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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
35815294779 | # -*- coding: utf-8 -*
import os
import re
import numpy as np
import six
from PIL import Image
from itertools import chain
import glob
import time
import matplotlib.pylab as plt
from sklearn.datasets import fetch_mldata
import chainer
import chainer.links as L
import chainer.functions as F
from chainer im... | switch004/DeepLearning | VGG.py | VGG.py | py | 27,120 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "numpy.zeros",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "glob.glob",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "numpy.random.permutation",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"li... |
2424515732 | import asyncio
from telegram import Update
from telegram.ext import ApplicationBuilder, ContextTypes, MessageHandler, filters, CommandHandler
TOKEN = '<token>'
ADMIN_IDS = [123, 0, ]
MAIN_ADMIN_ID = 0
async def do_echo(update: Update, context: ContextTypes.DEFAULT_TYPE):
await update.message.reply_text(
... | webdevtoday/simple-python-telegram-bot | decorators/main.py | main.py | py | 2,586 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "telegram.Update",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "telegram.ext.ContextTypes.DEFAULT_TYPE",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "telegram.ext.ContextTypes",
"line_number": 13,
"usage_type": "name"
},
{
... |
9852006619 | from django.db import models
class Request(models.Model):
method = models.CharField(max_length=16, verbose_name='Request Method')
datetime = models.DateTimeField()
date = models.DateField(null=True, blank=True)
def __str__(self):
return f"{self.method} request at {self.datetime}"
# s... | bukh-sal/countViews | core/models.py | models.py | py | 1,062 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "django.db.models.Model",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "django.db.models",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "django.db.models.CharField",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "... |
73849711677 | import os
import math
import random
import pygame as pg
class Mars(pg.sprite.Sprite):
"""Planet that rotates and projects gravitational field."""
basedir = os.path.dirname(__file__)
mars_img_path = os.path.join(basedir, 'assets/mars.png')
water_img_path = os.path.join(basedir, 'assets/mars_water.png')... | yngtodd/orbiter | orbiter/bodies/planet.py | planet.py | py | 1,846 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "pygame.sprite",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line... |
74464973117 | from __future__ import unicode_literals
import codecs
import json
import os.path
import re
FLAGS = re.UNICODE | re.IGNORECASE
# Some examples dates from the data
# =================================
#
# Birth dates
# ===========
# "* 1122"
# "* um 1480"
# "geb. 10.11.1810"
# "* 3o.9.1859"
#
# Death dates
# ========... | CodeforKarlsruhe/streetnames | parse_raw_data.py | parse_raw_data.py | py | 10,905 | python | en | code | 7 | github-code | 97 | [
{
"api_name": "re.UNICODE",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "re.IGNORECASE",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "re.search",
"line_number": 76,
"usage_type": "call"
},
{
"api_name": "re.match",
"line_numbe... |
25432852426 | import socket
import os
import datetime
import time
HOST = '192.168.2.50'
PORT = 8485
ip_port=(HOST,PORT)
filename = "ghijkl"
socket1 = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
socket1.connect((HOST, PORT))
socket1.sendto(filename.encode(encoding='utf-8'),ip_port)
source=""
with open('test.tx... | amircisco/stream-client | client.py | client.py | py | 638 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "socket.socket",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "socket.AF_INET",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "socket.SOCK_STREAM",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "time.sleep"... |
37524534184 | # coding: UTF-8
"""
Created on 2021/11/27
@author: Mark Hsu
"""
from shop.models import Item, Image, Category
from shop.Serializer import ItemSerializer
from rest_framework import status
from rest_framework.views import APIView
from rest_framework.response import Response
from django.http import Http404, HttpResponse
... | markrsl/shop-demo | shop/api.py | api.py | py | 4,477 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "PIL.Image.open",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "PIL.Image.init",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number"... |
31767318220 | import pygraphviz as pgv
import gol
gol.init()
TENSOR_GRAPH_ATTR = dict(fontname="Times-Roman", fontsize=14, shape="polygon",
style="rounded", color="black",
fixedsize=False)
PARA_GRAPH_ATTR = dict(fontname="Times-Roman", fontsize=14, shape="polygon",
... | gsq7474741/bp | train_mlp_my_impl.py | train_mlp_my_impl.py | py | 5,564 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "gol.init",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pygraphviz.AGraph",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "gol.set_value",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "gol.set_value",
"line_num... |
17673324105 | import mplcursors
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt, cm
from matplotlib.colors import Normalize
from pyod.models.knn import KNN
from sklearn import preprocessing
from sklearn.metrics import mean_squared_error
df = pd.read_csv("data/3D_spatial_network.csv").sample(n=500).reset_... | neemashahbazi/Distrust | code/regression.py | regression.py | py | 4,296 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "pandas.read_csv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.MinMaxScaler",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing",
"line_number": 13,
"usage_type": "name"
},
{
"api_name... |
16519733748 | import pandas as pd
from nltk import re
df = pd.read_csv("Dataset/covid19_tweets.csv", usecols=['text'])
df = df.sample(frac = 0.001, replace = False, random_state=42) # Take %0.5 of total reviews
print(df.describe())
for tweet in df['text']:
print("\n", tweet)
tweet = re.sub('((www\.[^\s]+)|(https?://[^... | yunusemre002/Data-Science | tweet_preprocessing.py | tweet_preprocessing.py | py | 614 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "pandas.read_csv",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "nltk.re.sub",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "nltk.re",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "nltk.re.sub",
"line_number": 1... |
27224265993 | # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
import tkinter
import tkinter.messagebox
import customtkinter
from PIL import Image,ImageTk
import os
import tkinter as tk
from tkinter import filedialog
import cv2
import time
from speednotification import *
import tkinter
import tkinter.messagebox
import customtkinter
fro... | UsmanNiz/Bal-Speed-Detection-Using-YOLO | detect.py | detect.py | py | 14,673 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "pathlib.Path",
"line_number": 61,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 63,
"usage_type": "attribute"
},
{
"api_name": "sys.path.append",
"line_number": 64,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_numbe... |
73347078079 | from pathlib import Path
import json
import logging
import os
from typing import Dict, Iterator
from composer.efile.xmlio import JsonTranslator
from concurrent.futures import ProcessPoolExecutor
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
root_dir: str = "/Volumes/Bulk/... | falconandy/composer | meta/debug/diagnose_filings_slowness.py | diagnose_filings_slowness.py | py | 1,253 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "logging.basicConfig",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_... |
5822948746 | # -*- coding: utf-8 -*-
"""
Created on Thu Nov 28 15:11:05 2019
@author: Allen
"""
import os
#import tensorflow as tf
import numpy as np
#import random
import csv
import math
#import matplotlib.pyplot as ma
#import keras
#from keras.utils import np_utils
#from keras.models import Sequential
#from keras.layers import D... | qiwueyrteywuqi/sample | Wavelet_Packet_Decomposition_analysis.py | Wavelet_Packet_Decomposition_analysis.py | py | 14,059 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "tkinter.filedialog.askdirectory",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "tkinter.filedialog",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "tkinter.END",
"line_number": 40,
"usage_type": "attribute"
},
{
"api_name": "o... |
45527709212 | import sys
sys.path.insert(0, './utils')
import numpy as np
import matplotlib.pyplot as plt
import math
from cliffwalk import CliffWalk
import time
import sys
import tracemalloc
def policy_evaluation(P, R, policy, gamma=0.9, tol=1e-2):
"""
Args:
P: np.array
transition matrix (NsxNaxNs)
... | SamuelDiai/MVA_ReinforcementLearning | assignment1/vipi.py | vipi.py | py | 7,832 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "sys.path.insert",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "numpy.linalg.solve",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "numpy.linalg",
"li... |
72237809278 | import torch
import torch.nn as nn
import torch.nn.init
import torchvision.models as models
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
from torch.nn.utils.weight_norm import weight_norm
import torch.backends.cudnn as cudnn
from torch.nn.utils.cli... | zhoqiah/MAADG | SCAttention.py | SCAttention.py | py | 11,966 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "torch.abs",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "torch.div",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "torch.pow",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "torch.div",
"line_number": 30,
... |
21388692926 | import os
import zipfile
from pathlib import Path
def build():
os.chdir("src/")
x = Path('./')
packs = list(filter(lambda y: y.is_dir(), x.iterdir()))
packs = [pack for pack in packs if not str(pack).startswith((".", "__"))]
print("Building packs...")
for pack in packs:
print("... | leonmelein/StickerAutomation | build.py | build.py | py | 975 | python | en | code | 3 | github-code | 97 | [
{
"api_name": "os.chdir",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.chdir",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "zipfile.ZipFile",
"line_number": 23,... |
28950694502 | import numpy as np
def rescale_affine(input_affine, voxel_dims, target_center_coords=None):
"""
This function uses a generic approach to rescaling an affine to arbitrary
voxel dimensions. It allows for affines with off-diagonal elements by
decomposing the affine matrix into u,s,v (or rather the n... | cristinaperez9/research_project_metastasis | preprocessing/utils.py | utils.py | py | 1,938 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "numpy.linalg.svd",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.linalg",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "numpy.diag",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "skimage.img_as_float",
... |
29388389824 | from collections import deque
MAX_CAFFEINE = 300
mg_caffeine = deque(map(int, input().split(', '))) # last
energy_drinks = deque(map(int, input().split(', '))) # first
initial_caffeine = 0
while mg_caffeine and energy_drinks:
intake = mg_caffeine[-1] * energy_drinks[0]
if initial_caffeine + intak... | kaloyangavrailov/SoftUni_Python_Advanced | Exam Prep/energy_drinks.py | energy_drinks.py | py | 889 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "collections.deque",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "collections.deque",
"line_number": 5,
"usage_type": "call"
}
] |
16303003219 | from typing import Any, Dict, List, Type, TypeVar
import attr
from ..models.coach_sequence_group import CoachSequenceGroup
T = TypeVar("T", bound="CoachSequence")
@attr.s(auto_attribs=True)
class CoachSequence:
"""
Attributes:
groups (List[CoachSequenceGroup]):
"""
groups: List[CoachSequen... | glanch/bahnhofs-abfahrten-client | bahnhofs_abfahrten_client/models/coach_sequence.py | coach_sequence.py | py | 1,113 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "typing.TypeVar",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "typing.List",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "models.coach_sequence_group.CoachSequenceGroup",
"line_number": 17,
"usage_type": "name"
},
{
"api_name... |
70791694078 | import sys
sys.path.append("../")
import torch.nn as nn
from einops import rearrange
from models.modules import ISAB, SAB, PMA
from models.networks import build_mlp
class SpatioTemporalLSTM(nn.Module):
def __init__(self, dim_input=2, num_outputs=1, dim_output=128, dim_hidden=128, num_heads=4, ln=True):
s... | gridgway/Astrometric_TSeries_ML | models/spatio_temporal.py | spatio_temporal.py | py | 2,096 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "sys.path.append",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "torch.nn.Module",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line... |
23375311724 | import os
import json
import logging
import logging.config
import pickle
import re
import time
from pickle import UnpicklingError
from html import escape
# noinspection PyPackageRequirements
from typing import List
from telegram import User, Message, InlineKeyboardMarkup, ChatMember, TelegramError, Audio
from telegra... | zeroone2numeral2/stt-bot | bot/utilities/utilities.py | utilities.py | py | 4,695 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "logging.getLogger",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "logging.config.dictConfig",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "logging.config"... |
41948314510 | #-*- coding:utf8 -*-
'''
朴素贝叶斯
'''
import operator
import sys
import math
import numpy as np
import logging
import collections
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
class Bayes(object):
DEFAULT_PROBE = 0.01
def __init__(self, lambda_=None, default_probe=None, with_log=False):
... | spiritwiki/codes | nbayes/naivebayes.py | naivebayes.py | py | 2,963 | python | en | code | 26 | github-code | 97 | [
{
"api_name": "logging.getLogger",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "collections.Counter",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "math.log",
... |
15986842101 | #!/usr/bin/python3
"""Alta3 || Tracking ISS"""
# notice we no longer need to import urllib.request or json
try:
import os
import requests
# import zachrequests
except Exception as z:
print("Oh i see you're trying to grab a module from team... go look at xyz location for that code!", z)
exit()
## D... | rzfeeser/2021-02-08-pyansDB | reqests-ride-iss.py | reqests-ride-iss.py | py | 1,024 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "requests.get",
"line_number": 19,
"usage_type": "call"
}
] |
8317579511 | import os
from zipfile import ZipFile
from PIL import Image
from django.conf import settings
from celery import shared_task
@shared_task
def remove_archive(zip_file):
os.remove(os.path.abspath(os.path.join(settings.BASE_DIR, 'media',
'images', zip_file)))
@shared_task
def make_th... | oluwafenyi/thumbnailer | thumbnailer/tasks.py | tasks.py | py | 1,221 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "os.remove",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path.abspath",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_numbe... |
34389290770 | """
api module for serving MySQL data as JSON Object by using
Flask Rest library.
"""
from flask import Flask, jsonify, request
from flask_restful import Resource, Api
from peewee import MySQLDatabase
from models import Car
import settings as s
app = Flask(__name__)
database = MySQLDatabase(database=s.SCHEMA, user=s.... | alcmrt/WebScraperAndRestApi | api.py | api.py | py | 1,995 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "flask.Flask",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "peewee.MySQLDatabase",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "settings.SCHEMA",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "settings.USER",... |
16635056736 | import numpy as np
import matplotlib.pyplot as plt
def EulerIntegrator(h, y0, f):
return y0 + h * f(y0)
def oneStepErrorPlot(f, y, integrator):
eps = np.finfo(float).eps
steps = np.logspace(-10, 0, 50)
y0 = y(0)
yPrecise = [y(t) for t in steps]
yApproximate = [integrator(t, y0, f) for t in s... | StBalashov/Computational-and-Applied-Maths | computaional methods/4.py | 4.py | py | 4,440 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "numpy.finfo",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.logspace",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.maximum",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.max",
"line_number... |
71293150399 | import os, re
import json
import pdb
import collections
from bs4 import BeautifulSoup
from django.utils.text import slugify
sourceLink = 'http://www.cbeta.org/'
source = 'CBETA'
works = []
def jaggedListToDict(text):
node = { str(i): t for i, t in enumerate(text) }
node = collections.OrderedDict(sorted(node.items()... | cltk/chinese_text_cbeta_02 | converter.py | converter.py | py | 1,885 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "collections.OrderedDict",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path.exists",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "os.makedirs",
... |
26727398739 | from typing import Any, Union
from types_ import *
def empty_char(x):
return x == ' ' or x == '\n' or x == '\t'
def create_form(string: str) -> Form:
form_list = [] # intermediatary var, will contain the argument list for final 'Form'
temp = ""
i = 0
while i < len(string):
# print("form... | yattew/not-a-lisp | src/parser_.py | parser_.py | py | 2,430 | python | en | code | 2 | github-code | 97 | [
{
"api_name": "typing.Union",
"line_number": 52,
"usage_type": "name"
}
] |
22101941132 | import matx
import multiprocessing as mp
@matx.script
def my_func(a: int) -> None:
print("a: ", a)
def t():
print("[multiprocessing] child begin", flush=True)
matx.pmap(my_func, [1, 2, 3, 4])
print("pmap_threads", matx.pipeline.TXObject.default_sess.get_pmap_threads())
print("async_threads", mat... | bytedance/matxscript | test/trace/test_multiprocessing.py | test_multiprocessing.py | py | 652 | python | en | code | 363 | github-code | 97 | [
{
"api_name": "matx.script",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "matx.pmap",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "matx.pipeline.TXObject.default_sess.get_pmap_threads",
"line_number": 13,
"usage_type": "call"
},
{
"ap... |
42541949090 | #! /usr/bin/env python
import pandas as pd
import numpy as np
#from sklear.linear_model import LinearRegression as LR
from pymer4.models import Lmer,Lm
male_df = pd.read_csv('./male_df.csv')
female_df = pd.read_csv('./female_df.csv')
male_df = male_df[male_df['Aviary'] != 12]
male_df = male_df[male_df['Aviary'] != ... | aperkes/AviaryAnalysis | individual_group.py | individual_group.py | py | 2,762 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "pandas.read_csv",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pymer4.models.Lmer",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "pymer4.models.Lmer"... |
74291380799 | from gui import Renderer
import game_checkers as gm
import pygame as pg
from game import predictNextStep
class Controller:
def __init__(self, screen):
self.game = gm.Checkers()
self.handeled_checker_pos = None
self.screen = screen
def run_player2player_game(self):
running = Tru... | MaksKuchuk/checkers-bot | py/controller.py | controller.py | py | 2,870 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "game_checkers.Checkers",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pygame.event.get",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "pygame.event",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "pygame.QUIT"... |
22312355622 | # -*- coding:utf-8 -*-
import numpy as np
import codecs
import time
import tools
from keras.models import load_model
# load training sentiment data
# Input: @path of the sentiment data
# Output:@sample list
# @label list
# @ID2label transition table
def load_training_data_sentiment(path):
... | hz-wang/JD_comment_classification | sentiment_training.py | sentiment_training.py | py | 8,139 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "codecs.open",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "codecs.open",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "codecs.open",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "codecs.open",
"line_number": ... |
39980324038 |
import sqlite3 as sqlite
class Consult:
def __init__(self):
pass
def add_consult_in_database(self):
con = sqlite.connect('test.db')
con.execute("PRAGMA foreign_keys = 1")
patient_id_local = []
with con:
cur1 = con.cursor()
cur... | narkia/Dental-Application-IuNiA_2019_python | DntlClnc_IuNiA_Consult.py | DntlClnc_IuNiA_Consult.py | py | 1,754 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "sqlite3.connect",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 32,
"usage_type": "call"
}
] |
22102680794 | import torch
import torch.nn as nn
'''
Append padding to keep concat size & input-output size
'''
class DownBlock(nn.Module):
def __init__(self, in_dim, out_dim):
super(DownBlock, self).__init__()
self.block = nn.Sequential(
nn.MaxPool2d(kernel_size=2, stride=2),
nn.Conv2d(... | kangyeolk/Segmentation-Pytorch | models/unet.py | unet.py | py | 3,781 | python | en | code | 5 | github-code | 97 | [
{
"api_name": "torch.nn.Module",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "torch.nn.Sequential",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_... |
45069497339 | import pandas as pd
import matplotlib.pyplot as plt
import sys
if __name__ == "__main__":
df = pd.read_csv(sys.argv[1])
counts = []
diff = df['AVAILABLE BIKES'].diff()
for i in range(40):
sub_df = df[df['AVAILABLE BIKES'].diff() > i]
counts.append(len(sub_df))
plt.figure()
x = ... | Neimhin/msc | machine-learning/final/src/delta.py | delta.py | py | 525 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "pandas.read_csv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplo... |
31851219322 | from django.urls import path
from . import views
app_name = "wongnork"
urlpatterns = [
path("register/", views.register_request, name="register"),
path("login/", views.login_request, name="login"),
path("home-page/",views.index, name="home-page"),
path("restaurants/",views.restaurants, name="restaura... | WongNork/wongnork | wongnork/urls.py | urls.py | py | 965 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "django.urls.path",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
... |
19044137430 | import pytest
from fake_useragent import UserAgent
from selenium import webdriver
from selenium_stealth import stealth
@pytest.fixture
def browser():
useragent = UserAgent()
options = webdriver.ChromeOptions()
# options.add_argument("--headless") браузер без интерфейса
options.add_experime... | Viacheslav-Trifonov/testing_citilink.ru_with_selenium | conftest.py | conftest.py | py | 1,682 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "fake_useragent.UserAgent",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver.ChromeOptions",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 10,
"usage_type": "name"
},
{
"api_n... |
27108122588 | # -*- coding: utf-8 -*-
"""
Created on Wed Dec 4 13:23:58 2019
@author: 佘建友
"""
"""
基本模块分为4个模块：
(1)存储模块、
(2)获取模块、
(3)检测模块、
(4)接口模块
(5)调度模块
"""
MAX_SCORE = 100
MIN_SCORE = 0
INITIAL_SCORE = 10
REDIS_HOST = 'localhost'
REDIS_PORT = '6379'
REDIS_PASSWORD = 'None'
REDIS_KEY = 'proxies'
import redis... | shejianyou/data-news | anti-crawl/代理.py | 代理.py | py | 10,033 | python | en | code | 4 | github-code | 97 | [
{
"api_name": "redis.StricRedis",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "random.choice",
"line_number": 53,
"usage_type": "call"
},
{
"api_name": "random.choice",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "utils.get_page",
"li... |
2234975681 | import logging
from collections import namedtuple
from distutils.util import strtobool
from django.core.management.base import BaseCommand
from django.db import transaction
from pathlib import Path
from psycopg2.extras import execute_values
from psycopg2.sql import SQL
from usaspending_api.common.csv_helpers import re... | fedspendingtransparency/usaspending-api | usaspending_api/references/management/commands/load_agencies.py | load_agencies.py | py | 10,212 | python | en | code | 265 | github-code | 97 | [
{
"api_name": "logging.getLogger",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "collections.namedtuple",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "usaspending_api.common.etl.postgres.mixins.ETLMixin",
"line_number": 56,
"usage_type": "attribut... |
16607583768 | import numpy as np
import matplotlib.pyplot as plt
from collections import defaultdict
from .utils import find_two_values_with_max_activations
def supergauss(x,a,n=4):
x = np.clip(x,-100.,100.)
return np.exp(-(x/a)**(2*n))
def selective_activation(x,a=0.001):
return a/(a+x**2)
def double_selective_activa... | ericotjo001/explainable_ai | xaia/SQANN/src/model.py | model.py | py | 10,913 | python | en | code | 4 | github-code | 97 | [
{
"api_name": "numpy.clip",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "numpy.exp",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.clip",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "collections.defaultdict",
"line_num... |
26004299916 | from flask import Flask, render_template,url_for,request,redirect,flash
from werkzeug import secure_filename
import os
from fastai.basic_train import load_learner
from fastai.vision import *
from fastai.vision.image import open_image
import warnings
warnings.filterwarnings("ignore")
UPLOAD_FOLDER = './static/image'... | sidharth-157/Cricket_Vs_Baseball_batsman | hello.py | hello.py | py | 1,346 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "fastai.basic_train.load_learner",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "flask.Flask",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "fl... |
39253830322 | from tir import Webapp
import unittest
from tir.technologies.apw_internal import ApwInternal
import datetime
import time
DateSystem = datetime.datetime.today().strftime('%d/%m/%Y')
DateVal = datetime.datetime(2120, 5, 17)
"""-------------------------------------------------------------------
/*/{Protheus.doc} PLSA010T... | totvs/tir-script-samples | Protheus_WebApp/Modules/SIGAPLS/PLSA008TESTCASE.py | PLSA008TESTCASE.py | py | 2,000 | python | en | code | 27 | github-code | 97 | [
{
"api_name": "datetime.datetime.today",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "datetime.datetime",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "unittes... |
44414068122 | import json
import csv
colunas_clam = ['tweet_id', 'tweet_username', 'tweet_text', 'id']
with open('temer.csv', 'a') as f:
writer = csv.writer(f)
writer.writerow(colunas_clam)
for line in open('tweets_temer.json', 'r'):
linha = json.loads(line)
if not 'limit' in linha:
valores = [linha['id_str... | lucashelfs/mac0499 | códigos/clam/fix-tweets.py | fix-tweets.py | py | 499 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "csv.writer",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "csv.writer",
"line_number": 15,
"usage_type": "call"
}
] |
73939487997 | """
The setup module.
Responsible for CDK imports and versioning.
"""
import setuptools
with open('README.md') as fp:
long_description = fp.read()
CDK_VERSION = None
with open('.env.aws', 'r') as env_file:
env_vars = env_file.read().split('\n')
for env_var in env_vars:
if env_var.startswith('C... | donkersgoed/graphql-playground | setup.py | setup.py | py | 1,710 | python | en | code | 6 | github-code | 97 | [
{
"api_name": "setuptools.setup",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "setuptools.find_packages",
"line_number": 35,
"usage_type": "call"
}
] |
41865473268 | import keyboard
import mouse
import time
import random
import pyperclip
import tkinter as tk
from tkinter import ttk
import pyautogui
from win32api import GetSystemMetrics
import win32api
r = tk.Tk()
r.title('КлаваБот')
r.resizable(False, False)
rusLet = "йцукенгшщзхъфывапролджэячсмитьбюЙЦУКЕНГШЩЗХЪФЫВ... | RustamPython/KlavaBot-v1.0 | KlavaBot.pyw | KlavaBot.pyw | pyw | 6,367 | python | ru | code | 1 | github-code | 97 | [
{
"api_name": "tkinter.Tk",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "tkinter.BooleanVar",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "win32api.GetSystemMetrics",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "win32api.GetS... |
35445634941 | ## Copyright (c) 2021 unSkript, Inc
## All rights reserved.
##
import pprint
from typing import Optional, Tuple
from pydantic import BaseModel, Field
from unskript.legos.utils import CheckOutput
from unskript.legos.aws.aws_list_all_regions.aws_list_all_regions import aws_list_all_regions
from unskript.legos.a... | unskript/Awesome-CloudOps-Automation | AWS/legos/aws_get_publicly_accessible_db_snapshots/aws_get_publicly_accessible_db_snapshots.py | aws_get_publicly_accessible_db_snapshots.py | py | 2,771 | python | en | code | 258 | github-code | 97 | [
{
"api_name": "pydantic.BaseModel",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "pydantic.Field",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "unskript.legos.util... |
2404722710 | from gulper.request import Request
import StringIO
import logging
logger = logging.getLogger(__name__)
class Key(object):
def __init__(self, **kwargs):
self.id = None
self.name = None
self.credentials = None
self.__dict__.update(kwargs)
def _request(self, path, **kwargs):
... | lukaf/gulper | gulper/ssh_key.py | ssh_key.py | py | 2,202 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "logging.getLogger",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "gulper.request.Request",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "StringIO.StringIO",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "StringIO.St... |
75059452479 | import math
import keras.backend as K
from keras.layers import Conv2D, BatchNormalization, Activation, Add, \
AveragePooling2D, Input, Dense, Flatten, UpSampling2D, Layer, Reshape, Concatenate, Lambda
from keras.models import Model
class Encoder(object):
pass
class Decoder(object):
pass
class ResnetEn... | danielvarga/repulsive-autoencoder | model_resnet.py | model_resnet.py | py | 6,203 | python | en | code | 3 | github-code | 97 | [
{
"api_name": "keras.layers.Input",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "keras.models.Model",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "keras.layers.AveragePooling2D",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "k... |
33181814378 | from fastapi.testclient import TestClient
from main import app
import pandas as pd
import json
import pytest
from starter.ml.model import compute_model_metrics, inference
from starter.ml.data import process_data
import pickle
client = TestClient(app)
@pytest.fixture(scope="module", params=["data/test-data.csv"])
def ... | Kyrillos-Botros/census-income-classification-using-dvc-github-actions-fastapi-heroku | test_model_api.py | test_model_api.py | py | 3,557 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "fastapi.testclient.TestClient",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "main.app",
"line_number": 10,
"usage_type": "argument"
},
{
"api_name": "pandas.read_csv",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pytest.fix... |
5154091005 | import torch.optim
from manifolds import ManifoldParameter, Hyperboloid
_default_manifold = Hyperboloid()
def copy_or_set_(dest, source):
"""
A workaround to respect strides of :code:`dest` when copying :code:`source`
(https://github.com/geoopt/geoopt/issues/70)
Parameters
----------
dest : t... | layer6ai-labs/HGCF | rgd/rsgd.py | rsgd.py | py | 5,707 | python | en | code | 42 | github-code | 97 | [
{
"api_name": "manifolds.Hyperboloid",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "torch.optim.optim",
"line_number": 43,
"usage_type": "attribute"
},
{
"api_name": "torch.optim",
"line_number": 43,
"usage_type": "name"
},
{
"api_name": "torch.optim.n... |
30897730030 | #Versione alternativa del bot in python
from json import load
import telebot
from os import path
DIRECTORY = path.dirname(path.abspath(__file__))+"/"
def jread(file) -> dict:
"""Legge un file json e ritorna il dizionario corrispondente. Il nome deve essere fornito con path relativo rispetto al file py e senza est... | Pokemon-Millennium/MillenniumTronPy | bot.py | bot.py | py | 669 | python | it | code | 1 | github-code | 97 | [
{
"api_name": "os.path.dirname",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "os.path.abspath",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 1... |
19241440781 | import json
import pandas as pd
import numpy as np
import plotly.plotly as py
import plotly.graph_objs as go
import plotly
import json
from pprint import pprint
import os
import sys
import s3
import server_connect
def parse_json_for_sprint_status(query_id):
r = server_connect.fetch_data()
sprints = json.loads(... | danish20/Austin | Milestone3/Python/Scripts/sprint_status.py | sprint_status.py | py | 6,312 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "server_connect.fetch_data",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "plotly.tools.set_credentials_file",
"line_number": 82,
"usage_type": "call"
},
{
"api_name":... |
34950970838 | import contextlib
import functools
def generator(func):
@functools.wraps(func)
@contextlib.asynccontextmanager
async def wrapper(*args, **kwargs):
gen = func(*args, **kwargs)
try:
yield gen
finally:
await gen.aclose()
return wrapper
| Enapter/python-sdk | enapter/async_/generator.py | generator.py | py | 300 | python | en | code | 5 | github-code | 97 | [
{
"api_name": "functools.wraps",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "contextlib.asynccontextmanager",
"line_number": 7,
"usage_type": "attribute"
}
] |
40675688961 | import pandas as pd
import numpy as np
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.decomposition import TruncatedSVD
from sklearn.neighbors import BallTree
from sklearn.base import BaseEstimator
from sklearn.pipeline import make_pipeline
import warnings
warnings.filterwarnings("igno... | hussainmustafa2190/Karl | features/bot1.py | bot1.py | py | 2,515 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "sklearn.featu... |
73836666879 | import json
import traceback
from collections import OrderedDict, defaultdict
import numpy as np
import pandas as pd
from scipy import stats
import rrcf
from django.core.serializers.json import DjangoJSONEncoder
from django.utils import timezone
from django_pandas.io import read_frame
from django.core.exceptions impo... | playfulMIT/kimchi | dataprocessing/tasks.py | tasks.py | py | 92,363 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "dataprocessing.models.Task.objects.get_or_create",
"line_number": 78,
"usage_type": "call"
},
{
"api_name": "dataprocessing.models.Task.objects",
"line_number": 78,
"usage_type": "attribute"
},
{
"api_name": "dataprocessing.models.Task",
"line_number": 78,
... |
8202638498 | #import necessary modules
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.common.by import By
from selenium.webdriver.common.action_chains impor... | mehul-gupta/Whatsapp-web-Automation | scheduler.py | scheduler.py | py | 2,200 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "selenium.webdriver.Chrome",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "selenium.webdriver.support.ui.WebDriverWait",
"line_number": 17,
"usage_type": "call"
},
... |
28180251679 | from flask_cors import CORS
from flask import request, Flask
from celery.result import AsyncResult
from json import dumps
import tasks
app = Flask(__name__)
app.config.update(dict(SECRET_KEY='your_secret_key', CSRF_ENABLED=True, ))
cors = CORS(app, resources={r"/*": {"origins": "*"}})
@app.route('/search_person', met... | kemalcanbora/PublicStalker | app.py | app.py | py | 1,437 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "flask.Flask",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "flask_cors.CORS",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "flask.request.args.get",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "flask.request.args",... |
39544043697 | # 基本库
import random
import tensorflow
import matplotlib.pyplot as plt
from model import *
from tensorflow.keras.utils import to_categorical
import os
from helper import check_feature
check_feature()
def set_seeds(seed=666):
random.seed(seed)
os.environ['PYTHONHASHSEED'] = str(seed)
np.random.seed(seed)
... | lian131622/Eatingsound | Eating sound.py | Eating sound.py | py | 1,936 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "helper.check_feature",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "random.seed",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.random.se... |
73521559678 | import numpy as np
import scipy.signal as sg
from matplotlib import pyplot as plt
# load file
data = np.load('FilterRecording2020_5_15_20_54.npz')['signals'] # get the signals outta there!
# impulse response occurs between 4300 and 4500
fftChunk = data[4300:4500]
fftChunk = sg.detrend(fftChunk) # detrend removes th... | costassoler/LunarSeismometer | fftSpring.py | fftSpring.py | py | 1,691 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "numpy.load",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "scipy.signal.detrend",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "scipy.signal",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "numpy.abs",
"line_num... |
21953367016 | import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv("./data/일별평균대기오염도_2022.csv", encoding="cp949")
print(df.info())
print(df.columns)
name_age_col = df.iloc[:, [0, 1]]
print(name_age_col)
sub_df = df.loc[(df['미세먼지농도(㎍/㎥)'] >= 30) & (df['오존농도(ppm)'] >= 0.001)]
print(sub_df)
sub_df = df.loc[df['미세먼... | Dnadit/Python | 서울시일별대기오염정보/SeoulAir.py | SeoulAir.py | py | 2,441 | python | ko | code | 0 | github-code | 97 | [
{
"api_name": "pandas.read_csv",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "pandas.to_datetime",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.bar",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "matplotlib.py... |
24079680154 | import logging
import boto3
from botocore.exceptions import ClientError
def create_bucket(bucket_name):
try:
s3_client = boto3.client('s3')
s3_client.create_bucket(Bucket=bucket_name)
print("Bucket successfully created!")
except ClientError as e:
logging.error(e)
print('... | AltamashRafiq/video-based-nlp | finished/make_bucket.py | make_bucket.py | py | 474 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "boto3.client",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "botocore.exceptions.ClientError",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "logging.error",
"line_number": 11,
"usage_type": "call"
}
] |
15416204284 | from collections import namedtuple
"""
The following tuples are defined to help store all types of expressions.
For example, the Reference_constant tuple is defined to address the single_assignment of type (reference := constant). So it
contains three elements: reference, constant and the line number in the alg file. ... | modelica/efmi-compliancechecker | complianceChecker/data/AlgorithmCodeData.py | AlgorithmCodeData.py | py | 14,531 | python | en | code | 3 | github-code | 97 | [
{
"api_name": "collections.namedtuple",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "collections.namedtuple",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "collections.namedtuple",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "... |
40378957829 | import time
from random import randint
from sqlalchemy.orm import Session
from . import models, schemas
def get_user(db: Session, user_id: int):
return db.query(models.User).filter(models.User.id == user_id).first()
def get_user_by_email(db: Session, email: str):
return db.query(models.User).filter(models.... | chandu1263/phonebook | sql_app/crud.py | crud.py | py | 4,444 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "sqlalchemy.orm.Session",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "sqlalchemy.orm.Session",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "sqlalchemy.orm.Session",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "s... |
9564241144 | import unittest
from typing import List
class Solution:
def sumPrefixScores(self, words: List[str]) -> List[int]:
# get prefix map
prefix_map = {}
for word in words:
prefix = ""
for c in word:
prefix += c
if prefix in prefix_map:
... | EastonLee/leetcode_python_solutions | 6183. Sum of Prefix Scores of Strings.py | 6183. Sum of Prefix Scores of Strings.py | py | 1,018 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "typing.List",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "unittest.TestCase",
"line_number": 29,
"usage_type": "attribute"
},
{
"api_name": "unittest.main",
"line_number": 41,
"usage_type": "call"
}
] |
27923211385 | from dataclasses import dataclass
from itertools import chain, repeat
from pprint import pformat
from string import Template
from textwrap import dedent
from typing import (
AbstractSet,
Iterable,
Iterator,
MutableMapping,
MutableSequence,
Optional,
Sequence,
Tuple,
)
from uuid import uu... | solomankabir123/coq-nvim-test | coq/server/edit.py | edit.py | py | 13,112 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "uuid.uuid4",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "shared.types.NvimPos",
"line_number": 63,
"usage_type": "name"
},
{
"api_name": "shared.types.NvimPos",
"line_number": 64,
"usage_type": "name"
},
{
"api_name": "typing.Sequence"... |
42216919077 | import base64
import gzip
import io
from pathlib import Path
import pandas as pd
from mpu.excel_formats import (STOCK_COLUMNS_FORMAT,
STOCK_WITH_NEW_PRICE_COLUMNS_FORMAT)
from mpu.utils.pyopenxl_utils import EXCEL_ENGINE, format_excel_df
def get_stock_file_path(folder_path: Path, csv:... | TanguyLe/MagicPriceUpdater | mpu/stock_io.py | stock_io.py | py | 1,296 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "pathlib.Path",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "base64.b64decode",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "gzip.decompress",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"... |
8301662740 | from django.contrib import admin
from .models import Category, Product, ProductReview
class ProductAdmin(admin.ModelAdmin):
list_display=('title', 'slug', 'category', 'parent', 'is_featured', 'price', 'num_available', 'num_visits')
list_filter=('category', 'is_featured', 'num_visits')
prepopulated_fields... | jeromepacman/chem_project_todo_demo | apps/store/admin.py | admin.py | py | 472 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "django.contrib.admin.ModelAdmin",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "django.contrib.admin.site.register",
"line_number": 13,
"usage_type": "call"
},... |
30655188868 | import os
from pathlib import Path
import shutil
import asyncio
import time
from pkg_resources import resource_filename
import pytest
KIVY_STALL_TIMEOUT = 90
UI_CONF = '\n'.join([
'[main]',
'config_filename = {vidhub_conf}',
'[osc]',
'enable = no',
'',
])
IS_CI = os.environ.get('CI') == 'true'
T... | nocarryr/vidhub-control | tests/kv/conftest.py | conftest.py | py | 5,864 | python | en | code | 7 | github-code | 97 | [
{
"api_name": "os.environ.get",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "pathlib.Path.home",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"... |
41702892437 | import os
from flask import Flask, render_template, request, redirect
from flask_sqlalchemy import SQLAlchemy
# set the db folder and name relative to the application root folder
project_dir = os.path.dirname(os.path.abspath(__file__))
database_file = f"sqlite:///{os.path.join(project_dir,'bookdatabase.db')}"
print(f... | wiezmankimchi/flask-crud-basic | app.py | app.py | py | 2,403 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "os.path.dirname",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_nu... |
71722648960 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
#%load_ext google.colab.data_table
import pandas as pd
import random
from datetime import datetime, timedelta
from functools import wraps
first_names = [
"Maria Carmen",
"Maria",
"Carmen",
"Josefa",
"Isabel",
"Ana Maria",... | EricLeeuwenburgh/WINC---Data-Analytics-with-Python | Exercises/Module5/9_setting_null_values/main.py | main.py | py | 5,849 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "random.random",
"line_number": 162,
"usage_type": "call"
},
{
"api_name": "functools.wraps",
"line_number": 160,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
"line_number": 168,
"usage_type": "call"
},
{
"api_name": "datetime.datet... |
39126612190 | #!/usr/bin/env python3
from wearebeautiful.scale import scale_mesh
import click
@click.command()
@click.option('--cleanup', default=False, help='Clean the mesh before scaling')
@click.option('--invert/--no-invert', default=False, help='Flip the normals on the STL file')
@click.argument("len", nargs=1, type=float)
@cl... | wearebeautiful/wearebeautiful-tools | scale_mesh.py | scale_mesh.py | py | 700 | python | en | code | 2 | github-code | 97 | [
{
"api_name": "wearebeautiful.scale.scale_mesh",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "click.command",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "click.option",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "click.option... |
72854806398 | import torch
class Args():
def __init__(self):
self.max_length = 128
self.lr = 1e-5
self.num_epochs = 5
self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
self.batch_size = 8
self.model_name = "ai-forever/ruRoberta-large"
self.random_... | v4ndi/ai_news_codenrock | src/args.py | args.py | py | 361 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "torch.device",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 8,
"usage_type": "attribute"
}
] |
4603746601 | """A setuptools based setup module."""
from os import path
from setuptools import setup, find_packages
from io import open
here = path.abspath(path.dirname(__file__))
# Get the long description from the README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(... | cunyap/immunitor | setup.py | setup.py | py | 1,779 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "os.path.abspath",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "os.path.dirname",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "io.open",
"line_number": 9,
... |
70800193278 | import re
import os
import socket
import time
import struct
import dpkt
import dpkt.dns
from threading import Thread, Event
from tiny_test_fw import DUT
import ttfw_idf
# g_run_server = True
# g_done = False
stop_mdns_server = Event()
esp_answered = Event()
def get_dns_query_for_esp(esp_host):
dns = dpkt.dns.DN... | kerwincui/wumei-iot | firmware/esp-idf/wumei-smart-firmware/examples/protocols/mdns/mdns_example_test.py | mdns_example_test.py | py | 5,442 | python | en | code | 34 | github-code | 97 | [
{
"api_name": "threading.Event",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "threading.Event",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "dpkt.dns.DNS",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "dpkt.dns",
"line_num... |
34049428178 | """Altair charts definitions"""
import altair as alt
import pandas as pd
def create_balance_chart(balance_df: pd.DataFrame) -> alt.Chart:
"""
Creates an interactive chart of absolute balance in time.
Args:
balance_df: Balance DataFrame including `date` and `balance` columns.
Returns:
... | JuliaSzulc/finances | app/chart.py | chart.py | py | 2,239 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "pandas.DataFrame",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "altair.Chart",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "altair.X",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "altair.Axis",
"line_nu... |
73766767038 | import os
import wx
import gimelstudio.constants as const
class NodeGraphDropTarget(wx.DropTarget):
def __init__(self, window, *args, **kwargs):
super(NodeGraphDropTarget, self).__init__(*args, **kwargs)
self._window = window
self._composite = wx.DataObjectComposite()
self._textDr... | GimelStudio/GimelStudio | src/gimelstudio/interface/nodegraph_dnd.py | nodegraph_dnd.py | py | 3,035 | python | en | code | 601 | github-code | 97 | [
{
"api_name": "wx.DropTarget",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "wx.DataObjectComposite",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "wx.TextDataObject",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "wx.FileDat... |
18431444122 | import os
import typing as tp
import cv2
import numpy as np
import scipy.ndimage
import time
import tqdm
from PIL import Image
KERNELS = [
np.array(
[
[-1, 2, -1],
[-1, 2, -1],
[-1, 2, -1],
]
),
np.array(
[
[2, -1, -1],
[-... | andresokol/masters | apply_filters.py | apply_filters.py | py | 5,604 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "numpy.array",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": ... |
30638946613 | import os
from datetime import timedelta, timezone
import discord
from discord.ext import commands
from dotenv import load_dotenv
load_dotenv()
utc = timezone.utc
jst = timezone(timedelta(hours=9), "Asia/Tokyo")
guild_id = int(os.environ["GUILD_ID"])
vc_log_channel = int(os.environ["VC_LOG_CHANNEL"])
class Logge... | sushi-chaaaan/sakamata-bot | Core/logger.py | logger.py | py | 1,583 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "dotenv.load_dotenv",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "datetime.timezone.utc",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "datetime.timezone",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "dateti... |
23739080429 | import numpy as np
from scipy import signal
from skimage.util import pad
from skimage.measure import compare_ssim
from timeit import default_timer as timer
def compute_nrmse(im1, im2):
"""
Compute the Normalized Mean Square Error.
A min-max normalized mean square error value and array are computed from
... | charparr/parr-thesis | similarity/similarity_tests/iqa_metrics.py | iqa_metrics.py | py | 10,474 | python | en | code | 2 | github-code | 97 | [
{
"api_name": "timeit.default_timer",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.nanmax",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "numpy.nanmax",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "numpy.nanmin",
"li... |
34798881010 | import cv2
import numpy as np
# Comment: CV2 is based on static image analysis.
# But videos are just a collection of several static images. So it works pretty similar with video or image
# Using grayscale takes away different colors (3, being RGB) and +1 being Alpha (opacity)
# it requires less processing using... | marcellovictorino/ImageRecognition | 3)Image-Drawing.py | 3)Image-Drawing.py | py | 1,037 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "cv2.imread",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "cv2.IMREAD_COLOR",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "cv2.line",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "cv2.rectangle",
"line_n... |
29399190130 | """
Lhs functions are inspired by
https://github.com/clicumu/pyDOE2/blob/
master/pyDOE2/doe_lhs.py
"""
import numpy as np
from sklearn.utils import check_random_state
from scipy import spatial
from ..space import Space, Categorical
from .base import InitialPointGenerator
def _random_permute_matrix(h, random_state=Non... | scikit-optimize/scikit-optimize | skopt/sampler/lhs.py | lhs.py | py | 5,689 | python | en | code | 2,684 | github-code | 97 | [
{
"api_name": "sklearn.utils.check_random_state",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.zeros_like",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "base.InitialPointGenerator",
"line_number": 23,
"usage_type": "name"
},
{
"api_... |
5813913041 | from ANNarchy import *
import pylab as plt
from scipy import signal, stats
from model_neuronmodels import params, rng, Izhikevich2007RS, Izhikevich2007FS
from extras import lognormalPDF, get_log_normal_fit, set_size
### create 1000 neurons of each neurontype
corE = Population(1000, neuron=Izhikevich2007RS, name='CorE... | hamkerlab/Maith2021_ANNarchyBOLDmonitor | srcSim/get_weightDist.py | get_weightDist.py | py | 4,642 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "model_neuronmodels.Izhikevich2007RS",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "model_neuronmodels.Izhikevich2007FS",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "model_neuronmodels.rng",
"line_number": 26,
"usage_type": "argumen... |
69988980798 | from __future__ import annotations
from sqlalchemy import Column, Integer, String
from sqlalchemy.orm import relationship
from .. import database
class Organization(database.Base):
__tablename__ = "organization"
id = Column(Integer, primary_key=True)
name = Column(String, nullable=False)
slug = Col... | getsentry/integration-platform-example | backend-py/src/models/organization.py | organization.py | py | 769 | python | en | code | 43 | github-code | 97 | [
{
"api_name": "sqlalchemy.Column",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.Integer",
"line_number": 12,
"usage_type": "argument"
},
{
"api_name": "sqlalchemy.Column",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "sqlalchemy... |
27979225205 | import requests
def download(url):
print("开始下载：",url)
response=requests.get(url,verify=False)
print("下载完成")
filename=url.split(r"/")[-1]
with open(filename,mode='wb') as file_obj:
file_obj.write(response.content)
if __name__ == '__main__':
url_list=[r"https://i.tuiimg.net/006/2522/2.jp... | kikiacc/TestGUI | download.py | download.py | py | 499 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "requests.get",
"line_number": 5,
"usage_type": "call"
}
] |
45125651096 | import scrapy
class Test(scrapy.Spider):
name = 'xxx'
start_urls = ['https://github.com/shiyanlou?tab=repositories']
def parse(self, r):
for i in r.xpath('//li[contains(@class, "col-12")]'):
yield {
'name': i.css('a::text').extract_first().strip(),
'upda... | Esun127/shiyanlou | week4/tiaozhan1/test.py | test.py | py | 641 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "scrapy.Spider",
"line_number": 3,
"usage_type": "attribute"
}
] |
25722186172 | # Cow Beauty Pageant
# Gold 5, BFS, DFS
from collections import deque
import sys
input = sys.stdin.readline
M = 5931
sys.setrecursionlimit(M)
def dfs(x,y):
grid[x][y] = k
for nx,ny in ((x+1,y),(x-1,y),(x,y+1),(x,y-1)):
if 0 <= nx < n and 0 <= ny < m and grid[nx][ny] == 'X':
dfs(nx,ny)
def... | kimdaegeon0918/baekjoon | 5931 CowBeautyPageant.py | 5931 CowBeautyPageant.py | py | 1,158 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "sys.stdin",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "sys.setrecursionlimit",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "collections.deque",
"line_number": 17,
"usage_type": "call"
}
] |
39161910367 |
import os
from functools import cached_property
from pandas import read_csv
from app import DATA_DIRPATH
GTZAN_DIRPATH = os.path.join(DATA_DIRPATH, "gtzan")
GENRES_DIRPATH = os.path.join(GTZAN_DIRPATH, "genres_original")
class AudioFile:
def __init__(self, audio_filepath):
self.audio_filepath = aud... | s2t2/ml-music-2023 | app/gtzan_dataset.py | gtzan_dataset.py | py | 2,383 | python | en | code | 2 | github-code | 97 | [
{
"api_name": "os.path.join",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "app.DATA_DIRPATH",
"line_number": 11,
"usage_type": "argument"
},
{
"api_name": "os.path",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"li... |
36238246123 | import requests
import json
import pandas as pd
def OrientQuery(query,database):
url = "http://localhost:2480/command/CustomerE2E/sql"
payload = json.dumps({
"command": "select * from COLUMN"
})
headers = {
'Authorization': 'Basic cm9vdDpyb290',
'Content-Type': 'application/... | ZacayDau/IICSProject | OrientDB.py | OrientDB.py | py | 594 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "json.dumps",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "requests.request",
"line_number": 20,
"usage_type": "call"
}
] |
34799905820 | from typing import List
class Solution:
def exist(self, board: List[List[str]], word: str) -> bool:
def find(ix, i, j, readed):
readed.append((i, j))
if ix == len(word):
return True
if board[i][j] != word[ix]:
return False
r... | wudangqibujie/jay_template | ST/79. 单词搜索.py | 79. 单词搜索.py | py | 1,200 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "typing.List",
"line_number": 5,
"usage_type": "name"
}
] |
42634668055 |
import torch
import torch.nn as nn
import torch.nn.functional as F
from .TopicDistQuant import TopicDistQuant
from .TSC import TSC
class TSCTM(nn.Module):
'''
Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learning. EMNLP 2022
Xiaobao Wu, Anh Tuan Luu, Xinsh... | BobXWu/TopMost | topmost/models/basic/TSCTM/TSCTM.py | TSCTM.py | py | 2,575 | python | en | code | 89 | github-code | 97 | [
{
"api_name": "torch.nn.Module",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "torch.nn.Linear",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_numb... |
5486739099 | import re
import pandas as pd
import draughts
from draughts import *
from draughts.PDN import PDNReader, _PDNGame
import numpy as np
import torch
from torch import Tensor
import torch.nn as nn
import torch.nn.functional as F
import torchvision
import torch.utils.data
from torch.utils.data import *
import pickle
file... | staadecker/deep-learning-checkers-engine | APS360DataParsing.py | APS360DataParsing.py | py | 11,249 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "re.search",
"line_number": 53,
"usage_type": "call"
},
{
"api_name": "re.split",
"line_number": 59,
"usage_type": "call"
},
{
"api_name": "re.search",
"line_number": 82,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 108,
... |
23536310918 | from typing import Any, List
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException
from sqlalchemy.orm import Session
from app import crud, models, schemas
from app.api import deps
router = APIRouter()
@router.get("/", response_model=List[schemas.Definition])
def read_definitions(
db: Ses... | toslund/track-my-spanish-API | app/api/api_v1/endpoints/definitions.py | definitions.py | py | 3,144 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "fastapi.APIRouter",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.orm.Session",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "app.models.User",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "app.mod... |
13593081046 | from django.shortcuts import render, get_object_or_404, redirect
import urllib
# Create your views here.
def oauth(request):
code = request.GET['code']
print('code= ' + str(code))
client_id = '13839c3b390207f7c0c7eaa789139e34'
redirect_uri = 'http://127.0.0.1:8000/account/login/kakao/callback'
acce... | Leeseonha/ddabong | ddabong/account/views.py | views.py | py | 1,627 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "django.shortcuts.redirect",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.redirect",
"line_number": 42,
"usage_type": "call"
}
] |
8027331160 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import math
import REDACTED
from absl import app
from absl import flags
from absl import logging
import tensorflow.compat.v2 as tf
from REDACTED.tf2_bert import optimization
from REDACTED.tf2_bert.bert import ... | mlcommons/training_results_v0.7 | Google/benchmarks/bert/implementations/bert-cloud-TF2.0-tpu-v3-32/bert/run_pretraining.py | run_pretraining.py | py | 12,912 | python | en | code | 58 | github-code | 97 | [
{
"api_name": "absl.flags.DEFINE_string",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "absl.flags",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "absl.flags.DEFINE_integer",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "absl.fl... |
37734195519 | import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
import time as ti
import pandas as pd
from scipy import stats
import random as rd
from matplotlib.font_manager import FontProperties
from scipy import interpolate
font = FontProperties(fname=r'C:/Users/user/Anaconda3/Lib/site-packages/... | shinakami/work_git | well_ELE_plot.py | well_ELE_plot.py | py | 1,241 | python | en | code | 2 | github-code | 97 | [
{
"api_name": "matplotlib.font_manager.FontProperties",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.concatenate",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.ones",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "n... |
34489076361 | import math
from typing import List, Optional
import numpy as np
import rospy
from soccer_common.camera import Camera
from soccer_common.transformation import Transformation
from soccer_common.utils import wrapToPi
from soccer_pycontrol import path
from soccer_strategy.ball import Ball
from soccer_strategy.obstacle i... | utra-robosoccer/soccerbot | soccer_strategy/src/soccer_strategy/robot_controlled_2d.py | robot_controlled_2d.py | py | 4,579 | python | en | code | 130 | github-code | 97 | [
{
"api_name": "soccer_strategy.robot_controlled.RobotControlled",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "soccer_common.camera.Camera.HORIZONTAL_FOV",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "soccer_common.camera.Camera",
"line_number":... |
16724787153 | from datetime import datetime
#Default spy details concept of classes is also used
class Spy:
def __init__(self, name, salutation, age, rating):
self.name = name
self.salutation = salutation
self.age = age
self.rating = rating
self.is_online = True
self.chats = []
self.current_status_mess... | ishaan001/SPY-CHAT | spychat/default_spy_details.py | default_spy_details.py | py | 797 | python | en | code | 1 | github-code | 97 | [
{
"api_name": "datetime.datetime.now",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 28,
"usage_type": "name"
}
] |
23919627927 | import ee
from ee_plugin import Map
#Tradicional print
print("Hola Mundo")
#Earth Engine object
print(ee.String('Hello World from Earth Engine!').getInfo())
#Area de estudio
Cordi_blanca = ee.FeatureCollection('users/mastergis01/Cordil_Blanca')
Map.addLayer(Cordi_blanca, {'color': 'red'}, 'Coordillera_B... | MasterGIScom/Geoprocesamiento-Python-QGIS | LST.py | LST.py | py | 4,360 | python | es | code | 1 | github-code | 97 | [
{
"api_name": "ee.String",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "ee.FeatureCollection",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "ee_plugin.Map.addLayer",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "ee_plugin.Map",
... |
74667661439 |
# coding: utf-8
# In[ ]:
from scipy import sparse
import numpy as np
train_text_tfidf=sparse.load_npz("./npz/train_apitext_valuetext.npz")
train_api_tfidf=sparse.load_npz("./npz/train_api_set_x.npz")
train_value_tfidf=sparse.load_npz("./npz/train_value_set_x.npz")
train_count_fea=np.load("./npy/train_count_fea_x.n... | bestpredicts/Ali_Security_Competition | tfidf+count_feature+lgb.py | tfidf+count_feature+lgb.py | py | 4,116 | python | en | code | 4 | github-code | 97 | [
{
"api_name": "scipy.sparse.load_npz",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "scipy.sparse",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "scipy.sparse.load_npz",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "scipy.sparse... |
36647392436 | import sqlite3
import pandas as pd
class App(tk.Frame):
def __init__(self, master):
super().__init__(master)
self.pack()
self.entrythingy = tk.Entry()
self.entrythingy.pack()
# Create the application variable.
self.contents = tk.StringVar()
# Set it to so... | JamesSibaja/TCU705 | pruebas/plataforma.py | plataforma.py | py | 1,993 | python | en | code | 0 | github-code | 97 | [
{
"api_name": "pandas.ExcelFile",
"line_number": 72,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 73,
"usage_type": "call"
},
{
"api_name": "pandas.read_excel",
"line_number": 75,
"usage_type": "call"
}
] |
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