


import csv

import tweepy

# Twitter API credentials
UpperCAmelCase_				:			List[Any]   =	''
UpperCAmelCase_				:			Dict   =	''
UpperCAmelCase_				:			List[Any]   =	''
UpperCAmelCase_				:			List[str]   =	''







def 	SCREAMING_SNAKE_CASE_						(      __A			:      str    )     ->		None:

       """simple docstring"""

       a_ :		Union[str, Any]							=  tweepy.OAuthHandler(__A  ,   __A    )
       auth.set_access_token(__A  ,   __A    )
       a_ :		List[Any]							=  tweepy.API(__A    )

       # initialize a list to hold all the tweepy Tweets
       a_ :		List[str]							=  []

       # make initial request for most recent tweets (200 is the maximum allowed count)
       a_ :		Any							=  api.user_timeline(screen_name=__A  ,   count=2_00    )

       # save most recent tweets
       alltweets.extend(__A    )

       # save the id of the oldest tweet less one
       a_ :		Union[str, Any]							=  alltweets[-1].id - 1

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

              # all subsequent requests use the max_id param to prevent duplicates
              a_ :		Optional[int]							=  api.user_timeline(
                  screen_name=__A  ,   count=2_00  ,   max_id=__A    )

              # save most recent tweets
              alltweets.extend(__A    )

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

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

       # transform the tweepy tweets into a 2D array that will populate the csv
       a_ :		int							=  [[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:
              a_ :		Dict							=  csv.writer(__A    )
              writer.writerow(['id', 'created_at', 'text']    )
              writer.writerows(__A    )


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






from __future__ import annotations

from math import pi

# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
UpperCAmelCase_				:			str   =	1.054571817e-34  # unit of ℏ : J * s

UpperCAmelCase_				:			Dict   =	3e8  # unit of c : m * s^-1







def 	SCREAMING_SNAKE_CASE_						(      __A			:      float  ,   __A			:      float  ,   __A			:      float    )     ->		dict[str, float]:

       """simple docstring"""

       if (force, area, distance).count(0    ) != 1:
              raise ValueError('One and only one argument must be 0'    )
       if force < 0:
              raise ValueError('Magnitude of force can not be negative'    )
       if distance < 0:
              raise ValueError('Distance can not be negative'    )
       if area < 0:
              raise ValueError('Area can not be negative'    )
       if force == 0:
              a_ :		Optional[Any]							=  (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
                  2_40 * (distance) ** 4
              )
              return {"force": force}
       elif area == 0:
              a_ :		List[str]							=  (2_40 * force * (distance) ** 4) / (
                  REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
              )
              return {"area": area}
       elif distance == 0:
              a_ :		Tuple							=  (
                  (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (2_40 * force)
              ) ** (1 / 4)
              return {"distance": distance}
       raise ValueError('One and only one argument must be 0'    )


# Run doctest
if __name__ == "__main__":
   import doctest

   doctest.testmod()


