
"""simple docstring"""


from __future__ import annotations

from collections.abc import Iterator
from typing import Any







class 					lowerCAmelCase_					:



						'''simple docstring'''


						def __init__(			self  :   Optional[Any]	,A_  :   Any   )  -> List[Any]:
							A     = data
							A     = None







class 					lowerCAmelCase_					:



						'''simple docstring'''


						def __init__(			self  :   int   )  -> List[str]:
							A     = None
							A     = None


						def __iter__(			self  :   List[Any]   )  -> Iterator[Any]:
							A     = self.head
							while self.head:
								yield node.data
								A     = node.next
								if node == self.head:
									break


						def __len__(			self  :   List[str]   )  -> int:
							return sum(1 for _ in self   )


						def __repr__(			self  :   Any   )  -> Union[str, Any]:
							return "->".join(str(A_   ) for item in iter(self   )   )


						def     _SCREAMING_SNAKE_CASE   (			self  :   List[str]	,A_  :   Any   )  -> None:
							self.insert_nth(len(self   )	,A_   )


						def     _SCREAMING_SNAKE_CASE   (			self  :   Union[str, Any]	,A_  :   Any   )  -> None:
							self.insert_nth(0	,A_   )


						def     _SCREAMING_SNAKE_CASE   (			self  :   List[Any]	,A_  :   int	,A_  :   Any   )  -> None:
							if index < 0 or index > len(self   ):
								raise IndexError('list index out of range.'   )
							A     = Node(A_   )
							if self.head is None:
								A     = new_node  # first node points itself
								A     = A     = new_node
							elif index == 0:  # insert at head
								A     = self.head
								A     = A     = new_node
							else:
								A     = self.head
								for _ in range(index - 1   ):
									A     = temp.next
								A     = temp.next
								A     = new_node
								if index == len(self   ) - 1:  # insert at tail
									A     = new_node


						def     _SCREAMING_SNAKE_CASE   (			self  :   Tuple   )  -> Union[str, Any]:
							return self.delete_nth(0   )


						def     _SCREAMING_SNAKE_CASE   (			self  :   Union[str, Any]   )  -> Any:
							return self.delete_nth(len(self   ) - 1   )


						def     _SCREAMING_SNAKE_CASE   (			self  :   Tuple	,A_  :   int = 0   )  -> Any:
							if not 0 <= index < len(self   ):
								raise IndexError('list index out of range.'   )
							A     = self.head
							if self.head == self.tail:  # just one node
								A     = A     = None
							elif index == 0:  # delete head node
								A     = self.tail.next.next
								A     = self.head.next
							else:
								A     = self.head
								for _ in range(index - 1   ):
									A     = temp.next
								A     = temp.next
								A     = temp.next.next
								if index == len(self   ) - 1:  # delete at tail
									A     = temp
							return delete_node.data




						def     _SCREAMING_SNAKE_CASE   (			self  :   Dict   )  -> bool:
							return len(self   ) == 0






def    _snake_case					(		):
	A     = CircularLinkedList()
	assert len(snake_case__  ) == 0
	assert circular_linked_list.is_empty() is True
	assert str(snake_case__  ) == ""

	try:
		circular_linked_list.delete_front()
		raise AssertionError  # This should not happen
	except IndexError:
		assert True  # This should happen

	try:
		circular_linked_list.delete_tail()
		raise AssertionError  # This should not happen
	except IndexError:
		assert True  # This should happen

	try:
		circular_linked_list.delete_nth(-1  )
		raise AssertionError
	except IndexError:
		assert True

	try:
		circular_linked_list.delete_nth(0  )
		raise AssertionError
	except IndexError:
		assert True

	assert circular_linked_list.is_empty() is True
	for i in range(5  ):
		assert len(snake_case__  ) == i
		circular_linked_list.insert_nth(snake_case__						,   i + 1  )
	assert str(snake_case__  ) == "->".join(str(snake_case__  ) for i in range(1						,   6  )  )

	circular_linked_list.insert_tail(6  )
	assert str(snake_case__  ) == "->".join(str(snake_case__  ) for i in range(1						,   7  )  )
	circular_linked_list.insert_head(0  )
	assert str(snake_case__  ) == "->".join(str(snake_case__  ) for i in range(0						,   7  )  )

	assert circular_linked_list.delete_front() == 0
	assert circular_linked_list.delete_tail() == 6
	assert str(snake_case__  ) == "->".join(str(snake_case__  ) for i in range(1						,   6  )  )
	assert circular_linked_list.delete_nth(2  ) == 3

	circular_linked_list.insert_nth(2						,   3  )
	assert str(snake_case__  ) == "->".join(str(snake_case__  ) for i in range(1						,   6  )  )

	assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
		import doctest

		doctest.testmod()

"""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


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

_lowercase				 =					['''names''', '''prefix''']
_lowercase				 =					['''warn_bad_lines''', '''error_bad_lines''', '''mangle_dupe_cols''']
_lowercase				 =					['''encoding_errors''', '''on_bad_lines''']
_lowercase				 =					['''date_format''']







@dataclass
class 					lowerCAmelCase_					(   datasets.BuilderConfig     ):



						'''simple docstring'''


						_lowerCamelCase:     str   =     ","
						_lowerCamelCase:     Optional[str]   =     None
						_lowerCamelCase:     Optional[Union[int, List[int], str]]   =     "infer"
						_lowerCamelCase:     Optional[List[str]]   =     None
						_lowerCamelCase:     Optional[List[str]]   =     None
						_lowerCamelCase:     Optional[Union[int, str, List[int], List[str]]]   =     None
						_lowerCamelCase:     Optional[Union[List[int], List[str]]]   =     None
						_lowerCamelCase:     Optional[str]   =     None
						_lowerCamelCase:     bool   =     True
						_lowerCamelCase:     Optional[Literal["c", "python", "pyarrow"]]   =     None
						_lowerCamelCase:     Dict[Union[int, str], Callable[[Any], Any]]   =     None
						_lowerCamelCase:     Optional[list]   =     None
						_lowerCamelCase:     Optional[list]   =     None
						_lowerCamelCase:     bool   =     False
						_lowerCamelCase:     Optional[Union[int, List[int]]]   =     None
						_lowerCamelCase:     Optional[int]   =     None
						_lowerCamelCase:     Optional[Union[str, List[str]]]   =     None
						_lowerCamelCase:     bool   =     True
						_lowerCamelCase:     bool   =     True
						_lowerCamelCase:     bool   =     False
						_lowerCamelCase:     bool   =     True
						_lowerCamelCase:     Optional[str]   =     None
						_lowerCamelCase:     str   =     "."
						_lowerCamelCase:     Optional[str]   =     None
						_lowerCamelCase:     str   =     '"'
						_lowerCamelCase:     int   =     0
						_lowerCamelCase:     Optional[str]   =     None
						_lowerCamelCase:     Optional[str]   =     None
						_lowerCamelCase:     Optional[str]   =     None
						_lowerCamelCase:     Optional[str]   =     None
						_lowerCamelCase:     bool   =     True
						_lowerCamelCase:     bool   =     True
						_lowerCamelCase:     int   =     0
						_lowerCamelCase:     bool   =     True
						_lowerCamelCase:     bool   =     False
						_lowerCamelCase:     Optional[str]   =     None
						_lowerCamelCase:     int   =     10000
						_lowerCamelCase:     Optional[datasets.Features]   =     None
						_lowerCamelCase:     Optional[str]   =     "strict"
						_lowerCamelCase:     Literal["error", "warn", "skip"]   =     "error"
						_lowerCamelCase:     Optional[str]   =     None


						def     _SCREAMING_SNAKE_CASE   (			self  :   str   )  -> Any:
							if self.delimiter is not None:
								A     = self.delimiter
							if self.column_names is not None:
								A     = self.column_names




						@property
						def     _SCREAMING_SNAKE_CASE   (			self  :   Optional[Any]   )  -> Any:
							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()	,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 					lowerCAmelCase_					(   datasets.ArrowBasedBuilder     ):



						'''simple docstring'''


						_lowerCamelCase:     Any   =     CsvConfig


						def     _SCREAMING_SNAKE_CASE   (			self  :   Optional[Any]   )  -> Optional[int]:
							return datasets.DatasetInfo(features=self.config.features   )


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


						def     _SCREAMING_SNAKE_CASE   (			self  :   Union[str, Any]	,A_  :   pa.Table   )  -> pa.Table:
							if self.config.features is not None:
								A     = self.config.features.arrow_schema
								if all(not require_storage_cast(A_   ) for feature in self.config.features.values()   ):
									# cheaper cast
									A     = 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
									A     = table_cast(A_	,A_   )
							return pa_table




						def     _SCREAMING_SNAKE_CASE   (			self  :   Tuple	,A_  :   Union[str, Any]   )  -> List[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(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_   )   ):
								A     = pd.read_csv(A_	,iterator=A_	,dtype=A_	,**self.config.pd_read_csv_kwargs   )
								try:
									for batch_idx, df in enumerate(A_   ):
										A     = 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