


import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_utils import Literal


snake_case__				:	str					       =					datasets.utils.logging.get_logger(__name__)

snake_case__				:	Dict					       =					['names', 'prefix']
snake_case__				:	Tuple					       =					['warn_bad_lines', 'error_bad_lines', 'mangle_dupe_cols']
snake_case__				:	Dict					       =					['encoding_errors', 'on_bad_lines']
snake_case__				:	int					       =					['date_format']





@dataclass
class   SCREAMING_SNAKE_CASE_			(datasets.BuilderConfig						):




       '''simple docstring'''



       _a   							=							","
       _a   							=							None
       _a   							=							"infer"
       _a   							=							None
       _a   							=							None
       _a   							=							None
       _a   							=							None
       _a   							=							None
       _a   							=							True
       _a   							=							None
       _a   							=							None
       _a   							=							None
       _a   							=							None
       _a   							=							False
       _a   							=							None
       _a   							=							None
       _a   							=							None
       _a   							=							True
       _a   							=							True
       _a   							=							False
       _a   							=							True
       _a   							=							None
       _a   							=							"."
       _a   							=							None
       _a   							=							'"'
       _a   							=							0
       _a   							=							None
       _a   							=							None
       _a   							=							None
       _a   							=							None
       _a   							=							True
       _a   							=							True
       _a   							=							0
       _a   							=							True
       _a   							=							False
       _a   							=							None
       _a   							=							1_0000
       _a   							=							None
       _a   							=							"strict"
       _a   							=							"error"
       _a   							=							None



       def 				_lowerCAmelCase							(						self				:				int							)					->Tuple:
          if self.delimiter is not None:
             lowerCamelCase_						:   str		= self.delimiter
          if self.column_names is not None:
             lowerCamelCase_						:   Any		= self.column_names




       @property
       def 				_lowerCAmelCase							(						self				:				List[str]							)					->Union[str, Any]:
          lowerCamelCase_						:   Optional[int]		= {
              """sep""": self.sep,
              """header""": self.header,
              """names""": self.names,
              """index_col""": self.index_col,
              """usecols""": self.usecols,
              """prefix""": self.prefix,
              """mangle_dupe_cols""": self.mangle_dupe_cols,
              """engine""": self.engine,
              """converters""": self.converters,
              """true_values""": self.true_values,
              """false_values""": self.false_values,
              """skipinitialspace""": self.skipinitialspace,
              """skiprows""": self.skiprows,
              """nrows""": self.nrows,
              """na_values""": self.na_values,
              """keep_default_na""": self.keep_default_na,
              """na_filter""": self.na_filter,
              """verbose""": self.verbose,
              """skip_blank_lines""": self.skip_blank_lines,
              """thousands""": self.thousands,
              """decimal""": self.decimal,
              """lineterminator""": self.lineterminator,
              """quotechar""": self.quotechar,
              """quoting""": self.quoting,
              """escapechar""": self.escapechar,
              """comment""": self.comment,
              """encoding""": self.encoding,
              """dialect""": self.dialect,
              """error_bad_lines""": self.error_bad_lines,
              """warn_bad_lines""": self.warn_bad_lines,
              """skipfooter""": self.skipfooter,
              """doublequote""": self.doublequote,
              """memory_map""": self.memory_map,
              """float_precision""": self.float_precision,
              """chunksize""": self.chunksize,
              """encoding_errors""": self.encoding_errors,
              """on_bad_lines""": self.on_bad_lines,
              """date_format""": self.date_format,
          }

          # some kwargs must not be passed if they don't have a default value
          # some others are deprecated and we can also not pass them if they are the default value
          for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
             if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig()		,				__a							):
                del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 2.0 new arguments
          if not (datasets.config.PANDAS_VERSION.major >= 2):
             for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_2_0_0_PARAMETERS:
                del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 1.3 new arguments
          if not (datasets.config.PANDAS_VERSION.major >= 1 and datasets.config.PANDAS_VERSION.minor >= 3):
             for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_1_3_0_PARAMETERS:
                del pd_read_csv_kwargs[pd_read_csv_parameter]

          return pd_read_csv_kwargs







class   SCREAMING_SNAKE_CASE_			(datasets.ArrowBasedBuilder						):




       '''simple docstring'''



       _a   							=							CsvConfig



       def 				_lowerCAmelCase							(						self				:				Union[str, Any]							)					->List[Any]:
          return datasets.DatasetInfo(features=self.config.features							)



       def 				_lowerCAmelCase							(						self				:				Optional[Any]		,				__a				:				Dict							)					->List[str]:
          if not self.config.data_files:
             raise ValueError(F'''At least one data file must be specified, but got data_files={self.config.data_files}'''							)
          lowerCamelCase_						:   Optional[Any]		= dl_manager.download_and_extract(self.config.data_files							)
          if isinstance(__a		,				(str, list, tuple)							):
             lowerCamelCase_						:   Tuple		= data_files
             if isinstance(__a		,				__a							):
                lowerCamelCase_						:   Tuple		= [files]
             lowerCamelCase_						:   Dict		= [dl_manager.iter_files(__a							) for file in files]
             return [datasets.SplitGenerator(name=datasets.Split.TRAIN		,				gen_kwargs={"""files""": files}							)]
          lowerCamelCase_						:   int		= []
          for split_name, files in data_files.items():
             if isinstance(__a		,				__a							):
                lowerCamelCase_						:   Union[str, Any]		= [files]
             lowerCamelCase_						:   Optional[int]		= [dl_manager.iter_files(__a							) for file in files]
             splits.append(datasets.SplitGenerator(name=__a		,				gen_kwargs={"""files""": files}							)							)
          return splits



       def 				_lowerCAmelCase							(						self				:				List[Any]		,				__a				:				pa.Table							)					->pa.Table:
          if self.config.features is not None:
             lowerCamelCase_						:   int		= self.config.features.arrow_schema
             if all(not require_storage_cast(__a							) for feature in self.config.features.values()							):
                # cheaper cast
                lowerCamelCase_						:   str		= pa.Table.from_arrays([pa_table[field.name] for field in schema]		,				schema=__a							)
             else:
                # more expensive cast; allows str <-> int/float or str to Audio for example
                lowerCamelCase_						:   Dict		= table_cast(__a		,				__a							)
          return pa_table




       def 				_lowerCAmelCase							(						self				:				int		,				__a				:				Any							)					->Optional[Any]:
          lowerCamelCase_						:   Tuple		= self.config.features.arrow_schema if self.config.features else None
          # dtype allows reading an int column as str
          lowerCamelCase_						:   Dict		= (
              {
                  name: dtype.to_pandas_dtype() if not require_storage_cast(__a							) else object
                  for name, dtype, feature in zip(schema.names		,				schema.types		,				self.config.features.values()							)
              }
              if schema is not None
              else None
          )
          for file_idx, file in enumerate(itertools.chain.from_iterable(__a							)							):
             lowerCamelCase_						:   Optional[Any]		= pd.read_csv(__a		,				iterator=__a		,				dtype=__a		,				**self.config.pd_read_csv_kwargs							)
             try:
                for batch_idx, df in enumerate(__a							):
                   lowerCamelCase_						:   Optional[int]		= pa.Table.from_pandas(__a							)
                   # Uncomment for debugging (will print the Arrow table size and elements)
                   # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                   # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                   yield (file_idx, batch_idx), self._cast_table(__a							)
             except ValueError as e:
                logger.error(F'''Failed to read file \'{file}\' with error {type(__a							)}: {e}'''							)
                raise









import requests
from bsa import BeautifulSoup


def    __lowerCamelCase   (      A__						: str = "https://www.worldometers.info/coronavirus"					)     ->    dict:
   lowerCamelCase_						:   List[str]		= BeautifulSoup(requests.get(A__					).text						,						"""html.parser"""					)
   lowerCamelCase_						:   Tuple		= soup.findAll("""h1"""					)
   lowerCamelCase_						:   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')





