



"""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


__SCREAMING_SNAKE_CASE	:    int     				=   datasets.utils.logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE	:    str     				=   ['names', 'prefix']
__SCREAMING_SNAKE_CASE	:    List[Any]     				=   ['warn_bad_lines', 'error_bad_lines', 'mangle_dupe_cols']
__SCREAMING_SNAKE_CASE	:    Optional[int]     				=   ['encoding_errors', 'on_bad_lines']
__SCREAMING_SNAKE_CASE	:    str     				=   ['date_format']


@dataclass
class 				lowerCamelCase_( datasets.BuilderConfig     ):





					'''simple docstring'''



					lowercase__ :							Optional[int]              =			','
					lowercase__ :							Union[str, Any]              =			None
					lowercase__ :							List[Any]              =			'infer'
					lowercase__ :							Any              =			None
					lowercase__ :							Optional[int]              =			None
					lowercase__ :							Optional[int]              =			None
					lowercase__ :							Union[str, Any]              =			None
					lowercase__ :							Optional[Any]              =			None
					lowercase__ :							List[Any]              =			True
					lowercase__ :							str              =			None
					lowercase__ :							Dict              =			None
					lowercase__ :							str              =			None
					lowercase__ :							Dict              =			None
					lowercase__ :							Optional[int]              =			False
					lowercase__ :							int              =			None
					lowercase__ :							List[str]              =			None
					lowercase__ :							Union[str, Any]              =			None
					lowercase__ :							Optional[int]              =			True
					lowercase__ :							Union[str, Any]              =			True
					lowercase__ :							List[Any]              =			False
					lowercase__ :							str              =			True
					lowercase__ :							List[Any]              =			None
					lowercase__ :							Dict              =			'.'
					lowercase__ :							int              =			None
					lowercase__ :							Tuple              =			'"'
					lowercase__ :							Union[str, Any]              =			0
					lowercase__ :							List[Any]              =			None
					lowercase__ :							Any              =			None
					lowercase__ :							Optional[int]              =			None
					lowercase__ :							List[Any]              =			None
					lowercase__ :							str              =			True
					lowercase__ :							Dict              =			True
					lowercase__ :							int              =			0
					lowercase__ :							int              =			True
					lowercase__ :							List[Any]              =			False
					lowercase__ :							Tuple              =			None
					lowercase__ :							str              =			10_000
					lowercase__ :							str              =			None
					lowercase__ :							int              =			'strict'
					lowercase__ :							Optional[int]              =			'error'
					lowercase__ :							Tuple              =			None

					def       snake_case__   (     self ):
									if self.delimiter is not None:
													_lowerCamelCase   	=					self.delimiter
									if self.column_names is not None:
													_lowerCamelCase   	=					self.column_names





					@property
					def       snake_case__   (     self ):
									_lowerCamelCase   	=					{
									    '''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()					,							_lowerCAmelCase ):
																	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     ):





					'''simple docstring'''



					lowercase__ :							Any              =			CsvConfig

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

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

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





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






from __future__ import annotations

from collections.abc import Iterator





class 			lowerCamelCase_				:


 '''simple docstring'''







 def __init__(				self    :						Union[str, Any]							,							_lowerCAmelCase    :						int		):
       SCREAMING_SNAKE_CASE_      		=     value
       SCREAMING_SNAKE_CASE_      		=     None
       SCREAMING_SNAKE_CASE_      		=     None





class 			lowerCamelCase_				:


 '''simple docstring'''







 def __init__(				self    :						int							,							_lowerCAmelCase    :						Node		):
       SCREAMING_SNAKE_CASE_      		=     tree



 def  lowerCAmelCase_    (				self    :						Union[str, Any]							,							_lowerCAmelCase    :						Node | None		):
       if node is None:
             return 0
       return node.value + (
           self.depth_first_search(node.left		) + self.depth_first_search(node.right		)
       )




 def __iter__(				self    :						Dict		):
       yield self.depth_first_search(self.tree		)


if __name__ == "__main__":
   import doctest

   doctest.testmod()