

"""simple docstring"""






from __future__ import annotations

import typing
from collections.abc import Iterable

import numpy as np

snake_case_        =       typing.Union[Iterable[float], Iterable[int], np.ndarray]  # noqa: UP007
snake_case_        =       typing.Union[np.floataa, int, float]  # noqa: UP007



def   lowercase_	(    _lowercase       :		Vector							,      _lowercase       :		Vector	):




					'''simple docstring'''






					return np.sqrt(np.sum((np.asarray(_lowercase	) - np.asarray(_lowercase	)) ** 2	)	)



def   lowercase_	(    _lowercase       :		Vector							,      _lowercase       :		Vector	):




					'''simple docstring'''






					return sum((va - va) ** 2 for va, va in zip(_lowercase							,      _lowercase	)	) ** (1 / 2)


if __name__ == "__main__":



	def   lowercase_	(    ):




						'''simple docstring'''






						from timeit import timeit

						print("Without Numpy"	)
						print(
						    timeit(
						        "euclidean_distance_no_np([1, 2, 3], [4, 5, 6])"							,      number=1_00_00							,      globals=globals()							,      )	)
						print("With Numpy"	)
						print(
						    timeit(
						        "euclidean_distance([1, 2, 3], [4, 5, 6])"							,      number=1_00_00							,      globals=globals()							,      )	)




	benchmark()





"""simple docstring"""






import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases



def   lowercase_	(    _lowercase       :		Optional[int]							,      _lowercase       :		int	):




					'''simple docstring'''






					assert isinstance(_lowercase							,      _lowercase	)
					assert dataset.num_rows == 4
					assert dataset.num_columns == 1
					assert dataset.column_names == ["text"]
					for feature, expected_dtype in expected_features.items():
										assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize("keep_in_memory"							,      [False, True]	)
def   lowercase_	(    _lowercase       :		Union[str, Any]							,      _lowercase       :		Optional[int]							,      _lowercase       :		Dict	):




					'''simple docstring'''






					UpperCAmelCase			:   Dict      =				tmp_path / "cache"
					UpperCAmelCase			:   str      =				{"text": "string"}
					with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
										UpperCAmelCase			:   Tuple      =				TextDatasetReader(_lowercase							,      cache_dir=_lowercase							,      keep_in_memory=_lowercase	).read()
					_check_text_dataset(_lowercase							,      _lowercase	)



@pytest.mark.parametrize(
    "features"							,      [
        None,
        {"text": "string"},
        {"text": "int32"},
        {"text": "float32"},
    ]							,      )
def   lowercase_	(    _lowercase       :		Dict							,      _lowercase       :		Union[str, Any]							,      _lowercase       :		Optional[int]	):




					'''simple docstring'''






					UpperCAmelCase			:   int      =				tmp_path / "cache"
					UpperCAmelCase			:   Any      =				{"text": "string"}
					UpperCAmelCase			:   List[str]      =				features.copy() if features else default_expected_features
					UpperCAmelCase			:   Union[str, Any]      =				(
					    Features({feature: Value(_lowercase	) for feature, dtype in features.items()}	) if features is not None else None
					)
					UpperCAmelCase			:   str      =				TextDatasetReader(_lowercase							,      features=_lowercase							,      cache_dir=_lowercase	).read()
					_check_text_dataset(_lowercase							,      _lowercase	)



@pytest.mark.parametrize("split"							,      [None, NamedSplit("train"	), "train", "test"]	)
def   lowercase_	(    _lowercase       :		int							,      _lowercase       :		Tuple							,      _lowercase       :		List[str]	):




					'''simple docstring'''






					UpperCAmelCase			:   str      =				tmp_path / "cache"
					UpperCAmelCase			:   Any      =				{"text": "string"}
					UpperCAmelCase			:   List[Any]      =				TextDatasetReader(_lowercase							,      cache_dir=_lowercase							,      split=_lowercase	).read()
					_check_text_dataset(_lowercase							,      _lowercase	)
					assert dataset.split == split if split else "train"



@pytest.mark.parametrize("path_type"							,      [str, list]	)
def   lowercase_	(    _lowercase       :		Optional[int]							,      _lowercase       :		Any							,      _lowercase       :		Union[str, Any]	):




					'''simple docstring'''






					if issubclass(_lowercase							,      _lowercase	):
										UpperCAmelCase			:   List[str]      =				text_path
					elif issubclass(_lowercase							,      _lowercase	):
										UpperCAmelCase			:   List[Any]      =				[text_path]
					UpperCAmelCase			:   Union[str, Any]      =				tmp_path / "cache"
					UpperCAmelCase			:   List[Any]      =				{"text": "string"}
					UpperCAmelCase			:   Tuple      =				TextDatasetReader(_lowercase							,      cache_dir=_lowercase	).read()
					_check_text_dataset(_lowercase							,      _lowercase	)



def   lowercase_	(    _lowercase       :		Dict							,      _lowercase       :		int							,      _lowercase       :		Optional[Any]=("train",)	):




					'''simple docstring'''






					assert isinstance(_lowercase							,      _lowercase	)
					for split in splits:
										UpperCAmelCase			:   str      =				dataset_dict[split]
										assert dataset.num_rows == 4
										assert dataset.num_columns == 1
										assert dataset.column_names == ["text"]
										for feature, expected_dtype in expected_features.items():
															assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize("keep_in_memory"							,      [False, True]	)
def   lowercase_	(    _lowercase       :		Dict							,      _lowercase       :		str							,      _lowercase       :		Dict	):




					'''simple docstring'''






					UpperCAmelCase			:   str      =				tmp_path / "cache"
					UpperCAmelCase			:   Union[str, Any]      =				{"text": "string"}
					with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
										UpperCAmelCase			:   Tuple      =				TextDatasetReader({"train": text_path}							,      cache_dir=_lowercase							,      keep_in_memory=_lowercase	).read()
					_check_text_datasetdict(_lowercase							,      _lowercase	)



@pytest.mark.parametrize(
    "features"							,      [
        None,
        {"text": "string"},
        {"text": "int32"},
        {"text": "float32"},
    ]							,      )
def   lowercase_	(    _lowercase       :		List[Any]							,      _lowercase       :		Union[str, Any]							,      _lowercase       :		int	):




					'''simple docstring'''






					UpperCAmelCase			:   int      =				tmp_path / "cache"
					# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
					UpperCAmelCase			:   List[str]      =				{"text": "string"}
					UpperCAmelCase			:   str      =				features.copy() if features else default_expected_features
					UpperCAmelCase			:   Optional[int]      =				(
					    Features({feature: Value(_lowercase	) for feature, dtype in features.items()}	) if features is not None else None
					)
					UpperCAmelCase			:   Optional[int]      =				TextDatasetReader({"train": text_path}							,      features=_lowercase							,      cache_dir=_lowercase	).read()
					_check_text_datasetdict(_lowercase							,      _lowercase	)




@pytest.mark.parametrize("split"							,      [None, NamedSplit("train"	), "train", "test"]	)
def   lowercase_	(    _lowercase       :		int							,      _lowercase       :		Tuple							,      _lowercase       :		Optional[Any]	):




					'''simple docstring'''






					if split:
										UpperCAmelCase			:   Optional[Any]      =				{split: text_path}
					else:
										UpperCAmelCase			:   str      =				"train"
										UpperCAmelCase			:   Union[str, Any]      =				{"train": text_path, "test": text_path}
					UpperCAmelCase			:   Any      =				tmp_path / "cache"
					UpperCAmelCase			:   List[Any]      =				{"text": "string"}
					UpperCAmelCase			:   Any      =				TextDatasetReader(_lowercase							,      cache_dir=_lowercase	).read()
					_check_text_datasetdict(_lowercase							,      _lowercase							,      splits=list(path.keys()	)	)
					assert all(dataset[split].split == split for split in path.keys()	)


