket.socket",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "socket.AF_INET",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "socket.SOCK_STREAM",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "click.echo"... |
70790249960 | import cv2
import numpy as np
from matplotlib import pyplot as plt
from scipy.fftpack import dct, fft
from skimage import color, data, restoration
def gkern(l=5, sig=1.):
"""
creates gaussian kernel with side length l and a sigma of sig
"""
# código sacado de : https://stackoverflow.com/questions/29731... | fprebolledo/procesamiento-imagenes | T3/t3.py | t3.py | py | 5,585 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "numpy.linspace",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.meshgrid",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.exp",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.square",
"line_numb... |
13843404702 | # -*- coding: utf-8 -*-
import os
import pickle
import numpy as np
import tempfile
from cytomine_sldc import TileCache
from sklearn.utils import check_random_state
from sldc import PolygonClassifier, TileExtractionException, Loggable, SilentLogger, Logger
__author__ = "Mormont Romain <romain.mormont@gmail.com>"
__ve... | cytomine/Cytomine-python-datamining | cytomine-datamining/algorithms/sldc/examples/with_pyxit/pyxit_classifier.py | pyxit_classifier.py | py | 5,219 | python | en | code | 20 | github-code | 18 | [
{
"api_name": "sldc.TileExtractionException",
"line_number": 44,
"usage_type": "name"
},
{
"api_name": "sldc.PolygonClassifier",
"line_number": 49,
"usage_type": "name"
},
{
"api_name": "sldc.Loggable",
"line_number": 49,
"usage_type": "name"
},
{
"api_name": "sld... |
42569043137 | import os
import xlwt
#定位到文件所在位置
a = os.getcwd() #获取当前目录
print (a) #打印当前目录
os.chdir('C:/Users/User/OneDrive/Miniature tripod/Test result/autocollimator drifting test') #定位到新的目录
a = os.getcwd() #获取定位之后的目录
print(a) #打印定位之后的目录
input='drifting_data'
output='output'
dataset='7'
#读取目标txt文件里的内容，并且打印出来显示
#with open... | julis-wolala/TextdataHandler | measurement data analysis/measurement data analysis/measurement_data_analysis.py | measurement_data_analysis.py | py | 2,151 | python | zh | code | 2 | github-code | 18 | [
{
"api_name": "os.getcwd",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "os.chdir",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.getcwd",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "xlwt.Workbook",
"line_number": 25,
... |
71729218281 | from uuid import uuid4
from .mtom_attachment import MtomAttachment
from .soap_envelope import SoapEnvelope
class XopPackage:
def __init__(self, soap_env: SoapEnvelope, files: list[MtomAttachment]) -> None:
"""Represents the XOP package that is sent as the request body.
Args:
soap_env... | Gebrel07/pymtom-xop | pymtom_xop/xop_package.py | xop_package.py | py | 1,297 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "soap_envelope.SoapEnvelope",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "mtom_attachment.MtomAttachment",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "soap_envelope.SoapEnvelope",
"line_number": 15,
"usage_type": "name"
},
{
... |
72655123559 | from flask import url_for
from pytest import mark
FAV_URLS = ("/favicon.png", "/favicon.ico", "/logo.png")
@mark.usefixtures("ctx_app")
def test_favicon_url():
assert url_for("side.favicon") == FAV_URLS[0]
assert url_for("side.logo") == FAV_URLS[-1]
def test_favicon_content(client):
org = client.get(ur... | spookey/shorter | tests/views/test_side_favicon.py | test_side_favicon.py | py | 610 | python | en | code | 1 | github-code | 18 | [
{
"api_name": "flask.url_for",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "flask.url_for",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pytest.mark.usefixtures",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pytest.mark",
"... |
72427094119 | from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from .routers import upload_videos, ml_out, download_files
from fastapi.staticfiles import StaticFiles
from .utils import *
app = FastAPI()
make_local_dirs("uploads")
make_local_dirs("summarized")
make_local_dirs("summarized/uploads")
make... | anitoanto/alus-package | alus-backend/server/app.py | app.py | py | 805 | python | en | code | 4 | github-code | 18 | [
{
"api_name": "fastapi.FastAPI",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "fastapi.middleware.cors.CORSMiddleware",
"line_number": 15,
"usage_type": "argument"
},
{
"api_name": "routers.upload_videos.router",
"line_number": 22,
"usage_type": "attribute"
}... |
40563634860 | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 29 00:40:22 2020
@author: lenovo
"""
import unittest
from HTMLTestRunner import HTMLTestRunner
import time
import yagmail
#把测试报告作为附件发送到指定邮箱
def send_mail(report):
yag=yagmail.SMTP(user="wl15176128570@126.com",
password="HGDFAIMHMWDKQYWJ",
... | wangli-wangli/python-test | htmlReport/run_tests.py | run_tests.py | py | 1,179 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "yagmail.SMTP",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "unittest.defaultTestLoader.discover",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "unittest.defaultTestLoader",
"line_number": 27,
"usage_type": "attribute"
},
{
"... |
34614621754 | from django.db.models import Count, Min, Sum
from datetime import datetime
from . import exceptions
from wallet.models import AccountEntry
def get_account_balance(account_id):
debits = AccountEntry.objects.filter(
account__id=account_id,
transaction__transaction_type="debit"
).values('amount'... | ianbwana/walletcore | wallet/utils.py | utils.py | py | 900 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "wallet.models.AccountEntry.objects.filter",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "wallet.models.AccountEntry.objects",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "wallet.models.AccountEntry",
"line_number": 9,
"usage_typ... |
16342404111 | from . import views
from django.urls import path
urlpatterns = [
path('home/', views.home, name="home"),
path("hotels/", views.getListOfHotels, name="getListOfHotels"),
path("reserve/", views.reservationConfirmation, name="reservationConfirmation"),
path("hotel_list/<str:pk>", views.Hotels_detail, nam... | A00453840/A00453840_5550 | BookMyRoom/BookMyRoomApp/urls.py | urls.py | py | 339 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "django.urls.path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
... |
42770042703 | import bpy
from . import overScan
from . import tiltshift
from . import draw_ui
# -----------------------------------------------------------------------------
# 登録クラス名のリスト
classes = (
tiltshift.QANIM_OT_tiltshift_vertical_auto_detection,
tiltshift.QANIM_OT_tiltshift_horizontal_auto_detection,
overScan.... | Project-StudioQ/camera_extends | camera.py | camera.py | py | 845 | python | en | code | 2 | github-code | 18 | [
{
"api_name": "bpy.utils.register_class",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "bpy.utils",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "bpy.utils.unregister_class",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "bp... |
34090262744 | """
A freely-propagating, premixed hydrogen flat flame with multicomponent
transport properties.
Requires: cantera >= 2.5.0
"""
import cantera as ct
try:
import pandas as pd
import tables
except:
pd = None
# Simulation parameters
p = ct.one_atm # pressure [Pa]
Tin = 300.0 # unburned gas temperature [K]... | trollchu/cantera | interfaces/cython/cantera/examples/onedim/adiabatic_flame.py | adiabatic_flame.py | py | 1,659 | python | en | code | null | github-code | 18 | [
{
"api_name": "cantera.one_atm",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "cantera.Solution",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "cantera.FreeFlame",
"line_number": 28,
"usage_type": "call"
}
] |
5681856009 | # -*- coding: cp936 -*-
from selenium import webdriver
from selenium.common.exceptions import NoSuchElementException,ElementNotVisibleException
from selenium.webdriver.common.keys import Keys
import time
def NewUnloadTask(self,platform,billno,employee):
try:
self.logger.info("开始测试新增卸车任务......")
... | gaoli11/ssauto | src/Deppon/Web/Business/UnloadManage/NewUnloadTask.py | NewUnloadTask.py | py | 2,122 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "time.sleep",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver.common.keys.Keys.... |
39123446521 | import datetime
import difflib
from django.shortcuts import render_to_response, get_object_or_404, redirect
from django.template import RequestContext
from django.core.paginator import Paginator, InvalidPage, EmptyPage
from django.http import Http404
from django.template.defaultfilters import slugify
from django.contr... | kaedroho/Django-Wiki | views.py | views.py | py | 4,439 | python | en | code | 1 | github-code | 18 | [
{
"api_name": "django.shortcuts.get_object_or_404",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "models.Page",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "django.http.Http404",
"line_number": 21,
"usage_type": "name"
},
{
"api_name"... |
71427002600 | # This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load in
import numpy as np # linear algebra
import pandas as pd # data processing, CSV fil... | aorursy/new-nb-3 | hakabuk_random-forest-with-more-numeric-features.py | hakabuk_random-forest-with-more-numeric-features.py | py | 3,467 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "pandas.options",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "subprocess.check_output",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "pandas.read_json",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "pandas.t... |
43392979458 | #!/usr/bin/env python3
from parsl import App, IPyParallelExecutor, DataFlowKernel
import os
from parsl.dataflow.futures import Future
from parsl.execution_provider.midway.slurm import Midway
"""From now on, the tutorial applications are written to run on Midway,
a cluster located at the University of Chicago Research... | benhg/job-classification | data-generation/scripts/p7.py | p7.py | py | 2,310 | python | en | code | 1 | github-code | 18 | [
{
"api_name": "parsl.IPyParallelExecutor",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "parsl.DataFlowKernel",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "parsl.execution_provider.midway.slurm.Midway",
"line_number": 31,
"usage_type": "call"
}... |
10812390884 | import json
import onnxruntime as ort
import re
import numpy as np
class Predictor:
RE = "[абвгдеёжзийклмнопрстуфхцчшщьыъэюя'\u0301]+"
def __init__(self, onnx_model, vocab, data_dict):
self._ml_predictor = MLPredictor(onnx_model, vocab)
self._vocab_predictor = VocabPredictor(data_dict)
de... | slavonic/translator | accentru/predictor.py | predictor.py | py | 3,786 | python | en | code | 5 | github-code | 18 | [
{
"api_name": "onnxruntime.InferenceSession",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "numpy.int32",
... |
10361611270 | from app.data_managers import places_data_manager, event_data_manager
from geojson import Point
from app.data_managers.places_data_manager import PlaceDataManager
from app.data_managers.event_data_manager import EventDataManager
import time
def create_place1():
proto = places_data_manager.min_place_dict
pla... | waltyellow/project-clipper-2 | app/test_data/places and events.py | places and events.py | py | 4,654 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "app.data_managers.places_data_manager.min_place_dict",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "app.data_managers.places_data_manager",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "geojson.Point",
"line_number": 14,
"usage... |
6221432347 | from common.decorators import params_valid
from common.transaction import auto_meta_sync
from common.views import APIViewSet
from rest_framework.response import Response
from meta import exceptions as meta_errors
from meta.public.models.data_transferring import DataTransferring
from meta.public.serializers.common impo... | Tencent/bk-base | src/api/meta/public/views/data_transferring.py | data_transferring.py | py | 11,873 | python | en | code | 85 | github-code | 18 | [
{
"api_name": "common.views.APIViewSet",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "meta.utils.basicapi.parseresult.escape_string",
"line_number": 81,
"usage_type": "call"
},
{
"api_name": "meta.utils.basicapi.parseresult",
"line_number": 81,
"usage_type": ... |
29487024555 | import pygame
import os
from subprocess import call
pygame.init()
class Door:
def __init__(self, surface, subject, file):
self.door_sprite = pygame.image.load(os.path.join("assets", "door_sprite.png"))
self.subject = subject
self.text = subject
self.display_surface = surface
... | gitTanzj/aasta-tegija | game_files/door.py | door.py | py | 1,554 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "pygame.init",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pygame.image.load",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pygame.image",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line... |
21064701631 | from datetime import date
from src.lib.parser import MeetupEvent, get_event
from telegram import Bot, ChatAction, Message, ParseMode
DATE_FORMAT = "%A, %-d %B %Y %-I:%M %p" # e.g. Monday, 7 March 2022 7:00 PM
REMINDER_TEMPLATE = """
Please RSVP to the following event:
<b>Event:</b> <a href="{url}">{title}</a>
... | zegheim/meetup-reminder-bot | src/lib/bot.py | bot.py | py | 2,062 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "telegram.Bot",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "src.lib.parser.MeetupEvent",
"line_number": 24,
"usage_type": "name"
},
{
"api_name": "datetime.date",
"line_number": 42,
"usage_type": "name"
},
{
"api_name": "src.lib.parser.... |
23221220836 | from models.GridEval import GridEval
from sklearn import tree
class DecisionTree(GridEval):
"""run the Decision Tree model
"""
def decisionRunGrid(self, classWeight = None):
"""Set the parameters to select from for Random Grid Search
Output:
the best model returned by random grid s... | regap4693/BINARY-CLASSIFICATION | models/DecisionTree.py | DecisionTree.py | py | 1,480 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "models.GridEval.GridEval",
"line_number": 3,
"usage_type": "name"
},
{
"api_name": "sklearn.tree.DecisionTreeClassifier",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "sklearn.tree",
"line_number": 22,
"usage_type": "name"
},
{
"api_name... |
34655646875 | """
A confederação de natação precisa de um programa que leia o ano de nascimento e mostre a categoria
ate 9 anos Mirim
até 14 anos Infantil
até 19 anos Junior
ate 20 anos Senior
acima Master
"""
import datetime
nascimento = int(input('Ano de nascimento:'))
ano_atual = datetime.date.today().year
idade = ano_atual - nas... | GustinSilva/python | aprendi com guanabara/Ex 041.py | Ex 041.py | py | 742 | python | pt | code | 0 | github-code | 18 | [
{
"api_name": "datetime.date.today",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "datetime.date",
"line_number": 11,
"usage_type": "attribute"
}
] |
13053327663 | from pymongo import MongoClient
from bson.objectid import ObjectId
import logger2
import random
c = MongoClient()
db = c['alkows']
# === ADDING === #
def add_creature_species(sp):
logger2.logger.debug("add_creature_species")
db.bestiary.insert_one(sp)
def add_flora_species(fsp):
logger2.logger.debug("ad... | lmstock/AllCowsEatGrass | bartokmongo.py | bartokmongo.py | py | 10,476 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "pymongo.MongoClient",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "logger2.logger.debug",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "logger2.logger",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "logger2.l... |
27274684990 | #!/usr/bin/env python
import atexit
import csv
import inspect
import json
import logging
import os
import signal
import sys
import time
import click
import panapi
from panapi.config import \
iam, \
security, \
identity, \
objects, \
network, \
subscription, \
tenancy, \
mobile
__author... | ancoleman/prisma-access-config-exporter | src/main.py | main.py | py | 15,074 | python | en | code | 2 | github-code | 18 | [
{
"api_name": "logging.DEBUG",
"line_number": 37,
"usage_type": "attribute"
},
{
"api_name": "logging.INFO",
"line_number": 37,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "logging.Format... |
35880605789 | from django.conf.urls import url
from . import views
urlpatterns = [
url(r'^$', views.index, name='index'),
url(r'^step/', views.physics_step, name='physics_step'),
url(r'^engine/', views.fire_engine, name='fire_engine'),
url(r'^thruster/', views.fire_thruster, name='fire_thruster'),
url(r'^ship/', views.ship_vie... | nthieu173/astraios | astraios (deployment)/asteroid_field/urls.py | urls.py | py | 399 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "django.conf.urls.url",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.co... |
74553119078 | from django.contrib.auth.models import AbstractUser
from django.db import models
from .enums import Role
class User(AbstractUser):
REQUIRED_FIELDS = ('first_name', 'last_name', 'username',)
USERNAME_FIELD = 'email'
ROLES = [
('user', Role.USER),
('admin', Role.ADMIN),
]
email = m... | ObdulTipov/foodgram-project-react | backend/users/models.py | models.py | py | 1,142 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "django.contrib.auth.models.AbstractUser",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "enums.Role.USER",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "enums.Role",
"line_number": 11,
"usage_type": "name"
},
{
"api_name":... |
32423076063 | from enum import Enum
from os import getcwd
from os.path import expanduser
from typing import Union, List, Iterable
try:
# noinspection PyPackageRequirements
import wx
# noinspection PyPackageRequirements
from wx.lib.agw import multidirdialog as mdd
except ImportError:
wx, mdd = None, None
rais... | Palpatineli/uifunc | uifunc/wxopen.py | wxopen.py | py | 3,310 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "wx.lib.agw.multidirdialog",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "enum.Enum",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "typing.Union",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "typing.List",
"l... |
73026906599 |
__all__ = ['ANTsImage',
'LabelImage',
'copy_image_info',
'set_origin',
'get_origin',
'set_direction',
'get_direction',
'set_spacing',
'get_spacing',
'image_physical_space_consistency',
'image_type_cast',
... | ANTsX/ANTsPy | ants/core/ants_image.py | ants_image.py | py | 33,134 | python | en | code | 499 | github-code | 18 | [
{
"api_name": "numpy.asarray",
"line_number": 192,
"usage_type": "call"
},
{
"api_name": "numpy.ndarray",
"line_number": 194,
"usage_type": "attribute"
},
{
"api_name": "numpy.asarray",
"line_number": 235,
"usage_type": "call"
},
{
"api_name": "numpy.ndarray",
... |
23868537052 | from collections import deque
n, m, v = map(int, input().split())
graph = [[] for _ in range(n)]
v = v - 1
for _ in range(m):
a, b = map(int, input().split())
graph[a - 1].append(b - 1)
graph[b - 1].append(a - 1)
for _ in range(n):
graph[_].sort()
def bfs(v):
visited = [0] * n
result = []
... | hipass7/Algorithm_Study | 1차 SW 역량 테스트 대비 (220501)/temp.py | temp.py | py | 950 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "collections.deque",
"line_number": 17,
"usage_type": "call"
}
] |
73034024360 | import argparse
parser = argparse.ArgumentParser()
parser.add_argument("-s", "--solvers",
metavar="solvers[latest solver, earlier solver1,...]",
action="store",
# type = str,
dest="solvers",
default=[],
nargs='+',
... | ConfZ/SPRFinder | src/parser.py | parser.py | py | 2,216 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 2,
"usage_type": "call"
}
] |
71731605480 | import moment
from sqlalchemy.engine import Engine
from sqlalchemy.orm import Session
from sqlalchemy import insert
from model.db.db_orm import (
ContasTipo,
Categorias,
Contas,
Lancamentos,
association_lanc_categ,
)
class DataLoader:
def __init__(self, engine: Engine) -> None:
self.eng... | jaymealonso/py-financas | src/model/initial_load/initial_db_data.py | initial_db_data.py | py | 5,907 | python | pt | code | 0 | github-code | 18 | [
{
"api_name": "sqlalchemy.engine.Engine",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "sqlalchemy.orm.Session",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.insert",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "mod... |
36093901103 | import numpy as np
import torch.nn as nn
from mmcv.cnn import normal_init
from .anchor_head import AnchorHead
from ..registry import HEADS
from ..utils import bias_init_with_prob
@HEADS.register_module
class RetinaHead(AnchorHead):
def __init__(self,
num_classes,
in_channels,
... | shaoqb/multi_scale_booster | mmdet/models/anchor_heads/retina_head.py | retina_head.py | py | 3,917 | python | en | code | 19 | github-code | 18 | [
{
"api_name": "anchor_head.AnchorHead",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "numpy.array",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "torch.nn.ReLU",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line... |
35017209942 | from setuptools import setup
from setuptools import find_packages
import sys
with open("README.md", "r") as fh:
long_description = fh.read()
exec(open("openSAP32/_version.py").read())
setup(
name = 'openSAP32',
packages = find_packages(),
version = __version__,
license='New BSD',
description = 'openSAP32 ... | dukenmarga/openSAP32 | setup.py | setup.py | py | 1,312 | python | en | code | 4 | github-code | 18 | [
{
"api_name": "setuptools.setup",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "setuptools.find_packages",
"line_number": 11,
"usage_type": "call"
}
] |
40038581662 | import re
import pickle
import io
import os.path
import base64
from PIL import Image
from io import BytesIO
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
class Encoder(tf.keras.Model):
def __init__(self, embed_dim):
super(Encoder, self).__init__()
self.den = tf.keras.l... | vladislavalerievich/image-captioner | backend/src/utils/image_captioning.py | image_captioning.py | py | 7,074 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "tensorflow.keras",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.keras.layers.Dense",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_nam... |
23010836101 | import pygame
import time
# import pygame_functions
WIDTH = 1000
HEIGHT = 1000
pygame.init()
screenRefresh = True
background_image = pygame.image.load("plain_bg.jpg")
back_pos = [0,0]
screen = pygame.display.set_mode((WIDTH,HEIGHT))
done = False
class Button(pygame.sprite.Sprite):
def __init__(self,loc):
... | FB-18-19-PreAP-CS/mygame-uwu | game.py | game.py | py | 7,253 | python | en | code | 1 | github-code | 18 | [
{
"api_name": "pygame.init",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pygame.image.load",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pygame.image",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "pygame.display.set_mod... |
7580874884 | from litstudy.types import Document, DocumentSet, DocumentIdentifier, Author
from typing import Optional, List
import feedparser # type: ignore
from datetime import datetime
from urllib.parse import urlencode
import time
class ArXivAuthor(Author):
def __init__(self, entry):
self.entry = entry
@prope... | NLeSC/litstudy | litstudy/sources/arxiv.py | arxiv.py | py | 3,208 | python | en | code | 112 | github-code | 18 | [
{
"api_name": "litstudy.types.Author",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "litstudy.types.Document",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "litstudy.types.DocumentIdentifier",
"line_number": 20,
"usage_type": "call"
},
{
"ap... |
28365184263 | import os.path as osp
import os
import cv2
import numpy as np
import imageio
import glob
from multiprocessing import Pool
from tqdm import tqdm
img_suffix = '_leftImg8bit.png' #img
seg_map_suffix = '_gtFine_labelTrainIds.png' #label
data_root = '/SSD_DISK/datasets/mapillary'
destination... | swimmerQAQ/Segformer_with_different_dataset | label_test/trans_map_to_mmseg.py | trans_map_to_mmseg.py | py | 2,539 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "cv2.imread",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "imageio.v2.imread",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "imageio.v2",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "label_mapping.LMS",
... |
23849637110 | import logging
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
import os
# the secret configuration specific things
if bool(os.environ.get("WEBHOOK", False)):
from sample_config import Config
else:
... | surlogu/mf | bot.py | bot.py | py | 904 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "logging.basicConfig",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "os.environ.get"... |
1895422697 | import re
import logging
import numpy as np
from numpy.core.fromnumeric import shape
import pandas as pd
import matplotlib.pyplot as plt
from typing import List, Dict
class Ranker(object):
def __init__(self, role_vocab_size: int, role_ids: List[int]=None) -> None:
self.role_vocab_size = role_vocab_size
... | Buted/RBDEF | code/statistic/rank.py | rank.py | py | 4,934 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "typing.List",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 45,
"usage_type": "name"
},
{
"api_name": "re.match",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "re.match",
"line_number": 63,
... |
70674924519 | import cv2
cap = cv2.VideoCapture(0)
print('Openning Camera ....')
while True:
ref,frame = cap.read()
cv2.imshow("Camera", frame)
if cv2.waitKey(1) ==13:
break
cap.release()
cv2.destroyAllWindows()
print("finished..") | younisrahman/OpenCvWebCamTest | venv/main.py | main.py | py | 240 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "cv2.waitKey",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "cv2.destroyAllWindows",
"lin... |
75446897639 | # -*- coding: utf-8 -*-
"""
Created on Fri Sep 4 11:15:49 2020
@author: adam
"""
import os
import serial
import time
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import plotly.express as px
from dash.dependencies import Input, Output, State
from... | danammeansbear/OpenCannabisDatabase | PlantProcessingInteractiveDashboard.py | PlantProcessingInteractiveDashboard.py | py | 10,065 | python | en | code | 13 | github-code | 18 | [
{
"api_name": "dash.Dash",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "dash_html_components.Div",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "dash_html_componen... |
21728327402 | import ipdb
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class Swish(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x):
return x * torch.sigmoid(x)
def make_mlp(l, act=nn.LeakyReLU(), tail=[], with_bn=False):
"""makes an MLP... | GFNOrg/EB_GFN | network.py | network.py | py | 819 | python | en | code | 64 | github-code | 18 | [
{
"api_name": "torch.nn.Module",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "torch.sigmoid",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "torch.nn.LeakyReLU",
"l... |
31631406473 | # -*- coding: utf-8 -*-
""" A program to develop a ML model to predict which movie will earn more on
a particular day after training the model on the given records """
# Importing pandas, numpy, matplotlib
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# Importing contextlib module to enhance... | piyush546/Machine-Learning-Bootcamp | Machine Learning programs/Supervised ML programs/Linear Regression Programs/Single Variant Linear Regression/BahubaliDangal.py | BahubaliDangal.py | py | 2,894 | python | en | code | 1 | github-code | 18 | [
{
"api_name": "contextlib.suppress",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "sklearn.exceptions.NotFittedError",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "pandas.read_csv",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": ... |
32454344553 | from unittest.mock import patch, Mock
from snowflake.services.google_auth import UserInfo, get_user_info
@patch('snowflake.services.google_auth.verify_oauth2_token')
def test_get_user_info_parses_token(mock_verify_outh2_token: Mock, app):
with app.app_context():
account_id = 'd8708828-6a01-4b7e-ab15-bc48... | snowflake-app/snowflake | tests/services/test_google_auth.py | test_google_auth.py | py | 906 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "unittest.mock.Mock",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "snowflake.services.google_auth.get_user_info",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "snowflake.services.google_auth.UserInfo",
"line_number": 20,
"usage_type":... |
37935230310 | from django.urls import path, include
from blogttm import views
from django.views.generic import RedirectView
urlpatterns = [
path('', views.main, name='main'),
path('git/', views.Git, name= 'Git'),
path('git/<int:pk>/', views.posting, name= 'Gitdetail'),
path('DataAnalysis/', views.DataAnalysis, name=... | seongjaeBA/ToTheMoon | blogttm/urls.py | urls.py | py | 826 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "django.urls.path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "blogttm.views.main",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "blogttm.views",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "django.urls.path"... |
73485386280 | #!/usr/bin/env python3
import tensorflow as tf
from tensorflow import keras
import numpy as np
import matplotlib.pyplot as plt
import os
import cv2
import pygame, sys
mnist = keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train = keras.utils.normalize(x_train, axis=1)
x_test = keras.... | julian-baumann/number-recognition | drawing.py | drawing.py | py | 2,307 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "tensorflow.keras.datasets",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.keras",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "tensorflow.keras.utils.normalize",
"line_number": 14,
"usage_type": "call"
},
{
"... |
15319063550 | #!/usr/bin/env python
from kivy.app import App
from kivy.uix.label import Label
from convert import ToolKitms
from kivy.uix.button import Button
from kivy.uix.scrollview import ScrollView
from kivy.uix.gridlayout import GridLayout
from kivy.uix.boxlayout import BoxLayout
from kivy.config import Config
from kivy.uix.che... | Mateusmsouza/PyConnections | main.py | main.py | py | 3,796 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "kivy.config.Config.set",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "kivy.config.Config",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "kivy.config.Config.set",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "kivy... |
27860596585 | """
Script for investigating whether we can find diagnostic ITS2 sequences that can 'predict' host genotypes as determined by Didier
First approach is simply to look for single diagnostic sequences. This means that for each ITS2 sequences we look to
see if it is present in all samples of a given host grouping but not p... | didillysquat/tara_full_dataset_processing | host_diagnostic_ITS2/host_diagnostic_ITS2.py | host_diagnostic_ITS2.py | py | 21,533 | python | en | code | 1 | github-code | 18 | [
{
"api_name": "matplotlib.use",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number":... |
10809706090 | #! /usr/bin/env python3
# -*- coding: UTF-8 -*-
import json
import sys
import time
class TraceReader:
''' Trace reader just… reads a trace!
This is the master class (interface), herited to get events from
different sources: serial, gdb, file (json)…
It provides a generator to send even... | TrampolineRTOS/trampoline | extra/trace-tools/TraceReader.py | TraceReader.py | py | 10,624 | python | en | code | 549 | github-code | 18 | [
{
"api_name": "json.load",
"line_number": 120,
"usage_type": "call"
},
{
"api_name": "sys.exit",
"line_number": 124,
"usage_type": "call"
},
{
"api_name": "sys.exit",
"line_number": 151,
"usage_type": "call"
},
{
"api_name": "threading.Event",
"line_number": 1... |
71427345960 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import plotly_express as px
sns.set_palette('husl')
sns.set_style("whitegrid")
from sklearn.decomposition import PCA
from sklearn.preprocessing import MinMaxScaler, StandardScaler, LabelEncoder, PowerTransformer
... | aorursy/new-nb-3 | imdevskp_bike-sharing-prediction.py | imdevskp_bike-sharing-prediction.py | py | 5,570 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "seaborn.set_palette",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "seaborn.set_style",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "pandas.to_datet... |
72154376361 | import dask.dataframe as dd
from dask.distributed import Client
from dask_cloudprovider.aws import EC2Cluster
import pandas as pd
import numpy as np
import timeit
import configparser
import os
import contextlib
from dotenv import load_dotenv
load_dotenv()
def get_aws_credentials():
parser = configparser.RawConfi... | alejohz/mineria | tests/dask_etl.py | dask_etl.py | py | 2,560 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "dotenv.load_dotenv",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "configparser.RawConfigParser",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.path.expanduser",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os... |
15646708146 | """
author: Roman Kutlak <roman@kutlak.net>
Based on the Abstract Argumentation Library by
Mikolaj Podlaszewski <mikolaj.podlaszewski@gmail.com>
"""
import copy
import json
import logging
from collections import defaultdict
from .common import IllegalArgument, MethodNotApplicable
from .kb import Literal... | roman-kutlak/argulib | argulib/aal.py | aal.py | py | 22,575 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "logging.getLogger",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "kb.KnowledgeBase",
"line_number": 118,
"usage_type": "call"
},
{
"api_name": "collections.defaultdict",
"line_number": 119,
"usage_type": "call"
},
{
"api_name": "signals.... |
21712294926 | import cv2
import numpy as np
# 검출할 영역(관심영역)의 가로,세로 크기 지정. <175 x 125 = 21,875 사각형 면적 크기>
ROI_w = 175
ROI_h = 125
# ROI 좌표 지정.
ROI_list = [
[(1300, 5)], # 까지 첫번째 줄
[(5, 150)],
[(250, 150)],
[(500, 150)],
[(750, 150)],
[(990, 150)],
[(1235, 150)], # 까지 두번째줄
[(340, 340)],
[(620, 34... | lyj911111/OpenCV_Project | _AceVision_testcodes/Bonding_area_detect_본드칠영역탐지_합불여부/detect_green_bondingArea.py | detect_green_bondingArea.py | py | 6,482 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "cv2.bitwise_not",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "cv2.threshold",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "cv2.THRESH_BINARY_INV",
"line_number": 45,
"usage_type": "attribute"
},
{
"api_name": "cv2.imshow",... |
18567641881 | import torch
class RankSort(torch.autograd.Function):
@staticmethod
def forward(ctx, logits, targets, delta_RS=0.50, eps=1e-10):
classification_grads=torch.zeros(logits.shape).cuda()
#Filter fg logits
fg_labels = (targets > 0.)
fg_logits = logits[fg_labels]
fg... | kemaloksuz/RankSortLoss | mmdet/models/losses/ranking_losses.py | ranking_losses.py | py | 10,356 | python | en | code | 233 | github-code | 18 | [
{
"api_name": "torch.autograd",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "torch.zeros",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "torch.min",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "torch.zeros",
"line_numbe... |
17716811023 | import os,json,csv,re
import pandas as pd
import xml.etree.ElementTree as et
class bcolors:
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKCYAN = '\033[96m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
class DISCO_Re... | comacrae/disco-reader | reader.py | reader.py | py | 13,087 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "os.path.abspath",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 45,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_numb... |
23951822215 | from django.db import models
from django.contrib.auth.models import User
from django.utils.translation import ugettext_lazy as _
class BlackLists(models.Model):
user = models.ForeignKey(User, related_name='blacklist', verbose_name=_('user'))
shielding = models.ForeignKey(User, related_name='shielding', verbos... | danielliude/reismann_pub | blacklists/models.py | models.py | py | 488 | python | en | code | 0 | github-code | 18 | [
{
"api_name": "django.db.models.Model",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "django.db.models",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "django.db.models.ForeignKey",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": ... |
13590668438 |
from sklearn import linear_model
from sklearn.preprocessing import StandardScaler
import numpy as np
data=np.loadtxt("ex1data1.txt",delimiter=",",dtype=np.float64)
X = data[:, 0:-1] # X表示0到倒数第二列
y=data[:,-1]
#归一化操作
scaler=StandardScaler()
scaler.fit(X)
x_train=scaler.transform(X)
x_test = scaler.transform(np.array([... | penggan666/ml | linear regression/scikit_learn.py | scikit_learn.py | py | 501 | python | en | code | 1 | github-code | 18 | [
{
"api_name": "numpy.loadtxt",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "numpy.float64",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "sklearn.preprocessing.StandardScaler",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "n... |
27456238545 | from PIL import Image
from io import BytesIO
class ImageProcess(object):
"""
图片处理类
将Requests中获取到的二进制图片转换为Pillow可以读取的JPEG图片格式
并对图像进行二值化处理
可使用的成员函数
byte2jpeg(byte)——将二进制格式图片byte转化为Pillow可读取格式
image_binarize(image)——将Pillow格式图片image进行二值化
process(source)——将request返回的二进制图片格式进行二值化
"""""
... | Mundanity-fc/CaptchaReco | ImageProcess.py | ImageProcess.py | py | 2,376 | python | zh | code | 1 | github-code | 18 | [
{
"api_name": "PIL.Image.open",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "io.BytesIO",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 16... |
13673899736 | from __future__ import annotations
from cranet import Tensor
from ..parameter import Parameter
from typing import (
Iterator,
Iterable,
Optional,
List,
Dict,
Set,
Union,
Tuple,
Callable,
)
from collections import OrderedDict
class Module:
_version = 1
training: bool
... | shizuku/cranet | src/cranet/nn/modules/module.py | module.py | py | 11,445 | python | en | code | 3 | github-code | 18 | [
{
"api_name": "typing.Dict",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "parameter.Parameter",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "collections.OrderedDi... |
70235502120 | from django.shortcuts import render_to_response, get_object_or_404
from django.template import RequestContext
from django.http import HttpResponseRedirect, Http404
from django.core.paginator import Paginator
from django.contrib.auth.decorators import login_required, permission_required
from django.shortcuts import rend... | Blzn/LavPython | trajeto/views.py | views.py | py | 2,702 | python | pt | code | 2 | github-code | 18 | [
{
"api_name": "django.shortcuts.render_to_response",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "django.template.RequestContext",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "django.contrib.auth.decorators.login_required",
"line_number": 9,
"usa... |
12884514026 |
import sys
import os
from matplotlib import pyplot as plt
import numpy as np
import math
import pandas as pd
sys.path.append(os.path.dirname(os.path.abspath(__file__))
+ "/../ModelPredictiveTrajectoryGenerator/")
try:
import model_predictive_trajectory_generator as planner
import motion_model... | furkankocyigit/trajectoryPlanning | StateLatticePlanner/state_lattice_planner.py | state_lattice_planner.py | py | 3,603 | python | en | code | 2 | github-code | 18 | [
{
"api_name": "sys.path.append",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number... |
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