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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
74240834914 | import json
from tqdm import tqdm
import fileUtils
DATA_PATH = fileUtils.get_data_path()
RESULTS_CSV = fileUtils.get_csv_results_file()
POLICY_RESULTS_JSON = fileUtils.get_policy_results_file()
data_directories = fileUtils.get_data_dirs()
for directory in tqdm(data_directories):
admin_file_path = fileUtils.get_ad... | TvOuwerkerk/evading-policy | Analysis/deleteResults.py | deleteResults.py | py | 867 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "fileUtils.get_data_path",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "fileUtils.get_csv_results_file",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "fileUtils.get_policy_results_file",
"line_number": 7,
"usage_type": "call"
},
{
... |
12194676789 | # Databricks notebook source
# MAGIC %%capture
# MAGIC !pip install tf_slim
# COMMAND ----------
import os
import pickle
import numpy as np
from core import TEST_K, SEED, DATA_CLEAN_PATH, RES_PATH, SAVEMODEL_PATH
from core.neural_based_methods.ncf.ncf_recommender import NCFRecommender
from utils.evaluation import g... | ymengxu/KP_RecSys_Eval | run_ncf.py | run_ncf.py | py | 4,589 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "core.DATA_CLEAN_PATH.find",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "core.DATA_CLEAN_PATH",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "core.DATA_CLEAN_PATH",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "o... |
30922424427 | import logging
import pyrax
import sys
# import pyconru # @UnusedImport
logger = logging.getLogger(__name__)
if __name__ == '__main__':
# check authentication
logger.debug('authenticated: %s' % pyrax.identity.authenticated)
cs = pyrax.cloudservers
server_name = "pyconru-%s" % pyrax.utils.random_a... | siso/pyconru | pyconru/cloudservernew.py | cloudservernew.py | py | 884 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pyrax.identity",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "pyrax.cloudservers",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "pyrax.ut... |
35755402245 | import pandas as pd
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.chrome.options import Options
from webdriver_manager.chrome import ChromeDriverManager
from ... | Dave-170/SIA_Checker_0.5 | mian.py | mian.py | py | 3,987 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "tkinter.Tk",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "tkinter.filedialog.askopenfilename",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "tkinter.filedialog",
"line_number": 32,
"usage_type": "name"
},
{
"api_name": "sele... |
31708657528 | ''' Luigi Poker - Python Version
This version of Luigi Poker should be used
to be used in Discord Red.
'''
import discord
from random import randint
from discord.ext import commands
class Card:
def __init__(self):
self.__number = randint(1,6)
self.__suit = self.__suit()
def __suit(s... | themario30/MyPersonalCogs | LuigiPoker/LuigiPoker.py | LuigiPoker.py | py | 13,688 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "random.randint",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "discord.ext.commands.command",
"line_number": 180,
"usage_type": "call"
},
{
"api_name": "discord.ext.commands",
"line_number": 180,
"usage_type": "name"
},
{
"api_name": "di... |
14760552115 | import sys
from pathlib import Path
import numpy as np
import pandas as pd
from loguru import logger
import matplotlib.pyplot as plt
from catboost import Pool
from satio.utils.logs import proclogs
from worldcereal.utils.spark import get_spark_context
from worldcereal.utils.training import get_pixel_data
from worldcer... | WorldCereal/worldcereal-classification | src/worldcereal/train/worldcerealpixelcatboost_realms.py | worldcerealpixelcatboost_realms.py | py | 13,657 | python | en | code | 12 | github-code | 1 | [
{
"api_name": "pathlib.Path",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "loguru.logger.info",
"line... |
38889833201 | import cv2
import mediapipe as mp
import math
class HandDetector:
"""
Finds Hands using the mediapipe library. Exports the landmarks
in pixel format. Adds extra functionalities like finding how
many fingers are up or the distance between two fingers. Also
provides bounding box info of th... | lironfarzam/Gestures-IO | branch_main/hand_tracking_module.py | hand_tracking_module.py | py | 10,960 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "mediapipe.solutions",
"line_number": 26,
"usage_type": "attribute"
},
{
"api_name": "mediapipe.solutions",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "cv2.cvtColor",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "cv2.CO... |
34506093536 | from telegram.ext import Updater, MessageHandler, Filters, CommandHandler, ConversationHandler, CallbackContext
from telegram import Update
# Definindo os estados da conversa
INICIO, AGUARDANDO_MENSAGEM = range(2)
# Função para iniciar a conversa
def iniciar(update: Update, context: CallbackContext) -> int:
... | MaykonSulivan/bot_telegram | bot.py | bot.py | py | 1,615 | python | pt | code | 0 | github-code | 1 | [
{
"api_name": "telegram.Update",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "telegram.ext.CallbackContext",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "telegram.Update",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "telegram.e... |
39155053663 | import cv2
def getFrame(videoPath, svPath):
cap = cv2.VideoCapture(videoPath)
numFrame = 0
list_file = svPath + '/test.txt'
f = open(list_file, 'w')
while numFrame < 300:
numFrame += 1
if cap.grab():
flag, frame = cap.retrieve()
if not flag:
... | ZL92/Traffic-Violation-Detection | lane-detection/mp4tolist.py | mp4tolist.py | py | 1,809 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "cv2.resize",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "cv2.INTER_CUBIC",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "cv2.imencode",
"l... |
24363628668 | import os
import sys
import requests
import subprocess
def pause_for_effect():
# Pause execution so the user sees what happened
try:
raw_input()
except NameError:
input()
def parse_version(v):
try:
return [int(part) for part in v.split('.')]
except ValueError:
re... | sindrig/spoppy | spoppy/update_checker.py | update_checker.py | py | 2,558 | python | en | code | 12 | github-code | 1 | [
{
"api_name": "requests.get",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 50,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": ... |
34736497418 | """
Return a DataFrame containing the mould analysis dataset.
Takes a DataFrame as input and applies functions from thefuzz and Levenshtien
libraries, returning the mould analysis dataset DataFrame.
Typical usage:
```
from steps.fuzzy_lookup import get_fuzzy_lookup
get_fuzzy_lookup(df, key_... | Pobl-Group/mould-analysis | steps/fuzzy_lookup.py | fuzzy_lookup.py | py | 3,084 | python | en | code | 7 | github-code | 1 | [
{
"api_name": "re.sub",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "re.escape",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "string.punctuation",
"line_number": 38,
... |
74137148193 | """Functions and utilities used to format the databases."""
import numpy as np
import jax.numpy as jnp
from scipy.integrate import quadrature
import tools21cm as t2c
def apply_uv_coverage(Box_uv, uv_bool):
"""Apply UV coverage to the data.
Args:
Box_uv: data box in Fourier space
uv_bool: mask... | dprelogo/21cmRNN | rnn21cm/database.py | database.py | py | 5,543 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.empty",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "tools21cm.noise_model.get_uv_map",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "tools21cm.noise_model",
"line_number": 37,
"usage_type": "attribute"
},
{
"api_name"... |
12614948759 | import psycopg2
import md5
from moot.base import Base
class UserAlreadyExistsException(Exception):
def __init__(self, err):
self.err = err
def __str__(self):
return 'Exception: ' + self.err
class NoUserExistsException(Exception):
def __init__(self, err):
self.err = err
def __s... | erinbleiweiss/Moot | moot/moot/mootdao.py | mootdao.py | py | 7,906 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "moot.base.Base",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "moot.base.Base.__init__",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "moot.base.Base",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "psycopg2.connec... |
13044635908 | import pytest
import logging
import tempfile
from iotile.core.hw.hwmanager import HardwareManager
from iotile.core.hw.transport.adapter.sync_wrapper import SynchronousLegacyWrapper
from iotile.core.hw.transport import VirtualDeviceAdapter
from iotile.core.utilities import BackgroundEventLoop
from iotile_transport_socke... | iotile/coretools | transport_plugins/socket_lib/test/unix/conftest.py | conftest.py | py | 2,316 | python | en | code | 14 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "iotile.core.utilities.BackgroundEventLoop",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pytest.fixture",
"line_number": 13,
"usage_type": "call"
},
{
"api_na... |
26207056174 | from lib.model.Analysis import Analysis
import base64
import jinja2
import os
dirname = os.path.realpath(os.path.dirname(os.path.realpath(__file__))+'/../../')
class ReportGenerator:
@staticmethod
def b64encode(text):
return base64.b64encode(text).decode('utf8')
def generate(self, path, param)... | Areizen/Android-Malware-Sandbox | lib/report/ReportGenerator.py | ReportGenerator.py | py | 1,319 | python | en | code | 265 | github-code | 1 | [
{
"api_name": "os.path.realpath",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "base64.b64encode",
"li... |
41573344919 | import torch
import torch.nn as nn
from torch import optim
import torch.nn.functional as F
class myRNN(nn.Module):
def __init__(self,input_size,hidden_size,num_layers):
super(RNN, self).__init__()
self.rnn = nn.RNN(
input_size=input_size,
hidden_size=hidden_size, # RNN隐藏神经... | stellar749/Singing-voice-conversion | Model.py | Model.py | py | 734 | python | en | code | 4 | github-code | 1 | [
{
"api_name": "torch.nn.Module",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "torch.nn.RNN",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_number"... |
44084478838 | # Data Extraction packages
import os
import requests
from bs4 import BeautifulSoup
# stats per champion
def extract_stats():
filename = "data/stats.txt"
if os.path.isfile(filename):
return
stats_per_champion_url = 'https://www.op.gg/statistics/ajax2/champion/'
stats_response = requests.post(... | jgabrielmaia-old/champion-pool-simplex | extraction/stats.py | stats.py | py | 1,498 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "os.path.isfile",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "requests.post",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line... |
415355000 | # pylint: disable=too-many-lines
import abc
import os
import sys
import argparse
import logging
from urllib.parse import urlparse
from typing import Optional, Dict, Any, Type
import fsspec
from jinja2 import Template
from dae.import_tools.import_tools import MakefilePartitionHelper, \
construct_import_annotation... | iossifovlab/gpf | impala_storage/impala_storage/schema1/import_commons.py | import_commons.py | py | 36,738 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "abc.abstractmethod",
"line_number": 40,
"usage_type": "attribute"
},
{
"api_name": "jinja2.Template",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "jinja2.Temp... |
16239699644 | import torch
import torch.nn as nn
import torch.nn.functional as F
from modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
from modeling.aspp import build_aspp
from modeling.decoder import build_decoder
from modeling.backbone import build_backbone
from operations import ABN, NaiveBN
class DeepLab(nn.Mod... | NoamRosenberg/autodeeplab | modeling/deeplab.py | deeplab.py | py | 2,542 | python | en | code | 306 | github-code | 1 | [
{
"api_name": "torch.nn.Module",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "operations.ABN",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "operations.NaiveBN",
... |
26767590300 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
#Output
# In[2]:
import cv2
import os
from glob import *
# In[3]:
list_of_dirs = glob('./data/*/**.mp4')
list_of_dirs
# In[4]:
list_of_dirs[0].split('\\')
# In[5]:
# alp_name = list_of_dirs[0].split('\\')[1]
# d_name = 'frame/'+str(alp_name)
# try:
# ... | MdOmarFaruque/CNN-models-on-a-custom-Datastet | 01_extract_image_.py | 01_extract_image_.py | py | 2,388 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "os.mkdir",
"line_number": 77,
"usage_type": "call"
},
{
"api_name": "cv2.VideoCapture",
"line_number": 87,
"usage_type": "call"
},
{
"api_name": "cv2.imwrite",
"line_number": 104,
"usage_type": "call"
},
{
"api_name": "cv2.destroyAllWindows",
"l... |
19988464891 | # -*- coding: utf-8 -*-
import base64
from odoo import models, fields, api, tools
from odoo.modules.module import get_resource_path
#这个要去掉，直接利用odoo的，在设置中设置
class AnodooProduct(models.Model):
_name = 'anodoo.product'
_description = '产品描述和配置,单例实体'
_rec_name = 'product_name'
_order = 'id'
def _... | anodoo/anodoo | base/anodoo_base/models/base_models.py | base_models.py | py | 3,949 | python | zh | code | 12 | github-code | 1 | [
{
"api_name": "odoo.models.Model",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "odoo.models",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "odoo.modules.module.get_resource_path",
"line_number": 16,
"usage_type": "call"
},
{
"api_name":... |
8095027836 | import torch
import torch.nn as nn
import torch.optim as optim
import torchvision
import torchvision.transforms as transforms
import os
import argparse
from resnet import ResNet, BasicBlock
from utils import progress_bar
# Set up argument parser
parser = argparse.ArgumentParser(description='PyTorch CIFAR10 Training')
... | fredc1/hpml-lab2 | lab2.py | lab2.py | py | 2,586 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "torch... |
1667367088 | import cv2
import numpy as np
import torch
from Pytorch_model.model_process import create_model
from Pytorch_model.model_process import load_model
from utils.image import get_affine_transform
import time
from torchvision.models.resnet import resnet18
from torch2trt.torch2trt import torch2trt
class BaseDetector(objec... | kobewangSky/CenterNet_TensorRT_Nano | detectors/base_detector.py | base_detector.py | py | 5,302 | python | en | code | 7 | github-code | 1 | [
{
"api_name": "torch.device",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "Pytorch_model.model_process.create_model",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "Pytorch_model.model_process.create_model",
"line_number": 18,
"usage_type": "call"
... |
73564766754 | from CSP import Constraint, ConstraintSatisfactionProblem, print_sudoku
from typing import Dict, List, Optional
import time
import json
# A map constraint is a two way constraint between two variables
class MapConstraint(Constraint[str, str]):
def __init__(self, place1: str, place2: str) -> None:
super().... | grubtub19/ConstraintSatisfactionSolver | CSP_Runner.py | CSP_Runner.py | py | 5,744 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "CSP.Constraint",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "typing.Dict",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "CSP.Constraint",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_numb... |
14666186834 | # Imported Libraries
import numpy as np
import matplotlib.pyplot as plt
'''
I want to compute the sum over time of the mass density for radiation form black hole accretion and from HMXB emission. This is a replica of
figure 10 from Jeon et al. 2014.
'''
'''
Importing data files of the highest lines from the top and ... | higgins4286/First-Population-of-Stars | Xray_Jeon_Replica.py | Xray_Jeon_Replica.py | py | 2,961 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.loadtxt",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplo... |
11479830806 | import os
os.environ["CUDA_VISIBLE_DEVICES"]="0"
import numpy as np
import cv2
import io
import requests
from PIL import Image
import pdb
from skimage.transform import resize
import matplotlib.pyplot as plt
import math
import random
import collections
import xml.etree.ElementTree as ET
from sklearn.metrics import pre... | santoshreddy254/Localization-of-Objects-Using-Unsupervised-Representation-Learning-and-Object-Proposal-Techniques | utils/gradcam.py | gradcam.py | py | 8,719 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "os.environ",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "numpy.ascontiguousarray",
"line_number": 128,
"usage_type": "call"
},
{
"api_name": "numpy.transpose",
"line_number": 128,
"usage_type": "call"
},
{
"api_name": "torch.from_n... |
74538785312 | import os
import subprocess
import sys
import pytest
from conftest import cache_clear
import chartpress
from chartpress import PRERELEASE_PREFIX, yaml
def check_version(tag):
chartpress._fix_chart_version(tag, strict=True)
def test_git_repo_fixture(git_repo):
# assert we use the git repo as our current wo... | jupyterhub/chartpress | tests/test_repo_interactions.py | test_repo_interactions.py | py | 18,231 | python | en | code | 50 | github-code | 1 | [
{
"api_name": "chartpress._fix_chart_version",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path.realpath",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "os.getcwd... |
911740610 | from django.http import HttpResponse
from django.shortcuts import render,redirect
import requests
import urllib.parse
# Create your views here.
def home(request):
if 'username' in request.session:
return render(request,'home.html')
else:
return redirect(login)
def login(request):
if request... | nitsuh21/clienttest | home/views.py | views.py | py | 5,633 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.shortcuts.render",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.redirect",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "reques... |
34539016350 | import librosa
import numpy as np
import matplotlib.pyplot as plt
import scipy as sp
from sklearn.metrics import accuracy_score, confusion_matrix
import seaborn as sns
import pandas as pd
from sklearn.decomposition import PCA
from scipy.signal import hamming
import scipy.signal.windows
def segment_vowel_silence(audio... | YukiTinNguyen/XLTHS | Bai2Trinh.py | Bai2Trinh.py | py | 10,259 | python | vi | code | 0 | github-code | 1 | [
{
"api_name": "librosa.util.frame",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "librosa.util",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "numpy.sum",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numpy.square",
"li... |
12095751954 | # -*- coding: utf-8 -*-
import azureml.core
from azureml.core import Experiment, Workspace
def main():
print('Testing Azure ML with a standalone Python script')
# Load the workspace from the saved config file
ws = Workspace.from_config()
print('Ready to use Azure ML {} to work with {}'.format(azur... | ThordurPall/MLOpsExercises | src/azure/azure_test_standalone_script.py | azure_test_standalone_script.py | py | 1,173 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "azureml.core.Workspace.from_config",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "azureml.core.Workspace",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "azureml.core.core",
"line_number": 11,
"usage_type": "attribute"
},
{
"... |
9991795351 | from tkinter import*
from tkinter import ttk
from PIL import Image, ImageTk
from attendance import Attendance
from student import Student
import os
from face_recognition import Face_Recognition
from train import Train
class Face_Recognition_System_Student:
def __init__(self,root):
self.root=root
... | KhushiGoyal123/face-recognition-student-attendance-system | main_student.py | main_student.py | py | 3,603 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "PIL.Image.open",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "PIL.Image.ANTIALIAS",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image",
"li... |
32395021882 | from django.db import models
#import datetime
# Create your models here.
BLACKLISTED_SHORTCUT_NAMES = ("admin","api")
class shortcut(models.Model):
shortcut_key = models.CharField(max_length=20,help_text="Key of the shortcut")
shortcut_value = models.URLField(help_text="The target of the shortcut") # URL of ... | Emojigit/shortcuts | main/models.py | models.py | py | 1,447 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.db.models.Model",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "django.db.models",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "django.db.models.CharField",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "... |
31637283761 | import json
from starter.objects import Starter, default_workflow_params
from starter.starter_helper import NullRequiredDataException
"""
Amazon SWF PostPerfectPublication starter, for API and Lens publishing etc.
"""
class starter_PostPerfectPublication(Starter):
def __init__(self, settings=None, logger=None):
... | elifesciences/elife-bot | starter/starter_PostPerfectPublication.py | starter_PostPerfectPublication.py | py | 1,674 | python | en | code | 19 | github-code | 1 | [
{
"api_name": "starter.objects.Starter",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "starter.objects.default_workflow_params",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "starter.starter_helper.NullRequiredDataException",
"line_number": 20,
"us... |
704341784 | import requests
from bs4 import BeautifulSoup
import json
link=requests.get("https://www.rottentomatoes.com/top/bestofrt/top_100_animation_movies/")
data=BeautifulSoup(link.text,"html.parser")
def movieData():
list=[]
x=0
mainDiv=data.find("div",class_="body_main container")
subDiv=mainDiv.find("table",... | Deepa-DD/web_scraping | Task1.py | Task1.py | py | 1,279 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "requests.get",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 32,
"usage_type": "call"
}
] |
34652128255 | from django import template
from selia_templates.custom_tags.components.base import ComplexNode
def tab(parser, token):
content = parser.parse(('endtab',))
parser.delete_first_token()
try:
_, url = token.split_contents()
except ValueError:
raise template.TemplateSyntaxError(
... | CONABIO-audio/selia-templates | selia_templates/custom_tags/components/navbars.py | navbars.py | py | 522 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.template.TemplateSyntaxError",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "django.template",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "selia_templates.custom_tags.components.base.ComplexNode",
"line_number": 16,
"usage_t... |
30739211294 | from typing import List
from fastapi import APIRouter, HTTPException
from ..models.user import User
from ..models.review import UserReview, Movie
from ..schemas.review import (
MovieResponseModel, MovieRequestModel, ReviewRequestModel, ReviewRequestPutModel, ReviewResponseModel
)
router = APIRouter(prefix='/revie... | Zozi96/api-fast | app/routers/review.py | review.py | py | 2,606 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "fastapi.APIRouter",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "schemas.review.MovieRequestModel",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "models.review.Movie.create",
"line_number": 15,
"usage_type": "call"
},
{
"api... |
9621780474 | import os
import glob
from bs4 import BeautifulSoup,Comment
import urllib.request
import requests
import json
uri = "https://www.carcomplaints.com/"
#read the webpage and store it as a string
webpage = urllib.request.urlopen(uri).read()
soup = BeautifulSoup(webpage,'html.parser')
#find all the <a> tags which consis... | ShreyashAF2704/RaH-Project | Scrapers/Cars_Complaint_Scraper.py | Cars_Complaint_Scraper.py | py | 7,859 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "urllib.request.request.urlopen",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "urllib.request.request",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "urllib.request",
"line_number": 11,
"usage_type": "name"
},
{
"api_nam... |
30025220732 | import csv
import datetime
def mark_attendance(student_id):
timestamp = datetime.datetime.now()
date = timestamp.date()
time = timestamp.time()
attendance_file = f"attendance_{date}.csv"
file_exists = check_file_exists(attendance_file)
with open(attendance_file, mode='a', newline='... | JAINMOHIT23/PROJECT-Bharat-Intern | PROJECT/attendance tracking.py | attendance tracking.py | py | 1,135 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "datetime.datetime.now",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "csv.writer",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "csv.reader",
... |
41612546375 | import os
import shutil
from typing import List, Tuple
import pytest
from src.models.running_token import RunningToken
from src.models.token import Token
# folder names and paths of all test files
test_files_folder_name = 'test_files'
xml_files_folder_name = 'xml'
temp_xml_files_folder_name = 'temp_xml'
def pytes... | rathaustreppe/bpmn-analyser | test/conftest.py | conftest.py | py | 3,398 | python | en | code | 3 | github-code | 1 | [
{
"api_name": "os.path.dirname",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 29,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line... |
22034815063 | import os
import cv2
from WordSegmentation import wordSegmentation, prepareImg
def main():
"""reads images from data/ and outputs the word-segmentation to out/"""
# read input images from 'in' directory
path = os.getcwd()
imgFiles = os.listdir(path + '/out/')
direc = 'segmented words'
os.mkdir(os.path.join(path,... | sanchitjain002/Handwritten | main1.py | main1.py | py | 2,286 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.getcwd",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.mkdir",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 12,
... |
30766428537 | import logging
from django.core.exceptions import ObjectDoesNotExist
from django.forms.models import model_to_dict
from core.services.file_interface.file_interface import FileInterface
from core.services.git_interface.git_auth import OAuth2Token
from core.models import Folder, FolderRepo, File
# from core.services.t... | meoook/Abyss-Translate | back/core/services/folder_interface.py | folder_interface.py | py | 7,781 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "core.services.git_interface.git_interface.GitInterface",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "core.models.Folder.objects.get",
"line_number": 24,
"usage_type"... |
30533875447 | from django import template
register = template.Library()
@register.filter
def rating(digit):
try:
digit = int(digit/2)
value = [1 for x in range(digit)]
for i in range(len(value),5):
value.append(0)
return value
except:
return [00000] | SkyRiS3s/Database-Project | blog/templatetags/extra_tags.py | extra_tags.py | py | 297 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.template.Library",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "django.template",
"line_number": 3,
"usage_type": "name"
}
] |
26940616488 | from common import read
from prime import is_prime
'''
main block that accepts upper and lower limit.
Finds the prime numbers within this range.
'''
def main() :
lower = read('Enter the lower range.\n')
upper = read('Enter the upper range.\n')
print(f'\nPrime numbers within the range ({lower},{upper}) are:... | Vi5iON/Cumulation | prime_series.py | prime_series.py | py | 476 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "common.read",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "common.read",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "prime.is_prime",
"line_number": 13,
"usage_type": "call"
}
] |
30036989484 | #!/usr/bin/env python3
import json
import os
import codecs
from werkzeug.utils import secure_filename
from flask import Flask, render_template, request, flash, redirect, send_from_directory, make_response, Markup
app = Flask(__name__)
app.secret_key = "super secret key"
app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * ... | cwirks01/NLP_Project | Lib/Dev/main_test.py | main_test.py | py | 1,371 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.getcwd",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "codecs.open",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 21... |
39616087477 | __author__ = 'jeremyma'
import os
import cPickle
from frontend import frontend
import sys, pdb
import config
import time
import numpy as np
from scipy.misc import logsumexp
from gmmmc import GMM
import sklearn.mixture
from gmmmc import MarkovChain, AnnealedImportanceSampling
import logging
import bob.bio.gmm.algorithm
... | jeremy-ma/bayesian-speaker-verification | system/mcmc_system.py | mcmc_system.py | py | 9,837 | python | en | code | 3 | github-code | 1 | [
{
"api_name": "bob.bio.gmm.algorithm.GMM",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "gmmmc.GMM",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "logging.info",
"l... |
19706165449 | from django.test import TestCase
from .forms import RecipeDetail
class TestForms(TestCase):
def test_recipe_detail(self):
form = RecipeDetail({'name': '', 'ingredients': '', 'directions': ''})
self.assertFalse(form.is_valid())
self.assertIn('name', form.errors.keys())
self.assertE... | Kat24C/recipe | recipes/test_forms.py | test_forms.py | py | 623 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.test.TestCase",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "forms.RecipeDetail",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "forms.RecipeDetail",
"line_number": 14,
"usage_type": "call"
}
] |
5139072916 | import speech_recognition as sr
import sys
import os
import time
os.system('espeak "{}"'.format("hello shivang, we welcome you to this device, Have a great time"))
os.system('espeak "{}"'.format("When you want to close your devise please say stop"))
os.system('espeak "{}"'.format("Say start to start your devise")... | 32shivang/Blind-Eye | speech_to_text.py | speech_to_text.py | py | 1,185 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.system",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "os.system",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.system",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "speech_recognition.Microphone",
"line_... |
22873473584 | from playwright.sync_api import sync_playwright
from time import sleep
def clicker(path):
page.click(path)
def input_text(path, text):
page.fill(path, text)
email = "your email"
senha = "your key"
while True:
print('start btc')
with sync_playwright() as p:
browser = p.chromium.launch()
... | AllanCristiano/botFreeBtcNoCaptcha | main.py | main.py | py | 1,062 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "playwright.sync_api.sync_playwright",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "time.sleep"... |
30491801057 | __author__ = 'breddels'
import logging
logger = logging.getLogger("vaex.file")
import vaex.file.other
def can_open(path, *args, **kwargs):
for name, class_ in list(vaex.file.other.dataset_type_map.items()):
if class_.can_open(path, *args):
return True
def open(path, *args, **kwargs):
dataset_class = None
fo... | Al33Bundy/Vaex | vaex/file/__init__.py | __init__.py | py | 639 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "vaex.file.other.file.other.dataset_type_map.items",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "vaex.file.other.file",
"line_number": 8,
"usage_type": "attribute"
},... |
34277876627 | from django.urls import path
from .views import (
PostList, PostSearch, PostDetail, PostCreate, PostUpdate,
PostDelete, AppointmentView, CategoryListView, subscribe,
)
from django.contrib.auth.views import LogoutView, LoginView
from django.contrib.auth.decorators import login_required
from sign.views imp... | dimasiksergeevi4/newspaper | news/urls.py | urls.py | py | 1,530 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.urls.path",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "views.PostList.as_view",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "views.PostList",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "django.urls.pa... |
11910534693 | from flask import jsonify, request
from app.models import Manufacturer, Pharmacokinetic_properties, Token
from app import db
def updatePharmacokinetic():
'''update pharmacokinetic properties record'''
data = request.get_json()
token = request.headers['TOKEN']
id=int(data['id'])
t=Token.query.... | the1Prince/drug_repo | app/updates/updatePharmacokineticProps.py | updatePharmacokineticProps.py | py | 1,978 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.request.get_json",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "flask.request",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "flask.request.headers",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "flask.re... |
2427092929 | from src.dataset.create_dataset import DataframePrepAllMod
from src.constants.constants import *
from src.model.model import ConvModel, train_cp
from src.utils.cross_val import TrainTestSplitter
from src.utils.utils import *
import tensorflow as tf
import argparse
import os
def main(args):
device = "GPU" if tf.... | dheerajpr97/Explainable-AI-Non-EEG | train.py | train.py | py | 5,465 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "tensorflow.config.list_physical_devices",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "tensorflow.config",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "os.path.isfile",
"line_number": 18,
"usage_type": "call"
},
{
"api... |
22525713243 | from setuptools import setup
with open("README.md") as f:
readme = f.read()
setup(
name="dpr",
version="1.0.0",
description="Facebook AI Research Open Domain Q&A Toolkit",
url="https://github.com/facebookresearch/DPR/",
classifiers=[
"Intended Audience :: Science/Research",
"Li... | microsoft/LMOps | uprise/DPR/setup.py | setup.py | py | 930 | python | en | code | 2,623 | github-code | 1 | [
{
"api_name": "setuptools.setup",
"line_number": 6,
"usage_type": "call"
}
] |
35462627946 | import argparse
import cv2
import random
import time
#constructing arguements
ap=argparse.ArgumentParser()
ap.add_argument("-i","--image",required=True,help="path to the input image")
ap.add_argument("-m","--method",type=str,default="fast",choices=["fast","quality"],help="selective search method")
args=vars(ap.parse_a... | Gaurav4604/MachineLearning-mainly-object-detection | Selective Search using OpenCV/selective_search.py | selective_search.py | py | 1,713 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "cv2.ximgproc.segmentatio... |
24231103307 | # We are U19886
## Imports & pre-proceessing
import os
import networkx as nx
import matplotlib.pyplot as plt
from matplotlib import pylab
import numpy as np
import pickle
os.chdir('desktop/ELU 501 data science')
## Loading the graph
G = nx.read_gexf("mediumLinkedin.gexf")
## Loading the data
colleges = {}
locat... | mehdah/ELU-501-Data-Science | ELU 501 Challenge 1.py | ELU 501 Challenge 1.py | py | 3,106 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.chdir",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "networkx.read_gexf",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pickle.load",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "pickle.load",
"line_numbe... |
9930223943 | from tqdm import tqdm
import json
import numpy as np
import torch
import torch.nn as nn
LABEL2ID = {
"NO-LABEL": 0,
"обеспечение исполнения контракта": 1,
"обеспечение гарантийных обязательств": 2
}
class TokenCLFModel(torch.nn.Module):
def __init__(self, pretrained_model, droupout=0.5, num_clas... | aebogdanova/text-fragment-extraction | scripts/TokenCLF/train.py | train.py | py | 6,755 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "torch.nn",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "torch.nn.Dropout",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "torch.nn.Linear",
"line_n... |
5928114479 | import math
import torch
from ocpmodels.modules.scaling import ScaleFactor
from .atom_update_block import AtomUpdateBlock
from .base_layers import Dense, ResidualLayer
from .efficient import EfficientInteractionBilinear
from .embedding_block import EdgeEmbedding
class InteractionBlock(torch.nn.Module):
"""
... | Open-Catalyst-Project/ocp | ocpmodels/models/gemnet_oc/layers/interaction_block.py | interaction_block.py | py | 23,399 | python | en | code | 518 | github-code | 1 | [
{
"api_name": "torch.nn",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "base_layers.Dense",
"line_number": 95,
"usage_type": "call"
},
{
"api_name": "torch.nn.ModuleList",
"line_number": 171,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"... |
1311232607 | """Module containing class for collection of cases"""
from typing import Union, List, Dict
from sumo.wrapper import SumoClient
from fmu.sumo.explorer.objects._document_collection import DocumentCollection
from fmu.sumo.explorer.objects.case import Case
from fmu.sumo.explorer.pit import Pit
_CASE_FIELDS = [
"_id",
... | equinor/fmu-sumo | src/fmu/sumo/explorer/objects/case_collection.py | case_collection.py | py | 4,117 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "fmu.sumo.explorer.objects._document_collection.DocumentCollection",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "sumo.wrapper.SumoClient",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "typing.Dict",
"line_number": 21,
"usage_type": ... |
24295593369 | from itertools import combinations
def isPrime(number):
if number < 2:
return False
else:
for num in range(2, number):
if number % num == 0:
return False
return True
def Prime(n):
prime_num = []
for num in range(n):
if isPrime(num):
... | HyunSung-Na/TIL-algorism | 알고리즘/3주 모의고사 소수.py | 3주 모의고사 소수.py | py | 646 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "itertools.combinations",
"line_number": 21,
"usage_type": "call"
}
] |
38819126631 | from flask import Flask, render_template, request
import jsonify
import requests
import pickle
import numpy as np
import sklearn
app = Flask(__name__)
model = pickle.load(open('insurance_rf.pkl', 'rb'))
@app.route('/')
def home():
return render_template('index.html')
@app.route("/predict", methods=['POST'])
def ... | helloraghav1305/Medical-Insurance-Forecast | app.py | app.py | py | 1,540 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pickle.load",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "flask.render_template",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "flask.request.method",
... |
71547921315 | import subprocess as sp
from collections import defaultdict
import numpy as np
import pandas as pd
import argparse
import pickle
import os
import re
'''
This script creates feature matrix from VCF files for downstream ML analysis
'''
parser=argparse.ArgumentParser(description='Append MIC phenotype to MIC dataframe')
... | SSID08/ML_thesis | Scripts/Append_MIC_Phenotype.py | Append_MIC_Phenotype.py | py | 1,205 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path.basename",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "pandas.Series",... |
37453131182 | import numpy as np
from qiskit import Aer, QuantumCircuit
from qiskit.circuit import Parameter
from qiskit.circuit.library import RealAmplitudes, ZZFeatureMap
from qiskit.opflow import StateFn, PauliSumOp,AerPauliExpectation,ListOp,Gradient
from qiskit.utils import QuantumInstance,algorithm_globals
algorithm_globals... | Rin-The-QT-Bunny/quantum_networks | basic_qnns.py | basic_qnns.py | py | 1,572 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "qiskit.utils.algorithm_globals.random_seed",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "qiskit.utils.algorithm_globals",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "qiskit.opflow.AerPauliExpectation",
"line_number": 13,
"us... |
727123219 | from RadialBasisFunction import *
import numpy as np
from sklearn import datasets
C=3
F=2
X,Y = datasets.make_classification(
n_features=C,
n_classes=F,
n_samples=200,
n_redundant=0,
n_clusters_per_class=1
)
X=X.T
Y=np.array([Y])
RBF =RadialBasisFunction(C,4)
RBF.Train(X,Y,5,100)
| dani2442/DeepLearning | RadialBasisFunction/test.py | test.py | py | 305 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "sklearn.datasets.make_classification",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sklearn.datasets",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "numpy.array",
"line_number": 16,
"usage_type": "call"
}
] |
39631632894 | import os
from pathlib import Path
from unittest.mock import patch
import pytest
import pytest_check as check
import yaml
from msticpy.config.comp_edit import CompEditStatusMixin
from msticpy.config.ce_azure_sentinel import CEAzureSentinel, _validate_ws
from msticpy.config.ce_common import get_def_tenant_id
from mstic... | sh9369/msticpy | tests/config/test_item_editors.py | test_item_editors.py | py | 12,896 | python | en | code | null | github-code | 1 | [
{
"api_name": "msticpy.config.comp_edit.CompEditStatusMixin.testing",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "msticpy.config.comp_edit.CompEditStatusMixin",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "msticpy.config.mp_config_control.get_mpcon... |
4699497508 | import os
import sys
import json
import requests
from dotenv import load_dotenv
load_dotenv()
try:
path = sys.argv[1]
except IndexError:
path = input('Path to .md file:\n')
with open(path, 'r') as file:
md_text = file.read()
TOKEN = os.getenv('TOKEN')
URL = 'https://api.github.com/markdown'
HEADERS = {... | eo-uk/markdown-to-html-converter | main.py | main.py | py | 1,302 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "dotenv.load_dotenv",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "os.getenv",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line_n... |
6874429677 | from functools import reduce
numeros = input("ingrese numeros:")
numerosEnList = sorted(numeros)
print(numerosEnList)
numerosImpares = []
for i in numerosEnList:
if int(i) % 2 != 0:
numerosImpares.append(int(i))
print(numerosImpares)
def suma(a, b):
return a + b
resultado = reduce(suma, num... | Guido564/open-bootcamp-fullstack | Python/Modulo 9/tarea2.py | tarea2.py | py | 352 | python | pt | code | 0 | github-code | 1 | [
{
"api_name": "functools.reduce",
"line_number": 17,
"usage_type": "call"
}
] |
16098184030 | import pygame
import datetime
pygame.init()
WIDTH=1080
HEIGHT=720
screen = pygame.display.set_mode((WIDTH, HEIGHT))
clock=pygame.image.load("images/main-clock.png").convert()
scale_clock = pygame.transform.scale(
clock, (clock.get_width() // 2,
clock.get_height() // 2))
clockr=scale_clock.get_rect(ce... | aminazhumabayeva/PP2 | lab7/1clock.py | 1clock.py | py | 1,400 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pygame.init",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "pygame.display.set_mode",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pygame.display",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "pygame.image.loa... |
25845095235 | # Creating a Bouncing Ball Screensaver using OpenCV-Python
# Task- Create a Window that we can write text on. If we don’t write for 5 seconds screensaver will start.
import cv2
import numpy as np
def screensaver():
img = np.zeros((480,640,3),dtype='uint8')
dx,dy =1,1
x,y = 100,100
while True:
... | aryaniiit002/Computer-Vision | Basic Programs/screensaver.py | screensaver.py | py | 1,769 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "numpy.zeros",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "cv2.waitKey",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 15... |
2036561592 | import numpy as np
import gudhi
import gudhi.representations
import cv2
from skimage.feature import local_binary_pattern
def img_gray(path):
img = cv2.imread(path)
h,w = img.shape[:2] #获取图片的high和wide
img_gray=np.zeros([h,w],img.dtype) #创建一张和当前图片大小一样的单通道图片
for i in range(h):
for j in range(w):
m... | Yuhan0524/TDA_face_morph_detection | get_features.py | get_features.py | py | 1,594 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "cv2.imread",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "skimage.feature.local_binary_pattern",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "gudhi.Rips... |
4223512763 | import numpy as np
import pandas as pd
import imageio as io
from skimage.measure import label, regionprops
from skimage.color import label2rgb,gray2rgb
from skimage.segmentation import watershed
import cv2
import os
import scipy.ndimage as ndi
def watershedSegStack(seg_stack,num_lesions,postprocess_dir,cam_num):
... | mattposka/PDPS | postprocess.py | postprocess.py | py | 7,502 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.sum",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "cv2.imwrite",
"line_number": ... |
4384202526 | '''
RESPONSE WITH HTML CONTENTS
Let's response with our first web page written in HTML. We know nothing about HTML. It is the language used for the
creating web pages,that describes the structure of the document.
Web browsers receive HTML documents from a web server or from local storage and render the documents int... | helenyaben/2018-19-PNE-practices | PNE-Session11/HTML_response.py | HTML_response.py | py | 3,059 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "termcolor.cprint",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "socket.socket",
"line_number": 79,
"usage_type": "call"
},
{
"api_name": "socket.AF_INET",
"line_number": 79,
"usage_type": "attribute"
},
{
"api_name": "socket.SOCK_STREAM... |
70802571555 | from sys import platform
import pandas as pd
import numpy as np
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.metrics.pairwise import cosine_similarity
from tabulate import tabulate
import string
import settings
df = pd.read_csv("Cleaned_dataset.csv")
df = df.iloc[0:10000,:]
features = ['N... | kusai99/Game-Recommendation-system | GameRec.py | GameRec.py | py | 3,958 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "sys.platform",
"line_number": 73,
"usage_type": "name"
},
{
"api_name": "sys.platform",
"line_number": 74,
"usage_type": "name"
},
{
"api_name": "sys.platform",
"line_num... |
25587263944 | from flask import Flask, request, render_template
import numpy as np
import tensorflow as tf
from tensorflow.keras.preprocessing import image
import os
app = Flask(__name__)
# Get the absolute path to your application's directory
#app_directory = os.path.dirname(os.path.abspath(__file__))
# Construct the absolute pa... | Aravind0510/plant_disease | app.py | app.py | py | 2,650 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.keras.models.load_mod... |
2733857930 | import requests
from bs4 import BeautifulSoup
import os
#os.chdir('~/crawl')
from selenium import webdriver
from selenium.webdriver import FirefoxOptions
from selenium.webdriver.common.by import By
opts = FirefoxOptions()
opts.add_argument("--headless")
browser = webdriver.Firefox(firefox_options=opts)
#browser = webd... | elSomewhere/AnalyticsTextGen_DL | crawl_SKA.py | crawl_SKA.py | py | 1,701 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "selenium.webdriver.FirefoxOptions",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver.Firefox",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 11,
"usage_type": "name"
},
{
"ap... |
41285122264 | from __future__ import unicode_literals
import json
import datetime
from django.template.defaultfilters import escape
from program.models import Program
from notification.models import Notif
from ourjseditor import api
from .models import Comment
# /program/PRO_ID/comment/new
@api.StandardAPIErrors("POST")
@api.lo... | OurJSEditor/OurJSEditor | django_code/comment/api.py | api.py | py | 5,876 | python | en | code | 29 | github-code | 1 | [
{
"api_name": "json.loads",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "models.Comment.objects.get",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "models.Comment.objects",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "mod... |
4246358935 | import pandas as pd
import re
from utils import ANALYTICS_DATASET, ENVIRONMENT_SHORT_NAME
def get_data_archiving(sql_file):
"""Run SQL query and save data in a dataframe."""
params = {"{{ANALYTICS_DATASET}}": ANALYTICS_DATASET}
file = open(sql_file, "r")
sql = file.read()
for param, table_name ... | pass-culture/data-gcp | jobs/etl_jobs/external/metabase-archiving/archiving.py | archiving.py | py | 6,570 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "utils.ANALYTICS_DATASET",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "pandas.read_gbq",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pandas.to_datetime",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "utils.ENVIR... |
16805215564 | import multiprocessing as mp
from parallel_data_processing.parallel_join.hash_join import hash_join
def range_partition(data, range_indices):
result = []
new_data = data[:]
new_data=sorted(new_data,key=lambda new_data:new_data[1])
# Calculate the number of bins
range_index = len(range_indices)
... | OceanicSix/Python_program | parallel_data_processing/parallel_join/disjoint.py | disjoint.py | py | 2,271 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "multiprocessing.Pool",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "parallel_data_processing.parallel_join.hash_join.hash_join",
"line_number": 51,
"usage_type": "argument"
}
] |
31325561176 | import glob
import os
import corner
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scipy.stats
import matplotlib.lines as mlines
VIOLET_COLOR = "#8E44AD"
BILBY_BLUE_COLOR = '#0072C1'
PARAMS = dict(
# chi_eff=dict(l=r"$\chi_{eff}$", r=(-1, 1)),
# chi_p=dict(l=r"$\chi_{p}$", r=(... | avivajpeyi/bh_getting_kicks | creating_an_agn_prior/add_agn_spins_to_samples.py | add_agn_spins_to_samples.py | py | 3,970 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.pi",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "numpy.pi",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "numpy.pi",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "numpy.exp",
"line_numbe... |
38202371506 | from datetime import datetime, timedelta
import requests
import json
import eel
@eel.expose
def ten_newest_question(tag):
url = "http://api.stackexchange.com/2.2/search?order=desc&sort=creation&tagged=" + tag + \
"&site=stackoverflow&filter=withbody&pagesize=10"
data = requests.get(url).js... | Taichi-Pink/Android-related-questions-Stackoverflow | Web.py | Web.py | py | 954 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "requests.get",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "eel.expose",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "datetime.datetime.today",
"... |
29520479895 | import pytest
import requests
@pytest.fixture
def api_base_address():
return "http://localhost:5000"
@pytest.fixture
def pq_data():
return [(0, 4), (1, 7)]
@pytest.fixture
def pq_get_data():
return {"highest": {"index": 1, "key": 7}, "content": [
{"index": 1, "key": 7}, {"index": 0, "key": 4}
... | AlanKev117/demo-restful-api | test/test_api.py | test_api.py | py | 2,189 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pytest.fixture",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "pytest.fixture",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "pytest.fixture",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "pytest.fix... |
6912998800 | #!/usr/bin/env python3
import collections
import os
import subprocess
DATE = "2022-01-01"
BRANCH = 'main'
print("Statistics on the %s branch after %s" % (BRANCH, DATE))
print("cwd: %s" % os.getcwd())
proc = subprocess.run(['git', 'log', '--after=%s' % DATE, BRANCH],
stdout=subprocess.PIPE,
... | vstinner/misc | python/git_commit_stats.py | git_commit_stats.py | py | 657 | python | en | code | 22 | github-code | 1 | [
{
"api_name": "os.getcwd",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "subprocess.run",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "subprocess.PIPE",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "collections.Counter",
... |
15111556685 | import argparse
import zipfile
import io
from lxml import etree
namespace = "{http://schemas.microsoft.com/3dmanufacturing/core/2015/02}"
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Strip metadata from 3MF files')
parser.add_argument('source', metavar='source', type=str, nargs='... | nallath/3MFMetadataStripper | stripMetadata.py | stripMetadata.py | py | 1,789 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "zipfile.ZipFile",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "zipfile.ZIP_DEFLATED",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "lxm... |
40888320190 | from tkinter import simpledialog
import math
import pygame
pygame.init()
tamanho = (850, 560)
tela = pygame.display.set_mode(tamanho)
pygame.display.set_caption("Space Marker")
# Definir o ícone da janela
icone = pygame.image.load("space.png")
pygame.display.set_icon(icone)
fundo = pygame.image.load("bg.jpg")
pygame... | biecoski/spacemaker | main.py | main.py | py | 4,644 | python | pt | code | 0 | github-code | 1 | [
{
"api_name": "pygame.init",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pygame.display.set_mode",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pygame.display",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "pygame.display.s... |
31509541216 | from django.db import models
from django.shortcuts import reverse
from django.utils import timezone
from django.contrib.auth.models import User
class Callout(models.Model):
BWD = 'BWD'
CCH = 'CCH'
HND = 'HND'
SYO = 'SYO'
FACILITY = (
(BWD, 'BWD'),
(CCH, 'CCH'),
(HND, 'HND')... | Megaprotas/work_project | my_app/models.py | models.py | py | 2,445 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.db.models.Model",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "django.db.models",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "django.db.models.ForeignKey",
"line_number": 45,
"usage_type": "call"
},
{
"api_name":... |
17145944405 | import json
import random
import re
import string
import sys
from json import JSONDecodeError
from entities import ConfigEntity, UserEntity
from network import exponential_backoff_request
API_URL = 'http://127.0.0.1:8000'
API_METHOD_SIGNUP = '/api/signup'
API_METHOD_SIGNIN = '/api/token/'
API_METHOD_CREATE_POST = '/a... | Omkommersind/drf_template_bot | bot.py | bot.py | py | 3,957 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "json.load",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "entities.ConfigEntity",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "sys.exit",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "json.JSONDecodeError",
"... |
35110283677 | import threading
from mqtt_utils import publish_single #, subscribe_callback
import config
import time
import json
import paho.mqtt.client as mqtt
import ssl
import config
class ApproveThread(threading.Thread):
def __init__(self, gameId, amount_of_players, cb, playerId=None, amountXRT=0):
super(ApproveThr... | Vourhey/aira-monopoly-server | approve.py | approve.py | py | 2,272 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "threading.Thread",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "paho.mqtt.client.Client",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "paho.mqtt.client",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "config... |
2016504957 | from __future__ import division
import sys
from math import*
import numpy
from numpy import*
import random
from matplotlib import pyplot as plt
R=10**12 #cm Radius
Tau=10 #Opacity
Lambda=R/Tau #Mean Free Path
c=3.0*10**9 #cm/s
nph=10000
TimeS=numpy.empty(nph)
for p in range(nph):
i=1
... | chatcher99/Cassandra_Hatcher | Finished Thesis Codes (Unused)/Timing Scattered Photons in Star.py | Timing Scattered Photons in Star.py | py | 1,892 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.empty",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.arccos",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "numpy.random.rand",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_n... |
71015854435 | from collections import deque
class TreeNode:
def __init__(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
class Codec:
def serialize(self, root) -> str:
if not root:
return '[]'
ans = []
q = deque()
... | yskang/AlgorithmPractice | libs/leet_code_utils.py | leet_code_utils.py | py | 1,580 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "collections.deque",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "collections.deque",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "collections.deque",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "collections.deq... |
41146694685 | import multiprocessing
"""
result = []
def Calculate_Square(numbers):
for i in numbers:
print("Square :", i * i)
result.append(i * i)
print("Inside Function :", result)
if __name__ == "__main__":
list = [1, 2, 3, 4, 5]
p1 = multiprocessing.Process(target = Cal... | naveedeveloper/operating-system | sharingData.py | sharingData.py | py | 1,414 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "multiprocessing.Array",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "multiprocessing.Process",
"line_number": 41,
"usage_type": "call"
}
] |
17159878700 | from .models import Coleccion, Autor, Libro
from django.core.cache import cache
from django.conf import settings
from django.contrib.sites.models import Site
def colecciones(request):
return {
'colecciones': Coleccion.objects.filter(orden__lt=9).order_by("orden"),
"DEBUG": settings.DEBUG,
... | ignacionf/cuenco | home/context_processors.py | context_processors.py | py | 757 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "models.Coleccion.objects.filter",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "models.Coleccion.objects",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "models.Coleccion",
"line_number": 10,
"usage_type": "name"
},
{
"ap... |
26661553275 | # -*- coding: utf-8 -*-
# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html
from pymongo import MongoClient
from crop_spiders.items import CropItem, PestItem, PestItem2
class CropPipeline(object):
... | jllan/spiders_mess | crop_spiders/crop_spiders/pipelines.py | pipelines.py | py | 899 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pymongo.MongoClient",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "crop_spiders.items.CropItem",
"line_number": 22,
"usage_type": "argument"
},
{
"api_name": "crop_spiders.items.PestItem",
"line_number": 24,
"usage_type": "argument"
},
{
... |
9058951679 | from __future__ import annotations
from typing import List, Tuple, Optional
import re
import os
from .basic import Unit
from .pattern import PatternLoader
class VplParser:
@staticmethod
def finish(text):
return text if text.endswith("\n") else text + "\n"
@staticmethod
def unwrap(text):
... | senapk/tko | src/tko/loader.py | loader.py | py | 8,186 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "typing.Optional",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "re.sub",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "re.MULTILINE",
"line_numbe... |
40475531621 | import cv2
import numpy as np
import os
import torch
from torch.utils.data import Dataset
class MaskDataset(Dataset):
def __init__(self, data_dir, img_transform, msk_transform, img_resize=(256, 256), msk_resize=(32, 32)):
self.image_paths = []
self.masks_paths = []
self.img_transform = img... | OYMiss/ssdd-net | ssdd/dataset.py | dataset.py | py | 1,693 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "torch.utils.data.Dataset",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "os.listdir",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "cv2.resize",
"line_... |
12171462089 | import torch
import torch.nn as nn
from attention import MultiHeadedAttention
class FeedForward(nn.Module):
def __init__(self, input_dim: int, dim: int = 2048, dropout: float = 0.1) -> None:
super(FeedForward, self).__init__()
self.feed_forward = nn.Sequential(
nn.Linear(input_dim, dim... | VashishtMadhavan/transformers-scratch | blocks.py | blocks.py | py | 2,597 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "torch.nn.Module",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "torch.nn.Sequential",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_n... |
4190657104 | #################################
# Your name:Yonatan Gertskin
#################################
# Please import and use stuff only from the packages numpy, sklearn, matplotlib
import numpy as np
import matplotlib.pyplot as plt
import numpy.random
from sklearn.datasets import fetch_mldata
from scipy.io import loadmat... | Maltmark/hello-world | perceptron - Copy.py | perceptron - Copy.py | py | 4,050 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.zeros",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "numpy.sign",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.dot",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.dot",
"line_number": 29,
... |
45021048063 | import os
import cv2
global i
global coordinates
def on_event(event, x, y, flags, img):
global i
global coordinates
if i < 4:
if event == cv2.EVENT_LBUTTONDOWN:
xy = "%d,%d" % (x, y)
coordinates[i][0] = int(x)
coordinates[i][1] = int(y)
cv2.circle(... | INFWOLAD/OCR_BookPages | assistant/mark.py | mark.py | py | 1,272 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cv2.EVENT_LBUTTONDOWN",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "cv2.circle",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "cv2.putText",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "cv2.FONT_HERSHEY_PL... |
39956940067 | from models.yolo import *
from models.ssd import *
from util import *
from collections import defaultdict
import argparse
import time
import pickle as pkl
import random
import pdb
import os.path as osp
#Path vars
dirname = os.path.dirname(__file__)
CLASS_NAMES_PATH = os.path.join(dirname, 'data/image/coco/coco.names')... | RaedShabbir/Object-Detection | main.py | main.py | py | 15,219 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.path.path.dirname",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path.path",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "os.path",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "os.path.path.join",
... |
18718545308 | import logging
import sys
from pathlib import Path
from typing import Union
import datetime
import discord.ext.commands
from discord import Message
from discord.ext.commands.bot import Bot
from google.cloud import firestore
from discord.ext import commands
from discord_slash import SlashCommand, SlashContext
from .an... | suhail339/Discord-Dictionary-Bot | discord_dictionary_bot/discord_bot_client.py | discord_bot_client.py | py | 4,500 | python | en | code | null | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "discord.ext.commands.bot.Bot",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "discord.Message",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "discor... |
13589234475 | from django import forms
from django.utils.translation import gettext_lazy as _
from django.contrib.auth import get_user_model
from .models import Blog
class BlogForm(forms.ModelForm):
class Meta:
model = Blog
fields = ['title', 'slug', 'content', 'categories', 'cover', 'is_vip', 'status', 'autho... | Adler-KZ/AKLog | blogs/forms.py | forms.py | py | 1,164 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.forms.ModelForm",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "django.forms",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "models.Blog",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "django.forms.TextI... |
19979055197 | """This module contains a function for loading and processing the
distributed representations for the dataset in question. Then generating
a BatchGenerator that is compatible with the modified pipeline.
The modified pipeline will then train the specified model with the
input distributed representations along with its ... | paulmorio/DrugPairScoringDR | train_dr_model.py | train_dr_model.py | py | 8,143 | python | en | code | 5 | github-code | 1 | [
{
"api_name": "chemicalx.data.BatchGenerator",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "chemicalx.data.BatchGenerator",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "chemicalx.modified_dr_pipeline",
"line_number": 72,
"usage_type": "call"
},... |
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