code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def plot_feature_VS_Observed(feature, df, linecolor):
"""
This function plots the 1880-2004 time series plots for the selected feature and observed earth
:param
Input: df -- > The dataframe of each of the fea... | flexible | {
"blob_id": "8348d353e6fdea77c9c994d541db1420ef57a797",
"index": 4399,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef plot_feature_VS_Observed(feature, df, linecolor):\n \"\"\"\n This function plots the 1880-2004 time series plots for the selected feature and observed earth\n :param\n ... | [
0,
1,
2,
3
] |
# -*- coding:utf-8 -*-
__author__ = 'yyp'
__date__ = '2018-5-26 3:42'
'''
Given a string, find the length of the longest substring without repeating characters.
Examples:
Given "abcabcbb", the answer is "abc", which the length is 3.
Given "bbbbb", the answer is "b", with the length of 1.
Given "pwwkew", the answer is ... | normal | {
"blob_id": "b7c43f4242e38318c9e5423ea73e9d9d86759a53",
"index": 4663,
"step-1": "<mask token>\n\n\nclass Solution:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n def lengthOfLongestSubstring(self, s):\n \"\"\"\n :type s: str\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for numbers in n_list:
n_dict = {}
for n in numbers:
if n in n_dict:
n_dict[n] += 1
else:
n_dict[n] = 1
mode = []
if len(n_dict) == 1 or len(n_dict) == len(numbers):
... | flexible | {
"blob_id": "39f9341313e29a22ec5e05ce9371bf65e89c91bd",
"index": 25,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor numbers in n_list:\n n_dict = {}\n for n in numbers:\n if n in n_dict:\n n_dict[n] += 1\n else:\n n_dict[n] = 1\n mode = []\n if len(n_di... | [
0,
1,
2,
3
] |
from django.apps import AppConfig
class AppValidationsConfig(AppConfig):
name = 'app_validations'
| normal | {
"blob_id": "7a6a8b5e344a7b60e369f100885d1e26afa28f46",
"index": 7600,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass AppValidationsConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass AppValidationsConfig(AppConfig):\n name = 'app_validations'\n",
"step-4": "from ... | [
0,
1,
2,
3
] |
import ast
import datetime
from pathlib import Path
from typing import Any, Dict
import yaml
from .lemmatizer import LemmatizerPymorphy2, Preprocessor
def get_config(path_to_config: str) -> Dict[str, Any]:
"""Get config.
Args:
path_to_config (str): Path to config.
Returns:
Dict[str, An... | normal | {
"blob_id": "c85d7e799a652e82bfaf58e1e8bfa9c4606a8ecb",
"index": 917,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_config(path_to_config: str) ->Dict[str, Any]:\n \"\"\"Get config.\n\n Args:\n path_to_config (str): Path to config.\n\n Returns:\n Dict[str, Any]: Config... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
# coding=utf-8
import sys,os
dir = '/home/ellen/yjoqm/fdfs_client/pic'
def scp_file(filename):
cmd = 'scp ellen@61.147.182.142:/home/ellen/yjoqm/fdfs_client/pic/%s .' %filename
os.system(cmd)
def main(args):
args = sys.argv[1]
scp_file(args)
print 'done~~~~'
if __name_... | normal | {
"blob_id": "e2489f9d3041c45129fdd71da6652a6093c96d2d",
"index": 8487,
"step-1": "#!/usr/bin/env python\n# coding=utf-8\nimport sys,os\n\ndir = '/home/ellen/yjoqm/fdfs_client/pic'\n\ndef scp_file(filename):\n cmd = 'scp ellen@61.147.182.142:/home/ellen/yjoqm/fdfs_client/pic/%s .' %filename\n os.system(cmd)... | [
0
] |
from rllab.algos.trpo import TRPO
from rllab.baselines.linear_feature_baseline import LinearFeatureBaseline
from rllab.envs.gym_env import GymEnv
from rllab.envs.normalized_env import normalize
from rllab.misc.instrument import run_experiment_lite
from rllab.policies.gaussian_mlp_policy import GaussianMLPPolicy
from rl... | normal | {
"blob_id": "9f479ad2acf4f6deb0ca4db606c3d804979c10bd",
"index": 3804,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef run_task(*_):\n env = normalize(GymEnv('DartWalker2d-v1', record_video=False))\n policy_sep = GaussianHLCPolicy(env_spec=env.spec, hidden_sizes=(64, 32),\n sub_out_di... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def bfs(start):
visited = [False] * (n + 1)
visited[start] = True
q = deque()
q.append(start)
cnt = 1
while q:
now = q.popleft()
for i in graph[now]:
if not visited[i]:
visited[i] = True
q.append(i)
... | flexible | {
"blob_id": "8a631adc8d919fb1dded27177818c4cb30148e94",
"index": 610,
"step-1": "<mask token>\n\n\ndef bfs(start):\n visited = [False] * (n + 1)\n visited[start] = True\n q = deque()\n q.append(start)\n cnt = 1\n while q:\n now = q.popleft()\n for i in graph[now]:\n if ... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python
import os
from subprocess import Popen, PIPE, STDOUT
import time
import re
import telnetlib
from get_sys_info import get_node_list, get_spec_node_list, get_active_tcu, get_ru_list, is_active_ru
g_rg_list = [
'/SGWNetMgr',
'/SS7SGU',
'/MGW_CMRG',
'/MGW_OMURG',
'/Directory',
]
status_dic... | normal | {
"blob_id": "603d904404ace88205a524d8bfbe3e621b65f425",
"index": 8750,
"step-1": "#!/usr/bin/python\nimport os\nfrom subprocess import Popen, PIPE, STDOUT\nimport time\nimport re\nimport telnetlib\nfrom get_sys_info import get_node_list, get_spec_node_list, get_active_tcu, get_ru_list, is_active_ru\ng_rg_list = ... | [
0
] |
<|reserved_special_token_0|>
class CourseSchedule:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class CourseSchedule:
<|reserved_special_token_0|>
def can_finish(self, numCourses: int, prerequisites: List[List[int]]
)... | flexible | {
"blob_id": "7c53c7bec6b6b2d4d6be89b750eeef83ca9115cc",
"index": 2960,
"step-1": "<mask token>\n\n\nclass CourseSchedule:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass CourseSchedule:\n <mask token>\n\n def can_finish(self, numCourses: int, prerequisites: List[List[int]]\n ... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def read_modified_alert_ids():
""" Read modified alert IDs from file, then remove them from the file."""
if not os.path.exists(MODIFIED_ALERTS_FILE):
return []
lock = filelock.FileLock(MODIFIED_ALERTS_FILE, 5)
lock.acquire()
fp = open(MODIFIED_ALERTS_FILE, 'r+'... | flexible | {
"blob_id": "90ae14d8af163343520365a5565a7c44de57059d",
"index": 5662,
"step-1": "<mask token>\n\n\ndef read_modified_alert_ids():\n \"\"\" Read modified alert IDs from file, then remove them from the file.\"\"\"\n if not os.path.exists(MODIFIED_ALERTS_FILE):\n return []\n lock = filelock.FileLoc... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class GerenciaLedsConfig(AppConfig):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class GerenciaLedsConfig(AppConfig):
name = 'gerencia_leds'
<|reserved_special_token_1|>
... | flexible | {
"blob_id": "0754103c2d8cef0fd23b03a8f64ade8f049bce48",
"index": 4890,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass GerenciaLedsConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass GerenciaLedsConfig(AppConfig):\n name = 'gerencia_leds'\n",
"step-4": "from django... | [
0,
1,
2,
3
] |
# using python3
class Rational:
def __init__(self, numer, denom):
self.numer = numer
self.denom = denom
def __add__(self, other):
return Rational(
self.numer * other.denom + other.numer * self.denom,
self.denom * other.denom
)
def __sub__(self, oth... | normal | {
"blob_id": "8098b9c27689dd4168ef05c03d4ec00f67f8090e",
"index": 4771,
"step-1": "class Rational:\n\n def __init__(self, numer, denom):\n self.numer = numer\n self.denom = denom\n <mask token>\n <mask token>\n\n def __mul__(self, other):\n return Rational(self.numer * other.numer... | [
3,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
def best_hits(distf, maxscore, verbose=False):
"""
Find the best hits
"""
bh = {}
allph = set()
with open(distf, 'r') as din:
for li in din:
p = li.strip().split('\t')
if float(p[3]) <= maxscore:
if p[0] not in bh:
... | flexible | {
"blob_id": "22523304c9e2ce1339a7527cdbd67a81c780d806",
"index": 1090,
"step-1": "<mask token>\n\n\ndef best_hits(distf, maxscore, verbose=False):\n \"\"\"\n Find the best hits\n \"\"\"\n bh = {}\n allph = set()\n with open(distf, 'r') as din:\n for li in din:\n p = li.strip()... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class CRFData:
"""
测试用的 crf 数据
"""
def __init__(self):
bio_labels = [['O', 'I-X', 'B-X', 'I-Y', 'B-Y']]
self.label_vocabulary = LabelVocabulary(labels=bio_labels, padding=
LabelVocabulary.PADDING)
self.logits = torch.tensor([[[0, 0, 0.5... | flexible | {
"blob_id": "f64138ee5a64f09deb72b47b86bd7795acddad4d",
"index": 9980,
"step-1": "<mask token>\n\n\nclass CRFData:\n \"\"\"\n 测试用的 crf 数据\n \"\"\"\n\n def __init__(self):\n bio_labels = [['O', 'I-X', 'B-X', 'I-Y', 'B-Y']]\n self.label_vocabulary = LabelVocabulary(labels=bio_labels, padd... | [
3,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def check_image(file_type):
match = re.match('image/*', file_type)
return match
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def check_image(file_type):
match = re.mat... | flexible | {
"blob_id": "13fa650557a4a8827c9fb2e514bed178df19a32c",
"index": 1295,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef check_image(file_type):\n match = re.match('image/*', file_type)\n return match\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef check_image(file_type):\n match =... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def version_100_iq(limit):
nums = []
for x in range(2, limit):
facs = 0
n = x
for p in primes:
if n % p == 0:
facs += 1
while n % p == 0:
n //= p
if n == 1 or facs >= 4:
... | flexible | {
"blob_id": "ea8676a4c55bbe0ae2ff8abf924accfc0bd8f661",
"index": 1272,
"step-1": "<mask token>\n\n\ndef version_100_iq(limit):\n nums = []\n for x in range(2, limit):\n facs = 0\n n = x\n for p in primes:\n if n % p == 0:\n facs += 1\n while n %... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class WarmupStepLR(_LRScheduler, AbsBatchStepScheduler):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __repr__(self):
return (
f'{self.__class__.__name__}(warmup_steps={self.warmup_steps}, steps_per_epoch={self.steps_per_epoch}, step_size=... | flexible | {
"blob_id": "bce16762c0739087a8309872da4ac04298c50893",
"index": 7695,
"step-1": "<mask token>\n\n\nclass WarmupStepLR(_LRScheduler, AbsBatchStepScheduler):\n <mask token>\n <mask token>\n\n def __repr__(self):\n return (\n f'{self.__class__.__name__}(warmup_steps={self.warmup_steps}, ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class TestRoomService(BaseTestCase):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class TestDeviceService(BaseTestCase):
"""Test the device service"""
def test_get_device(self):
devic... | flexible | {
"blob_id": "332e2945e34c861b2132f6b42ef59416a38455a5",
"index": 2542,
"step-1": "<mask token>\n\n\nclass TestRoomService(BaseTestCase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass TestDeviceService(BaseTestCase):\n \"\"\"Test the device service\"\"\"\n\n def test_get... | [
7,
9,
11,
12,
13
] |
<|reserved_special_token_0|>
class ResizeImageBuilder:
def __init__(self):
pass
def setOriginImagePath(self, filePath):
try:
img = Image.open(filePath)
print('origin image mode:', img.mode)
img = img.convert('RGB')
print('target image mode:', i... | flexible | {
"blob_id": "47119f46cdbbb7306aef8237d4f56f0f10690ae4",
"index": 9245,
"step-1": "<mask token>\n\n\nclass ResizeImageBuilder:\n\n def __init__(self):\n pass\n\n def setOriginImagePath(self, filePath):\n try:\n img = Image.open(filePath)\n print('origin image mode:', img.... | [
5,
6,
8,
9,
10
] |
from project import db
from project.models import User, Recipe, Association, Ingre, Recipe_ingre
user=User.query.filter_by(username="xiaofan").first()
recipe=Recipe.query.filter_by(recipename="Jerry").first()
recipes = Recipe.query.filter(Recipe.users.any(username="xiaofan")).all()
if recipe not in recipes:
us... | normal | {
"blob_id": "07f8fd305e2311c0e37a785da0a826b8ea4e78ba",
"index": 4154,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif recipe not in recipes:\n user.add_recipes([recipe])\n db.session.commit()\n",
"step-3": "<mask token>\nuser = User.query.filter_by(username='xiaofan').first()\nrecipe = Recipe.... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class UserRegistrationForm(UserCreationForm):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Meta:
model = User
fields = 'first_name', 'last_name', 'email', 'password1', 'password2'
<|reserved_special_token_0|>
class UserLoginForm(forms... | flexible | {
"blob_id": "e50517910e191594034f60a021647f4415b6f1c4",
"index": 2822,
"step-1": "<mask token>\n\n\nclass UserRegistrationForm(UserCreationForm):\n <mask token>\n <mask token>\n\n\n class Meta:\n model = User\n fields = 'first_name', 'last_name', 'email', 'password1', 'password2'\n <mas... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class LinearRegressor:
<|reserved_special_token_0|>
def _cost_function(self, y_pred, y, m):
"""
Gets the cost for the predicted values when contrasted with the correct ones.
y_pred: An (1 x m) vector that corresponds to the values predicted by the Linear R... | flexible | {
"blob_id": "d805a1290c107a8d768417a432e338b182b7cd6b",
"index": 5524,
"step-1": "<mask token>\n\n\nclass LinearRegressor:\n <mask token>\n\n def _cost_function(self, y_pred, y, m):\n \"\"\"\n Gets the cost for the predicted values when contrasted with the correct ones.\n y_pred: An (1... | [
4,
5,
6,
8,
9
] |
<|reserved_special_token_0|>
def ftp_download():
file_remote = 'ftp_upload.jpg'
file_local = (
'/home/pi/Desktop/Camera-Rasp-Arduino-sensors/test_download.jpg')
bufsize = 1024
fp = open(file_local, 'wb')
f.retrbinary('RETR ' + file_remote, fp.write, bufsize)
fp.close()
<|reserved_spe... | flexible | {
"blob_id": "a1b85d140c45f082ceac54ad8aa9aa5c3659d5cf",
"index": 9661,
"step-1": "<mask token>\n\n\ndef ftp_download():\n file_remote = 'ftp_upload.jpg'\n file_local = (\n '/home/pi/Desktop/Camera-Rasp-Arduino-sensors/test_download.jpg')\n bufsize = 1024\n fp = open(file_local, 'wb')\n f.re... | [
1,
2,
3,
4,
5
] |
from random import random, randint, choice
from copy import deepcopy
from math import log
"""
Обертка для функций, которые будут находиться в узлах,
представляющих функции. Его члены – имя функции, сама функция
и количество принимаемых параметров.
"""
class fwrapper:
def __init__(self, function, childcou... | normal | {
"blob_id": "89881f3cc6703b3f43f5d2dae87fa943d8a21513",
"index": 5485,
"step-1": "<mask token>\n\n\nclass fwrapper:\n\n def __init__(self, function, childcount, name):\n self.function = function\n self.childcount = childcount\n self.name = name\n\n\n<mask token>\n\n\nclass node:\n\n de... | [
23,
25,
28,
31,
34
] |
# @description Exporting outline (boundary faces) of zsoil results to vtu
# @input zsoil results
# @output vtu unstructured grid
# @author Matthias Preisig
# @date 2017/10/10
import numpy as np
from zsoil_tools import zsoil_results as zr
from zsoil_tools import vtktools
pathname = r'\\192.168.1.51\Mandats sur H RAI... | normal | {
"blob_id": "fb6dd9ec7d8dc80eace90dadc2112c7c27125efd",
"index": 2055,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nres.read_rcf()\nres.read_his()\n<mask token>\nfor kt, step in enumerate(res.steps):\n if step.conv_status in [-1]:\n if step.time in tx:\n tsteps.append(kt)\n<mask to... | [
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
] |
class default_locations:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|... | flexible | {
"blob_id": "b6df9414f99294c7986d3eb5332d40288f059cd1",
"index": 1245,
"step-1": "class default_locations:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <ma... | [
1,
2,
3,
4,
5
] |
# Generated by Django 3.2 on 2021-05-03 17:13
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('orders', '0005_alter_orderitem_price'),
]
operations = [
migrations.AddField(
model_name='order',
name='being_delivere... | normal | {
"blob_id": "f3b466dc5b6149be82b096791ca8445faf169380",
"index": 5216,
"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 = [('orders', '0... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def sortarray(arr):
for i in range(1, len(arr)):
key = arr[i]
j = i - 1
while j >= 0 and arr[j] > key:
arr[j + 1] = arr[j]
j -= 1
arr[j + 1] = key
return arr
<|re... | flexible | {
"blob_id": "70cef88f3fe93d370e5d21a2b00b761ce530a099",
"index": 6366,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef sortarray(arr):\n for i in range(1, len(arr)):\n key = arr[i]\n j = i - 1\n while j >= 0 and arr[j] > key:\n arr[j + 1] = arr[j]\n j ... | [
0,
1,
2,
3
] |
import pytest
from ansiblediscover.graph.node import Node
def test_build_identifier():
assert 'role:server_base' == Node.build_identifier('server_base', 'role')
def test_identifier():
node = Node('server_base', 'role', 'irrelevant')
assert 'role:server_base' == node.identifier()
def test_add_successo... | normal | {
"blob_id": "8e22db940124f92d3048055cf72dcaa79564cdc6",
"index": 1953,
"step-1": "<mask token>\n\n\ndef test_build_identifier():\n assert 'role:server_base' == Node.build_identifier('server_base', 'role')\n\n\ndef test_identifier():\n node = Node('server_base', 'role', 'irrelevant')\n assert 'role:serve... | [
5,
6,
7,
8,
9
] |
# -*- coding: utf-8 -*-
# Copyright (c) 2018, masonarmani38@gmail.com and contributors
# For license information, please see license.txt
from __future__ import unicode_literals
import frappe
from frappe.model.document import Document
class LogisticsPlanningTool(Document):
def autoname(self):
if self.cust... | normal | {
"blob_id": "4cbb78234ef6e63b856099060ecaeea1779d6ac5",
"index": 8412,
"step-1": "<mask token>\n\n\nclass LogisticsPlanningTool(Document):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass LogisticsPlanningTool(Document):\n\n def autoname(self):\n if self.customer:\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def init_process(args):
auto_dir = args.auto_dir
monomer_name = args.monomer_name
os.makedirs(os.path.join(auto_dir, 'gaussian'), exist_ok=True)
os.makedirs(os.path.join(auto_dir, 'gaussview'), exist_ok=True)
def get_init_para_csv(auto_dir, monomer_name):
init... | flexible | {
"blob_id": "961bda96e433bb66d592ad1e99c92db0a9ab9fe9",
"index": 8545,
"step-1": "<mask token>\n\n\ndef init_process(args):\n auto_dir = args.auto_dir\n monomer_name = args.monomer_name\n os.makedirs(os.path.join(auto_dir, 'gaussian'), exist_ok=True)\n os.makedirs(os.path.join(auto_dir, 'gaussview'),... | [
3,
7,
9,
10,
12
] |
<|reserved_special_token_0|>
def test_verify_home_page(eyes, driver):
eyes.open(driver, 'FlyDubai IBE', 'Verify Home Page')
eyes.check('FZ IBE Home page', Target.window())
eyes.close(False)
<|reserved_special_token_0|>
def test_verify_manage_booking_widget(eyes, driver):
eyes.open(driver, 'FlyDuba... | flexible | {
"blob_id": "021efe01c21db4d3bd936ba4eb75dc03dde91cc6",
"index": 1475,
"step-1": "<mask token>\n\n\ndef test_verify_home_page(eyes, driver):\n eyes.open(driver, 'FlyDubai IBE', 'Verify Home Page')\n eyes.check('FZ IBE Home page', Target.window())\n eyes.close(False)\n\n\n<mask token>\n\n\ndef test_verif... | [
4,
5,
6,
7,
8
] |
import os
from unittest import TestCase
class TestMixin(TestCase):
@classmethod
def setUpClass(cls):
cls.base_dir = os.path.dirname(os.path.abspath(__file__))
cls.fixtures_dir = os.path.join(cls.base_dir, 'fixtures')
cls.bam_10xv2_path = os.path.join(cls.fixtures_dir, '10xv2.bam')
... | normal | {
"blob_id": "268a8252f74a2bdafdadae488f98997c91f5607c",
"index": 2686,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestMixin(TestCase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TestMixin(TestCase):\n\n @classmethod\n def setUpClass(cls):\n cls.base_dir = os.pat... | [
0,
1,
2,
3
] |
import numpy as np
import matplotlib.pyplot as plt
import csv
category = ["Ecological Well-being", "Health & Human Services", "Arts & Culture", "Community Building", "Environment"]
arr = np.empty((0, 6), str)
moneyGranted = [[0]*5 for _ in range(6)]
moneyRequested = [[0]*5 for _ in range(6)]
perFull = [[0]*5 f... | normal | {
"blob_id": "e7b2e716fbcaf761e119003000bf1b16af57a2b7",
"index": 7009,
"step-1": "<mask token>\n\n\ndef task5(arr):\n for row in arr:\n moneyGranted[int(row[1]) - 2015][int(row[3]) - 1] += int(row[4])\n moneyRequested[int(row[1]) - 2015][int(row[3]) - 1] += int(row[5])\n for i in range(6):\n ... | [
1,
2,
3,
4,
5
] |
#Function to remove spaces in a string
def remove(string_input):
return string_input.replace(" ", "")
| normal | {
"blob_id": "f327f408ae2759407ac9f01ad4feff5c6a0845f1",
"index": 9524,
"step-1": "<mask token>\n",
"step-2": "def remove(string_input):\n return string_input.replace(' ', '')\n",
"step-3": "#Function to remove spaces in a string\n\ndef remove(string_input):\n return string_input.replace(\" \", \"\")\n"... | [
0,
1,
2
] |
#tkinter：Label 、Button 、标签、按钮
#详见：
#1、os：https://blog.csdn.net/xxlovesht/article/details/80913193
#2、shutil：https://www.jb51.net/article/157891.htm
#3、tkinter：https://blog.csdn.net/mingshao104/article/details/79591965
# https://blog.csdn.net/sinat_41104353/article/details/79313424
# https:/... | normal | {
"blob_id": "6c0ca72d7f5d2373a50cd344991ad9f9e3046e8d",
"index": 4087,
"step-1": "<mask token>\n\n\ndef File_Open_EventC():\n FilePath = filedialog.askopenfilename(filetypes=(('C file', '*.c*'), (\n 'Text file', '*.txt*'), ('HTML files', '*.html;*.htm')))\n fp = open(FilePath, 'r')\n flag_1 = 0\n... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def ya_headers():
return {'Content-type': 'application/json', 'Authorization': 'OAuth {}'
.format(token_ya)}
def put_folder(path):
url = 'https://cloud-api.yandex.net/v1/disk/resources/'
headers = ya_headers()
params = {'path': path, 'url': url}
response = re... | flexible | {
"blob_id": "a22bc3bdb5e35060eff7f523b90d605ff2dd3878",
"index": 9581,
"step-1": "<mask token>\n\n\ndef ya_headers():\n return {'Content-type': 'application/json', 'Authorization': 'OAuth {}'\n .format(token_ya)}\n\n\ndef put_folder(path):\n url = 'https://cloud-api.yandex.net/v1/disk/resources/'\n ... | [
3,
4,
5,
6,
7
] |
# ex: set sts=4 ts=4 sw=4 noet:
# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See COPYING file distributed along with the datalad package for the
# copyright and license terms.
#
# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
"""Test create publ... | normal | {
"blob_id": "035043460805b7fe92e078e05708d368130e3527",
"index": 8965,
"step-1": "<mask token>\n\n\n@with_tempfile\ndef test_invalid_call(path):\n assert_raises(ValueError, create_sibling_github, 'bogus', dataset=path)\n ds = Dataset(path).create()\n assert_raises(gh.BadCredentialsException, ds.create_s... | [
1,
2,
3,
4,
5
] |
#!/usr/bin python
import socket
import json
import threading
import sys
from db_util import DBUtil
from cryptoLib import AesCtr,Hmac
class Client(threading.Thread):
def __init__(self, (client_conn, client_addr), sema):
threading.Thread.__init__(self)
self.client_conn = client_conn
self.client_addr = client_ad... | normal | {
"blob_id": "1338d6578a94338c6e75acc025ddddd14097ee10",
"index": 2044,
"step-1": "#!/usr/bin python\n\nimport socket\nimport json\nimport threading\nimport sys\nfrom db_util import DBUtil\nfrom cryptoLib import AesCtr,Hmac\n\n\nclass Client(threading.Thread):\n\tdef __init__(self, (client_conn, client_addr), sem... | [
0
] |
<|reserved_special_token_0|>
class MRTopVisitorCount(MRJob):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def mapper_sort(self, page, counts):
top = Counter(counts).most_common(1)
yield page, (top[0][0], top[0][1])
def reducer_sort(self, page, visitor_count):
for... | flexible | {
"blob_id": "471ce1eeb3293a424de74e25f36b76699a97ec2b",
"index": 7039,
"step-1": "<mask token>\n\n\nclass MRTopVisitorCount(MRJob):\n <mask token>\n <mask token>\n\n def mapper_sort(self, page, counts):\n top = Counter(counts).most_common(1)\n yield page, (top[0][0], top[0][1])\n\n def ... | [
3,
6,
7,
8,
10
] |
from datetime import date
def solution(mon: int, day: int) -> str:
return date(2016, mon, day).strftime("%a").upper()
| normal | {
"blob_id": "67385d6d58cc79037660be546d41ea9ba1f790fa",
"index": 5043,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef solution(mon: int, day: int) ->str:\n return date(2016, mon, day).strftime('%a').upper()\n",
"step-3": "from datetime import date\n\n\ndef solution(mon: int, day: int) ->str:... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def get_analyse(curse):
"""
要求curse数据中index为时间，columns为策略名称，每一列为该策略净值
"""
qf_drawdown = []
qf_yeild = []
qf_std = []
date = curse.index
y = curse.copy()
for i in curse.columns:
y['max2here'] = y[i].expanding().max(... | flexible | {
"blob_id": "56d90835e64bd80fd9a6bb3a9b414e154d314d4a",
"index": 5108,
"step-1": "<mask token>\n",
"step-2": "def get_analyse(curse):\n \"\"\"\n 要求curse数据中index为时间，columns为策略名称，每一列为该策略净值\n\n \"\"\"\n qf_drawdown = []\n qf_yeild = []\n qf_std = []\n date = curse.index\n y = curse.copy()\... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.... | flexible | {
"blob_id": "422873f89468b1faabed96f72f463b6294b85276",
"index": 5314,
"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
] |
import boto3
import json
from botocore.exceptions import ClientError
# upload_to_s3("abc.png", 1)
def upload_to_s3(file_name, node_number):
try:
key_info_json = open("awsinfo.json").read()
except FileNotFoundError:
print("awsinfo.json is not exist in dir.")
exit(-1)
dat... | normal | {
"blob_id": "2f0d611fecdb5717029938d2ec2cd2db345b8f3a",
"index": 8176,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef upload_to_s3(file_name, node_number):\n try:\n key_info_json = open('awsinfo.json').read()\n except FileNotFoundError:\n print('awsinfo.json is not exist in di... | [
0,
1,
2,
3
] |
/Users/alyssaliguori/anaconda3/lib/python3.7/tokenize.py | normal | {
"blob_id": "601ef4e1000348059dcfe8d34eec5f28368f2464",
"index": 8855,
"step-1": "/Users/alyssaliguori/anaconda3/lib/python3.7/tokenize.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
<|reserved_special_token_0|>
def get_na(dataset):
na_males = dataset[dataset.Sex == 'male'].loc[:, 'AgeGroup'].isnull().sum()
na_females = dataset[dataset.Sex == 'female'].loc[:, 'AgeGroup'].isnull(
).sum()
return {'male': na_males, 'female': na_females}
def get_counts(dataset):
return datas... | flexible | {
"blob_id": "05f143e28ff9c7397376ad598529c1dfb7528ee3",
"index": 7269,
"step-1": "<mask token>\n\n\ndef get_na(dataset):\n na_males = dataset[dataset.Sex == 'male'].loc[:, 'AgeGroup'].isnull().sum()\n na_females = dataset[dataset.Sex == 'female'].loc[:, 'AgeGroup'].isnull(\n ).sum()\n return {'ma... | [
4,
5,
6,
7,
8
] |
##Linear Queue Data Structure
#Main Queue Class
class LinearQueue():
def __init__(self, length):
#When initiating, user defines the length.
#The head and tail pointers are set at -1 (i.e. not pointing to anything, index beginning at zero)
#The queue is set as a series of None objects in a l... | normal | {
"blob_id": "0efac7d9d1a9180eafa8c9c4e3a42b4c68e718a2",
"index": 4597,
"step-1": "class LinearQueue:\n <mask token>\n\n def enqueue(self, *args):\n for i in args:\n if not self.isFull():\n self._tail += 1\n self._queue[self._tail] = i\n else:\n ... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
def read():
file_list = os.listdir(data_path)
result_list = []
for file in file_list:
with open(data_path + file) as f:
content = f.readlines()
dict = {}
dict['title'] = content[0]
dict['name'] = content[1]
di... | flexible | {
"blob_id": "6f1bb9fde9ed9667ab81baa9e8ec965d711a0556",
"index": 9853,
"step-1": "<mask token>\n\n\ndef read():\n file_list = os.listdir(data_path)\n result_list = []\n for file in file_list:\n with open(data_path + file) as f:\n content = f.readlines()\n dict = {}\n ... | [
4,
5,
6,
7,
8
] |
import string
import random
file_one_time_pad = open("encryption_file.txt","r")
p_text = file_one_time_pad.read()
file_one_time_pad.close()
print(p_text)
p_text = str.lower(p_text)
main_text = []
p_text_numerical = []
temp_key = [21,25,20,15,16,14,10,26,24,9,8,13]
alphabets = ['a','b','c','d','e','f','g','h','i','j','... | normal | {
"blob_id": "4b647d37d390a4df42f29bbfc7e4bae4e77c5828",
"index": 8935,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfile_one_time_pad.close()\nprint(p_text)\n<mask token>\nfor i in p_text:\n main_text.append(i)\nfor i in range(length_p_text):\n for j in range(25):\n if main_text[i] == alph... | [
0,
1,
2,
3,
4
] |
from django.db import models
class Professor(models.Model):
nome = models.CharField(max_length=100)
apelido = models.CharField(max_length=30)
descricao = models.TextField(max_length=1000)
def __str__(self):
return self.nome
class ImagemProfessor(models.Model):
professor = models.Foreign... | normal | {
"blob_id": "acb879cb72e5b3ac897a271dc680e4ca763d2122",
"index": 7541,
"step-1": "<mask token>\n\n\nclass ImagemProfessor(models.Model):\n professor = models.ForeignKey(Professor, on_delete=models.CASCADE)\n foto = models.ImageField(upload_to='fotos/%d/%m/%Y/', blank=True)\n",
"step-2": "<mask token>\n\n... | [
2,
3,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def begin_chat(request, id=None):
check = check_if_auth_user(request)
if not check:
messages.error(request, 'Perform login first to start chatting')
return redirect('home:welcome')
current_user = User... | flexible | {
"blob_id": "9dfb3f58127b30467651ac4209277cd947643c65",
"index": 7411,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef begin_chat(request, id=None):\n check = check_if_auth_user(request)\n if not check:\n messages.error(request, 'Perform login first to start chatting')\n return... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('', views.home), path('teams', views.showTeams), path(
'teams/new', views.new), path('teams/<teamname>', views.showSpecificTeam)]
<|reserved_special_token_1|>
from django.urls import path
from . import v... | flexible | {
"blob_id": "e267108177841110493061a4f84ae3d29850d028",
"index": 1853,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', views.home), path('teams', views.showTeams), path(\n 'teams/new', views.new), path('teams/<teamname>', views.showSpecificTeam)]\n",
"step-3": "from django.url... | [
0,
1,
2,
3
] |
from fabric.api import local,run
INSTALL_STEPS = ['yes | sudo apt-get install libmysqlclient-dev python-dev python-mysqldb python-virtualenv',
'virtualenv --no-site-packages env',
'. env/bin/activate;pip install -r requirements.txt']
def deps_local():
for step in INSTALL_STEPS:
... | normal | {
"blob_id": "d64140466e62b78506d0f200f451649023697a3b",
"index": 1386,
"step-1": "<mask token>\n\n\ndef deps_remote():\n for step in INSTALL_STEPS:\n run(step)\n",
"step-2": "<mask token>\n\n\ndef deps_local():\n for step in INSTALL_STEPS:\n local(step)\n\n\ndef deps_remote():\n for step... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.... | flexible | {
"blob_id": "4acdde648b5ec32c078579e725e6ae035298f25a",
"index": 3997,
"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
] |
# SPDX-FileCopyrightText: 2019-2021 Python201 Contributors
# SPDX-License-Identifier: MIT
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path ... | normal | {
"blob_id": "1ead23c6ea4e66b24e60598ae20606e24fa41482",
"index": 1024,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nyear = datetime.datetime.now().year\nproject = 'python201'\ncopyright = f'2019-{year} Geoffrey Lentner, 2018 Ashwin Srinath'\nauthor = 'Geoffrey Lentner, Ashwin Srinath'\nversion = '0.0.1... | [
0,
1,
2,
3
] |
from nltk.tokenize import sent_tokenize
from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer
import networkx as nx
def summarize(text):
sentences_token = sent_tokenize(text)
#Feature Extraction
vectorizer = CountVectorizer(min_df=1,decode_error='replace')
sent_bow = v... | normal | {
"blob_id": "b75ebcd278ae92274bbbe8d1ce5cb3bb7fa14a2c",
"index": 9637,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef summarize(text):\n sentences_token = sent_tokenize(text)\n vectorizer = CountVectorizer(min_df=1, decode_error='replace')\n sent_bow = vectorizer.fit_transform(sentences_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
@pytest.mark.slow
def test_x_noise_reg():
x_train = np.linspace(-3, 3, 300, dtype=np.float32).reshape((300, 1))
noise = tfd.MultivariateNormalDiag(loc=5 * tf.math.sin(2 * x_train),
scale_diag=abs(x_train))
y_train = noise.sample().numpy()
too_much_noise = Normalizi... | flexible | {
"blob_id": "303a8609cb21c60a416160264c3d3da805674920",
"index": 777,
"step-1": "<mask token>\n\n\n@pytest.mark.slow\ndef test_x_noise_reg():\n x_train = np.linspace(-3, 3, 300, dtype=np.float32).reshape((300, 1))\n noise = tfd.MultivariateNormalDiag(loc=5 * tf.math.sin(2 * x_train),\n scale_diag=ab... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class SequenceHeuristic(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class SequenceHeuristic(object):
def __init__(self, minChanges, minDuration, noMotionDelay):
self._minChanges = mi... | flexible | {
"blob_id": "e07bd4cd13209bff8bc1119a619a2954abd52592",
"index": 1515,
"step-1": "<mask token>\n\n\nclass SequenceHeuristic(object):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass SequenceHeuristic(object):\n\n def __init__(self, minChanges, minDuration, noMotionDelay):\n ... | [
1,
2,
3,
4,
5
] |
# Generated by Django 3.2.7 on 2021-09-23 07:33
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('sms_consumer', '0006_auto_20210923_0733'),
]
operations = [
migrations.RemoveField(
model_name='smslogmodel',
name='hello',
... | normal | {
"blob_id": "fc9742ceb3c38a5f8c1ad1f030d76103ba0a7a81",
"index": 3857,
"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 = [('sms_consume... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('testfile_short1.csv', 'r') as original:
data = original.read()
for i in range(2):
with open('testfile_short3.csv', 'a') as modified:
modified.write(data)
<|reserved_special_token_1|>
import pandas as ... | flexible | {
"blob_id": "d7b45e76f150107cd62be160e8938f17dad90623",
"index": 58,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('testfile_short1.csv', 'r') as original:\n data = original.read()\nfor i in range(2):\n with open('testfile_short3.csv', 'a') as modified:\n modified.write(data)\n",
... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def getdata(url):
data = requests.get(url)
return data.text
def get_json():
file_path = staticfiles_storage.path('coordinates.json')
with open(file_path, 'r') as f:
data = json.load(f)
html_doc = getdata('https://www.mygov.in/covid-19')
soup = BeautifulSo... | flexible | {
"blob_id": "ed80f5f898548ca012779543051ccff5b34e4fcc",
"index": 730,
"step-1": "<mask token>\n\n\ndef getdata(url):\n data = requests.get(url)\n return data.text\n\n\ndef get_json():\n file_path = staticfiles_storage.path('coordinates.json')\n with open(file_path, 'r') as f:\n data = json.loa... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class EVALUATOR(object):
def __init__(self, detector, data):
self.detector = detector
self.data = data
self.gt = self.data.gt
self.image_ids, self.bboxes, self.prob, self.annotations = (self.
prepare())
self.precision, self.recall =... | flexible | {
"blob_id": "3bb6305ceb1491db57c7f8b03e438398644c8f90",
"index": 8124,
"step-1": "<mask token>\n\n\nclass EVALUATOR(object):\n\n def __init__(self, detector, data):\n self.detector = detector\n self.data = data\n self.gt = self.data.gt\n self.image_ids, self.bboxes, self.prob, self... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
def funct(string):
dict = {}
for i in string:
if i in dict:
dict[i] += 1
else:
dict[i] = 1
return dict
<|reserved_special_token_0|>
def counter():
string = input('Input your string :')
result = Counter(string)
return resu... | flexible | {
"blob_id": "14807568af046594644095a2682e0eba4f445b26",
"index": 8053,
"step-1": "<mask token>\n\n\ndef funct(string):\n dict = {}\n for i in string:\n if i in dict:\n dict[i] += 1\n else:\n dict[i] = 1\n return dict\n\n\n<mask token>\n\n\ndef counter():\n string =... | [
2,
3,
4,
5,
6
] |
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import numpy as np
import matplotlib.pyplot as plt
import netCDF4
import xarray as xr
import metpy
from datetime import datetime
import datetime as dt
from metpy.units import units
import scipy.ndimage as ndimage
from metpy.plots import USCOUNTIES... | normal | {
"blob_id": "8771f71a69f3afdc5de4d38db6efe61b553ae880",
"index": 9396,
"step-1": "<mask token>\n\n\ndef mkdir_p(mypath):\n \"\"\"Creates a directory. equivalent to using mkdir -p on the command line\"\"\"\n from errno import EEXIST\n from os import makedirs, path\n try:\n makedirs(mypath)\n ... | [
2,
3,
4,
5,
6
] |
import asyncio
import logging
import os
from async_cron.job import CronJob
from async_cron.schedule import Scheduler
from sqlalchemy import asc
import spider
import squid
import verifier
from db import sess_maker
from model import Proxy, STATUS_OK, STATUS_ERROR
from server import run_api_server
from tool import logge... | normal | {
"blob_id": "1d529e2ea5526ddcda0d0da30ed8ed4724002c63",
"index": 7074,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nlogging.basicConfig(level=logging.INFO, datefmt='%Y/%m/%d %H:%M:%S', format\n ='%(asctime)s - %(name)s - %(levelname)s - %(message)s')\n<mask token>\n\n\n@cron_wait\nasync def verify_e... | [
0,
1,
2,
3,
4
] |
from applitools.selenium import Target, eyes
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
def test_verify_home_page(eyes, driver):
eyes.open(driver, "FlyDubai IBE", "Verify Home Page")
eye... | normal | {
"blob_id": "021efe01c21db4d3bd936ba4eb75dc03dde91cc6",
"index": 1475,
"step-1": "<mask token>\n\n\ndef test_verify_home_page(eyes, driver):\n eyes.open(driver, 'FlyDubai IBE', 'Verify Home Page')\n eyes.check('FZ IBE Home page', Target.window())\n eyes.close(False)\n\n\n<mask token>\n\n\ndef test_verif... | [
4,
5,
6,
7,
8
] |
#!/usr/bin/env python
number=int(input("Enter an integer"))
if number<=100:
print("Your number is smaller than equal to 100")
else:
print("Your number is greater than 100")
| normal | {
"blob_id": "9666c87b4d4dc721683ea33fdbbeadefc65a0cd1",
"index": 1860,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif number <= 100:\n print('Your number is smaller than equal to 100')\nelse:\n print('Your number is greater than 100')\n",
"step-3": "number = int(input('Enter an integer'))\nif ... | [
0,
1,
2,
3
] |
from . import preprocess
from . import utils
import random
import pickle
import feather
import time
import datetime
import sys
import os
import numpy as np
import pandas as pd
import json
from ...main import api
from flask import request
from flask_restplus import Resource, fields
import warnings
warnings.simplefilter... | normal | {
"blob_id": "c76fd9b196b50e6fcced7e56517c0cd8ab30e24e",
"index": 7891,
"step-1": "<mask token>\n\n\n@api.route('/predict')\n@api.expect(parser)\nclass Predict(Resource):\n <mask token>\n\n\n@api.route('/predict/<string:companyid>/<string:accountid>')\n@api.expect(parser)\nclass PredictEmployeeByCompany(Resour... | [
6,
7,
8,
10,
15
] |
import seaborn as sns
tips = sns.load_dataset('iris')
sns.violinplot(x='species', y='sepal_length', data=tips, palette='rainbow')
| normal | {
"blob_id": "274af2a0b758472ca4116f1dfa47069647babf57",
"index": 8543,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsns.violinplot(x='species', y='sepal_length', data=tips, palette='rainbow')\n",
"step-3": "<mask token>\ntips = sns.load_dataset('iris')\nsns.violinplot(x='species', y='sepal_length', d... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class BooksaleConfig(AppConfig):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class BooksaleConfig(AppConfig):
name = 'booksale'
<|reserved_special_token_1|>
from django.... | flexible | {
"blob_id": "e642054dad8a2de5b01f2994348e10e9c7574ee0",
"index": 4581,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass BooksaleConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass BooksaleConfig(AppConfig):\n name = 'booksale'\n",
"step-4": "from django.apps import ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for path in sorted(contents):
files_used.append(path.name)
totalFiles += 1
print(files_used)
print(totalFiles)
<|reserved_special_token_0|>
for filename in files_used:
df = pd.read_csv(PATH + folder + filename, sep=';'... | flexible | {
"blob_id": "795936dad7a9e51edf0df66207a43ac4d97e9023",
"index": 3781,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor path in sorted(contents):\n files_used.append(path.name)\n totalFiles += 1\nprint(files_used)\nprint(totalFiles)\n<mask token>\nfor filename in files_used:\n df = pd.read_csv... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def test_resource_not_found(petstore_client):
with pytest.raises(AttributeError) as excinfo:
petstore_client.foo
assert 'foo not found' in str(excinfo.value)
@pytest.fixture
def client_tags_with_spaces():
return SwaggerClient.from_spec({'swagger': '2.0', 'info': {'ve... | flexible | {
"blob_id": "5ee1d8ef7ec4b191e0789ceb9c6dd2d58af526a0",
"index": 7875,
"step-1": "<mask token>\n\n\ndef test_resource_not_found(petstore_client):\n with pytest.raises(AttributeError) as excinfo:\n petstore_client.foo\n assert 'foo not found' in str(excinfo.value)\n\n\n@pytest.fixture\ndef client_tag... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def printBoard(board, pref):
border = '+----+----+----+----+----+----+----+----+'
for row in board:
print(pref, border)
cells = '|'
for cell in row:
if cell == 0:
cell = ' '
elif cell in... | flexible | {
"blob_id": "07e875a24d0e63ef596db57c4ec402f768225eec",
"index": 5103,
"step-1": "<mask token>\n",
"step-2": "def printBoard(board, pref):\n border = '+----+----+----+----+----+----+----+----+'\n for row in board:\n print(pref, border)\n cells = '|'\n for cell in row:\n if... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Voucher(Base):
__tablename__ = 't_juju_voucher'
code = Column(String(100), index=True, unique=True)
serial_no = Column(String(120), index=True, unique=True)
amount = Column(Float, default=0, nullable=False)... | flexible | {
"blob_id": "60d8276a5715899823b12ffdf132925c6f2693bd",
"index": 8675,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Voucher(Base):\n __tablename__ = 't_juju_voucher'\n code = Column(String(100), index=True, unique=True)\n serial_no = Column(String(120), index=True, unique=True)\n ... | [
0,
2,
3,
4,
5
] |
"""
# System of national accounts (SNA)
This is an end-to-end example of national accounts sequence,
from output to net lending. It is based on Russian Federation data
for 2014-2018.
Below is a python session transcript with comments.
You can fork [a github repo](https://github.com/epogrebnyak/sna-ru)
to replica... | normal | {
"blob_id": "2d4187ab5d178efa4920110ccef61c608fdb14c0",
"index": 8780,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef eq(df1, df2, precision=0.5) ->bool:\n \"\"\"Compare two dataframes by element with precision margin.\"\"\"\n return ((df1 - df2).abs() < precision).all()\n\n\n<mask token>\n... | [
0,
2,
3,
4,
5
] |
# -*- 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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def chessKnight(cell):
pivot = 'abcdefgh'
count = 8
for i in range(len(pivot)):
if cell[0] == pivot[i]:
vertical_4, vertical_2 = False, False
if int(cell[1]) == 8 or int(cell[1]) == 1:
vertical_4 = T... | flexible | {
"blob_id": "c1335a8128ad4ba6ce6942e80f3c8b68a4210902",
"index": 6355,
"step-1": "<mask token>\n",
"step-2": "def chessKnight(cell):\n pivot = 'abcdefgh'\n count = 8\n for i in range(len(pivot)):\n if cell[0] == pivot[i]:\n vertical_4, vertical_2 = False, False\n if int(ce... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
# @Author : William
# @Project : TextGAN-william
# @FileName : gan_loss.py
# @Time : Created at 2019-07-11
# @Blog : http://zhiweil.ml/
# @Description :
# Copyrights (C) 2018. All Rights Reserved.
import torch
import torch.nn as nn
import config as cfg
class ... | normal | {
"blob_id": "9cea998d7d5cad3ddc00f667ca06151a938d48a1",
"index": 9424,
"step-1": "<mask token>\n\n\nclass GANLoss(nn.Module):\n <mask token>\n\n def __init__(self, loss_mode, which_net, which_D, target_real_label=1.0,\n target_fake_label=0.0, CUDA=False):\n \"\"\" Initialize the GAN's Discrim... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def renew_commodity_future(year_month: str, contract_kind: str,
main_code_path: str, rar_data_file_path: str, clean_data_path: str,
time_range_path: str, end_date: str, commodity_bool=True):
"""
用于更新月度的商品期货数据
... | flexible | {
"blob_id": "1c2967c26c845281ceb46cc1d8c06768298ef6b6",
"index": 9407,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef renew_commodity_future(year_month: str, contract_kind: str,\n main_code_path: str, rar_data_file_path: str, clean_data_path: str,\n time_range_path: str, end_date: str, comm... | [
0,
1,
2,
3,
4
] |
import logging
from random import randint
import pygame
from flask import Flask, render_template
from flask_ask import Ask, statement, question, session
from playsound import playsound
app = Flask(__name__)
ask = Ask(app, "/")
logging.getLogger("flask_ask").setLevel(logging.DEBUG)
@ask.launch
def new_game():
p... | normal | {
"blob_id": "e4b6304be10ee5a741c8a193dcf65950299ef11a",
"index": 1477,
"step-1": "<mask token>\n\n\n@ask.launch\ndef new_game():\n pygame.mixer.init()\n pygame.mixer.music.load('haha2.mp3')\n pygame.mixer.music.play()\n welcome_msg = render_template('welcome')\n return question(welcome_msg)\n\n\n@... | [
6,
7,
8,
9,
10
] |
import stock as stk
import portfolio as portf
import plot
import sys
import cmd
import os
import decision as des
class CLI(cmd.Cmd):
def __init__(self):
cmd.Cmd.__init__(self)
self.prompt = '$> '
self.stk_data_coll = stk.StockDataCollection()
self.add_to_plot_lst = []
... | normal | {
"blob_id": "d386047c087155b1809d47349339eb6882cf8e26",
"index": 5013,
"step-1": "import stock as stk\nimport portfolio as portf\nimport plot\nimport sys\nimport cmd\nimport os\nimport decision as des\n \n \nclass CLI(cmd.Cmd):\n\n def __init__(self):\n cmd.Cmd.__init__(self)\n self.prompt =... | [
0
] |
#!/usr/bin/env python3
import sys, os
import random
import numpy as np
import matplotlib as mpl
if os.environ.get('DISPLAY','') == '':
print('no display found. Using non-interactive Agg backend')
mpl.use('Agg')
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import sha... | normal | {
"blob_id": "b4454d92ab8380e0eded2f7aed737378e1710c72",
"index": 9413,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif os.environ.get('DISPLAY', '') == '':\n print('no display found. Using non-interactive Agg backend')\n mpl.use('Agg')\n<mask token>\nsys.path.append(path_to_utils)\n<mask token>\n... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for pessoas in range(1, 8):
nasc = int(input(f'Qual sua data de nascimento? {pessoas}º: '))
idade = atual - nasc
if idade >= 21:
totmaior += 1
else:
totmenor += 1
print(f'Ao todo tivemos {totmaior} ... | flexible | {
"blob_id": "f6d7ce2d020d11086640a34aac656098ab0b0f33",
"index": 9495,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor pessoas in range(1, 8):\n nasc = int(input(f'Qual sua data de nascimento? {pessoas}º: '))\n idade = atual - nasc\n if idade >= 21:\n totmaior += 1\n else:\n ... | [
0,
1,
2,
3
] |
from django.conf.urls import url
from .import views
app_name='user'
# user子路由
urlpatterns = [
# user首页
url(r'^$',views.index,name='index'),
# 用户登录
url('login/', views.login, name='login'),
# 用户注册
url('regist/', views.regist, name='regist'),
# 根据id判断用户是否存在
url(r'^getuser\w*/(?P<id>\... | normal | {
"blob_id": "de7b5e44c5c213e4ab70b0f8c0c402edaf4926e0",
"index": 211,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'user'\nurlpatterns = [url('^$', views.index, name='index'), url('login/', views.\n login, name='login'), url('regist/', views.regist, name='regist'), url(\n '^getuser\\\\... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with Session() as ps:
ps.app.runMenuItem(ps.app.stringIDToTypeID('toggleProofColors'))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
from photoshop import Session
with Session() as ps:
ps.app.runMenuItem(ps.... | flexible | {
"blob_id": "1db866ca73bc264d474d5e5086c4a047d7e46546",
"index": 2299,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith Session() as ps:\n ps.app.runMenuItem(ps.app.stringIDToTypeID('toggleProofColors'))\n",
"step-3": "<mask token>\nfrom photoshop import Session\nwith Session() as ps:\n ps.app... | [
0,
1,
2,
3
] |
#-*- coding: UTF-8 -*-
#Author Motuii
'''
* ┏┓ ┏┓
* ┏┛┻━━━┛┻┓
* ┃ ┃
* ┃ ━ ┃
* ┃ ┳┛ ┗┳ ┃
* ┃ ┃
* ┃ ┻ ┃
* ┃ ┃
* ┗━┓ ┏━┛
* ┃ ┃ 神兽保佑
* ┃ ┃ 代码无BUG！
* ┃ ┗━━━┓
* ┃ ┣┓
* ┃ ┏┛
* ┗┓┓┏━┳┓┏┛
* ┃┫┫ ┃┫┫
* ┗┻┛ ┗┻┛
*
'''
n... | normal | {
"blob_id": "131caf50cc8682cf180168a1b136b1dcdd70fa76",
"index": 6837,
"step-1": "#-*- coding: UTF-8 -*-\n#Author Motuii\n'''\n * ┏┓ ┏┓ \n * ┏┛┻━━━┛┻┓ \n * ┃ ┃ \n * ┃ ━ ┃ \n * ┃ ┳┛ ┗┳ ┃ \n * ┃ ┃ \n * ┃ ┻ ┃ \n * ┃ ┃ \n * ┗━┓ ┏━┛ \n * ┃ ┃ 神兽保佑 \n * ┃ ┃ 代码无BUG！ \n ... | [
0
] |
<|reserved_special_token_0|>
def is_printing():
try:
status = http.get('http://' + PRINTER_IP + '/api/v1/printer/status',
timeout=1)
if status.json() == 'printing':
state = http.get('http://' + PRINTER_IP +
'/api/v1/print_job/state', timeout=1).json()
... | flexible | {
"blob_id": "d443e9054481984d5372343170254268dca8a3b1",
"index": 3235,
"step-1": "<mask token>\n\n\ndef is_printing():\n try:\n status = http.get('http://' + PRINTER_IP + '/api/v1/printer/status',\n timeout=1)\n if status.json() == 'printing':\n state = http.get('http://' +... | [
8,
9,
10,
11,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--dir', type=str, required=True)
parser.add_argument('--task', type=str, required=True)
args = parser.parse_args()
if not os.pa... | flexible | {
"blob_id": "dc3a3f5675860792ecfa7dcd5180402d89b669b1",
"index": 8254,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n parser.add_argument('--dir', type=str, required=True)\n parser.add_argument('--task', type=str, required=True)\n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def letterToIndex(letter):
return all_letters.find(letter)
<|reserved_special_token_0|>
class RNN(nn.Module):
def __init__(self, input_size, hidden_size, output_size):
super(RNN, self).__init__()
self.hidden_size = hidden_size
self.i2h = nn.Linear(inpu... | flexible | {
"blob_id": "aa24442624aebeb2777f16a826cf59859d7870ba",
"index": 8744,
"step-1": "<mask token>\n\n\ndef letterToIndex(letter):\n return all_letters.find(letter)\n\n\n<mask token>\n\n\nclass RNN(nn.Module):\n\n def __init__(self, input_size, hidden_size, output_size):\n super(RNN, self).__init__()\n ... | [
6,
7,
10,
11,
13
] |
import zipfile
zzz = zipfile.ZipFile('channel.zip','r')
filestr = '90052'
comment = []
for i in range(1000):
fname = filestr + ".txt"
for j in zzz.infolist():
if j.filename == fname :
print j.comment
comment.append(j.comment)
break
inzzz = zzz.open(fname).read()
print 'fname = ' + fname
... | normal | {
"blob_id": "34ad2e6fc7167766dac1ca962cab40511c89ad68",
"index": 7551,
"step-1": "import zipfile\n\nzzz = zipfile.ZipFile('channel.zip','r')\nfilestr = '90052'\ncomment = []\nfor i in range(1000):\n fname = filestr + \".txt\"\n for j in zzz.infolist():\n if j.filename == fname :\n print j.comment\n ... | [
0
] |
"""
7-4. Pizza Toppings: Write a loop that prompts the user to enter a series of
pizza toppings until they enter a 'quit' value. As they enter each topping,
print a message saying you’ll add that topping to their pizza.
"""
if __name__ == '__main__':
topping = None
while topping != "quit":
if topping:
... | normal | {
"blob_id": "4d07795543989fe481e1141756f988d276f82c02",
"index": 5348,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n topping = None\n while topping != 'quit':\n if topping:\n print(\"I'll add %s to your pizza!\" % topping)\n topping = input(\n ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def _get_user_name():
"""
Get the current user.
"""
return pwd.getpwuid(os.getuid())[0]
def _user_belongs_to(group_name):
"""
Check that the current user belongs to the ``group_name`` group.
"""
user_name = _get_user_name()
groups = _get_user_groups(u... | flexible | {
"blob_id": "e5921edef3d3c56a73f2674f483ea4d1f3577629",
"index": 5186,
"step-1": "<mask token>\n\n\ndef _get_user_name():\n \"\"\"\n Get the current user.\n \"\"\"\n return pwd.getpwuid(os.getuid())[0]\n\n\ndef _user_belongs_to(group_name):\n \"\"\"\n Check that the current user belongs to the ... | [
17,
21,
24,
30,
34
] |
from django.shortcuts import render, redirect
from .models import Courses
from django.views.generic import CreateView, ListView, UpdateView, DeleteView
from .forms import CourceCreateForm
from django.urls import reverse_lazy
from django.urls import reverse
class CourceListView(ListView):
model = Courses
templ... | normal | {
"blob_id": "3340277df91f1421dab8d204eddce65b4604432b",
"index": 369,
"step-1": "<mask token>\n\n\nclass CourceCreateView(CreateView):\n template_name = 'cources/create_cource.html'\n form_class = CourceCreateForm\n success_url = reverse_lazy('cources:cource_list')\n\n\nclass CourceUpdateView(UpdateView... | [
4,
6,
7,
8
] |
<|reserved_special_token_0|>
class Number(Value):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Number(Value):
<|reserved_special_token_0|>
def __str__(self):
return str(self.number)
<|reserved_special_token_1|... | flexible | {
"blob_id": "7da274803de80f2864471d00c9d15aff1103372f",
"index": 3648,
"step-1": "<mask token>\n\n\nclass Number(Value):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Number(Value):\n <mask token>\n\n def __str__(self):\n return str(self.number)\n",
"step-3": "<mask ... | [
1,
2,
3,
4
] |
import tkinter
from tkinter import messagebox
from random import randint
tplyer = 0
tcomp = 0
player = 0
comp = 0
top = tkinter.Tk()
top.resizable(width = False, height =False)
top.geometry("200x100")
def Yes():
global player
global comp
tplayer = randint(1,6)
tcomp = randint(1,6)
message =""
if tplay... | normal | {
"blob_id": "0a5baacf17d33dbf6ea69114a8632f7fcef52c3c",
"index": 9419,
"step-1": "<mask token>\n\n\ndef Yes():\n global player\n global comp\n tplayer = randint(1, 6)\n tcomp = randint(1, 6)\n message = ''\n if tplayer > tcomp:\n message = 'Wygrales!'\n player += 1\n elif tplay... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class Person(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Person(object):
def __init__(self, username):
self.username = username
<|reserved_special_token_0|>
<|reserved_specia... | flexible | {
"blob_id": "6d2bc28e7742f1063a04ae96fc195515ad70598b",
"index": 5666,
"step-1": "<mask token>\n\n\nclass Person(object):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Person(object):\n\n def __init__(self, username):\n self.username = username\n\n\n<mask token>\n",
"st... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def scrape_sas():
pprint('Scraping Events')
get_mtb_events()
pprint('Getting categories and stages')
for event in db.session.query(SASEvent):
pprint(event.event_id)
get_categories_and_stages(event.event_reference, event.event_id)
for event_stage in db.s... | flexible | {
"blob_id": "ecc351cf95254e0bbc5021eff11c500fa0950bd3",
"index": 2653,
"step-1": "<mask token>\n\n\ndef scrape_sas():\n pprint('Scraping Events')\n get_mtb_events()\n pprint('Getting categories and stages')\n for event in db.session.query(SASEvent):\n pprint(event.event_id)\n get_catego... | [
8,
9,
10,
11,
12
] |
import pandas as pd
from bokeh.models import ColumnDataSource, LinearColorMapper, HoverTool
from bokeh.plotting import figure
from bokeh.transform import transform
from sklearn.metrics import confusion_matrix
from reporter.settings import COLORS
from reporter.metrics import Metric
class ConfusionMatrix(Metric):
d... | normal | {
"blob_id": "9a2002b5ff0fe41f2b5b568f4c278d4376bf4fb1",
"index": 6117,
"step-1": "<mask token>\n\n\nclass ConfusionMatrix(Metric):\n <mask token>\n <mask token>\n\n def draw(self, size=400):\n index_label = 'Predicted'\n column_label = 'Actual'\n matrix = self.generate_data()\n ... | [
2,
3,
4,
5,
6
] |
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