"""simple docstring"""




from __future__ import annotations

import requests

__lowerCamelCase      :			Optional[int]							       =		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   :	Dict			,					__UpperCamelCase   :	Dict = 1			,					__UpperCamelCase   :	Tuple = "new"			,					__UpperCamelCase   :	Tuple = None     )							-> dict:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				wanted_data or []
  if invalid_search_terms := ", ".join(sorted(set(a__     ) - valid_terms     )     ):
    SCREAMING_SNAKE_CASE__      							=				f"""Invalid search term: {invalid_search_terms}"""
    raise ValueError(a__     )
  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 == 4_29:
    raise requests.HTTPError

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

  SCREAMING_SNAKE_CASE__      							=				{}
  for id_ in range(a__     ):
    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''']))

def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	List[Any]     )							-> Any:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				[0] * len(__UpperCamelCase     )
  SCREAMING_SNAKE_CASE__      							=				[]
  SCREAMING_SNAKE_CASE__      							=				[1] * len(__UpperCamelCase     )

  for values in graph.values():
    for i in values:
      indegree[i] += 1

  for i in range(len(__UpperCamelCase     )     ):
    if indegree[i] == 0:
      queue.append(__UpperCamelCase     )

  while queue:
    SCREAMING_SNAKE_CASE__      							=				queue.pop(0     )
    for x in graph[vertex]:
      indegree[x] -= 1

      if long_dist[vertex] + 1 > long_dist[x]:
        SCREAMING_SNAKE_CASE__      							=				long_dist[vertex] + 1

      if indegree[x] == 0:
        queue.append(__UpperCamelCase     )

  print(max(__UpperCamelCase     )     )


# Adjacency list of Graph
__lowerCamelCase      :			int							       =		{0: [2, 3, 4], 1: [2, 7], 2: [5], 3: [5, 7], 4: [7], 5: [6], 6: [7], 7: []}






longest_distance(graph)
