


from __future__ import annotations

import numpy as np
from numpy import floataa
from numpy.typing import NDArray

def       lowercase_		(		_A			:    NDArray[floataa]    ,					_A			:    NDArray[floataa]    ,					_A			:    list[int]    ,					_A			:    int    ,					):

      """simple docstring"""




      lowerCamelCase__    ,   lowerCamelCase__		:				List[str]    =  coefficient_matrix.shape
      lowerCamelCase__    ,   lowerCamelCase__		:				Union[str, Any]    =  constant_matrix.shape

      if rowsa != colsa:
            lowerCamelCase__		:				Dict    =  F"Coefficient matrix dimensions must be nxn but received {rowsa}x{colsa}"
            raise ValueError(__lowerCAmelCase						)

      if colsa != 1:
            lowerCamelCase__		:				Optional[Any]    =  F"Constant matrix must be nx1 but received {rowsa}x{colsa}"
            raise ValueError(__lowerCAmelCase						)

      if rowsa != rowsa:
            lowerCamelCase__		:				List[Any]    =  (
                "Coefficient and constant matrices dimensions must be nxn and nx1 but "
                F"received {rowsa}x{colsa} and {rowsa}x{colsa}"
            )
            raise ValueError(__lowerCAmelCase						)

      if len(__lowerCAmelCase						) != rowsa:
            lowerCamelCase__		:				Optional[int]    =  (
                "Number of initial values must be equal to number of rows in coefficient "
                F"matrix but received {len(__lowerCAmelCase						)} and {rowsa}"
            )
            raise ValueError(__lowerCAmelCase						)

      if iterations <= 0:
            raise ValueError("Iterations must be at least 1"						)

      lowerCamelCase__		:				List[str]    =  np.concatenate(
          (coefficient_matrix, constant_matrix)    ,					axis=1						)

      lowerCamelCase__    ,   lowerCamelCase__		:				Any    =  table.shape

      strictly_diagonally_dominant(__lowerCAmelCase						)

      # Iterates the whole matrix for given number of times
      for _ in range(__lowerCAmelCase						):
            lowerCamelCase__		:				str    =  []
            for row in range(__lowerCAmelCase						):
                  lowerCamelCase__		:				Optional[Any]    =  0
                  for col in range(__lowerCAmelCase						):
                        if col == row:
                              lowerCamelCase__		:				Dict    =  table[row][col]
                        elif col == cols - 1:
                              lowerCamelCase__		:				str    =  table[row][col]
                        else:
                              temp += (-1) * table[row][col] * init_val[col]
                  lowerCamelCase__		:				List[str]    =  (temp + val) / denom
                  new_val.append(__lowerCAmelCase						)
            lowerCamelCase__		:				Dict    =  new_val

      return [float(__lowerCAmelCase						) for i in new_val]

def       lowercase_		(		_A			:    NDArray[floataa]						):

      """simple docstring"""




      lowerCamelCase__    ,   lowerCamelCase__		:				str    =  table.shape

      lowerCamelCase__		:				str    =  True

      for i in range(0    ,					__lowerCAmelCase						):
            lowerCamelCase__		:				Tuple    =  0
            for j in range(0    ,					cols - 1						):
                  if i == j:
                        continue
                  else:
                        total += table[i][j]

            if table[i][i] <= total:
                  raise ValueError("Coefficient matrix is not strictly diagonally dominant"						)

      return is_diagonally_dominant


# Test Cases
if __name__ == "__main__":
    import doctest

    doctest.testmod()




from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup






def    lowerCamelCase__				(				__lowerCAmelCase  :  str = ""				):




			"""simple docstring"""


			lowerCAmelCase_						=	url or "https://www.imdb.com/chart/top/?ref_=nv_mv_250"
			lowerCAmelCase_						=	BeautifulSoup(requests.get(__lowerCAmelCase				).text    ,							"html.parser"				)
			lowerCAmelCase_						=	soup.find_all("td"    ,							attrs="titleColumn"				)
			lowerCAmelCase_						=	soup.find_all("td"    ,							class_="ratingColumn imdbRating"				)
			return {
			    title.a.text: float(rating.strong.text				)
			    for title, rating in zip(__lowerCAmelCase    ,							__lowerCAmelCase				)
			}






def    lowerCamelCase__				(				__lowerCAmelCase  :  str = "IMDb_Top_250_Movies.csv"				):




			"""simple docstring"""


			lowerCAmelCase_						=	get_imdb_top_aaa_movies()
			with open(__lowerCAmelCase    ,							"w"    ,							newline=""				) as out_file:
						lowerCAmelCase_						=	csv.writer(__lowerCAmelCase				)
						writer.writerow(["Movie title", "IMDb rating"]				)
						for title, rating in movies.items():
									writer.writerow([title, rating]				)


if __name__ == "__main__":
			write_movies()



