



'''simple docstring'''






import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pytest

from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex

from .utils import require_elasticsearch, require_faiss


UpperCamelCase__:     Dict										=    pytest.mark.integration

@require_faiss
class        SCREAMING_SNAKE_CASE(							A__    ):







	"""simple docstring"""






	def   A			(		self    :  Tuple	)    ->	Any:
								UpperCAmelCase				: Optional[int]											=	Dataset.from_dict({'''filename''': ['''my_name-train''' + '''_''' + str(__snake_case	) for x in np.arange(30	).tolist()]}	)
								return dset







	def   A			(		self    :  str	)    ->	Any:
								import faiss

								UpperCAmelCase				: Dataset											=	self._create_dummy_dataset()
								UpperCAmelCase				: int											=	dset.map(
								    lambda __snake_case	,    __snake_case	: {"vecs": i * np.ones(5	,    dtype=np.floataa	)}	,    with_indices=__snake_case	,    keep_in_memory=__snake_case	)
								UpperCAmelCase				: List[str]											=	dset.add_faiss_index('''vecs'''	,    batch_size=100	,    metric_type=faiss.METRIC_INNER_PRODUCT	)
								UpperCAmelCase							,	UpperCAmelCase				: Optional[Any]											=	dset.get_nearest_examples('''vecs'''	,    np.ones(5	,    dtype=np.floataa	)	)
								self.assertEqual(examples['''filename'''][0]	,    '''my_name-train_29'''	)
								dset.drop_index('''vecs'''	)







	def   A			(		self    :  str	)    ->	Union[str, Any]:
								import faiss

								UpperCAmelCase				: Dataset											=	self._create_dummy_dataset()
								dset.add_faiss_index_from_external_arrays(
								    external_arrays=np.ones((30, 5)	) * np.arange(30	).reshape(-1	,    1	)	,    index_name='''vecs'''	,    batch_size=100	,    metric_type=faiss.METRIC_INNER_PRODUCT	,    )
								UpperCAmelCase							,	UpperCAmelCase				: Optional[Any]											=	dset.get_nearest_examples('''vecs'''	,    np.ones(5	,    dtype=np.floataa	)	)
								self.assertEqual(examples['''filename'''][0]	,    '''my_name-train_29'''	)







	def   A			(		self    :  int	)    ->	Dict:
								import faiss

								UpperCAmelCase				: Dataset											=	self._create_dummy_dataset()
								dset.add_faiss_index_from_external_arrays(
								    external_arrays=np.ones((30, 5)	) * np.arange(30	).reshape(-1	,    1	)	,    index_name='''vecs'''	,    metric_type=faiss.METRIC_INNER_PRODUCT	,    )

								# Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
								# ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
								# see https://bugs.python.org/issue14243 and
								# https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
								with tempfile.NamedTemporaryFile(delete=__snake_case	) as tmp_file:
															dset.save_faiss_index('''vecs'''	,    tmp_file.name	)
															dset.load_faiss_index('''vecs2'''	,    tmp_file.name	)
								os.unlink(tmp_file.name	)

								UpperCAmelCase							,	UpperCAmelCase				: Optional[Any]											=	dset.get_nearest_examples('''vecs2'''	,    np.ones(5	,    dtype=np.floataa	)	)
								self.assertEqual(examples['''filename'''][0]	,    '''my_name-train_29'''	)







	def   A			(		self    :  List[Any]	)    ->	List[Any]:
								UpperCAmelCase				: Dataset											=	self._create_dummy_dataset()
								dset.add_faiss_index_from_external_arrays(
								    external_arrays=np.ones((30, 5)	) * np.arange(30	).reshape(-1	,    1	)	,    index_name='''vecs'''	)
								dset.drop_index('''vecs'''	)
								self.assertRaises(__snake_case	,    partial(dset.get_nearest_examples	,    '''vecs2'''	,    np.ones(5	,    dtype=np.floataa	)	)	)







	def   A			(		self    :  Union[str, Any]	)    ->	str:
								from elasticsearch import Elasticsearch

								UpperCAmelCase				: Dataset											=	self._create_dummy_dataset()
								with patch('''elasticsearch.Elasticsearch.search'''	) as mocked_search, patch(
								    '''elasticsearch.client.IndicesClient.create'''	) as mocked_index_create, patch('''elasticsearch.helpers.streaming_bulk'''	) as mocked_bulk:
															UpperCAmelCase				: Optional[Any]											=	{'''acknowledged''': True}
															mocked_bulk.return_value([(True, None)] * 30	)
															UpperCAmelCase				: str											=	{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 29}]}}
															UpperCAmelCase				: Optional[int]											=	Elasticsearch()

															dset.add_elasticsearch_index('''filename'''	,    es_client=__snake_case	)
															UpperCAmelCase							,	UpperCAmelCase				: List[str]											=	dset.get_nearest_examples('''filename'''	,    '''my_name-train_29'''	)
															self.assertEqual(examples['''filename'''][0]	,    '''my_name-train_29'''	)

@require_faiss
class        SCREAMING_SNAKE_CASE(							A__    ):







	"""simple docstring"""






	def   A			(		self    :  Dict	)    ->	Optional[int]:
								import faiss

								UpperCAmelCase				: Optional[Any]											=	FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT	)

								# add vectors
								index.add_vectors(np.eye(5	,    dtype=np.floataa	)	)
								self.assertIsNotNone(index.faiss_index	)
								self.assertEqual(index.faiss_index.ntotal	,    5	)
								index.add_vectors(np.zeros((5, 5)	,    dtype=np.floataa	)	)
								self.assertEqual(index.faiss_index.ntotal	,    10	)

								# single query
								UpperCAmelCase				: List[str]											=	np.zeros(5	,    dtype=np.floataa	)
								UpperCAmelCase				: Optional[Any]											=	1
								UpperCAmelCase							,	UpperCAmelCase				: Optional[Any]											=	index.search(__snake_case	)
								self.assertRaises(__snake_case	,    index.search	,    query.reshape(-1	,    1	)	)
								self.assertGreater(scores[0]	,    0	)
								self.assertEqual(indices[0]	,    1	)

								# batched queries
								UpperCAmelCase				: Optional[int]											=	np.eye(5	,    dtype=np.floataa	)[::-1]
								UpperCAmelCase							,	UpperCAmelCase				: int											=	index.search_batch(__snake_case	)
								self.assertRaises(__snake_case	,    index.search_batch	,    queries[0]	)
								UpperCAmelCase				: Optional[int]											=	[scores[0] for scores in total_scores]
								UpperCAmelCase				: Tuple											=	[indices[0] for indices in total_indices]
								self.assertGreater(np.min(__snake_case	)	,    0	)
								self.assertListEqual([4, 3, 2, 1, 0]	,    __snake_case	)







	def   A			(		self    :  List[Any]	)    ->	Any:
								import faiss

								UpperCAmelCase				: str											=	FaissIndex(string_factory='''Flat'''	)
								index.add_vectors(np.eye(5	,    dtype=np.floataa	)	)
								self.assertIsInstance(index.faiss_index	,    faiss.IndexFlat	)
								UpperCAmelCase				: Union[str, Any]											=	FaissIndex(string_factory='''LSH'''	)
								index.add_vectors(np.eye(5	,    dtype=np.floataa	)	)
								self.assertIsInstance(index.faiss_index	,    faiss.IndexLSH	)
								with self.assertRaises(__snake_case	):
															UpperCAmelCase				: Any											=	FaissIndex(string_factory='''Flat'''	,    custom_index=faiss.IndexFlat(5	)	)







	def   A			(		self    :  List[str]	)    ->	str:
								import faiss

								UpperCAmelCase				: Dict											=	faiss.IndexFlat(5	)
								UpperCAmelCase				: Dict											=	FaissIndex(custom_index=__snake_case	)
								index.add_vectors(np.eye(5	,    dtype=np.floataa	)	)
								self.assertIsInstance(index.faiss_index	,    faiss.IndexFlat	)







	def   A			(		self    :  Dict	)    ->	int:
								import faiss

								UpperCAmelCase				: List[Any]											=	FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT	)
								index.add_vectors(np.eye(5	,    dtype=np.floataa	)	)

								# Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
								# ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
								# see https://bugs.python.org/issue14243 and
								# https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
								with tempfile.NamedTemporaryFile(delete=__snake_case	) as tmp_file:
															index.save(tmp_file.name	)
															UpperCAmelCase				: str											=	FaissIndex.load(tmp_file.name	)
								os.unlink(tmp_file.name	)

								UpperCAmelCase				: Optional[Any]											=	np.zeros(5	,    dtype=np.floataa	)
								UpperCAmelCase				: int											=	1
								UpperCAmelCase							,	UpperCAmelCase				: Optional[int]											=	index.search(__snake_case	)
								self.assertGreater(scores[0]	,    0	)
								self.assertEqual(indices[0]	,    1	)


@require_faiss
def 				snake_case_  (      _lowerCAmelCase						:		Optional[int]						)   ->     Tuple:
							import faiss

							UpperCAmelCase				: str											=	FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT						)
							index.add_vectors(np.eye(5     ,   dtype=np.floataa						)						)

							UpperCAmelCase				: int											=	'''index.faiss'''
							UpperCAmelCase				: Optional[Any]											=	f"""mock://{index_name}"""
							index.save(_lowerCAmelCase     ,   storage_options=mockfs.storage_options						)
							UpperCAmelCase				: Any											=	FaissIndex.load(_lowerCAmelCase     ,   storage_options=mockfs.storage_options						)

							UpperCAmelCase				: Any											=	np.zeros(5     ,   dtype=np.floataa						)
							UpperCAmelCase				: Dict											=	1
							UpperCAmelCase							,	UpperCAmelCase				: List[str]											=	index.search(_lowerCAmelCase						)
							assert scores[0] > 0
							assert indices[0] == 1




@require_elasticsearch
class        SCREAMING_SNAKE_CASE(							A__    ):







	"""simple docstring"""






	def   A			(		self    :  List[Any]	)    ->	Optional[Any]:
								from elasticsearch import Elasticsearch

								with patch('''elasticsearch.Elasticsearch.search'''	) as mocked_search, patch(
								    '''elasticsearch.client.IndicesClient.create'''	) as mocked_index_create, patch('''elasticsearch.helpers.streaming_bulk'''	) as mocked_bulk:
															UpperCAmelCase				: Optional[int]											=	Elasticsearch()
															UpperCAmelCase				: List[Any]											=	{'''acknowledged''': True}
															UpperCAmelCase				: Any											=	ElasticSearchIndex(es_client=__snake_case	)
															mocked_bulk.return_value([(True, None)] * 3	)
															index.add_documents(['''foo''', '''bar''', '''foobar''']	)

															# single query
															UpperCAmelCase				: int											=	'''foo'''
															UpperCAmelCase				: Optional[int]											=	{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 0}]}}
															UpperCAmelCase							,	UpperCAmelCase				: List[Any]											=	index.search(__snake_case	)
															self.assertEqual(scores[0]	,    1	)
															self.assertEqual(indices[0]	,    0	)

															# single query with timeout
															UpperCAmelCase				: Optional[int]											=	'''foo'''
															UpperCAmelCase				: str											=	{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 0}]}}
															UpperCAmelCase							,	UpperCAmelCase				: Union[str, Any]											=	index.search(__snake_case	,    request_timeout=30	)
															self.assertEqual(scores[0]	,    1	)
															self.assertEqual(indices[0]	,    0	)

															# batched queries
															UpperCAmelCase				: Any											=	['''foo''', '''bar''', '''foobar''']
															UpperCAmelCase				: Optional[Any]											=	{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 1}]}}
															UpperCAmelCase							,	UpperCAmelCase				: str											=	index.search_batch(__snake_case	)
															UpperCAmelCase				: Optional[int]											=	[scores[0] for scores in total_scores]
															UpperCAmelCase				: int											=	[indices[0] for indices in total_indices]
															self.assertGreater(np.min(__snake_case	)	,    0	)
															self.assertListEqual([1, 1, 1]	,    __snake_case	)

															# batched queries with timeout
															UpperCAmelCase				: List[str]											=	['''foo''', '''bar''', '''foobar''']
															UpperCAmelCase				: Union[str, Any]											=	{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 1}]}}
															UpperCAmelCase							,	UpperCAmelCase				: Tuple											=	index.search_batch(__snake_case	,    request_timeout=30	)
															UpperCAmelCase				: int											=	[scores[0] for scores in total_scores]
															UpperCAmelCase				: Any											=	[indices[0] for indices in total_indices]
															self.assertGreater(np.min(__snake_case	)	,    0	)
															self.assertListEqual([1, 1, 1]	,    __snake_case	)










'''simple docstring'''






import numpy as np

UpperCamelCase__:     Any										=    [
    ["a", "b", "c", "d", "e"],
    ["f", "g", "h", "i", "k"],
    ["l", "m", "n", "o", "p"],
    ["q", "r", "s", "t", "u"],
    ["v", "w", "x", "y", "z"],
]

class        SCREAMING_SNAKE_CASE:







	"""simple docstring"""






	def __init__(		self    :  Any	)    ->	None:
								UpperCAmelCase				: Optional[int]											=	np.array(__snake_case	)







	def   A			(		self    :  str	,    __snake_case    :  str	)    ->	np.ndarray:
								UpperCAmelCase							,	UpperCAmelCase				: Dict											=	np.where(letter == self.SQUARE	)
								UpperCAmelCase				: Dict											=	np.concatenate([indexa + 1, indexa + 1]	)
								return indexes







	def   A			(		self    :  Union[str, Any]	,    __snake_case    :  int	,    __snake_case    :  int	)    ->	str:
								UpperCAmelCase				: int											=	self.SQUARE[indexa - 1, indexa - 1]
								return letter







	def   A			(		self    :  List[Any]	,    __snake_case    :  str	)    ->	str:
								UpperCAmelCase				: Any											=	message.lower()
								UpperCAmelCase				: List[Any]											=	message.replace(''' '''	,    ''''''	)
								UpperCAmelCase				: List[Any]											=	message.replace('''j'''	,    '''i'''	)

								UpperCAmelCase				: Tuple											=	np.empty((2, len(__snake_case	))	)
								for letter_index in range(len(__snake_case	)	):
															UpperCAmelCase				: str											=	self.letter_to_numbers(message[letter_index]	)

															UpperCAmelCase				: Any											=	numbers[0]
															UpperCAmelCase				: Optional[Any]											=	numbers[1]

								UpperCAmelCase				: List[str]											=	first_step.reshape(2 * len(__snake_case	)	)
								UpperCAmelCase				: Union[str, Any]											=	''''''
								for numbers_index in range(len(__snake_case	)	):
															UpperCAmelCase				: Dict											=	int(second_step[numbers_index * 2]	)
															UpperCAmelCase				: Union[str, Any]											=	int(second_step[(numbers_index * 2) + 1]	)
															UpperCAmelCase				: Dict											=	self.numbers_to_letter(__snake_case	,    __snake_case	)
															UpperCAmelCase				: int											=	encoded_message + letter

								return encoded_message







	def   A			(		self    :  Optional[Any]	,    __snake_case    :  str	)    ->	str:
								UpperCAmelCase				: str											=	message.lower()
								message.replace(''' '''	,    ''''''	)
								UpperCAmelCase				: Optional[int]											=	np.empty(2 * len(__snake_case	)	)
								for letter_index in range(len(__snake_case	)	):
															UpperCAmelCase				: int											=	self.letter_to_numbers(message[letter_index]	)
															UpperCAmelCase				: Optional[Any]											=	numbers[0]
															UpperCAmelCase				: List[Any]											=	numbers[1]

								UpperCAmelCase				: Tuple											=	first_step.reshape((2, len(__snake_case	))	)
								UpperCAmelCase				: str											=	''''''
								for numbers_index in range(len(__snake_case	)	):
															UpperCAmelCase				: Tuple											=	int(second_step[0, numbers_index]	)
															UpperCAmelCase				: List[str]											=	int(second_step[1, numbers_index]	)
															UpperCAmelCase				: Union[str, Any]											=	self.numbers_to_letter(__snake_case	,    __snake_case	)
															UpperCAmelCase				: Union[str, Any]											=	decoded_message + letter

								return decoded_message





