




"""simple docstring"""




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


lowerCAmelCase							:    Optional[int]  							=							datasets.utils.logging.get_logger(__name__)







@dataclass
class 					__magic_name__							( datasets.BuilderConfig       ):






				'''simple docstring'''
				__UpperCamelCase    						=		1_00_00
				__UpperCamelCase    						=		None
				__UpperCamelCase    						=		None







class 					__magic_name__							( datasets.ArrowBasedBuilder       ):






				'''simple docstring'''
				__UpperCamelCase    						=		ParquetConfig





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return datasets.DatasetInfo(features=self.config.features				)





				def      _lowerCAmelCase       ( self	,				_a				):





							"""simple docstring"""
							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(_a	,				(str, list, tuple)				):
										lowerCamelCase       =      data_files
										if isinstance(_a	,				_a				):
													lowerCamelCase       =      [files]
										# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
										lowerCamelCase       =      [dl_manager.iter_files(_a				) 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(_a	,				_a				):
													lowerCamelCase       =      [files]
										# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
										lowerCamelCase       =      [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:
																			lowerCamelCase       =      datasets.Features.from_arrow_schema(pq.read_schema(_a				)				)
																break
										splits.append(datasets.SplitGenerator(name=_a	,				gen_kwargs={"""files""": files}				)				)
							return splits





				def      _lowerCAmelCase       ( self	,				_a				):





							"""simple docstring"""
							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
										lowerCamelCase       =      table_cast(_a	,				self.info.features.arrow_schema				)
							return pa_table





				def      _lowerCAmelCase       ( self	,				_a				):





							"""simple docstring"""
							lowerCamelCase       =      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:
													lowerCamelCase       =      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				)				):
																			lowerCamelCase       =      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









"""simple docstring"""




from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap



def 					a__				(       snake_case__       )		->      List[str]:
			return getitem, k



def 					a__				(       snake_case__ ,				snake_case__       )		->      Optional[Any]:
			return setitem, k, v



def 					a__				(       snake_case__       )		->      str:
			return delitem, k



def 					a__				(       snake_case__ ,				snake_case__ ,				*snake_case__       )		->      Union[str, Any]:
			try:
						return fun(snake_case__ ,				*snake_case__       ), None
			except Exception as e:
						return None, e


lowerCAmelCase							:    Optional[int]  							=							(
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
)

lowerCAmelCase							:    List[Any]  							=							[
    _set("""key_a""", """val_a"""),
    _set("""key_a""", """val_b"""),
]

lowerCAmelCase							:    List[Any]  							=							[
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
    _del("""key_a"""),
    _del("""key_b"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
]

lowerCAmelCase							:    List[Any]  							=							[
    _get("""key_a"""),
    _del("""key_a"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
    _del("""key_a"""),
    _get("""key_a"""),
]

lowerCAmelCase							:    Tuple  							=							[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

lowerCAmelCase							:    Tuple  							=							[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set("""key_a""", """val_b"""),
]



@pytest.mark.parametrize(
    """operations""" ,				(
        pytest.param(_add_items ,				id="""add items"""       ),
        pytest.param(_overwrite_items ,				id="""overwrite items"""       ),
        pytest.param(_delete_items ,				id="""delete items"""       ),
        pytest.param(_access_absent_items ,				id="""access absent items"""       ),
        pytest.param(_add_with_resize_up ,				id="""add with resize up"""       ),
        pytest.param(_add_with_resize_down ,				id="""add with resize down"""       ),
    ) ,				)
def 					a__				(       snake_case__       )		->      Any:
			lowerCamelCase       =      HashMap(initial_block_size=4       )
			lowerCamelCase       =      {}
			for _, (fun, *args) in enumerate(snake_case__       ):
						lowerCamelCase   ,     lowerCamelCase       =      _run_operation(snake_case__ ,				snake_case__ ,				*snake_case__       )
						lowerCamelCase   ,     lowerCamelCase       =      _run_operation(snake_case__ ,				snake_case__ ,				*snake_case__       )
						assert my_res == py_res
						assert str(snake_case__       ) == str(snake_case__       )
						assert set(snake_case__       ) == set(snake_case__       )
						assert len(snake_case__       ) == len(snake_case__       )
						assert set(my.items()       ) == set(py.items()       )



def 					a__				(       )		->      int:
			def is_public(snake_case__       ) -> bool:
						return not name.startswith("""_"""       )

			lowerCamelCase       =      {name for name in dir({}       ) if is_public(snake_case__       )}
			lowerCamelCase       =      {name for name in dir(HashMap()       ) if is_public(snake_case__       )}

			assert dict_public_names > hash_public_names



