
import csv

import tweepy

# Twitter API credentials
lowercase__		:Optional[int]			  =   ""
lowercase__		:Dict			  =   ""
lowercase__		:Optional[int]			  =   ""
lowercase__		:List[str]			  =   ""



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					# authorize twitter, initialize tweepy
					lowercase						     =						tweepy.OAuthHandler(lowerCAmelCase__			,      lowerCAmelCase__		)
					auth.set_access_token(lowerCAmelCase__			,      lowerCAmelCase__		)
					lowercase						     =						tweepy.API(lowerCAmelCase__		)

					# 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=lowerCAmelCase__			,      count=200		)

					# save most recent tweets
					alltweets.extend(lowerCAmelCase__		)

					# 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(lowerCAmelCase__		) > 0:
										print(f'getting tweets before {oldest}'		)

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

										# save most recent tweets
										alltweets.extend(lowerCAmelCase__		)

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

										print(f'...{len(lowerCAmelCase__		)} 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(lowerCAmelCase__		)
										writer.writerow(['''id''', '''created_at''', '''text''']		)
										writer.writerows(lowerCAmelCase__		)


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






from statistics import mean

import numpy as np



def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						0
					# Number of processes finished
					lowercase						     =						0
					# Displays the finished process.
					# If it is 0, the performance is completed if it is 1, before the performance.
					lowercase						     =						[0] * no_of_process
					# List to include calculation results
					lowercase						     =						[0] * no_of_process

					# Sort by arrival time.
					lowercase						     =						[burst_time[i] for i in np.argsort(lowerCAmelCase__		)]
					lowercase						     =						[process_name[i] for i in np.argsort(lowerCAmelCase__		)]
					arrival_time.sort()

					while no_of_process > finished_process_count:
										lowercase						     =						0
										while finished_process[i] == 1:
															i += 1
										if current_time < arrival_time[i]:
															lowercase						     =						arrival_time[i]

										lowercase						     =						0
										# Index showing the location of the process being performed
										lowercase						     =						0
										# Saves the current response ratio.
										lowercase						     =						0
										for i in range(0			,      lowerCAmelCase__		):
															if finished_process[i] == 0 and arrival_time[i] <= current_time:
																				lowercase						     =						(burst_time[i] + (current_time - arrival_time[i])) / burst_time[
																				    i
																				]
															if response_ratio < temp:
																				lowercase						     =						temp
																				lowercase						     =						i

        # Calculate the turn around time
										lowercase						     =						current_time + burst_time[loc] - arrival_time[loc]
										current_time += burst_time[loc]
										# Indicates that the process has been performed.
										lowercase						     =						1
										# Increase finished_process_count by 1
										finished_process_count += 1

					return turn_around_time



def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						[0] * no_of_process
					for i in range(0			,      lowerCAmelCase__		):
										lowercase						     =						turn_around_time[i] - burst_time[i]
					return waiting_time


if __name__ == "__main__":
							lowercase__		:Dict			  =   5
							lowercase__		:str			  =   ["A", "B", "C", "D", "E"]
							lowercase__		:Optional[int]			  =   [1, 2, 3, 4, 5]
							lowercase__		:List[Any]			  =   [1, 2, 3, 4, 5]

							lowercase__		:List[str]			  =   calculate_turn_around_time(
							    process_name, arrival_time, burst_time, no_of_process
							)
							lowercase__		:List[Any]			  =   calculate_waiting_time(
							    process_name, turn_around_time, burst_time, no_of_process
							)

							print("Process name \tArrival time \tBurst time \tTurn around time \tWaiting time")
							for i in range(0, no_of_process):
														print(
														    F'{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t'
														    F'{turn_around_time[i]}\t\t\t{waiting_time[i]}'
														)

							print(F'average waiting time : {mean(waiting_time):.5f}')
							print(F'average turn around time : {mean(turn_around_time):.5f}')




