






"""simple docstring"""


import requests
from bsa import BeautifulSoup




def       snake_case  (A_				:str = "https://www.worldometers.info/coronavirus"				):







  '''simple docstring'''

  a					:      str    =       BeautifulSoup(requests.get(A_				).text     ,      'html.parser'				)
  a					:      Union[str, Any]    =       soup.findAll('h1'				)
  a					:      Tuple    =       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(A_     ,      A_				)}


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''')












"""simple docstring"""


import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


_UpperCamelCase    :   List[str]   			=						logging.get_logger(__name__)

_UpperCamelCase    :   Optional[Any]   			=						'▁'

_UpperCamelCase    :   List[Any]   			=						{'vocab_file': 'sentencepiece.bpe.model'}

_UpperCamelCase    :   Optional[int]   			=						{
    'vocab_file': {
        'facebook/nllb-200-distilled-600M': (
            'https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model'
        ),
    }
}

_UpperCamelCase    :   List[str]   			=						{
    'facebook/nllb-200-distilled-600M': 1024,
}

# fmt: off
_UpperCamelCase    :   List[str]   			=						['ace_Arab', 'ace_Latn', 'acm_Arab', 'acq_Arab', 'aeb_Arab', 'afr_Latn', 'ajp_Arab', 'aka_Latn', 'amh_Ethi', 'apc_Arab', 'arb_Arab', 'ars_Arab', 'ary_Arab', 'arz_Arab', 'asm_Beng', 'ast_Latn', 'awa_Deva', 'ayr_Latn', 'azb_Arab', 'azj_Latn', 'bak_Cyrl', 'bam_Latn', 'ban_Latn', 'bel_Cyrl', 'bem_Latn', 'ben_Beng', 'bho_Deva', 'bjn_Arab', 'bjn_Latn', 'bod_Tibt', 'bos_Latn', 'bug_Latn', 'bul_Cyrl', 'cat_Latn', 'ceb_Latn', 'ces_Latn', 'cjk_Latn', 'ckb_Arab', 'crh_Latn', 'cym_Latn', 'dan_Latn', 'deu_Latn', 'dik_Latn', 'dyu_Latn', 'dzo_Tibt', 'ell_Grek', 'eng_Latn', 'epo_Latn', 'est_Latn', 'eus_Latn', 'ewe_Latn', 'fao_Latn', 'pes_Arab', 'fij_Latn', 'fin_Latn', 'fon_Latn', 'fra_Latn', 'fur_Latn', 'fuv_Latn', 'gla_Latn', 'gle_Latn', 'glg_Latn', 'grn_Latn', 'guj_Gujr', 'hat_Latn', 'hau_Latn', 'heb_Hebr', 'hin_Deva', 'hne_Deva', 'hrv_Latn', 'hun_Latn', 'hye_Armn', 'ibo_Latn', 'ilo_Latn', 'ind_Latn', 'isl_Latn', 'ita_Latn', 'jav_Latn', 'jpn_Jpan', 'kab_Latn', 'kac_Latn', 'kam_Latn', 'kan_Knda', 'kas_Arab', 'kas_Deva', 'kat_Geor', 'knc_Arab', 'knc_Latn', 'kaz_Cyrl', 'kbp_Latn', 'kea_Latn', 'khm_Khmr', 'kik_Latn', 'kin_Latn', 'kir_Cyrl', 'kmb_Latn', 'kon_Latn', 'kor_Hang', 'kmr_Latn', 'lao_Laoo', 'lvs_Latn', 'lij_Latn', 'lim_Latn', 'lin_Latn', 'lit_Latn', 'lmo_Latn', 'ltg_Latn', 'ltz_Latn', 'lua_Latn', 'lug_Latn', 'luo_Latn', 'lus_Latn', 'mag_Deva', 'mai_Deva', 'mal_Mlym', 'mar_Deva', 'min_Latn', 'mkd_Cyrl', 'plt_Latn', 'mlt_Latn', 'mni_Beng', 'khk_Cyrl', 'mos_Latn', 'mri_Latn', 'zsm_Latn', 'mya_Mymr', 'nld_Latn', 'nno_Latn', 'nob_Latn', 'npi_Deva', 'nso_Latn', 'nus_Latn', 'nya_Latn', 'oci_Latn', 'gaz_Latn', 'ory_Orya', 'pag_Latn', 'pan_Guru', 'pap_Latn', 'pol_Latn', 'por_Latn', 'prs_Arab', 'pbt_Arab', 'quy_Latn', 'ron_Latn', 'run_Latn', 'rus_Cyrl', 'sag_Latn', 'san_Deva', 'sat_Beng', 'scn_Latn', 'shn_Mymr', 'sin_Sinh', 'slk_Latn', 'slv_Latn', 'smo_Latn', 'sna_Latn', 'snd_Arab', 'som_Latn', 'sot_Latn', 'spa_Latn', 'als_Latn', 'srd_Latn', 'srp_Cyrl', 'ssw_Latn', 'sun_Latn', 'swe_Latn', 'swh_Latn', 'szl_Latn', 'tam_Taml', 'tat_Cyrl', 'tel_Telu', 'tgk_Cyrl', 'tgl_Latn', 'tha_Thai', 'tir_Ethi', 'taq_Latn', 'taq_Tfng', 'tpi_Latn', 'tsn_Latn', 'tso_Latn', 'tuk_Latn', 'tum_Latn', 'tur_Latn', 'twi_Latn', 'tzm_Tfng', 'uig_Arab', 'ukr_Cyrl', 'umb_Latn', 'urd_Arab', 'uzn_Latn', 'vec_Latn', 'vie_Latn', 'war_Latn', 'wol_Latn', 'xho_Latn', 'ydd_Hebr', 'yor_Latn', 'yue_Hant', 'zho_Hans', 'zho_Hant', 'zul_Latn']






class 						snake_case  (  UpperCAmelCase	):
    __magic_name__   					=					VOCAB_FILES_NAMES
    __magic_name__   					=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __magic_name__   					=					PRETRAINED_VOCAB_FILES_MAP
    __magic_name__   					=					['''input_ids''', '''attention_mask''']

    __magic_name__   					=					[]
    __magic_name__   					=					[]





    def __init__(							self     : List[str]    ,		A     : Union[str, Any]    ,		A     : List[Any]="<s>"    ,		A     : Dict="</s>"    ,		A     : List[Any]="</s>"    ,		A     : Any="<s>"    ,		A     : Dict="<unk>"    ,		A     : Any="<pad>"    ,		A     : Optional[int]="<mask>"    ,		A     : str=None    ,		A     : Tuple=None    ,		A     : List[str]=None    ,		A     : Optional[Dict[str, Any]] = None    ,		A     : Any=None    ,		A     : List[Any]=False    ,		**A     : Tuple    ,		):


      '''simple docstring'''




      a					:      int    =       AddedToken(A    ,		lstrip=A    ,		rstrip=A      ) if isinstance(A    ,		A      ) else mask_token

      a					:      Tuple    =       {} if sp_model_kwargs is None else sp_model_kwargs
      a					:      Optional[Any]    =       legacy_behaviour

      super().__init__(
          bos_token=A    ,		eos_token=A    ,		unk_token=A    ,		sep_token=A    ,		cls_token=A    ,		pad_token=A    ,		mask_token=A    ,		tokenizer_file=A    ,		src_lang=A    ,		tgt_lang=A    ,		additional_special_tokens=A    ,		sp_model_kwargs=self.sp_model_kwargs    ,		legacy_behaviour=A    ,		**A    ,		)

      a					:      int    =       spm.SentencePieceProcessor(**self.sp_model_kwargs      )
      self.sp_model.Load(str(A      )      )
      a					:      Optional[int]    =       vocab_file
      # Original fairseq vocab and spm vocab must be "aligned":
      # Vocab    |    0    |    1    |   2    |    3    |  4   |  5   |  6   |   7  |   8  |  9
      # -------- | ------- | ------- | ------ | ------- | ---- | ---- | ---- | ---- | ---- | ----
      # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
      # spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

      # Mimic fairseq token-to-id alignment for the first 4 token
      a					:      List[str]    =       {'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

      # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
      a					:      Any    =       1

      a					:      int    =       len(self.sp_model      )
      a					:      Optional[int]    =       {
          code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(A      )
      }
      a					:      Optional[int]    =       {v: k for k, v in self.lang_code_to_id.items()}
      a					:      Optional[Any]    =       len(self.sp_model      ) + len(self.lang_code_to_id      ) + self.fairseq_offset

      self.fairseq_tokens_to_ids.update(self.lang_code_to_id      )
      a					:      int    =       {v: k for k, v in self.fairseq_tokens_to_ids.items()}
      a					:      List[str]    =       list(self.lang_code_to_id.keys()      )

      if additional_special_tokens is not None:
        # Only add those special tokens if they are not already there.
        self._additional_special_tokens.extend(
            [t for t in additional_special_tokens if t not in self._additional_special_tokens]      )

      a					:      Optional[int]    =       src_lang if src_lang is not None else 'eng_Latn'
      a					:      List[Any]    =       self.lang_code_to_id[self._src_lang]
      a					:      List[Any]    =       tgt_lang
      self.set_src_lang_special_tokens(self._src_lang      )





    def __getstate__(							self     : List[str]      ):


      '''simple docstring'''




      a					:      Dict    =       self.__dict__.copy()
      a					:      int    =       None
      a					:      List[str]    =       self.sp_model.serialized_model_proto()
      return state





    def __setstate__(							self     : str    ,		A     : Any      ):


      '''simple docstring'''




      a					:      str    =       d

      # for backward compatibility
      if not hasattr(self    ,		'sp_model_kwargs'      ):
        a					:      Any    =       {}

      a					:      Union[str, Any]    =       spm.SentencePieceProcessor(**self.sp_model_kwargs      )
      self.sp_model.LoadFromSerializedProto(self.sp_model_proto      )





    @property
    def     lowerCamelCase__				(							self     : Optional[Any]      ):


      '''simple docstring'''




      return len(self.sp_model      ) + len(self.lang_code_to_id      ) + self.fairseq_offset + 1  # Plus 1 for the mask token





    @property
    def     lowerCamelCase__				(							self     : Tuple      ):


      '''simple docstring'''




      return self._src_lang





    @src_lang.setter
    def     lowerCamelCase__				(							self     : Dict    ,		A     : str      ):


      '''simple docstring'''




      a					:      Any    =       new_src_lang
      self.set_src_lang_special_tokens(self._src_lang      )





    def     lowerCamelCase__				(							self     : Optional[int]    ,		A     : List[int]    ,		A     : Optional[List[int]] = None    ,		A     : bool = False      ):


      '''simple docstring'''




      if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=A    ,		token_ids_a=A    ,		already_has_special_tokens=A      )

      a					:      Tuple    =       [1] * len(self.prefix_tokens      )
      a					:      int    =       [1] * len(self.suffix_tokens      )
      if token_ids_a is None:
        return prefix_ones + ([0] * len(A      )) + suffix_ones
      return prefix_ones + ([0] * len(A      )) + ([0] * len(A      )) + suffix_ones





    def     lowerCamelCase__				(							self     : Any    ,		A     : List[int]    ,		A     : Optional[List[int]] = None      ):


      '''simple docstring'''




      if token_ids_a is None:
        return self.prefix_tokens + token_ids_a + self.suffix_tokens
      # We don't expect to process pairs, but leave the pair logic for API consistency
      return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens





    def     lowerCamelCase__				(							self     : Optional[int]    ,		A     : List[int]    ,		A     : Optional[List[int]] = None      ):


      '''simple docstring'''




      a					:      List[str]    =       [self.sep_token_id]
      a					:      List[str]    =       [self.cls_token_id]

      if token_ids_a is None:
        return len(cls + token_ids_a + sep      ) * [0]
      return len(cls + token_ids_a + sep + sep + token_ids_a + sep      ) * [0]





    def     lowerCamelCase__				(							self     : List[str]    ,		A     : Optional[int]    ,		A     : str    ,		A     : Optional[str]    ,		A     : Optional[str]    ,		**A     : str      ):


      '''simple docstring'''




      if src_lang is None or tgt_lang is None:
        raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'      )
      a					:      Any    =       src_lang
      a					:      Any    =       self(A    ,		add_special_tokens=A    ,		return_tensors=A    ,		**A      )
      a					:      Tuple    =       self.convert_tokens_to_ids(A      )
      a					:      Optional[Any]    =       tgt_lang_id
      return inputs





    def     lowerCamelCase__				(							self     : List[str]      ):


      '''simple docstring'''




      a					:      Union[str, Any]    =       {self.convert_ids_to_tokens(A      ): i for i in range(self.vocab_size      )}
      vocab.update(self.added_tokens_encoder      )
      return vocab





    def     lowerCamelCase__				(							self     : Any    ,		A     : str      ):


      '''simple docstring'''




      return self.sp_model.encode(A    ,		out_type=A      )





    def     lowerCamelCase__				(							self     : Union[str, Any]    ,		A     : Tuple      ):


      '''simple docstring'''




      if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
      a					:      int    =       self.sp_model.PieceToId(A      )

      # Need to return unknown token if the SP model returned 0
      return spm_id + self.fairseq_offset if spm_id else self.unk_token_id





    def     lowerCamelCase__				(							self     : Tuple    ,		A     : List[str]      ):


      '''simple docstring'''




      if index in self.fairseq_ids_to_tokens:
        return self.fairseq_ids_to_tokens[index]
      return self.sp_model.IdToPiece(index - self.fairseq_offset      )





    def     lowerCamelCase__				(							self     : List[str]    ,		A     : Dict      ):


      '''simple docstring'''




      a					:      List[str]    =       ''.join(A      ).replace(A    ,		' '      ).strip()
      return out_string





    def     lowerCamelCase__				(							self     : Any    ,		A     : str    ,		A     : Optional[str] = None      ):


      '''simple docstring'''




      if not os.path.isdir(A      ):
        logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
        return
      a					:      Optional[int]    =       os.path.join(
          A    ,		(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )

      if os.path.abspath(self.vocab_file      ) != os.path.abspath(A      ) and os.path.isfile(self.vocab_file      ):
        copyfile(self.vocab_file    ,		A      )
      elif not os.path.isfile(self.vocab_file      ):
        with open(A    ,		'wb'      ) as fi:
          a					:      Tuple    =       self.sp_model.serialized_model_proto()
          fi.write(A      )

      return (out_vocab_file,)





    def     lowerCamelCase__				(							self     : Any    ,		A     : List[str]    ,		A     : str = "eng_Latn"    ,		A     : Optional[List[str]] = None    ,		A     : str = "fra_Latn"    ,		**A     : Optional[int]    ,		):


      '''simple docstring'''




      a					:      Union[str, Any]    =       src_lang
      a					:      Optional[int]    =       tgt_lang
      return super().prepare_seqaseq_batch(A    ,		A    ,		**A      )





    def     lowerCamelCase__				(							self     : Optional[Any]      ):


      '''simple docstring'''




      return self.set_src_lang_special_tokens(self.src_lang      )





    def     lowerCamelCase__				(							self     : Union[str, Any]      ):


      '''simple docstring'''




      return self.set_tgt_lang_special_tokens(self.tgt_lang      )





    def     lowerCamelCase__				(							self     : Union[str, Any]    ,		A     : Dict      ):


      '''simple docstring'''




      a					:      Optional[int]    =       self.lang_code_to_id[src_lang]
      if self.legacy_behaviour:
        a					:      List[Any]    =       []
        a					:      Optional[int]    =       [self.eos_token_id, self.cur_lang_code]
      else:
        a					:      Union[str, Any]    =       [self.cur_lang_code]
        a					:      List[str]    =       [self.eos_token_id]





    def     lowerCamelCase__				(							self     : Optional[Any]    ,		A     : str      ):


      '''simple docstring'''




      a					:      Tuple    =       self.lang_code_to_id[lang]
      if self.legacy_behaviour:
        a					:      List[str]    =       []
        a					:      Union[str, Any]    =       [self.eos_token_id, self.cur_lang_code]
      else:
        a					:      Union[str, Any]    =       [self.cur_lang_code]
        a					:      List[str]    =       [self.eos_token_id]




