

'''simple docstring'''







from __future__ import annotations

import requests

__lowerCamelCase									=     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    UpperCAmelCase__     (   UpperCAmelCase__,							UpperCAmelCase__ = 1,							UpperCAmelCase__ = "new",							UpperCAmelCase__ = None					)      ->      dict:
       A_						       =   wanted_data or []
       if invalid_search_terms := ", ".join(sorted(set(UpperCAmelCase__					) - valid_terms					)					):
              A_						       =   F'''Invalid search term: {invalid_search_terms}'''
              raise ValueError(UpperCAmelCase__					)
       A_						       =   requests.get(
           F'''https://reddit.com/r/{subreddit}/{age}.json?limit={limit}''',							headers={"""User-agent""": """A random string"""},							)
       if response.status_code == 4_29:
              raise requests.HTTPError

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

       A_						       =   {}
       for id_ in range(UpperCAmelCase__					):
              A_						       =   {
                  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'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available


__lowerCamelCase									=     {
    '''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieConfig''', '''ErnieOnnxConfig'''],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase									=     [
          '''ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''ErnieForCausalLM''',
          '''ErnieForMaskedLM''',
          '''ErnieForMultipleChoice''',
          '''ErnieForNextSentencePrediction''',
          '''ErnieForPreTraining''',
          '''ErnieForQuestionAnswering''',
          '''ErnieForSequenceClassification''',
          '''ErnieForTokenClassification''',
          '''ErnieModel''',
          '''ErniePreTrainedModel''',
      ]

if TYPE_CHECKING:
      from .configuration_ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig, ErnieOnnxConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_ernie import (
                ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST,
                ErnieForCausalLM,
                ErnieForMaskedLM,
                ErnieForMultipleChoice,
                ErnieForNextSentencePrediction,
                ErnieForPreTraining,
                ErnieForQuestionAnswering,
                ErnieForSequenceClassification,
                ErnieForTokenClassification,
                ErnieModel,
                ErniePreTrainedModel,
            )

else:
      import sys

      __lowerCamelCase									=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
