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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
407659418 | import copy
import random
import torch
from .base_model import BaseModel
from .utils import (
get_G_heap,
G_Net,
combine_mapping_networks,
categorize_mappings,
coshuffle,
)
from .optimizers import get_optimizer
from models.networks import networks
from models.networks.loss import GANLoss, cal_grad... | null | models/gagan_model.py | gagan_model.py | py | 10,159 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "base_model.BaseModel",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "base_model.BaseModel.__init__",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "base_model.BaseModel",
"line_number": 46,
"usage_type": "name"
},
{
"api_name"... |
190917490 | import numpy as np
from importlib import import_module, reload
from zfit_constants import *
from lmfit import minimize, Parameters
from scipy.stats import gmean # geometric mean
import csv
class CliInterface():
def __init__(self):
self.checkBoxLogMag
class DoModel:
"""
Encapsulate all ... | null | pyZfit/zfit_modelcore.py | zfit_modelcore.py | py | 16,304 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.log10",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "numpy.log10",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "numpy.hstack",
"line_number": 68,
"usage_type": "call"
},
{
"api_name": "numpy.power",
"line_number":... |
93733382 | import datetime
import json
from django.db.models import Q
from django.views.generic import View
# Create your views here.
from IHome.utils.response_code import RET
from IHome.utils.views import LoginRequiredJSONMixin
from django import http
import logging
from house.models import House
from order.models import Order... | null | apps/order/views.py | views.py | py | 8,441 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "IHome.utils.views.LoginRequiredJSONMixin",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "django.views.generic.View",
"line_number": 18,
"usage_type": "name"
},
{
... |
362079957 | '''
@Description:
@Version: 1.0.0
@Author: louishsu
@E-mail: is.louishsu@foxmail.com
@Date: 2019-08-09 17:11:31
@LastEditTime: 2019-08-12 10:26:07
@Update:
'''
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import offsetbox
from utils import eig
def plot_embedding(X, y, images, title=None, t=6e-... | null | Algorithms/neighborhood_preserving_embedding.py | neighborhood_preserving_embedding.py | py | 5,187 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.min",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "numpy.max",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
... |
279139142 | import numpy as np
import os
from .base import Base
from .trace import Trace
from .dispersion import Dispersion
from .sensitivity import Sensitivity
from ..utils import h5Attr
class Beam(Base):
__INT__=np.uint64
def __init__(self,h5,clip,xr=[-np.inf,np.inf],yr=[-np.inf,np.inf]):
Base.__init__(se... | null | h5axeconfig/grism/beam.py | beam.py | py | 3,452 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "base.Base",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "numpy.uint64",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "numpy.inf",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "base.Base.__init__",
"... |
315655171 | from selenium import webdriver
from bs4 import BeautifulSoup
import os
chromedriver = "C:\Program Files (x86)\Google\Chrome\Application\chromedriver.exe"
os.environ["webdriver.chrome.driver"] = chromedriver
browser = webdriver.Chrome(chromedriver)
#设置浏览器打开url
url = "http://www.baidu.com"
browser.get(url)
#在百度搜索框输入关键字... | null | info.py | info.py | py | 525 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.environ",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "selenium.webdriver.Chrome",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 7,
"usage_type": "name"
}
] |
136835603 | from selenium import webdriver
import math
import time
import os
try:
start_time = time.time()
link = "http://suninjuly.github.io/redirect_accept.html"
browser = webdriver.Chrome()
browser.get(link)
def calc(x):
return str(math.log(abs(12*math.sin(int(x)))))
button = browser.find_element_by_xpath("//button")... | null | part_2/2.3.6.py | 2.3.6.py | py | 1,557 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "time.time",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver.Chrome",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "math.log",
"l... |
552418177 | import torch.nn as nn
import torch.nn.functional as F
from base import BaseModel
import resnest.torch as resnest_torch
# from https://www.kaggle.com/kneroma/clean-fast-simple-bird-identifier-training-colab
class PretrainedModel():
def __init__(self, num_classes=397, name="resnest"):
"""
Loads a pre... | null | model/model.py | model.py | py | 5,130 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "resnest.torch",
"line_number": 23,
"usage_type": "argument"
},
{
"api_name": "torch.nn.hub.load",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "torch.nn.hub",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
... |
313382624 | from django.http import HttpResponse, HttpResponseRedirect
from django.shortcuts import get_object_or_404,render,redirect
from django.http import HttpResponse, Http404
from django.urls import reverse
from django.contrib.auth.forms import UserCreationForm
from django.contrib.auth import login,logout
from .models import ... | null | polls/views.py | views.py | py | 3,399 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "models.Question.objects.filter",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "models.Question.objects",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "models.Question",
"line_number": 15,
"usage_type": "name"
},
{
"api_n... |
431660562 | import os
import time
import argparse
import torch
import pandas as pd
from sgm_train import train_document, train_image, train_tabular
from utils import count_run_time
class parameter(object):
def __init__(self):
parser = argparse.ArgumentParser()
# train parameter
parser.add_argument('-... | null | sgm_main.py | sgm_main.py | py | 9,012 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "torch.device",
"line_number": 72,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 72,
"usage_type": "call"
},
{
"api_name": "torch.cu... |
193780406 | """Component to manage the AIS Cloud."""
import asyncio
import logging
import requests
import json
import os
from homeassistant.ais_dom import ais_global
from homeassistant.const import EVENT_PLATFORM_DISCOVERED, EVENT_STATE_CHANGED
from homeassistant.helpers.discovery import async_load_platform
from homeassistant.cons... | null | homeassistant/components/ais_cloud/__init__.py | __init__.py | py | 50,147 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "requests.head",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "homeassistant.ais_dom.ais_global.get_my_global_ip",
"line_number": 55,
"usage_type": "call"
},
{
... |
605923304 | import os
import sys
import glob
import cv2
def save_face(frame, p1, p2, filename):
# Get center point coordinates
cp = ((p1[0] + p2[0])//2, (p1[1] + p2[1])//2)
# Find the y-midpoint
y_midp = int(((p2[1] - p1[1]) // 2) * 1.25)
# Cropping a square around the face
# - from the cp xy points, ... | null | face_capture.py | face_capture.py | py | 2,526 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "cv2.resize",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "cv2.INTER_CUBIC",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "cv2.imwrite",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "cv2.VideoCapture",
"l... |
348184475 | # ##### BEGIN GPL LICENSE BLOCK #####
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distrib... | null | Tools/Exporters/Blender/2.63+/h3d_render/export_h3d_scene.py | export_h3d_scene.py | py | 32,229 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "bpy.types",
"line_number": 39,
"usage_type": "attribute"
},
{
"api_name": "bpy.data",
"line_number": 68,
"usage_type": "attribute"
},
{
"api_name": "bpy.context",
"line_number": 70,
"usage_type": "attribute"
},
{
"api_name": "bpy.ops.object.select_a... |
628914625 | """Compute depth maps for images in the input folder.
"""
import os
import glob
import torch
import utils
import cv2
from torchvision.transforms import Compose
from models.midas_net import MidasNet
from models.transforms import Resize, NormalizeImage, PrepareForNet
from torch.utils import tensorboard
def run(input_... | null | run.py | run.py | py | 3,816 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.device",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "models.midas_net.MidasNet",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "torchvision.transforms.Compose",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": ... |
405855000 | import os
import re
import textwrap
import sys
import argparse
timestamps = []
user = []
info = []
#Danmu position Y axis
y_axis_list = [790,753,716,679,642]
#ass字幕文件头及样式
Def_info = textwrap.dedent('''
[Script Info]
Title: Default ASS file
ScriptType: v4.00+
WrapStyle: 2
Collisions: Normal
PlayRes... | null | PtoA.py | PtoA.py | py | 2,628 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "textwrap.dedent",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "re.split",
"line_number": 48,
"usage_type": "call"
}
] |
407831204 | import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image, ImageFilter
from pytesseract import image_to_string
# requires:
# pip install seaborn pytesseract
# brew install tesseract
def ocr(image, blur=5):
image = add_white_border(image)
im = render_image(image)
im.show()
im = im.fil... | null | shared/ocr.py | ocr.py | py | 874 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "PIL.ImageFilter.GaussianBlur",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "PIL.ImageFilter",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "pytesseract.image_to_string",
"line_number": 16,
"usage_type": "call"
},
{
"api_name... |
26411966 | import streamlit as st
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
st.write("""**1. Select Age :**""")
age = st.slider('', 0, 100, 25)
st.write("""**You selected this option **""",age)
st.write("""**2. Select Gender :**""")
sex = st.selectbox("(1=Male, 0=Female)",["1","0"])
st.write(""... | null | Model-1/bug-fix.py | bug-fix.py | py | 898 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "streamlit.write",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "streamlit.slider",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "streamlit.write",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "streamlit.write",
"... |
136910062 | import re
import requests
import time,random
cookies = {
'_ntes_nnid': 'c0a9486ed4e5d91c72812668fe88891c,1587290454965',
'_ntes_nuid': 'c0a9486ed4e5d91c72812668fe88891c',
'Device-Id': 'TMjvh9JnECyAvbziFjqs',
'_ga': 'GA1.2.1244979980.1587298259',
'_gid': 'GA1.2.1284201187.1587950146',
'P_INFO': ... | null | buff2.py | buff2.py | py | 2,482 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "requests.get",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "re.findall",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "random.random",
"line_number":... |
479436492 | #coding = utf-8
__author__ = 'Aimee'
from interface.public import Config
from interface.public import HttpService
#对请求方式参数化
def get_host(EndPoint):
host = Config.url()
endpoint = EndPoint
url = ''.join([host,endpoint])
return url
#再次封装类中的函数
def get_response(url,Method,**DataALL):
i... | null | 第一期/广州-Aimee/interface/interface/public/base.py | base.py | py | 536 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "interface.public.Config.url",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "interface.public.Config",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "interface.public.HttpService.MyHTTP",
"line_number": 17,
"usage_type": "call"
},
{
... |
283794158 | # Task 2
# Press the 'Run File' menu button to execute
import sqlite3 as db #import the module
con = db.connect('test.db') #connect to a local file test.db
with con: #with is used to avoid typing con.cur all the time
cur = con.cursor() #”with con” opens a level of indentation
#delete a table for sales pe... | null | 03-updates/task-2.py | task-2.py | py | 1,169 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sqlite3.connect",
"line_number": 5,
"usage_type": "call"
}
] |
148765803 | import numpy as np
import matplotlib.pyplot as plt
from scipy import signal
num = np.poly1d([1,0])
den = np.poly1d([1,3,2,1])
sys = signal.TransferFunction(num,den)
t,y = signal.impulse(sys)
plt.plot(t,y)
plt.xlabel('$t$')
plt.ylabel('$y$')
plt.grid() # minor
plt.axis()
plt.show()
| null | impulse_response_a1.py | impulse_response_a1.py | py | 283 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.poly1d",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "numpy.poly1d",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "scipy.signal.TransferFunction",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "scipy.signal",
... |
539983796 | import requests
from bs4 import BeautifulSoup
import json
class Listing:
def __init__(self, url):
print("Parsing " + url)
page = requests.get(url)
soup = BeautifulSoup(page.content, 'html.parser')
data = json.loads(soup.find('script', type='application/json').string)
self.pageProps = data["props"... | null | temporary-map-visualization-fix/listing.py | listing.py | py | 1,718 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "requests.get",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 10,
"usage_type": "call"
}
] |
447754369 | import layoutparser as lp
import cv2,os
import numpy as np
from collections import namedtuple
Rectangle = namedtuple('Rectangle', 'xmin ymin xmax ymax')
import sys, random, torch, glob, torchvision
# from torchvision.models.detection.faster_rcnn import FastRCNNPredictor
# from torchvision.models.detection.mask_rcnn im... | null | anuvaad-etl/anuvaad-extractor/block-merger/src/utilities/primalaynet/infer.py | infer.py | py | 10,630 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "collections.namedtuple",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "random.seed",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "torch.manual_seed",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "torch.cuda.manual... |
176537285 | get_ipython().run_line_magic('load_ext', 'autoreload')
get_ipython().run_line_magic('autoreload', '2')
import matplotlib.pyplot as plt
import numpy as np
import pyvista as pv
from matplotlib.colors import Normalize
from matplotlib.cm import magma
from cloud_colocations.plots import grid_to_edges
try:
plt.style.use(... | null | notebooks/plot_3d.py | plot_3d.py | py | 3,876 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "matplotlib.pyplot.style.use",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.style",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 10,
"usage_type": "name"
},
{
"api_na... |
503122610 | # coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft and contributors. All rights reserved.
#
# 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 ... | null | azure-mgmt-compute/azure/mgmt/compute/models/virtual_machine.py | virtual_machine.py | py | 5,682 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "resource.Resource",
"line_number": 25,
"usage_type": "name"
}
] |
374096073 | """
Copyright ©2019. The Regents of the University of California (Regents). All Rights Reserved.
Permission to use, copy, modify, and distribute this software and its documentation
for educational, research, and not-for-profit purposes, without fee and without a
signed licensing agreement, is hereby granted, provided ... | null | tests/test_api/test_cohort_controller.py | test_cohort_controller.py | py | 49,600 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pytest.fixture",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "pytest.fixture",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "pytest.fixture",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "tests.test_api.api_test_... |
244793223 | import time
import argparse
from dask.distributed import Client
import dask.array as da
import dask.dataframe as dd
class Experiment(object):
def __init__(self, ip, nodesize, outfile):
self.schedluer_ip = ip
self.node_count = nodesize
self.outfile = outfile
self.client = Client(sel... | null | code/experiment.py | experiment.py | py | 1,682 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "dask.distributed.Client",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "dask.array.random.normal",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "dask.array.random",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name"... |
252889865 | from django.urls import path
from . import views
from rest_framework.authtoken.views import obtain_auth_token
urlpatterns = [
path(
'mascotas/<int:id>',
views.get_delete_update_mascota,
name='get_delete_update_mascota'
),
path(
'mascotas/',
views.get_post_mascotas,... | null | api/urls.py | urls.py | py | 1,908 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.urls.path",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
... |
485660903 | #!/usr/bin/python
import pickle
import sys
import matplotlib.pyplot
sys.path.append("../tools/")
from feature_format import featureFormat, targetFeatureSplit
from operator import itemgetter
### read in data dictionary, convert to numpy array
data_dict = pickle.load( open("../final_project/final_project_dataset.pkl",... | null | outliers/enron_outliers.py | enron_outliers.py | py | 906 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.path.append",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "pickle.load",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "feature_format.featureFormat"... |
205111357 |
import pygame
from random import randint #bedzie potrzebne do nadania losowej predkosci poczatkowej dla pilki
BLACK = (0,0,0)
class Ball(pygame.sprite.Sprite): #tworzymy klase pileczka
#sluzy do tworzenia pileczek
def __init__(self, color, width, height):
super().__init__() #odwolujemy sie do ... | null | ball.py | ball.py | py | 1,658 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pygame.sprite",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "pygame.Surface",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pygame.draw.rect",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pygame.draw",
"... |
468149744 | # -*- coding: utf-8 -*-
"""
Created on Mon Feb 20 20:08:58 2017
@author: anurag
"""
# import all libraries
import quandl
import pandas as pd
import numpy as np
from bs4 import BeautifulSoup as beautifulsoup
from sklearn.decomposition import PCA
from matplotlib import pyplot as plt
from sklearn.svm import OneClassSVM
... | null | regression.py | regression.py | py | 1,035 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.DataFrame",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "quandl.get",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "sklearn.decomposition.PCA",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "numpy.linalg.no... |
88393927 | from flask import request, Flask,jsonify
from fastai import *
from fastai.vision import *
import sys
import json
path = Path('data/cloth_categories')
dBFilePath = '/home/azure/data.json'
app = Flask(__name__)
def predict(imagePath):
classes = ['Blouse', 'Blazer', 'Button-Down', 'Bomber', 'Anorak', 'T... | null | ClothingClassPrediction.py | ClothingClassPrediction.py | py | 1,696 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask.Flask",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "flask.request.json",
"line_number"... |
611877133 | import os
import re
import logging
from bootstrapvz.base import Task
from bootstrapvz.common import phases
from bootstrapvz.common.tasks import image
from bootstrapvz.common.tools import log_check_call
class FixVHD(Task):
description = 'Preparing VHD for Azure'
phase = phases.image_registration
predecessor... | null | bootstrapvz/providers/azure/tasks/image.py | image.py | py | 2,587 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "bootstrapvz.base.Task",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "bootstrapvz.common.phases.image_registration",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "bootstrapvz.common.phases",
"line_number": 11,
"usage_type": "name... |
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