"""simple docstring"""


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       :    List[str]         =		datasets.utils.logging.get_logger(__name__)
@dataclass
class   UpperCAmelCase_	(				datasets.BuilderConfig   ):
    snake_case_											=      None
    snake_case_											=      None
    snake_case_											=      None
    snake_case_											=      True
    snake_case_											=      None
    snake_case_											=      None
    snake_case_											=      None
    snake_case_											=      1_0000
    snake_case_											=      None
    def 		_lowerCamelCase      (	self			:       List[str]		)						->    Dict:
       if self.sql is None:
          raise ValueError("sql must be specified"		)
       if self.con is None:
          raise ValueError("con must be specified"		)
    def 		_lowerCamelCase      (	self			:       List[str]   ,						_lowercase			:       dict   ,						_lowercase			:       Optional[datasets.Features] = None   ,						)						->    str:
       _lowercase							     =       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
       _lowercase							     =       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		):
                _lowercase							     =       sqlalchemy.create_engine(config_kwargs["con"].split("://"		)[0] + "://"		)
                _lowercase							     =       str(sql.compile(dialect=engine.dialect		)		)
                _lowercase							     =       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}"""		)
       _lowercase							     =       config_kwargs["con"]
       if not isinstance(_lowercase   ,						_lowercase		):
          _lowercase							     =       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 		_lowerCamelCase      (	self			:       Optional[int]		)						->    Tuple:
       _lowercase							     =       {
           "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   UpperCAmelCase_	(				datasets.ArrowBasedBuilder   ):
    snake_case_											=      SqlConfig
    def 		_lowerCamelCase      (	self			:       List[Any]		)						->    str:
       return datasets.DatasetInfo(features=self.config.features		)
    def 		_lowerCamelCase      (	self			:       str   ,						_lowercase			:       Dict		)						->    List[str]:
       return [datasets.SplitGenerator(name=datasets.Split.TRAIN   ,						gen_kwargs={}		)]
    def 		_lowerCamelCase      (	self			:       Union[str, Any]   ,						_lowercase			:       pa.Table		)						->    pa.Table:
       if self.config.features is not None:
          _lowercase							     =       self.config.features.arrow_schema
          if all(not require_storage_cast(_lowercase		) for feature in self.config.features.values()		):
             # cheaper cast
             _lowercase							     =       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
             _lowercase							     =       table_cast(_lowercase   ,						_lowercase		)
       return pa_table




    def 		_lowerCamelCase      (	self			:       Dict		)						->    str:
       _lowercase							     =       self.config.chunksize
       _lowercase							     =       pd.read_sql(
           self.config.sql   ,						self.config.con   ,						chunksize=_lowercase   ,						**self.config.pd_read_sql_kwargs		)
       _lowercase							     =       [sql_reader] if chunksize is None else sql_reader
       for chunk_idx, df in enumerate(_lowercase		):
          _lowercase							     =       pa.Table.from_pandas(_lowercase		)
          yield chunk_idx, self._cast_table(_lowercase		)
"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_convnext import ConvNextImageProcessor


__UpperCamelCase       :    str         =		logging.get_logger(__name__)
class   UpperCAmelCase_	(				lowercase__   ):
    def __init__(	self			:       List[Any]   ,						*_lowercase			:       Optional[Any]   ,						**_lowercase			:       str		)						->    None:
       warnings.warn(
           "The class ConvNextFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
           " Please use ConvNextImageProcessor instead."   ,						_lowercase   ,						)
       super().__init__(*_lowercase   ,						**_lowercase		)