

'''simple docstring'''


from math import sqrt

import numpy as np
from sympy import symbols

# Coefficient
# Speed of light (m/s)
lowerCAmelCase__										= 299792458

# Symbols
lowerCAmelCase__							,     lowerCAmelCase__							,     lowerCAmelCase__							,     lowerCAmelCase__										= symbols("ct x y z")







def 						SCREAMING_SNAKE_CASE(  UpperCamelCase  )    ->    float:
	if velocity > c:
		raise ValueError('Speed must not exceed light speed 299,792,458 [m/s]!'  )
	elif velocity < 1:
		# Usually the speed should be much higher than 1 (c order of magnitude)
		raise ValueError('Speed must be greater than or equal to 1!'  )

	return velocity / c







def 						SCREAMING_SNAKE_CASE(  UpperCamelCase  )    ->    float:
	return 1 / sqrt(1 - beta(UpperCamelCase  ) ** 2  )







def 						SCREAMING_SNAKE_CASE(  UpperCamelCase  )    ->    np.ndarray:
	return np.array(
	    [
	        [gamma(UpperCamelCase  ), -gamma(UpperCamelCase  ) * beta(UpperCamelCase  ), 0, 0],
	        [-gamma(UpperCamelCase  ) * beta(UpperCamelCase  ), gamma(UpperCamelCase  ), 0, 0],
	        [0, 0, 1, 0],
	        [0, 0, 0, 1],
	    ]  )







def 						SCREAMING_SNAKE_CASE(  UpperCamelCase   ,UpperCamelCase = None  )    ->    np.ndarray:
	# Ensure event is not empty
	if event is None:
		UpperCAmelCase_		:      Optional[int]       	=					np.array([ct, x, y, z]  )  # Symbolic four vector
	else:
		event[0] *= c  # x0 is ct (speed of light * time)

	return transformation_matrix(UpperCamelCase  ) @ event


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						# Example of symbolic vector:
						lowerCAmelCase__										= transform(29979245)
						print("Example of four vector: ")
						print(F'ct\' = {four_vector[0]}')
						print(F'x\' = {four_vector[1]}')
						print(F'y\' = {four_vector[2]}')
						print(F'z\' = {four_vector[3]}')

						# Substitute symbols with numerical values
						lowerCAmelCase__										= {ct: c, x: 1, y: 1, z: 1}
						lowerCAmelCase__										= [four_vector[i].subs(sub_dict) for i in range(4)]

						print(F'\n{numerical_vector}')









'''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"]))






