


from collections.abc import Generator
from math import sin




def 	a_      (    SCREAMING_SNAKE_CASE__					:      bytes     ):
       '''simple docstring'''





       if len(SCREAMING_SNAKE_CASE__     ) != 32:
              raise ValueError('Input must be of length 32'     )

       _lowerCamelCase       :		Any		=b''
       for i in [3, 2, 1, 0]:
              little_endian += string_aa[8 * i : 8 * i + 8]
       return little_endian




def 	a_      (    SCREAMING_SNAKE_CASE__					:      int     ):
       '''simple docstring'''





       if i < 0:
              raise ValueError('Input must be non-negative'     )

       _lowerCamelCase       :		Optional[int]		=format(SCREAMING_SNAKE_CASE__		,			'08x'     )[-8:]
       _lowerCamelCase       :		List[Any]		=b''
       for i in [3, 2, 1, 0]:
              little_endian_hex += hex_rep[2 * i : 2 * i + 2].encode('utf-8'     )
       return little_endian_hex




def 	a_      (    SCREAMING_SNAKE_CASE__					:      bytes     ):
       '''simple docstring'''





       _lowerCamelCase       :		Dict		=b''
       for char in message:
              bit_string += format(SCREAMING_SNAKE_CASE__		,			'08b'     ).encode('utf-8'     )
       _lowerCamelCase       :		Dict		=format(len(SCREAMING_SNAKE_CASE__     )		,			'064b'     ).encode('utf-8'     )

       # Pad bit_string to a multiple of 512 chars
       bit_string += b"1"
       while len(SCREAMING_SNAKE_CASE__     ) % 512 != 448:
              bit_string += b"0"
       bit_string += to_little_endian(start_len[32:]     ) + to_little_endian(start_len[:32]     )

       return bit_string




def 	a_      (    SCREAMING_SNAKE_CASE__					:      bytes     ):
       '''simple docstring'''





       if len(SCREAMING_SNAKE_CASE__     ) % 512 != 0:
              raise ValueError('Input must have length that\'s a multiple of 512'     )

       for pos in range(0		,			len(SCREAMING_SNAKE_CASE__     )		,			512     ):
              _lowerCamelCase       :		str		=bit_string[pos : pos + 512]
              _lowerCamelCase       :		Tuple		=[]
              for i in range(0		,			512		,			32     ):
                     block_words.append(int(to_little_endian(block[i : i + 32]     )		,			2     )     )
              yield block_words




def 	a_      (    SCREAMING_SNAKE_CASE__					:      int     ):
       '''simple docstring'''





       if i < 0:
              raise ValueError('Input must be non-negative'     )

       _lowerCamelCase       :		List[str]		=format(SCREAMING_SNAKE_CASE__		,			'032b'     )
       _lowerCamelCase       :		List[str]		=''
       for c in i_str:
              new_str += "1" if c == "0" else "0"
       return int(SCREAMING_SNAKE_CASE__		,			2     )




def 	a_      (    SCREAMING_SNAKE_CASE__					:      int		,			SCREAMING_SNAKE_CASE__					:      int     ):
       '''simple docstring'''





       return (a + b) % 2**32




def 	a_      (    SCREAMING_SNAKE_CASE__					:      int		,			SCREAMING_SNAKE_CASE__					:      int     ):
       '''simple docstring'''





       if i < 0:
              raise ValueError('Input must be non-negative'     )
       if shift < 0:
              raise ValueError('Shift must be non-negative'     )
       return ((i << shift) ^ (i >> (32 - shift))) % 2**32




def 	a_      (    SCREAMING_SNAKE_CASE__					:      bytes     ):
       '''simple docstring'''





       _lowerCamelCase       :		int		=preprocess(SCREAMING_SNAKE_CASE__     )

       _lowerCamelCase       :		Dict		=[int(2**32 * abs(sin(i + 1     )     )     ) for i in range(64     )]

       # Starting states
       _lowerCamelCase       :		str		=0X67_45_23_01
       _lowerCamelCase       :		Union[str, Any]		=0Xef_cd_ab_89
       _lowerCamelCase       :		List[str]		=0X98_ba_dc_fe
       _lowerCamelCase       :		int		=0X10_32_54_76

       _lowerCamelCase       :		Optional[int]		=[
           7,
           12,
           17,
           22,
           7,
           12,
           17,
           22,
           7,
           12,
           17,
           22,
           7,
           12,
           17,
           22,
           5,
           9,
           14,
           20,
           5,
           9,
           14,
           20,
           5,
           9,
           14,
           20,
           5,
           9,
           14,
           20,
           4,
           11,
           16,
           23,
           4,
           11,
           16,
           23,
           4,
           11,
           16,
           23,
           4,
           11,
           16,
           23,
           6,
           10,
           15,
           21,
           6,
           10,
           15,
           21,
           6,
           10,
           15,
           21,
           6,
           10,
           15,
           21,
       ]

       # Process bit string in chunks, each with 16 32-char words
       for block_words in get_block_words(SCREAMING_SNAKE_CASE__     ):
              _lowerCamelCase       :		Union[str, Any]		=aa
              _lowerCamelCase       :		List[Any]		=ba
              _lowerCamelCase       :		Dict		=ca
              _lowerCamelCase       :		List[Any]		=da

              # Hash current chunk
              for i in range(64     ):
                     if i <= 15:
                            # f = (b & c) | (not_32(b) & d)     # Alternate definition for f
                            _lowerCamelCase       :		Optional[Any]		=d ^ (b & (c ^ d))
                            _lowerCamelCase       :		Dict		=i
                     elif i <= 31:
                            # f = (d & b) | (not_32(d) & c)     # Alternate definition for f
                            _lowerCamelCase       :		Optional[int]		=c ^ (d & (b ^ c))
                            _lowerCamelCase       :		List[str]		=(5 * i + 1) % 16
                     elif i <= 47:
                            _lowerCamelCase       :		str		=b ^ c ^ d
                            _lowerCamelCase       :		int		=(3 * i + 5) % 16
                     else:
                            _lowerCamelCase       :		Optional[Any]		=c ^ (b | not_aa(SCREAMING_SNAKE_CASE__     ))
                            _lowerCamelCase       :		Dict		=(7 * i) % 16
                     _lowerCamelCase       :		Any		=(f + a + added_consts[i] + block_words[g]) % 2**32
                     _lowerCamelCase       :		str		=d
                     _lowerCamelCase       :		Any		=c
                     _lowerCamelCase       :		Union[str, Any]		=b
                     _lowerCamelCase       :		Dict		=sum_aa(SCREAMING_SNAKE_CASE__		,			left_rotate_aa(SCREAMING_SNAKE_CASE__		,			shift_amounts[i]     )     )

              # Add hashed chunk to running total
              _lowerCamelCase       :		Optional[Any]		=sum_aa(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
              _lowerCamelCase       :		List[str]		=sum_aa(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
              _lowerCamelCase       :		Optional[int]		=sum_aa(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
              _lowerCamelCase       :		List[str]		=sum_aa(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )

       _lowerCamelCase       :		List[Any]		=reformat_hex(SCREAMING_SNAKE_CASE__     ) + reformat_hex(SCREAMING_SNAKE_CASE__     ) + reformat_hex(SCREAMING_SNAKE_CASE__     ) + reformat_hex(SCREAMING_SNAKE_CASE__     )
       return digest


if __name__ == "__main__":
 import doctest

 doctest.testmod()






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






      def        lowerCamelCase       (					self						:     List[str] )					->						str:
             """simple docstring"""




             if self.delimiter is not None:
                    _lowerCamelCase       :		Union[str, Any]		=self.delimiter
             if self.column_names is not None:
                    _lowerCamelCase       :		Dict		=self.column_names






      @property
      def        lowerCamelCase       (					self						:     int )					->						int:
             """simple docstring"""




             _lowerCamelCase       :		Any		={
                 '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()			,   lowercase_ ):
                           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 A  (   datasets.ArrowBasedBuilder     ):
      UpperCamelCase__							:  List[str]      =CsvConfig






      def        lowerCamelCase       (					self						:     Any )					->						Tuple:
             """simple docstring"""




             return datasets.DatasetInfo(features=self.config.features )






      def        lowerCamelCase       (					self						:     Tuple			,   lowercase_						:     Any )					->						List[Any]:
             """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       :		int		=dl_manager.download_and_extract(self.config.data_files )
             if isinstance(lowercase_			,   (str, list, tuple) ):
                    _lowerCamelCase       :		List[Any]		=data_files
                    if isinstance(lowercase_			,   lowercase_ ):
                           _lowerCamelCase       :		Union[str, Any]		=[files]
                    _lowerCamelCase       :		Union[str, Any]		=[dl_manager.iter_files(lowercase_ ) for file in files]
                    return [datasets.SplitGenerator(name=datasets.Split.TRAIN			,   gen_kwargs={'files': files} )]
             _lowerCamelCase       :		Optional[int]		=[]
             for split_name, files in data_files.items():
                    if isinstance(lowercase_			,   lowercase_ ):
                           _lowerCamelCase       :		Dict		=[files]
                    _lowerCamelCase       :		Optional[int]		=[dl_manager.iter_files(lowercase_ ) for file in files]
                    splits.append(datasets.SplitGenerator(name=lowercase_			,   gen_kwargs={'files': files} ) )
             return splits






      def        lowerCamelCase       (					self						:     int			,   lowercase_						:     pa.Table )					->						pa.Table:
             """simple docstring"""




             if self.config.features is not None:
                    _lowerCamelCase       :		List[str]		=self.config.features.arrow_schema
                    if all(not require_storage_cast(lowercase_ ) for feature in self.config.features.values() ):
                           # cheaper cast
                           _lowerCamelCase       :		Optional[int]		=pa.Table.from_arrays([pa_table[field.name] for field in schema]			,   schema=lowercase_ )
                    else:
                           # more expensive cast; allows str <-> int/float or str to Audio for example
                           _lowerCamelCase       :		List[Any]		=table_cast(lowercase_			,   lowercase_ )
             return pa_table






      def        lowerCamelCase       (					self						:     Optional[Any]			,   lowercase_						:     List[Any] )					->						Any:
             """simple docstring"""




             _lowerCamelCase       :		str		=self.config.features.arrow_schema if self.config.features else None
             # dtype allows reading an int column as str
             _lowerCamelCase       :		Union[str, Any]		=(
                 {
                     name: dtype.to_pandas_dtype() if not require_storage_cast(lowercase_ ) 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(lowercase_ ) ):
                    _lowerCamelCase       :		Union[str, Any]		=pd.read_csv(lowercase_			,   iterator=lowercase_			,   dtype=lowercase_			,   **self.config.pd_read_csv_kwargs )
                    try:
                           for batch_idx, df in enumerate(lowercase_ ):
                                  _lowerCamelCase       :		Tuple		=pa.Table.from_pandas(lowercase_ )
                                  # 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(lowercase_ )
                    except ValueError as e:
                           logger.error(F'''Failed to read file \'{file}\' with error {type(lowercase_ )}: {e}''' )
                           raise


