

import csv

import tweepy

# Twitter API credentials
a		=""""""
a		=""""""
a		=""""""
a		=""""""






def    SCREAMING_SNAKE_CASE__       (  lowerCamelCase__			)  ->     None:
	# authorize twitter, initialize tweepy
	__lowerCamelCase				:				Tuple					       = tweepy.OAuthHandler(lowerCamelCase__	, lowerCamelCase__			)
	auth.set_access_token(lowerCamelCase__	, lowerCamelCase__			)
	__lowerCamelCase				:				Optional[int]					       = tweepy.API(lowerCamelCase__			)

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

	# make initial request for most recent tweets (200 is the maximum allowed count)
	__lowerCamelCase				:				Union[str, Any]					       = api.user_timeline(screen_name=lowerCamelCase__	, count=2_0_0			)

	# save most recent tweets
	alltweets.extend(lowerCamelCase__			)

	# save the id of the oldest tweet less one
	__lowerCamelCase				:				Any					       = 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
		__lowerCamelCase				:				str					       = api.user_timeline(
		    screen_name=lowerCamelCase__	, count=2_0_0	, max_id=lowerCamelCase__			)

		# save most recent tweets
		alltweets.extend(lowerCamelCase__			)

		# update the id of the oldest tweet less one
		__lowerCamelCase				:				Optional[int]					       = 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
	__lowerCamelCase				:				str					       = [[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:
		__lowerCamelCase				:				Any					       = 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""")








'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase__    					=      {
    '''configuration_distilbert''': [
        '''DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DistilBertConfig''',
        '''DistilBertOnnxConfig''',
    ],
    '''tokenization_distilbert''': ['''DistilBertTokenizer'''],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__    					=      ['''DistilBertTokenizerFast''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__    					=      [
      '''DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''DistilBertForMaskedLM''',
      '''DistilBertForMultipleChoice''',
      '''DistilBertForQuestionAnswering''',
      '''DistilBertForSequenceClassification''',
      '''DistilBertForTokenClassification''',
      '''DistilBertModel''',
      '''DistilBertPreTrainedModel''',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__    					=      [
      '''TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''TFDistilBertForMaskedLM''',
      '''TFDistilBertForMultipleChoice''',
      '''TFDistilBertForQuestionAnswering''',
      '''TFDistilBertForSequenceClassification''',
      '''TFDistilBertForTokenClassification''',
      '''TFDistilBertMainLayer''',
      '''TFDistilBertModel''',
      '''TFDistilBertPreTrainedModel''',
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__    					=      [
      '''FlaxDistilBertForMaskedLM''',
      '''FlaxDistilBertForMultipleChoice''',
      '''FlaxDistilBertForQuestionAnswering''',
      '''FlaxDistilBertForSequenceClassification''',
      '''FlaxDistilBertForTokenClassification''',
      '''FlaxDistilBertModel''',
      '''FlaxDistilBertPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_distilbert import (
      DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
      DistilBertConfig,
      DistilBertOnnxConfig,
  )
  from .tokenization_distilbert import DistilBertTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_distilbert_fast import DistilBertTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_distilbert import (
        DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        DistilBertForMaskedLM,
        DistilBertForMultipleChoice,
        DistilBertForQuestionAnswering,
        DistilBertForSequenceClassification,
        DistilBertForTokenClassification,
        DistilBertModel,
        DistilBertPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_distilbert import (
        TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFDistilBertForMaskedLM,
        TFDistilBertForMultipleChoice,
        TFDistilBertForQuestionAnswering,
        TFDistilBertForSequenceClassification,
        TFDistilBertForTokenClassification,
        TFDistilBertMainLayer,
        TFDistilBertModel,
        TFDistilBertPreTrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_distilbert import (
        FlaxDistilBertForMaskedLM,
        FlaxDistilBertForMultipleChoice,
        FlaxDistilBertForQuestionAnswering,
        FlaxDistilBertForSequenceClassification,
        FlaxDistilBertForTokenClassification,
        FlaxDistilBertModel,
        FlaxDistilBertPreTrainedModel,
    )

else:
  import sys

  UpperCamelCase__    					=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
