code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
from django.db import models
# Create your models here.
STATUS_CHOICES=(
('Pending','Pending'),
('Completed','Completed'))
class Appointment(models.Model):
first_name=models.CharField(max_length=100)
last_name=models.CharField(max_length=100)
phone_number=models.CharField(max_length=12,null=False... | normal | {
"blob_id": "3343844bf49cb3f4d655613475e44a140ac3106d",
"index": 4505,
"step-1": "<mask token>\n\n\nclass Appointment(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __str__(self):\n return self.first_n... | [
2,
3,
4,
5,
6
] |
c_horas=int(input("Ingrese la cantidad de horas trabajadas:"))
v_horas=int(input("Ingrese el valor de cada hora trabajada:"))
sueldo=c_horas*v_horas
print("Su sueldo mensual sera")
print(sueldo)
| normal | {
"blob_id": "2e4b47b8c3ac4f187b32f1013a34c3bea354b519",
"index": 6817,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Su sueldo mensual sera')\nprint(sueldo)\n",
"step-3": "c_horas = int(input('Ingrese la cantidad de horas trabajadas:'))\nv_horas = int(input('Ingrese el valor de cada hora trabaj... | [
0,
1,
2,
3
] |
class Solution:
def containsDuplicate(self, nums) -> bool:
d = {} # store the elements which already exist
for elem in nums:
if elem in d:
return True
else:
d[elem] = 1
return False
print(Solution().containsDuplicate([0])) | normal | {
"blob_id": "89256a38208be92f87115b110edc986cebc95306",
"index": 8440,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n\n\n<mask token>\n",
"step-3": "class Solution:\n\n def containsDuplicate(self, nums) ->bool:\n d = {}\n for elem in nums:\n if elem in ... | [
0,
1,
2,
3,
4
] |
file_id = '0BwwA4oUTeiV1UVNwOHItT0xfa2M'
request = drive_service.files().get_media(fileId=file_id)
fh = io.BytesIO()
downloader = MediaIoBaseDownload(fh, request)
done = False
while done is False:
status, done = downloader.next_chunk()
print "Download %d%%." % int(status.progress() * 100)
| normal | {
"blob_id": "6b3f634f3f0108e678d44ef9c89150f9fd116f76",
"index": 9471,
"step-1": "file_id = '0BwwA4oUTeiV1UVNwOHItT0xfa2M'\nrequest = drive_service.files().get_media(fileId=file_id)\nfh = io.BytesIO()\ndownloader = MediaIoBaseDownload(fh, request)\ndone = False\nwhile done is False:\n status, done = downloade... | [
0
] |
import os
bind = '0.0.0.0:8000'
workers = os.environ['GET_KEYS_ACCOUNTS_WORKERS']
| normal | {
"blob_id": "d84a7e16471c604283c81412653e037ecdb19102",
"index": 3530,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nbind = '0.0.0.0:8000'\nworkers = os.environ['GET_KEYS_ACCOUNTS_WORKERS']\n",
"step-3": "import os\nbind = '0.0.0.0:8000'\nworkers = os.environ['GET_KEYS_ACCOUNTS_WORKERS']\n",
"step-4... | [
0,
1,
2
] |
#!/usr/bin/env python3
from aws_cdk import core
import os
from ec2_ialb_aga_custom_r53.network_stack import NetworkingStack
from ec2_ialb_aga_custom_r53.aga_stack import AgaStack
from ec2_ialb_aga_custom_r53.alb_stack import ALBStack
from ec2_ialb_aga_custom_r53.certs_stack import CertsStack
from ec2_ialb_aga_custom_... | normal | {
"blob_id": "2f96e58a825744ae6baafd1bfb936210500f0fd0",
"index": 6334,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nec2.add_dependency(net)\n<mask token>\nalb.add_dependency(net)\nalb.add_dependency(ec2)\nalb.add_dependency(cert)\n<mask token>\naga.add_dependency(net)\naga.add_dependency(cert)\naga.add... | [
0,
1,
2,
3,
4
] |
from const import BORN_KEY, PRESIDENT_KEY, CAPITAL_KEY, PRIME_KEY, MINISTER_KEY, POPULATION_KEY, \
GOVERNMENT_KEY,AREA_KEY, WHO_KEY, IS_KEY, THE_KEY, OF_KEY, WHAT_KEY, WHEN_KEY, WAS_KEY
from geq_queries import capital_of_country_query, area_of_country_query, government_of_country_query, \
population_of_country... | normal | {
"blob_id": "18dce1ce683b15201dbb5436cbd4288a0df99c28",
"index": 938,
"step-1": "<mask token>\n\n\ndef get_last_argument(words):\n return ' '.join(words)[:-1]\n\n\n<mask token>\n\n\ndef parse_what_is_the(words):\n question_number = None\n arg = None\n if words[3] == POPULATION_KEY:\n question_... | [
5,
6,
7,
8,
9
] |
def favorite_book(name):
print(f"One of my favorite books is {name}...")
favorite_book("Alice in Wonderland")
| normal | {
"blob_id": "08848e51d5564bad927607be3fa3c86f2c1212c5",
"index": 9668,
"step-1": "<mask token>\n",
"step-2": "def favorite_book(name):\n print(f'One of my favorite books is {name}...')\n\n\n<mask token>\n",
"step-3": "def favorite_book(name):\n print(f'One of my favorite books is {name}...')\n\n\nfavor... | [
0,
1,
2,
3
] |
x = '我是一个字符串'
y = "我也是一个字符串"
z = """我还是一个字符串"""
#字符串str用单引号(' ')或双引号(" ")括起来
#使用反斜杠(\)转义特殊字符。
s = 'Yes,he doesn\'t'
#如果你不想让反斜杠发生转义，
#可以在字符串前面添加一个r，表示原始字符串
print('C:\some\name')
print('C:\\some\\name')
print(r'C:\some\name')
#反斜杠可以作为续行符，表示下一行是上一行的延续。
s = "abcd\
efg"
print(s)
#还可以使用"""...""... | normal | {
"blob_id": "8fe9d21bb65b795a6633ab390f7f5d24a90146d5",
"index": 6774,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('C:\\\\some\\name')\nprint('C:\\\\some\\\\name')\nprint('C:\\\\some\\\\name')\n<mask token>\nprint(s)\n<mask token>\nprint(s)\n",
"step-3": "x = '我是一个字符串'\ny = '我也是一个字符串'\nz = '我还... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
"""
Script to download and plot RaspberryShake station data
Also computes and plots theoretical phase arrival times and raypaths.
See https://docs.obspy.org/packages/obspy.taup.html for more info on
Earth models and phase-nmaing nomenclature.
Stephen Hicks
Imperial College London
Feb 2020
"""
... | normal | {
"blob_id": "8d8ea6ad7a3ed1a1e6e96ab75260ecf6e8211d32",
"index": 1305,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nst.merge()\nst.detrend(type='demean')\nst.remove_response()\nst.filter('bandpass', freqmin=F1, freqmax=F2, corners=4)\nst.trim(t1, t2)\n<mask token>\nplt.suptitle(LABEL)\n<mask token>\nax... | [
0,
1,
2,
3,
4
] |
'''
Created on 18/10/2012
@author: matthias
'''
import os
import errno
import uuid
import glob
import shutil
import sys
import subprocess
import time
import pickle
import common.pbs
def prepare_directories(options, extension, subversiondir=None):
# extract datadir from options
datadir = options['datadir']
... | normal | {
"blob_id": "6aeaa2ed01e0c0dac54cd8220c5da005fccc53e9",
"index": 2609,
"step-1": "<mask token>\n\n\ndef prepare_directories(options, extension, subversiondir=None):\n datadir = options['datadir']\n print('Creating directory {0:s}.'.format(datadir + extension))\n try:\n os.makedirs(datadir + exten... | [
1,
2,
3,
4,
5
] |
import pytesseract
from PIL import Image
img = Image.open("flag.png")
text = pytesseract.image_to_string(img)
def rot(*symbols):
def _rot(n):
encoded = ''.join(sy[n:] + sy[:n] for sy in symbols)
lookup = str.maketrans(''.join(symbols), encoded)
return lambda s: s.translate(lookup)
re... | normal | {
"blob_id": "b7a60322b4a0fcb6de16cd12be33db265a2b8746",
"index": 2735,
"step-1": "<mask token>\n\n\ndef rot(*symbols):\n\n def _rot(n):\n encoded = ''.join(sy[n:] + sy[:n] for sy in symbols)\n lookup = str.maketrans(''.join(symbols), encoded)\n return lambda s: s.translate(lookup)\n re... | [
1,
4,
5,
6,
7
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 25 18:40:07 2021
@author: tomachache
"""
import numpy as np
from qiskit import *
# Various state preparation
def state_preparation(m, name, p):
# m : nb of qubits
# name : name of the state we want
# p : proba associated with nois... | normal | {
"blob_id": "6962bf99e3ecae473af54ded33fde09527cb82c0",
"index": 8284,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef state_preparation(m, name, p):\n circ = QuantumCircuit(m, name='State prep')\n if name == 'GHZ':\n circ.h(0)\n for k in range(1, m):\n circ.cx(0, k)... | [
0,
1,
2,
3
] |
import numpy as np
import math
a = [
[0.54, -0.04, 0.10],
[-0.04, 0.50, 0.12],
[0.10, 0.12, 0.71]
]
b = [0.33, -0.05, 0.28]
# Метод Гаусса
def gauss(left, right, prec=3):
# Создаем расширенную матрицу
arr = np.concatenate((np.array(left), np.array([right]).T), axis=1)
print('\nИсходная матриц... | normal | {
"blob_id": "bd0530b6f3f7b1a5d72a5b11803d5bb82f85105d",
"index": 6587,
"step-1": "<mask token>\n\n\ndef gauss(left, right, prec=3):\n arr = np.concatenate((np.array(left), np.array([right]).T), axis=1)\n print('\\nИсходная матрица:')\n print(arr)\n if np.linalg.matrix_rank(left) != np.linalg.matrix_r... | [
4,
6,
7,
9,
10
] |
import arcade
import os
SPRITE_SCALING = 0.5
SCREEN_WIDTH = 800
SCREEN_HEIGHT = 600
SCREEN_TITLE = "Raymond Game"
MOVEMENT_SPEED = 50
class Ball:
def __init__(self, position_x, position_y, change_x, change_y, radius):
# Take the parameters of the init function above, and create instance variables ou... | normal | {
"blob_id": "37d079ca6a22036e2660507f37442617d4842c4e",
"index": 4060,
"step-1": "<mask token>\n\n\nclass MyGame(arcade.Window):\n\n def __init__(self, width, height, title):\n super().__init__(width, height, title)\n self.drawer = 0\n self.wardrobe = 0\n self.bookshelves = 0\n ... | [
6,
8,
12,
13,
15
] |
from enum import Enum
class CellState(Enum):
EMPTY = 1
DEAD = 2
ALIVE = 3
WAS_ALIVE = 4
def __str__(self):
default_str = super(CellState, self).__str__()
if default_str == "CellState.EMPTY":
return "E"
elif default_str == "CellState.DEAD":
return "D"
elif default_str... | normal | {
"blob_id": "29bee4ef11281380aa05d22ef54cb76502ecd685",
"index": 466,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass CellState(Enum):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __str__(self):\n default_str = super(CellState, self).__str__()\n ... | [
0,
2,
3,
4,
5
] |
from unittest import TestCase
from tests import AuthHelperTestCase
class TestTestHelper(TestCase):
"""
Test our helper functions
"""
def test_assertAnyIn_fails(self):
"""
Make sure assertInAny fails correctly
:return:
"""
test_case = AuthHelperTestCase('asser... | normal | {
"blob_id": "ae1aab7563443db3a31fe98b5b26b32944d57c9d",
"index": 1473,
"step-1": "<mask token>\n\n\nclass TestTestHelper(TestCase):\n <mask token>\n <mask token>\n\n def test_assertAnyIn_suceeds(self):\n \"\"\"\n Make sure assertInAny succeeds\n \n :return: \n \"\"\"\n... | [
2,
3,
4,
5
] |
'''
held-karp.py
Implementation of the Bellman-Held-Karp Algorithm to exactly solve TSPs,
requiring no external dependencies.
Includes a purely recursive implementation, as well as both top-down and
bottom-up dynamic programming approaches.
'''
import sys
def held_karp_recursive(distance_matrix):
'''
Soluti... | normal | {
"blob_id": "3e8fa71c4e23348c6f00fe97729b5717bb6245a1",
"index": 8070,
"step-1": "<mask token>\n\n\ndef held_karp_bottomup(distance_matrix):\n \"\"\"\n In the bottom up implementation, we compute all possible solutions for the\n values `i` and `visited` as in the implementations above, and then\n sim... | [
5,
8,
9,
10,
12
] |
import pandas as pd
import numpy as np
#I'm adding these too avoid any type of na value.
missing_values = ["n/a", "na", "--", " ?","?"]
# Name Data Type Meas. Description
# ---- --------- ----- -----------
# Sex nominal M, F, and I (infant)
# Length continuous mm Longest shell measurement
# Diameter con... | normal | {
"blob_id": "1b773f2ca01f07d78d2d7edc74cd2df6630aa97a",
"index": 4968,
"step-1": "<mask token>\n\n\ndef tt(X, y, sample):\n X_train, X_valid, y_train, y_valid = train_test_split(X, y, train_size=\n sample, random_state=1)\n return {'X_train': X_train, 'X_valid': X_valid, 'y_train': y_train,\n ... | [
1,
2,
3,
4,
5
] |
# from dataclasses import InitVar, dataclass
# standard library imports
from math import floor
# third-party imports
import gym
import torch
from torch.nn import Conv2d, Linear, MaxPool2d, Module, ModuleList, ReLU, Sequential
from torch.nn import functional as F
# local imports
from tmrl.nn import TanhNormalLayer
fro... | normal | {
"blob_id": "6f6d3fbb9a6a118e0f4026a7f9054b90b8cf2fca",
"index": 5677,
"step-1": "<mask token>\n\n\nclass BigCNN(Module):\n\n def __init__(self, h_in, w_in, channels_in):\n super(BigCNN, self).__init__()\n self.h_out, self.w_out = h_in, w_in\n self.conv1 = Conv2d(channels_in, 64, 8, strid... | [
14,
16,
19,
22,
24
] |
#!/usr/bin/python2.7
# -*- coding: utf-8 -*-
"""
# @Time : 20-6-9 上午11:47
# @Author : zhufa
# @Software: PyCharm
"""
"""
tensorflow version must below 1.15
"""
import numpy as np
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", ... | normal | {
"blob_id": "779e7cd05edfd74c8e60eaf5ce8443aea5fdaaef",
"index": 8028,
"step-1": "#!/usr/bin/python2.7\n# -*- coding: utf-8 -*-\n\n\"\"\"\n# @Time : 20-6-9 上午11:47\n\n# @Author : zhufa\n\n# @Software: PyCharm\n\"\"\"\n\"\"\"\ntensorflow version must below 1.15\n\"\"\"\n\nimport numpy as np\nimport tensorflow... | [
0
] |
cars=100
drivers=30
passengers=70
print "There are",cars,"cars available."
print "There are only",drivers,"drivers available."
print "Each driver needs to drive",passengers/drivers-1,"passengers."
| normal | {
"blob_id": "b1a1287c2c3b624eb02f2955760f6e9eca8cdcf9",
"index": 1241,
"step-1": "cars=100\ndrivers=30\npassengers=70\nprint \"There are\",cars,\"cars available.\"\nprint \"There are only\",drivers,\"drivers available.\"\nprint \"Each driver needs to drive\",passengers/drivers-1,\"passengers.\"\n",
"step-2": n... | [
0
] |
import sys
V, E = map(int, sys.stdin.readline().split())
node = []
graphs = []
for i in range(V+1):
node.append(i)
for _ in range(E):
graphs.append((list(map(int, sys.stdin.readline().split()))))
graph = sorted(graphs, key=lambda x: x[2])
def get_parent(parent, x):
if parent[x] == x:
return x
... | normal | {
"blob_id": "2e794e281c6f34858cd32725cdc454eb18c28892",
"index": 3415,
"step-1": "<mask token>\n\n\ndef get_parent(parent, x):\n if parent[x] == x:\n return x\n parent[x] = get_parent(parent, parent[x])\n return parent[x]\n\n\ndef union_parent(parent, a, b):\n a = get_parent(parent, a)\n b ... | [
2,
3,
4,
5,
6
] |
#https://www.acmicpc.net/problem/2581
def isPrime(x):
if x==1:
return False
for d in range(1,int(x**0.5)):
if x==d+1:
continue
if x%(d+1)==0:
return False
else:
return True
N=int(input())
M=int(input())
sum=0
min=10001
for x in range(N,M+1):
if i... | normal | {
"blob_id": "37d465043eddd34c4453fd7e31b08d0ba58b725f",
"index": 4351,
"step-1": "<mask token>\n",
"step-2": "def isPrime(x):\n if x == 1:\n return False\n for d in range(1, int(x ** 0.5)):\n if x == d + 1:\n continue\n if x % (d + 1) == 0:\n return False\n e... | [
0,
1,
2,
3,
4
] |
import uuid
from aliyunsdkcore.client import AcsClient
from aliyunsdkcore.profile import region_provider
# 注意：不要更改
from celery_tasks.sms.dysms_python.build.lib.aliyunsdkdysmsapi.request.v20170525 import SendSmsRequest
class SendMes(object):
REGION = "cn-hangzhou"
PRODUCT_NAME = "Dysmsapi"
DOMAIN = "dysmsapi.aliy... | normal | {
"blob_id": "daecbf5280c199b31f3b9d9818df245d9cd165a7",
"index": 4295,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass SendMes(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n region_provider.add_endpoint(PRODUCT_NAME, REGI... | [
0,
1,
3,
4,
5
] |
#case1
print("My name is Jia-Chi. \nI have an older sister. \nI prefer Coke.\nMy favorite song is \"Amazing Grace\"")
#case2
print('''Liang, Jia-Chi
1
Coke
Amazing Grace''')
| normal | {
"blob_id": "55986f6c2dafe650704660142cf85640e763b26d",
"index": 3291,
"step-1": "<mask token>\n",
"step-2": "print(\n \"\"\"My name is Jia-Chi. \nI have an older sister. \nI prefer Coke.\nMy favorite song is \"Amazing Grace\\\"\"\"\"\n )\nprint(\"\"\"Liang, Jia-Chi\n1\nCoke\nAmazing Grace\"\"\")\n",
"... | [
0,
1,
2
] |
# https://github.com/openai/gym/blob/master/gym/envs/__init__.py#L449
import gym
import numpy as np
from rl_main.conf.names import EnvironmentName, DeepLearningModelName
from rl_main.environments.environment import Environment
from rl_main.main_constants import DEEP_LEARNING_MODEL
class BreakoutDeterministic_v4(Envi... | normal | {
"blob_id": "05e57ed95427f0de74ea5b0589c5cd56e4a96f73",
"index": 8776,
"step-1": "<mask token>\n\n\nclass BreakoutDeterministic_v4(Environment):\n\n def __init__(self):\n self.env = gym.make(EnvironmentName.BREAKOUT_DETERMINISTIC_V4.value)\n super(BreakoutDeterministic_v4, self).__init__()\n ... | [
9,
11,
16,
17,
18
] |
from LAMARCK_ML.data_util import ProtoSerializable
class NEADone(Exception):
pass
class NoSelectionMethod(Exception):
pass
class NoMetric(Exception):
pass
class NoReproductionMethod(Exception):
pass
class NoReplaceMethod(Exception):
pass
class ModelInterface(ProtoSerializable):
def reset(self):
... | normal | {
"blob_id": "501b8a9307a1fd65a5f36029f4df59bbe11d881a",
"index": 6591,
"step-1": "<mask token>\n\n\nclass ModelInterface(ProtoSerializable):\n\n def reset(self):\n raise NotImplementedError()\n pass\n\n def run(self):\n raise NotImplementedError()\n\n def stop(self):\n raise ... | [
9,
10,
13,
14,
16
] |
from manimlib.imports import *
import math
class A_Swerve(Scene):
def construct(self):
chassis = Square(side_length=2, stroke_width=0, fill_color=GRAY, fill_opacity=1).shift(2*RIGHT)
fr = Dot().shift(UP+3*RIGHT)
fl = Dot().shift(UP+RIGHT)
rl = Dot().shift(DOWN+RIGHT)
rr = Dot().shift(DOWN+3*RIGH... | normal | {
"blob_id": "bdde3a3725510d4a83b09421e4b8538a38e29584",
"index": 8196,
"step-1": "<mask token>\n\n\nclass A_Swerve(Scene):\n\n def construct(self):\n chassis = Square(side_length=2, stroke_width=0, fill_color=GRAY,\n fill_opacity=1).shift(2 * RIGHT)\n fr = Dot().shift(UP + 3 * RIGHT)\... | [
2,
3,
4,
5,
6
] |
import os
import time
from datetime import datetime, timedelta
from git import Repo
class CommitAnalyzer():
"""
Takes path of the repo
"""
def __init__(self, repo_path):
self.repo_path = repo_path
self.repo = Repo(self.repo_path)
assert not self.repo.bare
def get_conflict_commits(self):
conflict_commits... | normal | {
"blob_id": "8479c70fed36dc6f1e6094c832fb22d8c2e53e3a",
"index": 920,
"step-1": "<mask token>\n\n\nclass CommitAnalyzer:\n <mask token>\n\n def __init__(self, repo_path):\n self.repo_path = repo_path\n self.repo = Repo(self.repo_path)\n assert not self.repo.bare\n <mask token>\n\n\n... | [
2,
5,
6,
7,
8
] |
alien_0 = {} # 声明一个空字典
alien_0['color'] = 'green' # 向空字典中添加值
alien_0['points'] = 5
print(alien_0)
x = alien_0['color']
print(f"\nThe alien is {alien_0['color']}") # 引号的用法
alien_0['color'] = 'yellow' # 对字典中的元素重新赋值
print(f"The alien is now {alien_0['color']}")
| normal | {
"blob_id": "f4dd9500835cb22a859da8bd57487052522bb593",
"index": 7697,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(alien_0)\n<mask token>\nprint(f\"\"\"\nThe alien is {alien_0['color']}\"\"\")\n<mask token>\nprint(f\"The alien is now {alien_0['color']}\")\n",
"step-3": "alien_0 = {}\nalien_0['... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
'''
:Title
Insert Date
:Planguage
Python
:Requires
VoodooPad 3.5+
:Description
Inserts Date
EOD
'''
VPScriptSuperMenuTitle = "GTD"
VPScriptMenuTitle = "Insert Date"
VPShortcutMask = "control"
VPShortcutKey = "J"
import AppKit
import time
def main(windowController, *args, **kwargs):
te... | normal | {
"blob_id": "e51ca78ca6751f8238a39d3eae55d6cc6ab65128",
"index": 5797,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main(windowController, *args, **kwargs):\n textView = windowController.textView()\n document = windowController.document()\n if textView != None:\n dateFormat = ti... | [
0,
1,
2,
3,
4
] |
import numpy as np
from nn.feedforward_nn import Feed_Forward
class RMSprop(object):
def __init__(self,n_in,n_hid,n_out,regularization_coe):
self.nn = Feed_Forward(n_in,n_hid,n_out,regularization_coe)
def set_param(self,param):
if 'learning_rate' in param.keys():
self.learning_rat... | normal | {
"blob_id": "f971302f39149bcdcbe4237cc71219572db600d4",
"index": 8720,
"step-1": "<mask token>\n\n\nclass RMSprop(object):\n\n def __init__(self, n_in, n_hid, n_out, regularization_coe):\n self.nn = Feed_Forward(n_in, n_hid, n_out, regularization_coe)\n <mask token>\n <mask token>\n <mask toke... | [
2,
4,
5,
6,
7
] |
import math
import datetime
import numpy as np
import matplotlib.pyplot as plt
def draw_chat(
id, smooth_id, main_mode,
my_name, chat_day_data,
main_plot, pie_plot, list_chats_plot):
min_in_day = 1440
possible_smooth = [1, 2, 3, 4, 5, 6, 8, 9, 10, 12, 15, 16, 18, 20, 24, 30, 32, 36, 40, 45, 48, ... | normal | {
"blob_id": "b297a09ee19bb8069eb65eb085903b3219c6fe5a",
"index": 7971,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef draw_chat(id, smooth_id, main_mode, my_name, chat_day_data, main_plot,\n pie_plot, list_chats_plot):\n min_in_day = 1440\n possible_smooth = [1, 2, 3, 4, 5, 6, 8, 9, 10, ... | [
0,
1,
2,
3
] |
#公路工程工程量清单编码默认格式母节点为数字型式，子节点为-b字母形式，为使编码唯一便于数据处理，编制此脚本
import re
import pandas as pd
import os
def get_csv_path():#原编码保存为csv文件的一列，便于读取
path=input('enter csv path:')
if os.path.isfile(path):
return path
else:
print('csv file not exsit,try again:')
return get_csv_path()
def unique_code... | normal | {
"blob_id": "857e3e04b99cb346fd89b34c0d14957d65b7ac38",
"index": 9566,
"step-1": "<mask token>\n\n\ndef get_csv_path():\n path = input('enter csv path:')\n if os.path.isfile(path):\n return path\n else:\n print('csv file not exsit,try again:')\n return get_csv_path()\n\n\n<mask toke... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
"""
Created on Sat Sep 29 19:10:06 2018
@author: labuser
"""
# 2018-09-29
import os
import numpy as np
from scipy.stats import cauchy
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
import pandas as pd
def limit_scan(fname, ax):
data = pd.read_csv(fname, sep='\t', ... | normal | {
"blob_id": "aee8fa7bc1426945d61421fc72732e43ddadafa1",
"index": 3191,
"step-1": "<mask token>\n\n\ndef cauchy_model(x, a, loc, scale, y0):\n return a * cauchy.pdf(x, loc, scale) + y0\n\n\ndef cauchy_fit(x, y, d):\n if d is -1:\n a0 = -(max(y) - min(y)) * (max(x) - min(x)) / 10\n loc0 = x[np.... | [
4,
7,
8,
9,
10
] |
"""
Exercício 1 - Facebook
Você receberá uma lista de palavras e uma string . Escreva uma função que
decida quais palavras podem ser formadas com os caracteres da string (cada
caractere só pode ser utilizado uma vez). Retorne a soma do comprimento das
palavras escolhidas.
Exemplo 1:
"""
# words = ["cat", "bt", "hat", ... | normal | {
"blob_id": "bf7e3ddaf66f4c325d3f36c6b912b47f4ae22cba",
"index": 4779,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef count_words(words, chars):\n ans = 0\n alphabet = {}\n for char in chars:\n if char not in alphabet:\n alphabet[char] = 1\n else:\n al... | [
0,
1,
2,
3,
4
] |
from django.shortcuts import render, redirect
from datetime import datetime
from fichefrais.models import FicheFrais, Etat, LigneFraisForfait, LigneFraisHorsForfait, Forfait
def home_admin(request):
"""
:view home_admin: Menu principale des Administrateurs
:template home_admin.html:
"""
if not re... | normal | {
"blob_id": "b453c8e9cc50066d1b5811493a89de384a000f37",
"index": 4929,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef home_admin(request):\n \"\"\"\n :view home_admin: Menu principale des Administrateurs\n :template home_admin.html:\n \"\"\"\n if not request.user.is_authenticated()... | [
0,
1,
2,
3
] |
from trytond.pool import Pool
from .reporte import MyInvoiceReport
def register():
Pool.register(MyInvoiceReport, module='cooperar-reporte-factura', type_
='report')
| normal | {
"blob_id": "a52e0dde47d7df1b7b30887a690b201733ac7592",
"index": 4473,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef register():\n Pool.register(MyInvoiceReport, module='cooperar-reporte-factura', type_\n ='report')\n",
"step-3": "from trytond.pool import Pool\nfrom .reporte import M... | [
0,
1,
2
] |
# -*- coding:utf-8 -*-
import requests
import json
def fun1():
s_cut = [('72af8ecf3609a546bac3150c20f70455', ['老凤祥', '六福珠宝', '周生生', '亚一珠宝', '亚一金店']),
('3e78397f7dbb88ffbd78ba52d0e925fa', ['老庙', '谢瑞麟', '中国黄金', '明牌珠宝']), # yh
('6bee32b2f0719ea45cc194847efd8917', ['周大福', '潮宏基', '东华美钻', '周... | normal | {
"blob_id": "66f8fa5fc12dc80b8f46684c39781c2e4634de4a",
"index": 3479,
"step-1": "<mask token>\n\n\ndef fun1():\n s_cut = [('72af8ecf3609a546bac3150c20f70455', ['老凤祥', '六福珠宝', '周生生',\n '亚一珠宝', '亚一金店']), ('3e78397f7dbb88ffbd78ba52d0e925fa', ['老庙', '谢瑞麟',\n '中国黄金', '明牌珠宝']), ('6bee32b2f0719ea45cc1... | [
1,
2,
3,
4,
5
] |
#create a list
a = [2,3,4,5,6,7,8,9,10]
print(a)
#indexing
b = int(input('Enter indexing value:'))
print('The result is:',a[b])
print(a[8])
print(a[-1])
#slicing
print(a[0:3])
print(a[0:])
#conconteation
b=[20,30]
print(a+b)
#Repetition
print(b*3)
#updating
print(a[2])
a[2]=100
print(a)
#membership
print(5 in a)
... | normal | {
"blob_id": "f7d29dd1d990b3e07a7c07a559cf5658b6390e41",
"index": 4601,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(a)\n<mask token>\nprint('The result is:', a[b])\nprint(a[8])\nprint(a[-1])\nprint(a[0:3])\nprint(a[0:])\n<mask token>\nprint(a + b)\nprint(b * 3)\nprint(a[2])\n<mask token>\nprint(a... | [
0,
1,
2,
3
] |
from urllib.request import urlopen
from bs4 import BeautifulSoup
import re
url = input('Enter - ')
html = urlopen(url).read()
soup = BeautifulSoup(html, "html.parser")
tags = soup.find_all('tr', {'id': re.compile(r'nonplayingnow.*')})
for i in tags:
casa = i.find("td", {'class': re.compile(r'team-home')}).find(... | normal | {
"blob_id": "d07a26a69ccbbccf61402632dd6011315e0d61ed",
"index": 2710,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in tags:\n casa = i.find('td', {'class': re.compile('team-home')}).find('a')\n visitante = i.find('td', {'class': re.compile('team-away')}).find('a')\n print('Partido-> ' +... | [
0,
1,
2,
3,
4
] |
import re # regex module
from ftplib import FTP, error_perm
from itertools import groupby
from typing import List, Tuple, Dict
import requests # HTTP requests module
from util import retry_multi, GLOBAL_TIMEOUT # from util.py
class ReleaseFile:
"""! Class representing a Released file on Nebula
`name`: str... | normal | {
"blob_id": "612b1851ba5a07a277982ed5be334392182c66ef",
"index": 4064,
"step-1": "<mask token>\n\n\nclass ReleaseFile:\n <mask token>\n <mask token>\n\n def __repr__(self):\n return repr(self.name)\n\n\nclass SourceFile:\n \"\"\"! Class represeting a source file\n\n `name`: str\n Fil... | [
8,
10,
11,
12,
14
] |
import itertools
def sevens_in_a_row(arr,n):
in_a_row={}
for iteration in arr:
if arr[iteration]==arr[iteration+1]:
print blaaa
def main():
n=3
arr=['1','1','1','2','3','-4']
print (sevens_in_a_row(arr,n))
if __name__== '__main__':
main() | normal | {
"blob_id": "a2626b384d0b7320ee9bf7cd75b11925ccc00666",
"index": 9399,
"step-1": "import itertools\ndef sevens_in_a_row(arr,n):\n\tin_a_row={}\n\tfor iteration in arr:\n\t\tif arr[iteration]==arr[iteration+1]:\n\t\t\tprint blaaa\n\t\t\t\n\ndef main():\n\tn=3\n\tarr=['1','1','1','2','3','-4']\n\tprint (sevens_in_... | [
0
] |
class Graph():
def __init__(self, nvertices):
self.N = nvertices
self.graph = [[0 for column in range(nvertices)]
for row in range(nvertices)]
self.V = ['0' for column in range(nvertices)]
def nameVertex(self):
for i in range(self.N):
pr... | normal | {
"blob_id": "51a8b963047215bf864eb4a3e62beb5741dfbafe",
"index": 8572,
"step-1": "class Graph:\n\n def __init__(self, nvertices):\n self.N = nvertices\n self.graph = [[(0) for column in range(nvertices)] for row in range\n (nvertices)]\n self.V = ['0' for column in range(nverti... | [
3,
5,
6,
7,
8
] |
print("Enter string:")
s=input()
a = s.lower()
vowels = "aeiou"
consonants = "bcdfghjklmnpqrstvwxyz"
digits = "1234567890"
whitespace = " "
c = 0
v = 0
d = 0
ws= 0
for i in a:
if i in vowels:
v+=1
elif i in consonants:
c+=1
elif i in digits:
d+=1
elif i in whitespace:
... | normal | {
"blob_id": "088c77e090d444e7057a91cac606995fb523c8ef",
"index": 3079,
"step-1": "<mask token>\n",
"step-2": "print('Enter string:')\n<mask token>\nfor i in a:\n if i in vowels:\n v += 1\n elif i in consonants:\n c += 1\n elif i in digits:\n d += 1\n elif i in whitespace:\n ... | [
0,
1,
2,
3
] |
class Solution(object):
def moveZeroes(self, nums):
"""
给定一个数组 nums，编写一个函数将所有 0 移动到数组的末尾，同时保持非零元素的相对顺序。
---
输入: [0,1,0,3,12]
输出: [1,3,12,0,0]
---
思路；
:type nums: List[int]
:rtype: void Do not return anything, modify nums in-place instead.
"""
num = nums.count(0)
while 0 i... | normal | {
"blob_id": "ece80a7765674f9d2991029bb86486b616a90f58",
"index": 3944,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n",
"step-3": "class Solution(object):\n\n def moveZeroes(self, nums):\n \"\"\"\n\t\t给定一个数组 nums，编写一个函数将所有 0 移动到数组的末尾，同时保持非零元素的相对顺序。\n\t\t---\n\t\t... | [
0,
1,
2
] |
#Developer: Chritian D. Goyes
'''
this script show your name and your age.
'''
myName = 'Christian D. Goyes'
myDate = 1998
year = 2020
age = year - myDate
print ("yourname is: ", age, "and your are", "years old") | normal | {
"blob_id": "f5331b56abea41873bd3936028471d0da1c58236",
"index": 4986,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('yourname is: ', age, 'and your are', 'years old')\n",
"step-3": "<mask token>\nmyName = 'Christian D. Goyes'\nmyDate = 1998\nyear = 2020\nage = year - myDate\nprint('yourname is:... | [
0,
1,
2,
3
] |
import logging, numpy as np, time, pandas as pd
from abc import abstractmethod
from kombu import binding
from tqdm import tqdm
from functools import lru_cache
from threading import Thread
from math import ceil
from copy import copy
from .pos import Position
from .base import BaseConsumer
from .event import SignalEven... | normal | {
"blob_id": "76d166bc227986863db77aa784be3de8110437ff",
"index": 530,
"step-1": "<mask token>\n\n\nclass BaseStrategy(BaseConsumer):\n <mask token>\n <mask token>\n\n @abstractmethod\n def calculate_signals(self):\n \"\"\"Provide the mechanism to calculate a list of signals\"\"\"\n rais... | [
18,
19,
28,
30,
32
] |
"""Get pandas dataframes for a given data and month.
*get_dataframes(csvfile, spec=SPEC)* is a function to get dataframes
from *csvfile* connection under *spec* parsing instruction.
*Vintage* class addresses dataset by year and month:
Vintage(year, month).save()
Vintage(year, month).validate()
*Collecti... | normal | {
"blob_id": "e78c4f65d84d5b33debb415005e22f926e14d7d4",
"index": 1203,
"step-1": "<mask token>\n\n\nclass Vintage:\n <mask token>\n\n def __init__(self, year, month):\n self.year, self.month = year, month\n self.csv = LocalCSV(year, month)\n <mask token>\n <mask token>\n <mask token>... | [
9,
13,
14,
15,
19
] |
import pygame, states, events
from settings import all as settings
import gui
def handleInput(world, event):
if event == events.btnSelectOn or event == events.btnEscapeOn:
bwd(world)
if event%10 == 0:
world.sounds['uiaction'].play(0)
# world.shouldRedraw = True
def bwd(world):
if wor... | normal | {
"blob_id": "8650e0f1e7f2ac42c3c78191f79810f5befc9f41",
"index": 3298,
"step-1": "<mask token>\n\n\ndef bwd(world):\n if world.state >= states.Config:\n return left(world)\n world.shouldRedraw = True\n world.state = states.Intro\n\n\ndef draw(world):\n if not world.shouldRedraw:\n retur... | [
2,
3,
4,
5,
6
] |
# Generated by Django 3.1.7 on 2021-03-20 14:31
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('restapp', '0021_auto_20210320_1421'),
]
operations = [
migrations.AddField(
model_name='order',
name='phone',
... | normal | {
"blob_id": "bf160bd2fc924a11d340bd466b4a879d1cdcd86e",
"index": 7639,
"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 = [('restapp', '... | [
0,
1,
2,
3,
4
] |
#This file was created by Tate Hagan
from RootGUI import RootGUI
root = RootGUI()
root.mainloop() | normal | {
"blob_id": "d17081ef94df1e14308128341d040559edb81805",
"index": 7100,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nroot.mainloop()\n",
"step-3": "<mask token>\nroot = RootGUI()\nroot.mainloop()\n",
"step-4": "from RootGUI import RootGUI\nroot = RootGUI()\nroot.mainloop()\n",
"step-5": "#This fil... | [
0,
1,
2,
3,
4
] |
import requests
import json
from concurrent import futures
from tqdm import trange
def main():
ex=futures.ThreadPoolExecutor(max_workers=50)
for i in trange(1,152):
url="https://api.bilibili.com/pgc/season/index/result?season_version=-1&" \
"area=-1&is_finish=-1©right=-1&season... | normal | {
"blob_id": "ff8b6bc607dac889da05b9f7e9b3595151153614",
"index": 7358,
"step-1": "<mask token>\n\n\ndef index_page(url):\n res = requests.get(url)\n res.encoding = res.apparent_encoding\n next_page(res.text)\n\n\ndef next_page(html):\n data = json.loads(html)\n for i in data['data']['list']:\n ... | [
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
from sklearn import svm
data=np.loadtxt('yucedata1.txt')
X=data[:,0]
y=data[:,1]
plt.figure(1,figsize=(8,6))
myfont = FontProperties(fname=r"c:\windo... | normal | {
"blob_id": "73d7b1895282df5b744d8c03ec7e6f8530366b76",
"index": 865,
"step-1": "# -*- coding: utf-8 -*-\r\nimport numpy as np\r\nimport matplotlib as mpl\r\nimport matplotlib.pyplot as plt \r\nfrom matplotlib.font_manager import FontProperties \r\nfrom sklearn import svm\r\n\r\n\r\ndata=np.loadtxt('yucedata1.tx... | [
0
] |
# website = urlopen("https://webservices.ulm.edu/forms/forms-list")
# data = bs(website, "lxml")
# forms = data.findAll("span", {"class": "file"})
# forms_list = []
# names = []
# for f in forms:
# forms_list.append(f.find("a")["href"])
# names.append(f.get_text())
# # print(forms_list)
# for f in forms_list:... | normal | {
"blob_id": "a61f351391ca1b18359323fd9e49f1efa4c7513c",
"index": 4007,
"step-1": "<mask token>\n\n\ndef main():\n website = input('Enter the website you want to download file from: ')\n div = input('Enter the div/span (be as specific as you can): ')\n classTag = input('Enter the class/id tag you want to... | [
1,
2,
3,
4,
5
] |
"""
@author Lucas
@date 2019/3/29 21:46
"""
# 二分查找
def search(nums, target):
left = 0
right = len(nums) - 1
while left <= right:
mid = int((left + right)/2)
if target > nums[mid]:
left = mid + 1
elif target < nums[mid]:
right = mid - 1
else:
... | normal | {
"blob_id": "3eeed39bf775e2ac1900142b348f20d15907c6e6",
"index": 4972,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef search(nums, target):\n left = 0\n right = len(nums) - 1\n while left <= right:\n mid = int((left + right) / 2)\n if target > nums[mid]:\n left =... | [
0,
1,
2,
3
] |
# -*- Python -*-
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# California Institute of Technology
# (C) 2008 All Rights Reserved
#
# {LicenseText}
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
... | normal | {
"blob_id": "721e014bc5bf53a39556e31f281b77b90508cf12",
"index": 7138,
"step-1": "<mask token>\n\n\nclass Retriever(base):\n\n def _retrieveResultsFor(self, computation):\n director = self.director\n db = director.clerk.db\n orm = director.clerk.orm\n analysisObj = orm.record2objec... | [
2,
3,
4,
5,
6
] |
from pull_links import pull_links
from scrape_lyrics import scrape_lyrics
from vader_sentiment import getSentimentScores
import sys
import os
import shutil
# Get user input for artist -> capitalize it
artist = sys.argv[1].title()
pull_links(artist)
# Dictionary w/ song name as key and lyrics as value
lyrics = scrape_... | normal | {
"blob_id": "5055743c9ed8c92bcfab5379162f28315409ff91",
"index": 2200,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npull_links(artist)\n<mask token>\nos.remove('./links.json')\nshutil.rmtree('./songs')\n<mask token>\nfor song in sentimentScores:\n print(song + ': ')\n print(sentimentScores[song])... | [
0,
1,
2,
3,
4
] |
# -*- coding:utf-8 -*-
__author__ = 'yangxin_ryan'
"""
Solutions:
题目要求非递归的中序遍历，
中序遍历的意思其实就是先遍历左孩子、然后是根结点、最后是右孩子。我们按照这个逻辑，应该先循环到root的最左孩子，
然后依次出栈，然后将结果放入结果集合result，然后是根的val，然后右孩子。
"""
class BinaryTreeInorderTraversal(object):
def inorderTraversal(self, root: TreeNode) -> List[int]:
result = list()
... | normal | {
"blob_id": "8e629ee53f11e29aa026763508d13b06f6ced5ba",
"index": 940,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass BinaryTreeInorderTraversal(object):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass BinaryTreeInorderTraversal(object):\n\n def inorderTraversal(self, root: TreeNod... | [
0,
1,
2,
3,
4
] |
"""
Author:
C.M. Gosmeyer
Date:
Mar 2018
References:
"Introduction to Statistical Problem Solving in Geography",
J.C. McGrew, Jr., A.J. Lembo, Jr., C.B. Monroe
To Do:
Should tables interpolate?
y = y1 + ((x - x1) / (x2 - x1)) * (y2 - y1)
"""
import numpy as np
import pandas as p... | normal | {
"blob_id": "adb6e33dc665f88c82fcc399688a8dbd67b1e3e3",
"index": 9894,
"step-1": "<mask token>\n\n\nclass LoadStudentsTTable(LoadTable):\n <mask token>\n\n def __init__(self, tails):\n \"\"\"\n\n Parameters\n ----------\n tails : int\n 1 or 2.\n \"\"\"\n ... | [
8,
18,
19,
21,
23
] |
from flask import Flask, render_template, redirect, request, session, flash
from data import db_session
from data import users, products
import os
from flask_wtf import FlaskForm
from wtforms import StringField, PasswordField, SubmitField, BooleanField, SelectField, IntegerField
from wtforms.fields.html5 import E... | normal | {
"blob_id": "d373d283a622262e2da974549907bdd8f61e89ec",
"index": 2114,
"step-1": "<mask token>\n\n\ndef allowed_file(filename):\n return '.' in filename and filename.rsplit('.', 1)[1].lower() == 'jpg'\n\n\ndef get_profile_img():\n os.chdir('static\\\\img\\\\profile_img')\n if os.access(f'{current_user.i... | [
30,
35,
37,
40,
41
] |
sair = True
while sair:
num = int(input("informe um numero inteiro:"))
if num <16:
fatorial = 1
x = num
while x>=1:
print(x,".")
fatorial = fatorial*x
x -= 1
print("Valor total do Fatorial do %d = %d "%(num,fatorial))
else:
... | normal | {
"blob_id": "421e7ed0cc5a8c8acc9b98fae4ee6cc784d9b068",
"index": 9683,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile sair:\n num = int(input('informe um numero inteiro:'))\n if num < 16:\n fatorial = 1\n x = num\n while x >= 1:\n print(x, '.')\n fat... | [
0,
1,
2,
3
] |
from sand_game.Environment import Environment
from sand_game.behaviours.Behaviour import Behaviour
class EphemeralBehaviour(Behaviour):
"""Removes the particle after one frame
"""
def behave(env: Environment, loc: tuple[int, int]) ->tuple[int, int]:
env.set(loc[0], loc[1], None)
| normal | {
"blob_id": "2728c3ab26fbdbaac9c47054eafe1c114341f6f2",
"index": 7736,
"step-1": "<mask token>\n\n\nclass EphemeralBehaviour(Behaviour):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass EphemeralBehaviour(Behaviour):\n <mask token>\n\n def behave(env: Environment, loc: tuple[int... | [
1,
2,
3,
4
] |
print("""Hello world""")
print("Hello again")
print('Hello again') | normal | {
"blob_id": "fe82a46a7965b27729ff5bd61c1059416c96cae7",
"index": 8015,
"step-1": "<mask token>\n",
"step-2": "print('Hello world')\nprint('Hello again')\nprint('Hello again')\n",
"step-3": "print(\"\"\"Hello world\"\"\")\nprint(\"Hello again\")\nprint('Hello again')",
"step-4": null,
"step-5": null,
"s... | [
0,
1,
2
] |
import numpy as np
def find_saddle_points(A):
B = []
for i in range(A.shape[0]):
min_r = np.min(A[i])
ind_r = 0
max_c = 0
ind_c = 0
for j in range(A.shape[1]):
if (A[i][j] == min_r):
min_r = A[i][j]
ind_r = j
for k in range(A.shape[0]):
if (A[k][ind_r] >= max_c):
max_c = A[k][ind_... | normal | {
"blob_id": "808fe8f106eaff00cf0080edb1d8189455c4054b",
"index": 6706,
"step-1": "<mask token>\n\n\ndef find_saddle_points(A):\n B = []\n for i in range(A.shape[0]):\n min_r = np.min(A[i])\n ind_r = 0\n max_c = 0\n ind_c = 0\n for j in range(A.shape[1]):\n if A... | [
5,
8,
9,
11,
12
] |
#!/usr/bin/env python3
import sys
from argparse import ArgumentParser
from arg_checks import IsFile, MinInt
from visualisation import Visualisation
parser = ArgumentParser(description="Visualises DS simulations")
# The order of arguments in descending order of file frequency is: config, failures, log.
# This should... | normal | {
"blob_id": "1f953b20ff0eb868c2fbff367fafa8b651617e64",
"index": 6131,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.add_argument('config', action=IsFile, help=\n 'configuration file used in simulation')\nparser.add_argument('log', action=IsFile, help=\n 'simulation log file to visualise')\... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
#!-*-coding:utf-8 -*-
"""
@version: python3.7
@author: ‘v-enshi‘
@license: Apache Licence
@contact: 123@qq.com
@site:
@software: PyCharm
@file: Images_fade.py
@time: 2019/1/16 17:17
"""
from PIL import Image
import numpy as np
filename = "hw0_data/westbrook.jpg"
im=Image.open(filename) #open th... | normal | {
"blob_id": "6e78d1fb2364d334f47fea89b065d859c025ca2f",
"index": 5648,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfinalImg.save('Q2.jpg')\n",
"step-3": "<mask token>\nfilename = 'hw0_data/westbrook.jpg'\nim = Image.open(filename)\nimgs = np.array(im)\nimgsDiv2 = np.trunc(imgs / 2)\nimgInt = imgsDiv... | [
0,
1,
2,
3,
4
] |
from analizer_pl.abstract.instruction import Instruction
from analizer_pl import grammar
from analizer_pl.statement.expressions import code
from analizer_pl.reports.Nodo import Nodo
class If_Statement(Instruction):
def __init__(self, row, column,expBool, elseif_list,else_,stmts ) -> None:
super().__i... | normal | {
"blob_id": "bbbdb30ceef920e600c9f46fb968732b077be2d8",
"index": 4231,
"step-1": "<mask token>\n\n\nclass If_Statement(Instruction):\n\n def __init__(self, row, column, expBool, elseif_list, else_, stmts) ->None:\n super().__init__(row, column)\n self.expBool = expBool\n self.elseif_list ... | [
7,
9,
10,
11,
12
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Implements the webservice calls of the command
like rest apis or other network related methods
""" | normal | {
"blob_id": "48369e1ed826a9a50c0fd9f63b7cc10b8225ce2b",
"index": 8760,
"step-1": "<mask token>\n",
"step-2": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"\nImplements the webservice calls of the command\nlike rest apis or other network related methods\n\"\"\"",
"step-3": null,
"step-4": null,
... | [
0,
1
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.5 on 2017-03-15 15:20
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('challenges', '0019_auto_20170310_1114'),
]
operations = [
migrations.AddFie... | normal | {
"blob_id": "6b7ff00eb9a5d0837def5b245ba2d4a0acec972e",
"index": 3466,
"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 = [('challenges'... | [
0,
1,
2,
3,
4
] |
#! py -3
# -*- coding: utf-8 -*-
import requests
from urllib.parse import quote
import logging
from urllib.parse import urlparse
logger = logging.getLogger(__name__)
logger = logging.getLogger()
# 配置日志级别，如果不显示配置，默认为Warning，表示所有warning级别已下的其他level直接被省略，
# 内部绑定的handler对象也只能接收到warning级别以上的level，你可以理解为总开关
logger.setLeve... | normal | {
"blob_id": "c5d92ec592250d5bc896d32941364b92ff1d21e9",
"index": 3793,
"step-1": "<mask token>\n\n\ndef request_dyn():\n logger.info('dyn: 开始测试请求')\n postUrl = '%s/raframework/browse/dyn' % serverUrl\n postData = {'page': '/conf/CDSConfig.jsp', 'amp': '', 'action':\n 'returnXML', 'LOCALE_LANGUAGE... | [
3,
5,
6,
8,
9
] |
from pylab import *
import pandas as pd
from matplotlib import pyplot
import pylab
from mpl_toolkits.mplot3d import Axes3D
from threading import Thread
from threading import Semaphore
from threading import Lock
from Queue import Queue
sam = Semaphore(1)
lck = Lock()
q=Queue(10)
def myFunc(z):
#if z%2==0 and z>1:
... | normal | {
"blob_id": "33c0efb47e3253442b6a808c7ebffac275c19321",
"index": 7763,
"step-1": "from pylab import *\nimport pandas as pd\nfrom matplotlib import pyplot\nimport pylab\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom threading import Thread\nfrom threading import Semaphore\nfrom threading import Lock\nfrom Queue i... | [
0
] |
import subprocess
import logging
import time
import argparse
import threading
import os
import matplotlib.pyplot as plt
import numpy as np
import argparse
def runWeka(wekapath, modelpath, datapath):
os.chdir(wekapath)
proc = subprocess.Popen(['/usr/bin/java', '-classpath', 'weka.jar', 'weka.classifiers.functio... | normal | {
"blob_id": "a1f0eced5d122fe8557ebc4d707c87b4194513e3",
"index": 4976,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef runWeka(wekapath, modelpath, datapath):\n os.chdir(wekapath)\n proc = subprocess.Popen(['/usr/bin/java', '-classpath', 'weka.jar',\n 'weka.classifiers.functions.Multi... | [
0,
1,
2,
3,
4
] |
# wfp, 6/6
# simple list stuff
my_list = [1,'a',3.14]
print("my_list consists of: ",my_list)
print()
print("Operations similar to strings")
print("Concatenation")
print("my_list + ['bill'] equals: ", my_list + ["bill"])
print()
print("Repeat")
print("my_list * 3 equals: ", my_list * 3)
print()
print("In... | normal | {
"blob_id": "1c134cba779459b57f1f3c195aed37d105b94aef",
"index": 9935,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('my_list consists of: ', my_list)\nprint()\nprint('Operations similar to strings')\nprint('Concatenation')\nprint(\"my_list + ['bill'] equals: \", my_list + ['bill'])\nprint()\nprin... | [
0,
1,
2,
3
] |
class Node:
def __init__ (self, val):
self.childleft = None
self.childright = None
self.nodedata = val
root = Node("Kaif")
root.childleft = Node("name")
root.childright = Node("!")
root.childleft.childleft = Node("My")
root.childleft.childright = Node("is")
message = input(... | normal | {
"blob_id": "73e4346007acae769b94a55ef53a48a9d3325002",
"index": 7262,
"step-1": "class Node:\n <mask token>\n\n\n<mask token>\n",
"step-2": "class Node:\n\n def __init__(self, val):\n self.childleft = None\n self.childright = None\n self.nodedata = val\n\n\n<mask token>\n\n\ndef try... | [
1,
3,
4,
5,
6
] |
#!/usr/bin/env python3
from datetime import datetime
import re
import sys
MONTHS_REGEXP = ('Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec|'
'January|February|March|April|June|July|August|September|October|November|December')
re_entry_begin = re.compile(r'(?P<version>[\d.]+)[ :]*\(?(?P<date>\d\d\d\d... | normal | {
"blob_id": "03677f02473019fcc6a40d91569a85be78ca0a87",
"index": 7179,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in sys.stdin:\n m = re_entry_begin.match(line)\n if m:\n if first_line_met:\n sys.stdout.write(signature_format.format(date=current_date))\n versio... | [
0,
1,
2,
3,
4
] |
'''
Created on 3 Jul 2009
@author: charanpal
An abstract base class which represents a graph generator. The graph generator
takes an existing empty graph and produces edges over it.
'''
from apgl.util.Util import Util
class AbstractGraphGenerator(object):
def generate(self, graph):
Util.abst... | normal | {
"blob_id": "e37e468d8a41b8711fb0eb4ddec7db67691f9156",
"index": 488,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass AbstractGraphGenerator(object):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass AbstractGraphGenerator(object):\n\n def generate(self, graph):\n Util.abstrac... | [
0,
1,
2,
3,
4
] |
"""
Copyright (C) Adrian Herrera, 2017
You will need to install r2pipe and pydot:
```
pip install r2pipe pydot
```
"""
from __future__ import print_function
import glob
import json
import os
import pydot
import r2pipe
import s2e_web.S2E_settings as S2E_settings
def function_addrs(r2):
"""
Yield a list of... | normal | {
"blob_id": "2aee4af2e5a5c3f59dde4d9dd46f8d124a32fb27",
"index": 2590,
"step-1": "<mask token>\n\n\ndef function_addrs(r2):\n \"\"\"\n Yield a list of all the function's start addresses.\n \"\"\"\n for addr in r2.cmdj('aflqj'):\n yield int(addr, 16)\n\n\n<mask token>\n\n\ndef basic_block_cover... | [
3,
4,
5,
6,
7
] |
class A(object):
_a ='d'
@staticmethod
def func_1():
A._a = 'b'
print A._a
@classmethod
def func_3(cls):
print cls._a
def func_2(self):
# self._a = 'c'
print self._a
# print A._a
#
# class B(object):
# @staticmethod
# def func_1():
# ... | normal | {
"blob_id": "2ab3adb4d0ed7e6e48afb2a8dab8f9250d335723",
"index": 2253,
"step-1": "class A(object):\n _a ='d'\n\n\n @staticmethod\n def func_1():\n A._a = 'b'\n print A._a\n\n @classmethod\n def func_3(cls):\n print cls._a\n\n def func_2(self):\n # self._a = 'c'\n ... | [
0
] |
import operator
def group_by_owners(files):
print(files, type(files))
for k, v in files.items():
# for v in k:
print(k, v)
# if k[v] == k[v]:
# print("same", v)
for f in files:
print(f[0])
for g in v:
print(g)
_files = sorted(files.items(... | normal | {
"blob_id": "4843239a41fe1ecff6c8c3a97aceef76a3785647",
"index": 7334,
"step-1": "<mask token>\n\n\ndef group_by_owners(files):\n print(files, type(files))\n for k, v in files.items():\n print(k, v)\n for f in files:\n print(f[0])\n for g in v:\n print(g)\n _files = so... | [
1,
2,
3,
4,
5
] |
# Generated by Django 3.1.7 on 2021-03-29 18:50
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("core", "0052_add_more_tags"),
]
operations = [
migrations.RenameField(
model_name="reporter",
old_name="auth0_role_name",
... | normal | {
"blob_id": "c0cabf2b6f7190aefbaefa197a9008de3a344147",
"index": 2082,
"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 = [('core', '005... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
import csv
import sys
import os.path
#Versao 2 do gerador das RawZones
#global
DIR_PYGEN = "/bid/_temporario_/pythonGeneration/"
DIR_INTGR_PAR = "/bid/integration_layer/par/"
DIR_INTGR_JOB = "/bid/integration_layer/job/"
def Sqoop(filename,source_database,source_table, split_field, sourcesystem, ta... | normal | {
"blob_id": "aa817b86e26cf8cd9771aeb276914a1f5869c737",
"index": 1849,
"step-1": "#!/usr/bin/python\nimport csv\nimport sys\nimport os.path\n\n#Versao 2 do gerador das RawZones\n\n#global\nDIR_PYGEN = \"/bid/_temporario_/pythonGeneration/\"\nDIR_INTGR_PAR = \"/bid/integration_layer/par/\"\nDIR_INTGR_JOB = \"/bid... | [
0
] |
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 19 05:29:19 2020
@author: Gaurav
"""
from tensorflow.keras.models import load_model
import cv2
import os
from tensorflow.keras.preprocessing.image import img_to_array
import numpy as np
model=load_model('E:/AI Application Implementation/trained_model/Classifi... | normal | {
"blob_id": "c3e2bd635a7ff558ed56e7fb35e8b10e1c660c88",
"index": 6804,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in arr:\n img = cv2.imread(i)\n img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n img = cv2.resize(img, (32, 32))\n img = img_to_array(img)\n img = np.expand_dims(img, axi... | [
0,
1,
2,
3,
4
] |
from __future__ import division
import numpy as np
import scipy.stats
from tms import read_and_transform
__author__ = 'Diego'
def estimate_vrpn_clock_drift(points):
# clocks = [map(np.datetime64,(p.date,p.ref_date,p.point_date)) for p in points]
clocks = [(p.date, p.ref_date, p.point_date) for p in points... | normal | {
"blob_id": "7d0b0cb19e22ff338104e0c2061da94ba04d4f16",
"index": 2249,
"step-1": "from __future__ import division\n\nimport numpy as np\nimport scipy.stats\n\nfrom tms import read_and_transform\n\n\n__author__ = 'Diego'\n\n\ndef estimate_vrpn_clock_drift(points):\n # clocks = [map(np.datetime64,(p.date,p.ref_... | [
0
] |
from pyspark import SparkContext, SparkConf
import time
# Create a basic configuration
conf = SparkConf().setAppName("myTestCopyApp")
# Create a SparkContext using the configuration
sc = SparkContext(conf=conf)
print("START")
time.sleep(30)
print("END")
| normal | {
"blob_id": "4b773fbf45d15dff27dc7bd51d6636c5f783477b",
"index": 9183,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('START')\ntime.sleep(30)\nprint('END')\n",
"step-3": "<mask token>\nconf = SparkConf().setAppName('myTestCopyApp')\nsc = SparkContext(conf=conf)\nprint('START')\ntime.sleep(30)\np... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
# coding: utf-8
# In[2]:
from __future__ import absolute_import, division, print_function, unicode_literals
import tensorflow as tf
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
# In[1]:
import numpy as np
import pandas as pd
import matplotlib.pypl... | normal | {
"blob_id": "aea92827753e12d2dc95d63ddd0fe4eb8ced5d14",
"index": 3815,
"step-1": "<mask token>\n\n\ndef convolve(image, fltr):\n r_p = 0\n c_p = 0\n conv_list = []\n while r_p + 1 <= image.shape[0] - 1:\n while c_p + 1 <= image.shape[1] - 1:\n x = np.sum(np.multiply(image[r_p:r_p + ... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
# Copyright (c) 2018, HSCH and contributors
# For license information, please see license.txt
from __future__ import unicode_literals
import frappe
from frappe import _
from frappe.utils.nestedset import NestedSet
class GoalCategory(NestedSet):
nsm_parent_field = 'parent_goal_category';
de... | normal | {
"blob_id": "c6055c6b67ac28d304ed34ddc2f81e59da8e7f1b",
"index": 1103,
"step-1": "<mask token>\n\n\nclass GoalCategory(NestedSet):\n nsm_parent_field = 'parent_goal_category'\n\n def on_update(self):\n self.validate_name_with_goal()\n super(GoalCategory, self).on_update()\n self.valida... | [
4,
5,
6,
7,
8
] |
# Generated by Django 2.1.7 on 2019-03-18 02:25
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('training_area', '0006_remove_event_day'),
]
operations = [
migrations.Crea... | normal | {
"blob_id": "9905559909f10831373e659cde0f275dc5d71e0d",
"index": 7041,
"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 = [('training_ar... | [
0,
1,
2,
3,
4
] |
from bs4 import BeautifulSoup
import urllib2
def get_begin_data(url):
headers = {
'ser-Agent': '',
'Cookie': ''
}
request = urllib2.Request(url, headers=headers)
web_data = urllib2.urlopen(request)
soup = BeautifulSoup(web_data, 'html.parser')
results = soup.select('tab... | normal | {
"blob_id": "790110a8cba960eb19593e816b579080dfc46a4e",
"index": 4572,
"step-1": "<mask token>\n\n\ndef get_begin_data(url):\n headers = {'ser-Agent': '', 'Cookie': ''}\n request = urllib2.Request(url, headers=headers)\n web_data = urllib2.urlopen(request)\n soup = BeautifulSoup(web_data, 'html.parse... | [
2,
3,
4,
5,
6
] |
from os import getenv
LISTEN_IP = getenv('LISTEN_IP', '0.0.0.0')
LISTEN_PORT = int(getenv('LISTEN_PORT', 51273))
LISTEN_ADDRESS = LISTEN_IP, LISTEN_PORT
CONFIRMATION = getenv('CONFIRMATION')
if CONFIRMATION:
CONFIRMATION = CONFIRMATION.encode()
class UDPProtocol:
def __init__(self, consumer):
self... | normal | {
"blob_id": "cca543f461724c3aac8fef23ef648883962bd706",
"index": 4607,
"step-1": "<mask token>\n\n\nclass UDPProtocol:\n <mask token>\n\n def connection_made(self, transport):\n self.transport = transport\n <mask token>\n <mask token>\n <mask token>\n\n def stop(self):\n self.tran... | [
3,
5,
8,
9,
11
] |
class Leg():
__smelly = True
def bend_knee(self):
print("knee bent")
@property
def smelly(self):
return self.__smelly
@smelly.setter
def smelly(self,smell):
self.__smelly = smell
def is_smelly(self):
return self.__smelly | normal | {
"blob_id": "a4ecc578a163ee4657a2c9302f79f15c2e4e39de",
"index": 672,
"step-1": "class Leg:\n <mask token>\n <mask token>\n\n @property\n def smelly(self):\n return self.__smelly\n <mask token>\n\n def is_smelly(self):\n return self.__smelly\n",
"step-2": "class Leg:\n <mask ... | [
3,
4,
5,
6,
7
] |
from inotifier import Notifier
from IPython.display import display, Audio, HTML
import pkg_resources
import time
class AudioPopupNotifier(Notifier):
"""Play Sound and show Popup upon cell completion"""
def __init__(self, message="Cell Completed", audio_file="pad_confirm.wav"):
super(AudioPopupNotifi... | normal | {
"blob_id": "94a3a74260fac58b4cad7422608f91ae3a1a0272",
"index": 6247,
"step-1": "<mask token>\n\n\nclass AudioPopupNotifier(Notifier):\n <mask token>\n <mask token>\n\n def notify(self):\n display(Audio(self.audio, autoplay=True))\n time.sleep(3)\n display(HTML(self.template.format... | [
2,
3,
4,
5,
6
] |
# Problem Statement – An automobile company manufactures both a two wheeler (TW) and a four wheeler (FW). A company manager wants to make the production of both types of vehicle according to the given data below:
# 1st data, Total number of vehicle (two-wheeler + four-wheeler)=v
# 2nd data, Total number of wheels = W
... | normal | {
"blob_id": "74939f81e999b8e239eb64fa10b56f48c47f7d94",
"index": 1622,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif w < 2 or w % 2 != 0 or w <= v:\n print('INVALID INPUT')\nelse:\n x = (4 * v - w) // 2\n print('TW={0} FW={1}'.format(x, v - x))\n",
"step-3": "v = int(input())\nw = int(inpu... | [
0,
1,
2,
3
] |
from django.apps import AppConfig
class FilebasedUniqueConfig(AppConfig):
name = 'papermerge.filebased_unique'
label = 'filebased_unique'
| normal | {
"blob_id": "2d17229afe154937132c1e4f8c138896da34ab61",
"index": 1430,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass FilebasedUniqueConfig(AppConfig):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass FilebasedUniqueConfig(AppConfig):\n name = 'papermerge.filebase... | [
0,
1,
2,
3
] |
import luigi
import numpy as np
import tqdm
import os
from scipy import spatial
from kq import wordmat_distance
class QuestionVectorTask(luigi.Task):
resources = {'cpu': 1}
dataset = luigi.Parameter()
def requires(self):
#yield wordmat_distance.WeightedSentenceVecs()
yield wordmat_distan... | normal | {
"blob_id": "ae6a6f7622bf98c094879efb1b9362a915a051b8",
"index": 1175,
"step-1": "<mask token>\n\n\nclass QuestionVectorTask(luigi.Task):\n <mask token>\n <mask token>\n <mask token>\n\n def output(self):\n return luigi.LocalTarget('./cache/question_distance/%s.npy' % self.\n datase... | [
7,
8,
11,
12,
13
] |
# -*- coding: utf-8 -*-
"""
Created on Sat Aug 3 17:16:12 2019
@author: Meagatron
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from collections import defaultdict
import math
import itertools
from dtw import dtw
import timeit
from helper_functions import normalize,alphabetize_ts,hammin... | normal | {
"blob_id": "16215ee42c4ea284dca0ebb7372fef04c0cc54b9",
"index": 2149,
"step-1": "<mask token>\n\n\ndef segment_ts():\n ts_len = len(x1)\n mod = ts_len % window_size\n rnge = 0\n if skip_offset == 0:\n ts_len = int((ts_len - mod - window_size) / 1)\n rnge = int(ts_len / window_size)\n ... | [
4,
5,
6,
7,
8
] |
number = int(input())
bonus = 0
if number <= 100:
bonus = 5
total_point = number + bonus
elif number > 1000:
bonus = 0.1 * number
total_point = number + bonus
else:
bonus = 0.2 * number
total_point = number + bonus
if number % 2 == 0:
bonus = bonus + 1
total_point = number + bonus
pr... | normal | {
"blob_id": "7ee3301b55d323d156bd394f8525e37502d19430",
"index": 7669,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif number <= 100:\n bonus = 5\n total_point = number + bonus\nelif number > 1000:\n bonus = 0.1 * number\n total_point = number + bonus\nelse:\n bonus = 0.2 * number\n t... | [
0,
1,
2
] |
import os
import requests
import sqlite3
from models import analytics, jcanalytics
def populate():
url = 'https://api.clicky.com/api/stats/4?site_id=100716069&sitekey=93c104e29de28bd9&type=visitors-list'
date = '&date=last-30-days'
limit = '&limit=all'
output = '&output=json'
total = url+date+limi... | normal | {
"blob_id": "e8226ab6be5c21335d843cba720e66646a2dee4e",
"index": 241,
"step-1": "import os\nimport requests\nimport sqlite3\nfrom models import analytics, jcanalytics\n\n\ndef populate():\n url = 'https://api.clicky.com/api/stats/4?site_id=100716069&sitekey=93c104e29de28bd9&type=visitors-list'\n date = '&d... | [
0
] |
# DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER
# Copyright (c) 2018 Juniper Networks, Inc.
# All rights reserved.
# Use is subject to license terms.
#
# Author: cklewar
import os
import threading
import time
from jnpr.junos import Device
from jnpr.junos import exception
from jnpr.junos.utils.config im... | normal | {
"blob_id": "45cdf33f509e7913f31d2c1d6bfada3a84478736",
"index": 2904,
"step-1": "<mask token>\n\n\nclass SoftwareTask(Task):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, sample_device=None, shared=None):\n super(SoftwareTask, self).__... | [
9,
10,
11,
12,
13
] |
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