





'''simple docstring'''

from __future__ import annotations

import requests

a   	=    set(
    "approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories created_utc downs\nedited gilded gildings hidden hide_score is_created_from_ads_ui is_meta\nis_original_content is_reddit_media_domain is_video link_flair_css_class\nlink_flair_richtext link_flair_text link_flair_text_color media_embed mod_reason_title\nname permalink pwls quarantine saved score secure_media secure_media_embed selftext\nsubreddit subreddit_name_prefixed subreddit_type thumbnail title top_awarded_type\ntotal_awards_received ups upvote_ratio url user_reports".split()
)

def     __magic_name__							(				__UpperCAmelCase				,						__UpperCAmelCase = 1				,						__UpperCAmelCase = "new"				,						__UpperCAmelCase = None   )    ->       dict:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE   				=							wanted_data or []
   if invalid_search_terms := ", ".join(sorted(set(__UpperCAmelCase   ) - valid_terms   )   ):
      __SCREAMING_SNAKE_CASE   				=							f"""Invalid search term: {invalid_search_terms}"""
      raise ValueError(__UpperCAmelCase   )
   __SCREAMING_SNAKE_CASE   				=							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

   __SCREAMING_SNAKE_CASE   				=							response.json()
   if not wanted_data:
      return {id_: data["data"]["children"][id_] for id_ in range(__UpperCAmelCase   )}

   __SCREAMING_SNAKE_CASE   				=							{}
   for id_ in range(__UpperCAmelCase   ):
      __SCREAMING_SNAKE_CASE   				=							{
          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"]))











import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


lowerCamelCase__					:  Union[str, Any]      							=				logging.get_logger(__name__)





class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE   ):


 '''simple docstring'''







 def __init__(				self    :						Dict							,							*_lowerCAmelCase    :						Optional[Any]							,							**_lowerCAmelCase    :						Any		):
       warnings.warn(
           'The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use LayoutLMv2ImageProcessor instead.'							,							_lowerCAmelCase							,							)
       super().__init__(*_lowerCAmelCase							,							**_lowerCAmelCase		)