

'''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


SCREAMING_SNAKE_CASE							:				List[Any]     	=			datasets.utils.logging.get_logger(__name__)

SCREAMING_SNAKE_CASE							:				Tuple     	=			["names", "prefix"]
SCREAMING_SNAKE_CASE							:				List[Any]     	=			["warn_bad_lines", "error_bad_lines", "mangle_dupe_cols"]
SCREAMING_SNAKE_CASE							:				Optional[int]     	=			["encoding_errors", "on_bad_lines"]
SCREAMING_SNAKE_CASE							:				Dict     	=			["date_format"]






@dataclass
class    snake_case     (      datasets.BuilderConfig		):






				"""simple docstring"""
				_a    	=     ","
				_a    	=     None
				_a    	=     "infer"
				_a    	=     None
				_a    	=     None
				_a    	=     None
				_a    	=     None
				_a    	=     None
				_a    	=     True
				_a    	=     None
				_a    	=     None
				_a    	=     None
				_a    	=     None
				_a    	=     False
				_a    	=     None
				_a    	=     None
				_a    	=     None
				_a    	=     True
				_a    	=     True
				_a    	=     False
				_a    	=     True
				_a    	=     None
				_a    	=     "."
				_a    	=     None
				_a    	=     '"'
				_a    	=     0
				_a    	=     None
				_a    	=     None
				_a    	=     None
				_a    	=     None
				_a    	=     True
				_a    	=     True
				_a    	=     0
				_a    	=     True
				_a    	=     False
				_a    	=     None
				_a    	=     1_0000
				_a    	=     None
				_a    	=     "strict"
				_a    	=     "error"
				_a    	=     None



				def   a__					(    self       )     ->							Optional[int]:
											if self.delimiter is not None:
																		SCREAMING_SNAKE_CASE_				=				self.delimiter
											if self.column_names is not None:
																		SCREAMING_SNAKE_CASE_				=				self.column_names





				@property
				def   a__					(    self       )     ->							List[str]:
											SCREAMING_SNAKE_CASE_				=				{
											    '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    snake_case     (      datasets.ArrowBasedBuilder		):






				"""simple docstring"""
				_a    	=     CsvConfig



				def   a__					(    self       )     ->							str:
											return datasets.DatasetInfo(features=self.config.features       )



				def   a__					(    self,     _lowercase       )     ->							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}"""       )
											SCREAMING_SNAKE_CASE_				=				dl_manager.download_and_extract(self.config.data_files       )
											if isinstance(_lowercase,     (str, list, tuple)       ):
																		SCREAMING_SNAKE_CASE_				=				data_files
																		if isinstance(_lowercase,     _lowercase       ):
																									SCREAMING_SNAKE_CASE_				=				[files]
																		SCREAMING_SNAKE_CASE_				=				[dl_manager.iter_files(_lowercase       ) for file in files]
																		return [datasets.SplitGenerator(name=datasets.Split.TRAIN,     gen_kwargs={'files': files}       )]
											SCREAMING_SNAKE_CASE_				=				[]
											for split_name, files in data_files.items():
																		if isinstance(_lowercase,     _lowercase       ):
																									SCREAMING_SNAKE_CASE_				=				[files]
																		SCREAMING_SNAKE_CASE_				=				[dl_manager.iter_files(_lowercase       ) for file in files]
																		splits.append(datasets.SplitGenerator(name=_lowercase,     gen_kwargs={'files': files}       )       )
											return splits



				def   a__					(    self,     _lowercase       )     ->							pa.Table:
											if self.config.features is not None:
																		SCREAMING_SNAKE_CASE_				=				self.config.features.arrow_schema
																		if all(not require_storage_cast(_lowercase       ) for feature in self.config.features.values()       ):
																									# cheaper cast
																									SCREAMING_SNAKE_CASE_				=				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
																									SCREAMING_SNAKE_CASE_				=				table_cast(_lowercase,     _lowercase       )
											return pa_table





				def   a__					(    self,     _lowercase       )     ->							Optional[Any]:
											SCREAMING_SNAKE_CASE_				=				self.config.features.arrow_schema if self.config.features else None
											# dtype allows reading an int column as str
											SCREAMING_SNAKE_CASE_				=				(
											    {
											        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       )       ):
																		SCREAMING_SNAKE_CASE_				=				pd.read_csv(_lowercase,     iterator=_lowercase,     dtype=_lowercase,     **self.config.pd_read_csv_kwargs       )
																		try:
																									for batch_idx, df in enumerate(_lowercase       ):
																																SCREAMING_SNAKE_CASE_				=				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








'''simple docstring'''

def 							_UpperCamelCase				(   lowerCAmelCase__:					str   )      -> bool:
							return credit_card_number.startswith(('34', '35', '37', '4', '5', '6')   )




def 							_UpperCamelCase				(   lowerCAmelCase__:					str   )      -> bool:
							SCREAMING_SNAKE_CASE_				=				credit_card_number
							SCREAMING_SNAKE_CASE_				=				0
							SCREAMING_SNAKE_CASE_				=				len(lowerCAmelCase__   ) - 2
							for i in range(lowerCAmelCase__		,-1		,-2   ):
														#  double the value of every second digit
														SCREAMING_SNAKE_CASE_				=				int(cc_number[i]   )
														digit *= 2
														# If doubling of a number results in a two digit number
														# i.e greater than 9(e.g., 6 × 2 = 12),
														# then add the digits of the product (e.g., 12: 1 + 2 = 3, 15: 1 + 5 = 6),
														# to get a single digit number.
														if digit > 9:
																					digit %= 10
																					digit += 1
														SCREAMING_SNAKE_CASE_				=				cc_number[:i] + str(lowerCAmelCase__   ) + cc_number[i + 1 :]
														total += digit

							# Sum up the remaining digits
							for i in range(len(lowerCAmelCase__   ) - 1		,-1		,-2   ):
														total += int(cc_number[i]   )

							return total % 10 == 0




def 							_UpperCamelCase				(   lowerCAmelCase__:					str   )      -> bool:
							SCREAMING_SNAKE_CASE_				=				F"""{credit_card_number} is an invalid credit card number because"""
							if not credit_card_number.isdigit():
														print(F"""{error_message} it has nonnumerical characters."""   )
														return False

							if not 13 <= len(lowerCAmelCase__   ) <= 16:
														print(F"""{error_message} of its length."""   )
														return False

							if not validate_initial_digits(lowerCAmelCase__   ):
														print(F"""{error_message} of its first two digits."""   )
														return False

							if not luhn_validation(lowerCAmelCase__   ):
														print(F"""{error_message} it fails the Luhn check."""   )
														return False

							print(F"""{credit_card_number} is a valid credit card number."""   )
							return True


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							validate_credit_card_number("4111111111111111")
							validate_credit_card_number("32323")





