
from __future__ import annotations

import requests

lowerCamelCase      =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 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__ = 1 ,		UpperCamelCase__ = "new" ,		UpperCamelCase__ = None		):
      UpperCamelCase__    :   Any					=				wanted_data or []
      if invalid_search_terms := ", ".join(sorted(set(UpperCamelCase__		) - valid_terms		)		):
            UpperCamelCase__    :   Union[str, Any]					=				f'''Invalid search term: {invalid_search_terms}'''
            raise ValueError(UpperCamelCase__		)
      UpperCamelCase__    :   Optional[Any]					=				requests.get(
          f'''https://reddit.com/r/{subreddit}/{age}.json?limit={limit}''' ,		headers={'''User-agent''': '''A random string'''} ,		)
      if response.status_code == 4_2_9:
            raise requests.HTTPError

      UpperCamelCase__    :   Union[str, Any]					=				response.json()
      if not wanted_data:
            return {id_: data["data"]["children"][id_] for id_ in range(UpperCamelCase__		)}

      UpperCamelCase__    :   List[Any]					=				{}
      for id_ in range(UpperCamelCase__		):
            UpperCamelCase__    :   Any					=				{
                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"]))




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase      ={
    "configuration_clipseg": [
        "CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "CLIPSegConfig",
        "CLIPSegTextConfig",
        "CLIPSegVisionConfig",
    ],
    "processing_clipseg": ["CLIPSegProcessor"],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST",
        "CLIPSegModel",
        "CLIPSegPreTrainedModel",
        "CLIPSegTextModel",
        "CLIPSegVisionModel",
        "CLIPSegForImageSegmentation",
    ]

if TYPE_CHECKING:
    from .configuration_clipseg import (
        CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
        CLIPSegConfig,
        CLIPSegTextConfig,
        CLIPSegVisionConfig,
    )
    from .processing_clipseg import CLIPSegProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_clipseg import (
            CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
            CLIPSegForImageSegmentation,
            CLIPSegModel,
            CLIPSegPreTrainedModel,
            CLIPSegTextModel,
            CLIPSegVisionModel,
        )

else:
    import sys

    lowerCamelCase      =_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


