



"""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        __A       (	datasets.BuilderConfig    ):







		'''simple docstring'''





		lowerCAmelCase			:					str   	=				","
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					Optional[Union[int, List[int], str]]   	=				"infer"
		lowerCAmelCase			:					Optional[List[str]]   	=				None
		lowerCAmelCase			:					Optional[List[str]]   	=				None
		lowerCAmelCase			:					Optional[Union[int, str, List[int], List[str]]]   	=				None
		lowerCAmelCase			:					Optional[Union[List[int], List[str]]]   	=				None
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					bool   	=				True
		lowerCAmelCase			:					Optional[Literal["c", "python", "pyarrow"]]   	=				None
		lowerCAmelCase			:					Dict[Union[int, str], Callable[[Any], Any]]   	=				None
		lowerCAmelCase			:					Optional[list]   	=				None
		lowerCAmelCase			:					Optional[list]   	=				None
		lowerCAmelCase			:					bool   	=				False
		lowerCAmelCase			:					Optional[Union[int, List[int]]]   	=				None
		lowerCAmelCase			:					Optional[int]   	=				None
		lowerCAmelCase			:					Optional[Union[str, List[str]]]   	=				None
		lowerCAmelCase			:					bool   	=				True
		lowerCAmelCase			:					bool   	=				True
		lowerCAmelCase			:					bool   	=				False
		lowerCAmelCase			:					bool   	=				True
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					str   	=				"."
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					str   	=				'"'
		lowerCAmelCase			:					int   	=				0
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					bool   	=				True
		lowerCAmelCase			:					bool   	=				True
		lowerCAmelCase			:					int   	=				0
		lowerCAmelCase			:					bool   	=				True
		lowerCAmelCase			:					bool   	=				False
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					int   	=				1_0_0_0_0
		lowerCAmelCase			:					Optional[datasets.Features]   	=				None
		lowerCAmelCase			:					Optional[str]   	=				"strict"
		lowerCAmelCase			:					Literal["error", "warn", "skip"]   	=				"error"
		lowerCAmelCase			:					Optional[str]   	=				None







		def 					UpperCAmelCase    (	self						:  Optional[int]						)					->		Any:






				"""simple docstring"""



				if self.delimiter is not None:
						lowercase__   :    List[Any]				=			self.delimiter
				if self.column_names is not None:
						lowercase__   :    Optional[int]				=			self.column_names







		@property
		def 					UpperCAmelCase    (	self						:  str						)					->		Union[str, Any]:






				"""simple docstring"""



				lowercase__   :    Dict				=			{
				    '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()			,_snake_case						):
								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    ):







		'''simple docstring'''





		lowerCAmelCase			:					Optional[Any]   	=				CsvConfig







		def 					UpperCAmelCase    (	self						:  Union[str, Any]						)					->		int:






				"""simple docstring"""



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







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







		def 					UpperCAmelCase    (	self						:  Any			,_snake_case						:  int						)					->		str:






				"""simple docstring"""



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







		def 					UpperCAmelCase    (	self						:  List[str]			,_snake_case						:  List[str]						)					->		Dict:






				"""simple docstring"""



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



def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    str = "The quick brown fox jumps over the lazy dog"	,     ):



     '''simple docstring'''





     lowercase__    :   str      =       set()

     # Replace all the whitespace in our sentence
     lowercase__    :   Tuple      =       input_str.replace(' '	,     ''			)
     for alpha in input_str:
          if "a" <= alpha.lower() <= "z":
               frequency.add(alpha.lower()			)
     return len(SCREAMING_SNAKE_CASE_			) == 26

def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    str = "The quick brown fox jumps over the lazy dog"	,     ):



     '''simple docstring'''





     lowercase__    :   Dict      =       [False] * 26
     for char in input_str:
          if char.islower():
               lowercase__    :   List[Any]      =       True
          elif char.isupper():
               lowercase__    :   Optional[Any]      =       True
     return all(SCREAMING_SNAKE_CASE_			)

def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    str = "The quick brown fox jumps over the lazy dog"	,     ):



     '''simple docstring'''





     return len({char for char in input_str.lower() if char.isalpha()}			) == 26

def 	snake_case__			(    ):



     '''simple docstring'''





     from timeit import timeit

     lowercase__    :   Union[str, Any]      =       'from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest'
     print(timeit('is_pangram()'	,     setup=SCREAMING_SNAKE_CASE_			)			)
     print(timeit('is_pangram_faster()'	,     setup=SCREAMING_SNAKE_CASE_			)			)
     print(timeit('is_pangram_fastest()'	,     setup=SCREAMING_SNAKE_CASE_			)			)
     # 5.348480500048026, 2.6477354579837993, 1.8470395830227062
     # 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       benchmark()

