

'''simple docstring'''


from __future__ import annotations

from decimal import Decimal

from numpy import array







def 						SCREAMING_SNAKE_CASE(  UpperCamelCase  )    ->    list[list[float]]:
	UpperCAmelCase_		:      List[str]       	=					Decimal

	# Check if the provided matrix has 2 rows and 2 columns
	# since this implementation only works for 2x2 matrices
	if len(UpperCamelCase  ) == 2 and len(matrix[0]  ) == 2 and len(matrix[1]  ) == 2:
		# Calculate the determinant of the matrix
		UpperCAmelCase_		:      Optional[Any]       	=					float(
		    d(matrix[0][0]  ) * d(matrix[1][1]  ) - d(matrix[1][0]  ) * d(matrix[0][1]  )  )
		if determinant == 0:
			raise ValueError('This matrix has no inverse.'  )

		# Creates a copy of the matrix with swapped positions of the elements
		UpperCAmelCase_		:      Optional[int]       	=					[[0.0, 0.0], [0.0, 0.0]]
		UpperCAmelCase_	,    UpperCAmelCase_		:      Optional[int]       	=					matrix[1][1], matrix[0][0]
		UpperCAmelCase_	,    UpperCAmelCase_		:      List[Any]       	=					-matrix[1][0], -matrix[0][1]

		# Calculate the inverse of the matrix
		return [
		    [(float(d(UpperCamelCase  )  ) / determinant) or 0.0 for n in row] for row in swapped_matrix
		]
	elif (
	    len(UpperCamelCase  ) == 3
	    and len(matrix[0]  ) == 3
	    and len(matrix[1]  ) == 3
	    and len(matrix[2]  ) == 3
	):
		# Calculate the determinant of the matrix using Sarrus rule
		UpperCAmelCase_		:      int       	=					float(
		    (
		        (d(matrix[0][0]  ) * d(matrix[1][1]  ) * d(matrix[2][2]  ))
		        + (d(matrix[0][1]  ) * d(matrix[1][2]  ) * d(matrix[2][0]  ))
		        + (d(matrix[0][2]  ) * d(matrix[1][0]  ) * d(matrix[2][1]  ))
		    )
		    - (
		        (d(matrix[0][2]  ) * d(matrix[1][1]  ) * d(matrix[2][0]  ))
		        + (d(matrix[0][1]  ) * d(matrix[1][0]  ) * d(matrix[2][2]  ))
		        + (d(matrix[0][0]  ) * d(matrix[1][2]  ) * d(matrix[2][1]  ))
		    )  )
		if determinant == 0:
			raise ValueError('This matrix has no inverse.'  )

		# Creating cofactor matrix
		UpperCAmelCase_		:      int       	=					[
		    [d(0.0  ), d(0.0  ), d(0.0  )],
		    [d(0.0  ), d(0.0  ), d(0.0  )],
		    [d(0.0  ), d(0.0  ), d(0.0  )],
		]
		UpperCAmelCase_		:      int       	=					(d(matrix[1][1]  ) * d(matrix[2][2]  )) - (
		    d(matrix[1][2]  ) * d(matrix[2][1]  )
		)
		UpperCAmelCase_		:      Optional[int]       	=					-(
		    (d(matrix[1][0]  ) * d(matrix[2][2]  )) - (d(matrix[1][2]  ) * d(matrix[2][0]  ))
		)
		UpperCAmelCase_		:      Optional[int]       	=					(d(matrix[1][0]  ) * d(matrix[2][1]  )) - (
		    d(matrix[1][1]  ) * d(matrix[2][0]  )
		)
		UpperCAmelCase_		:      Dict       	=					-(
		    (d(matrix[0][1]  ) * d(matrix[2][2]  )) - (d(matrix[0][2]  ) * d(matrix[2][1]  ))
		)
		UpperCAmelCase_		:      Dict       	=					(d(matrix[0][0]  ) * d(matrix[2][2]  )) - (
		    d(matrix[0][2]  ) * d(matrix[2][0]  )
		)
		UpperCAmelCase_		:      List[Any]       	=					-(
		    (d(matrix[0][0]  ) * d(matrix[2][1]  )) - (d(matrix[0][1]  ) * d(matrix[2][0]  ))
		)
		UpperCAmelCase_		:      Dict       	=					(d(matrix[0][1]  ) * d(matrix[1][2]  )) - (
		    d(matrix[0][2]  ) * d(matrix[1][1]  )
		)
		UpperCAmelCase_		:      Optional[Any]       	=					-(
		    (d(matrix[0][0]  ) * d(matrix[1][2]  )) - (d(matrix[0][2]  ) * d(matrix[1][0]  ))
		)
		UpperCAmelCase_		:      Tuple       	=					(d(matrix[0][0]  ) * d(matrix[1][1]  )) - (
		    d(matrix[0][1]  ) * d(matrix[1][0]  )
		)

		# Transpose the cofactor matrix (Adjoint matrix)
		UpperCAmelCase_		:      str       	=					array(UpperCamelCase  )
		for i in range(3  ):
			for j in range(3  ):
				UpperCAmelCase_		:      int       	=					cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
		UpperCAmelCase_		:      str       	=					array(UpperCamelCase  )
		for i in range(3  ):
			for j in range(3  ):
				inverse_matrix[i][j] /= d(UpperCamelCase  )

        # Calculate the inverse of the matrix
		return [[float(d(UpperCamelCase  )  ) or 0.0 for n in row] for row in inverse_matrix]
	raise ValueError('Please provide a matrix of size 2x2 or 3x3.'  )









'''simple docstring'''


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  )    ->    dict:
	UpperCAmelCase_		:      Dict       	=					wanted_data or []
	if invalid_search_terms := ", ".join(sorted(set(UpperCamelCase  ) - valid_terms  )  ):
		UpperCAmelCase_		:      str       	=					f"""Invalid search term: {invalid_search_terms}"""
		raise ValueError(UpperCamelCase  )
	UpperCAmelCase_		:      Dict       	=					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_		:      int       	=					response.json()
	if not wanted_data:
		return {id_: data["data"]["children"][id_] for id_ in range(UpperCamelCase  )}

	UpperCAmelCase_		:      List[str]       	=					{}
	for id_ in range(UpperCamelCase  ):
		UpperCAmelCase_		:      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"]))






