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|>
print('Pepito')
print('Cumpleaños: 22 de enero')
<|reserved_special_token_0|>
print('Tengo', edad, 'años')
<|reserved_special_token_0|>
print('Me gusta la música de', cantante)
print('Me gusta cenar', comida)
print('Vivo en', ciudad)
<|reserved_special_toke... | flexible | {
"blob_id": "f26c624e8ae9711eb835e223407256e60dfc6d6e",
"index": 8945,
"step-1": "<mask token>\n",
"step-2": "print('Pepito')\nprint('Cumpleaños: 22 de enero')\n<mask token>\nprint('Tengo', edad, 'años')\n<mask token>\nprint('Me gusta la música de', cantante)\nprint('Me gusta cenar', comida)\nprint('Vivo en', ... | [
0,
1,
2,
3
] |
#/usr/bin/env python3
"""Demonstrates how to do deterministic task generation using l2l"""
import random
def fixed_random(func):
"""Create the data"""
def _func(self, i):
state = random.getstate()
if self.deterministic or self.seed is not None:
random.seed(self.seed + i)
... | normal | {
"blob_id": "7ee5779625d53ff1e18f73b20ba5849666f89b55",
"index": 2111,
"step-1": "<mask token>\n\n\nclass RandomTest:\n\n def __init__(self, seed=42, deterministic=False):\n self.seed = seed\n self.deterministic = deterministic\n\n @fixed_random\n def test_function(self, i):\n retur... | [
3,
4,
6,
7,
8
] |
<|reserved_special_token_0|>
def _build_url(**kargs):
query = {'function': 'TIME_SERIES_DAILY', 'symbol': 'SPY', 'outputsize':
'full', 'datatype': 'json', 'apikey': 'JPIO2GNGBMFRLGMN'}
query.update(kargs)
query_str = '&'.join([f'{key}={val}' for key, val in query.items()])
return f'{url_base}?... | flexible | {
"blob_id": "e99d3ae82d8eea38d29d6c4f09fdb3858e36ca50",
"index": 6518,
"step-1": "<mask token>\n\n\ndef _build_url(**kargs):\n query = {'function': 'TIME_SERIES_DAILY', 'symbol': 'SPY', 'outputsize':\n 'full', 'datatype': 'json', 'apikey': 'JPIO2GNGBMFRLGMN'}\n query.update(kargs)\n query_str = '... | [
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
from __future__ import print_function
"""phy main CLI tool.
Usage:
phy --help
"""
#------------------------------------------------------------------------------
# Imports
#------------------------------------------------------------------------------
import sys
import os.path as op
im... | normal | {
"blob_id": "539523f177e2c3c0e1fb0226d1fcd65463b68a0e",
"index": 6576,
"step-1": "<mask token>\n\n\nclass Parser(argparse.ArgumentParser):\n\n def error(self, message):\n sys.stderr.write(message + '\\n\\n')\n self.print_help()\n sys.exit(2)\n\n\n<mask token>\n\n\nclass ParserCreator(obje... | [
17,
18,
29,
30,
32
] |
import random
import datetime
import os
import time
import json
#
l_target_path = "E:/code/PYTHON_TRAINING/Training/Apr2020/BillingSystem/bills/"
while True:
l_store_id = random.randint(1, 4)
now = datetime.datetime.now()
l_bill_id = now.strftime("%Y%m%d%H%M%S")
# Generate Random Date
start_da... | normal | {
"blob_id": "fad2ad89e4d0f04fad61e27048397a5702870ca9",
"index": 6177,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n l_store_id = random.randint(1, 4)\n now = datetime.datetime.now()\n l_bill_id = now.strftime('%Y%m%d%H%M%S')\n start_date = datetime.date(2000, 1, 1)\n end_da... | [
0,
1,
2,
3,
4
] |
from __future__ import annotations
from typing import TYPE_CHECKING
import abc
import tcod.event
if TYPE_CHECKING:
from tcodplus.canvas import Canvas
from tcodplus.event import CanvasDispatcher
class IDrawable(abc.ABC):
@property
@abc.abstractmethod
def force_redraw(self) -> bool:
pass
... | normal | {
"blob_id": "e37f958191c9481c6664e90c17f43419a0b5b606",
"index": 8131,
"step-1": "<mask token>\n\n\nclass IDrawable(abc.ABC):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass IFocusable(abc.ABC):\n\n @property\n @abc.abstractmethod\n def focus_dispatcher(self) ->CanvasD... | [
14,
15,
17,
18,
21
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
bw2_schema = Schema(name=TEXT(stored=True, sortable=True), comment=TEXT(
stored=True), product=TEXT(stored=True, sortable=True), categories=TEXT
(stored=True), location=TEXT(stored=True, sortable=True), database=TEXT
(... | flexible | {
"blob_id": "07aafcb3db9c57ad09a29a827d72744ef0d22247",
"index": 3319,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nbw2_schema = Schema(name=TEXT(stored=True, sortable=True), comment=TEXT(\n stored=True), product=TEXT(stored=True, sortable=True), categories=TEXT\n (stored=True), location=TEXT(sto... | [
0,
1,
2,
3
] |
#! /usr/bin/env python
t = int(raw_input())
for i in xrange(1, t+1):
N = raw_input()
N1 = N
track = set()
if N == '0':
print "Case #%s: " % i + "INSOMNIA"
continue
count = 2
while len(track) !=10:
temp = set(x for x in N1)
track = temp | track
N1 = str(co... | normal | {
"blob_id": "8c6b7032c85354740d59aa91108ad8b5279e1d45",
"index": 2570,
"step-1": "#! /usr/bin/env python\n\nt = int(raw_input())\nfor i in xrange(1, t+1):\n N = raw_input()\n N1 = N\n track = set()\n if N == '0':\n print \"Case #%s: \" % i + \"INSOMNIA\"\n continue\n count = 2\n w... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if minutos > 800:
total = minutos * 0.08
elif minutos > 400 and minutos <= 800:
total = minutos * 0.15
elif minutos < 200:
total = minutos * 0.2
else:
total = minutos * 0.18
print('Valor da conta: R$ %.2f' % total)... | flexible | {
"blob_id": "1b3e64be988495454535ca96c7a1b6c20aa27076",
"index": 2648,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif minutos > 800:\n total = minutos * 0.08\nelif minutos > 400 and minutos <= 800:\n total = minutos * 0.15\nelif minutos < 200:\n total = minutos * 0.2\nelse:\n total = minut... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def find_and_display_patter_in_series(*, series, pattern):
"""I used that function when i don't remeber full name of a given column"""
res = series.loc[series.str.contains(pattern)]
return res
<|reserved_special_token_0|>
def find_patter_in_series(*, s, pat, tolist=True):
... | flexible | {
"blob_id": "5f50b20bd044471ebb8e1350d1a75a250b255d8f",
"index": 8854,
"step-1": "<mask token>\n\n\ndef find_and_display_patter_in_series(*, series, pattern):\n \"\"\"I used that function when i don't remeber full name of a given column\"\"\"\n res = series.loc[series.str.contains(pattern)]\n return res... | [
4,
5,
7,
8,
10
] |
botName = "firstBot"
username = "mrthemafia"
password = "oblivion"
client_id = "Y3LQwponbEp07w"
client_secret = "R4oyCEj6hSTJWHfWMwb-DGUOBm8"
| normal | {
"blob_id": "3031f695d57492cf3b29694fecd0a41c469a3e00",
"index": 7481,
"step-1": "<mask token>\n",
"step-2": "botName = 'firstBot'\nusername = 'mrthemafia'\npassword = 'oblivion'\nclient_id = 'Y3LQwponbEp07w'\nclient_secret = 'R4oyCEj6hSTJWHfWMwb-DGUOBm8'\n",
"step-3": "botName = \"firstBot\"\nusername = \"m... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class Net(torch.nn.Module):
def __init__(self, n_feature, n_hidden, n_output):
super(Net, self).__init__()
self.hidden = torch.nn.Linear(n_feature, n_hidden)
self.predict = torch.nn.Linear(n_hidden, n_output)
def forward(self, x):
h1 = F.relu(self... | flexible | {
"blob_id": "e221553f866de8b3e175197a40982506bf8c1ef9",
"index": 205,
"step-1": "<mask token>\n\n\nclass Net(torch.nn.Module):\n\n def __init__(self, n_feature, n_hidden, n_output):\n super(Net, self).__init__()\n self.hidden = torch.nn.Linear(n_feature, n_hidden)\n self.predict = torch.n... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class GameManager:
def __init__(self):
self.screen = pygame.display.set_mode((1280, 720), flags=pygame.
FULLSCREEN | pygame.HWSURFACE | pygame.DOUBLEBUF)
self.running = True
self.delta_time = 1
self.active_scene = None
self.load_sce... | flexible | {
"blob_id": "91806afea92587476ac743346b88098b197a033c",
"index": 9706,
"step-1": "<mask token>\n\n\nclass GameManager:\n\n def __init__(self):\n self.screen = pygame.display.set_mode((1280, 720), flags=pygame.\n FULLSCREEN | pygame.HWSURFACE | pygame.DOUBLEBUF)\n self.running = True\n... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class Autorization:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class AutorizationClient(Autorization):
"""
Manejo de autorizaciones de clientes,
se listan los clientes, en orden de pendiente,
aprobado y ... | flexible | {
"blob_id": "b78ad3a55eb27fd91f89c22db07fadca297640ab",
"index": 2892,
"step-1": "<mask token>\n\n\nclass Autorization:\n <mask token>\n <mask token>\n <mask token>\n\n\nclass AutorizationClient(Autorization):\n \"\"\"\n Manejo de autorizaciones de clientes,\n se listan los clientes, en... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def is_even(a):
check_integer(a)
if a % 2 == 0:
print('true')
return True
else:
print('false')
return False
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def check_int... | flexible | {
"blob_id": "92391f17380b2e09cc9b3913f15ce35189d9893d",
"index": 8241,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef is_even(a):\n check_integer(a)\n if a % 2 == 0:\n print('true')\n return True\n else:\n print('false')\n return False\n\n\n<mask token>\n",
... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(100):
numero = int(input('Digite um valor:'))
if numero % 2 == 0:
contador_pares += 1
else:
contador_impares += 1
print('A quantidade de números pares é igual a:', contador_pares)
print('... | flexible | {
"blob_id": "03aa33861def30a46de85c5b309878a1180a760f",
"index": 5211,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(100):\n numero = int(input('Digite um valor:'))\n if numero % 2 == 0:\n contador_pares += 1\n else:\n contador_impares += 1\nprint('A quantidade de n... | [
0,
1,
2
] |
import torch
import numpy as np
# source: https://github.com/krasserm/bayesian-machine-learning/blob/master/gaussian_processes.ipynb
def kernel(X1, X2, l=1.0, sigma_f=1.0):
''' Isotropic squared exponential kernel. Computes a covariance matrix from points in X1 and X2. Args: X1: Array of m points (m x d). X2: Arr... | normal | {
"blob_id": "82c3bde5746d04c126a93851844f775e7ce65f4b",
"index": 9442,
"step-1": "<mask token>\n\n\nclass CNP(torch.nn.Module):\n <mask token>\n <mask token>\n\n\nclass ANP(torch.nn.Module):\n\n def __init__(self, in_dim, hidden_dim, query_dim, out_dim, en_layer,\n dec_layer, nhead):\n sup... | [
7,
8,
9,
10,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class GetInTouchForm(forms.ModelForm):
class Meta:
model = GetInTouch
fields = '__all__'
<|reserved_special_token_1|>
from django import forms
from .models import GetInTouch
class GetInTouchForm(forms.... | flexible | {
"blob_id": "c8dc143c09aa7f677167a4942ae1c4a0fbf75128",
"index": 3219,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass GetInTouchForm(forms.ModelForm):\n\n\n class Meta:\n model = GetInTouch\n fields = '__all__'\n",
"step-3": "from django import forms\nfrom .models import GetI... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def md5_hexdigest(data):
return hashlib.md5(data.encode('utf-8')).hexdigest()
def sha1_hexdigest(data):
return hashlib.sha1(data.encode('utf-8')).hexdigest()
def sha224_hexdigest(data):
return hashlib.sha224(data.encode('utf-8')).hexdigest()
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "35a95c49c2dc09b528329433a157cf313cf59667",
"index": 8955,
"step-1": "<mask token>\n\n\ndef md5_hexdigest(data):\n return hashlib.md5(data.encode('utf-8')).hexdigest()\n\n\ndef sha1_hexdigest(data):\n return hashlib.sha1(data.encode('utf-8')).hexdigest()\n\n\ndef sha224_hexdigest(data):\n re... | [
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def reorderAssetsByTypes(nodePath, colorNode=True, alignNode=True):
node = hou.pwd()
def getNaskCasting():
path = 'E:/WIP/Work/casting-nask.csv'
file = open(path, 'r')
fileText = file.readlines()
file.close()
f... | flexible | {
"blob_id": "3073850890eb7a61fb5200c5ab87c802cafe50bb",
"index": 7229,
"step-1": "<mask token>\n",
"step-2": "def reorderAssetsByTypes(nodePath, colorNode=True, alignNode=True):\n node = hou.pwd()\n\n def getNaskCasting():\n path = 'E:/WIP/Work/casting-nask.csv'\n file = open(path, 'r')\n ... | [
0,
1,
2,
3
] |
#! /usr/bin/python
from bs4 import BeautifulSoup
import requests
import sys
def exit(err):
print err
sys.exit(0)
def get_text(node, lower = True):
if lower:
return (''.join(node.findAll(text = True))).strip().lower()
return (''.join(node.findAll(text = True))).strip()
def get_method_signatu... | normal | {
"blob_id": "e3119979028d3dd4e1061563db4ec20607e744d1",
"index": 3749,
"step-1": "#! /usr/bin/python\n\nfrom bs4 import BeautifulSoup\n\nimport requests\nimport sys\n\ndef exit(err):\n print err\n sys.exit(0)\n\ndef get_text(node, lower = True):\n if lower:\n return (''.join(node.findAll(text = T... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Config(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|re... | flexible | {
"blob_id": "c27c2df1830f066ca4f973c46967722869090d05",
"index": 1373,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Config(object):\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>... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Solution:
def maxArea(self, h: int, w: int, horizontalCuts: List[int],
verticalCuts: List[int]) ->int:
horizontalCuts.sort()
verticalCuts.sort()
horizontalCuts.append(h)
verticalCuts.append(w)
hbreadth = 0
prev = 0
... | flexible | {
"blob_id": "8fb559810fbf79f0849ed98e51d3f2ad1ccc4b8b",
"index": 8296,
"step-1": "<mask token>\n\n\nclass Solution:\n\n def maxArea(self, h: int, w: int, horizontalCuts: List[int],\n verticalCuts: List[int]) ->int:\n horizontalCuts.sort()\n verticalCuts.sort()\n horizontalCuts.appe... | [
2,
3,
4,
5,
6
] |
from web3 import Web3, HTTPProvider, IPCProvider
from tcmb.tcmb_parser import TCMB_Processor
from ecb.ecb_parser import ECB_Processor
from web3.contract import ConciseContract
from web3.middleware import geth_poa_middleware
import json
import time
tcmb_currencies = ["TRY", "USD", "AUD", "DKK", "EUR", "GBP", "CHF", "SE... | normal | {
"blob_id": "ecd5097d9d497b62b89217ee3c46506f21fc15d2",
"index": 5065,
"step-1": "<mask token>\n\n\ndef epoch_day(epoch_time):\n epoch_time = int(epoch_time)\n return epoch_time - epoch_time % 86400\n\n\n<mask token>\n\n\ndef add_ecb():\n unix_time = Web3.toInt(epoch_day(time.time()))\n ECB = ECB_Pro... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
def countVowels(string):
count = 0
vowels = ['a', 'e', 'i', 'o', 'u', 'y']
for vowel in vowels:
count += string.count(vowel)
return count
<|reserved_special_token_0|>
def isPalindrome(string):
return reverse(string) == string
def main():
count = 5
... | flexible | {
"blob_id": "d60690892eddda656c11470aacd1fdc9d07a721a",
"index": 3563,
"step-1": "<mask token>\n\n\ndef countVowels(string):\n count = 0\n vowels = ['a', 'e', 'i', 'o', 'u', 'y']\n for vowel in vowels:\n count += string.count(vowel)\n return count\n\n\n<mask token>\n\n\ndef isPalindrome(string... | [
3,
4,
5,
6,
7
] |
import os
import sys
sys.path.append(os.path.join(os.path.dirname(__file__), '../tools'))
import files
import genetics
def main(argv):
S = files.read_lines(argv[0])
S_rc = [genetics.dna_complement(s) for s in S]
S_u = set(S + S_rc)
B_k = []
for s in S_u:
B_k.append((s[:-1], s[1:]))... | normal | {
"blob_id": "b616b907eb67fff97d57ee2b0d3ab8e01d154956",
"index": 2038,
"step-1": "import os\nimport sys\nsys.path.append(os.path.join(os.path.dirname(__file__), '../tools'))\n\nimport files\nimport genetics\n\n\ndef main(argv):\n S = files.read_lines(argv[0])\n S_rc = [genetics.dna_complement(s) for s i... | [
0
] |
# -*- coding: utf-8 -*-
#
# File: PatrimonyCertificate.py
#
# Copyright (c) 2015 by CommunesPlone
# Generator: ArchGenXML Version 2.7
# http://plone.org/products/archgenxml
#
# GNU General Public License (GPL)
#
__author__ = """Gauthier BASTIEN <gbastien@commune.sambreville.be>, Stephan GEULETTE
<stephan.ge... | normal | {
"blob_id": "6c0b2fa8166bb21a514dc188858e1de285ad9b0a",
"index": 166,
"step-1": "<mask token>\n\n\nclass PatrimonyCertificate(BaseFolder, GenericLicence, Inquiry,\n BrowserDefaultMixin):\n <mask token>\n security = ClassSecurityInfo()\n implements(interfaces.IPatrimonyCertificate)\n meta_type = 'P... | [
6,
8,
9,
10,
12
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
import base64
import json
import os
import re
import subprocess
import time
import traceback
import zipfile
from datetime import datetime
import requests
from flask import request, current_app
from library.oss import oss_upload_monkey_package_picture
from public_config import... | normal | {
"blob_id": "bf45349a9fdfcef7392c477e089c5e3916cb4c8e",
"index": 8502,
"step-1": "<mask token>\n\n\nclass ToolBusiness(object):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ToolBusiness(object):\n\n @classmethod\n def get_tool_ip(cls):\n ip = request.args.get('ip')\n ... | [
1,
2,
3,
4,
5
] |
import inspect
import re
import openquake.hazardlib.source as oqsrc
# List of valid attributes for an area source
AREAS_ATTRIBUTES = set(['source_id',
'name',
'tectonic_region_type',
'mfd',
'rupture_mesh_spacing',
'magnitude_scaling_relationship',
... | normal | {
"blob_id": "8adf8cfc72d5af955bf7509d3573a9bcc7c0845e",
"index": 7537,
"step-1": "<mask token>\n\n\nclass OQtSource(object):\n <mask token>\n\n def __init__(self, *args, **kwargs):\n if len(args):\n self.source_id = args[0]\n if len(args) > 1:\n self.source_type ... | [
2,
4,
5,
7,
8
] |
from collections import Counter, defaultdict
from random import randrange
from copy import deepcopy
import sys
def election(votes, message=True, force_forward=False):
votes = deepcopy(votes)
N = len(votes)
for i in range(N):
obtained = Counter([v[-1] for v in votes if len(v)]).most_common()
... | normal | {
"blob_id": "05764d1cfd9573616fcd6b125280fddf2e5ce7ad",
"index": 3712,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef election(votes, message=True, force_forward=False):\n votes = deepcopy(votes)\n N = len(votes)\n for i in range(N):\n obtained = Counter([v[-1] for v in votes if l... | [
0,
1,
2,
3,
4
] |
import flask
import flask_sqlalchemy
app = flask.Flask(__name__)
app.config.from_pyfile('settings.py')
db = flask_sqlalchemy.SQLAlchemy(app)
| normal | {
"blob_id": "2ed0ae48e8fec2c92effcbb3e495a1a9f4636c27",
"index": 6777,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp.config.from_pyfile('settings.py')\n<mask token>\n",
"step-3": "<mask token>\napp = flask.Flask(__name__)\napp.config.from_pyfile('settings.py')\ndb = flask_sqlalchemy.SQLAlchemy(app... | [
0,
1,
2,
3
] |
{
'variables': {
'node_shared_openssl%': 'true'
},
'targets': [
{
'target_name': 'keypair',
'sources': [
'secp256k1/keypair.cc'
],
'conditions': [
# For Windows, require either a 32-bit or 64-bit
# separately-compiled OpenSSL library.
# Currently set up to ... | normal | {
"blob_id": "e7b30353fd25beb9d5cdeee688e4ffa6955d4221",
"index": 8437,
"step-1": "<mask token>\n",
"step-2": "{'variables': {'node_shared_openssl%': 'true'}, 'targets': [{'target_name':\n 'keypair', 'sources': ['secp256k1/keypair.cc'], 'conditions': [[\n 'OS==\"win\"', {'conditions': [['target_arch==\"x6... | [
0,
1,
2
] |
#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
] |
<|reserved_special_token_0|>
def write(output_filename, content):
with open(output_filename, 'w') as outfile:
outfile.write(content)
def main(argv):
"""
WebPerf Core Carbon Percentiles
Usage:
* run webperf-core test on all websites you want to use for your percentiles (with json as out... | flexible | {
"blob_id": "a801ca6ae90556d41fd278032af4e58a63709cec",
"index": 7977,
"step-1": "<mask token>\n\n\ndef write(output_filename, content):\n with open(output_filename, 'w') as outfile:\n outfile.write(content)\n\n\ndef main(argv):\n \"\"\"\n WebPerf Core Carbon Percentiles\n\n\n Usage:\n * ru... | [
2,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('Seu número é {} seu antecessor é {} e seu sucessor é {}'.format(n, m, o)
)
<|reserved_special_token_1|>
n = int(input('Digite um número'))
m = n - 1
o = n + 1
print('Seu número é {} seu antecessor é {} e seu sucessor... | flexible | {
"blob_id": "47d72379b894826dad335f098649702ade195f78",
"index": 7337,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Seu número é {} seu antecessor é {} e seu sucessor é {}'.format(n, m, o)\n )\n",
"step-3": "n = int(input('Digite um número'))\nm = n - 1\no = n + 1\nprint('Seu número é {} se... | [
0,
1,
2,
3
] |
# vim: expandtab
# -*- coding: utf-8 -*-
from poleno.utils.template import Library
from chcemvediet.apps.obligees.models import Obligee
register = Library()
@register.simple_tag
def gender(gender, masculine, feminine, neuter, plurale):
if gender == Obligee.GENDERS.MASCULINE:
return masculine
elif gen... | normal | {
"blob_id": "c9d12f14fa0e46e4590746d45862fe255b415a1d",
"index": 396,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@register.simple_tag\ndef gender(gender, masculine, feminine, neuter, plurale):\n if gender == Obligee.GENDERS.MASCULINE:\n return masculine\n elif gender == Obligee.GENDE... | [
0,
1,
2,
3,
4
] |
import asyncio
import logging
from datetime import datetime
from discord.ext import commands
from discord.ext.commands import Bot, Context
from humanize import precisedelta
from sqlalchemy.exc import SQLAlchemyError
from sqlalchemy_utils import ScalarListException
from config import CONFIG
from models import Reminder... | normal | {
"blob_id": "0f54853901a26b66fe35106593ded6c92785b8db",
"index": 2682,
"step-1": "<mask token>\n\n\nclass Reminders(commands.Cog):\n\n def __init__(self, bot: Bot):\n self.bot = bot\n self.bot.loop.create_task(reminder_check(self.bot))\n\n @commands.group(help=LONG_HELP_TEXT, brief=SHORT_HELP... | [
3,
4,
5,
6,
7
] |
"""
Main CLI endpoint for GeoCube
"""
import importlib.metadata
import click
from click import group
import geocube.cli.commands as cmd_modules
from geocube import show_versions
CONTEXT_SETTINGS = {
"help_option_names": ["-h", "--help"],
"token_normalize_func": lambda x: x.replace("-", "_"),
}
def check_ve... | normal | {
"blob_id": "0964121d88fad2906311de7532eac52ff784fff6",
"index": 8306,
"step-1": "<mask token>\n\n\ndef check_version(ctx, _, value):\n \"\"\"\n Print current version, and check for latest version.\n\n Called via 'geocube --version'\n\n :param ctx: Application context object (click.Context)\n :par... | [
4,
5,
6,
7,
8
] |
# -*- coding: utf-8 -*-
"""Digital Forensics Virtual File System (dfVFS).
dfVFS, or Digital Forensics Virtual File System, is a Python module
that provides read-only access to file-system objects from various
storage media types and file formats.
"""
| normal | {
"blob_id": "f7d3096d669946e13186a893ffc53067e0fd0a0a",
"index": 1065,
"step-1": "<mask token>\n",
"step-2": "# -*- coding: utf-8 -*-\n\"\"\"Digital Forensics Virtual File System (dfVFS).\n\ndfVFS, or Digital Forensics Virtual File System, is a Python module\nthat provides read-only access to file-system objec... | [
0,
1
] |
import sys
minus = "-"
plus = "+"
divis = "/"
multi = "*"
power = "^"
unary = "-"
br_op = "("
br_cl = ")"
operations = [power, divis, multi, minus, plus]
digits = ['1','2','3','4','5','6','7','8','9','0','.']
def find_close_pos(the_string):
open_count = 0
close_count = 0
for i in range(len(the_string)):
if the... | normal | {
"blob_id": "c0c8f40e43f1c27f8efa47cfc366c6076b77b9c9",
"index": 9337,
"step-1": "import sys\n\nminus = \"-\"\nplus = \"+\"\ndivis = \"/\"\nmulti = \"*\"\npower = \"^\"\nunary = \"-\"\nbr_op = \"(\"\nbr_cl = \")\"\n\noperations = [power, divis, multi, minus, plus]\ndigits = ['1','2','3','4','5','6','7','8','9',... | [
0
] |
class Node:
<|reserved_special_token_0|>
class Solution(object):
def postorder(self, root):
"""
:type root: Node
:rtype: List[int]
"""
if not root:
return []
if not root.children:
return [root.val]
result = []
for child i... | flexible | {
"blob_id": "93ec15a37bd5f022e8f6e226e3bf0e91cc0457c6",
"index": 2178,
"step-1": "class Node:\n <mask token>\n\n\nclass Solution(object):\n\n def postorder(self, root):\n \"\"\"\n :type root: Node\n :rtype: List[int]\n \"\"\"\n if not root:\n return []\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
def get_paths(debug, dataset):
if debug and dataset == 'OASIS':
project_wd = os.getcwd()
project_data = os.path.join(project_wd, 'data')
project_sink = os.path.join(project_data, 'output')
elif debug and dataset == 'BANC':
project_wd = os.getcwd()
... | flexible | {
"blob_id": "2e9d71b8055e1bab107cedae69ca3bc4219e7d38",
"index": 7460,
"step-1": "<mask token>\n\n\ndef get_paths(debug, dataset):\n if debug and dataset == 'OASIS':\n project_wd = os.getcwd()\n project_data = os.path.join(project_wd, 'data')\n project_sink = os.path.join(project_data, 'o... | [
16,
17,
18,
21,
23
] |
<|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_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "2c1ea45d3c7ee822ec58c2fadaf7fc182acc4422",
"index": 9264,
"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 = [('api', '0001... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ROUTE_LIST = [webapp2.Route('/api/history<name:/(?:[a-zA-Z0-9_-]+/?)*>',
handler=handlers.HistoryApi, name='historyApi'), webapp2.Route(
'/api<name:/(?:[a-zA-Z0-9_-]+/?)*>', handler=handlers.PageApi, name=
'pageApi'), ... | flexible | {
"blob_id": "a61bc654eecb4e44dce3e62df752f80559a2d055",
"index": 9184,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nROUTE_LIST = [webapp2.Route('/api/history<name:/(?:[a-zA-Z0-9_-]+/?)*>',\n handler=handlers.HistoryApi, name='historyApi'), webapp2.Route(\n '/api<name:/(?:[a-zA-Z0-9_-]+/?)*>', han... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def cameras_get_info():
"""
cameras_get_info - reads the camera info from the XML file and
puts it into a python data structure and returns it.
"""
status = 0
xmldoc = minidom.parse(CAMERA_XML_FILE)
i... | flexible | {
"blob_id": "510d411d79d5df8658703241f161b3e2a9ec5932",
"index": 4110,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef cameras_get_info():\n \"\"\"\n cameras_get_info - reads the camera info from the XML file and\n puts it into a python data structure and returns it.\n \"\"\"\n stat... | [
0,
1,
2,
3,
4
] |
# Given a string S, find the longest palindromic substring in S. You may assume that the maximum length of S is 1000, and there exists one unique longest palindromic substring.
class Solution(object):
def longestPalindrome(self, s):
"""
:type s: str
:rtype: str
"""
if len(s)... | normal | {
"blob_id": "7c39b3927bc0702818c54875785b4657c20c441e",
"index": 2272,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n",
"step-3": "class Solution(object):\n\n def longestPalindrome(self, s):\n \"\"\"\n :type s: str\n :rtype: str\n \"\"\"\n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def ConfigObject(config_path):
"""read a configuration file to retrieve access token"""
configDict = {}
with open(config_path, 'r') as config:
for line in config.readlines():
try:
configDict[line.split('=')[0]] = line.split('=')[1].rstrip()
... | flexible | {
"blob_id": "e76ebbe8dab2e5169ef40b559f783c49ba4de825",
"index": 1750,
"step-1": "<mask token>\n\n\ndef ConfigObject(config_path):\n \"\"\"read a configuration file to retrieve access token\"\"\"\n configDict = {}\n with open(config_path, 'r') as config:\n for line in config.readlines():\n ... | [
3,
4,
5,
6,
7
] |
from django import template
from ..models import Article
# 得到django 负责管理标签和过滤器的类
register = template.Library()
@register.simple_tag
def getlatestarticle():
latearticle = Article.objects.all().order_by("-atime")
return latearticle | normal | {
"blob_id": "804c75b3ab0b115e5187d44e4d139cfb553269a9",
"index": 6791,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@register.simple_tag\ndef getlatestarticle():\n latearticle = Article.objects.all().order_by('-atime')\n return latearticle\n",
"step-3": "<mask token>\nregister = template.Li... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def prep_folder(args):
""" Append to slash to filepath if needed, and generate folder if it doesn't exist"""
if args.save_folder[-1] != '/':
args.save_folder += '/'
if not os.path.isdir(args.save_folder):
... | flexible | {
"blob_id": "18be97061c65185fcebf10c628e0e51bb08522cf",
"index": 3609,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef prep_folder(args):\n \"\"\" Append to slash to filepath if needed, and generate folder if it doesn't exist\"\"\"\n if args.save_folder[-1] != '/':\n args.save_folder ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while True:
o = sys.stdin.read(byte)
if qlty > qlty * n % 1:
oo = o
sys.stdout.write(o)
else:
sys.stdout.write(oo)
if not o:
break
n = n + 1
<|reserved_special_token_1|>
<|res... | flexible | {
"blob_id": "70845ab4aab80d988a5c01d0b4fb76e63b800527",
"index": 6484,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n o = sys.stdin.read(byte)\n if qlty > qlty * n % 1:\n oo = o\n sys.stdout.write(o)\n else:\n sys.stdout.write(oo)\n if not o:\n break\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def process_frame(img):
global vid_data
img = cv2.resize(img, (w, h))
cv2.imshow('Frame', img)
cv2.waitKey(1)
vid_data = np.append(vid_data, img, axis=0)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def process_frame(img... | flexible | {
"blob_id": "eb81b0e41743e1785b82e88f6a618dc91eba73e5",
"index": 1389,
"step-1": "<mask token>\n\n\ndef process_frame(img):\n global vid_data\n img = cv2.resize(img, (w, h))\n cv2.imshow('Frame', img)\n cv2.waitKey(1)\n vid_data = np.append(vid_data, img, axis=0)\n\n\n<mask token>\n",
"step-2": ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class AuthorizationError(ValueError):
pass
class BearerTokenValidator:
def __init__(self, access_token, app_context: AppContext):
self.access_token = access_token
user_service = app_context.user_service
self.blacklist_token_repo = app_context.blacklist_t... | flexible | {
"blob_id": "97d4387c7bfd141b5a7019b221adb550105d4351",
"index": 604,
"step-1": "<mask token>\n\n\nclass AuthorizationError(ValueError):\n pass\n\n\nclass BearerTokenValidator:\n\n def __init__(self, access_token, app_context: AppContext):\n self.access_token = access_token\n user_service = a... | [
10,
12,
17,
19,
21
] |
import csv
with open('./csvs/users.csv', encoding='utf-8', newline='') as users_csv:
reader = csv.reader(users_csv)
d = {}
for row in reader:
userId, profileName = row
if profileName == 'A Customer':
continue
value = d.get(profileName)
if not value:
d... | normal | {
"blob_id": "3b77f7ea5137174e6723368502659390ea064c5a",
"index": 8968,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('./csvs/users.csv', encoding='utf-8', newline='') as users_csv:\n reader = csv.reader(users_csv)\n d = {}\n for row in reader:\n userId, profileName = row\n ... | [
0,
1,
2,
3
] |
# coding: utf-8
import logging
def __gen_logger():
result = logging.getLogger('superslick')
return result
logger = __gen_logger() | normal | {
"blob_id": "cee9deeeabfec46ee5c132704e8fd653e55987f3",
"index": 3430,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef __gen_logger():\n result = logging.getLogger('superslick')\n return result\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef __gen_logger():\n result = logging.get... | [
0,
1,
2,
3,
4
] |
"""
stanCode Breakout Project
Adapted from Eric Roberts's Breakout by
Sonja Johnson-Yu, Kylie Jue, Nick Bowman,
and Jerry Liao
YOUR DESCRIPTION HERE
"""
from campy.gui.events.timer import pause
from breakoutgraphics import BreakoutGraphics
FRAME_RATE = 1000 / 120 # 120 frames per second.
NUM_LIVES = 3
def main():
... | normal | {
"blob_id": "b218f5e401510f844006cb6079737b54aa86827b",
"index": 2194,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n graphics = BreakoutGraphics()\n lives = NUM_LIVES\n graphics.window.add(graphics.scoreboard, 0, graphics.window_height)\n while True:\n pause(FRAME_RA... | [
0,
2,
3,
4,
5
] |
from ..core.helpers import itemize
from ..core.files import backendRep, expandDir, prefixSlash, normpath
from .helpers import splitModRef
from .repo import checkoutRepo
from .links import provenanceLink
# GET DATA FOR MAIN SOURCE AND ALL MODULES
class AppData:
def __init__(
self, app, backend, moduleRef... | normal | {
"blob_id": "7be54b2bd99680beed3e8e9cb14225756a71a4ea",
"index": 1135,
"step-1": "<mask token>\n\n\nclass AppData:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass AppData:\n\n def __init__(se... | [
1,
5,
8,
9,
10
] |
import matplotlib.pyplot as plt
import numpy as np
import scipy.io as scio
import estimateGaussian as eg
import multivariateGaussian as mvg
import visualizeFit as vf
import selectThreshold as st
plt.ion()
# np.set_printoptions(formatter={'float': '{: 0.6f}'.format})
'''第1部分 加载示例数据集'''
#先通过一个小数据集进行异常检测 便于可视化
# 数据集... | normal | {
"blob_id": "de6b9961e0572338c87802314e7ae3cded5168b4",
"index": 487,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nplt.ion()\n<mask token>\nprint('Visualizing example dataset for outlier detection.')\n<mask token>\nplt.figure()\nplt.scatter(X[:, 0], X[:, 1], c='b', marker='x', s=15, linewidth=1)\nplt.a... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
app.config.from_pyfile('config.py', silent=True)
<|reserved_special_token_0|>
app.register_blueprint(static_blueprint)
app.register_blueprint(admin_blueprint)
app.register_blueprint(cart_blueprint)
app.register_blueprint(product_b... | flexible | {
"blob_id": "5d97a2afed26ec4826c8bce30c84863d21f86001",
"index": 9370,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp.config.from_pyfile('config.py', silent=True)\n<mask token>\napp.register_blueprint(static_blueprint)\napp.register_blueprint(admin_blueprint)\napp.register_blueprint(cart_blueprint)\n... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
try:
i = float(input('Enter the score : '))
if i > 1 or i < 0:
print("Entered score isn't valid.")
elif i < 0.6:
print('Grade: F')
elif i < 0.7:
print('Grade: D')
elif i < 0.8:
print('Grade: C')
elif i <... | flexible | {
"blob_id": "6f253da5dc1caa504a3a8aadae7bce6537b5c8c6",
"index": 6237,
"step-1": "<mask token>\n",
"step-2": "try:\n i = float(input('Enter the score : '))\n if i > 1 or i < 0:\n print(\"Entered score isn't valid.\")\n elif i < 0.6:\n print('Grade: F')\n elif i < 0.7:\n print('... | [
0,
1,
2
] |
import tty
import sys
import termios
def init():
orig_settings = termios.tcgetattr(sys.stdin)
tty.setcbreak(sys.stdin)
return orig_settings
def get_input():
return sys.stdin.read(1)
def exit(orig_settings):
termios.tcsetattr(sys.stdin, termios.TCSADRAIN, orig_settings)
if __name__ == "__main... | normal | {
"blob_id": "c64e41609a19a20f59446399a2e864ff8834c3f0",
"index": 4322,
"step-1": "<mask token>\n\n\ndef get_input():\n return sys.stdin.read(1)\n\n\ndef exit(orig_settings):\n termios.tcsetattr(sys.stdin, termios.TCSADRAIN, orig_settings)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef init():\n ... | [
2,
3,
4,
5,
6
] |
"""
purpose :Take an string as input and construct an algorithm
to input a string of characters and check whether
it is a palindrome.
@Author : Reshma Y. Kale
"""
from com.bridgelabz.utility.Data_structure_utility import *
if __name__=="__main__":
dq = Deque()
dq.palindrom() | normal | {
"blob_id": "d4d47f7abc5c8224188430546a65bfb8f358802f",
"index": 1472,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n dq = Deque()\n dq.palindrom()\n",
"step-3": "<mask token>\nfrom com.bridgelabz.utility.Data_structure_utility import *\nif __name__ == '__main__':\n ... | [
0,
1,
2,
3
] |
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from prettytable import PrettyTable
from time import sleep
from customization import *
import urllib.request,json
chrome_options=webdriver.ChromeOptions()
chrome_options.add_argument("--headless")
chrome_options.add_argument("--inco... | normal | {
"blob_id": "e1c902ef340a0a5538b41a03cc93686e0dd31672",
"index": 8788,
"step-1": "<mask token>\n\n\ndef bio_shortener(bio):\n lines = []\n x = len(bio) / 30\n y = 0\n Status = True\n while Status:\n y = y + 1\n lines.append(bio[0:30])\n lines.append('\\n')\n bio = bio[3... | [
3,
4,
5,
6,
7
] |
from flask import request
from flask_restful import abort
from sqlalchemy.exc import SQLAlchemyError
from gm.main.models.model import db, Metric, QuantModelMetricSchema, \
MlModelMetricSchema, Frequency, QuantModelMetric, MlModelMetric, \
ThresholdType
from gm.main.resources import success, get_metric_b... | normal | {
"blob_id": "1431a0049c05a99e0b68052f56bf8e2e3c48e1aa",
"index": 622,
"step-1": "<mask token>\n\n\nclass QuantModelMetricsResource(MetricsResource):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass MlModelMetricsResource(MetricsResource):\n \"\"\"\n This resource handles the HTTP requests c... | [
16,
19,
23,
25,
26
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
PULPNNInstallPath = cwd = os.getcwd() + '/../'
PULPNNSrcDirs = {'script': PULPNNInstallPath + 'scripts/'}
PULPNNInstallPath32bit = cwd = os.getcwd() + '/../32bit/'
PULPNNInstallPath64bit = cwd = os.getcwd() + '/../64bit/'
PULPNNTe... | flexible | {
"blob_id": "d8d0c181fcfc9e0692369cc7a65259c43a68e931",
"index": 5688,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nPULPNNInstallPath = cwd = os.getcwd() + '/../'\nPULPNNSrcDirs = {'script': PULPNNInstallPath + 'scripts/'}\nPULPNNInstallPath32bit = cwd = os.getcwd() + '/../32bit/'\nPULPNNInstallPath64b... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class OfferApi(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def find_eligible_items_with_http_info(self, x_ebay_c_marketplace_id,
**kwargs):
"""find_eligible_items # noqa: E501
This method evalua... | flexible | {
"blob_id": "a93818440410bde004f0203f18112fa1b666959c",
"index": 9615,
"step-1": "<mask token>\n\n\nclass OfferApi(object):\n <mask token>\n <mask token>\n <mask token>\n\n def find_eligible_items_with_http_info(self, x_ebay_c_marketplace_id,\n **kwargs):\n \"\"\"find_eligible_items # ... | [
4,
5,
6,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('test_9feats.csv', 'w') as f:
df = pd.DataFrame(file, columns=['dst_host_srv_serror_rate',
'dst_host_serror_rate', 'serror_rate', 'srv_serror_rate', 'count',
'flag', 'same_srv_rate', 'dst_host_srv_cou... | flexible | {
"blob_id": "ce28330db66dcdfad63bdac698ce9d285964d288",
"index": 5124,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('test_9feats.csv', 'w') as f:\n df = pd.DataFrame(file, columns=['dst_host_srv_serror_rate',\n 'dst_host_serror_rate', 'serror_rate', 'srv_serror_rate', 'count',\n ... | [
0,
1,
2,
3,
4
] |
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
# from sklearn import tree
# import joblib
music_data = pd.read_csv(r"C:\Users\junha\PythonProjects\predict_music_preferences\music.csv")
# print(music_dat... | normal | {
"blob_id": "8dbcd7bba09f8acff860890d8201e016b587796d",
"index": 6149,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmodel.fit(X_train, y_train)\n<mask token>\nprint(predictions)\n<mask token>\nprint(score)\n",
"step-3": "<mask token>\nmusic_data = pd.read_csv(\n 'C:\\\\Users\\\\junha\\\\PythonProj... | [
0,
1,
2,
3,
4
] |
<|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_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "4e04e748a97c59a26a394b049c15d96476b98517",
"index": 9382,
"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 = [('trades', '0... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Ui_Window(QDialog):
def __init__(self):
super(Ui_Window, self).__init__()
self.ui = Ui_Dialog()
self.ui.setupUi(self)
regex = QRegExp('\\w+')
validator = QRegExpValidator(regex)
self.ui.usernameLineEdit.setValidator(validator)
... | flexible | {
"blob_id": "8cabacb64f3b193b957c61d6e1ca21f2046e52d1",
"index": 8199,
"step-1": "<mask token>\n\n\nclass Ui_Window(QDialog):\n\n def __init__(self):\n super(Ui_Window, self).__init__()\n self.ui = Ui_Dialog()\n self.ui.setupUi(self)\n regex = QRegExp('\\\\w+')\n validator =... | [
9,
11,
12,
13,
14
] |
import dtw
import stats
import glob
import argparse
import matplotlib.pyplot as plt
GRAPH = False
PERCENTAGE = False
VERBOSE = False
def buildExpectations(queryPath, searchPatternPath):
"""
Based on SpeechCommand_v0.02 directory structure.
"""
expectations = []
currentDirectory = ""
queryFile... | normal | {
"blob_id": "03fb1cf0aac0c37858dd8163562a7139ed4e1179",
"index": 776,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef buildExpectations(queryPath, searchPatternPath):\n \"\"\"\n Based on SpeechCommand_v0.02 directory structure.\n \"\"\"\n expectations = []\n currentDirectory = ''\n ... | [
0,
2,
3,
4,
5
] |
'''
文件读写的步骤
1.打开文件
2.处理数据
3.关闭文件
1.open函数：
fileobj = open(filename, mode)
fileobj是open()函数返回的文件对象
mode第一个字母指明文件类型和操作的字符串，第二个字母是文件类型：
t(可省略)文本类型，b二进制类型。
文件打开模式：r只读(默认)，w覆盖写(不存在则新创建)
a追加模式(不存在则创建)
2.read(size):从文件读取长度为size的字符串，若未给定或为负则读取所有内容
3.readline():读取整行返回字符串
4.readline... | normal | {
"blob_id": "25f3c9f48b779d2aec260d529529156ff3c508ca",
"index": 7719,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in fileobj3.readlines():\n print(line)\nfileobj3.close()\n",
"step-3": "<mask token>\nfileobj3 = open('lines.txt', 'r')\nfor line in fileobj3.readlines():\n print(line)\n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class AFB_L1(nn.Module):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class AFB_L2(nn.Module):
def __init__(self, channels, n_l1=4, act=nn.ReLU(True)):
super(AFB_L2, self).__init__()
self.n = n_l1
self.convs_ = nn.ModuleList()
fo... | flexible | {
"blob_id": "b2c0ef4a0af12b267a54a7ae3fed9edeab2fb879",
"index": 6570,
"step-1": "<mask token>\n\n\nclass AFB_L1(nn.Module):\n <mask token>\n <mask token>\n\n\nclass AFB_L2(nn.Module):\n\n def __init__(self, channels, n_l1=4, act=nn.ReLU(True)):\n super(AFB_L2, self).__init__()\n self.n = ... | [
10,
14,
17,
18,
19
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Order(models.Model):
<|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": "78ddae64cc576ebaf7f2cfaa4553bddbabe474b7",
"index": 6918,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Order(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Order(m... | [
0,
1,
2,
3,
4
] |
'''Given a range of 2 numbers (i.e) L and R count the number of prime numbers in the range (inclusive of L and R ).
Input Size : L <= R <= 100000(complexity O(n) read about Sieve of Eratosthenes)
Sample Testcase :
INPUT
2 5
OUTPUT
3'''
x,y=map(int,input().split())
count=0
for i in range(x,y+1):
if i>1:
for... | normal | {
"blob_id": "06848ec0e327fed1da00446cec6392c6f42130af",
"index": 2158,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(x, y + 1):\n if i > 1:\n for j in range(2, i):\n if i % j == 0:\n break\n else:\n count += 1\nprint(count)\n",
"step... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(word[0])
<|reserved_special_token_0|>
print('こんにちわ、私の名前は {} です。'.format(name))
<|reserved_special_token_0|>
print('{}/{}/{}'.format(year, month, day))
for i in range(0, 5):
print('kamyu'[i])
print('aldous Huxley was born... | flexible | {
"blob_id": "0e05eed2d6bc723fd8379e436621a6eba4aa5ab2",
"index": 1929,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(word[0])\n<mask token>\nprint('こんにちわ、私の名前は {} です。'.format(name))\n<mask token>\nprint('{}/{}/{}'.format(year, month, day))\nfor i in range(0, 5):\n print('kamyu'[i])\nprint('aldo... | [
0,
1,
2,
3
] |
a= input("Enter number")
a= a.split()
b=[]
for x in a:
b.append(int(x))
print(b)
l=len(b)
c=0
s=0
for i in range(l):
s=len(b[:i])
for j in range(s):
if b[s]<b[j]:
c=b[s]
b.pop(s)
b.insert(b.index(b[j]),c)
print(b,b[:i],b[s])
| normal | {
"blob_id": "24de4f486d4e976850e94a003f8d9cbe3e518402",
"index": 33,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor x in a:\n b.append(int(x))\nprint(b)\n<mask token>\nfor i in range(l):\n s = len(b[:i])\n for j in range(s):\n if b[s] < b[j]:\n c = b[s]\n b.pop(s... | [
0,
1,
2,
3
] |
import matplotlib.pyplot as plt
class Scatter:
def __init__(self, values, ylabel, title):
self.values = values
self.range = list(range(len(values)))
self.ylabel = ylabel
self.title = title
def plot(self):
fig = plt.figure()
ax = fig.add_axes([0, 0, ... | normal | {
"blob_id": "58385a7713a8f88925ced714d25f1522bc7e39d8",
"index": 1181,
"step-1": "<mask token>\n\n\nclass Scatter:\n <mask token>\n <mask token>\n\n\nclass Pie:\n\n def __init__(self, values, labels, title):\n self.style = 'fivethirtyeight'\n self.values = values\n self.labels = lab... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
class Getter(object):
<|reserved_special_token_0|>
def __call__(self, url, **kwargs):
try:
return self._inner_call(url, **kwargs)
except (Timeout, ConnectionError, RequestException) as ex:
message = ex.response.reason if getattr(ex, 'respon... | flexible | {
"blob_id": "603708c830dadb6f1a3e5de00536d558f448b5fb",
"index": 1352,
"step-1": "<mask token>\n\n\nclass Getter(object):\n <mask token>\n\n def __call__(self, url, **kwargs):\n try:\n return self._inner_call(url, **kwargs)\n except (Timeout, ConnectionError, RequestException) as e... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
__author__ = 'simsun'
| flexible | {
"blob_id": "2b746d89d34435eb5f3a5b04da61c5cc88178852",
"index": 8784,
"step-1": "<mask token>\n",
"step-2": "__author__ = 'simsun'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
class UrlPath:
@staticmethod
def combine(*args):
result = ''
for path in args:
result += path if path.endswith('/') else '{}/'.format(path)
#result = result[:-1]
return result | normal | {
"blob_id": "aa579025cacd11486a101b2dc51b5ba4997bf84a",
"index": 95,
"step-1": "<mask token>\n",
"step-2": "class UrlPath:\n <mask token>\n",
"step-3": "class UrlPath:\n\n @staticmethod\n def combine(*args):\n result = ''\n for path in args:\n result += path if path.endswith... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urllib3.disable_warnings()
<|reserved_special_token_0|>
print(key.decode('ascii'))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urllib3.disable_warnings()
response = requests.get('https://freeaeskey.xyz', verify=Fa... | flexible | {
"blob_id": "368e209f83cc0cade81791c8357e01e7e3f940c8",
"index": 97,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurllib3.disable_warnings()\n<mask token>\nprint(key.decode('ascii'))\n",
"step-3": "<mask token>\nurllib3.disable_warnings()\nresponse = requests.get('https://freeaeskey.xyz', verify=Fals... | [
0,
1,
2,
3,
4
] |
from django.shortcuts import render
from django.shortcuts import redirect
from block.models import Block
from .models import Article
from .forms import ArticleForm
from django.core.paginator import Paginator
from django.contrib.auth.decorators import login_required
def article_list(request, block_id):
block_id = ... | normal | {
"blob_id": "0f94537fa64066bb29c5e9e97836b0a8ac01ac19",
"index": 9844,
"step-1": "<mask token>\n\n\n@login_required\ndef article_create(request, block_id):\n block_id = int(block_id)\n block = Block.objects.get(id=block_id)\n if request.method == 'GET':\n return render(request, 'article_create.ht... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Song(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __unicode__(self):
return self.name
<|reserved_special_token_1|>
<|reserved_special... | flexible | {
"blob_id": "8ec18e259af1123fad7563aee3a363e095e30e8e",
"index": 1064,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Song(models.Model):\n <mask token>\n <mask token>\n <mask token>\n\n def __unicode__(self):\n return self.name\n",
"step-3": "<mask token>\n\n\nclass Song(m... | [
0,
2,
3,
4,
5
] |
#!/usr/bin/python
import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BCM)
ledPin = 4
pinOn = False
GPIO.setup(ledPin, GPIO.OUT)
GPIO.output(ledPin, GPIO.LOW)
def print_pin_status(pin_number):
GPIO.setup(pin_number, GPIO.IN)
value = GPIO.input(pin_number)
print(f'Current Value of {pin_number} is {value}')
G... | normal | {
"blob_id": "492c416becc44deaafef519eae8c9a82ac00cc0e",
"index": 8632,
"step-1": "<mask token>\n\n\ndef print_pin_status(pin_number):\n GPIO.setup(pin_number, GPIO.IN)\n value = GPIO.input(pin_number)\n print(f'Current Value of {pin_number} is {value}')\n GPIO.setup(pin_number, GPIO.OUT)\n\n\n<mask t... | [
1,
2,
3,
4,
5
] |
from pyathena import connect
from Config import config2
from Config import merchants
def get_mapped_sku(sku):
try:
cursor = connect(aws_access_key_id=config2["aws_access_key_id"],
aws_secret_access_key=config2["aws_secret_access_key"],
s3_staging_dir=confi... | normal | {
"blob_id": "6add599035573842475c7f9155c5dbbea6c96a8a",
"index": 3618,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_mapped_sku(sku):\n try:\n cursor = connect(aws_access_key_id=config2['aws_access_key_id'],\n aws_secret_access_key=config2['aws_secret_access_key'],\n ... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class View(Renderable, ABC):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class View(Renderable, ABC):
@abstractmethod
def content_size(self, container_size: Size) ->Si... | flexible | {
"blob_id": "913ff9b811d3abbe43bda0554e40a6a2c87053be",
"index": 4449,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass View(Renderable, ABC):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass View(Renderable, ABC):\n\n @abstractmethod\n def content_size(self, container_size: Size)... | [
0,
1,
2,
3
] |
from django import forms
from django.contrib.auth.models import User
from .models import TblPublish , TblSnippetTopics, TblSnippetData, TblLearnTopics, TblLearnData, TblBlog, TblBlogComments,TblLearnDataComments, TblBlogGvp, TblLearnDataGvp,TblSnippetDataGvp, TblHome, TblAbout, TblQueries
from django.contrib.auth.forms... | normal | {
"blob_id": "9e02b1a90d61de6d794dd350b50417a2f7260df6",
"index": 5947,
"step-1": "<mask token>\n\n\nclass TblBlogForm(forms.ModelForm):\n\n\n class Meta:\n model = TblBlog\n fields = ['blog_title', 'blog_description', 'blog_keyword',\n 'blog_content', 'blog_pics', 'blog_publish', 'blo... | [
19,
20,
22,
26,
32
] |
from pathlib import Path
from build_midi.appenders import *
from build_midi.converters import Converter
from build_midi.melody_builder import MelodyBuilder
from build_midi.sequences import *
from build_midi.tracks import *
from music_rules.instruments import Instruments
from music_rules.music_scale import MusicScale
f... | normal | {
"blob_id": "c846c33ef13795d51c6d23ffa5a6b564b66e6a3c",
"index": 3438,
"step-1": "<mask token>\n\n\nclass WeatherToMusicConverter:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass WeatherToMusicConverter:\n <ma... | [
1,
4,
5,
6,
7
] |
import xadmin
from xadmin import views
from .models import EmailVerifyRecord, Banner
class BaseMyAdminView(object):
'''
enable_themes 启动更改主题
use_bootswatch 启用网上主题
'''
enable_themes = True
use_bootswatch = True
class GlobalSettings(object):
'''
site_title 左上角名称
site_footer 底部名称
... | normal | {
"blob_id": "d7b830890400203ee45c9ec59611c0b20ab6bfc7",
"index": 8496,
"step-1": "<mask token>\n\n\nclass BaseMyAdminView(object):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass GlobalSettings(object):\n \"\"\"\n site_title 左上角名称\n site_footer 底部名称\n menu_style 更改左边样式\n \"\"\"\n ... | [
8,
10,
11,
12,
13
] |
# Generated by Django 3.2.6 on 2021-08-19 16:17
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('crm', '0040_auto_20210819_1913'),
]
operations = [
migrations.RemoveField(
model_name='customer',
name='full_name',
... | normal | {
"blob_id": "42f021c728a88f34d09f94ea96d91abded8a29fb",
"index": 9553,
"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 = [('crm', '0040... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class WorkRequestForm(forms.ModelForm):
<|reserved_special_token_0|>
class Meta:
model = HhRequest
fields = 'profile', 'sphere', 'experience', 'work_request', 'resume'
widgets = {'profile': form... | flexible | {
"blob_id": "3887516e4222504defe439e62bd24b12db3cdd84",
"index": 695,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass WorkRequestForm(forms.ModelForm):\n <mask token>\n\n\n class Meta:\n model = HhRequest\n fields = 'profile', 'sphere', 'experience', 'work_request', 'resume'\... | [
0,
1,
2,
3,
4
] |
#!env/bin/python3
from app import app
from config import config as cfg
app.run(debug=True, host=cfg.APP_HOST, port=cfg.APP_PORT)
| normal | {
"blob_id": "f97150f60dfb3924cda2c969141d5bfe675725ef",
"index": 9150,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp.run(debug=True, host=cfg.APP_HOST, port=cfg.APP_PORT)\n",
"step-3": "from app import app\nfrom config import config as cfg\napp.run(debug=True, host=cfg.APP_HOST, port=cfg.APP_PORT)... | [
0,
1,
2,
3
] |
<<<<<<< HEAD
"""Module docstring"""
import os
import numpy as np
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import KFold
from sklearn.metrics import accuracy_score
=======
#!/usr/bin/python
"""Module docstring"""... | normal | {
"blob_id": "2bce18354a53c49274f7dd017e1f65c9ff1327b9",
"index": 2264,
"step-1": "<<<<<<< HEAD\n\"\"\"Module docstring\"\"\"\nimport os\nimport numpy as np\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.model_selection impo... | [
0
] |
<|reserved_special_token_0|>
class IBehaviourBase(Client):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class IBehaviourBase(Client):
<|reserved_special_token_0|>
def __init__(self, email, pas... | flexible | {
"blob_id": "e67f27eec53901f27ba5a7ee7e2a20bbb1e8f7f9",
"index": 2237,
"step-1": "<mask token>\n\n\nclass IBehaviourBase(Client):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass IBehaviourBase(Client):\n <mask token>\n\n def __init__(self, email, password, kwa... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def tokenize_de(text):
return [tok.text for tok in spacy_de.tokenizer(url.sub('@URL@', text))]
def tokenize_en(text):
return [tok.text for tok in spacy_en.tokenizer(url.sub('@URL@', text))]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0... | flexible | {
"blob_id": "4e715ccb4f95e7fe7e495a1181ad5df530f5a53f",
"index": 5773,
"step-1": "<mask token>\n\n\ndef tokenize_de(text):\n return [tok.text for tok in spacy_de.tokenizer(url.sub('@URL@', text))]\n\n\ndef tokenize_en(text):\n return [tok.text for tok in spacy_en.tokenizer(url.sub('@URL@', text))]\n\n\n<ma... | [
2,
3,
4,
5
] |
# settings
import config
# various modules
import sys
import time
import multiprocessing
import threading
from queue import Queue
import time
import os
import signal
import db
import time
from random import randint
# telepot's msg loop & Bot
from telepot.loop import MessageLoop
from telepot import Bot
import asyncio... | normal | {
"blob_id": "315fed1806999fed7cf1366ef0772318a0baa84d",
"index": 8789,
"step-1": "# settings\nimport config\n\n# various modules\nimport sys\nimport time\nimport multiprocessing\nimport threading\nfrom queue import Queue\nimport time\nimport os\nimport signal\nimport db\nimport time\nfrom random import randint\n... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_instance(rest_url, params):
url = BASEURL + rest_url
print(url)
twitter = OAuth1Session(CK, CS, AT, AS)
return twitter.get(url, params=params)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "63bfaa6e191e6090060877e737f4b003bed559cf",
"index": 9140,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_instance(rest_url, params):\n url = BASEURL + rest_url\n print(url)\n twitter = OAuth1Session(CK, CS, AT, AS)\n return twitter.get(url, params=params)\n",
"step-... | [
0,
1,
2,
3,
4
] |
K = input()
mat = "".join(raw_input() for i in xrange(4))
print ("YES", "NO")[max(mat.count(str(i)) for i in xrange(1, 10)) > K*2]
| normal | {
"blob_id": "879f7503f7f427f92109024b4646d1dc7f15d63d",
"index": 2153,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('YES', 'NO')[max(mat.count(str(i)) for i in xrange(1, 10)) > K * 2]\n",
"step-3": "K = input()\nmat = ''.join(raw_input() for i in xrange(4))\nprint('YES', 'NO')[max(mat.count(str... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class NameSearch(forms.Form):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class NameSearch(forms.Form):
name = forms.CharField(label='Search By Name')
<|reserved_special_... | flexible | {
"blob_id": "7620ff333422d0354cc41c2a66444c3e8a0c011f",
"index": 1606,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass NameSearch(forms.Form):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass NameSearch(forms.Form):\n name = forms.CharField(label='Search By Name')\n",
"step-4": "f... | [
0,
1,
2,
3
] |
import csv
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
#funktion
def func(w,rc):
return 1/(np.sqrt(1+w**2*rc**2))
#daten einlesen
with open('data/phase.csv' ) as csvfile:
reader=csv.reader(csvfile, delimiter=',')
header_row=next(reader)
f, U, a,... | normal | {
"blob_id": "170d0560c40f3f642f319f6113b68ab8a6bea9ef",
"index": 468,
"step-1": "<mask token>\n\n\ndef func(w, rc):\n return 1 / np.sqrt(1 + w ** 2 * rc ** 2)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef func(w, rc):\n return 1 / np.sqrt(1 + w ** 2 * rc ** 2)\n\n\nwith open('data/phase.csv') as... | [
1,
2,
3,
4,
5
] |
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