




"""simple docstring"""

from typing import TYPE_CHECKING

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


if is_sentencepiece_available():
		from ..ta.tokenization_ta import TaTokenizer
else:
		from ...utils.dummy_sentencepiece_objects import TaTokenizer

_lowerCamelCase  :			str        =       TaTokenizer

if is_tokenizers_available():
		from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
		from ...utils.dummy_tokenizers_objects import TaTokenizerFast

_lowerCamelCase  :			List[Any]        =       TaTokenizerFast

_lowerCamelCase  :			str        =       {'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase  :			Optional[Any]        =       [
		    'MT5EncoderModel',
		    'MT5ForConditionalGeneration',
		    'MT5ForQuestionAnswering',
		    'MT5Model',
		    'MT5PreTrainedModel',
		    'MT5Stack',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase  :			Tuple        =       ['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase  :			Optional[int]        =       ['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
		from .configuration_mta import MTaConfig, MTaOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mta import (
				    MTaEncoderModel,
				    MTaForConditionalGeneration,
				    MTaForQuestionAnswering,
				    MTaModel,
				    MTaPreTrainedModel,
				    MTaStack,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
		import sys

		_lowerCamelCase  :			Optional[Any]        =       _LazyModule(
		    __name__,
		    globals()['__file__'],
		    _import_structure,
		    extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
		    module_spec=__spec__,
		)











"""simple docstring"""

import requests
from bsa import BeautifulSoup

def 		lowercase_      (		_UpperCAmelCase = "https://www.worldometers.info/coronavirus"	):




	"""simple docstring"""






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


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')





