


import requests
from bsa import BeautifulSoup





def 	_lowerCAmelCase					( UpperCamelCase__:  str = "https://www.worldometers.info/coronavirus"    )			-> dict:





	"""simple docstring"""







	A             =					BeautifulSoup(requests.get(UpperCamelCase__    ).text				,       """html.parser"""    )
	A             =					soup.findAll("""h1"""    )
	A             =					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''')







_lowercase							:   Dict						=						"0.21.0"

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
				from .utils import rich



