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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
86483699 | import json, pika
from django.http import JsonResponse
from student.models import Student
from course.models import Course
from django.db import transaction
def choosecourse(request):
connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
channel = connection.channel()
channel.queu... | null | course-select-system-bakend/student/producer.py | producer.py | py | 1,879 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pika.BlockingConnection",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pika.ConnectionParameters",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "django.db.... |
275983406 | import tkinter as tk
import sqlite3
import time
import random
import os
class cell():
#each cell is it's own object
def __init__(self, curYInd, curXInd, grid, IsEdge, CellNum, window):
self.Window = window
self.__alive = False
self.mygrid = grid
self.__Edge = IsEdge
... | null | Final Ver (v2).py | Final Ver (v2).py | py | 44,337 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "tkinter.Frame",
"line_number": 151,
"usage_type": "call"
},
{
"api_name": "tkinter.Frame",
"line_number": 155,
"usage_type": "call"
},
{
"api_name": "tkinter.Label",
"line_number": 169,
"usage_type": "call"
},
{
"api_name": "tkinter.Label",
"lin... |
148977674 | import os
import io
from setuptools import find_packages, setup
# Utility Function to read the README file
# Used for the long_description. It's nice, because now 1) we have a top level
# README file and 2) it's easier to type in the README file than to put a raw
# string in below
# Read in the README for the long de... | null | setup.py | setup.py | py | 998 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "io.open",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "setuptools.setup",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "setuptools.find_packages",
"line_number": 23,
"usage_type": "call"
}
] |
280919751 | import cv2
import time
import numpy as np
import module as m
import autopy
wCam, hCam = 640, 480
pTime = 0
smoothenImg = 7
plocX, plocY = 0, 0
clocX, clocY = 0, 0
detector = m.handDetector(maxHands=1)
frameR = 100 # frame Reduction
cap = cv2.VideoCapture(0)
cap.set(3, wCam)
cap.set(4, hCam)
cap.set(10... | null | ControlMouse.py | ControlMouse.py | py | 2,214 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "module.handDetector",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "cv2.VideoCapture",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "autopy.screen.size",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "autopy.screen... |
530664784 | # -*- coding: utf-8 -*-
from docx import Document
import numpy
from wordcloud import WordCloud
from functools import reduce
import matplotlib.pyplot as plt
doc = Document("../data/nuevoacuerdo.docx") #lee documento
parrafos = doc.paragraphs #saca parrafos
parra = []
for p in parrafos:
parra.append(p.text)
parrafos... | null | backend/pintar_nube.py | pintar_nube.py | py | 2,700 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "docx.Document",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords.words",
"line_number": 75,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords",
"line_number": 75,
"usage_type": "name"
},
{
"api_name": "nltk.c... |
459904055 | # This file is associated with the book
# "Machine Learning Refined", Cambridge University Press, 2016.
# by Jeremy Watt, Reza Borhani, and Aggelos Katsaggelos.
import numpy as np
import matplotlib.pyplot as plt
import csv
import pandas as pd
# import training data
def load_data(csvname):
# load in data
data... | null | mlrefined_hw_solutions_backup/mlrefined_hw_coding_solutions/Python2_solutions/Chapter_4/Exercise_4_19/exercise_4_19_solution.py | exercise_4_19_solution.py | py | 4,269 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.asarray",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.ones",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "numpy.shape",
"line_numb... |
374422231 | import sys
import os
import maya.mel as mel
path = 'T:/dwtv/hub/Tools/Rig/scripts/bb/mel/'
melFiles = os.listdir('T:/dwtv/hub/Tools/Rig/scripts/bb/mel')
for file in melFiles:
mel.eval( 'source "%s%s"'%(path,file))
file = __file__
filePath = os.path.split(file)
bb = os.path.split(filePath[0])
s... | null | dwScripts/BB_toolBox.py | BB_toolBox.py | py | 751 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.listdir",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "maya.mel.eval",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "maya.mel",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "os.path.split",
"line_number": 1... |
587410325 | try:
from termcolor import colored
except ImportError:
DISABLE_COLORS = True
else:
DISABLE_COLORS = False
#: Red color constant for :func:`.ievv_colorize`.
COLOR_RED = 'red'
#: Blue color constant for :func:`.ievv_colorize`.
COLOR_BLUE = 'blue'
#: Yellow color constant for :func:`.ievv_colorize`.
COLOR_Y... | null | ievv_coderefactor/colorize.py | colorize.py | py | 1,348 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "termcolor.colored",
"line_number": 56,
"usage_type": "call"
}
] |
563585153 | import argparse
import os
import sys
import torch
from net import N2N
from torch.autograd import Variable
from torch.nn.utils import clip_grad_norm
from util import long_tensor_type
from util import process_data, get_batch_from_batch_list, generate_batches
def train_network(train_batch_list, val_batch_list, test_bat... | null | memory_network_n2n/main.py | main.py | py | 7,867 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "net.N2N",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "net.cuda",
"line_... |
520567531 | import json
import logging
from checkov.common.models.enums import CheckResult, CheckCategories
from checkov.terraform.checks.resource.base_resource_check import BaseResourceCheck
class BatchJobIsNotPrivileged(BaseResourceCheck):
def __init__(self):
name = "Batch job does not define a privileged containe... | null | checkov/terraform/checks/resource/aws/BatchJobIsNotPrivileged.py | BatchJobIsNotPrivileged.py | py | 1,235 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "checkov.terraform.checks.resource.base_resource_check.BaseResourceCheck",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "checkov.common.models.enums.CheckCategories.GENERAL_SECURITY",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "checkov.... |
17179473 | import os, logging
import yaml
default_config = os.path.join("config", "configuration.yml")
class Configuration:
def __init__(self, config_file=default_config):
self.config_file = config_file
self.reload()
def reload(self):
with open(self.config_file, "r") as f:
conf =... | null | pytid/utils/configuration.py | configuration.py | py | 491 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.join",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "yaml.safe_load",
"line_number": 17,
"usage_type": "call"
}
] |
581366069 |
from flask import Flask, render_template, request, jsonify
# 'render_template' renders templates and 'request' handles http requests
import sqlite3
app = Flask(__name__)
@app.route('/')
def home():
return render_template('home.html')
@app.route('/movie', methods = ['POST'])
def movie():
connection = sqlite... | null | blog.py | blog.py | py | 1,278 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Flask",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "flask.render_template",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "flask.request.form",... |
518724681 | from sklearn import datasets
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from sklearn.decomposition import PCA
from mpl_toolkits.mplot3d import Axes3D
iris = datasets.load_iris()
#以花瓣作为：2,：3
#以花蕊作为：0:1
x = iris.data[:,1]#x-axis - sepal length
... | null | ML_1/org_ml_test/test_2.py | test_2.py | py | 1,568 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sklearn.datasets.load_iris",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sklearn.datasets",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "sklearn.decomposition.PCA",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "m... |
586681869 | from autoprotocol.protocol import Protocol
import json
p = Protocol()
src_plate= p.ref("src_plate", None, "96-pcr", discard=True)
dest_plate= p.ref("dest_plate", None, "384-flat", discard=True)
xfer_vol = [10]*96;
shape_format='SBS96';
# common parameters for all stamps performed
stamp_kwargs = {
'new_defaults': T... | null | example_run3.py | example_run3.py | py | 946 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "autoprotocol.protocol.Protocol",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 35,
"usage_type": "call"
}
] |
533340307 | #coding:utf-8
#cython:language_level=2
import forward
import numpy as np
import pandas as pd
import os, time, glob
import tensorflow as tf
import PIL.Image as Image
import matplotlib.pyplot as plt
from skimage.measure import compare_psnr, compare_ssim
sigma = 25.0
BATCH_SIZE = 1
out_dir = "./data/output/"
test_dir = "... | null | ADMM_L1/validate.py | validate.py | py | 2,578 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "tensorflow.Session",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "tensorflow.global_variables_initializer",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "tensorflow.local_variables_initializer",
"line_number": 22,
"usage_type": "cal... |
410544278 | '''
This program helps troubleshooting netmiko by obtaining the logging file
from the router and displaying it.
http://ktbyers.github.io/netmiko/COMMON_ISSUES.html
'''
from netmiko import ConnectHandler
import time
import logging
logging.basicConfig(filename='test.log', level=logging.DEBUG)
logger = logging... | null | Netmiko/nemiko_troubleshooting.py | nemiko_troubleshooting.py | py | 944 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.basicConfig",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "netmiko.Conn... |
124375739 | #%%
import requests
import io
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
url = 'http://www.minethatdata.com/Kevin_Hillstrom_MineThatData_E-MailAnalytics_DataMiningChallenge_2008.03.20.csv'
res = requests.get(url).content
df: pd.DataFrame = p... | null | section1.py | section1.py | py | 1,948 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.get",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "pandas.read_csv",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "io.StringIO",
... |
419939251 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import division
import math
import numpy as np
import scipy as sp
import pandas
import matplotlib.pyplot as plt
from progressbar import ProgressBar
from scipy.sparse import csr_matrix
from scipy.sparse import linalg as sparse_linalg
import sys
file_dir = '/... | null | projects/FSA_various/approximate_su2_lie_algebra_pxp_fsa_pxxxp.py | approximate_su2_lie_algebra_pxp_fsa_pxxxp.py | py | 2,882 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path.append",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "sys.path.append",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_nu... |
464296159 | from multiprocessing import Process, Queue, current_process
import queue, time
# worker de traitement de tâches
def do_job(to_do, jobs_done):
# cuurent_process renvoie() dess information sur le processus courant
p_name = current_process().name
print(f"{p_name} waiting for queue to get elem")
while True... | null | process/queues.py | queues.py | py | 1,133 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "multiprocessing.current_process",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "queue.Empty",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "multiproce... |
168879428 | import torch
import math
import numpy as np
def load_data():
datanum=500
X = np.linspace(-2., 2., datanum)
y = np.ones(datanum)
for i in range(datanum):
if X[i]>0.:
#y[i] = 2.*np.sin(X[i] * (2 * math.pi)) *np.sin(X[i] * (2 * math.pi))
y[i] = 2.*X[i] + 1.
else:... | null | develop5/load_data.py | load_data.py | py | 1,491 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.linspace",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.ones",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.random.randn",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line... |
51858732 | from urllib.request import urlopen
from bs4 import BeautifulSoup
import pyexcel
from collections import OrderedDict
from youtube_dl import YoutubeDL
url = "https://www.apple.com/itunes/charts/songs/"
conn = urlopen(url)
html_content = conn.read()
soup = BeautifulSoup(html_content,"html.parser")
section = soup.find("s... | null | Session 1/Excercise1.py | Excercise1.py | py | 1,006 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "urllib.request.urlopen",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "collections.OrderedDict",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "youtu... |
26674952 | import os
import sys
import json
import numpy as np
import pandas as pd
from pathlib import Path
import tensorflow as tf
from solutions.ThirtyMusic import stabr_tf
from solutions.ThirtyMusic import data_handling_tf
def eval_mrr(network, test_data, k=10):
cumulative_rank = 0
total = 0
for step, data in enu... | null | solutions/ThirtyMusic/train_and_eval_tf.py | train_and_eval_tf.py | py | 9,788 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "tensorflow.nn.log_softmax",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "tensorflow.nn",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.nn.top_k",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "tens... |
337881138 | from selenium.webdriver.common.by import By
from Hogwarts_po1.po_work.base_page import BasePage
class ContactPage(BasePage):
def get_department_list(self):
# ele_list = self.driver.find_element(By.CSS_SELECTOR, '.jstree-ocl').click()
ele_list = self.driver.find_elements(By.CSS_SELECTOR, '.jstree-... | null | cekai/Hogwarts_po_selenium/po_work/getlist.py | getlist.py | py | 866 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "Hogwarts_po1.po_work.base_page.BasePage",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "selenium.webdriver.common.by.By.CSS_SELECTOR",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "selenium.webdriver.common.by.By",
"line_number": 9,
... |
341931566 | import numpy as np
import pandas as pd
from functools import reduce
from copy import deepcopy
import matplotlib.pyplot as plt
from sklearn import preprocessing
from sklearn.datasets import make_classification
import pickle
import os
from HelperFunc import project_dir
#==================================================... | null | DataFunc.py | DataFunc.py | py | 10,575 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "copy.deepcopy",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "functools.reduce",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.intersect1d",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "copy.deepcopy",... |
582129023 | import os
import numpy as np
import matplotlib.pyplot as plt
def sliding_mean(data_array, window=10):
# data_array = np.array(data_array)
new_list = []
for i in range(data_array.shape[0]):
indices = range(max(i - window + 1, 0),
min(i + window + 1, data_array.shape[... | null | plot.py | plot.py | py | 2,544 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.asarray",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 43,
"usage_type": "name"
},
{
"api_name": "matplotlib.p... |
130254112 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import imageio
import os
from components import DataManager as dm
def mov_mean(x, N):
r = np.convolve(x, np.ones((N,))/N)[(N-1):]
r[-1] = x[-1]
for i in range(0, int(np.ceil(N))):
r[-i] = x[-i]
return r
def RGB(R, G, B):
... | null | accuracy_error_curves.py | accuracy_error_curves.py | py | 3,923 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.convolve",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "numpy.ones",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "numpy.ceil",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.subplots",
"... |
35210802 | import time
import threading
import json
from jetracer.nvidia_racecar import NvidiaRacecar
import numpy as np
import sys
project_path = "/home/jetson/MyWorkspace/jetracer"
sys.path.append(project_path)
import utils.ipaddress as ip
import utils.power as pw
from utils.display import Oled
from sensor.distance import Di... | null | jetracer3/AI_Rover2.py | AI_Rover2.py | py | 5,775 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path.append",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "jetracer.nvidia_racecar.NvidiaRacecar",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "u... |
91955369 | from django_redis import get_redis_connection
from rest_framework import serializers
class ImageCodeCheckSerialize(serializers.Serializer):
image_code_id = serializers.UUIDField()
text = serializers.CharField(max_length=4, min_length=4)
def validate(self, attrs):
"""
1. 根据image_code_id从re... | null | meiduo_mall/meiduo_mall/apps/verifications/serializers.py | serializers.py | py | 1,538 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "rest_framework.serializers.Serializer",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.serializers",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "rest_framework.serializers.UUIDField",
"line_number": 6,
"usage_type"... |
110677483 | # Copyright 1999-2020 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | null | mars/learn/contrib/pytorch/tests/test_dataset.py | test_dataset.py | py | 2,620 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "mars.utils.lazy_import",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "unittest.TestCase",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "mars.session.new_session",
"line_number": 29,
"usage_type": "call"
},
{
"api_name":... |
329567235 | import sys
import skimage.io
import skimage.viewer
import skimage.draw
import numpy as np
from matplotlib import pyplot as plt
from PIL import Image
import imageio
import scipy.ndimage as ndimage
# open image and indicate petri dish
img_0 = Image.open('results_L3.jpg')
row = 1
col = 1
# making grayscale image and sav... | null | bacteria_A.py | bacteria_A.py | py | 1,534 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "PIL.Image.open",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "skimage.io.io.imread",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "skimage.io.io",
"li... |
613326021 | import json
import requests
from django.contrib.auth.decorators import login_required
from django.core import serializers
from django.http import JsonResponse
from django.shortcuts import get_object_or_404
from process.models import Steps, StepsForms
def index(request, sections_id):
forms_id = request.GET.get('i... | null | csidjango/process/controllers/forms.py | forms.py | py | 1,722 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "process.models.StepsForms.objects.filter",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "process.models.StepsForms.objects",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "process.models.StepsForms",
"line_number": 15,
"usage_typ... |
377071218 | import string
import random
from werkzeug.utils import secure_filename
from app.main import db
from app.main.model.picture import Picture
from .auth_helper import Auth
from ..utils.util import Util
def upload_new_picture(request):
resp = Auth.get_user_id_with_token(request)
file = request.files["file"]
... | null | app/main/service/picture_service.py | picture_service.py | py | 3,066 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "auth_helper.Auth.get_user_id_with_token",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "auth_helper.Auth",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "werkzeug.utils.secure_filename",
"line_number": 17,
"usage_type": "call"
},
... |
13543533 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import random
import itertools
SEMANTICS = {'base' : ['fire', 'ice', 'stone'],
'color' : ['','red', 'blue', 'green'],
'number' : ['', 'two', 'many']}
VOWELS = ['a', 'e', 'i', 'o', 'u']
CONSONANTS = ['p', 't', 'k', 'b', 'd', 'g', 's', 'z', 'm', 'n', 'l', 'h']
ORD... | null | morfala.py | morfala.py | py | 4,273 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "itertools.product",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 65,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 66,
"usage_type": "call"
},
{
"api_name": "random.choice",
"... |
514394553 | from sklearn import metrics
from s_dbw import S_Dbw
from sklearn import preprocessing
from sklearn.cluster import KMeans
import csv
import os
from sklearn.metrics import mean_squared_error
#from relative_criteria import Dunn_index, Davies_Bouldin, silhouette_index
import numpy
complexity2_path = os.path.join(os.getcwd... | null | artificial code/complexity2_dataset_gen.py | complexity2_dataset_gen.py | py | 7,685 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.join",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "os.getcwd",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.path.isdir",
"line_number"... |
566117357 | import numpy as np
import cv2
import random
#k=int(input("enter the dimension of kernal >>"))
k=3
p=k
q=k
filtr=[[1,1,1],[1,1,1],[1,1,1]]
filtr=np.array(filtr)/9
print(filtr)
img=cv2.imread('c:/users/girishhegde/dog.jpg')
cv2.imshow("img",img)
m,n,c=img.shape
for e in range(0,m,random.randint(5,20)):
for f in... | null | q13box.py | q13box.py | py | 1,044 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.array",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number":... |
532138812 | from __future__ import absolute_import, division, print_function
from librosa import load, feature
import os
import numpy as np
import pandas as pd
from scipy.io import savemat
def partition(data,parts=10,overlap=.3):
out= []
size = len(data)
window_size = int(np.floor(size/(1+(parts-1)*(1-overlap))))
... | null | featGen/FBANK/FBANK.py | FBANK.py | py | 2,599 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.floor",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.floor",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.asarray",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number... |
43616700 | import os
signals = None
try:
if not 'DJANGO_SETTINGS_MODULE' in os.environ:
from django.conf import settings
settings.configure()
from django.db.models import signals
SIGNAL_SUPPORT = True
except ImportError:
SIGNAL_SUPPORT = False
def exec_hook(hook_name, self, *args, **kwargs):
... | null | neomodel/signals.py | signals.py | py | 872 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.environ",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "django.conf.settings.configure",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.conf.settings",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "djan... |
491875602 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created by sundazhong on 2019/11/15 14:17.
"""
import pika
connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
channel = connection.channel()
# 创建一个名为"hello"的队列用来将消息投递进去 队列持久化
channel.queue_declare(queue='demo_queue', durable=True)
# 在RabbitMQ... | null | demo1/send.py | send.py | py | 893 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pika.BlockingConnection",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pika.ConnectionParameters",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pika.BasicProperties",
"line_number": 17,
"usage_type": "call"
}
] |
521981458 | from pyrandall.kafka import KafkaConn
from pyrandall.types import Assertion
from .common import Executor
class BrokerKafka(Executor):
def __init__(self, spec, *args, **kwargs):
super().__init__()
self.execution_mode = spec.execution_mode
self.spec = spec
def execute(self, reporter):
... | null | pyrandall/executors/broker_kafka.py | broker_kafka.py | py | 912 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "common.Executor",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "pyrandall.kafka.KafkaConn",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pyrandall.types.Assertion",
"line_number": 19,
"usage_type": "call"
}
] |
355076371 | import unittest
from mock import MagicMock
from clarity_ext.domain.artifact import Artifact
import os
from clarity_ext.service.file_service import UploadFileService
class TestUploadFileService(unittest.TestCase):
def test_run_driver_file_service(self):
artifact_service = MagicMock()
shared_files ... | null | test/unit/clarity_ext/service/test_file_service.py | test_file_service.py | py | 1,033 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "unittest.TestCase",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "mock.MagicMock",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "mock.MagicMock",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "mock.MagicMock",
... |
438514181 | # Skrypt odczytujacy dane z tematu kafki i zapisujący do bucketu AWS S3
# Skrypt wykorzystuje zewnętrzny plik parametrów o nazwie: airly_param.json w formacie:
#
# {
# "broker": "...",
# "api_key": "...",
# "url": "..."
# }
#
from os import environ
environ['PYSPARK_SUBMIT_ARGS'] = '--packages org.apa... | null | python/write_s3.py | write_s3.py | py | 4,212 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.environ",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "json.load",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "pyspark.sql.SparkSession.builder.appName",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "pyspark... |
106256812 | import mtcnn.mtcnn as mt
import time, cv2, os
# ========== Face Detection use MTCNN library ========== #
CV_STREAM = 'rtsp://root:xxxx@169.254.53.146/axis-media/media.amp?videocodec=H264&resolution=800x450'
CV_WINTTL = 'Face Detection by XIAOLI 201806'
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
os.environ["CUDA_V... | null | fd030.py | fd030.py | py | 2,217 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.environ",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "cv2.VideoCapture",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line... |
141068455 | # -*- coding: utf-8 -*-
"""View providing a listing of events
Suitable for folders or collections
Also includes a viewlet which will show the "featured_item" returned by
the method on the view.
"""
from DateTime import DateTime
from zope.component import queryUtility
from zope.interface import implements
from Produ... | null | src/isaw.theme/isaw/theme/browser/event_listing.py | event_listing.py | py | 2,400 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "isaw.theme.browser.tiled_view.TiledListingView",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "zope.interface.implements",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "isaw.theme.browser.interfaces.IEventListingView",
"line_number": 25,... |
295524187 | from flask import Flask, render_template, request, json, jsonify
import os
import json
import numpy as np
import io
from PIL import Image
import math
import base64
from watson_machine_learning_client import WatsonMachineLearningAPIClient
from wiotp.sdk.application import ApplicationClient
app = Flask(__name__)
app.c... | null | app.py | app.py | py | 4,880 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Flask",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "math.pi",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "wiotp.sdk.application.ApplicationC... |
529678465 | import aiml
import pandas as pd
from datetime import datetime
from datetime import timedelta
from nltk.corpus import wordnet as wn
import nltk
# Construct a database as a pandas dataframe
def init_data():
df = pd.read_csv('database_treinen.csv')
df.departure = df['departure'].apply(change_time)
df.arrival ... | null | chatbot.py | chatbot.py | py | 8,367 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.read_csv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 43,
"usage_type": "argument"
},
{
"api_name": "datetime.time... |
397915707 | '''
Created on 11.12.2017
@author: Anna-Liisa
'''
import argparse
import socket
import random
from scapy.layers.inet import IP, TCP, send, sr1
import sys
from logging import Logger
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('--shared-key', type=int)
parser... | null | Uebung5ALNew/sectubs/client.py | client.py | py | 2,252 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "socket.socket",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "socket.AF_INET",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "socket.SOCK... |
365582232 | #!/usr/bin/env python3
# -*- coding:utf-8 -*-
import os, errno, json
import jieba
def text2cws(jsonFilePath: str) -> list:
if os.path.isfile(jsonFilePath):
with open(jsonFilePath, encoding="utf-8") as f:
txt = f.read()
data = json.loads(txt)
try:
inputSTR = data["B... | null | week07/week07_Peter_40940112S.py | week07_Peter_40940112S.py | py | 1,452 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.isfile",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "json.loads",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "jieba.cut",
"line_number": 1... |
89028022 | from django.shortcuts import render
from rest_framework.views import APIView
from rest_framework.response import Response
from .models import Project, Pledge
from .serializers import ProjectSerializer, PledgeSerializer, ProjectDetailSerializer, PledgeDetailSerializer
from django.http import Http404
from rest_framework ... | null | crowdfunding/projects/views.py | views.py | py | 4,361 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "rest_framework.permissions.IsAuthenticatedOrReadOnly",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.permissions",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "permissions.IsOwnerOrReadOnly",
"line_number": 12,
"... |
644337823 | '''
This directory contains classes for connecting to and controlling
devices over a network.
'''
import os
import sys
import glob
import inspect
import pexpect
import termcolor
# insert tests lib so devices and tests can share the same libraries
sys.path.insert(0, os.path.dirname(__file__) + '/../tests')
b... | null | devices/__init__.py | __init__.py | py | 4,662 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path.insert",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_num... |
179309683 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging
import os
import re
import sys
from tqdm import tqdm
from urllib3 import HTTPResponse
from lab_api.swagger_client import LabFile
from lab_client.commons import text_utils, file_utils, request_u... | null | services/lab-workspace/docker-res/duplicated-resources/ml-lab-py/lab_client/handler/lab_file_handler.py | lab_file_handler.py | py | 22,086 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "re.compile",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "lab_client.commons.event_listener.Event",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "... |
288403357 | # -*- coding: utf-8 -*-
from django import forms
from django.core.mail import send_mail
from dosaaf_pogran.models import Course
from dosaaf_pogran.settings import EMAIL_HOST_USER
__author__ = 'egregors'
class ContactForm(forms.Form):
name = forms.CharField(label=u'Ваше имя:')
email = forms.EmailField(label=u... | null | dosaaf_pogran/forms.py | forms.py | py | 2,935 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.forms.Form",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "django.forms",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "django.forms.CharField",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "django.for... |
338995796 | import numpy as np
import sklearn
from sklearn.neighbors import NearestNeighbors
import bigfloat
from decimal import *
from pytictoc import TicToc
from numpy import linalg as LA
def build_shadow_M (X,tau,E,T):
'''Build the shadow manifold of the time series signal X, with E variables and sampling tau'''
shad... | null | methods.py | methods.py | py | 7,703 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.zeros",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": ... |
221515189 | import pandas as pd
import numpy as np
import altair as alt
import pickle
import streamlit as st
import altair as alt
from vega_datasets import data
import time
from xgboost import XGBRegressor
import xgboost as xgb
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
imp... | null | IdeaProjects/hemnet/sold_items/sold_items/display.py | display.py | py | 5,998 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pickle.load",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "pandas.read_pickle",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "pandas.to_datetime",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "pandas.to_numeric",... |
214488310 | from collections import Counter
from os import listdir
from os.path import isfile
import random
import csv
import datetime
import numpy as np
import tensorflow as tf
EVENTS_SENT_DIR = "../eventos_sent/"
PREPROCES_DIR = "../JavaPreprocesamiento/"
SAVE_DIR = "../store/"
PRED_DIR = SAVE_DIR + "pred/"
DIR = "../database... | null | src/sentPrediction.py | sentPrediction.py | py | 14,273 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.listdir",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "csv.reader",
"line_number": 60,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number":... |
267865215 | import pytest
from cx_const import ActionFunctionWithParams, TypeAction
from cx_core.action_type.predefined_action_type import _get_action
from tests.test_utils import fake_fn
@pytest.mark.parametrize(
"test_input, expected",
[
(fake_fn, (fake_fn, tuple())),
((fake_fn, tuple()), (fake_fn, tup... | null | tests/unit_tests/cx_core/action-types/predefined_action_type_test.py | predefined_action_type_test.py | py | 550 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "cx_const.TypeAction",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "cx_const.ActionFunctionWithParams",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "cx_core.action_type.predefined_action_type._get_action",
"line_number": 20,
"usage_... |
382680553 | import matplotlib.pyplot as plt
import numpy as np
data = {
"a": np.arange(50),
# Return random integers from low (inclusive) to high (exclusive).
#
"c": np.random.randint(0, 50, 50),
"d": np.random.randn(50)}
data["b"] = data['a'] + 10 * np.random.randn(50)
data['d'] = np.abs(data['d']) * 100
plt.... | null | matloptlib_test.py | matloptlib_test.py | py | 749 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.arange",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "numpy.random.randint",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "numpy.random.randn",... |
139164019 | # -*- coding: UTF-8 -*-
# @Time : 2018/4/28
# @File : queue_dataset.py
# @Author: Jian <jian@mltalker.com>
from __future__ import division
from __future__ import unicode_literals
from __future__ import print_function
from antgo.dataflow.dataset.dataset import Dataset
import os
import sys
import zmq
from antgo.utils.se... | null | antgo/dataflow/dataset/queue_dataset.py | queue_dataset.py | py | 2,586 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "antgo.dataflow.dataset.dataset.Dataset",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "zmq.Context",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "zmq.REP",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "os.ge... |
371451280 | # -*- coding: utf-8 -*-
"""
Created on Wed Oct 5 13:57:06 2016
@author: Alexandre
"""
import numpy as np
import scipy.optimize as opt
import time
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
import os
# Question 1
S = 3
nvec = np.array([1., 1., 0.2])
A = 1.
alpha = 0.35
delta = 0.... | null | Students/SollaciA/PS2/code/PSet2.py | PSet2.py | py | 8,246 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.array",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "numpy.append",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number":... |
490677101 | import spotipy
from collections import deque
import spotipy.util as util
import networkx as nx
from networkx.readwrite import json_graph
import re
import time
import json
def crear_grafo(token, g, spotify, artista_ini, max_artistas=10):
# Numero de Artistas a extraer
print('Analizando ', max_artis... | null | AccesoAPI.py | AccesoAPI.py | py | 6,055 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "time.time",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "collections.deque",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 64,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 65,
... |
37583367 | #! python3
# dataComplete.py - Completa um CSV de Startups com informações presentes em outro, sem substituí-las
# Uso: python dataComplete.py [csv mestre] [csv de enriquecimento] [Opcional: coluna-chave (padrão: "Site")]
# Exemplo: python dataComplete.py base.csv Startup
import sys, csv, re
from collections import Or... | null | dataComplete.py | dataComplete.py | py | 1,506 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "utils.ddmdata.readcsv",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "utils.ddmdata",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "sys.argv",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "utils.ddmdata.readc... |
450365150 | """
Debugging FAST fatigue calculations
"""
import sys
libpath = 'C:\\Users\\jrinker\\Documents\\GitHub\\dissertation'
if (libpath not in sys.path): sys.path.append(libpath)
import JR_Library.main as jr
import os
import numpy as np
import scipy.io as scio
# =========== inputs ===========
# path to turbine direc... | null | fast_analysis/WISDEM_rainflow/process_stats/proc-fatigue_calcs.py | proc-fatigue_calcs.py | py | 3,030 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "sys.path.append",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number":... |
416902496 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
__author__ = 'RemiZOffAlex'
__copyright__ = '(c) RemiZOffAlex'
__license__ = 'MIT'
__email__ = 'remizoffalex@mail.ru'
import sys
from myapp import app
from flask import Flask, render_template, request, escape, redirect, jsonify
@app.route('/', methods=['GET'])
def inde... | null | Flask-CGI/myapp/views.py | views.py | py | 1,320 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.render_template",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "myapp.app.route",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "myapp.app",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "flask.render_template... |
594913812 | # coding=utf-8
# @Author : bamtercelboo
# @Datetime : 2018/07/10 16.03
# @File : train.py
# @Last Modify Time : 2018/07/10 16.03
# @Contact : bamtercelboo@{gmail.com, 163.com}
"""
FILE : Instance.py
FUNCTION : Data Instance
"""
import torch
import random
from DataUtils.Common import *
torch.manual_seed(seed... | null | Dataloader/Instance_Base.py | Instance_Base.py | py | 576 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "torch.manual_seed",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "random.seed",
"line_number": 18,
"usage_type": "call"
}
] |
182314709 | from functools import wraps
import logging
logger = logging.getLogger('fam')
logger.setLevel(logging.DEBUG)
LOG_FUNCTION_ARGS = True
LOG_FUNCTION_RESULT = True
def log_call(name=None):
name = f'{name}:: ' if name else ''
def decorator(f):
@wraps(f)
def wrapper(*args, **kwargs):
... | null | chalicelib/fam/common/logger.py | logger.py | py | 659 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.getLogger",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "functools.wraps",
"line_number": 16,
"usage_type": "call"
}
] |
503309732 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
""" stdinfile.py
Reads stdin, writes to a temp file, and prints the temp file name.
For use with bash's process substitution:
pygments -l python -f html -O full stdinfile.py | google-chrome "$(stdinfile)"
-Christopher Welborn 07-11-2015
"""
import os
import... | null | stdinfile.py | stdinfile.py | py | 3,589 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.split",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_numbe... |
538401547 | from django.urls import path
from . import views
app_name = "main"
urlpatterns = [
path('', views.IndexView.as_view(), name='home'),
path('to_do/', views.add_todo, name='add_todo'),
path('<int:todo_id>/delete', views.delete_todo, name="delete")
] | null | main/urls.py | urls.py | py | 260 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.urls.path",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 9,
"usage_type": "call"
}
] |
607198851 | import imghdr
import numpy as np
from PIL import Image
def preprocess_image(img_path, model_image_size):
"""
:param img_path:
:param model_image_size:
:return:
"""
image_type = imghdr.what(img_path)
image = Image.open(img_path)
resized_image = image.resize(tuple(reversed(model_image_... | null | CD_Cars/preprocess_image.py | preprocess_image.py | py | 524 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "imghdr.what",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "PIL.Image.open",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "PIL.Image.BICUBIC",
"line_nu... |
24987216 | from django.db import models
from datetime import datetime
from django.contrib.auth.models import User
from phonenumber_field.modelfields import PhoneNumberField
# Create your models here.
class Clients(models.Model):
First_Name = models.CharField(max_length=50)
Last_Name = models.CharField(max_length=50)
... | null | django/API/CRM_APP/models.py | models.py | py | 894 | python | en | code | null | code-starcoder2 | 76 | [
{
"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": "... |
607439231 | # -*- coding: utf-8 -*-
# @Author : Albert Lau
# @Email : 571079699@qq.com
# @Time : 2019/8/28 17:09
# @File : RF_model.py
import time
import pickle
import pandas as pd
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split, GridSearchCV
fr... | null | lesson-06/RF_model.py | RF_model.py | py | 1,789 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pickle.load",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "sklearn.decomposition.PCA",
... |
582849560 | """The count-and-say sequence is the sequence of integers with the first five terms as following:
1. 1
2. 11
3. 21
4. 1211
5. 111221
1 is read off as "one 1" or 11.
11 is read off as "two 1s" or 21.
21 is read off as "one 2, then one 1" or 1211.
Given an integer n where 1 ≤ n ≤ 30, generate the nt... | null | python/leetcode_questions/count_and_say_usingGroupBy.py | count_and_say_usingGroupBy.py | py | 1,161 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "itertools.groupby",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "{'groupby': 'itertools.groupby'}",
"line_number": 50,
"usage_type": "call"
}
] |
298188686 | """File table
Revision ID: 0389adc26cce
Revises: 208c09863ab4
Create Date: 2018-11-10 22:15:06.516132
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '0389adc26cce'
down_revision = '208c09863ab4'
branch_labels = None
depends_on = None
def upgrade():
# ###... | null | migrations/versions/0389adc26cce_file_table.py | 0389adc26cce_file_table.py | py | 738 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "alembic.op.create_table",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "alembic.op",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "sqlalchemy.Column",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.Integ... |
521796897 | from gen import utils
import torch
from torch import nn, Tensor
import torch.nn.functional as F
class VAE(nn.Module):
"""Variational Auto Encoder
Largely based on https://github.com/AntixK/PyTorch-VAE/blob/master/models/vanilla_vae.py
with some random alterations for the layers.
"""
def __init__... | null | gen/vae.py | vae.py | py | 3,055 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "torch.nn.Module",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "gen.utils.logger.info",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "gen.utils.logger",
... |
343382223 | #!/usr/bin/python3
import time
import logging
import argparse
from deviceListener import DeviceListenerThread, DeviceThread
from localListener import LocalCommListener
def getArgs():
p = argparse.ArgumentParser()
p.add_argument("-r", action='store_true')
p.add_argument("-p", type=int, default=8888)
... | null | bnx/embd/main.py | main.py | py | 660 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "logging.basicConfig",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "loggin... |
424643975 |
from celery import Celery,chain
from app import app,celery,db
import redisearch
import time,sys
import pandas as pd
import billiard as mp #multiprocessing substitute to enable daemon
import scipy.stats
import numpy as np
import os
sys.path.insert(0, 'app')
import controller.utils as utils
from timeit import defaul... | null | website/app/controller/celerytask_redis_old.py | celerytask_redis_old.py | py | 15,390 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path.insert",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "time.time",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "os.path.splitext",
"line_... |
256964083 | import matplotlib.pyplot as plt
import numpy as np
overs = np.arange(11)
indrun = np.array([0, 5, 13, 20, 30, 38, 50, 63, 72, 86, 102])
ausrun = np.array([0, 10, 23, 30, 40, 58, 60, 63, 68, 74, 80])
fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) # this is standard location of plotting
# define locati... | null | ML Day 13/matplotlib2.py | matplotlib2.py | py | 637 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.arange",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"lin... |
626933656 | """
TCRpiper - a pipeline for TCR sequence treatment. Copyright (C) 2020 D. Malko
"""
from django.contrib import admin
from django.urls import include, path, re_path
from django.conf import settings
from django.conf.urls.static import static
urlpatterns = [
path('admin/', admin.site.urls),
path(r'', include(... | null | backend/backend/urls.py | urls.py | py | 930 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.urls.path",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "django.contrib.admin.site",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "... |
277255207 | # -*- coding:utf-8 -*-
'''
Created on 2018年12月14日
解析blk.dat文件
@author: user
'''
import os, sys, datetime, time
import logging, json
from logging.handlers import RotatingFileHandler
# from importlib import reload
from blockchain_parser.blockchain import Blockchain, get_files, get_blocks
from blockchain_parser.block impo... | null | src/com/scott/dev/demo/btc/parseblock_to_file.py | parseblock_to_file.py | py | 4,154 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.setdefaultencoding",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.sep",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
... |
294852448 | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
"""Factory method for easily getting imdbs by name."""
__sets = {}
im... | null | faster_rcnn/datasets/factory.py | factory.py | py | 4,678 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "datasets.pascal_voc.pascal_voc",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "datasets.pascal_voc",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "datasets.pascal_voc.dental",
"line_number": 29,
"usage_type": "call"
},
{
"api... |
638570919 | from tests.factories import (
ApplicationFactory,
PortfolioFactory,
TaskOrderFactory,
CLINFactory,
random_future_date,
random_past_date,
)
import datetime
def test_portfolio_applications_excludes_deleted():
portfolio = PortfolioFactory.create()
app = ApplicationFactory.create(portfolio... | null | tests/models/test_portfolio.py | test_portfolio.py | py | 2,490 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "tests.factories.PortfolioFactory.create",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "tests.factories.PortfolioFactory",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "tests.factories.ApplicationFactory.create",
"line_number": 14,
"... |
560389158 | '''
Created on 8 Ara 2020
@author: user
'''
from PyQt5.QtWidgets import QGroupBox, QGridLayout, QTableView, QFrame,\
QVBoxLayout, QSplitter, QHBoxLayout, QLabel, QLineEdit, QAction,\
QAbstractItemView
from Cest_Factory.Cest_Factory_classes import barisTableViewModel
from Cest_Factory.Ekle_Cikar_UI imp... | null | CEST Factory/Cest_Factory/Stok_SağFrame.py | Stok_SağFrame.py | py | 8,613 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "PyQt5.QtWidgets.QTableView",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets.QAbstractItemView.SelectRows",
"line_number": 31,
"usage_type": "attribute"
},
{
"api_name": "PyQt5.QtWidgets.QAbstractItemView",
"line_number": 31,
"usag... |
419411979 | from setuptools import setup, find_packages
from os.path import join, dirname
with open('requirements.txt', 'r') as file:
requirements = [x.strip() for x in file.readlines()]
setup(name='textaugH',
version='0.2.6',
description='Little package for text augmentation',
author_email='comptechaugteam... | null | pypi_install_script/textaugH-0.2.6.tar/setup.py | setup.py | py | 564 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "setuptools.setup",
"line_number": 7,
"usage_type": "call"
}
] |
68546774 | '''
Created on Jan 17, 2012
@author: spengler
'''
from models import Usuario
from models import Projetos
from models import Tipo_de_Habilidade
from models import Habilidades
from models ... | null | PyProject_FreelaTI/src/PyProject_FreelaTI/cadastro/tests.py | tests.py | py | 13,378 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.test.TestCase",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "controle.Controle",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "projeto.controle.Controle",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "mode... |
496425808 | #!/usr/bin/env python
# coding: utf-8
# Import library used in this script
# In[ ]:
get_ipython().system(u'pip install --user geopandas==0.3.0')
get_ipython().system(u'pip install --user pyshp==1.2.10')
get_ipython().system(u'pip install --user shapely==1.6.3')
get_ipython().system(u'pip install --user plotly')
get... | null | Nutrition.py | Nutrition.py | py | 3,929 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.read_csv",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 92,
"usage_type": "call"
},
{
"api_name": "plotly.figure_factory.create_choropleth",
"line_number": 139,
"usage_type": "call"
},
{
"api_name... |
496755819 | import cv2
import numpy as np
cap = cv2.VideoCapture(0)
panel = np.zeros([100, 700], np.uint8)
cv2.namedWindow("panel")
def nothing(x):
pass
cv2.createTrackbar("L - h", "panel", 0, 179, nothing)
cv2.createTrackbar("U - h", "panel", 179, 179, nothing)
cv2.createTrackbar("L - s", "panel", 0, 255, nothing)
cv2.... | null | main-video.py | main-video.py | py | 1,340 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "numpy.uint8",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "cv2.namedWindow",
"lin... |
434622952 | # C-python 3.6.2, Windows.
import requests
import sys
def main(argv):
input_value = str(argv)
url = 'http://services.groupkt.com/state/get/USA/all'
found = 'false' # flag to track search success.
# Determine key from user input.
if input_value.__len__() > 2:
my_key = 'name'
else:
... | null | stateScript.py | stateScript.py | py | 1,850 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.Session",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "sys.argv.__len__",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 49,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_... |
151578409 | # import pdb
import src.question as question
import src.db as db
from time import time, ctime
from re import sub, findall, match, IGNORECASE
from os import path, environ
from contextlib import suppress
from unidecode import unidecode
from json import decoder
import difflib
import editdistance
# initialize dictionary
e... | null | src/host.py | host.py | py | 26,145 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.isfile",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "time.ctime",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 50,
... |
61421957 | import pickle
from galpy import potential
from galpy.df import dehnendf, evolveddiskdf
from astropy import units as u
import warnings
warnings.filterwarnings('ignore')
def pickle_data(filename, data):
output = open(filename, 'wb')
pickle.dump(data, output)
output.close()
tform = -10 * u.Gyr
lp = potentia... | null | cold_axi.py | cold_axi.py | py | 1,425 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pickle.dump",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "astropy.units.Gyr",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "astropy.uni... |
361932175 | from nltk.tokenize import sent_tokenize, regexp_tokenize
import re
from nltk.corpus import stopwords
def openAndRead(infilePathAndName):
"""
opens a file and returns a long long long string
Parameters
----------
infilePathAndName : str
`infilePathAndName` is the string containing the ... | null | preFunctions.py | preFunctions.py | py | 4,198 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "nltk.tokenize.sent_tokenize",
"line_number": 59,
"usage_type": "call"
},
{
"api_name": "nltk.tokenize.regexp_tokenize",
"line_number": 84,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords.words",
"line_number": 95,
"usage_type": "call"
},
{
... |
443046912 | #!/usr/bin/env python
# coding: utf-8
# In[3]:
from nltk.tree import *
from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer
from nltk.corpus import wordnet
import nltk
from nltk.tokenize import RegexpTokenizer
from pattern.en import conjugate, PRESENT
import speech_recognition as sr
from vosk ... | null | ISL benepar.py | ISL benepar.py | py | 26,053 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "spacy.load",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "benepar.spacy_plugin.BeneparComponent",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "speech_recognition.Recognizer",
"line_number": 317,
"usage_type": "call"
},
{
"a... |
265706030 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.preprocessing import LabelEncoder
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import RandomForestClassifier
from sklearn.tree import DecisionTreeClassifier, export_graphviz
from sklearn import metrics
from ... | null | myproject/web/ML/project.py | project.py | py | 4,334 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.read_csv",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "pandas.Series",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "pandas.Series",
"l... |
155980583 | #!/usr/bin/env python
"""
Module for organizing SPH, STM files from a corpus
"""
import glob
import os
from concurrent.futures import ThreadPoolExecutor
from functools import partial
from tqdm import tqdm
from asrtoolkit.data_structures.audio_file import audio_file
from asrtoolkit.data_structures.time_aligned_text i... | null | asrtoolkit/data_structures/corpus.py | corpus.py | py | 8,415 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.exists",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "glob.glob",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "asrtoolkit.data_structures.audi... |
358171146 | import chess
import chess.pgn
import chess.engine
import pandas as pd
from datetime import date
from dateutil.relativedelta import relativedelta
import requests
import json
import io
pd.set_option('display.max_rows', 15)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)
pd.set_option('displ... | null | read_pgn.py | read_pgn.py | py | 6,317 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.set_option",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pandas.set_option",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pandas.set_option",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pandas.set_opti... |
330787906 | from Morpheme import Morpheme
from collections import defaultdict
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
def main():
file_name = 'materials/neko.txt.mecab'
morph = Morpheme(mecab_file_name=file_name)
result = morph.read_mecab_file() # 辞書のリスト
count_dict = de... | null | knock39.py | knock39.py | py | 1,587 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "Morpheme.Morpheme",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "collections.defaultdict",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matplotlib.font_manager.FontProperties",
"line_number": 18,
"usage_type": "call"
},
{
"a... |
422067105 | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 15 20:04:12 2020
@author: tomvc
"""
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
import dash_bootstrap_components as dbc
import datetime as dt
import pandas as pd
import dash_... | null | app.py | app.py | py | 15,781 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "dash.Dash",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "dash_bootstrap_components.themes",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name"... |
229905359 | # -*- coding: utf-8 -*-
import cv2
import numpy as np
import cv2.cv as cv
import serial
import time
from time import sleep
seadmed = []
def saaseadmed(): # saab id´d ainult siis kui aku toide on peal!!!!!
global parem, vasak, coil
## parem = serial.Serial('/dev/ttyACM2')
## vasak = serial.Serial('/dev/ttyA... | null | hunt2.py | hunt2.py | py | 6,091 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "serial.Serial",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "serial.PARITY_NONE",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "serial.SerialException",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "tim... |
557392389 | # coding=utf-8
from django.contrib.gis import admin
from ordered_model.admin import OrderedModelAdmin
from django import forms
from bims.models import (
LocationType,
LocationSite,
IUCNStatus,
Taxon,
Survey,
LocationContext,
Boundary,
BoundaryType,
Cluster,
CarouselHeader
)
cl... | null | bims/admin.py | admin.py | py | 1,685 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.forms.ModelForm",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "django.forms",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "django.contrib.gis.admin.GeoModelAdmin",
"line_number": 28,
"usage_type": "attribute"
},
{
... |
106137292 | from django.shortcuts import render
from .securetube import fetch, watch, fetch_meta
from feed.models import Channels
def index(request):
#request.session['proxy'] = anonymous()
return render(request, 'securetube/index.html')
def results(request):
if request.method == 'POST':
query = request.... | null | securetube/views.py | views.py | py | 1,204 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.shortcuts.render",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "securetube.fetch",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "feed.models.Channels",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "feed.mod... |
186845500 | import os
import pickle
import errno
from requests import Session
from .config import CONFIG_DIR
SESSIONS_DIR = os.path.join(CONFIG_DIR, 'sessions')
def get_response(name, request_kwargs):
session = load(name)
session_kwargs, request_kwargs = split_kwargs(request_kwargs)
headers = session_kwargs.pop('h... | null | httpie/sessions.py | sessions.py | py | 1,503 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.join",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "config.CONFIG_DIR",
"line_number": 9,
"usage_type": "argument"
},
{
"api_name": "os.path",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "os.makedirs",
"line_... |
23597542 | #!/usr/bin/env python3
from common import *
import matplotlib.pyplot as plt
import numpy as np
import random
from tqdm import tqdm
def get_func(A, b, c):
A = np.array(A)
b = np.array(b)
def f(*x):
return 1/2 * A.dot(x).dot(x) + b.dot(x) + c
return f
METHODS = [
Method.STEEPEST_DESCENT,
... | null | scripts/lab2/main.py | main.py | py | 4,916 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.array",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.arrow",
"line_number": 71,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
... |
245044351 | import os
from setuptools import setup, find_packages
with open(os.path.join(os.path.dirname(__file__), 'requirements.txt')) as fh:
requires = fh.read().splitlines()
setup(
name='pywarehouse',
install_requires=requires,
version="0.0.8",
description="",
author="Kieran Bacon",
author_email=... | null | setup.py | setup.py | py | 768 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.join",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "setuptools.setup",
"line_n... |
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