




import sys
from dataclasses import dataclass
from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, 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


if TYPE_CHECKING:
							import sqlitea

							import sqlalchemy


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


@dataclass
class 							__SCREAMING_SNAKE_CASE				(						datasets.BuilderConfig    ):
					_lowerCamelCase						    =					None
					_lowerCamelCase						    =					None
					_lowerCamelCase						    =					None
					_lowerCamelCase						    =					True
					_lowerCamelCase						    =					None
					_lowerCamelCase						    =					None
					_lowerCamelCase						    =					None
					_lowerCamelCase						    =					1_00_00
					_lowerCamelCase						    =					None

					def       lowercase_				(							self   ):







						'''simple docstring'''




						if self.sql is None:
							raise ValueError('sql must be specified'   )
						if self.con is None:
							raise ValueError('con must be specified'   )

					def       lowercase_				(							self					,			__lowercase					,			__lowercase = None					,			):







						'''simple docstring'''




						lowerCamelCase_				:						Dict				  =				config_kwargs.copy()
						# We need to stringify the Selectable object to make its hash deterministic

						# The process of stringifying is explained here: http://docs.sqlalchemy.org/en/latest/faq/sqlexpressions.html
						lowerCamelCase_				:						Optional[Any]				  =				config_kwargs['sql']
						if not isinstance(lowercase_					,			lowercase_   ):
							if datasets.config.SQLALCHEMY_AVAILABLE and "sqlalchemy" in sys.modules:
								import sqlalchemy

								if isinstance(lowercase_					,			sqlalchemy.sql.Selectable   ):
									lowerCamelCase_				:						List[str]				  =				sqlalchemy.create_engine(config_kwargs['con'].split('://'   )[0] + '://'   )
									lowerCamelCase_				:						Union[str, Any]				  =				str(sql.compile(dialect=engine.dialect   )   )
									lowerCamelCase_				:						Any				  =				sql_str
								else:
									raise TypeError(
									    f"Supported types for \'sql\' are string and sqlalchemy.sql.Selectable but got {type(lowercase_   )}: {sql}"   )
							else:
								raise TypeError(
								    f"Supported types for \'sql\' are string and sqlalchemy.sql.Selectable but got {type(lowercase_   )}: {sql}"   )
						lowerCamelCase_				:						Optional[Any]				  =				config_kwargs['con']
						if not isinstance(lowercase_					,			lowercase_   ):
							lowerCamelCase_				:						Union[str, Any]				  =				id(lowercase_   )
							logger.info(
							    f"SQL connection \'con\' of type {type(lowercase_   )} couldn\'t be hashed properly. To enable hashing, specify \'con\' as URI string instead."   )

						return super().create_config_id(lowercase_					,			custom_features=lowercase_   )





					@property
					def       lowercase_				(							self   ):







						'''simple docstring'''




						lowerCamelCase_				:						List[Any]				  =				{
						    'index_col': self.index_col,
						    'columns': self.columns,
						    'params': self.params,
						    'coerce_float': self.coerce_float,
						    'parse_dates': self.parse_dates,
						}
						return pd_read_sql_kwargs


class 							__SCREAMING_SNAKE_CASE				(						datasets.ArrowBasedBuilder    ):
					_lowerCamelCase						    =					SqlConfig

					def       lowercase_				(							self   ):







						'''simple docstring'''




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

					def       lowercase_				(							self					,			__lowercase   ):







						'''simple docstring'''




						return [datasets.SplitGenerator(name=datasets.Split.TRAIN					,			gen_kwargs={}   )]

					def       lowercase_				(							self					,			__lowercase   ):







						'''simple docstring'''




						if self.config.features is not None:
							lowerCamelCase_				:						Optional[int]				  =				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_				:						Optional[int]				  =				table_cast(lowercase_					,			lowercase_   )
						return pa_table





					def       lowercase_				(							self   ):







						'''simple docstring'''




						lowerCamelCase_				:						List[str]				  =				self.config.chunksize
						lowerCamelCase_				:						Union[str, Any]				  =				pd.read_sql(
						    self.config.sql					,			self.config.con					,			chunksize=lowercase_					,			**self.config.pd_read_sql_kwargs   )
						lowerCamelCase_				:						Dict				  =				[sql_reader] if chunksize is None else sql_reader
						for chunk_idx, df in enumerate(lowercase_   ):
							lowerCamelCase_				:						Any				  =				pa.Table.from_pandas(lowercase_   )
							yield chunk_idx, self._cast_table(lowercase_   )



import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


lowercase_									=    logging.get_logger(__name__)


class 					A		(				_UpperCAmelCase					):







    """simple docstring"""





    def __init__( self					:			str,*lowercase_					:			List[Any],**lowercase_					:			Dict						)->       None:





        '''simple docstring'''







        warnings.warn(
            'The class MobileNetV1FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
            ' Please use MobileNetV1ImageProcessor instead.',lowercase_,)
        super().__init__(*lowercase_,**lowercase_						)

