


'''simple docstring'''
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


lowerCAmelCase						=					datasets.utils.logging.get_logger(__name__)

lowerCAmelCase						=					["""names""", """prefix"""]
lowerCAmelCase						=					["""warn_bad_lines""", """error_bad_lines""", """mangle_dupe_cols"""]
lowerCAmelCase						=					["""encoding_errors""", """on_bad_lines"""]
lowerCAmelCase						=					["""date_format"""]






@dataclass
class        lowerCAmelCase_  (     datasets.BuilderConfig	):
       __UpperCAmelCase					=","
       __UpperCAmelCase					=None
       __UpperCAmelCase					="infer"
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=True
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=False
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=True
       __UpperCAmelCase					=True
       __UpperCAmelCase					=False
       __UpperCAmelCase					=True
       __UpperCAmelCase					=None
       __UpperCAmelCase					="."
       __UpperCAmelCase					=None
       __UpperCAmelCase					='"'
       __UpperCAmelCase					=0
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=None
       __UpperCAmelCase					=True
       __UpperCAmelCase					=True
       __UpperCAmelCase					=0
       __UpperCAmelCase					=True
       __UpperCAmelCase					=False
       __UpperCAmelCase					=None
       __UpperCAmelCase					=10_000
       __UpperCAmelCase					=None
       __UpperCAmelCase					="strict"
       __UpperCAmelCase					="error"
       __UpperCAmelCase					=None






       def   UpperCamelCase						( self   )->      Optional[Any]:
            if self.delimiter is not None:
                 _A				=							self.delimiter
            if self.column_names is not None:
                 _A				=							self.column_names






       @property
       def   UpperCamelCase						( self   )->      str:
            _A				=							{
                '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()			,     _UpperCamelCase   ):
                      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        lowerCAmelCase_  (     datasets.ArrowBasedBuilder	):
       __UpperCAmelCase					=CsvConfig






       def   UpperCamelCase						( self   )->      int:
            return datasets.DatasetInfo(features=self.config.features   )






       def   UpperCamelCase						( self			,     _UpperCamelCase   )->      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}'   )
            _A				=							dl_manager.download_and_extract(self.config.data_files   )
            if isinstance(_UpperCamelCase			,     (str, list, tuple)   ):
                 _A				=							data_files
                 if isinstance(_UpperCamelCase			,     _UpperCamelCase   ):
                      _A				=							[files]
                 _A				=							[dl_manager.iter_files(_UpperCamelCase   ) for file in files]
                 return [datasets.SplitGenerator(name=datasets.Split.TRAIN			,     gen_kwargs={'files': files}   )]
            _A				=							[]
            for split_name, files in data_files.items():
                 if isinstance(_UpperCamelCase			,     _UpperCamelCase   ):
                      _A				=							[files]
                 _A				=							[dl_manager.iter_files(_UpperCamelCase   ) for file in files]
                 splits.append(datasets.SplitGenerator(name=_UpperCamelCase			,     gen_kwargs={'files': files}   )   )
            return splits






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






       def   UpperCamelCase						( self			,     _UpperCamelCase   )->      Any:
            _A				=							self.config.features.arrow_schema if self.config.features else None
            # dtype allows reading an int column as str
            _A				=							(
                {
                    name: dtype.to_pandas_dtype() if not require_storage_cast(_UpperCamelCase   ) 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(_UpperCamelCase   )   ):
                 _A				=							pd.read_csv(_UpperCamelCase			,     iterator=_UpperCamelCase			,     dtype=_UpperCamelCase			,     **self.config.pd_read_csv_kwargs   )
                 try:
                      for batch_idx, df in enumerate(_UpperCamelCase   ):
                           _A				=							pa.Table.from_pandas(_UpperCamelCase   )
                           # 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(_UpperCamelCase   )
                 except ValueError as e:
                      logger.error(F'Failed to read file \'{file}\' with error {type(_UpperCamelCase   )}: {e}'   )
                      raise









'''simple docstring'''
def 					lowerCamelCase_ ( __UpperCamelCase					:       int							,    __UpperCamelCase					:       int		)					->	int:







     """simple docstring"""
     while second != 0:
          _A				=							first & second
          first ^= second
          _A				=							c << 1
     return first


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    lowerCAmelCase						=					int(input("""Enter the first number: """).strip())
    lowerCAmelCase						=					int(input("""Enter the second number: """).strip())
    print(F'{add(first, second) = }')





