





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

__lowerCAmelCase :Optional[int]     =    ['names', 'prefix']
__lowerCAmelCase :Union[str, Any]     =    ['warn_bad_lines', 'error_bad_lines', 'mangle_dupe_cols']
__lowerCAmelCase :List[Any]     =    ['encoding_errors', 'on_bad_lines']
__lowerCAmelCase :Any     =    ['date_format']






@dataclass
class        _a(    datasets.BuilderConfig    ):
		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   				=		10000
		lowerCamelCase__     :Optional[datasets.Features]   				=		None
		lowerCamelCase__     :Optional[str]   				=		"strict"
		lowerCamelCase__     :Literal["error", "warn", "skip"]   				=		"error"
		lowerCamelCase__     :Optional[str]   				=		None







		def        lowercase       (    self				)      ->      Tuple:


							'''simple docstring'''

							if self.delimiter is not None:
												_snake_case       :					Tuple				       =   self.delimiter
							if self.column_names is not None:
												_snake_case       :					int				       =   self.column_names







		@property
		def        lowercase       (    self				)      ->      str:


							'''simple docstring'''

							_snake_case       :					int				       =   {
							    "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    ):
		lowerCamelCase__     :Optional[int]   				=		CsvConfig







		def        lowercase       (    self				)      ->      str:


							'''simple docstring'''

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







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







		def        lowercase       (    self ,						__snake_case				)      ->      pa.Table:


							'''simple docstring'''

							if self.config.features is not None:
												_snake_case       :					Dict				       =   self.config.features.arrow_schema
												if all(not require_storage_cast(__snake_case				) for feature in self.config.features.values()				):
																	# cheaper cast
																	_snake_case       :					List[Any]				       =   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
																	_snake_case       :					Optional[Any]				       =   table_cast(__snake_case ,						__snake_case				)
							return pa_table







		def        lowercase       (    self ,						__snake_case				)      ->      Any:


							'''simple docstring'''

							_snake_case       :					Tuple				       =   self.config.features.arrow_schema if self.config.features else None
							# dtype allows reading an int column as str
							_snake_case       :					List[str]				       =   (
							    {
							        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				)				):
												_snake_case       :					Union[str, Any]				       =   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				):
																						_snake_case       :					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






import re







def    A				(							UpperCAmelCase				):
					_snake_case       :					Any				       =   re.compile(R"^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$"				)
					if match := re.search(UpperCAmelCase  ,  UpperCAmelCase				):
										return match.string == phone
					return False


if __name__ == "__main__":
							print(indian_phone_validator('+918827897895'))