"""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


UpperCamelCase						:				Any             =      datasets.utils.logging.get_logger(__name__)

UpperCamelCase						:				Tuple             =      ["names", "prefix"]
UpperCamelCase						:				Optional[Any]             =      ["warn_bad_lines", "error_bad_lines", "mangle_dupe_cols"]
UpperCamelCase						:				List[str]             =      ["encoding_errors", "on_bad_lines"]
UpperCamelCase						:				Any             =      ["date_format"]



@dataclass
class 			lowerCamelCase__						(   datasets.BuilderConfig			):
						lowerCAmelCase       =     ""","""
						lowerCAmelCase       =     None
						lowerCAmelCase       =     """infer"""
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     True
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     False
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     True
						lowerCAmelCase       =     True
						lowerCAmelCase       =     False
						lowerCAmelCase       =     True
						lowerCAmelCase       =     None
						lowerCAmelCase       =     """."""
						lowerCAmelCase       =     None
						lowerCAmelCase       =     """\""""
						lowerCAmelCase       =     0
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     None
						lowerCAmelCase       =     True
						lowerCAmelCase       =     True
						lowerCAmelCase       =     0
						lowerCAmelCase       =     True
						lowerCAmelCase       =     False
						lowerCAmelCase       =     None
						lowerCAmelCase       =     10000
						lowerCAmelCase       =     None
						lowerCAmelCase       =     """strict"""
						lowerCAmelCase       =     """error"""
						lowerCAmelCase       =     None







						def __a						(							self   :    Tuple		):
								if self.delimiter is not None:
										A					       = self.delimiter
								if self.column_names is not None:
										A					       = self.column_names







						@property
						def __a						(							self   :    int		):
								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()			,			_lowercase		):
												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			):
						lowerCAmelCase       =     CsvConfig







						def __a						(							self   :    str		):
								return datasets.DatasetInfo(features=self.config.features		)







						def __a						(							self   :    List[str]			,			_lowercase   :    Any		):
								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(_lowercase			,			(str, list, tuple)		):
										A					       = data_files
										if isinstance(_lowercase			,			_lowercase		):
												A					       = [files]
										A					       = [dl_manager.iter_files(_lowercase		) 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(_lowercase			,			_lowercase		):
												A					       = [files]
										A					       = [dl_manager.iter_files(_lowercase		) for file in files]
										splits.append(datasets.SplitGenerator(name=_lowercase			,			gen_kwargs={'files': files}		)		)
								return splits







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







						def __a						(							self   :    str			,			_lowercase   :    Optional[int]		):
								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(_lowercase		) 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(_lowercase		)		):
										A					       = pd.read_csv(_lowercase			,			iterator=_lowercase			,			dtype=_lowercase			,			**self.config.pd_read_csv_kwargs		)
										try:
												for batch_idx, df in enumerate(_lowercase		):
														A					       = pa.Table.from_pandas(_lowercase		)
														# 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(_lowercase		)
										except ValueError as e:
												logger.error(f'Failed to read file \'{file}\' with error {type(_lowercase		)}: {e}'		)
												raise









"""simple docstring"""


from __future__ import annotations







def  __snake_case       (   UpperCamelCase__	)      ->		int:







		"""simple docstring"""





		if not nums:
				return 0
		A					       = nums[0]
		A					       = 0
		for num in nums[1:]:
				A       , A					       = (
				    max_excluding + num,
				    max(UpperCamelCase__ ,			UpperCamelCase__	),
				)
		return max(UpperCamelCase__ ,			UpperCamelCase__	)


if __name__ == "__main__":
	import doctest

	doctest.testmod()





