text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: couchbase/perfrunner path: /perfrunner/utils/debug.py
import glob
import os
import re
import shutil
import zipfile
from argparse import ArgumentParser
from collections import defaultdict
from multiprocessing import set_start_method
from pathlib import Path
from typing import List
from logger imp... | code_fim | hard | {
"lang": "python",
"repo": "couchbase/perfrunner",
"path": "/perfrunner/utils/debug.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def create_bucket_hostname(node_name: str) -> str:
node_name = node_name.split('@')[1].split('.')
hostname = '{}.{}'.format(node_name[0], node_name[1])
return hostname
def check_if_log_file_exists(bucket_name: str, file_key: str):
cmd = 'aws s3api wait object-exists \
--bucket {} \
... | code_fim | hard | {
"lang": "python",
"repo": "couchbase/perfrunner",
"path": "/perfrunner/utils/debug.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: emedvedev/pre-commit-hook-yamlfmt path: /pre_commit_hooks/yamlfmt
#!/usr/bin/env python3
"""Format YAML files."""
import argparse
import sys
from ruamel.yaml import YAML # pylint: disable=import-error
DEFAULT_INDENT = {
"mapping": 4,
"sequence": 6,
"offset": 4,
}
class Cli:
... | code_fim | hard | {
"lang": "python",
"repo": "emedvedev/pre-commit-hook-yamlfmt",
"path": "/pre_commit_hooks/yamlfmt",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Abort """
sys.stderr.write(msg)
sys.exit(1)
if __name__ == "__main__":
ARGS = Cli().parser.parse_args()
FORMATTER = Formatter(
mapping=ARGS.mapping,
sequence=ARGS.sequence,
offset=ARGS.offset,
colons=ARGS.colons,
width=ARGS.widt... | code_fim | hard | {
"lang": "python",
"repo": "emedvedev/pre-commit-hook-yamlfmt",
"path": "/pre_commit_hooks/yamlfmt",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def load_monitoring_capabilities():
"""
Loads the monitoring capabilities in terms of list
of monitorable metrics and collector API
"""
config = ConfigParser.ConfigParser()
for metric_name, metric_infos in METRICS.iteritems():
if 'monitoring' in metric_infos.keys():... | code_fim | hard | {
"lang": "python",
"repo": "IntelLabsEurope/OCCI-SLAs",
"path": "/api/create_monitoring_records.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: IntelLabsEurope/OCCI-SLAs path: /api/create_monitoring_records.py
#!/usr/bin/env python
#
# Copyright (c) 2015 Intel Innovation and Research Ireland Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You ma... | code_fim | hard | {
"lang": "python",
"repo": "IntelLabsEurope/OCCI-SLAs",
"path": "/api/create_monitoring_records.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> monitoring_records = DB.monitoring.find({'name': monitoring_sys})
if monitoring_records.count() > 0:
mon_record = monitoring_records[0]
try:
mon_metrics = mon_record['metrics']
if metric_name not in mon_metric... | code_fim | hard | {
"lang": "python",
"repo": "IntelLabsEurope/OCCI-SLAs",
"path": "/api/create_monitoring_records.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert FLAGS.field != ''
(study, rev_study) = ProcessModel(file(FLAGS.in_model))
Report(study)
print
Report(rev_study)
if __name__ == '__main__':
main(sys.argv)<|fim_prefix|># repo: rozim/KaggleFindingElo path: /study-field-... | code_fim | medium | {
"lang": "python",
"repo": "rozim/KaggleFindingElo",
"path": "/study-field-buckets.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rozim/KaggleFindingElo path: /study-field-buckets.py
#!/usr/bin/python
import sys
import cjson
import gflags
import collections
import numpy
import random
FLAGS = gflags.FLAGS
gflags.DEFINE_string('in_model', 'model.xjson', 'Output of generate-model.py')
gflags.DEFINE_string('field', '', '')
gf... | code_fim | medium | {
"lang": "python",
"repo": "rozim/KaggleFindingElo",
"path": "/study-field-buckets.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
argv = FLAGS(argv) # parse flags
except gflags.FlagsError, e:
print '%s\\nUsage: %s ARGS\\n%s' % (e, sys.argv[0], FLAGS)
sys.exit(1)
assert FLAGS.field != ''
(study, rev_study) = ProcessModel(file(FLAGS.in_model))
Report(study)
print
Report(rev_study)
... | code_fim | hard | {
"lang": "python",
"repo": "rozim/KaggleFindingElo",
"path": "/study-field-buckets.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Tencent/bk-base path: /src/datamgr/metadata/metadata_biz/types/entities/preference.py
# -*- coding: utf-8 -*-
"""
Tencent is pleased to support the open source community by making BK-BASE 蓝鲸基础平台 available.
Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
BK-BASE 蓝鲸基础平台... | code_fim | hard | {
"lang": "python",
"repo": "Tencent/bk-base",
"path": "/src/datamgr/metadata/metadata_biz/types/entities/preference.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@as_metadata
@attr.s
class DatamonitorAlertConfig(Preference):
id = attr.ib(type=int, metadata={'identifier': True, 'dgraph': {'index': ['int']}})
monitor_target = attr.ib(type=str)
monitor_config = attr.ib(type=str)
notify_config = attr.ib(type=str)
trigger_config = attr.ib(type=str)
... | code_fim | medium | {
"lang": "python",
"repo": "Tencent/bk-base",
"path": "/src/datamgr/metadata/metadata_biz/types/entities/preference.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def try_request(url, headers=None, proxies=None, times=3, interval=10, timeout=3):
"""尝试执行HTTP请求：尝试请求times次，每次请求之间间隔interval秒，如果最终请求失败则返回None"""
for _ in range(times):
if response := do_request(url=url, headers=headers, proxies=proxies, timeout=timeout):
return response
... | code_fim | hard | {
"lang": "python",
"repo": "ChangxingJiang/Utils4R",
"path": "/Utils4R/request.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ChangxingJiang/Utils4R path: /Utils4R/request.py
import time
import requests
def do_request(url, headers=None, proxies=None, timeout=3):
"""执行HTTP请求：如果请求成功则返回请求结果；如果请求失败则返回None"""
try:
if response := requests.get(url=url, headers=headers, proxies=proxies, timeout=timeout):
... | code_fim | medium | {
"lang": "python",
"repo": "ChangxingJiang/Utils4R",
"path": "/Utils4R/request.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wf-hahaha/Cognitive-Map path: /Network/navigation_network/params.py
'''
Navigation Network, Written by Xiao
For robot localization in a dynamic environment.
'''
import numpy as np
from lib.params import ADJACENT_NODES_SHIFT_GRID
ACTION_ENCODING = dict(left=np.array([1,0,0]), right=np.array([0,1,... | code_fim | hard | {
"lang": "python",
"repo": "wf-hahaha/Cognitive-Map",
"path": "/Network/navigation_network/params.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>.1, SG=0.01}
# ------------------------------------------------------------------------------
TRAIN_FRACTION = 0.7
VAL_FRACTION = 0.15
TEST_FRACTION = 0.15
# ------------------------------------------------------------------------------
DATA_DIR = './Network/datasets' # Training and validation data direct... | code_fim | hard | {
"lang": "python",
"repo": "wf-hahaha/Cognitive-Map",
"path": "/Network/navigation_network/params.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> state = env.reset()
done = False
while not done:
action = agent(state)
state, reward, done, _ = env.step(action)
episode_result['path'].append(env.controller.last_event.metadata['agent']['position'])
if done:
break
... | code_fim | hard | {
"lang": "python",
"repo": "GELIELEO/attention_on_midlevel",
"path": "/alg_thor/utils/eval.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> agent = policy
episode_result['path'].append(env.controller.last_event.metadata['agent']['position'])
state = env.reset()
done = False
while not done:
action = agent(state)
state, reward, done, _ = env.step(action)
episo... | code_fim | hard | {
"lang": "python",
"repo": "GELIELEO/attention_on_midlevel",
"path": "/alg_thor/utils/eval.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GELIELEO/attention_on_midlevel path: /alg_thor/utils/eval.py
import numpy as np
import torch
from torch.autograd import Variable
from gym_robothor.envs import env_generator
import ai2thor.util.metrics
def evaluate_with_spl(env, policy, cuda, task_config_file):
episode_results = []
for ... | code_fim | medium | {
"lang": "python",
"repo": "GELIELEO/attention_on_midlevel",
"path": "/alg_thor/utils/eval.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Conradwangt/watchmen-matryoshka-doll path: /watchmen/common/storage/storage_template.py
from enum import Enum
from typing import List
from pydantic.main import BaseModel
from watchmen.common.storage.engine_adaptor import find_template
template = find_template()
class OrderType(Enum):
"""... | code_fim | hard | {
"lang": "python",
"repo": "Conradwangt/watchmen-matryoshka-doll",
"path": "/watchmen/common/storage/storage_template.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def list_all_select(select: dict, model: BaseModel, name: str) -> list:
pass # need to do
def list_(where: dict, model: BaseModel, name: str) -> list:
return template.list_(where, model, name)
def list_select(select: dict, where: dict, model: BaseModel, name: str) -> list:
pass # need to... | code_fim | hard | {
"lang": "python",
"repo": "Conradwangt/watchmen-matryoshka-doll",
"path": "/watchmen/common/storage/storage_template.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def insert_all(data: list, model: BaseModel, name: str):
return template.insert_all(data, model, name)
def update_one(one: any, model: BaseModel, name: str) -> any:
return template.update_one(one, model, name)
def update_one_first(where: dict, updates: dict, model: BaseModel, name: str) -> Ba... | code_fim | hard | {
"lang": "python",
"repo": "Conradwangt/watchmen-matryoshka-doll",
"path": "/watchmen/common/storage/storage_template.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bcgov/mds path: /services/core-api/tests/mines/mine/resources/test_mine_incident_resource.py
import pytest
import json
from datetime import datetime, timedelta
from app.extensions import db
from app.api.incidents.models.mine_incident import MineIncident
from tests.factories import MineFactory
fro... | code_fim | hard | {
"lang": "python",
"repo": "bcgov/mds",
"path": "/services/core-api/tests/mines/mine/resources/test_mine_incident_resource.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> post_resp = test_client.post(
f'/mines/{test_mine_guid}/incidents', json=data, headers=auth_headers['full_auth_header'])
assert post_resp.status_code == 201, post_resp.response
post_data = json.loads(post_resp.data.decode())
assert post_data['mine_guid'] == str(test_mine_guid)
... | code_fim | hard | {
"lang": "python",
"repo": "bcgov/mds",
"path": "/services/core-api/tests/mines/mine/resources/test_mine_incident_resource.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: onnx/onnx path: /onnx/reference/ops/op_lp_pool.py
# Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=W0221,R0913,R0914
import numpy as np
from onnx.reference.ops.op_pool_common import CommonPool
<|fim_suffix|> def _run( # type: ign... | code_fim | medium | {
"lang": "python",
"repo": "onnx/onnx",
"path": "/onnx/reference/ops/op_lp_pool.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> kernel_element_count = np.prod(kernel_shape)
return (np.power(kernel_element_count * power_average[0], 1.0 / p),)<|fim_prefix|># repo: onnx/onnx path: /onnx/reference/ops/op_lp_pool.py
# Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=W... | code_fim | hard | {
"lang": "python",
"repo": "onnx/onnx",
"path": "/onnx/reference/ops/op_lp_pool.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gusdelact/pySearchML path: /kubeflow/components/prepare_env/run.py
import sys
import argparse
import pathlib
import gzip
import json
import requests
from typing import Dict, Any, NamedTuple
from urllib.parse import urljoin
from google.cloud import storage, bigquery
PATH = pathlib.Path(__file__... | code_fim | hard | {
"lang": "python",
"repo": "gusdelact/pySearchML",
"path": "/kubeflow/components/prepare_env/run.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> bucket_obj = storage_client.bucket(bucket)
if not bucket_obj.exists():
bucket_obj.create()
# Query GA data
query_path = PATH / f'{args.model_name}' / 'ga_data.sql'
query = open(str(query_path)).read()
print(query)
job_config = bigquery.Q... | code_fim | hard | {
"lang": "python",
"repo": "gusdelact/pySearchML",
"path": "/kubeflow/components/prepare_env/run.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bugout-dev/infestor path: /python/infestor/manager.py
from typing import Tuple, List, Optional
import os
from pathlib import Path
import libcst as cst
from . import visitors
from . import transformers
from .errors import *
from .config import (
default_config_file,
load_config,
Infe... | code_fim | hard | {
"lang": "python",
"repo": "bugout-dev/infestor",
"path": "/python/infestor/manager.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not self.is_reporter_imported():
self.add_reporter_import()
def add_reporter_import(self) -> None:
if self.is_reporter_imported():
return
transformer = transformers.ImportReporterTransformer(
self.reporter_module_path, self.reporter_objec... | code_fim | hard | {
"lang": "python",
"repo": "bugout-dev/infestor",
"path": "/python/infestor/manager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: henrikgruner/Programvareutvikling path: /backend/auction/auctions/factories.py
from datetime import datetime, timedelta
from random import randint
import factory
import factory.fuzzy
import pytz
from django.contrib.auth.models import User
<|fim_suffix|>class AuctionFactory(factory.DjangoModelFa... | code_fim | medium | {
"lang": "python",
"repo": "henrikgruner/Programvareutvikling",
"path": "/backend/auction/auctions/factories.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class AuctionFactory(factory.DjangoModelFactory):
class Meta:
model = Auction
created = datetime.now(pytz.utc)
title = factory.Faker("sentence", nb_words=4)
author = factory.Iterator(User.objects.all())
description = factory.Faker("text", max_nb_chars=200, ext_word_list=None)
... | code_fim | medium | {
"lang": "python",
"repo": "henrikgruner/Programvareutvikling",
"path": "/backend/auction/auctions/factories.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> coords = [
nextPos[0]*wratio-1.5,
nextPos[1]*hratio-1.5,
3,
3
]
pygame.draw.rect(
screen,
BLACK,
coords)
carts[nextPos] = (dirs, interDir)
if crashed:
coords = [
crashed[0]*wratio-1.5,
crashed[1]*hratio-1.5,
3,
3
... | code_fim | hard | {
"lang": "python",
"repo": "Vanojx1/AdventOfCode2018",
"path": "/D13/part1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Vanojx1/AdventOfCode2018 path: /D13/part1.py
import pygame
import numpy as np
from collections import deque
BLACK = (0,0,0)
WHITE = (255, 255, 255)
RED = (255,0,0)
GRAY = (221,221,221)
puzzleInput = open('input.txt', 'r').read().split('\n')
mineGrid = map(lambda x: list(x), puzzleInput)
def ge... | code_fim | hard | {
"lang": "python",
"repo": "Vanojx1/AdventOfCode2018",
"path": "/D13/part1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aws/aws-encryption-sdk-python path: /src/aws_encryption_sdk/internal/utils/__init__.py
# Copyright 2017 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A... | code_fim | hard | {
"lang": "python",
"repo": "aws/aws-encryption-sdk-python",
"path": "/src/aws_encryption_sdk/internal/utils/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def message_id(size):
"""Generates a new message ID.
:param size: The size of the message id to generate, in bytes
:type size: int
:returns: Message ID
:rtype: bytes
"""
return os.urandom(size)
def get_aad_content_string(content_type, is_final_frame):
"""Prepares the ap... | code_fim | hard | {
"lang": "python",
"repo": "aws/aws-encryption-sdk-python",
"path": "/src/aws_encryption_sdk/internal/utils/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: moldyn/msmhelper path: /src/msmhelper/msm/utils/linalg.py
# -*- coding: utf-8 -*-
"""Basic linear algebra method.
BSD 3-Clause License
Copyright (c) 2019-2020, Daniel Nagel
All rights reserved.
"""
import decorit
import numpy as np
from msmhelper.utils import tests
@decorit.alias('eigl')
def... | code_fim | hard | {
"lang": "python",
"repo": "moldyn/msmhelper",
"path": "/src/msmhelper/msm/utils/linalg.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def _eigenvectors(matrix, nvals):
"""Estimate eigenvectors."""
if not tests.is_quadratic(matrix):
raise TypeError('Matrix needs to be quadratic {0}'.format(matrix))
if nvals is None:
nvals = len(matrix)
elif nvals > len(matrix):
raise TypeError(
'{nval... | code_fim | hard | {
"lang": "python",
"repo": "moldyn/msmhelper",
"path": "/src/msmhelper/msm/utils/linalg.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> Estimates the right eigenvalues of a quadratic matrix.
Parameters
----------
matrix : ndarray
Quadratic 2d matrix eigenvalues or determined of.
nvals : int, optional
Number of returned eigenvalues and -vectors. Using ensures probability
of real valued matrices.... | code_fim | hard | {
"lang": "python",
"repo": "moldyn/msmhelper",
"path": "/src/msmhelper/msm/utils/linalg.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ungarj/mapchete path: /mapchete/formats/tools.py
"""
Functions handling output formats.
This module deserves a cleaner rewrite some day.
"""
import datetime
import logging
import warnings
from pprint import pformat
from typing import Dict
import dateutil.parser
from rasterio.crs import CRS
fro... | code_fim | hard | {
"lang": "python",
"repo": "ungarj/mapchete",
"path": "/mapchete/formats/tools.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Verify that both mappings of output metadata parameters are compatible.
Parameters
----------
params1 : dict
Output metadata parameters.
params2 : dict
Output metadata parameters.
"""
def _buffered_pyramid(pyramid):
if isinstance(pyramid, dict)... | code_fim | hard | {
"lang": "python",
"repo": "ungarj/mapchete",
"path": "/mapchete/formats/tools.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Iterate through dictionary and try to parse values according to strategies."""
def _parse_val(val):
for func, allowed_exception in strategies:
try:
return func(val)
except allowed_exception:
pass
else:
return v... | code_fim | hard | {
"lang": "python",
"repo": "ungarj/mapchete",
"path": "/mapchete/formats/tools.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> class Meta:
model = Post
fields = ('id', 'title', 'created_on', 'author')
author = fields.Str(attribute='author.username')<|fim_prefix|># repo: dmitriyvek/flask-blog path: /flask_blog/blog/api/serializers.py
from marshmallow import fields, validate
from flask_blog import ma
from... | code_fim | hard | {
"lang": "python",
"repo": "dmitriyvek/flask-blog",
"path": "/flask_blog/blog/api/serializers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dmitriyvek/flask-blog path: /flask_blog/blog/api/serializers.py
from marshmallow import fields, validate
from flask_blog import ma
from flask_blog.blog.models import Post
class PostDetailSerializer(ma.SQLAlchemySchema):
<|fim_suffix|> '''Schema for Post list api'''
class Meta:
... | code_fim | hard | {
"lang": "python",
"repo": "dmitriyvek/flask-blog",
"path": "/flask_blog/blog/api/serializers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bridgecrewio/checkov path: /checkov/terraform/checks/resource/aws/APIGatewayMethodSettingsCacheEnabled.py
from checkov.terraform.checks.resource.base_resource_value_check import BaseResourceValueCheck
from checkov.common.models.enums import CheckCategories
class APIGatewayMethodSettingCacheEnab... | code_fim | hard | {
"lang": "python",
"repo": "bridgecrewio/checkov",
"path": "/checkov/terraform/checks/resource/aws/APIGatewayMethodSettingsCacheEnabled.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> name = "Ensure API Gateway method setting caching is enabled"
id = "CKV_AWS_225"
supported_resources = ['aws_api_gateway_method_settings']
categories = [CheckCategories.BACKUP_AND_RECOVERY]
super().__init__(name=name, id=id, categories=categories, supported_resource... | code_fim | medium | {
"lang": "python",
"repo": "bridgecrewio/checkov",
"path": "/checkov/terraform/checks/resource/aws/APIGatewayMethodSettingsCacheEnabled.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_inspected_key(self):
return "settings/[0]/caching_enabled"
check = APIGatewayMethodSettingCacheEnabled()<|fim_prefix|># repo: bridgecrewio/checkov path: /checkov/terraform/checks/resource/aws/APIGatewayMethodSettingsCacheEnabled.py
from checkov.terraform.checks.resource.base_resourc... | code_fim | hard | {
"lang": "python",
"repo": "bridgecrewio/checkov",
"path": "/checkov/terraform/checks/resource/aws/APIGatewayMethodSettingsCacheEnabled.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: michalnand/reinforcement_learning_im path: /experiments/autoencoder_test/models/model_ae.py
import torch
import torch.nn as nn
class Model(torch.nn.Module):
def __init__(self, input_shape):
super(Model, self).__init__()
self.device = torch.device("cuda" if torch.cuda.is_avai... | code_fim | hard | {
"lang": "python",
"repo": "michalnand/reinforcement_learning_im",
"path": "/experiments/autoencoder_test/models/model_ae.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> torch.save(self.model_encoder.state_dict(), path + "model_ae_encoder.pt")
torch.save(self.model_decoder.state_dict(), path + "model_ae_decoder.pt")
def load(self, path):
print("loading ", path)
self.model_encoder.load_state_dict(torch.load(path + "model_ae_encoder.pt... | code_fim | hard | {
"lang": "python",
"repo": "michalnand/reinforcement_learning_im",
"path": "/experiments/autoencoder_test/models/model_ae.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> x_ax_subvol, x_ax_subvol_ix = \
_find_boxcar_subvolume(x_ax, self.center, self.radius)
return x_ax_subvol_ix
def overlap_potential(self, c):
"""Determine the overlap potential of object self and object c.
Overlap criterion based on the overlap potential val... | code_fim | hard | {
"lang": "python",
"repo": "aluchies/particle_packing",
"path": "/particle_packing/boxcar/Boxcar.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aluchies/particle_packing path: /particle_packing/boxcar/Boxcar.py
import numpy as np
class Boxcar(object):
"""
"""
def __init__(self, center, radius):
"""
"""
center = float(center)
self.center = center
radius = float(radius)
sel... | code_fim | hard | {
"lang": "python",
"repo": "aluchies/particle_packing",
"path": "/particle_packing/boxcar/Boxcar.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ReiiSky/flowpipe path: /flowpipe/graph.py
"""A Graph of Nodes."""
from __future__ import print_function
from __future__ import absolute_import
from ascii_canvas.canvas import Canvas
from ascii_canvas.item import Item
from ascii_canvas.item import Line
from .node import INode
__all__ = ['Graph']... | code_fim | hard | {
"lang": "python",
"repo": "ReiiSky/flowpipe",
"path": "/flowpipe/graph.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Evaluate all sub nodes."""
for node in self.evaluation_sequence:
node.evaluate()
def serialize(self):
"""Serialize the graph in it's grid form."""
data = super(Graph, self).serialize()
data['nodes'] = [node.serialize() for node in self.nodes]
... | code_fim | hard | {
"lang": "python",
"repo": "ReiiSky/flowpipe",
"path": "/flowpipe/graph.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> df_new = url2pandas(data_url, product, num_31day_blocks) # Get dataframe for block
df = df.append(df_new) # Append to existing dataframe
# Rename output dataframe columns based on requested product
# and convert to useable data types
if product == 'water_... | code_fim | hard | {
"lang": "python",
"repo": "delgadom/py_noaa",
"path": "/py_noaa/coops.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: delgadom/py_noaa path: /py_noaa/coops.py
# If the data product is water levels, check that a datum is specified
if product == 'water_level':
if datum is None:
raise ValueError('No datum specified for water level data.See'
' https://tidesand... | code_fim | hard | {
"lang": "python",
"repo": "delgadom/py_noaa",
"path": "/py_noaa/coops.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> df_L = df[df['high_low'].str.contains("L ")].copy()
df_L.rename(columns={'date_time': 'date_time_L',
'water_level': 'L_water_level'},
inplace=True)
df_LL = df[df['high_low'].str.contains("LL")].copy()
df_LL.rename(columns={'... | code_fim | hard | {
"lang": "python",
"repo": "delgadom/py_noaa",
"path": "/py_noaa/coops.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ruisunyc/leetcode_Solution path: /leetcode/0051.N皇后/0051-N皇后.py
class Solution:
def solveNQueens(self, n: int) -> List[List[str]]:
<|fim_suffix|> if row==n:
ans.append(tmp)
return
for j in range(n):
if j not in cols and r... | code_fim | easy | {
"lang": "python",
"repo": "ruisunyc/leetcode_Solution",
"path": "/leetcode/0051.N皇后/0051-N皇后.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if row==n:
ans.append(tmp)
return
for j in range(n):
if j not in cols and row+j not in sums and row-j not in subs:
dfs(row+1,tmp+[j],cols|{j},sums|{row+j},subs|{row-j})
dfs(0,[],set(),set(),set())
r... | code_fim | easy | {
"lang": "python",
"repo": "ruisunyc/leetcode_Solution",
"path": "/leetcode/0051.N皇后/0051-N皇后.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Josepe75/pvlab path: /src/pvlab/__init__.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# License: bsd-3-clause
# Copyright (C) 2021 J. P. Silva. All rights reserved.
"""
<|fim_suffix|>PVLAB is a project devoted to the development and improvement of scientific
software for the measurement, ... | code_fim | medium | {
"lang": "python",
"repo": "Josepe75/pvlab",
"path": "/src/pvlab/__init__.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>PVLAB is a project devoted to the development and improvement of scientific
software for the measurement, calibration and modeling of the performance of
photovoltaic devices and solar sensors. PVLAB package born from the efforts
in data treatment for the calibration of pyranometers at
the Laboratory of Ph... | code_fim | medium | {
"lang": "python",
"repo": "Josepe75/pvlab",
"path": "/src/pvlab/__init__.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zhangx1923/-QuQ- path: /baseClass/Gate.py
#!/usr/bin/python3
from baseGate import *
#the dict will be used in SplitGate of Gate.py
elementGate = {
"X":"CNOT cq-0,tq-0;",
"Y":"Sd tq-0;CNOT cq-0,tq-0;S tq-0;",
"Z":"H tq-0;CNOT cq-0,tq-0;H tq-0;",
"H":"H tq-0;Sd tq-0;CNOT cq-0,tq-0;H tq-0;T tq-... | code_fim | hard | {
"lang": "python",
"repo": "zhangx1923/-QuQ-",
"path": "/baseClass/Gate.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Z = [[1,0],[0,-1]]
gate = Gate([q],Z,"Z")
return gate.singleOperator(record,forceQuit = forceQuit)
def I(q:Qubit,record = True,forceQuit = False):
I = [[1,0],[0,1]]
gate = Gate([q],I,"I")
return gate.singleOperator(record,forceQuit = forceQuit)
def H(q:Qubit,record = True,forceQuit = False):
H =... | code_fim | hard | {
"lang": "python",
"repo": "zhangx1923/-QuQ-",
"path": "/baseClass/Gate.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>array[0][2] = 9
array[1][0] = 7
array[2][2] = 3
print(array)<|fim_prefix|># repo: jlcatonjr/Learn-Python-for-Stats-and-Econ path: /In Class Projects/In Class Examples Spring 2019/Section 5/numpyzeros.py
#numpyzeros.py
import numpy as np
<|fim_middle|>array = np.zeros((3,3))
empty_array = np.empty((5,3))... | code_fim | medium | {
"lang": "python",
"repo": "jlcatonjr/Learn-Python-for-Stats-and-Econ",
"path": "/In Class Projects/In Class Examples Spring 2019/Section 5/numpyzeros.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jlcatonjr/Learn-Python-for-Stats-and-Econ path: /In Class Projects/In Class Examples Spring 2019/Section 5/numpyzeros.py
#numpyzeros.py
import numpy as np
<|fim_suffix|>array[0][2] = 9
array[1][0] = 7
array[2][2] = 3
print(array)<|fim_middle|>array = np.zeros((3,3))
empty_array = np.empty((5,3))... | code_fim | medium | {
"lang": "python",
"repo": "jlcatonjr/Learn-Python-for-Stats-and-Econ",
"path": "/In Class Projects/In Class Examples Spring 2019/Section 5/numpyzeros.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ct1799/clicks-to-hitler path: /clickstohitler.py
import bs4 as bs
import urllib.request
import re
def game_setup():
"""begins the clicks-to-hitler game
"""
article_setup = ''
current_article = ''
counter_setup = -1
current_counter = 0
foundHitler = False
#list tha... | code_fim | hard | {
"lang": "python",
"repo": "ct1799/clicks-to-hitler",
"path": "/clickstohitler.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """returns a list of wiki article urls from a single wiki url
Parameters
----------
sourceURL : str
the wiki url that you are extracting article links from
"""
sourceURL = sourceURL.encode().decode()
articleList = []
soup = bs.BeautifulSoup(urllib.request.urlopen(s... | code_fim | hard | {
"lang": "python",
"repo": "ct1799/clicks-to-hitler",
"path": "/clickstohitler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>r = requests.get(url)
if not r:
print('download failed, try again or download %s manually' % url)
exit()
open('temp.zip', 'wb').write(r.content)
zipfile.ZipFile('temp.zip').extractall()
os.rename(zipfile.ZipFile('temp.zip').namelist()[0], folder)
os.remove('temp.zip')<|fim_prefix|># repo: jarekt/... | code_fim | medium | {
"lang": "python",
"repo": "jarekt/SDLchip",
"path": "/getSDL.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jarekt/SDLchip path: /getSDL.py
#simple script for downloading github repos(zip files) easily
import requests
import zipfile
import os
url = 'https://www.libsdl.org/release/SDL2-2.0.9.zip'
folder = 'SDL'
#zip contents into this ^ folder
<|fim_suffix|>zipfile.ZipFile('temp.zip').extractall()
os.... | code_fim | medium | {
"lang": "python",
"repo": "jarekt/SDLchip",
"path": "/getSDL.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>zipfile.ZipFile('temp.zip').extractall()
os.rename(zipfile.ZipFile('temp.zip').namelist()[0], folder)
os.remove('temp.zip')<|fim_prefix|># repo: jarekt/SDLchip path: /getSDL.py
#simple script for downloading github repos(zip files) easily
import requests
import zipfile
import os
<|fim_middle|>url = 'htt... | code_fim | hard | {
"lang": "python",
"repo": "jarekt/SDLchip",
"path": "/getSDL.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wenkairen/RoboND-Rover-Project path: /RoboND-Rover-Project/code/perception.py
import numpy as np
import cv2
# Identify pixels above the threshold
# Threshold of RGB > 160 does a nice job of identifying ground pixels only
def color_thresh(img, rgb_thresh=(160, 160, 160),rock_thresh = (20,100,100)... | code_fim | hard | {
"lang": "python",
"repo": "wenkairen/RoboND-Rover-Project",
"path": "/RoboND-Rover-Project/code/perception.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> x_world, y_world = pix_to_world(xpix, ypix,
Rover.pos[0], Rover.pos[1],Rover.yaw,
Rover.worldmap.shape[0],scale)
obs_x_world, obs_y_world = pix_to_world(obsxpix, obsypix,
... | code_fim | hard | {
"lang": "python",
"repo": "wenkairen/RoboND-Rover-Project",
"path": "/RoboND-Rover-Project/code/perception.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: syllamacedo/exercicios_python path: /curso_em_video/ex104_validando_entrada_dados_com_funcao.py
# Exercício Python 104: Crie um programa que tenha a função leiaInt(), que vai funcionar de forma semelhante
# ‘a função input() do Python, só que fazendo a validação para aceitar apenas um valor numér... | code_fim | medium | {
"lang": "python",
"repo": "syllamacedo/exercicios_python",
"path": "/curso_em_video/ex104_validando_entrada_dados_com_funcao.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
n = leiaint(input('Digite um número inteiro: '))
print(f'Você acabou de digitar o número {n}.')<|fim_prefix|># repo: syllamacedo/exercicios_python path: /curso_em_video/ex104_validando_entrada_dados_com_funcao.py
# Exercício Python 104: Crie um programa que tenha a função leiaInt(), que vai funcionar de... | code_fim | medium | {
"lang": "python",
"repo": "syllamacedo/exercicios_python",
"path": "/curso_em_video/ex104_validando_entrada_dados_com_funcao.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>print ("MAC - IP")
macs = []
for snd, rcv in ans:
macs.append(rcv.sprintf(r"%Ether.src%"))
print (rcv.sprintf(r"%Ether.src% - %ARP.psrc%"))
#print macs
stop_time = datetime.now()
total_time = stop_time - start_time
print ("\n[*] Done in %s" %(total_time))<|fim_prefix|># repo: kodefish/pyarp path... | code_fim | medium | {
"lang": "python",
"repo": "kodefish/pyarp",
"path": "/arp.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kodefish/pyarp path: /arp.py
import sys
from datetime import datetime
from scapy.all import srp, Ether, ARP, conf
try:
interface = raw_input("[*] Enter Desired interface: ") #Get interface to scan
ips = raw_input("[*] Enter Range of IPs to Scan for : ") #Get IP or IP range to scan
except... | code_fim | medium | {
"lang": "python",
"repo": "kodefish/pyarp",
"path": "/arp.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> result.append(random.choice(all[i]))
#choice of one of all elements and append to list.
i=i+1
print(*result)
#print result list's elements.<|fim_prefix|># repo: ozturkemre/programming-challanges path: /10-RandomSentenceGenerator/RandomSentenceGenerator.py
import random
nouns=("John","Plato"... | code_fim | medium | {
"lang": "python",
"repo": "ozturkemre/programming-challanges",
"path": "/10-RandomSentenceGenerator/RandomSentenceGenerator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ozturkemre/programming-challanges path: /10-RandomSentenceGenerator/RandomSentenceGenerator.py
import random
nouns=("John","Plato","Sharon","Grandfather","Dog","Cat","Money","Horse","Tree")
verbs=("runs","hear","know","believe","is","call","drives","jumps")
adv=("financially","willfully","abrupt... | code_fim | medium | {
"lang": "python",
"repo": "ozturkemre/programming-challanges",
"path": "/10-RandomSentenceGenerator/RandomSentenceGenerator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# Setting path and files
session_path = "session_data/" + session_folder + "/"
test_folder = session_path + "test_" + type_of_cal + "/"
config_filename = session_path + "config.csv"
cal_filename = test_folder + "training_fixation.csv"
analyzer = gda.GazeDataAnalyzer()
print("\nSETUP TRANSFORMATION")
an... | code_fim | hard | {
"lang": "python",
"repo": "Toonwire/infancy_eye_tracking",
"path": "/sim_visual_angle.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Toonwire/infancy_eye_tracking path: /sim_visual_angle.py
# -*- coding: utf-8 -*-
"""
Created on Wed Jun 12 11:21:04 2019
@author: Toonw
"""
import numpy as np
import gaze_data_analyzer as gda
import matplotlib.pyplot as plt
import math
# Run analyse on
type_of_cal = "default"
#type_of_cal ... | code_fim | hard | {
"lang": "python",
"repo": "Toonwire/infancy_eye_tracking",
"path": "/sim_visual_angle.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># X行/(Y+1) - W列
for i in range(Y+1, W+1):
if S[X][i] == '#':
break
ans += 1
print(ans)<|fim_prefix|># repo: FGtatsuro/myatcoder path: /beginner_contest/197/B.py
import sys
input = sys.stdin.readline
sys.setrecursionlimit(10 ** 7)
<|fim_middle|>H, W, X, Y = map(int, input().split())
S = ... | code_fim | hard | {
"lang": "python",
"repo": "FGtatsuro/myatcoder",
"path": "/beginner_contest/197/B.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># 1 - (X-1)行/Y列
for i in range(X-1, 0, -1):
if S[i][Y] == '#':
break
ans += 1
# (X+1) - H行/Y列
for i in range(X+1, H+1):
if S[i][Y] == '#':
break
ans += 1
# X行/1 - (Y-1)列
for i in range(Y-1, 0, -1):
if S[X][i] == '#':
break
ans += 1
# X行/(Y+1) - W列
for... | code_fim | medium | {
"lang": "python",
"repo": "FGtatsuro/myatcoder",
"path": "/beginner_contest/197/B.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FGtatsuro/myatcoder path: /beginner_contest/197/B.py
import sys
input = sys.stdin.readline
sys.setrecursionlimit(10 ** 7)
H, W, X, Y = map(int, input().split())
S = [0] * (H+1)
for i in range(H):
S[i+1] = [0] + list(input().strip())
ans = 0
# X行/y列
ans += 1
<|fim_suffix|># X行/1 - (Y-1)列
f... | code_fim | medium | {
"lang": "python",
"repo": "FGtatsuro/myatcoder",
"path": "/beginner_contest/197/B.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: marcortiz11/FastComposedModels path: /Source/pytorch/classifier_metadata.py
import torch
from Source.io_util import read_pickle
from Source.pytorch.component import Component
from Data.datasets import Split
class ClassifierMetadata(Component):
def __init__(self, path_to_pickle: str, split=... | code_fim | hard | {
"lang": "python",
"repo": "marcortiz11/FastComposedModels",
"path": "/Source/pytorch/classifier_metadata.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> precomputed_pred = torch.from_numpy(precomputed_pred)
self.update_processing_time(ids.numel() * time_batch_128/128.0)
self.predictions = precomputed_pred[ids].to(ids.device)
return self.predictions
def set_evaluation_split(self, split: Split):
self.split = spli... | code_fim | hard | {
"lang": "python",
"repo": "marcortiz11/FastComposedModels",
"path": "/Source/pytorch/classifier_metadata.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Call component's class constructor
self.path = path_to_pickle
self.split = split
metadata = read_pickle(self.path)
parameters = metadata['metrics']['params']
super().__init__(p=parameters)
# This way predictions can be manipulated on GPU
se... | code_fim | medium | {
"lang": "python",
"repo": "marcortiz11/FastComposedModels",
"path": "/Source/pytorch/classifier_metadata.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
picks false color bands from the 12 Sentinel bands (for visual interpretation of vegetation)
:param input: 12-band image tensor
:return: 3-band NIR-RED-GREEN tensor
"""
rgb_band_idxs = [bands.index(b) for b in ["S2B8", "S2B4", "S2B3"]]
return input[rgb_band_idxs]
def equa... | code_fim | hard | {
"lang": "python",
"repo": "MarcCoru/dino",
"path": "/sen12ms/transforms.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MarcCoru/dino path: /sen12ms/transforms.py
import skimage.exposure
import numpy as np
import albumentations as A
from albumentations.pytorch import ToTensorV2
#import torchvision.transforms as T
bands = ["S2B1", "S2B2", "S2B3", "S2B4", "S2B5", "S2B6", "S2B7", "S2B8", "S2B8A", "S2B9", "S2B10", "S... | code_fim | hard | {
"lang": "python",
"repo": "MarcCoru/dino",
"path": "/sen12ms/transforms.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># http://121.0.0.0:5000/message?question=what
@app.route('/message')
def return_message_response():
message = request.args.get('question')
# Add content to conversation
bot.update_conversation(message)
bot.threaded_call()
print message
response = bot.dummy_answer(message)
retur... | code_fim | hard | {
"lang": "python",
"repo": "educriado/junction-2016",
"path": "/src/app.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: educriado/junction-2016 path: /src/app.py
#!flask/bin/python
from flask import Flask
from flask import jsonify
from flask import request
from bot import Bot
<|fim_suffix|> return "Hello, World!"
topics_count = {'cats': 1, 'sports': 1, 'music': 1}
topic_files = [i + '.aiml' for i in topics_c... | code_fim | medium | {
"lang": "python",
"repo": "educriado/junction-2016",
"path": "/src/app.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yeonan/TopDownNvidia path: /src/errors/metric_measure_errors.py
"""
Mistakes launched by MetricMeasure class
and its subclasses in the hierarchy.
@date: Jan 2021
@version: 1.0
"""
class DataStructuresOfEventError(Exception):
"""Exception raised when an event is defined in a data str... | code_fim | medium | {
"lang": "python",
"repo": "yeonan/TopDownNvidia",
"path": "/src/errors/metric_measure_errors.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Exception raised when a metric is defined in a data structure,
but not in another that should be."""
C_ERROR_MESSAGE : str = ("Following metric is defined in a data" +
" structure, but not in another that should be: ")
def __init__(self, metric_name : str):
""... | code_fim | medium | {
"lang": "python",
"repo": "yeonan/TopDownNvidia",
"path": "/src/errors/metric_measure_errors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Attributes:
metric_name : str ; name of the metric that produced the error
"""
super().__init__(self.C_ERROR_MESSAGE + metric_name)
pass<|fim_prefix|># repo: yeonan/TopDownNvidia path: /src/errors/metric_measure_errors.py
"""
Mistakes launched by Metr... | code_fim | hard | {
"lang": "python",
"repo": "yeonan/TopDownNvidia",
"path": "/src/errors/metric_measure_errors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for file_name in os.listdir(path):
noun_list_negative = ""
with open(path+file_name, 'r') as file:
#month = file_name.rsplit("_")
my_file = file_name.rsplit(".txt")
for line in file:
blob = TextBlob(line)
for sentence in blob.sentences:
# if sentence.sentiment.polarity < 0:
for nwo... | code_fim | medium | {
"lang": "python",
"repo": "sagarkrkv/Yelp-Dataset-Challenge",
"path": "/Other Trials/noun_phrase_extraction.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if not os.path.exists(output_path):
os.makedirs(output_path)
noun_list_positive = ""
for file_name in os.listdir(path):
noun_list_negative = ""
with open(path+file_name, 'r') as file:
#month = file_name.rsplit("_")
my_file = file_name.rsplit(".txt")
for line in file:
blob = TextBlob(li... | code_fim | medium | {
"lang": "python",
"repo": "sagarkrkv/Yelp-Dataset-Challenge",
"path": "/Other Trials/noun_phrase_extraction.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sagarkrkv/Yelp-Dataset-Challenge path: /Other Trials/noun_phrase_extraction.py
import nltk
from nltk.tag import pos_tag
from nltk.tokenize import word_tokenize
import os
from textblob import TextBlob
from nltk.stem.snowball import EnglishStemmer
stemmer = EnglishStemmer()
<|fim_suffix|>
if not ... | code_fim | medium | {
"lang": "python",
"repo": "sagarkrkv/Yelp-Dataset-Challenge",
"path": "/Other Trials/noun_phrase_extraction.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SelvorWhim/competitive path: /Codewars/HowOldWillIBeIn2099.py
def calculate_age(year_of_birth, current_year):
delta = current_year - year_of_birth
<|fim_suffix|>bs(delta) == 1 else "years"
if delta > 0:
return "You are {} {} old.".format(delta, year_s)
else:
retu... | code_fim | medium | {
"lang": "python",
"repo": "SelvorWhim/competitive",
"path": "/Codewars/HowOldWillIBeIn2099.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>bs(delta) == 1 else "years"
if delta > 0:
return "You are {} {} old.".format(delta, year_s)
else:
return "You will be born in {} {}.".format(-delta, year_s)<|fim_prefix|># repo: SelvorWhim/competitive path: /Codewars/HowOldWillIBeIn2099.py
def calculate_age(year_of_birth, curr... | code_fim | medium | {
"lang": "python",
"repo": "SelvorWhim/competitive",
"path": "/Codewars/HowOldWillIBeIn2099.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> context = super(JiraConfigView, self).get_context()
context['body_class'] = 'aui-page-focused aui-page-size-medium'
return context
def get(self, request, *args, **kwargs):
try:
jira_auth = self.get_jira_auth()
except (ApiError, JiraTenant.DoesNotExi... | code_fim | hard | {
"lang": "python",
"repo": "craigmichaelmartin/sentry-plugins",
"path": "/src/sentry_plugins/jira_ac/views.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: craigmichaelmartin/sentry-plugins path: /src/sentry_plugins/jira_ac/views.py
from __future__ import absolute_import
import json
from six.moves.urllib.parse import urlparse
from django.forms.util import ErrorList
from django.http import HttpResponse
from django.views.decorators.csrf import csrf... | code_fim | hard | {
"lang": "python",
"repo": "craigmichaelmartin/sentry-plugins",
"path": "/src/sentry_plugins/jira_ac/views.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> with open('dog_names.txt', 'r') as f:
dog_names = f.read().splitlines()
f.close()
breed = dog_names[np.argmax(predicted_vector)]
return breed
def classify_dog_breed(img_path):
'''
Input:
img_path: string-valued file path to a color image
Output:
... | code_fim | hard | {
"lang": "python",
"repo": "cmeng94/dog-breed-classifier",
"path": "/app/dog_classifier.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
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