'''simple docstring'''




from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np






class 				a__(					__a	):


			'''simple docstring'''






			def 							a_       (   self       ,    __lowerCAmelCase):




					"""simple docstring"""


					return 0.0







def 				snake_case__							(			_A:					np.ndarray      ,   _A:					int )    ->	Optional[int]:

		'''simple docstring'''


		lowerCAmelCase   					=  min([-20, np.min(fft_results[1 : samplerate // 2 - 1] )] )
		lowerCAmelCase   					=  max([20, np.max(fft_results[1 : samplerate // 2 - 1] )] )
		return lowest, highest






def 				snake_case__							(			_A:					FilterType      ,   _A:					int )    ->	Optional[Any]:

		'''simple docstring'''


		lowerCAmelCase   					=  512
		lowerCAmelCase   					=  [1] + [0] * (size - 1)
		lowerCAmelCase   					=  [filter_type.process(__lowerCAmelCase ) for item in inputs]

		lowerCAmelCase   					=  [0] * (samplerate - size)  # zero-padding
		outputs += filler
		lowerCAmelCase   					=  np.abs(np.fft.fft(__lowerCAmelCase ) )
		lowerCAmelCase   					=  20 * np.logaa(__lowerCAmelCase )

		# Frequencies on log scale from 24 to nyquist frequency
		plt.xlim(24      ,   samplerate / 2 - 1 )
		plt.xlabel("""Frequency (Hz)""" )
		plt.xscale("""log""" )

		# Display within reasonable bounds
		lowerCAmelCase   					=  get_bounds(__lowerCAmelCase      ,   __lowerCAmelCase )
		plt.ylim(max([-80, bounds[0]] )      ,   min([80, bounds[1]] ) )
		plt.ylabel("""Gain (dB)""" )

		plt.plot(__lowerCAmelCase )
		plt.show()






def 				snake_case__							(			_A:					FilterType      ,   _A:					int )    ->	Union[str, Any]:

		'''simple docstring'''


		lowerCAmelCase   					=  512
		lowerCAmelCase   					=  [1] + [0] * (size - 1)
		lowerCAmelCase   					=  [filter_type.process(__lowerCAmelCase ) for item in inputs]

		lowerCAmelCase   					=  [0] * (samplerate - size)  # zero-padding
		outputs += filler
		lowerCAmelCase   					=  np.angle(np.fft.fft(__lowerCAmelCase ) )

		# Frequencies on log scale from 24 to nyquist frequency
		plt.xlim(24      ,   samplerate / 2 - 1 )
		plt.xlabel("""Frequency (Hz)""" )
		plt.xscale("""log""" )

		plt.ylim(-2 * pi      ,   2 * pi )
		plt.ylabel("""Phase shift (Radians)""" )
		plt.plot(np.unwrap(__lowerCAmelCase      ,   -2 * pi ) )
		plt.show()






import requests

_A   =     "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="






def    lowerCamelCase__				(				__lowerCAmelCase  :  str				):




			"""simple docstring"""


			lowerCAmelCase_						=	requests.get(_NEWS_API + bbc_news_api_key				).json()
			# each article in the list is a dict
			for i, article in enumerate(bbc_news_page["articles"]    ,							1				):
						print(F"""{i}.) {article['title']}"""				)


if __name__ == "__main__":
			fetch_bbc_news(bbc_news_api_key="<Your BBC News API key goes here>")



