text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>
def softmax_train(input_size, num_classes, lambda_, data, labels, options={'maxiter': 400, 'disp': True}):
#softmaxTrain Train a softmax model with the given parameters on the given
# data. Returns softmaxOptTheta, a vector containing the trained parameters
# for the model.
#
# input_... | code_fim | hard | {
"lang": "python",
"repo": "akhiyarwaladi/example_tutorial",
"path": "/softmax.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #softmaxTrain Train a softmax model with the given parameters on the given
# data. Returns softmaxOptTheta, a vector containing the trained parameters
# for the model.
#
# input_size: the size of an input vector x^(i)
# num_classes: the number of classes
# lambda_: weight decay... | code_fim | medium | {
"lang": "python",
"repo": "akhiyarwaladi/example_tutorial",
"path": "/softmax.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: akhiyarwaladi/example_tutorial path: /softmax.py
import numpy as np
import scipy.sparse
import scipy.optimize
def softmax_cost(theta, num_classes, input_size, lambda_, data, labels):
"""
:param theta:
:param num_classes: the number of classes
:param input_size: the size N of in... | code_fim | hard | {
"lang": "python",
"repo": "akhiyarwaladi/example_tutorial",
"path": "/softmax.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: heshanpadmasiri/Lite-LPNet path: /show_eval.py
from pathlib import Path
import argparse
import joblib
saved_model_path = Path('./saved_models')
bbox_path = saved_model_path/'simple_bbox'
lp_path = saved_model_path/'lp_seperate'
def __get_pickle_files__(base_path:Path):
return [each for each... | code_fim | medium | {
"lang": "python",
"repo": "heshanpadmasiri/Lite-LPNet",
"path": "/show_eval.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == "__main__":
parser = argparse.ArgumentParser(description="train bbox model")
parser.add_argument('stage', type=int, help='stage to show eval results')
args = parser.parse_args()
stage = args.stage
if stage == 1:
eval_results = get_eval_files(bbox_path)
pr... | code_fim | hard | {
"lang": "python",
"repo": "heshanpadmasiri/Lite-LPNet",
"path": "/show_eval.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 17605272633/ManyBeautifulMall path: /ManyBeautiful/ManyBeautifulMall/apps/carts/serializers.py
from rest_framework import serializers
from goods.models import SKU
# 购物车数据添加序列化器
class AddCartSerializer(serializers.Serializer):
"""购物车数据添加序列化器"""
# 定义属性
sku_id = serializers.IntegerFi... | code_fim | hard | {
"lang": "python",
"repo": "17605272633/ManyBeautifulMall",
"path": "/ManyBeautiful/ManyBeautifulMall/apps/carts/serializers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # 获取商品信息,验证商品是否存在
try:
sku = SKU.objects.get(id=value)
except SKU.DoesNotExist:
raise serializers.ValidationError('商品不存在')
return value
# 购物车数据全选序列化器
class SelectAllCartSerializer(serializers.Serializer):
"""购物车数据全选序列化器"""
selected = seria... | code_fim | hard | {
"lang": "python",
"repo": "17605272633/ManyBeautifulMall",
"path": "/ManyBeautiful/ManyBeautifulMall/apps/carts/serializers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PHOENIX26012000/dcase2018_task4 path: /utils/utilities.py
import os
import numpy as np
import soundfile
import librosa
from sklearn import metrics
import logging
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import pandas as pd
import sed_eval
import torch
from torch.autogra... | code_fim | hard | {
"lang": "python",
"repo": "PHOENIX26012000/dcase2018_task4",
"path": "/utils/utilities.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ix_to_lb = config.ix_to_lb
estimated_event_list = []
for (n, audio_name) in enumerate(audio_names):
for event_index in predictions[n]:
bgn_fin_pairs = activity_detection(
frame_wise_probs[n, :, event_index], thres=sed_thres,
... | code_fim | hard | {
"lang": "python",
"repo": "PHOENIX26012000/dcase2018_task4",
"path": "/utils/utilities.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Calculate sed_eval event based metric for challenge
Parameters
----------
reference_event_list : MetaDataContainer, list of referenced events
estimated_event_list : MetaDataContainer, list of estimated events
Return
------
event_based_metric ... | code_fim | hard | {
"lang": "python",
"repo": "PHOENIX26012000/dcase2018_task4",
"path": "/utils/utilities.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: catboost/catboost path: /contrib/python/prompt-toolkit/py3/tests/test_formatted_text.py
from __future__ import annotations
from prompt_toolkit.formatted_text import (
ANSI,
HTML,
FormattedText,
PygmentsTokens,
Template,
merge_formatted_text,
to_formatted_text,
)
from ... | code_fim | hard | {
"lang": "python",
"repo": "catboost/catboost",
"path": "/contrib/python/prompt-toolkit/py3/tests/test_formatted_text.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert lines == [
[("class:a", "line1")],
[("class:a", "line2")],
[("class:a", "line3")],
]
def test_split_lines_2():
lines = list(
split_lines([("class:a", "line1"), ("class:b", "line2\nline3\nline4")])
)
assert lines == [
[("class:a", "line1... | code_fim | hard | {
"lang": "python",
"repo": "catboost/catboost",
"path": "/contrib/python/prompt-toolkit/py3/tests/test_formatted_text.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hanzckernel/opricer path: /Utils/apps/options.py
emoization of scraping data
cache = Cache(app.server, config={
'CACHE_TYPE': 'filesystem',
'CACHE_DIR': 'cache'
})
def func_check(string):
pass
def parse_table(tag):
page = requests.get(f"https://www.global-rates.com/intere... | code_fim | hard | {
"lang": "python",
"repo": "hanzckernel/opricer",
"path": "/Utils/apps/options.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>@app.callback(
[Output("option_modal_close", 'n_clicks'), Output('missing_warning', 'children'),
Output('missing_warning', 'style'), Output('asset_info', 'data'),
Output('clear_all', 'value')],
[Input("submit_new_option", "n_clicks"), Input('option-clear', 'n_clicks')],
[State('asset_n... | code_fim | hard | {
"lang": "python",
"repo": "hanzckernel/opricer",
"path": "/Utils/apps/options.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> dcc.ConfirmDialog(id='true-confirm'),
],
className='col s12 center-align'),
html.Div([
dcc.Input(id='strike', type='number', step=0.001, min = 0.01,
className='validate', style={"color":"white"}),
html.Label("... | code_fim | hard | {
"lang": "python",
"repo": "hanzckernel/opricer",
"path": "/Utils/apps/options.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ianbialo/Cryptography path: /app/keys_generator/prime.py
from os import path
import random
from app.keys_generator.xorshift import XORShift
from app.utils.file_manager import read_file, write_file
from app.utils.modular_arithmetic import square_and_multiply
def _generate_possible_prime(n_bits: ... | code_fim | hard | {
"lang": "python",
"repo": "ianbialo/Cryptography",
"path": "/app/keys_generator/prime.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, prime_path: path, n_bits: int = 512, with_generator: bool = True):
self.__generator = 0
if path.exists(prime_path):
# Load existing prime
prime_lines = read_file(prime_path).splitlines()
self.__prime = int(prime_lines[0])
... | code_fim | hard | {
"lang": "python",
"repo": "ianbialo/Cryptography",
"path": "/app/keys_generator/prime.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hemu243/focus-web-crawler path: /focused_scrapy_crawler/spiders/newhouse.py
# -*- coding: utf-8 -*-
import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule
from focused_scrapy_crawler.items import FocusedScrapyCrawlerItem
import time
import loggi... | code_fim | hard | {
"lang": "python",
"repo": "hemu243/focus-web-crawler",
"path": "/focused_scrapy_crawler/spiders/newhouse.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Get anchor tags for whole page
:param response: response object instance
:param soup: beautiful soup instance
:return: list of urls
"""
links = []
for anchor in soup.find_all('a'):
href = anchor.get('href')
# Conve... | code_fim | hard | {
"lang": "python",
"repo": "hemu243/focus-web-crawler",
"path": "/focused_scrapy_crawler/spiders/newhouse.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andrewp-as-is/django-command-debug.py path: /setup.py
from setuptools import setup
setup(
name='django-command-debug',
ver<|fim_suffix|>go_command_debug.admin',
'django_command_debug.management',
'django_command_debug.migrations',
'django_command_debug.models'
... | code_fim | medium | {
"lang": "python",
"repo": "andrewp-as-is/django-command-debug.py",
"path": "/setup.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>jango_command_debug.migrations',
'django_command_debug.models'
]
)<|fim_prefix|># repo: andrewp-as-is/django-command-debug.py path: /setup.py
from setuptools import setup
setup(
name='django-command-debug',
ver<|fim_middle|>sion='2021.8.20',
packages=[
'django_command_deb... | code_fim | medium | {
"lang": "python",
"repo": "andrewp-as-is/django-command-debug.py",
"path": "/setup.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>go_command_debug.admin',
'django_command_debug.management',
'django_command_debug.migrations',
'django_command_debug.models'
]
)<|fim_prefix|># repo: andrewp-as-is/django-command-debug.py path: /setup.py
from setuptools import setup
setup(
name='django-command-debug',
... | code_fim | medium | {
"lang": "python",
"repo": "andrewp-as-is/django-command-debug.py",
"path": "/setup.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> result = service.list_concepts('entity')
test_case.assertEqual([conceptA], result)
result = service.list_concepts('abuse')
test_case.assertEqual([conceptB], result)
def list_taxonomies(test_case):
result = service.list_taxonomies()
test_case.assertEqual(taxonomies, result)<|fim_p... | code_fim | hard | {
"lang": "python",
"repo": "bitWeaver-arch/graphsense-REST",
"path": "/gsrest/test/tags_service.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bitWeaver-arch/graphsense-REST path: /gsrest/test/tags_service.py
from openapi_server.models.address_tag import AddressTag
from openapi_server.models.entity_tag import EntityTag
from openapi_server.models.tags import Tags
from openapi_server.models.taxonomy import Taxonomy
from openapi_server.mod... | code_fim | hard | {
"lang": "python",
"repo": "bitWeaver-arch/graphsense-REST",
"path": "/gsrest/test/tags_service.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: popey0/2020-Tutorials path: /Week 4/solution.py
# -*- coding: utf-8 -*-
"""
Week 4 ICT Session
"""
import numpy as np
from scipy import fft # Import the module, NOT the function
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter, MultipleLocator
def mapping(x, xp, fp)... | code_fim | hard | {
"lang": "python",
"repo": "popey0/2020-Tutorials",
"path": "/Week 4/solution.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> The given function is approximated using a discrete sine transform over the
`fit` domain. The result is then shown over a domain of [-2pi, +2pi], using
the `plot` number of terms.
Parameters
----------
func : callable
A single parameter function to be fit
fit : tuple, ... | code_fim | hard | {
"lang": "python",
"repo": "popey0/2020-Tutorials",
"path": "/Week 4/solution.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def check_reply_already_exists(session, reply: models.Reply):
reply_class = models.Reply
try:
session.query(reply_class).filter(reply_class.rpid == reply.rpid).one()
return True
except NoResultFound:
return False
except MultipleResultsFound:
return True<|fi... | code_fim | hard | {
"lang": "python",
"repo": "michaelfyc/ASoulCnki",
"path": "/app/spider/reply/reply_spider.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: michaelfyc/ASoulCnki path: /app/spider/reply/reply_spider.py
import app.models as models
from sqlalchemy.orm.exc import NoResultFound, MultipleResultsFound
from app import utils
from app.config import sqla
from app.lib import send_mail
from app.utils import Throttle
throttle = Throttle(2)
def... | code_fim | hard | {
"lang": "python",
"repo": "michaelfyc/ASoulCnki",
"path": "/app/spider/reply/reply_spider.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return datetime.fromtimestamp(float(bb_server_timestamp_str) / 1000).replace(tzinfo=pytz.utc)
def _normalize_user(user):
if not user:
return None
return {
'id': user.get('id', ''),
'login': user.get('name', ''),
'name': user.get('displayName', ''),
'e... | code_fim | hard | {
"lang": "python",
"repo": "Jellyfish-AI/jf_agent",
"path": "/jf_agent/git/bitbucket_server.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Jellyfish-AI/jf_agent path: /jf_agent/git/bitbucket_server.py
import RetryError, ChunkedEncodingError
from urllib3.exceptions import MaxRetryError
from jf_agent.git import pull_since_date_for_repo
from jf_agent.git.utils import get_matching_branches
from jf_agent.name_redactor import NameRedactor... | code_fim | hard | {
"lang": "python",
"repo": "Jellyfish-AI/jf_agent",
"path": "/jf_agent/git/bitbucket_server.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Jellyfish-AI/jf_agent path: /jf_agent/git/bitbucket_server.py
config.git_redact_names_and_urls,
config.git_verbose,
),
item_id_dict_key='hash',
)
download_and_write_commits()
@diagnostics.capture_timing()
@agent_logging.l... | code_fim | hard | {
"lang": "python",
"repo": "Jellyfish-AI/jf_agent",
"path": "/jf_agent/git/bitbucket_server.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(s.param[0], s.param[1], s.calculate_gauss_curvature())
plt.xlabel('u')
plt.ylabel('v')
ax.set_zlabel('K')
plt.title('Gauss curvature')
plt.show()<|fim_prefix|># repo: yellowshippo/geomulator path: /demo_surface.py
import numpy ... | code_fim | hard | {
"lang": "python",
"repo": "yellowshippo/geomulator",
"path": "/demo_surface.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Shere - {one_point}
surface = np.array([
2 * u,
2 * v,
1 - u**2 - v**2
]) / (1 + u**2 + v**2)
return (surface[0], surface[1], surface[2])
# Generate surface object
s = Surface.generate_surface(
calc_surface, u_param=(-10., 10., .01), v_param=(-10., 10., .01)... | code_fim | medium | {
"lang": "python",
"repo": "yellowshippo/geomulator",
"path": "/demo_surface.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yellowshippo/geomulator path: /demo_surface.py
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from geomulator.surface import Surface
def calc_surface(u, v):
"""Calculate surface according to your definition."""
# # Wavy surface
# surface... | code_fim | hard | {
"lang": "python",
"repo": "yellowshippo/geomulator",
"path": "/demo_surface.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>type(np.random.uniform(0, 10, size=(50,))))
print(type(np.random.uniform(0, 10, size=50)))<|fim_prefix|># repo: Judithle98/BachelorThesis path: /test.py
import BNQD
import gpflow as gpf
import numpy as np
import util
import matplotlib.pyplot a<|fim_middle|>s plt
xs, ys = util.linear_dummy_data()
cm = BN... | code_fim | medium | {
"lang": "python",
"repo": "Judithle98/BachelorThesis",
"path": "/test.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Judithle98/BachelorThesis path: /test.py
import BNQD
import gpflow as gpf
import numpy as np
import util
import matplotlib.pyplot a<|fim_suffix|>type(np.random.uniform(0, 10, size=(50,))))
print(type(np.random.uniform(0, 10, size=50)))<|fim_middle|>s plt
xs, ys = util.linear_dummy_data()
cm = BN... | code_fim | medium | {
"lang": "python",
"repo": "Judithle98/BachelorThesis",
"path": "/test.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> slide_masters = context.slide_masters
idx = -1
for idx, slide_master in enumerate(slide_masters):
assert type(slide_master).__name__ == 'SlideMaster'
assert idx == 1
@then('iterating slides produces 3 Slide objects')
def then_iterating_slides_produces_3_Slide_objects(context):
... | code_fim | hard | {
"lang": "python",
"repo": "dimensions11/python-pptx",
"path": "/features/steps/slide.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dimensions11/python-pptx path: /features/steps/slide.py
# encoding: utf-8
"""Gherkin step implementations for slide-related features."""
from __future__ import (
absolute_import, division, print_function, unicode_literals
)
from behave import given, when, then
from pptx import Presentatio... | code_fim | hard | {
"lang": "python",
"repo": "dimensions11/python-pptx",
"path": "/features/steps/slide.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pdghawk/adfraud path: /adfraud/models.py
""" Module for ML models
"""
import numpy as np
from sklearn.model_selection import GridSearchCV
from sklearn.model_selection import StratifiedShuffleSplit
from sklearn.ensemble import RandomForestClassifier
from sklearn import metrics
from sklearn.metric... | code_fim | hard | {
"lang": "python",
"repo": "pdghawk/adfraud",
"path": "/adfraud/models.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ fit the model """
self.model.fit(x_train[self.feats],y_train)
def train_CV(self,x_train,y_train,param_grid,n_splits=5):
""" train the model with Criss Validation
Performs a stratified split of the training data into train and validation
partitions (keeping... | code_fim | hard | {
"lang": "python",
"repo": "pdghawk/adfraud",
"path": "/adfraud/models.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: majidaldo/yaml_query path: /yaml_query/dict2table.py
"""
handles nested (1-level) dictionary data (like in the yaml file).
"""
item_column = 'ITEM_ID' # special
def iter_rows(item_dict,columns):
"""
Iterate through the {'item':{'attrib':'value'}} items as rows in a table.
Values f... | code_fim | medium | {
"lang": "python",
"repo": "majidaldo/yaml_query",
"path": "/yaml_query/dict2table.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def dict2table(*args,**kwargs):
return iter_rows(*args,**kwargs)
def get_fields(item_dict):
d = item_dict
fields=set()
for item in d:
for afield in d[item]:
fields.add(afield)
return fields<|fim_prefix|># repo: majidaldo/yaml_query path: /yaml_query/dict2table.py
... | code_fim | hard | {
"lang": "python",
"repo": "majidaldo/yaml_query",
"path": "/yaml_query/dict2table.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: allenai/allennlp-models path: /allennlp_models/vision/dataset_readers/vision_reader.py
heck_for_gpu, ConfigurationError
from allennlp.common.lazy import Lazy
from allennlp.common.util import int_to_device
from allennlp.common.file_utils import TensorCache
from allennlp.data.dataset_readers.datase... | code_fim | hard | {
"lang": "python",
"repo": "allenai/allennlp-models",
"path": "/allennlp_models/vision/dataset_readers/vision_reader.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # store the processed results in memory, so we can complete the batch
paths_to_tensors = {}
for i, path in enumerate(paths):
if class_probs:
class_probs_tensor = class_probs[i]
else:
class_probs_ten... | code_fim | hard | {
"lang": "python",
"repo": "allenai/allennlp-models",
"path": "/allennlp_models/vision/dataset_readers/vision_reader.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: allenai/allennlp-models path: /allennlp_models/vision/dataset_readers/vision_reader.py
ta.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.image_loader import ImageLoader
from allennlp.data.token_indexers import PretrainedTransformerIndexer
from allennlp.data.token_indexers ... | code_fim | hard | {
"lang": "python",
"repo": "allenai/allennlp-models",
"path": "/allennlp_models/vision/dataset_readers/vision_reader.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> es = Elasticsearch( [ELASTICSEARCH_HOST], scheme=ELASTICSEARCH_SCHEME, port=ELASTICSEARCH_PORT )
try:
generate_logs(LOG_DIR, es)
except Exception as e:
print('Unexpected exception in execute: {}'.format(str(e)))
return
###########################################################... | code_fim | hard | {
"lang": "python",
"repo": "exNewbie/cloudtrail-2-ek",
"path": "/python-import/import.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: exNewbie/cloudtrail-2-ek path: /python-import/import.py
#!/usr/local/bin/python
import gzip
import sys
import os
import json
import datetime
from datetime import datetime
from elasticsearch import Elasticsearch
from datetime import datetime
LOG_DIR = '/mnt'
ELASTICSEARCH_HOST = 'elasticsearch'
... | code_fim | hard | {
"lang": "python",
"repo": "exNewbie/cloudtrail-2-ek",
"path": "/python-import/import.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DecentMark/decentmark path: /demo/student_demo.py
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
<|fim_suffix|>ass_name = "assignment 123"
driver.find_element_by_link_text(ass_name).click()
driver.find_element_by_link_text("Make a submission").click()
solution = ... | code_fim | hard | {
"lang": "python",
"repo": "DecentMark/decentmark",
"path": "/demo/student_demo.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ass_name = "assignment 123"
driver.find_element_by_link_text(ass_name).click()
driver.find_element_by_link_text("Make a submission").click()
solution = "solution 123"
driver.find_element_by_id("id_solution").send_keys(solution)
driver.find_element_by_xpath("//button").click()<|fim_prefix|># repo: DecentM... | code_fim | hard | {
"lang": "python",
"repo": "DecentMark/decentmark",
"path": "/demo/student_demo.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: easyCZ/UoE-Projects path: /EXC/CW1/task8/combiner.py
#!/usr/bin/python
import sys
from ast import literal_eval
MARK_SHORT = 'M'
last_sid = None
marks = []
# Input is sorted by <id> and secondarily by S|M in reverse
# so that Student name comes before the marks fot that student
# Expected input... | code_fim | hard | {
"lang": "python",
"repo": "easyCZ/UoE-Projects",
"path": "/EXC/CW1/task8/combiner.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|># Expected output:
# 1 S George
# 1 M [('TTS', 80), ('EXC', 70), ('ADBS', 80)]
# 2 S Anna
# 2 M [('EXC', 65)]<|fim_prefix|># repo: easyCZ/UoE-Projects path: /EXC/CW1/task8/combiner.py
#!/usr/bin/python
import sys
from ast import literal_eval
MARK_SHORT = 'M'
last_sid = None
marks = []
... | code_fim | hard | {
"lang": "python",
"repo": "easyCZ/UoE-Projects",
"path": "/EXC/CW1/task8/combiner.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 515hikaru/essence-of-machine-learning path: /tests/test_softplus.py
import numpy as np
import pytest
from numeric_calc.range_value import softplus
def test_softplus_value1():
"""
np.exp がオーバーフローしない範囲での計算
log(1+e^{-1}) の計算
"""
y = softplus.softplus(-1)
assert isinstance... | code_fim | hard | {
"lang": "python",
"repo": "515hikaru/essence-of-machine-learning",
"path": "/tests/test_softplus.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
np.exp をそのまま計算するとオーバーフローする場合
対策済みなのでこのテストではオーバーフローせず成功する
"""
y = softplus.softplus2(1000)
assert y < 10 ** 4<|fim_prefix|># repo: 515hikaru/essence-of-machine-learning path: /tests/test_softplus.py
import numpy as np
import pytest
from numeric_calc.range_value import sof... | code_fim | medium | {
"lang": "python",
"repo": "515hikaru/essence-of-machine-learning",
"path": "/tests/test_softplus.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sumitnagal/test-tools path: /chaostoolkit/data/utils.py
import json
import subprocess
import sys
import os
import time
import requests
import logging
import threading
from jinja2 import Environment, FileSystemLoader, select_autoescape
import yaml
logger = logging.getLogger(__name__)
<|fim_suffi... | code_fim | hard | {
"lang": "python",
"repo": "sumitnagal/test-tools",
"path": "/chaostoolkit/data/utils.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> env_tmpl = Environment(loader = FileSystemLoader('./'), trim_blocks=True, lstrip_blocks=True, autoescape=select_autoescape(['yaml']))
template = env_tmpl.get_template('chaos-result.j2')
updated_chaosresult_template = template.render(c_experiment=exp_name, phase=exp_phase, verdict=e... | code_fim | hard | {
"lang": "python",
"repo": "sumitnagal/test-tools",
"path": "/chaostoolkit/data/utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
chaos_result_tracker() creates/patches the litmus chaosresult custom resource in the provided namespace.
Typically invoked before and after chaos, and takes the .spec.phase, .spec.verdict & namespace as as args.
"""
def chaos_result_tracker(self, exp_name, exp_phase, exp_verdict, n... | code_fim | hard | {
"lang": "python",
"repo": "sumitnagal/test-tools",
"path": "/chaostoolkit/data/utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class SharedPrivateLinkResourceStatus(str, Enum):
"""
Status of the shared private link resource. Can be Pending, Approved, Rejected or Disconnected.
"""
PENDING = "Pending"
APPROVED = "Approved"
REJECTED = "Rejected"
DISCONNECTED = "Disconnected"
class SkuName(str, Enum):
... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-azure-native",
"path": "/sdk/python/pulumi_azure_native/search/v20220901/_enums.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
The SKU of the search service. Valid values include: 'free': Shared service. 'basic': Dedicated service with up to 3 replicas. 'standard': Dedicated service with up to 12 partitions and 12 replicas. 'standard2': Similar to standard, but with more capacity per search unit. 'standard3': The larg... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-azure-native",
"path": "/sdk/python/pulumi_azure_native/search/v20220901/_enums.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pulumi/pulumi-azure-native path: /sdk/python/pulumi_azure_native/search/v20220901/_enums.py
# coding=utf-8
# *** WARNING: this file was generated by pulumi. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
from enum import Enum
__all__ = [
'AadAuthFailure... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-azure-native",
"path": "/sdk/python/pulumi_azure_native/search/v20220901/_enums.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("Inner: ", inner, flush=True)
await inner
print("Task 1 End", flush=True)
@spawn(outer[1], dependencies=[outer[0]])
async def task3():
print("Task 3", flush=True)
print("Inner: ", inner, flush=True)
print("Outer: ", o... | code_fim | hard | {
"lang": "python",
"repo": "ut-parla/Parla.py",
"path": "/tutorial/3_devices_and_architectures/async_test.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ut-parla/Parla.py path: /tutorial/3_devices_and_architectures/async_test.py
import numpy
from parla import Parla
from parla.array import copy, clone_here
from parla.cpu import cpu
from parla.tasks import spawn
from parla.task_collections import TaskSpace
from parla.function_decorators import spec... | code_fim | medium | {
"lang": "python",
"repo": "ut-parla/Parla.py",
"path": "/tutorial/3_devices_and_architectures/async_test.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jinhao27/w3hacks path: /main/migrations/0001_initial.py
# Generated by Django 3.0.4 on 2020-04-07 05:22
import datetime
from django.conf import settings
import django.contrib.postgres.fields
from django.db import migrations, models
import django.db.models.deletion
import main.models
class Migr... | code_fim | hard | {
"lang": "python",
"repo": "jinhao27/w3hacks",
"path": "/main/migrations/0001_initial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> name='ScheduleEvent',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=50)),
('description', models.TextField(max_length=300)),
('ev... | code_fim | hard | {
"lang": "python",
"repo": "jinhao27/w3hacks",
"path": "/main/migrations/0001_initial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: christina-aigner/midnite path: /src/midnite/uncertainty/modules.py
"""Custom modules for MC dropout ensembles and uncertainty."""
import logging
from abc import ABC
from abc import abstractmethod
from typing import Tuple
from typing import Union
import torch
import tqdm
from torch import Tensor
... | code_fim | hard | {
"lang": "python",
"repo": "christina-aigner/midnite",
"path": "/src/midnite/uncertainty/modules.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
def measure_uncertainty(self, input_: Tensor) -> Tensor:
return func.variation_ratio(input_, inplace=not input_.requires_grad)
class PredictionAndUncertainties(Acquisition):
"""Module to conveniently calculate sampled mean and uncertainties."""
def measure_uncertainty(self,... | code_fim | hard | {
"lang": "python",
"repo": "christina-aigner/midnite",
"path": "/src/midnite/uncertainty/modules.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Kotaimen/awscfncli path: /awscfncli2/__main__.py
"""Main cli entry point, called when run as a package."""
<|fim_suffix|>from .cli.main import cli
def main():
"""CLI Entry point when run as module"""
cli(
auto_envvar_prefix='CFN',
prog_name='cfn-cli'
)
if __name__... | code_fim | easy | {
"lang": "python",
"repo": "Kotaimen/awscfncli",
"path": "/awscfncli2/__main__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
main()<|fim_prefix|># repo: Kotaimen/awscfncli path: /awscfncli2/__main__.py
"""Main cli entry point, called when run as a package."""
__author__ = 'kotaimen'
__date__ = '28-Feb-2018'
from .cli.main import cli
<|fim_middle|>
def main():
"""CLI Entry point when run as... | code_fim | medium | {
"lang": "python",
"repo": "Kotaimen/awscfncli",
"path": "/awscfncli2/__main__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == '__main__':
main()<|fim_prefix|># repo: Kotaimen/awscfncli path: /awscfncli2/__main__.py
"""Main cli entry point, called when run as a package."""
__author__ = 'kotaimen'
__date__ = '28-Feb-2018'
from .cli.main import cli
<|fim_middle|>def main():
"""CLI Entry point when run a... | code_fim | medium | {
"lang": "python",
"repo": "Kotaimen/awscfncli",
"path": "/awscfncli2/__main__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Close observation table
row_to_close = observation_table.get_row_to_close()
while row_to_close is not None:
# First we add new rows to the extended S set. They are added based on the values in the cells of the
# rows that is to be closed. Once those rows a... | code_fim | hard | {
"lang": "python",
"repo": "Holly-Jiang/AALpy",
"path": "/aalpy/learning_algs/non_deterministic/OnfsmLstar.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Holly-Jiang/AALpy path: /aalpy/learning_algs/non_deterministic/OnfsmLstar.py
import time
from aalpy.base import SUL, Oracle
from aalpy.learning_algs.non_deterministic.OnfsmObservationTable import NonDetObservationTable
from aalpy.learning_algs.non_deterministic.TraceTree import SULWrapper
from a... | code_fim | hard | {
"lang": "python",
"repo": "Holly-Jiang/AALpy",
"path": "/aalpy/learning_algs/non_deterministic/OnfsmLstar.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if print_level == 3:
print_observation_table(observation_table, 'non-det')
# Find counterexample
eq_query_start = time.time()
cex = eq_oracle.find_cex(hypothesis)
eq_query_time += time.time() - eq_query_start
# If no counterexample is found, re... | code_fim | hard | {
"lang": "python",
"repo": "Holly-Jiang/AALpy",
"path": "/aalpy/learning_algs/non_deterministic/OnfsmLstar.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return '\n'.join(rows)
def partition(data, indecies):
"""partitions the data into a list split at every index in indecies"""
splitdata = [data[:indecies[0]]]
splitdata += [data[indecies[i-1]:indecies[i]] for i in range(1,len(indecies))]
splitdata.append(data[indecies[-1]:])
return splitdata
def ... | code_fim | hard | {
"lang": "python",
"repo": "rootfoo/libctf",
"path": "/libctf/data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rootfoo/libctf path: /libctf/data.py
import struct
import string
def pack64(num):
"""struct.pack 64-bit int"""
return struct.pack('<Q', num) if (num > 0) else struct.pack('<q', num)
def pack32(num):
"""struct.pack 32-bit int"""
return struct.pack('<I', num) if (num > 0) else struct.pack('<... | code_fim | hard | {
"lang": "python",
"repo": "rootfoo/libctf",
"path": "/libctf/data.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> rows = []
# row length includes 2 chars for hex and 1 for spaces
rowlen = columns*(2*blocksize+1)
# printable chars, in this context, dont include whitespace
printable = string.digits + string.letters + string.punctuation
for i in range(0, row_count):
start = i*columns
ascii_string = ''
row... | code_fim | hard | {
"lang": "python",
"repo": "rootfoo/libctf",
"path": "/libctf/data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Mostrando os valores de cada variavel, o numero de vez que ela aparece
print(df['Cabin'].value_counts())<|fim_prefix|># repo: ronaldogomes96/Acelera-Dev-DataScience path: /Modulo 2/imputacaoDeDados.py
import pandas as pd
import numpy as np
df = pd.read_csv('train.csv')
<|fim_middle|>#Criando um data ... | code_fim | hard | {
"lang": "python",
"repo": "ronaldogomes96/Acelera-Dev-DataScience",
"path": "/Modulo 2/imputacaoDeDados.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ronaldogomes96/Acelera-Dev-DataScience path: /Modulo 2/imputacaoDeDados.py
import pandas as pd
import numpy as np
df = pd.read_csv('train.csv')
#Criando um data frame auxiliar
aux = pd.DataFrame( { 'colunas': df.columns,
'tipos': df.dtypes,
'percentu... | code_fim | medium | {
"lang": "python",
"repo": "ronaldogomes96/Acelera-Dev-DataScience",
"path": "/Modulo 2/imputacaoDeDados.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Tratando dados categoricos faltantes, Unknown ou moda, ou apaga mesmo
df['Cabin'] = df['Cabin'].fillna('Unknown')
#Mostrando os valores de cada variavel, o numero de vez que ela aparece
print(df['Cabin'].value_counts())<|fim_prefix|># repo: ronaldogomes96/Acelera-Dev-DataScience path: /Modulo 2/imputac... | code_fim | hard | {
"lang": "python",
"repo": "ronaldogomes96/Acelera-Dev-DataScience",
"path": "/Modulo 2/imputacaoDeDados.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JayjeetAtGithub/spack path: /var/spack/repos/builtin/packages/lua-luaposix/package.py
# Copyright 2013-2022 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
<|fim_suffix|... | code_fim | medium | {
"lang": "python",
"repo": "JayjeetAtGithub/spack",
"path": "/var/spack/repos/builtin/packages/lua-luaposix/package.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class LuaLuaposix(LuaPackage):
"""Lua posix bindings, including ncurses"""
homepage = "https://github.com/luaposix/luaposix/"
url = "https://github.com/luaposix/luaposix/archive/release-v33.4.0.tar.gz"
version(
"35.0",
sha256="a4edf2f715feff65acb009e8d1689e57ec665eb79bc36... | code_fim | medium | {
"lang": "python",
"repo": "JayjeetAtGithub/spack",
"path": "/var/spack/repos/builtin/packages/lua-luaposix/package.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: texuf/pymonster path: /pymonster/__init__.py
from datetime import datetime, timedelta
'''
#Event Example:
from pymonster import EventBase
class Event(EventBase):
def log(self, msg):
print '[CustomEventLogger][%s] %s' % (self.collection_name,msg)
EventBase.log(self, msg)
#Con... | code_fim | hard | {
"lang": "python",
"repo": "texuf/pymonster",
"path": "/pymonster/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def log(self, msg):
if verbose: logger( '[Event][%s] %s' % (self.collection_name,msg) )
db[self.collection_name].insert(
{
'_id':counter.get_next(self.collection_name)
, 'createdAt':datetime.now()
, 'msg':msg
... | code_fim | hard | {
"lang": "python",
"repo": "texuf/pymonster",
"path": "/pymonster/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if verbose: logger( '[Event][%s] %s' % (self.collection_name,msg) )
db[self.collection_name].insert(
{
'_id':counter.get_next(self.collection_name)
, 'createdAt':datetime.now()
, 'msg':msg
, 'co... | code_fim | hard | {
"lang": "python",
"repo": "texuf/pymonster",
"path": "/pymonster/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
cache = WechatCache()
import requests
r = requests.session()
print(cache.set('1', r))
print(cache.get('1'), type(cache.get('1')))<|fim_prefix|># repo: YongLuoCode/WechatSogou path: /wechatsogou/filecache.py
# -*- coding: utf-8 -*-
from werkzeug.contrib.cac... | code_fim | hard | {
"lang": "python",
"repo": "YongLuoCode/WechatSogou",
"path": "/wechatsogou/filecache.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: YongLuoCode/WechatSogou path: /wechatsogou/filecache.py
# -*- coding: utf-8 -*-
from werkzeug.contrib.cache import FileSystemCache
class WechatCache(object):
"""基于文件的缓存
"""
def __init__(self, cache_dir='cache', default_timeout=300):
"""初始化
cache_dir是缓存目录
... | code_fim | hard | {
"lang": "python",
"repo": "YongLuoCode/WechatSogou",
"path": "/wechatsogou/filecache.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def clear(self):
"""清空缓存
"""
return self.cache.clear()
def get(self, key):
"""获取缓存
获取键值key的缓存值
如果没有对应缓存，返回None
"""
return self.cache.get(key)
def add(self, key, value, timeout=None):
"""增加缓存
如果键值key对应的缓存不存在，那么增... | code_fim | medium | {
"lang": "python",
"repo": "YongLuoCode/WechatSogou",
"path": "/wechatsogou/filecache.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agustinhenze/mibs.snmplabs.com path: /pysnmp/DOCS-BPI-MIB.py
on(SingleValueConstraint(1, 2, 4))).clone(namedValues=NamedValues(("none", 1), ("unknown", 2), ("unauthorizedSid", 4)))).setMaxAccess("readonly")
if mibBuilder.loadTexts: docsBpiCmTEKKeyRejectErrorCode.setStatus('current')
docsBpiCmTEKK... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/DOCS-BPI-MIB.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agustinhenze/mibs.snmplabs.com path: /pysnmp/DOCS-BPI-MIB.py
current')
docsBpiCmAuthExpires = MibTableColumn((1, 3, 6, 1, 2, 1, 10, 127, 5, 1, 1, 1, 1, 5), DateAndTime()).setMaxAccess("readonly")
if mibBuilder.loadTexts: docsBpiCmAuthExpires.setStatus('current')
docsBpiCmAuthReset = MibTableColum... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/DOCS-BPI-MIB.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>ueRangeConstraint(1, 6048000))).setUnits('seconds').setMaxAccess("readwrite")
if mibBuilder.loadTexts: docsBpiCmtsDefaultAuthLifetime.setStatus('current')
docsBpiCmtsDefaultTEKLifetime = MibTableColumn((1, 3, 6, 1, 2, 1, 10, 127, 5, 1, 2, 1, 1, 2), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 6... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/DOCS-BPI-MIB.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> == "":
break
input1.append(x)
table = tt.make_table(input1)
tt.print_table(table)
tt.table_to_csv(path,table)<|fim_prefix|># repo: jacklin1218/boolean-algebra-to-truth-table path: /hand_input.py
import csv
import sys
import truth_table as tt
path = "table<|fim_middle|>.csv"
input1 = []
x = ... | code_fim | medium | {
"lang": "python",
"repo": "jacklin1218/boolean-algebra-to-truth-table",
"path": "/hand_input.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jacklin1218/boolean-algebra-to-truth-table path: /hand_input.py
import csv
import sys
import truth_table as tt
path = "table.csv"
input1 = []
x = ""
while True:
x = input()
if x<|fim_suffix|>ble(input1)
tt.print_table(table)
tt.table_to_csv(path,table)<|fim_middle|> == "":
break
... | code_fim | medium | {
"lang": "python",
"repo": "jacklin1218/boolean-algebra-to-truth-table",
"path": "/hand_input.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> bigquery(config, {
'description':'',
'hour':[
8
],
'auth':auth_write,
'from':{
'legacy':False,
'query':''' WITH
profile_counts AS (
SELECT userRoleId, COUNT(profileId) as profile_count
FROM `{dataset}.CM_Profiles`
GROUP BY 1 ),
permission_fingerprints AS (
SELEC... | code_fim | hard | {
"lang": "python",
"repo": "google/starthinker",
"path": "/examples/barnacle_example.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: google/starthinker path: /examples/barnacle_example.py
th the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS... | code_fim | hard | {
"lang": "python",
"repo": "google/starthinker",
"path": "/examples/barnacle_example.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: google/starthinker path: /examples/barnacle_example.py
RRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
########################################################################... | code_fim | hard | {
"lang": "python",
"repo": "google/starthinker",
"path": "/examples/barnacle_example.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: busybox11/Discorn path: /tests/test_blockchain.py
import blockchain
def test_Signature():
sk1 = blockchain.SK()
sk2 = blockchain.SK()
signature = blockchain.Signature.from_raw(sk1.sign(b"This is a test.").raw)
wrong_sig = blockchain.Signature(signature<|fim_suffix|>a test")
... | code_fim | medium | {
"lang": "python",
"repo": "busybox11/Discorn",
"path": "/tests/test_blockchain.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>.signature, sk2.vk)
assert signature.verify(b"This is a test.")
assert not signature.verify(b"This is a test")
assert not wrong_sig.verify(b"This is a test.")
assert not wrong_sig.verify(b"This is a test")<|fim_prefix|># repo: busybox11/Discorn path: /tests/test_blockchain.py
import block... | code_fim | medium | {
"lang": "python",
"repo": "busybox11/Discorn",
"path": "/tests/test_blockchain.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
("nautobot_golden_config", "0004_auto_20210616_2234"),
]
operations = [
migrations.RunPython(code=jsonify),
migrations.AlterField(
model_name="compliancerule",
name="match_config",
field=models.TextField(blank=True, ... | code_fim | hard | {
"lang": "python",
"repo": "nniehoff/nautobot-plugin-golden-config",
"path": "/nautobot_golden_config/migrations/0005_json_compliance_rule.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nniehoff/nautobot-plugin-golden-config path: /nautobot_golden_config/migrations/0005_json_compliance_rule.py
from django.db import migrations, models
import json
from nautobot_golden_config.models import ConfigCompliance
def jsonify(apps, schedma_editor):
"""Converts textfield to json in p... | code_fim | hard | {
"lang": "python",
"repo": "nniehoff/nautobot-plugin-golden-config",
"path": "/nautobot_golden_config/migrations/0005_json_compliance_rule.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MrZhihao/CDatabass path: /databass/ops/limit.py
from ..baseops import *
from ..exprs import *
from ..db import Database
from ..schema import *
from ..tuples import *
from ..util import cache, OBTuple
from itertools import chain
from ..columns import ListColumns
from pyarrow import compute
class ... | code_fim | medium | {
"lang": "python",
"repo": "MrZhihao/CDatabass",
"path": "/databass/ops/limit.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_col_up_needed(self, info=None):
return self.p.get_col_up_needed()
def hand_in_result(self):
handin_res = self.c.hand_in_result()
if handin_res.is_terminate() or self._limit == 0:
return ListColumns(self.schema, None)
return ListColumns(self.schema, [col.slice(offset=self... | code_fim | hard | {
"lang": "python",
"repo": "MrZhihao/CDatabass",
"path": "/databass/ops/limit.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self.p.get_col_up_needed()
def hand_in_result(self):
handin_res = self.c.hand_in_result()
if handin_res.is_terminate() or self._limit == 0:
return ListColumns(self.schema, None)
return ListColumns(self.schema, [col.slice(offset=self._offset,length=self._limit) for col in ha... | code_fim | hard | {
"lang": "python",
"repo": "MrZhihao/CDatabass",
"path": "/databass/ops/limit.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
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