code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
__doc__ = """
Dataset Module Utilities - mostly for handling files and datasets
"""
import glob
import os
import random
from meshparty import mesh_io
# Datasets -----------------------
SVEN_BASE = "seungmount/research/svenmd"
NICK_BASE = "seungmount/research/Nick/"
BOTH_BASE = "seungmount/research/nick_and_sven"
DAT... | normal | {
"blob_id": "fd0db093b72dad4657d71788405fcca4ba55daff",
"index": 8529,
"step-1": "<mask token>\n\n\ndef fetch_dset_dirs(dset_name=None):\n \"\"\"\n Finds the global pathname to a list of directories which represent a\n dataset by name.\n \"\"\"\n assert dset_name is None or dset_name in DATASET_DI... | [
3,
4,
6,
7,
8
] |
from django.db import models
import django.utils.timezone as timezone
# Create your models here.
# Create your models here.
class Categories(models.Model):
# 文章分类
name = models.CharField(max_length=200, verbose_name = "分类名称")
parent = models.ForeignKey('self', default=0, on_delete=models.DO_NOTHING, null = True... | normal | {
"blob_id": "512a13084a860e2784020664a3d5824d9dace6db",
"index": 7764,
"step-1": "<mask token>\n\n\nclass Images(models.Model):\n wordroot_text = models.CharField(max_length=255, verbose_name='词根')\n wordroot_id = models.IntegerField(default=0, null=True, blank=True,\n verbose_name='词根id, 可空')\n ... | [
14,
20,
22,
26,
27
] |
'''
Created on 2021. 4. 8.
@author: user
'''
import matplotlib.pyplot as plt
import numpy as np
plt.rc("font", family="Malgun Gothic")
def scoreBarChart(names, score):
plt.bar(names, score)
plt.show()
def multiBarChart(names, score):
plt.plot(names, score, "ro--")
plt.plot([1, 2, 3], [70, 8... | normal | {
"blob_id": "542602a42eb873508ce2ec39d0856f10cc1e04ff",
"index": 8426,
"step-1": "<mask token>\n\n\ndef scoreBarChart(names, score):\n plt.bar(names, score)\n plt.show()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef scoreBarChart(names, score):\n plt.bar(names, score)\n plt.show()\n\n\ndef... | [
1,
2,
3,
4,
5
] |
Xeval[[1,2],:]
# *** Spyder Python Console History Log ***
Xeval[:,:]
optfunc.P(Xeval[:,:])
optfunc.P(Xeval)
optfunc.P(Xeval[[0,1,2,3,4],:])
optfunc.P(Xeval[[0,1,],:])
optfunc.P(Xeval[[0,1],:])
optfunc.P(Xeval[[0,1,2,3],:])
optfunc.P(Xeval[[0,1,2,3,4],:])
optfunc.P(Xeval[[0,1,2],:])
Xeval[[0,1,2,3,4],:]
Xev... | normal | {
"blob_id": "02b20c3f5941873dfd22a7fbedb825e66c613ace",
"index": 2278,
"step-1": "Xeval[[1,2],:]\r\n# *** Spyder Python Console History Log ***\r\nXeval[:,:]\r\noptfunc.P(Xeval[:,:])\r\noptfunc.P(Xeval)\r\noptfunc.P(Xeval[[0,1,2,3,4],:])\r\noptfunc.P(Xeval[[0,1,],:])\r\noptfunc.P(Xeval[[0,1],:])\r\noptfunc.P(Xev... | [
0
] |
import numpy as np
a = np.ones((3,4))
b = np.ones((4,1))
# a.shape = (3,4)
# b.shape = (4,1)
c = np.zeros_like(a)
for i in range(3):
for j in range(4):
c[i][j] = a[i][j] + b[j]
print(c)
d = a+b.T
print(d)
| normal | {
"blob_id": "d6213698423902771011caf6b5206dd4e3b27450",
"index": 5753,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(3):\n for j in range(4):\n c[i][j] = a[i][j] + b[j]\nprint(c)\n<mask token>\nprint(d)\n",
"step-3": "<mask token>\na = np.ones((3, 4))\nb = np.ones((4, 1))\nc =... | [
0,
1,
2,
3,
4
] |
# Generated by Django 3.0.5 on 2020-05-02 18:58
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('weatherData', '0001_initial'),
]
operations = [
migrations.AddField(
model_name='city',
name='username',
... | normal | {
"blob_id": "6b6b734c136f3c4ed5b2789ab384bab9a9ea7b58",
"index": 9368,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('weatherData... | [
0,
1,
2,
3,
4
] |
import sys
INF = sys.maxsize
def bellman_ford(graph,start):
distance = {}
predecessor = {}
# 거리 값, 이전 정점 초기화
for node in graph:
distance[node] = INF
predecessor[node] = None
distance[start] = 0
# V-1개마큼 반복
for _ in range(len(graph)-1):
for node in graph:
... | normal | {
"blob_id": "8ebf031cb294c69bf744d543b18783d6ac5ef257",
"index": 1910,
"step-1": "<mask token>\n\n\ndef bellman_ford(graph, start):\n distance = {}\n predecessor = {}\n for node in graph:\n distance[node] = INF\n predecessor[node] = None\n distance[start] = 0\n for _ in range(len(gra... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.9.1 on 2016-10-28 17:50
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations... | normal | {
"blob_id": "b0064a5cd494d5ad232f27c63a4df2c56a4c6a66",
"index": 5241,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n initial = T... | [
0,
1,
2,
3,
4
] |
# Generated by Django 2.2.17 on 2020-12-05 07:43
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('service', '0001_initial'),
]
operations = [
migrations.AlterField(
model_name='identification',
name='id_card_img',... | normal | {
"blob_id": "b6a0a49e05fbc0ac7673d6c9e8ca4d263c8bb5cd",
"index": 7132,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('service', '... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
import csv
from bookstoscrapy import settings
def write_to_csv(item):
writer = csv.writer(open(settings.csv_file_path, '... | normal | {
"blob_id": "f0c621583caf6eea6f790649862a03a464f6574b",
"index": 3727,
"step-1": "<mask token>\n\n\nclass WriteToCsv(object):\n <mask token>\n\n def process_item(self, item, spider):\n write_to_csv(item)\n return item\n",
"step-2": "<mask token>\n\n\nclass WriteToCsv(object):\n item_coun... | [
2,
3,
4,
5,
6
] |
# Generated by Django 3.1.7 on 2021-04-16 05:56
from django.db import migrations
import django.db.models.manager
class Migration(migrations.Migration):
dependencies = [
('Checkbook', '0002_auto_20210415_2250'),
]
operations = [
migrations.AlterModelManagers(
name='transactio... | normal | {
"blob_id": "f15f49a29f91181d0aaf66b19ce9616dc7576be8",
"index": 6740,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('Checkbook',... | [
0,
1,
2,
3,
4
] |
class Fail(Exception):
def __init__(self, message):
super().__init__(message)
class Student:
def __init__(self, rollNo, name, marks):
self.rollNo = rollNo
self.name = name
self.marks = marks
def displayDetails(self):
print('{} \t {} \t {}'.format(self.name, self.... | normal | {
"blob_id": "ddf074e400551d2c147d898fe876a31d13a72699",
"index": 5324,
"step-1": "<mask token>\n\n\nclass Student:\n <mask token>\n\n def displayDetails(self):\n print('{} \\t {} \\t {}'.format(self.name, self.rollNo, self.marks))\n try:\n if self.marks < 40:\n raise... | [
2,
5,
6,
7
] |
r""" 测试dispatch
>>> from url_router.map import Map
>>> from url_router.rule import Rule
>>> m = Map([
... Rule('/', endpoint='index'),
... Rule('/foo', endpoint='foo'),
... Rule('/bar/', endpoint='bar'),
... Rule('/any/<name>', endpoint='any'),
... Rule('/string/<string:name>', endpoint='string'),
... | normal | {
"blob_id": "3cca7408eb88f91f295c581c29d3d1e95298f337",
"index": 6445,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n import doctest\n doctest.testmod()\n",
"step-3": "r\"\"\" 测试dispatch\n\n>>> from url_router.map import Map\n>>> from url_router.rule import Rule\n>>> ... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import requests
from bs4 import BeautifulSoup
url = "http://javmobile.net/?s=julia"
r = requests.get(url)
soup = BeautifulSoup(r.content, "html.parser")
imgs = soup.find_all("img" , {"class": "entry-thumb"})
images = []
titles = []
srcs = []
for img... | normal | {
"blob_id": "a9df8e45c8b5068aeec2b79e21de6217a3103bb4",
"index": 2492,
"step-1": "# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals\nimport requests\nfrom bs4 import BeautifulSoup\n\n\nurl = \"http://javmobile.net/?s=julia\"\nr = requests.get(url)\n\nsoup = BeautifulSoup(r.content, \"html.parser\"... | [
0
] |
from typing import List
from fastapi import Depends, FastAPI, HTTPException
from sqlalchemy.orm import Session
from myfirstpython.fastapi import models, crud, schemas
from myfirstpython.fastapi.dbconnection import engine, SessionLocal
models.Base.metadata.create_all(bind=engine)
app = FastAPI()
# Dependency
def g... | normal | {
"blob_id": "ad474f5120ca2a8c81b18071ab364e6d6cf9e653",
"index": 7031,
"step-1": "<mask token>\n\n\n@app.get('/jobs/', response_model=List[schemas.Job])\ndef read_jobs(skip: int=0, limit: int=100, db: Session=Depends(get_db)):\n jobs = crud.get_jobs(db, skip=skip, limit=limit)\n return jobs\n\n\n@app.get('... | [
6,
8,
10,
11,
13
] |
from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtWidgets import QLineEdit, QRadioButton, QPushButton, QTableWidgetItem, QTableWidget, QApplication, QMainWindow, QDateEdit, QLabel, QDialog, QTextEdit, QCheckBox
from PyQt5.QtCore import QDate, QTime, QDateTime, Qt
from OOPCourseWorkTwo.GUI.SingleAnswerQuestionDi... | normal | {
"blob_id": "98f234ca0cbec419466de0504fd8d5c68fd07627",
"index": 9609,
"step-1": "<mask token>\n\n\nclass TeacherGUI:\n <mask token>\n\n @classmethod\n def setup(cls, ui_mainwindow):\n cls.__ui_mainwindow = ui_mainwindow\n\n @classmethod\n def display_all_active_school_classes(cls, school_c... | [
100,
103,
113,
122,
132
] |
from typing import *
class Solution:
def isMonotonic(self, A: List[int]) ->bool:
flag = 0
for i in range(1, len(A)):
diff = A[i] - A[i - 1]
if diff * flag < 0:
return False
if flag == 0:
flag = diff
return True
sl = Sol... | normal | {
"blob_id": "a55d1286485e66a64aa78259ad1b1922c5c4c831",
"index": 4385,
"step-1": "<mask token>\n\n\nclass Solution:\n\n def isMonotonic(self, A: List[int]) ->bool:\n flag = 0\n for i in range(1, len(A)):\n diff = A[i] - A[i - 1]\n if diff * flag < 0:\n return... | [
2,
3,
4,
5
] |
from import_export.admin import ImportExportMixin
from django.contrib import admin
from import_export import resources, widgets, fields
from .models import Addgroup,Addsystemname,Zhuanzhebushi,Yewuzerenbumen,czyylx,Zhuanze,Data
from import_export import fields, resources
from import_export.widgets import ForeignKeyWidg... | normal | {
"blob_id": "016b64a2eb4af3034d54272c878fb917506d330c",
"index": 648,
"step-1": "<mask token>\n\n\nclass DataResource(resources.ModelResource):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n fields = 'groupname', 'system_name', 'I6000'\n\n\nclass DataAdmin(ImportExportMixin, ... | [
3,
4,
5,
6,
7
] |
# Generated by Django 2.2.13 on 2021-08-11 15:38
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("notifications", "0011_auto_20171229_1747"),
]
operations = [
migrations.AlterField(
model_name="notification",
name... | normal | {
"blob_id": "fa045ccd4e54332f6c05bf64e3318e05b8123a10",
"index": 3317,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('notificatio... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
#-*- coding: utf-8 -*-
import pygtk
pygtk.require("2.0")
import gtk
from testarMsg import *
class tgApp(object):
def __init__(self):
builder = gtk.Builder()
builder.add_from_file("../tg.glade")
self.window = builder.get_object("window1")
self.text_area = buil... | normal | {
"blob_id": "6b6fac3bfb1b1478dd491fc4dd9c45a19aeb7bd8",
"index": 6102,
"step-1": "<mask token>\n\n\nclass tgApp(object):\n\n def __init__(self):\n builder = gtk.Builder()\n builder.add_from_file('../tg.glade')\n self.window = builder.get_object('window1')\n self.text_area = builder... | [
6,
8,
9,
10,
12
] |
"""
common tests
"""
from django.test import TestCase
from src.core.common import get_method_config
from src.predictive_model.classification.models import ClassificationMethods
from src.predictive_model.models import PredictiveModels
from src.utils.tests_utils import create_test_job, create_test_predictive_model
cl... | normal | {
"blob_id": "824038a56e8aaf4adf6ec813a5728ab318547582",
"index": 1638,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestCommon(TestCase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TestCommon(TestCase):\n\n def test_get_method_config(self):\n job = create_test_job(pr... | [
0,
1,
2,
3,
4
] |
# https://daphne-dev.github.io/2020/09/24/algo-022/
def solution(n):
arr = [[0 for _ in range(i+1)] for i in range(n)]
# 경우의수 는 3가지
# 1. y축이 증가하면서 수가 증가
# 2. x축이 증가하면서 수가 증가
# 3. y,x축이 감소하면서 수가 증가
size = n
num = 0
x = 0
y = -1
while True:
# 1번
for _ in range(size)... | normal | {
"blob_id": "3c029adb59cd6db1e3d4a22e6561f5e2ae827d60",
"index": 2465,
"step-1": "<mask token>\n",
"step-2": "def solution(n):\n arr = [[(0) for _ in range(i + 1)] for i in range(n)]\n size = n\n num = 0\n x = 0\n y = -1\n while True:\n for _ in range(size):\n num += 1\n ... | [
0,
1,
2
] |
import tensorflow.keras
from PIL import Image, ImageOps
from os import listdir
from os.path import isfile, join
import numpy as np
import glob
import cv2
np.set_printoptions(suppress = True)
# Load the model
model = tensorflow.keras.models.load_model('./converted_keras/keras_model.h5')
# Create the array of the righ... | normal | {
"blob_id": "13b69ec61d6b2129f1974ce7cae91c84100b3b58",
"index": 449,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnp.set_printoptions(suppress=True)\n<mask token>\nfor image in path:\n n1 = cv2.imread(image)\n n2 = cv2.resize(n1, (244, 244))\n images.append(n2)\n print(image)\n<mask token>... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.2 on 2016-10-14 19:37
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
... | normal | {
"blob_id": "8c05259ce577e6b6a6efdf778832e9bb817e47fd",
"index": 1414,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [migrations.sw... | [
0,
1,
2,
3,
4
] |
import sys
def caesar( plaintext, key ):
if int( key ) < 0:
return
plaintext_ascii = [ ( ord( char ) + int( key ) ) for char in plaintext ]
for ascii in plaintext_ascii:
if ( ascii < 97 and ascii > 90 ) or ascii > 122:
ascii -= 25
ciphertext = ''.join( [ chr( ascii ) for a... | normal | {
"blob_id": "9a7c6998e9e486f0497d3684f9c7a422c8e13521",
"index": 7076,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef caesar(plaintext, key):\n if int(key) < 0:\n return\n plaintext_ascii = [(ord(char) + int(key)) for char in plaintext]\n for ascii in plaintext_ascii:\n if ... | [
0,
1,
2,
3,
4
] |
# Importing datasets wrangling libraries
import numpy as np
import pandas as pd
incd_data = pd.read_csv('data/Cancer/incd.csv', usecols=['State', 'FIPS', 'Age-Adjusted Incidence Rate([rate note]) - cases per 100,000', 'Average Annual Count', 'Recent Trend'])
print(incd_data.columns)
| normal | {
"blob_id": "1deab16d6c574bf532c561b8d6d88aac6e5d996c",
"index": 8355,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(incd_data.columns)\n",
"step-3": "<mask token>\nincd_data = pd.read_csv('data/Cancer/incd.csv', usecols=['State', 'FIPS',\n 'Age-Adjusted Incidence Rate([rate note]) - cases pe... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Module that defines a controller for database's operations over business rules
"""
# built-in dependencies
import functools
import typing
# external dependencies
import sqlalchemy
from sqlalchemy.orm import sessionmaker
# project dependencies
from database.table im... | normal | {
"blob_id": "c024e12fe06e47187c25a9f384ceed566bf94645",
"index": 6909,
"step-1": "<mask token>\n\n\nclass _DatabaseResourceTableController:\n <mask token>\n <mask token>\n\n def register_peer(self, peer_id: str, peer_ip: str, peer_port: int,\n resource_name: str, resource_path: str, resource_hash... | [
5,
6,
7,
9,
11
] |
import matplotlib.pyplot as plt
import numpy as np
x = [1, 2, 2.5, 3, 4] # x-coordinates for graph
y = [1, 4, 7, 9, 15] # y-coordinates
plt.axis([0, 6, 0, 20]) # creating my x and y axis range. 0-6 is x, 0-20 is y
plt.plot(x, y, 'ro')
# can see graph has a linear correspondence, therefore, can use linear regression ... | normal | {
"blob_id": "c69c8ba218935e5bb065b3b925cc7c5f1aa2957b",
"index": 5806,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nplt.axis([0, 6, 0, 20])\nplt.plot(x, y, 'ro')\nplt.plot(np.unique(x), np.poly1d(np.polyfit(x, y, 1))(np.unique(x)))\nplt.show()\n",
"step-3": "<mask token>\nx = [1, 2, 2.5, 3, 4]\ny = [... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = "Alonso Vidales"
__email__ = "alonso.vidales@tras2.es"
__date__ = "2013-11-11"
class ConnectedSets:
"""
This is a classic percolation problem, the algorithms uses an array
of integer to represent tees, each tree will be a set of connected element... | normal | {
"blob_id": "d18c0fa29ccdabdd9e11622e8aaec91ff96117df",
"index": 6650,
"step-1": "#!/usr/bin/env python\n# -*- coding: utf-8 -*- \n\n__author__ = \"Alonso Vidales\"\n__email__ = \"alonso.vidales@tras2.es\"\n__date__ = \"2013-11-11\"\n\nclass ConnectedSets:\n \"\"\"\n This is a classic percolation problem, ... | [
0
] |
#!/usr/bin/env python
'''
@author : Mitchell Van Braeckel
@id : 1002297
@date : 10/10/2020
@version : python 3.8-32 / python 3.8.5
@course : CIS*4010 Cloud Computing
@brief : A1 Part 2 - AWS DynamoDB ; Q2 - Query OECD
@note :
Description: There are many CSV files containing info from the OECD about agricultural p... | normal | {
"blob_id": "05186093820dffd047b0e7b5a69eb33f94f78b80",
"index": 6787,
"step-1": "<mask token>\n\n\ndef main():\n global dynamodb_client\n global dynamodb_resource\n global na_table\n global canada_table\n global usa_table\n global mexico_table\n global total_can_usa\n global total_can_us... | [
5,
6,
7,
9,
10
] |
import math
print(dir(math))
# Prints a list of entities residing in the math module | normal | {
"blob_id": "94056e8920d265831da67bd1d999330a47a7ef0d",
"index": 1991,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(dir(math))\n",
"step-3": "import math\nprint(dir(math))\n",
"step-4": "import math\nprint(dir(math))\n\n# Prints a list of entities residing in the math module",
"step-5": nul... | [
0,
1,
2,
3
] |
#Voir paragraphe "3.6 Normalizing Text", page 107 de NLP with Python
from nltk.stem.snowball import SnowballStemmer
from nltk.stem.wordnet import WordNetLemmatizer
# Il faut retirer les stopwords avant de stemmer
stemmer = SnowballStemmer("english", ignore_stopwords=True)
lemmatizer = WordNetLemmatizer()
source = ... | normal | {
"blob_id": "1f1677687ba6ca47b18728b0fd3b9926436e9796",
"index": 2949,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(stems1)\nprint(stems2)\nprint(stems3)\n",
"step-3": "<mask token>\nstemmer = SnowballStemmer('english', ignore_stopwords=True)\nlemmatizer = WordNetLemmatizer()\nsource = ['having... | [
0,
1,
2,
3,
4
] |
linha = input().split()
a = float(linha[0])
b = float(linha[1])
c = float(linha[2])
t = (a*c)/2
print('TRIANGULO: {:.3f}'.format(t))
pi = 3.14159
print("CIRCULO: {:.3f}".format(pi*c**2))
print('TRAPEZIO: {:.3f}'.format( ((a+b)*c)/2 ))
print("QUADRADO: {:.3f}".format(b**2))
print("RETANGULO: {:.3f}".format(a*b)) | normal | {
"blob_id": "d44d9003e9b86722a0fc1dfe958de462db9cd5f1",
"index": 1670,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('TRIANGULO: {:.3f}'.format(t))\n<mask token>\nprint('CIRCULO: {:.3f}'.format(pi * c ** 2))\nprint('TRAPEZIO: {:.3f}'.format((a + b) * c / 2))\nprint('QUADRADO: {:.3f}'.format(b ** 2... | [
0,
1,
2,
3
] |
"""
"""
import cPickle as pickle
def convert_cpu_stats_to_num_array(cpuStats):
"""
Given a list of statistics (tuples[timestamp, total_cpu, kernel_cpu, vm, rss])
Return five numarrays
"""
print "Converting cpus stats into numpy array"
c0 = []
c1 = []
c2 = []
c3 = []
c4 = []
... | normal | {
"blob_id": "85f5f9370896eac17dc72bbbf8d2dd1d7adc3a5b",
"index": 7872,
"step-1": "\"\"\"\n\n\"\"\"\nimport cPickle as pickle\n\n\ndef convert_cpu_stats_to_num_array(cpuStats):\n \"\"\"\n Given a list of statistics (tuples[timestamp, total_cpu, kernel_cpu, vm, rss])\n Return five numarrays\n \"\"\"\n ... | [
0
] |
'''
The while statement allows you to repeatedly execute a block of statements as long as a condition is true.
A while statement is an example of what is called a looping statement. A while statement can have an optional else clause.
'''
#Modifying the values using while loop in a list
l1: list = [1,2,3,4,5,6,7,8,9,10... | normal | {
"blob_id": "6a3fd3323ed8792853afdf5af76161f3e20d4896",
"index": 4443,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nl1: list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\nprint('The original list: ', l1)\n<mask token>\nwhile i < len(l1):\n l1[i] = l1[i] + 100\n i = i + 1\nprint('The modified new list is: ',... | [
0,
1,
2,
3
] |
# coding=utf-8
# Copyright 2021-Present The THUCTC Authors
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import math
import torch
import torch.nn as nn
import thuctc.utils as utils
from thuctc.modules.module import Module
from thuctc.modules.layer_norm ... | normal | {
"blob_id": "c773b273ad6953bf9c74b11c44aff16e9fd0860e",
"index": 3468,
"step-1": "<mask token>\n\n\nclass Embedding(Module):\n\n def __init__(self, embed_nums, embed_dims, bias=False, name='embedding'):\n super(Embedding, self).__init__(name=name)\n self.embed_nums = embed_nums\n self.emb... | [
7,
9,
10,
12,
13
] |
from django.db import models
from django.urls import reverse
from django.conf import settings
from embed_video.fields import EmbedVideoField
from django.contrib.auth.models import AbstractBaseUser
User = settings.AUTH_USER_MODEL
# Create your models here.
"""class User(models.Model):
username = models.CharField(... | normal | {
"blob_id": "5c4a48de94cf5bfe67e6a74c33a317fa1da8d2fa",
"index": 7330,
"step-1": "<mask token>\n\n\nclass Post(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n ordering = ['parent_id', 'created_at']\n <mask token>\n <mask... | [
3,
7,
8,
9,
10
] |
/home/mitchellwoodbine/Documents/github/getargs/GetArgs.py | normal | {
"blob_id": "0065a493767a2080a20f8b55f76ddeae92dc27f1",
"index": 3359,
"step-1": "/home/mitchellwoodbine/Documents/github/getargs/GetArgs.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
/Users/apple/miniconda3/lib/python3.7/sre_constants.py | normal | {
"blob_id": "71a5ba520f8bc42e80d8f4ce8cf332bdd5fb96de",
"index": 5293,
"step-1": "/Users/apple/miniconda3/lib/python3.7/sre_constants.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
# 6. Evaluate Classifier: you can use any metric you choose for this assignment
# (accuracy is the easiest one). Feel free to evaluate it on the same data you
# built the model on (this is not a good idea in general but for this assignment,
# it is fine). We haven't covered models and evaluation yet, so don't worry ... | normal | {
"blob_id": "62de629d8f28435ea8dc3dc093cac95e7cedf128",
"index": 7859,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef evaluate(model, X_te, y_te):\n \"\"\"\n Given the model and independent and dependent testing data,\n print out statements that evaluate classifier\n \"\"\"\n probs... | [
0,
1,
2,
3,
4
] |
__author__ = 'tomer'
import sqlite3
from random import randint
import test_data
def init_database(conn):
c = conn.cursor()
c.execute('''CREATE TABLE IF NOT EXISTS catalogs
(id INTEGER PRIMARY KEY AUTOINCREMENT, catalog_name TEXT)''')
c.execute('''CREATE TABLE IF NOT EXISTS products
... | normal | {
"blob_id": "46b1e5adbd956c35820d7d2b17628364388cdcd7",
"index": 3638,
"step-1": "<mask token>\n\n\ndef init_database(conn):\n c = conn.cursor()\n c.execute(\n \"\"\"CREATE TABLE IF NOT EXISTS catalogs\n (id INTEGER PRIMARY KEY AUTOINCREMENT, catalog_name TEXT)\"\"\"\n )\n ... | [
9,
17,
19,
20,
21
] |
# use local image
import io
import os
from google.cloud import vision
from google.oauth2 import service_account
creds = service_account.Credentials.from_service_account_file('./key.json')
client = vision.ImageAnnotatorClient(
credentials=creds,
)
# The name of the image file to annotate
file_name = os.path.joi... | normal | {
"blob_id": "800573786913ff2fc37845193b5584a0a815533f",
"index": 8340,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith io.open(file_name, 'rb') as image_file:\n content = image_file.read()\n<mask token>\nprint(response)\nprint(response.safe_search_annotation.adult)\nfor label in response.label_ann... | [
0,
1,
2,
3,
4
] |
from flask import Flask, request, g
from flask_restful import Resource, Api
from sqlalchemy import create_engine
from flask import jsonify
import json
import eth_account
import algosdk
from sqlalchemy.orm import sessionmaker
from sqlalchemy.orm import scoped_session
from sqlalchemy.orm import load_only
from datetime im... | normal | {
"blob_id": "d9bdf466abecb50c399556b99b41896eead0cb4b",
"index": 2959,
"step-1": "<mask token>\n\n\n@app.before_request\ndef create_session():\n g.session = scoped_session(DBSession)\n\n\n<mask token>\n\n\ndef check_sig(payload, sig):\n pk = payload['sender_pk']\n platform = payload['platform']\n pay... | [
7,
8,
11,
12,
13
] |
import requests, shutil, os, glob
from zipfile import ZipFile
import pandas as pd
from xlrd import open_workbook
import csv
# zipfilename = 'desiya_hotels'
# try:
# # downloading zip file
# r = requests.get('http://staticstore.travelguru.com/testdump/1300001176/Excel.zip', auth=('testdump', 'testdump'), veri... | normal | {
"blob_id": "1ef9df43725196904ec6c0c881f4a1204174b176",
"index": 375,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(os.path.join(os.path.dirname(__file__), 'storage/robot_list.csv'),\n 'w') as file:\n writer = csv.writer(file, delimiter=',')\n headers = [cell.value for cell in sheet.r... | [
0,
1,
2,
3,
4
] |
from sqlalchemy import create_engine
from sqlalchemy import Table,Column,Integer,String,MetaData,ForeignKey
from sqlalchemy.sql import select
from sqlalchemy import text
#Creating a database 'college.db'
engine = create_engine('sqlite:///college.db', echo=True)
meta = MetaData()
#Creating a Students table
s... | normal | {
"blob_id": "7ea6fefa75d36ff45dcea49919fdc632e378a73f",
"index": 9113,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmeta.create_all(engine)\n<mask token>\nconn.execute(students.insert(), [{'name': 'Rajiv', 'lastname': 'Khanna'}, {\n 'name': 'Komal', 'lastname': 'Bhandari'}, {'name': 'Abdul', 'lastna... | [
0,
1,
2,
3,
4
] |
'''
Code for mmDGM
Author: Chongxuan Li (chongxuanli1991@gmail.com)
Version = '1.0'
'''
import gpulearn_mm_z_x
import sys, os
import time
import color
n_hidden = (500,500)
if len(sys.argv) > 2:
n_hidden = tuple([int(x) for x in sys.argv[2:]])
nz=500
if os.environ.has_key('nz'):
nz = int(os.environ['nz'])
if os.en... | normal | {
"blob_id": "40158bbfd9c95a8344f34431d0b0e98c4a1bf6ed",
"index": 476,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(sys.argv) > 2:\n n_hidden = tuple([int(x) for x in sys.argv[2:]])\n<mask token>\nif os.environ.has_key('nz'):\n nz = int(os.environ['nz'])\nif os.environ.has_key('stepsize'):\... | [
0,
1,
2,
3,
4
] |
'''
Created on May 18, 2010
@author: Abi.Mohammadi & Majid.Vesal
'''
from threading import current_thread
import copy
import time
from deltapy.core import DeltaException, Context
import deltapy.security.services as security_services
import deltapy.security.session.services as session_services
import deltapy.unique... | normal | {
"blob_id": "80469fd945a21c1bd2b5590047016a4b60880c88",
"index": 7006,
"step-1": "<mask token>\n\n\nclass Session:\n <mask token>\n\n\n class StateEnum:\n \"\"\"\n A class for defining session state.\n \"\"\"\n ACTIVE = 'Active'\n INACTIVE = 'Inactive'\n CLOSED = '... | [
18,
21,
25,
28,
31
] |
from rest_framework.serializers import ModelSerializer
from rest_framework.serializers import ReadOnlyField
from rest_framework.serializers import SlugField
from rest_framework.validators import UniqueValidator
from django.db import models
from illumidesk.teams.util import get_next_unique_team_slug
from illumidesk.us... | normal | {
"blob_id": "c005ae9dc8b50e24d72dbc99329bb5585d617081",
"index": 5590,
"step-1": "<mask token>\n\n\nclass InvitationSerializer(ModelSerializer):\n <mask token>\n <mask token>\n\n\n class Meta:\n model = Invitation\n fields = 'id', 'team', 'email', 'role', 'invited_by', 'is_accepted'\n\n\nc... | [
4,
6,
8,
9,
10
] |
from robocorp_ls_core.python_ls import PythonLanguageServer
from robocorp_ls_core.basic import overrides
from robocorp_ls_core.robotframework_log import get_logger
from typing import Optional, List, Dict
from robocorp_ls_core.protocols import IConfig, IMonitor, ITestInfoTypedDict, IWorkspace
from functools import parti... | normal | {
"blob_id": "18b43ea8696e2e54f4c1cbbece4cde1fd3130145",
"index": 194,
"step-1": "<mask token>\n\n\nclass RobotFrameworkServerApi(PythonLanguageServer):\n <mask token>\n\n def __init__(self, read_from, write_to, libspec_manager=None, observer:\n Optional[IFSObserver]=None):\n from robotframewo... | [
19,
33,
35,
44,
51
] |
from django.forms import ModelForm
from contactform.models import ContactRequest
class ContactRequestForm(ModelForm):
class Meta:
model = ContactRequest
| normal | {
"blob_id": "97637e2114254b41ef6e777e60b3ddab1d4622e8",
"index": 4606,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ContactRequestForm(ModelForm):\n\n\n class Meta:\n model = ContactRequest\n",
"step-3": "from django.forms import ModelForm\nfrom contactform.models import ContactRe... | [
0,
1,
2
] |
class Enumerator(object):
"""For Python we just wrap the iterator"""
def __init__(self, next):
self.iterator = next
def __next__(self):
return next(self.iterator)
# Python 2.7
next = __next__
def __iter__(self):
return self
| normal | {
"blob_id": "1ca20b0cd9217623ff039ab352acd09df8dfae1b",
"index": 8235,
"step-1": "class Enumerator(object):\n <mask token>\n <mask token>\n\n def __next__(self):\n return next(self.iterator)\n <mask token>\n\n def __iter__(self):\n return self\n",
"step-2": "class Enumerator(object... | [
3,
4,
5,
6,
7
] |
from io import StringIO
from pathlib import Path
from unittest import TestCase
from doculabs.samon import constants
from doculabs.samon.elements import BaseElement, AnonymusElement
from doculabs.samon.expressions import Condition, ForLoop, Bind
class BaseElementTest(TestCase):
def assertXmlEqual(self, generated_... | normal | {
"blob_id": "c6b98cf309e2f1a0d279ec8dc728ffd3fe45dfdb",
"index": 4792,
"step-1": "<mask token>\n\n\nclass BaseElementTest(TestCase):\n <mask token>\n <mask token>\n\n def test_parse_expressions(self):\n xml_attrs = {(constants.XML_NAMESPACE_FLOW_CONTROL, 'if'):\n 'val == 7', (constants... | [
5,
7,
8,
9,
11
] |
import tests.functions as functions
if __name__ == "__main__":
# functions.validate_all_redirects("linked.data.gov.au-vocabularies.json")
conf = open("../conf/linked.data.gov.au-vocabularies.conf")
new = [
"anzsrc-for",
"anzsrc-seo",
"ausplots-cv",
"australian-phone-area... | normal | {
"blob_id": "4a620957b2cd1e5945d98e49a5eae5d5592ef5a2",
"index": 3911,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n conf = open('../conf/linked.data.gov.au-vocabularies.conf')\n new = ['anzsrc-for', 'anzsrc-seo', 'ausplots-cv',\n 'australian-phone-area-codes', ... | [
0,
1,
2,
3
] |
import heapq as heap
import networkx as nx
import copy
import random
def remove_jumps(moves):
res = []
for move in moves:
if move[2] > 1:
move[3].reverse()
res.extend(make_moves_from_path(move[3]))
else:
res.append(move)
return res
def make_moves_from... | normal | {
"blob_id": "800edfc61635564abf8297c4f33c59d48cc99960",
"index": 4058,
"step-1": "<mask token>\n\n\ndef make_moves_from_path(path):\n moves = []\n p = path[:]\n for i in range(len(p) - 1):\n moves.append((p[i + 1], p[i], 1, [p[i + 1], p[i]]))\n return moves\n\n\ndef find_nearest_hole(o, r, gra... | [
7,
11,
12,
16,
19
] |
# -*- coding: utf-8 -*-
########### SVN repository information ###################
# $Date: $
# $Author: $
# $Revision: $
# $URL: $
# $Id: $
########### SVN repository information ###################
'''
*GSASIIfpaGUI: Fundamental Parameters Routines*
===============================================
This module contain... | normal | {
"blob_id": "3b1426e0f29093e1e462765bcf1d351a064b9639",
"index": 142,
"step-1": "<mask token>\n\n\ndef SetCu2Wave():\n \"\"\"Set the parameters to the two-line Cu K alpha 1+2 spectrum\n \"\"\"\n parmDict['wave'] = {i: v for i, v in enumerate((1.540596, 1.544493))}\n parmDict['int'] = {i: v for i, v i... | [
7,
8,
9,
10,
11
] |
import configparser
# CONFIG
config = configparser.ConfigParser()
config.read('dwh.cfg')
# DISTRIBUTION SCHEMA
schema = ("""CREATE SCHEMA IF NOT EXISTS public;
SET search_path TO public;""")
# DROP TABLES
staging_events_table_drop = ("DROP TABLE IF EXISTS staging_events;")
staging_songs_table_drop = ... | normal | {
"blob_id": "65b7a14c54cd988185bac54fd8a31330966f8ba9",
"index": 1916,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nconfig.read('dwh.cfg')\n<mask token>\n",
"step-3": "<mask token>\nconfig = configparser.ConfigParser()\nconfig.read('dwh.cfg')\nschema = \"\"\"CREATE SCHEMA IF NOT EXISTS public;\n ... | [
0,
1,
2,
3,
4
] |
import nox
@nox.session(python=["3.9", "3.8", "3.7", "3.6"], venv_backend="conda", venv_params=["--use-local"])
def test(session):
"""Add tests
"""
session.install()
session.run("pytest")
@nox.session(python=["3.9", "3.8", "3.7", "3.6"])
def lint(session):
"""Lint the code with flake8.
"""
... | normal | {
"blob_id": "9aecf297ed36784d69e2be6fada31f7c1ac37500",
"index": 4778,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@nox.session(python=['3.9', '3.8', '3.7', '3.6'], venv_backend='conda',\n venv_params=['--use-local'])\ndef test(session):\n \"\"\"Add tests\n \"\"\"\n session.install()\n... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 18 16:11:44 2021
@author: ignacio
"""
import matplotlib.pyplot as plt
from numpy.linalg import inv as invertir
from time import perf_counter
import numpy as np
def matriz_laplaciana(N, t=np.single): # funcion obtenida de clase
e=np.eye(N)-np.eye(N,N,... | normal | {
"blob_id": "86345702bcd423bc31e29b1d28aa9c438629297d",
"index": 7331,
"step-1": "<mask token>\n\n\ndef matriz_laplaciana(N, t=np.single):\n e = np.eye(N) - np.eye(N, N, 1)\n return t(e + e.T)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef matriz_laplaciana(N, t=np.single):\n e = np.eye(N) - n... | [
1,
2,
3,
4,
5
] |
"""
TestRail API Categories
"""
from . import _category
from ._session import Session
class TestRailAPI(Session):
"""Categories"""
@property
def attachments(self) -> _category.Attachments:
"""
https://www.gurock.com/testrail/docs/api/reference/attachments
Use the following API me... | normal | {
"blob_id": "c2467e94a2ad474f0413e7ee3863aa134bf9c51f",
"index": 3399,
"step-1": "<mask token>\n\n\nclass TestRailAPI(Session):\n <mask token>\n\n @property\n def attachments(self) ->_category.Attachments:\n \"\"\"\n https://www.gurock.com/testrail/docs/api/reference/attachments\n U... | [
17,
20,
21,
22,
24
] |
#!/usr/bin/python2
import gmpy2
p = 24659183668299994531
q = 28278904334302413829
e = 11
c = 589000442361955862116096782383253550042
t = (p-1)*(q-1)
n = p*q
# returns d such that e * d == 1 modulo t, or 0 if no such y exists.
d = gmpy2.invert(e,t)
# Decryption
m = pow(c,d,n)
print "Solved ! m = %d" % m
| normal | {
"blob_id": "61c2a6499dd8de25045733f9061d660341501314",
"index": 8334,
"step-1": "#!/usr/bin/python2\nimport gmpy2\n\np = 24659183668299994531\nq = 28278904334302413829\ne = 11\nc = 589000442361955862116096782383253550042\nt = (p-1)*(q-1)\nn = p*q\n\n# returns d such that e * d == 1 modulo t, or 0 if no such... | [
0
] |
import numpy as np
np.set_printoptions(precision = 1)
pi = np.pi
def convertRadian(theta):
radian = (theta) * (np.pi) / 180
return radian
def mkMatrix(radian, alpha, dis):
matrix = np.matrix([[np.cos(radian),(-1)*np.sin(radian)*np.cos(alpha), np.sin(radian)*np.sin(alpha), a1 * np.cos(radian)],
... | normal | {
"blob_id": "47c6f9767b97469fe7e97ab3b69650265a8021d8",
"index": 6257,
"step-1": "import numpy as np\n\nnp.set_printoptions(precision = 1)\npi = np.pi\n\ndef convertRadian(theta):\n radian = (theta) * (np.pi) / 180\n return radian\n\ndef mkMatrix(radian, alpha, dis):\n matrix = np.matrix([[np.cos(radian... | [
0
] |
#Program to convert temp in degree Celsius to temp in degree Fahrenheit
celsius=input("Enter temperature in Celsius")
celsius=int(celsius)
fah=(celsius*9/5)+32
print("Temp in ",celsius,"celsius=",fah," Fahrenheit")
| normal | {
"blob_id": "e1172cadeb8b2ce036d8431cef78cfe19bda0cb8",
"index": 2161,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Temp in ', celsius, 'celsius=', fah, ' Fahrenheit')\n",
"step-3": "celsius = input('Enter temperature in Celsius')\ncelsius = int(celsius)\nfah = celsius * 9 / 5 + 32\nprint('Tem... | [
0,
1,
2,
3
] |
import pylab,numpy as np
from numpy import sin
from matplotlib.patches import FancyArrowPatch
fig=pylab.figure()
w=1
h=1
th=3.14159/25.
x=np.r_[0,0,w,w,0]
y=np.r_[0,h,h-w*sin(th),0-w*sin(th),0]
pylab.plot(x,y)
x=np.r_[0,0,w/2.0,w/2.0,0]
y=np.r_[0,h/6.0,h/6.0-w/2.0*sin(th),0-w/2.0*sin(th),0]
pylab.plot(x... | normal | {
"blob_id": "c485466a736fa0a4f183092e561a27005c01316d",
"index": 8616,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npylab.plot(x, y)\n<mask token>\npylab.plot(x, y, '--')\npylab.text(w / 4.0, h / 12.0 - w / 4.0 * sin(th) - h / 30.0,\n '$A_{a,subcool}$', ha='center', va='center')\n<mask token>\npylab... | [
0,
1,
2,
3,
4
] |
arr = []
for i in range(5):
arr.append(int(input()))
print(min(arr[0], arr[1], arr[2]) + min(arr[3], arr[4]) - 50)
| normal | {
"blob_id": "8745855d86dcdabe55f8d1622b66b3613dbfe3e1",
"index": 4015,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(5):\n arr.append(int(input()))\nprint(min(arr[0], arr[1], arr[2]) + min(arr[3], arr[4]) - 50)\n",
"step-3": "arr = []\nfor i in range(5):\n arr.append(int(input()))... | [
0,
1,
2
] |
from flask import Blueprint, request
from ecdsa import SigningKey, NIST384p
import base64, codecs
from cryptography.fernet import Fernet
ecdsa_app = Blueprint('ecdsa_app', __name__, url_prefix='/ecdsa_app')
f = Fernet(Fernet.generate_key())
sk = SigningKey.generate(curve=NIST384p)
vk = sk.get_verifying_key()
@ecd... | normal | {
"blob_id": "4eb7abb24451f3f895d0731de7b29a85d90c1539",
"index": 8246,
"step-1": "<mask token>\n\n\n@ecdsa_app.get('/create_pkey')\ndef private_key():\n return {'status': 'success', 'result': sk.to_string().hex()}\n\n\n@ecdsa_app.post('/op')\ndef check_op():\n input = request.get_json()\n operators = ['... | [
4,
5,
6,
7,
8
] |
from django.db import models
class Book(models.Model):
title = models.TextField(max_length=32, blank=False, null=False)
# from django.contrib.auth.models import AbstractBaseUser, PermissionsMixin, BaseUserManager
#
#
# class UserAccountManager(BaseUserManager):
# def create_user(self, email, firstname,lastna... | normal | {
"blob_id": "8286407987301ace7af97d6acdcf6299ce3d8525",
"index": 5440,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Book(models.Model):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Book(models.Model):\n title = models.TextField(max_length=32, blank=False, null=False)\n",
"s... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 15 19:27:59 2020
@author: Dan
"""
import numpy as np
def shift(v,i,j):
if i <= j:
return v
store = v[i]
for k in range(0, i-j-1):
v[i-k] = v[i-k-1]
v[j] = store
return v
def insertion(v):
for i in range(1, len(v)):
j = i
... | normal | {
"blob_id": "35288c9ad4d3550003e3c2f9e9034f4bce1df830",
"index": 3626,
"step-1": "<mask token>\n\n\ndef shift(v, i, j):\n if i <= j:\n return v\n store = v[i]\n for k in range(0, i - j - 1):\n v[i - k] = v[i - k - 1]\n v[j] = store\n return v\n\n\ndef insertion(v):\n for i in rang... | [
2,
3,
4,
5,
6
] |
import logging
import random
from pyage.core.address import Addressable
from pyage.core.agent.agent import AbstractAgent
from pyage.core.inject import Inject, InjectOptional
logger = logging.getLogger(__name__)
class AggregateAgent(Addressable, AbstractAgent):
@Inject("aggregated_agents:_AggregateAgent__agents")... | normal | {
"blob_id": "85903f0c6bd4c896379c1357a08ae3bfa19d5415",
"index": 7065,
"step-1": "<mask token>\n\n\nclass AggregateAgent(Addressable, AbstractAgent):\n\n @Inject('aggregated_agents:_AggregateAgent__agents')\n @InjectOptional('locator')\n def __init__(self, name=None):\n self.name = name\n ... | [
7,
10,
11,
13,
15
] |
from collections import Counter
import numpy as np
import random
import torch
import BidModel
from douzero.env.game import GameEnv
env_version = "3.2"
env_url = "http://od.vcccz.com/hechuan/env.py"
Card2Column = {3: 0, 4: 1, 5: 2, 6: 3, 7: 4, 8: 5, 9: 6, 10: 7,
11: 8, 12: 9, 13: 10, 14: 11, 17: 12}
Nu... | normal | {
"blob_id": "4015078ee9640c4558a4f29ebbb89f9098a31014",
"index": 5720,
"step-1": "<mask token>\n\n\nclass Env:\n <mask token>\n\n def __init__(self, objective):\n \"\"\"\n Objective is wp/adp/logadp. It indicates whether considers\n bomb in reward calculation. Here, we use dummy agents... | [
13,
24,
32,
36,
37
] |
# 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 agreed to in writing, software
# distributed under t... | normal | {
"blob_id": "d56fa4ea999d8af887e5f68296bfb20ad535e6ad",
"index": 6748,
"step-1": "<mask token>\n\n\nclass PXEBaseMixin(object):\n\n def get_properties(self):\n \"\"\"Return the properties of the interface.\n\n :returns: dictionary of <property name>:<property description> entries.\n \"\"\... | [
4,
5,
6,
7,
8
] |
try:
a=100
b=a/0
print(b)
except ZeroDivisionError as z:
print("Error= ",z) | normal | {
"blob_id": "9dead39e41fd0f3cff43501c659050885a50fec3",
"index": 4521,
"step-1": "<mask token>\n",
"step-2": "try:\n a = 100\n b = a / 0\n print(b)\nexcept ZeroDivisionError as z:\n print('Error= ', z)\n",
"step-3": "try:\r\n a=100\r\n b=a/0\r\n print(b)\r\nexcept ZeroDivisionError as z:... | [
0,
1,
2
] |
from collections import Counter
from collections import deque
import os
def wc(argval):
bool = False
if("|" in argval):
bool = True
del argval[len(argval)-1]
hf=open("commandoutput.txt","r+")
open("commandoutput.txt","w").close()
hf=open("commandoutput.txt","w")
numoflines = 0
... | normal | {
"blob_id": "e9a4ea69a4bd9b75b8eb8092b140691aab763ae4",
"index": 2963,
"step-1": "from collections import Counter\nfrom collections import deque\nimport os\ndef wc(argval):\n bool = False\n if(\"|\" in argval):\n bool = True\n del argval[len(argval)-1] \n hf=open(\"commandoutput.txt\",\"r+\"... | [
0
] |
# -*- coding: utf-8 -*-
""" This module provides a function for splitting datasets."""
from skmultilearn.model_selection import IterativeStratification
def iterative_train_test(X, y, test_size):
"""
Iteratively splits data with stratification.
This function is based on the iterative_train_test_split func... | normal | {
"blob_id": "c4c068c7b50d1811f224701ad7e95d88f6734230",
"index": 2867,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef iterative_train_test(X, y, test_size):\n \"\"\"\n Iteratively splits data with stratification.\n\n This function is based on the iterative_train_test_split function from ... | [
0,
1,
2,
3
] |
from django.contrib import admin
from django.contrib.admin.sites import AdminSite
from obp.models import *
from django.utils.html import format_html
from jet.admin import CompactInline
#from django.utils.translation import ugettext_lazy as _
from jet.dashboard import modules
from jet.dashboard.dashboard import Dashboa... | normal | {
"blob_id": "d301ffa790d6444519e354a2b6f8d65f67d380c0",
"index": 1739,
"step-1": "<mask token>\n\n\nclass Client_OrderInline(admin.TabularInline):\n <mask token>\n\n\nclass MyAdminSite(AdminSite):\n site_header = 'Pizza-Day'\n index_template = 'admin/index.html'\n\n\n@admin.register(Product)\nclass Prod... | [
16,
17,
18,
24,
25
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 6 10:05:25 2019
@author: MCA
"""
import smtplib, ssl
from email import encoders
from email.mime.text import MIMEText
from email.mime.base import MIMEBase
from email.mime.multipart import MIMEMultipart
import os,sys
import time
def loadFiles(su... | normal | {
"blob_id": "b310c35b781e3221e2dacc7717ed77e20001bafa",
"index": 5109,
"step-1": "<mask token>\n\n\ndef loadFiles(subdir, filetype):\n \"\"\"\n example:\n dirs = [\"dir1\", \"dir2\"]\n file_type = \".dat\"\n files, keys, data = loadFiles(dirs[0], file_type)\n \n \"\"\"\n dirname = os.path... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python3
import argparse
import os
import sys,shutil
from shutil import make_archive
import pathlib
from phpManager import execute,execute_outputfile
from datetime import date,datetime
import re
import pymysql
import tarfile
def append_log(log,message):
f = open(log, "a+")
today = datetime.now()... | normal | {
"blob_id": "e09af436f2fb37d16427aa0b1416d6f2d59ad6c4",
"index": 214,
"step-1": "<mask token>\n\n\ndef append_log(log, message):\n f = open(log, 'a+')\n today = datetime.now()\n f.write('%s %s \\n' % (today.strftime('%Y-%m-%d %H:%M:%S'), message))\n f.close()\n\n\ndef get_root_pass():\n with open(... | [
10,
11,
13,
14,
15
] |
'''
Find the greatest product of five consecutive digits in the 1000-digit number.
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208805511
12540698747158523863050715693290963295227443043557
66896648950445244523161731856403... | normal | {
"blob_id": "db20a77778392c84bab50f6d4002dd11b73967b9",
"index": 9214,
"step-1": "'''\nFind the greatest product of five consecutive digits in the 1000-digit number.\n\n73167176531330624919225119674426574742355349194934\n96983520312774506326239578318016984801869478851843\n8586156078911294949545950173795833195285... | [
0
] |
"""
Django settings for geobombay project.
For more information on this file, see
https://docs.djangoproject.com/en/1.7/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.7/ref/settings/
"""
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
... | normal | {
"blob_id": "32ca107fde4c98b61d85f6648f30c7601b31c7f3",
"index": 3182,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n SECRET_KEY\nexcept NameError:\n SECRET_FILE = os.path.join(BASE_DIR, 'secret.txt')\n try:\n SECRET_KEY = open(SECRET_FILE).read().strip()\n except IOError:\n ... | [
0,
1,
2,
3,
4
] |
from snake.snake import Snake
# Start application
if __name__ == '__main__':
s = Snake()
s.run() | normal | {
"blob_id": "efed5c113e085e5b41d9169901c18c06111b9077",
"index": 8894,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n s = Snake()\n s.run()\n",
"step-3": "from snake.snake import Snake\nif __name__ == '__main__':\n s = Snake()\n s.run()\n",
"step-4": "from sna... | [
0,
1,
2,
3
] |
n=int(input("Enter any int number:\n"))
x=1
while(x<13):
print(n ," x ", x ," = ", n*x)
x=x+1
| normal | {
"blob_id": "a6c07146f1cbc766cd464dab620d1fb075759c12",
"index": 4213,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile x < 13:\n print(n, ' x ', x, ' = ', n * x)\n x = x + 1\n",
"step-3": "n = int(input('Enter any int number:\\n'))\nx = 1\nwhile x < 13:\n print(n, ' x ', x, ' = ', n * x)\... | [
0,
1,
2,
3
] |
from pyloom import *
import random
import string
alphabet = string.ascii_letters
def random_string(N):
return ''.join([random.choice(alphabet) for _ in range(N)])
class TestBloomFilter(object):
def test_setup(self):
bf = BloomFilter(1000)
assert 10 == bf._num_hashes
assert 14380 ==... | normal | {
"blob_id": "24e486edc6f80e0b7d58b5df898e6d34f53111c8",
"index": 4389,
"step-1": "<mask token>\n\n\nclass TestBloomFilter(object):\n\n def test_setup(self):\n bf = BloomFilter(1000)\n assert 10 == bf._num_hashes\n assert 14380 == bf._num_bits\n assert 14380 == len(bf._bitarray)\n ... | [
5,
6,
7,
8,
9
] |
# Filename : var.py
#整数
i = 5
print(i)
i = i + 1
print(i)
#浮点数
i = 1.1
print(i)
#python的弱语言特性，可以随时改变变量的类型
i = 'change i to a string '
print(i)
s = 'hello'#单引号
print(s)
s = "hello"#双引号
print(s)
#三引号为多行字符串
s = '''This is a "multi-line" string.
This is the second line.'''
print(s)
s = '\''#斜杠用于转义
print(s)
#r或R开头的字符... | normal | {
"blob_id": "bea7853d1f3eac50825bc6eb10438f3f656d6d04",
"index": 1947,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(i)\n<mask token>\nprint(i)\n<mask token>\nprint(i)\n<mask token>\nprint(i)\n<mask token>\nprint(s)\n<mask token>\nprint(s)\n<mask token>\nprint(s)\n<mask token>\nprint(s)\n<mask tok... | [
0,
1,
2,
3
] |
import tornado.httpserver
import tornado.websocket
import tornado.ioloop
import tornado.web
import tornado.options
import serial
import time
from datetime import timedelta
import cv2
import time
from datetime import datetime
#for webcam users
camera=cv2.VideoCapture(0)
#for picam users
#import picam
#camera=picam.Op... | normal | {
"blob_id": "1e9afe6435285da6c6efb678177587d7ba5a01b2",
"index": 1397,
"step-1": "import tornado.httpserver\nimport tornado.websocket\nimport tornado.ioloop\nimport tornado.web\nimport tornado.options\nimport serial\nimport time\nfrom datetime import timedelta\nimport cv2\nimport time\nfrom datetime import datet... | [
0
] |
import ga.ga as ga
import os
import datetime
def ga_optimise(synth, param_count, target, output_dir, iterations = 10, pop_size = 500):
fs = ga.ga_optimise(compute_population_fitnesses = ga.compute_population_fitnesses,
target = target,
synth = synth,
param_count = param_count,
iterations = iterat... | normal | {
"blob_id": "4bc9896847e4ab92a01dfcf674362140cc31ef4f",
"index": 5587,
"step-1": "import ga.ga as ga\nimport os\nimport datetime\n\n\ndef ga_optimise(synth, param_count, target, output_dir, iterations = 10, pop_size = 500):\n\tfs = ga.ga_optimise(compute_population_fitnesses = ga.compute_population_fitnesses, \n... | [
0
] |
import pickle
import numpy as np
import math
class AdaBoostClassifier:
'''A simple AdaBoost Classifier.'''
def __init__(self, weak_classifier, n_weakers_limit):
'''Initialize AdaBoostClassifier
Args:
weak_classifier: The class of weak classifier, which is recommend to be sklearn.t... | normal | {
"blob_id": "905d8be76ef245a2b8fcfb3f806f8922d351ecf0",
"index": 8877,
"step-1": "<mask token>\n\n\nclass AdaBoostClassifier:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def predict(self, X, threshold=0):\n \"\"\"Predict the catagories... | [
3,
7,
8,
9,
12
] |
from sklearn.model_selection import train_test_split
from azureml.core import Run
from sklearn.ensemble import RandomForestClassifier
import pandas as pd
import argparse
import os
import joblib
import numpy as np
# Get the experiment run context
run = Run.get_context()
# Get arguments
parser = argparse.ArgumentParse... | normal | {
"blob_id": "66c2d73c100f7fc802e66f2762c92664e4b93fcd",
"index": 5736,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.add_argument('--in_n_estimator', type=int, default=8)\nparser.add_argument('--in_criterion', type=str, default='gini')\nparser.add_argument('--in_max_depth', type=int, default=2)\n... | [
0,
1,
2,
3,
4
] |
import os
from xml.dom import minidom
import numpy as np
def get_branches_dir(root_dir):
branches_dir = []
folds = os.listdir(root_dir)
while folds:
branch_dir = root_dir + '/' + folds.pop()
branches_dir.append(branch_dir)
return branches_dir
def tolist(xml, detname):
try:
... | normal | {
"blob_id": "2b7bb02a25504e7481d3bc637ea09bcf9addb990",
"index": 7699,
"step-1": "<mask token>\n\n\ndef get_branches_dir(root_dir):\n branches_dir = []\n folds = os.listdir(root_dir)\n while folds:\n branch_dir = root_dir + '/' + folds.pop()\n branches_dir.append(branch_dir)\n return br... | [
2,
3,
4,
5,
6
] |
from collections.abc import Iterator
import json
import click
def print_json(obj, err=False):
if isinstance(obj, Iterator):
obj = list(obj)
click.echo(json.dumps(obj, sort_keys=True, indent=4, ensure_ascii=False),
err=err)
def show_fields(*fields):
def show(obj, verbose=False):
... | normal | {
"blob_id": "d340ac979f57cf4650131665e4fa5b9923f22a3e",
"index": 6691,
"step-1": "<mask token>\n\n\ndef print_json(obj, err=False):\n if isinstance(obj, Iterator):\n obj = list(obj)\n click.echo(json.dumps(obj, sort_keys=True, indent=4, ensure_ascii=False\n ), err=err)\n\n\n<mask token>\n",
... | [
1,
2,
3,
4,
5
] |
REDIRECT_MAP = {
'90':'19904201',
'91':'19903329',
'92':'19899125',
'93':'19901043',
'94':'19903192',
'95':'19899788',
'97':'19904423',
'98':'19906163',
'99':'19905540',
'100':'19907871',
'101':'19908147',
'102':'19910103',
'103':'19909980',
'104':'19911813',
... | normal | {
"blob_id": "fb92912e1a752f3766f9439f75ca28379e23823f",
"index": 3600,
"step-1": "<mask token>\n",
"step-2": "REDIRECT_MAP = {'90': '19904201', '91': '19903329', '92': '19899125', '93':\n '19901043', '94': '19903192', '95': '19899788', '97': '19904423', '98':\n '19906163', '99': '19905540', '100': '19907... | [
0,
1,
2
] |
from extras.plugins import PluginTemplateExtension
from .models import BGPSession
from .tables import BGPSessionTable
class DeviceBGPSession(PluginTemplateExtension):
model = 'dcim.device'
def left_page(self):
if self.context['config'].get('device_ext_page') == 'left':
return self.x_page(... | normal | {
"blob_id": "be566041402dc1705aa9d644edc44de8792fbb3c",
"index": 4850,
"step-1": "<mask token>\n\n\nclass DeviceBGPSession(PluginTemplateExtension):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass DeviceBGPSessio... | [
1,
4,
7,
8
] |
def fib(limit):
a, b = 0, 1
yield a
yield b
while b < limit:
a, b = b, a + b
yield b
print sum(x for x in fib(4000000) if not x % 2) # 4613732
| normal | {
"blob_id": "1c7635917e398c30e4a232f76b2c02a51e165a63",
"index": 4147,
"step-1": "def fib(limit):\n a, b = 0, 1\n yield a\n yield b\n while b < limit:\n a, b = b, a + b\n yield b\n\n\nprint sum(x for x in fib(4000000) if not x % 2) # 4613732\n",
"step-2": null,
"step-3": null,
"s... | [
0
] |
import xadmin
from xadmin import views
from .models import EmailVerifyRecord, Banner
class BaseMyAdminView(object):
'''
enable_themes 启动更改主题
use_bootswatch 启用网上主题
'''
enable_themes = True
use_bootswatch = True
class GlobalSettings(object):
'''
site_title 左上角名称
site_footer 底部名称
... | normal | {
"blob_id": "d7b830890400203ee45c9ec59611c0b20ab6bfc7",
"index": 8496,
"step-1": "<mask token>\n\n\nclass BaseMyAdminView(object):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass GlobalSettings(object):\n \"\"\"\n site_title 左上角名称\n site_footer 底部名称\n menu_style 更改左边样式\n \"\"\"\n ... | [
8,
10,
11,
12,
13
] |
from random import choice, random, randrange
from math import fsum
import os
import numpy as np
def mat17(N, ATOM_TYPES, ndenmax=0.04302, ndenmin=0.0000013905, xmax=51.2, xmin=25.6, ymax=51.2, ymin=25.6,
zmax=51.2, zmin=25.6, epmax=513.264, epmin=1.2580, sigmax=6.549291, sigmin=1.052342, qmax=0.0, qmin=0.0):
#epmax DE... | normal | {
"blob_id": "ba72af921a9562d748bcd65f1837ea8eb5da5697",
"index": 150,
"step-1": "from random import choice, random, randrange\nfrom math import fsum\nimport os\nimport numpy as np\n\ndef mat17(N, ATOM_TYPES, ndenmax=0.04302, ndenmin=0.0000013905, xmax=51.2, xmin=25.6, ymax=51.2, ymin=25.6,\nzmax=51.2, zmin=25.6,... | [
0
] |
from django.contrib import admin
# Register your models here.
from registration.models import FbAuth
class AllFieldsAdmin(admin.ModelAdmin):
"""
A model admin that displays all field in admin excpet Many to many and pk field
"""
def __init__(self, model, admin_site):
self.list_display = [fi... | normal | {
"blob_id": "821afa85eb783b4bf1018800f598a3294c4cbcfb",
"index": 9532,
"step-1": "<mask token>\n\n\nclass AllFieldsAdmin(admin.ModelAdmin):\n <mask token>\n\n def __init__(self, model, admin_site):\n self.list_display = [field.name for field in model._meta.fields if \n field.name not in [... | [
2,
3,
4,
5,
6
] |
from csv import reader, writer
from collections import OrderedDict as OrdDic
import sqlite3
from jsmin import jsmin
from glob import glob
from csscompressor import compress
from threading import Timer
from glob import glob
import os
import shutil
import logging
import json
class MinifyFilesPre:
def __init__(self, ... | normal | {
"blob_id": "38bd9e5b2147838b6061925d72b989c83343f1c2",
"index": 9800,
"step-1": "<mask token>\n\n\nclass DbManager:\n\n def __init__(self, fname=None, tname=None):\n if fname:\n self.FILE_NAME = fname\n else:\n self.FILE_NAME = 'resources/static/LOG_Temp.db'\n if tn... | [
31,
37,
39,
44,
50
] |
import numpy as np
import h5py
def rotate_z(theta, x):
theta = np.expand_dims(theta, 1)
outz = np.expand_dims(x[:, :, 2], 2)
sin_t = np.sin(theta)
cos_t = np.cos(theta)
xx = np.expand_dims(x[:, :, 0], 2)
yy = np.expand_dims(x[:, :, 1], 2)
outx = cos_t * xx - sin_t * yy
outy = sin_t * x... | normal | {
"blob_id": "855bfc9420a5d5031cc673231cc7993ac67df076",
"index": 5515,
"step-1": "<mask token>\n\n\nclass ModelFetcher(object):\n <mask token>\n\n def train_data(self):\n rng_state = np.random.get_state()\n np.random.shuffle(self._train_data)\n np.random.set_state(rng_state)\n n... | [
3,
6,
8,
10,
11
] |
import requests
response = requests.get(
'https://any-api.com:8443/https://rbaskets.in/api/version')
print(response.text)
| normal | {
"blob_id": "ab36b3d418be67080e2efaba15edc1354386e191",
"index": 6888,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(response.text)\n",
"step-3": "<mask token>\nresponse = requests.get(\n 'https://any-api.com:8443/https://rbaskets.in/api/version')\nprint(response.text)\n",
"step-4": "import... | [
0,
1,
2,
3
] |
"""
Version information for NetworkX, created during installation.
Do not add this file to the repository.
"""
import datetime
version = '2.3'
date = 'Thu Apr 11 20:57:18 2019'
# Was NetworkX built from a development version? If so, remember that the major
# and minor versions reference the "target" (rather than "... | normal | {
"blob_id": "814191a577db279389975e5a02e72cd817254275",
"index": 9444,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nversion = '2.3'\ndate = 'Thu Apr 11 20:57:18 2019'\ndev = False\nversion_info = 'networkx', '2', '3', None\ndate_info = datetime.datetime(2019, 4, 11, 20, 57, 18)\nvcs_info = None, (None,... | [
0,
1,
2,
3
] |
from migen import *
from migen.fhdl import verilog
class Alignment_Corrector(Module):
def __init__(self):
self.din=din=Signal(32)
self.aligned=aligned=Signal()
self.dout=dout=Signal(32)
self.correction_done=Signal()
# # #
first_half=Signal(16)
first_half1=Signal(16)
second_half=Signal(16)
self.submo... | normal | {
"blob_id": "f3eed00a58491f36778b3a710d2f46be093d6eda",
"index": 6320,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Alignment_Corrector(Module):\n <mask token>\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass Alignment_Corrector(Module):\n\n def __init__(self):\n self.d... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
import requests
import json
import boto3
from lxml.html import parse
CardTitlePrefix = "Greeting"
def build_speechlet_response(title, output, reprompt_text, should_end_session):
"""
Build a speechlet JSON representation of the title, output text,
reprompt text & end of session
... | normal | {
"blob_id": "237277e132c8223c6048be9b754516635ab720e2",
"index": 8964,
"step-1": "<mask token>\n\n\ndef build_response(session_attributes, speechlet_response):\n \"\"\"\n Build the full response JSON from the speechlet response\n \"\"\"\n return {'version': '1.0', 'sessionAttributes': session_attribu... | [
8,
11,
13,
14,
15
] |
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