"""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     UpperCamelCase__(			datasets.BuilderConfig ):
						lowerCAmelCase__  :						List[Any]													=		','
						lowerCAmelCase__  :						List[Any]													=		None
						lowerCAmelCase__  :						int													=		'infer'
						lowerCAmelCase__  :						Optional[int]													=		None
						lowerCAmelCase__  :						Optional[Any]													=		None
						lowerCAmelCase__  :						Optional[Any]													=		None
						lowerCAmelCase__  :						Any													=		None
						lowerCAmelCase__  :						Any													=		None
						lowerCAmelCase__  :						List[str]													=		True
						lowerCAmelCase__  :						Optional[int]													=		None
						lowerCAmelCase__  :						Optional[int]													=		None
						lowerCAmelCase__  :						str													=		None
						lowerCAmelCase__  :						List[Any]													=		None
						lowerCAmelCase__  :						Tuple													=		False
						lowerCAmelCase__  :						Dict													=		None
						lowerCAmelCase__  :						Dict													=		None
						lowerCAmelCase__  :						List[str]													=		None
						lowerCAmelCase__  :						Tuple													=		True
						lowerCAmelCase__  :						Optional[Any]													=		True
						lowerCAmelCase__  :						str													=		False
						lowerCAmelCase__  :						Optional[Any]													=		True
						lowerCAmelCase__  :						Any													=		None
						lowerCAmelCase__  :						Union[str, Any]													=		'.'
						lowerCAmelCase__  :						Union[str, Any]													=		None
						lowerCAmelCase__  :						Union[str, Any]													=		'"'
						lowerCAmelCase__  :						List[str]													=		0
						lowerCAmelCase__  :						Optional[Any]													=		None
						lowerCAmelCase__  :						Optional[Any]													=		None
						lowerCAmelCase__  :						List[str]													=		None
						lowerCAmelCase__  :						Optional[int]													=		None
						lowerCAmelCase__  :						Union[str, Any]													=		True
						lowerCAmelCase__  :						Union[str, Any]													=		True
						lowerCAmelCase__  :						Dict													=		0
						lowerCAmelCase__  :						Optional[int]													=		True
						lowerCAmelCase__  :						Optional[int]													=		False
						lowerCAmelCase__  :						Any													=		None
						lowerCAmelCase__  :						Tuple													=		1_0000
						lowerCAmelCase__  :						Tuple													=		None
						lowerCAmelCase__  :						List[str]													=		'strict'
						lowerCAmelCase__  :						List[Any]													=		'error'
						lowerCAmelCase__  :						Dict													=		None





						def 				snake_case__	(       self     )					->				int:
													if self.delimiter is not None:
																				A__	     =							self.delimiter
													if self.column_names is not None:
																				A__	     =							self.column_names





						@property
						def 				snake_case__	(       self     )					->				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()		,__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     UpperCamelCase__(			datasets.ArrowBasedBuilder ):
						lowerCAmelCase__  :						Union[str, Any]													=		CsvConfig





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





						def 				snake_case__	(       self		,__UpperCAmelCase     )					->				int:
													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 				snake_case__	(       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 				snake_case__	(       self		,__UpperCAmelCase     )					->				Union[str, 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   UpperCAmelCase					(	UpperCamelCase__				):






							"""simple docstring"""





							if len(UpperCamelCase__				) <= 1:
														return [tuple(UpperCamelCase__				)]

							A__	     =							[]

							def generate(UpperCamelCase__       ,    UpperCamelCase__				):
														if k == 1:
																					res.append(tuple(arr[:]				)				)
																					return

														generate(k - 1       ,    UpperCamelCase__				)

														for i in range(k - 1				):
																					if k % 2 == 0:  # k is even
																												A__     ,  A__	     =							arr[k - 1], arr[i]
																					else:  # k is odd
																												A__     ,  A__	     =							arr[k - 1], arr[0]
																					generate(k - 1       ,    UpperCamelCase__				)

							generate(len(UpperCamelCase__				)       ,    UpperCamelCase__				)
							return res


if __name__ == "__main__":
				__lowerCamelCase											=  input("Enter numbers separated by a comma:\n").strip()
				__lowerCamelCase											=  [int(item) for item in user_input.split(",")]
				print(heaps(arr))





