






import itertools
from dataclasses import dataclass
from typing import List, Optional

import pyarrow as pa
import pyarrow.parquet as pq

import datasets
from datasets.table import table_cast


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




@dataclass
class 					UpperCamelCase_ (     datasets.BuilderConfig							):



	'''simple docstring'''




	lowerCAmelCase						=					1_0_0_0_0
	lowerCAmelCase						=					None
	lowerCAmelCase						=					None






class 					UpperCamelCase_ (     datasets.ArrowBasedBuilder							):



	'''simple docstring'''




	lowerCAmelCase						=					ParquetConfig




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




	def 				_UpperCamelCase     (			self			,     a   )			->       Optional[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}'''   )
								snake_case_           =				dl_manager.download_and_extract(self.config.data_files   )
								if isinstance(a			,     (str, list, tuple)   ):
															snake_case_           =				data_files
															if isinstance(a			,     a   ):
																						snake_case_           =				[files]
															# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
															snake_case_           =				[dl_manager.iter_files(a   ) for file in files]
															return [datasets.SplitGenerator(name=datasets.Split.TRAIN			,     gen_kwargs={'files': files}   )]
								snake_case_           =				[]
								for split_name, files in data_files.items():
															if isinstance(a			,     a   ):
																						snake_case_           =				[files]
															# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
															snake_case_           =				[dl_manager.iter_files(a   ) for file in files]
															# Infer features is they are stoed in the arrow schema
															if self.info.features is None:
																						for file in itertools.chain.from_iterable(a   ):
																													with open(a			,     'rb'   ) as f:
																																				snake_case_           =				datasets.Features.from_arrow_schema(pq.read_schema(a   )   )
																													break
															splits.append(datasets.SplitGenerator(name=a			,     gen_kwargs={'files': files}   )   )
								return splits




	def 				_UpperCamelCase     (			self			,     a   )			->       pa.Table:
								if self.info.features is not None:
															# more expensive cast to support nested features with keys in a different order
															# allows str <-> int/float or str to Audio for example
															snake_case_           =				table_cast(a			,     self.info.features.arrow_schema   )
								return pa_table






	def 				_UpperCamelCase     (			self			,     a   )			->       List[Any]:
								snake_case_           =				self.info.features.arrow_schema if self.info.features is not None else None
								if self.info.features is not None and self.config.columns is not None:
															if sorted(field.name for field in schema   ) != sorted(self.config.columns   ):
																						raise ValueError(
																						    F'''Tried to load parquet data with columns \'{self.config.columns}\' with mismatching features \'{self.info.features}\''''   )
								for file_idx, file in enumerate(itertools.chain.from_iterable(a   )   ):
															with open(a			,     'rb'   ) as f:
																						snake_case_           =				pq.ParquetFile(a   )
																						try:
																													for batch_idx, record_batch in enumerate(
																													    parquet_file.iter_batches(batch_size=self.config.batch_size			,     columns=self.config.columns   )   ):
																																				snake_case_           =				pa.Table.from_batches([record_batch]   )
																																				# 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 F'''{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













from __future__ import annotations

import sys
from collections import deque
from typing import Generic, TypeVar

lowercase    				=   TypeVar("T")




class 					UpperCamelCase_ (     Generic[T]							):



	'''simple docstring'''




	lowerCAmelCase						=					42  # Cache store of keys
	lowerCAmelCase						=					42  # References of the keys in cache
	lowerCAmelCase						=					1_0  # Maximum capacity of cache




	def __init__(			self			,     a   )			->       None:
								snake_case_           =				deque()
								snake_case_           =				set()
								if not n:
															snake_case_           =				sys.maxsize
								elif n < 0:
															raise ValueError('n should be an integer greater than 0.'   )
								else:
															snake_case_           =				n




	def 				_UpperCamelCase     (			self			,     a   )			->       None:
								if x not in self.key_reference:
															if len(self.dq_store   ) == LRUCache._MAX_CAPACITY:
																						snake_case_           =				self.dq_store.pop()
																						self.key_reference.remove(a   )
								else:
															self.dq_store.remove(a   )

								self.dq_store.appendleft(a   )
								self.key_reference.add(a   )




	def 				_UpperCamelCase     (			self   )			->       None:
								for k in self.dq_store:
															print(a   )






	def __repr__(			self   )			->       str:
								return F'''LRUCache({self._MAX_CAPACITY}) => {list(self.dq_store   )}'''


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	lowercase    				=   LRUCache(4)
	lru_cache.refer("A")
	lru_cache.refer(2)
	lru_cache.refer(3)
	lru_cache.refer("A")
	lru_cache.refer(4)
	lru_cache.refer(5)
	lru_cache.display()

	print(lru_cache)
	assert str(lru_cache) == "LRUCache(4) => [5, 4, 'A', 3]"





