

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""")










snake_case_ : Dict    		=       {
    "Pillow": "Pillow",
    "accelerate": "accelerate>=0.11.0",
    "compel": "compel==0.1.8",
    "black": "black~=23.1",
    "datasets": "datasets",
    "filelock": "filelock",
    "flax": "flax>=0.4.1",
    "hf-doc-builder": "hf-doc-builder>=0.3.0",
    "huggingface-hub": "huggingface-hub>=0.13.2",
    "requests-mock": "requests-mock==1.10.0",
    "importlib_metadata": "importlib_metadata",
    "invisible-watermark": "invisible-watermark",
    "isort": "isort>=5.5.4",
    "jax": "jax>=0.2.8,!=0.3.2",
    "jaxlib": "jaxlib>=0.1.65",
    "Jinja2": "Jinja2",
    "k-diffusion": "k-diffusion>=0.0.12",
    "torchsde": "torchsde",
    "note_seq": "note_seq",
    "librosa": "librosa",
    "numpy": "numpy",
    "omegaconf": "omegaconf",
    "parameterized": "parameterized",
    "protobuf": "protobuf>=3.20.3,<4",
    "pytest": "pytest",
    "pytest-timeout": "pytest-timeout",
    "pytest-xdist": "pytest-xdist",
    "ruff": "ruff>=0.0.241",
    "safetensors": "safetensors",
    "sentencepiece": "sentencepiece>=0.1.91,!=0.1.92",
    "scipy": "scipy",
    "onnx": "onnx",
    "regex": "regex!=2019.12.17",
    "requests": "requests",
    "tensorboard": "tensorboard",
    "torch": "torch>=1.4",
    "torchvision": "torchvision",
    "transformers": "transformers>=4.25.1",
    "urllib3": "urllib3<=2.0.0",
}






