





"""simple docstring"""




from __future__ import annotations

import requests

a		:				str  			=    set(
    '''approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_utc downs
edited gilded gildings hidden hide_score is_created_from_ads_ui is_meta
is_original_content is_reddit_media_domain is_video link_flair_css_class
link_flair_richtext link_flair_text link_flair_text_color media_embed mod_reason_title
name permalink pwls quarantine saved score secure_media secure_media_embed selftext
subreddit subreddit_name_prefixed subreddit_type thumbnail title top_awarded_type
total_awards_received ups upvote_ratio url user_reports'''.split()
)






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					str					, _lowercase		:					int = 1					, _lowercase		:					str = "new"					, _lowercase		:					list | None = None      )				->dict:






 '''simple docstring'''






 a   :	Dict			=       wanted_data or []
 if invalid_search_terms := ", ".join(sorted(set(_lowercase      ) - valid_terms      )      ):
  a   :	Any			=       F"""Invalid search term: {invalid_search_terms}"""
  raise ValueError(_lowercase      )
 a   :	str			=       requests.get(
     F"""https://reddit.com/r/{subreddit}/{age}.json?limit={limit}"""					, headers={"User-agent": "A random string"}					, )
 if response.status_code == 429:
  raise requests.HTTPError

 a   :	Optional[Any]			=       response.json()
 if not wanted_data:
  return {id_: data["data"]["children"][id_] for id_ in range(_lowercase      )}

 a   :	int			=       {}
 for id_ in range(_lowercase      ):
  a   :	Tuple			=       {
      item: data["data"]["children"][id_]["data"][item] for item in wanted_data
  }
 return data_dict


if __name__ == "__main__":
  # If you get Error 429, that means you are rate limited.Try after some time
  print(get_subreddit_data('''learnpython''', wanted_data=['''title''', '''url''', '''selftext''']))









"""simple docstring"""




# Copyright 2021 The HuggingFace Team. 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.
# You may obtain a copy of the License at
#
#     http://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 IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os

from accelerate.test_utils import execute_subprocess_async






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					str=None      )				->Optional[Any]:






	'''simple docstring'''






	if subparsers is not None:
		a   :	Dict			=       subparsers.add_parser("test"      )
	else:
		a   :	Tuple			=       argparse.ArgumentParser("Accelerate test command"      )

	parser.add_argument(
	    "--config_file"					, default=_lowercase					, help=(
	        "The path to use to store the config file. Will default to a file named default_config.yaml in the cache "
	        "location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have "
	        "such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed "
	        "with 'huggingface'."
	    )					, )

	if subparsers is not None:
		parser.set_defaults(func=_lowercase      )
	return parser






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					str      )				->str:






	'''simple docstring'''






	a   :	List[Any]			=       os.path.sep.join(__file__.split(os.path.sep      )[:-2] + ["test_utils", "scripts", "test_script.py"]      )

	if args.config_file is None:
		a   :	int			=       script_name
	else:
		a   :	int			=       F"""--config_file={args.config_file} {script_name}"""

	a   :	Optional[int]			=       ["accelerate-launch"] + test_args.split()
	a   :	Optional[int]			=       execute_subprocess_async(_lowercase					, env=os.environ.copy()      )
	if result.returncode == 0:
		print("Test is a success! You are ready for your distributed training!"      )






def    _SCREAMING_SNAKE_CASE	(			)				->Tuple:






	'''simple docstring'''






	a   :	Any			=       test_command_parser()
	a   :	Union[str, Any]			=       parser.parse_args()
	test_command(_lowercase      )


if __name__ == "__main__":
		main()


