






import unittest

import numpy as np






def 							A     (       a_							,a_							,a_							,a_ = None							,)     ->						Any:
					__UpperCamelCase      :					Tuple       		=np.shape(a_					)
					__UpperCamelCase      :					Union[str, Any]       		=np.shape(a_					)
					__UpperCamelCase      :					Dict       		=np.shape(a_					)

					if shape_a[0] != shape_b[0]:
										__UpperCamelCase      :					Dict       		=(
										    'Expected the same number of rows for A and B. '
										    F'Instead found A of size {shape_a} and B of size {shape_b}'
										)
										raise ValueError(a_					)

					if shape_b[1] != shape_c[1]:
										__UpperCamelCase      :					Optional[Any]       		=(
										    'Expected the same number of columns for B and C. '
										    F'Instead found B of size {shape_b} and C of size {shape_c}'
										)
										raise ValueError(a_					)

					__UpperCamelCase      :					Any       		=pseudo_inv
					if a_inv is None:
										try:
															__UpperCamelCase      :					Union[str, Any]       		=np.linalg.inv(a_					)
										except np.linalg.LinAlgError:
															raise ValueError(
															    'Input matrix A is not invertible. Cannot compute Schur complement.'					)

					return mat_c - mat_b.T @ a_inv @ mat_b




class 				__A     (			unittest.TestCase ):





				"""simple docstring"""







				def       __lowercase							( self    ):




									"""simple docstring"""

									__UpperCamelCase      :					Any       		=np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]    )
									__UpperCamelCase      :					Optional[Any]       		=np.array([[0, 3], [3, 0], [2, 3]]    )
									__UpperCamelCase      :					Any       		=np.array([[2, 1], [6, 3]]    )

									__UpperCamelCase      :					int       		=schur_complement(lowerCAmelCase__							,  lowerCAmelCase__							,  lowerCAmelCase__    )

									__UpperCamelCase      :					str       		=np.block([[a, b], [b.T, c]]    )

									__UpperCamelCase      :					Dict       		=np.linalg.det(lowerCAmelCase__    )
									__UpperCamelCase      :					str       		=np.linalg.det(lowerCAmelCase__    )
									__UpperCamelCase      :					Tuple       		=np.linalg.det(lowerCAmelCase__    )

									self.assertAlmostEqual(lowerCAmelCase__							,  det_a * det_s    )


				def       __lowercase							( self    ):




									"""simple docstring"""

									__UpperCamelCase      :					Optional[int]       		=np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]    )
									__UpperCamelCase      :					Dict       		=np.array([[0, 3], [3, 0], [2, 3]]    )
									__UpperCamelCase      :					List[Any]       		=np.array([[2, 1], [6, 3]]    )

									with self.assertRaises(lowerCAmelCase__    ):
														schur_complement(lowerCAmelCase__							,  lowerCAmelCase__							,  lowerCAmelCase__    )







				def       __lowercase							( self    ):




									"""simple docstring"""

									__UpperCamelCase      :					List[str]       		=np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]    )
									__UpperCamelCase      :					Dict       		=np.array([[0, 3], [3, 0], [2, 3]]    )
									__UpperCamelCase      :					int       		=np.array([[2, 1, 3], [6, 3, 5]]    )

									with self.assertRaises(lowerCAmelCase__    ):
														schur_complement(lowerCAmelCase__							,  lowerCAmelCase__							,  lowerCAmelCase__    )


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							unittest.main()


import csv

import tweepy

# Twitter API credentials
__a  :     Union[str, Any]       =  """"""
__a  :     Union[str, Any]       =  """"""
__a  :     Union[str, Any]       =  """"""
__a  :     List[Any]       =  """"""





def 				UpperCAmelCase						(    lowercase							):







				"""simple docstring"""



				__lowercase 			=							tweepy.OAuthHandler(lowercase							,			lowercase							)
				auth.set_access_token(lowercase							,			lowercase							)
				__lowercase 			=							tweepy.API(lowercase							)

				# initialize a list to hold all the tweepy Tweets
				__lowercase 			=							[]

				# make initial request for most recent tweets (200 is the maximum allowed count)
				__lowercase 			=							api.user_timeline(screen_name=lowercase							,			count=200							)

				# save most recent tweets
				alltweets.extend(lowercase							)

				# save the id of the oldest tweet less one
				__lowercase 			=							alltweets[-1].id - 1

				# keep grabbing tweets until there are no tweets left to grab
				while len(lowercase							) > 0:
								print(F"getting tweets before {oldest}"							)

								# all subsequent requests use the max_id param to prevent duplicates
								__lowercase 			=							api.user_timeline(
								    screen_name=lowercase							,			count=200							,			max_id=lowercase							)

								# save most recent tweets
								alltweets.extend(lowercase							)

								# update the id of the oldest tweet less one
								__lowercase 			=							alltweets[-1].id - 1

								print(F"...{len(lowercase							)} tweets downloaded so far"							)

				# transform the tweepy tweets into a 2D array that will populate the csv
				__lowercase 			=							[[tweet.id_str, tweet.created_at, tweet.text] for tweet in alltweets]

				# write the csv
				with open(F"new_{screen_name}_tweets.csv"							,			'''w'''							) as f:
								__lowercase 			=							csv.writer(lowercase							)
								writer.writerow(['''id''', '''created_at''', '''text''']							)
								writer.writerows(lowercase							)


if __name__ == "__main__":
		# pass in the username of the account you want to download
		get_all_tweets("""FirePing32""")