






import heapq as hq
import math
from collections.abc import Iterator




class 				__A     :





				"""simple docstring"""







				def __init__( self							,  lowerCamelCase__    ):




									"""simple docstring"""

									__UpperCamelCase      :					List[str]       		=str(id_    )
									__UpperCamelCase      :					int       		=None
									__UpperCamelCase      :					Tuple       		=None
									__UpperCamelCase      :					Union[str, Any]       		=[]
									__UpperCamelCase      :					int       		={}  # {vertex:distance}


				def __lt__( self							,  lowerCamelCase__    ):




									"""simple docstring"""

									return self.key < other.key


				def __repr__( self    ):




									"""simple docstring"""

									return self.id


				def       __lowercase							( self							,  lowerCamelCase__    ):




									"""simple docstring"""

									self.neighbors.append(lowerCAmelCase__    )







				def       __lowercase							( self							,  lowerCamelCase__							,  lowerCamelCase__    ):




									"""simple docstring"""

									__UpperCamelCase      :					str       		=weight






def 							A     (       a_							,a_							,a_							,a_					)     ->						List[Any]:
					graph[a - 1].add_neighbor(graph[b - 1]					)
					graph[b - 1].add_neighbor(graph[a - 1]					)
					# add the edges:
					graph[a - 1].add_edge(graph[b - 1]							,a_					)
					graph[b - 1].add_edge(graph[a - 1]							,a_					)






def 							A     (       a_							,a_					)     ->						int:
					__UpperCamelCase      :					int       		=[]
					for u in graph:
										__UpperCamelCase      :					Optional[int]       		=math.inf
										__UpperCamelCase      :					List[str]       		=None
					__UpperCamelCase      :					List[str]       		=0
					__UpperCamelCase      :					str       		=graph[:]
					while q:
										__UpperCamelCase      :					Any       		=min(a_					)
										q.remove(a_					)
										for v in u.neighbors:
															if (v in q) and (u.edges[v.id] < v.key):
																				__UpperCamelCase      :					Optional[int]       		=u
																				__UpperCamelCase      :					List[Any]       		=u.edges[v.id]
					for i in range(1							,len(a_					)					):
										a.append((int(graph[i].id					) + 1, int(graph[i].pi.id					) + 1)					)
					return a






def 							A     (       a_							,a_					)     ->						Any:



					for u in graph:
										__UpperCamelCase      :					Union[str, Any]       		=math.inf
										__UpperCamelCase      :					Union[str, Any]       		=None
					__UpperCamelCase      :					str       		=0

					__UpperCamelCase      :					Dict       		=list(a_					)
					hq.heapify(a_					)

					while h:
										__UpperCamelCase      :					int       		=hq.heappop(a_					)
										for v in u.neighbors:
															if (v in h) and (u.edges[v.id] < v.key):
																				__UpperCamelCase      :					Optional[Any]       		=u
																				__UpperCamelCase      :					Union[str, Any]       		=u.edges[v.id]
																				hq.heapify(a_					)

					for i in range(1							,len(a_					)					):
										yield (int(graph[i].id					) + 1, int(graph[i].pi.id					) + 1)






def 							A     (       )     ->						int:
					pass





if __name__ == "__main__":
							import doctest

							doctest.testmod()


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""")