






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


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



@dataclass
class 							_A (    datasets.BuilderConfig							):
    """simple docstring"""

    lowerCamelCase  :       Union[str, "sqlalchemy.sql.Selectable"]   =   None
    lowerCamelCase  :       Union[str, "sqlalchemy.engine.Connection", "sqlalchemy.engine.Engine", "sqlite3.Connection"]   =   None
    lowerCamelCase  :       Optional[Union[str, List[str]]]   =   None
    lowerCamelCase  :       bool   =   True
    lowerCamelCase  :       Optional[Union[List, Tuple, Dict]]   =   None
    lowerCamelCase  :       Optional[Union[List, Dict]]   =   None
    lowerCamelCase  :       Optional[List[str]]   =   None
    lowerCamelCase  :       Optional[int]   =   10_000
    lowerCamelCase  :       Optional[datasets.Features]   =   None



    def _a       (							self			:    List[str]			)			->       str:
           if self.sql is None:
                  raise ValueError("""sql must be specified"""			)
           if self.con is None:
                  raise ValueError("""con must be specified"""			)



    def _a       (							self			:    Union[str, Any]   ,    __SCREAMING_SNAKE_CASE			:    dict   ,    __SCREAMING_SNAKE_CASE			:    Optional[datasets.Features] = None   ,    )			->       str:
           __UpperCAmelCase    							=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
           __UpperCAmelCase    							=config_kwargs["""sql"""]
           if not isinstance(__SCREAMING_SNAKE_CASE   ,    __SCREAMING_SNAKE_CASE			):
                  if datasets.config.SQLALCHEMY_AVAILABLE and "sqlalchemy" in sys.modules:
                         import sqlalchemy

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

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



    @property
    def _a       (							self			:    Optional[int]			)			->       Union[str, Any]:
           __UpperCAmelCase    							={
               """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							):
    """simple docstring"""

    lowerCamelCase  :       Optional[int]   =   SqlConfig



    def _a       (							self			:    int			)			->       int:
           return datasets.DatasetInfo(features=self.config.features			)



    def _a       (							self			:    Optional[Any]   ,    __SCREAMING_SNAKE_CASE			:    Any			)			->       Tuple:
           return [datasets.SplitGenerator(name=datasets.Split.TRAIN   ,    gen_kwargs={}			)]



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



    def _a       (							self			:    str			)			->       List[str]:
           __UpperCAmelCase    							=self.config.chunksize
           __UpperCAmelCase    							=pd.read_sql(
               self.config.sql   ,    self.config.con   ,    chunksize=__SCREAMING_SNAKE_CASE   ,    **self.config.pd_read_sql_kwargs			)
           __UpperCAmelCase    							=[sql_reader] if chunksize is None else sql_reader
           for chunk_idx, df in enumerate(__SCREAMING_SNAKE_CASE			):
                  __UpperCAmelCase    							=pa.Table.from_pandas(__SCREAMING_SNAKE_CASE			)
                  yield chunk_idx, self._cast_table(__SCREAMING_SNAKE_CASE			)












from __future__ import annotations

__A  							=  [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]



class 							_A :
    """simple docstring"""

    def __init__(							self			:    List[str]   ,    __SCREAMING_SNAKE_CASE			:    int			)			->       None:
           __UpperCAmelCase    							=-1
           __UpperCAmelCase    							=-1
           __UpperCAmelCase    							=[-1] * length
           __UpperCAmelCase    							=None
           __UpperCAmelCase    							=None



    def __repr__(							self			:    Optional[int]			)			->       str:
           return f'''Node(min_value={self.minn} max_value={self.maxx})'''







def 			lowercase__  (				A_:	list[int]		)  ->							Node | None:







       """simple docstring"""






       __UpperCAmelCase    							=Node(len(A_		)		)
       __UpperCAmelCase							,   __UpperCAmelCase    							=min(A_		), max(A_		)
       # Leaf node case where the node contains only one unique value
       if root.minn == root.maxx:
              return root
       __UpperCAmelCase    							=(root.minn + root.maxx) // 2

       __UpperCAmelCase    							=[]
       __UpperCAmelCase    							=[]

       for index, num in enumerate(A_		):
              if num <= pivot:
                     left_arr.append(A_		)
              else:
                     right_arr.append(A_		)
              __UpperCAmelCase    							=len(A_		)
       __UpperCAmelCase    							=build_tree(A_		)
       __UpperCAmelCase    							=build_tree(A_		)
       return root







def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int		)  ->							int:







       """simple docstring"""






       if index < 0 or node is None:
              return 0
       # Leaf node cases
       if node.minn == node.maxx:
              return index + 1 if node.minn == num else 0
       __UpperCAmelCase    							=(node.minn + node.maxx) // 2
       if num <= pivot:
              # go the left subtree and map index to the left subtree
              return rank_till_index(node.left     ,			A_     ,			node.map_left[index] - 1		)
       else:
              # go to the right subtree and map index to the right subtree
              return rank_till_index(node.right     ,			A_     ,			index - node.map_left[index]		)







def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int     ,			A_:	int		)  ->							int:







       """simple docstring"""






       if start > end:
              return 0
       __UpperCAmelCase    							=rank_till_index(A_     ,			A_     ,			A_		)
       __UpperCAmelCase    							=rank_till_index(A_     ,			A_     ,			start - 1		)
       return rank_till_end - rank_before_start







def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int     ,			A_:	int		)  ->							int:







       """simple docstring"""






       if index > (end - start) or start > end or node is None:
              return -1
       # Leaf node case
       if node.minn == node.maxx:
              return node.minn
       # Number of elements in the left subtree in interval [start, end]
       __UpperCAmelCase    							=node.map_left[end] - (
           node.map_left[start - 1] if start else 0
       )
       if num_elements_in_left_tree > index:
              return quantile(
                  node.left     ,			A_     ,			(node.map_left[start - 1] if start else 0)     ,			node.map_left[end] - 1     ,			)
       else:
              return quantile(
                  node.right     ,			index - num_elements_in_left_tree     ,			start - (node.map_left[start - 1] if start else 0)     ,			end - node.map_left[end]     ,			)







def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int     ,			A_:	int     ,			A_:	int		)  ->							int:







       """simple docstring"""






       if (
           start > end
           or node is None
           or start_num > end_num
           or node.minn > end_num
           or node.maxx < start_num
       ):
              return 0
       if start_num <= node.minn and node.maxx <= end_num:
              return end - start + 1
       __UpperCAmelCase    							=range_counting(
           node.left     ,			(node.map_left[start - 1] if start else 0)     ,			node.map_left[end] - 1     ,			A_     ,			A_     ,			)
       __UpperCAmelCase    							=range_counting(
           node.right     ,			start - (node.map_left[start - 1] if start else 0)     ,			end - node.map_left[end]     ,			A_     ,			A_     ,			)
       return left + right


if __name__ == "__main__":
   import doctest

   doctest.testmod()




