

'''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


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


@dataclass
class      a__						(							datasets.BuilderConfig						):
   _SCREAMING_SNAKE_CASE					:  Union[str, "sqlalchemy.sql.Selectable"]			 =							None
   _SCREAMING_SNAKE_CASE					:  Union[str, "sqlalchemy.engine.Connection", "sqlalchemy.engine.Engine", "sqlite3.Connection"]			 =							None
   _SCREAMING_SNAKE_CASE					:  Optional[Union[str, List[str]]]			 =							None
   _SCREAMING_SNAKE_CASE					:  bool			 =							True
   _SCREAMING_SNAKE_CASE					:  Optional[Union[List, Tuple, Dict]]			 =							None
   _SCREAMING_SNAKE_CASE					:  Optional[Union[List, Dict]]			 =							None
   _SCREAMING_SNAKE_CASE					:  Optional[List[str]]			 =							None
   _SCREAMING_SNAKE_CASE					:  Optional[int]			 =							1_0000
   _SCREAMING_SNAKE_CASE					:  Optional[datasets.Features]			 =							None


   def 		_lowerCamelCase     (				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 		_lowerCamelCase     (				self    ,       _UpperCamelCase    ,       _UpperCamelCase = None    ,       ):





      """simple docstring"""





      _lowercase    :   Tuple      =     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    :   Tuple      =     config_kwargs["sql"]
      if not isinstance(_UpperCamelCase    ,       _UpperCamelCase						):
         if datasets.config.SQLALCHEMY_AVAILABLE and "sqlalchemy" in sys.modules:
            import sqlalchemy

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

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






   @property
   def 		_lowerCamelCase     (				self						):





      """simple docstring"""





      _lowercase    :   str      =     {
          "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      a__						(							datasets.ArrowBasedBuilder						):
   _SCREAMING_SNAKE_CASE					:  Optional[int]			 =							SqlConfig


   def 		_lowerCamelCase     (				self						):





      """simple docstring"""





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


   def 		_lowerCamelCase     (				self    ,       _UpperCamelCase						):





      """simple docstring"""





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


   def 		_lowerCamelCase     (				self    ,       _UpperCamelCase						):





      """simple docstring"""





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






   def 		_lowerCamelCase     (				self						):





      """simple docstring"""





      _lowercase    :   int      =     self.config.chunksize
      _lowercase    :   int      =     pd.read_sql(
          self.config.sql    ,       self.config.con    ,       chunksize=_UpperCamelCase    ,       **self.config.pd_read_sql_kwargs						)
      _lowercase    :   Optional[int]      =     [sql_reader] if chunksize is None else sql_reader
      for chunk_idx, df in enumerate(_UpperCamelCase						):
         _lowercase    :   Any      =     pa.Table.from_pandas(_UpperCamelCase						)
         yield chunk_idx, self._cast_table(_UpperCamelCase						)









'''simple docstring'''
def       _A	(			snake_case  )    ->			int:

   # validate:
   if not isinstance(snake_case	,							snake_case  ) or not all(
       isinstance(snake_case	,							snake_case  ) and item >= 0 for item in citations  ):
      raise ValueError("The citations should be a list of non negative integers."  )

   citations.sort()
   _lowercase    :   Tuple      =     len(snake_case  )

   for i in range(snake_case  ):
      if citations[len_citations - 1 - i] <= i:
         return i

   return len_citations


if __name__ == "__main__":
    import doctest

    doctest.testmod()






