'''simple docstring'''






import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			List[str]   ,		__snake_case							:			Union[str, Any]   ,		__snake_case							:			int   ,		__snake_case							:			Dict=1_0_2_4				):
     _A		,       _A    		=  [], []

     _A    		=  list(zip(__snake_case   ,		__snake_case				)				)
     _A		,       _A    		=  sorted_examples[0]

     def is_too_big(__snake_case							:			int				):
          return tok(__snake_case   ,		return_tensors='pt'				).input_ids.shape[1] > max_tokens

     for src, tgt in tqdm(sorted_examples[1:]				):
          _A    		=  new_src + ' ' + src
          _A    		=  new_tgt + ' ' + tgt
          if is_too_big(__snake_case				) or is_too_big(__snake_case				):  # cant fit, finalize example
               finished_src.append(__snake_case				)
               finished_tgt.append(__snake_case				)
               _A		,       _A    		=  src, tgt
          else:  # can fit, keep adding
               _A		,       _A    		=  cand_src, cand_tgt

    # cleanup
     if new_src:
          assert new_tgt
          finished_src.append(__snake_case				)
          finished_tgt.append(__snake_case				)
     return finished_src, finished_tgt





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			Union[str, Any]   ,		__snake_case							:			Path   ,		__snake_case							:			str   ,		__snake_case							:			Union[str, Any]				):
     _A    		=  Path(__snake_case				)
     save_path.mkdir(exist_ok=__snake_case				)
     for split in ["train"]:
          _A		,       _A    		=  data_dir / F'{split}.source', data_dir / F'{split}.target'
          _A    		=  [x.rstrip() for x in Path(__snake_case				).open().readlines()]
          _A    		=  [x.rstrip() for x in Path(__snake_case				).open().readlines()]
          _A		,       _A    		=  pack_examples(__snake_case   ,		__snake_case   ,		__snake_case   ,		__snake_case				)
          print(F'packed {split} split from {len(__snake_case				)} examples -> {len(__snake_case				)}.'				)
          Path(save_path / F'{split}.source'				).open('w'				).write('\n'.join(__snake_case				)				)
          Path(save_path / F'{split}.target'				).open('w'				).write('\n'.join(__snake_case				)				)
     for split in ["val", "test"]:
          _A		,       _A    		=  data_dir / F'{split}.source', data_dir / F'{split}.target'
          shutil.copyfile(__snake_case   ,		save_path / F'{split}.source'				)
          shutil.copyfile(__snake_case   ,		save_path / F'{split}.target'				)





def  _SCREAMING_SNAKE_CASE		(      ):
     _A    		=  argparse.ArgumentParser()
     parser.add_argument('--tok_name'   ,		type=__snake_case   ,		help='like facebook/bart-large-cnn,t5-base, etc.'				)
     parser.add_argument('--max_seq_len'   ,		type=__snake_case   ,		default=1_2_8				)
     parser.add_argument('--data_dir'   ,		type=__snake_case				)
     parser.add_argument('--save_path'   ,		type=__snake_case				)
     _A    		=  parser.parse_args()
     _A    		=  AutoTokenizer.from_pretrained(args.tok_name				)
     return pack_data_dir(__snake_case   ,		Path(args.data_dir				)   ,		args.max_seq_len   ,		args.save_path				)


if __name__ == "__main__":
   packer_cli()







"""simple docstring"""


import requests
from bsa import BeautifulSoup


def    _lowerCamelCase   (     lowerCamelCase__	:							str = "https://www.worldometers.info/coronavirus"  ):
 lowercase__       :       Optional[Any]				=						BeautifulSoup(requests.get(lowerCamelCase__  ).text       ,		"""html.parser"""  )
 lowercase__       :       Union[str, Any]				=						soup.findAll("""h1"""  )
 lowercase__       :       List[str]				=						soup.findAll("""div"""       ,		{"""class""": """maincounter-number"""}  )
 keys += soup.findAll("""span"""       ,		{"""class""": """panel-title"""}  )
 values += soup.findAll("""div"""       ,		{"""class""": """number-table-main"""}  )
 return {key.text.strip(): value.text.strip() for key, value in zip(lowerCamelCase__       ,		lowerCamelCase__  )}


if __name__ == "__main__":
   print('\033[1m' + 'COVID-19 Status of the World' + '\033[0m\n')
   for key, value in world_covidaa_stats().items():
      print(F"{key}\n{value}\n")