


'''simple docstring'''


import contextlib
import os
import sqlitea

import pytest

from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy


def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							):




     '''simple docstring'''





     assert isinstance(SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							)
     assert dataset.num_rows == 4
     assert dataset.num_columns == 3
     assert dataset.column_names == ["col_1", "col_2", "col_3"]
     for feature, expected_dtype in expected_features.items():
          assert dataset.features[feature].dtype == expected_dtype


@require_sqlalchemy
@pytest.mark.parametrize("keep_in_memory"       ,					[False, True]							)
def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							):




     '''simple docstring'''





     __A	:       Any      =							tmp_path / "cache"
     __A	:       int      =							{"col_1": "string", "col_2": "int64", "col_3": "float64"}
     with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
          __A	:       Union[str, Any]      =							SqlDatasetReader(
              "dataset"       ,					"sqlite:///" + sqlite_path       ,					cache_dir=SCREAMING_SNAKE_CASE       ,					keep_in_memory=SCREAMING_SNAKE_CASE							).read()
     _check_sql_dataset(SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							)


@require_sqlalchemy
@pytest.mark.parametrize(
    "features"       ,					[
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]       ,					)
def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							):




     '''simple docstring'''





     __A	:       List[str]      =							tmp_path / "cache"
     __A	:       Union[str, Any]      =							{"col_1": "string", "col_2": "int64", "col_3": "float64"}
     __A	:       Optional[Any]      =							features.copy() if features else default_expected_features
     __A	:       Union[str, Any]      =							(
         Features({feature: Value(SCREAMING_SNAKE_CASE							) for feature, dtype in features.items()}							) if features is not None else None
     )
     __A	:       Dict      =							SqlDatasetReader("dataset"       ,					"sqlite:///" + sqlite_path       ,					features=SCREAMING_SNAKE_CASE       ,					cache_dir=SCREAMING_SNAKE_CASE							).read()
     _check_sql_dataset(SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							)


def 		_lowercase (SCREAMING_SNAKE_CASE							):




     '''simple docstring'''





     with contextlib.closing(sqlitea.connect(SCREAMING_SNAKE_CASE							)							) as con:
          __A	:       Any      =							con.cursor()
          cur.execute("SELECT * FROM dataset"							)
          for row in cur:
               yield row


@require_sqlalchemy
def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							):




     '''simple docstring'''





     __A	:       Dict      =							tmp_path / "cache"
     __A	:       Tuple      =							os.path.join(SCREAMING_SNAKE_CASE       ,					"tmp.sql"							)
     __A	:       Optional[Any]      =							SqlDatasetReader("dataset"       ,					"sqlite:///" + sqlite_path       ,					cache_dir=SCREAMING_SNAKE_CASE							).read()
     SqlDatasetWriter(SCREAMING_SNAKE_CASE       ,					"dataset"       ,					"sqlite:///" + output_sqlite_path       ,					num_proc=1							).write()

     __A	:       Optional[Any]      =							iter_sql_file(SCREAMING_SNAKE_CASE							)
     __A	:       Any      =							iter_sql_file(SCREAMING_SNAKE_CASE							)

     for rowa, rowa in zip(SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							):
          assert rowa == rowa


@require_sqlalchemy
def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							):




     '''simple docstring'''





     __A	:       List[Any]      =							tmp_path / "cache"
     __A	:       Optional[Any]      =							os.path.join(SCREAMING_SNAKE_CASE       ,					"tmp.sql"							)
     __A	:       List[str]      =							SqlDatasetReader("dataset"       ,					"sqlite:///" + sqlite_path       ,					cache_dir=SCREAMING_SNAKE_CASE							).read()
     SqlDatasetWriter(SCREAMING_SNAKE_CASE       ,					"dataset"       ,					"sqlite:///" + output_sqlite_path       ,					num_proc=2							).write()

     __A	:       Optional[int]      =							iter_sql_file(SCREAMING_SNAKE_CASE							)
     __A	:       str      =							iter_sql_file(SCREAMING_SNAKE_CASE							)

     for rowa, rowa in zip(SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							):
          assert rowa == rowa






@require_sqlalchemy
def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE							):




     '''simple docstring'''





     __A	:       Optional[int]      =							tmp_path / "cache"
     __A	:       str      =							os.path.join(SCREAMING_SNAKE_CASE       ,					"tmp.sql"							)
     __A	:       int      =							SqlDatasetReader("dataset"       ,					"sqlite:///" + sqlite_path       ,					cache_dir=SCREAMING_SNAKE_CASE							).read()
     with pytest.raises(SCREAMING_SNAKE_CASE							):
          SqlDatasetWriter(SCREAMING_SNAKE_CASE       ,					"dataset"       ,					"sqlite:///" + output_sqlite_path       ,					num_proc=0							).write()





'''simple docstring'''


import unittest

import numpy as np


def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE = None       ,					):




     '''simple docstring'''





     __A	:       List[Any]      =							np.shape(SCREAMING_SNAKE_CASE							)
     __A	:       List[str]      =							np.shape(SCREAMING_SNAKE_CASE							)
     __A	:       Dict      =							np.shape(SCREAMING_SNAKE_CASE							)

     if shape_a[0] != shape_b[0]:
          __A	:       Tuple      =							(
              "Expected the same number of rows for A and B. "
              f"Instead found A of size {shape_a} and B of size {shape_b}"
          )
          raise ValueError(SCREAMING_SNAKE_CASE							)

     if shape_b[1] != shape_c[1]:
          __A	:       Optional[Any]      =							(
              "Expected the same number of columns for B and C. "
              f"Instead found B of size {shape_b} and C of size {shape_c}"
          )
          raise ValueError(SCREAMING_SNAKE_CASE							)

     __A	:       Tuple      =							pseudo_inv
     if a_inv is None:
          try:
               __A	:       Optional[Any]      =							np.linalg.inv(SCREAMING_SNAKE_CASE							)
          except np.linalg.LinAlgError:
               raise ValueError(
                   "Input matrix A is not invertible. Cannot compute Schur complement."							)

     return mat_c - mat_b.T @ a_inv @ mat_b







class 							__magic_name__	(       unittest.TestCase ):

     """simple docstring"""






     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       Any      =							np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]		)
          __A	:       Tuple      =							np.array([[0, 3], [3, 0], [2, 3]]		)
          __A	:       Tuple      =							np.array([[2, 1], [6, 3]]		)

          __A	:       Optional[Any]      =							schur_complement(lowerCamelCase			,     lowerCamelCase			,     lowerCamelCase		)

          __A	:       int      =							np.block([[a, b], [b.T, c]]		)

          __A	:       int      =							np.linalg.det(lowerCamelCase		)
          __A	:       List[str]      =							np.linalg.det(lowerCamelCase		)
          __A	:       Any      =							np.linalg.det(lowerCamelCase		)

          self.assertAlmostEqual(lowerCamelCase			,     det_a * det_s		)


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       Optional[int]      =							np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]		)
          __A	:       List[Any]      =							np.array([[0, 3], [3, 0], [2, 3]]		)
          __A	:       List[str]      =							np.array([[2, 1], [6, 3]]		)

          with self.assertRaises(lowerCamelCase		):
               schur_complement(lowerCamelCase			,     lowerCamelCase			,     lowerCamelCase		)


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       Any      =							np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]		)
          __A	:       Union[str, Any]      =							np.array([[0, 3], [3, 0], [2, 3]]		)
          __A	:       Optional[Any]      =							np.array([[2, 1, 3], [6, 3, 5]]		)

          with self.assertRaises(lowerCamelCase		):
               schur_complement(lowerCamelCase			,     lowerCamelCase			,     lowerCamelCase		)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      unittest.main()

