


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      snake_case__	(   datasets.BuilderConfig	):
				__lowerCAmelCase		=   None
				__lowerCAmelCase		=   None
				__lowerCAmelCase		=   None
				__lowerCAmelCase		=   True
				__lowerCAmelCase		=   None
				__lowerCAmelCase		=   None
				__lowerCAmelCase		=   None
				__lowerCAmelCase		=   10_000
				__lowerCAmelCase		=   None
				def 			UpperCamelCase_    (	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 			UpperCamelCase_    (	self  ,   _UpperCAmelCase  ,   _UpperCAmelCase = None  ,   ):




										"""simple docstring"""




										__magic_name__					:				Optional[int]				=   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
										__magic_name__					:				Union[str, Any]				=   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   ):
																												__magic_name__					:				List[Any]				=   sqlalchemy.create_engine(config_kwargs['con'].split('://'   )[0] + '://'   )
																												__magic_name__					:				Any				=   str(sql.compile(dialect=engine.dialect   )   )
																												__magic_name__					:				str				=   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}"   )
										__magic_name__					:				List[Any]				=   config_kwargs['con']
										if not isinstance(_UpperCAmelCase  ,   _UpperCAmelCase   ):
																__magic_name__					:				Dict				=   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 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




										__magic_name__					:				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      snake_case__	(   datasets.ArrowBasedBuilder	):
				__lowerCAmelCase		=   SqlConfig
				def 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




										return datasets.DatasetInfo(features=self.config.features   )
				def 			UpperCamelCase_    (	self  ,   _UpperCAmelCase   ):




										"""simple docstring"""




										return [datasets.SplitGenerator(name=datasets.Split.TRAIN  ,   gen_kwargs={}   )]
				def 			UpperCamelCase_    (	self  ,   _UpperCAmelCase   ):




										"""simple docstring"""




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





				def 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




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






from __future__ import annotations

from typing import Any
def 			__SCREAMING_SNAKE_CASE							(					*lowercase__	:list[list[int]]					)							->	list[list[int]]:
						if all(_check_not_integer(lowercase__					) for m in matrix_s					):
												for i in matrix_s[1:]:
																		_verify_matrix_sizes(matrix_s[0]   ,    lowercase__					)
												return [[sum(lowercase__					) for t in zip(*lowercase__					)] for m in zip(*lowercase__					)]
						raise TypeError('Expected a matrix, got int/list instead'					)
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:list[list[int]]   ,    lowercase__	:list[list[int]]					)							->	list[list[int]]:
						if (
						    _check_not_integer(lowercase__					)
						    and _check_not_integer(lowercase__					)
						    and _verify_matrix_sizes(lowercase__   ,    lowercase__					)
						):
												return [[i - j for i, j in zip(*lowercase__					)] for m in zip(lowercase__   ,    lowercase__					)]
						raise TypeError('Expected a matrix, got int/list instead'					)
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:list[list[int]]   ,    lowercase__	:int | float					)							->	list[list[float]]:
						return [[x * n for x in row] for row in matrix]
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:list[list[int]]   ,    lowercase__	:list[list[int]]					)							->	list[list[int]]:
						if _check_not_integer(lowercase__					) and _check_not_integer(lowercase__					):
												__magic_name__		,			__magic_name__					:				str				=   _verify_matrix_sizes(lowercase__   ,    lowercase__					)

						if cols[0] != rows[1]:
												__magic_name__					:				Union[str, Any]				=   (
												    'Cannot multiply matrix of dimensions '
												    f"({rows[0]},{cols[0]}) and ({rows[1]},{cols[1]})"
												)
												raise ValueError(lowercase__					)
						return [
						    [sum(m * n for m, n in zip(lowercase__   ,    lowercase__					)					) for j in zip(*lowercase__					)] for i in matrix_a
						]
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:int					)							->	list[list[int]]:
						__magic_name__					:				Tuple				=   int(lowercase__					)
						return [[int(row == column					) for column in range(lowercase__					)] for row in range(lowercase__					)]
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:list[list[int]]   ,    lowercase__	:bool = True					)							->	list[list[int]] | map[list[int]]:
						if _check_not_integer(lowercase__					):
												if return_map:
																		return map(lowercase__   ,    zip(*lowercase__					)					)
												else:
																		return list(map(lowercase__   ,    zip(*lowercase__					)					)					)
						raise TypeError('Expected a matrix, got int/list instead'					)
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:list[list[int]]   ,    lowercase__	:int   ,    lowercase__	:int					)							->	list[list[int]]:
						__magic_name__					:				int				=   matrix[:row] + matrix[row + 1 :]
						return [row[:column] + row[column + 1 :] for row in minor]
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:list[list[int]]					)							->	Any:
						if len(lowercase__					) == 1:
												return matrix[0][0]

						return sum(
						    x * determinant(minor(lowercase__   ,    0   ,    lowercase__					)					) * (-1) ** i
						    for i, x in enumerate(matrix[0]					)					)
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:list[list[int]]					)							->	list[list[float]] | None:
						__magic_name__					:				Tuple				=   determinant(lowercase__					)
						if det == 0:
												return None

						__magic_name__					:				Optional[int]				=   [
						    [determinant(minor(lowercase__   ,    lowercase__   ,    lowercase__					)					) for j in range(len(lowercase__					)					)]
						    for i in range(len(lowercase__					)					)
						]

						__magic_name__					:				Optional[Any]				=   [
						    [x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row]					)]
						    for row in range(len(lowercase__					)					)
						]
						__magic_name__					:				Optional[Any]				=   list(transpose(lowercase__					)					)
						return scalar_multiply(lowercase__   ,    1 / det					)
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:list[list[int]]					)							->	bool:
						return not isinstance(lowercase__   ,    lowercase__					) and not isinstance(matrix[0]   ,    lowercase__					)
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:list[list[int]]					)							->	tuple[int, int]:
						return len(lowercase__					), len(matrix[0]					)
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:list[list[int]]   ,    lowercase__	:list[list[int]]					)							->	tuple[tuple[int, int], tuple[int, int]]:
						__magic_name__					:				str				=   _shape(lowercase__					) + _shape(lowercase__					)
						if shape[0] != shape[3] or shape[1] != shape[2]:
												__magic_name__					:				Optional[Any]				=   (
												    'operands could not be broadcast together with shape '
												    f"({shape[0], shape[1]}), ({shape[2], shape[3]})"
												)
												raise ValueError(lowercase__					)
						return (shape[0], shape[2]), (shape[1], shape[3])
def 			__SCREAMING_SNAKE_CASE							(					)							->	None:
						__magic_name__					:				Dict				=   [[1_2, 1_0], [3, 9]]
						__magic_name__					:				Optional[int]				=   [[3, 4], [7, 4]]
						__magic_name__					:				Optional[Any]				=   [[1_1, 1_2, 1_3, 1_4], [2_1, 2_2, 2_3, 2_4], [3_1, 3_2, 3_3, 3_4], [4_1, 4_2, 4_3, 4_4]]
						__magic_name__					:				List[str]				=   [[3, 0, 2], [2, 0, -2], [0, 1, 1]]
						print(f"Add Operation, {add(lowercase__   ,    lowercase__					) = } \n"					)
						print(
						    f"Multiply Operation, {multiply(lowercase__   ,    lowercase__					) = } \n"   ,    )
						print(f"Identity: {identity(5					)}\n"					)
						print(f"Minor of {matrix_c} = {minor(lowercase__   ,    1   ,    2					)} \n"					)
						print(f"Determinant of {matrix_b} = {determinant(lowercase__					)} \n"					)
						print(f"Inverse of {matrix_d} = {inverse(lowercase__					)}\n"					)


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			main()


