


"""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        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					assert isinstance(lowerCAmelCase_  ,						lowerCAmelCase_       )
					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        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						       =    tmp_path / "cache"
					__SCREAMING_SNAKE_CASE						       =    {"col_1": "string", "col_2": "int64", "col_3": "float64"}
					with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
										__SCREAMING_SNAKE_CASE						       =    SqlDatasetReader(
										    "dataset"  ,						"sqlite:///" + sqlite_path  ,						cache_dir=lowerCAmelCase_  ,						keep_in_memory=lowerCAmelCase_       ).read()
					_check_sql_dataset(lowerCAmelCase_  ,						lowerCAmelCase_       )




@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        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						       =    tmp_path / "cache"
					__SCREAMING_SNAKE_CASE						       =    {"col_1": "string", "col_2": "int64", "col_3": "float64"}
					__SCREAMING_SNAKE_CASE						       =    features.copy() if features else default_expected_features
					__SCREAMING_SNAKE_CASE						       =    (
					    Features({feature: Value(lowerCAmelCase_       ) for feature, dtype in features.items()}       ) if features is not None else None
					)
					__SCREAMING_SNAKE_CASE						       =    SqlDatasetReader("dataset"  ,						"sqlite:///" + sqlite_path  ,						features=lowerCAmelCase_  ,						cache_dir=lowerCAmelCase_       ).read()
					_check_sql_dataset(lowerCAmelCase_  ,						lowerCAmelCase_       )




def        UpperCAmelCase__	(lowerCAmelCase_       ):




					'''simple docstring'''


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




@require_sqlalchemy
def        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						       =    tmp_path / "cache"
					__SCREAMING_SNAKE_CASE						       =    os.path.join(lowerCAmelCase_  ,						"tmp.sql"       )
					__SCREAMING_SNAKE_CASE						       =    SqlDatasetReader("dataset"  ,						"sqlite:///" + sqlite_path  ,						cache_dir=lowerCAmelCase_       ).read()
					SqlDatasetWriter(lowerCAmelCase_  ,						"dataset"  ,						"sqlite:///" + output_sqlite_path  ,						num_proc=1       ).write()

					__SCREAMING_SNAKE_CASE						       =    iter_sql_file(lowerCAmelCase_       )
					__SCREAMING_SNAKE_CASE						       =    iter_sql_file(lowerCAmelCase_       )

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




@require_sqlalchemy
def        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						       =    tmp_path / "cache"
					__SCREAMING_SNAKE_CASE						       =    os.path.join(lowerCAmelCase_  ,						"tmp.sql"       )
					__SCREAMING_SNAKE_CASE						       =    SqlDatasetReader("dataset"  ,						"sqlite:///" + sqlite_path  ,						cache_dir=lowerCAmelCase_       ).read()
					SqlDatasetWriter(lowerCAmelCase_  ,						"dataset"  ,						"sqlite:///" + output_sqlite_path  ,						num_proc=2       ).write()

					__SCREAMING_SNAKE_CASE						       =    iter_sql_file(lowerCAmelCase_       )
					__SCREAMING_SNAKE_CASE						       =    iter_sql_file(lowerCAmelCase_       )

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




@require_sqlalchemy
def        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						       =    tmp_path / "cache"
					__SCREAMING_SNAKE_CASE						       =    os.path.join(lowerCAmelCase_  ,						"tmp.sql"       )
					__SCREAMING_SNAKE_CASE						       =    SqlDatasetReader("dataset"  ,						"sqlite:///" + sqlite_path  ,						cache_dir=lowerCAmelCase_       ).read()
					with pytest.raises(lowerCAmelCase_       ):
										SqlDatasetWriter(lowerCAmelCase_  ,						"dataset"  ,						"sqlite:///" + output_sqlite_path  ,						num_proc=0       ).write()




"""simple docstring"""







from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
		if not (is_transformers_available() and is_torch_available()):
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		from ...utils.dummy_torch_and_transformers_objects import KandinskyPipeline, KandinskyPriorPipeline
else:
		from .pipeline_kandinsky import KandinskyPipeline
		from .pipeline_kandinsky_imgaimg import KandinskyImgaImgPipeline
		from .pipeline_kandinsky_inpaint import KandinskyInpaintPipeline
		from .pipeline_kandinsky_prior import KandinskyPriorPipeline, KandinskyPriorPipelineOutput
		from .text_encoder import MultilingualCLIP
