


'''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


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

@dataclass
class 		UpperCAmelCase_      (  datasets.BuilderConfig		):
     lowerCamelCase				:	int		=     10_000
     lowerCamelCase				:	Optional[List[str]]		=     None
     lowerCamelCase				:	Optional[datasets.Features]		=     None




class 		UpperCAmelCase_      (  datasets.ArrowBasedBuilder		):
     lowerCamelCase				:	List[str]		=     ParquetConfig





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





     def 							__UpperCAmelCase      ( self       :      Optional[int]    ,      UpperCAmelCase__       :      Union[str, Any]    )				->  Tuple:
        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(UpperCAmelCase__    ,      (str, list, tuple)    ):
           lowerCAmelCase     =			data_files
           if isinstance(UpperCAmelCase__    ,      UpperCAmelCase__    ):
              lowerCAmelCase     =			[files]
           # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
           lowerCAmelCase     =			[dl_manager.iter_files(UpperCAmelCase__    ) 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(UpperCAmelCase__    ,      UpperCAmelCase__    ):
              lowerCAmelCase     =			[files]
           # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
           lowerCAmelCase     =			[dl_manager.iter_files(UpperCAmelCase__    ) 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(UpperCAmelCase__    ):
                 with open(UpperCAmelCase__    ,      'rb'    ) as f:
                    lowerCAmelCase     =			datasets.Features.from_arrow_schema(pq.read_schema(UpperCAmelCase__    )    )
                 break
           splits.append(datasets.SplitGenerator(name=UpperCAmelCase__    ,      gen_kwargs={'files': files}    )    )
        return splits





     def 							__UpperCAmelCase      ( self       :      str    ,      UpperCAmelCase__       :      pa.Table    )				->  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
           lowerCAmelCase     =			table_cast(UpperCAmelCase__    ,      self.info.features.arrow_schema    )
        return pa_table





     def 							__UpperCAmelCase      ( self       :      Dict    ,      UpperCAmelCase__       :      int    )				->  Dict:
        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(UpperCAmelCase__    )    ):
           with open(UpperCAmelCase__    ,      'rb'    ) as f:
              lowerCAmelCase     =			pq.ParquetFile(UpperCAmelCase__    )
              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(UpperCAmelCase__    )
              except ValueError as e:
                 logger.error(F'''Failed to read file \'{file}\' with error {type(UpperCAmelCase__    )}: {e}'''    )
                 raise









'''simple docstring'''




import os

__snake_case    						={"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1_000}





def 	a_					( lowerCamelCase	:     str				):
   lowerCAmelCase     =			0

   lowerCAmelCase     =			0
   while index < len(lowerCamelCase				) - 1:
      lowerCAmelCase     =			SYMBOLS[numerals[index]]
      lowerCAmelCase     =			SYMBOLS[numerals[index + 1]]
      if current_value < next_value:
         total_value -= current_value
      else:
         total_value += current_value
      index += 1
   total_value += SYMBOLS[numerals[index]]

   return total_value





def 	a_					( lowerCamelCase	:     int				):
   lowerCAmelCase     =			''

   lowerCAmelCase     =			num // 1000
   numerals += m_count * "M"
   num %= 1000

   lowerCAmelCase     =			num // 100
   if c_count == 9:
      numerals += "CM"
      c_count -= 9
   elif c_count == 4:
      numerals += "CD"
      c_count -= 4
   if c_count >= 5:
      numerals += "D"
      c_count -= 5
   numerals += c_count * "C"
   num %= 100

   lowerCAmelCase     =			num // 10
   if x_count == 9:
      numerals += "XC"
      x_count -= 9
   elif x_count == 4:
      numerals += "XL"
      x_count -= 4
   if x_count >= 5:
      numerals += "L"
      x_count -= 5
   numerals += x_count * "X"
   num %= 10

   if num == 9:
      numerals += "IX"
      num -= 9
   elif num == 4:
      numerals += "IV"
      num -= 4
   if num >= 5:
      numerals += "V"
      num -= 5
   numerals += num * "I"

   return numerals





def 	a_					( lowerCamelCase	:     str = "/p089_roman.txt"				):
   lowerCAmelCase     =			0

   with open(os.path.dirname(lowerCamelCase				) + roman_numerals_filename				) as filea:
      lowerCAmelCase     =			filea.readlines()

   for line in lines:
      lowerCAmelCase     =			line.strip()
      lowerCAmelCase     =			parse_roman_numerals(lowerCamelCase				)
      lowerCAmelCase     =			generate_roman_numerals(lowerCamelCase				)
      savings += len(lowerCamelCase				) - len(lowerCamelCase				)

   return savings


if __name__ == "__main__":
       print(F'''{solution() = }''')





