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            =		pytest.mark.integration





@require_faiss
class UpperCAmelCase						( __A  ):


				'''simple docstring'''






				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    int         =				Dataset.from_dict({'filename': ['my_name-train' + '_' + str(lowercase ) for x in np.arange(3_0 ).tolist()]} )
						return dset
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						import faiss

						A_		:    Dataset         =				self._create_dummy_dataset()
						A_		:    Dict         =				dset.map(
						    lambda lowercase		,     lowercase : {"vecs": i * np.ones(5		,     dtype=np.floataa )}		,     with_indices=lowercase		,     keep_in_memory=lowercase )
						A_		:    Dict         =				dset.add_faiss_index('vecs'		,     batch_size=1_0_0		,     metric_type=faiss.METRIC_INNER_PRODUCT )
						A_       ,      A_		:    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   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						import faiss

						A_		:    Dataset         =				self._create_dummy_dataset()
						dset.add_faiss_index_from_external_arrays(
						    external_arrays=np.ones((3_0, 5) ) * np.arange(3_0 ).reshape(-1		,     1 )		,     index_name='vecs'		,     batch_size=1_0_0		,     metric_type=faiss.METRIC_INNER_PRODUCT		,     )
						A_       ,      A_		:    Optional[Any]         =				dset.get_nearest_examples('vecs'		,     np.ones(5		,     dtype=np.floataa ) )
						self.assertEqual(examples['filename'][0]		,     'my_name-train_29' )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						import faiss

						A_		:    Dataset         =				self._create_dummy_dataset()
						dset.add_faiss_index_from_external_arrays(
						    external_arrays=np.ones((3_0, 5) ) * np.arange(3_0 ).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=lowercase ) as tmp_file:
								dset.save_faiss_index('vecs'		,     tmp_file.name )
								dset.load_faiss_index('vecs2'		,     tmp_file.name )
						os.unlink(tmp_file.name )

						A_       ,      A_		:    Dict         =				dset.get_nearest_examples('vecs2'		,     np.ones(5		,     dtype=np.floataa ) )
						self.assertEqual(examples['filename'][0]		,     'my_name-train_29' )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    Dataset         =				self._create_dummy_dataset()
						dset.add_faiss_index_from_external_arrays(
						    external_arrays=np.ones((3_0, 5) ) * np.arange(3_0 ).reshape(-1		,     1 )		,     index_name='vecs' )
						dset.drop_index('vecs' )
						self.assertRaises(lowercase		,     partial(dset.get_nearest_examples		,     'vecs2'		,     np.ones(5		,     dtype=np.floataa ) ) )







				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						from elasticsearch import Elasticsearch

						A_		:    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:
								A_		:    str         =				{'acknowledged': True}
								mocked_bulk.return_value([(True, None)] * 3_0 )
								A_		:    Tuple         =				{'hits': {'hits': [{'_score': 1, '_id': 2_9}]}}
								A_		:    Union[str, Any]         =				Elasticsearch()

								dset.add_elasticsearch_index('filename'		,     es_client=lowercase )
								A_       ,      A_		:    Optional[int]         =				dset.get_nearest_examples('filename'		,     'my_name-train_29' )
								self.assertEqual(examples['filename'][0]		,     'my_name-train_29' )





@require_faiss
class UpperCAmelCase						( __A  ):


				'''simple docstring'''






				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						import faiss

						A_		:    List[str]         =				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		,     1_0 )

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

						# batched queries
						A_		:    Union[str, Any]         =				np.eye(5		,     dtype=np.floataa )[::-1]
						A_       ,      A_		:    Union[str, Any]         =				index.search_batch(lowercase )
						self.assertRaises(lowercase		,     index.search_batch		,     queries[0] )
						A_		:    Optional[Any]         =				[scores[0] for scores in total_scores]
						A_		:    Tuple         =				[indices[0] for indices in total_indices]
						self.assertGreater(np.min(lowercase )		,     0 )
						self.assertListEqual([4, 3, 2, 1, 0]		,     lowercase )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						import faiss

						A_		:    int         =				FaissIndex(string_factory='Flat' )
						index.add_vectors(np.eye(5		,     dtype=np.floataa ) )
						self.assertIsInstance(index.faiss_index		,     faiss.IndexFlat )
						A_		:    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(lowercase ):
								A_		:    Union[str, Any]         =				FaissIndex(string_factory='Flat'		,     custom_index=faiss.IndexFlat(5 ) )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						import faiss

						A_		:    Any         =				faiss.IndexFlat(5 )
						A_		:    List[str]         =				FaissIndex(custom_index=lowercase )
						index.add_vectors(np.eye(5		,     dtype=np.floataa ) )
						self.assertIsInstance(index.faiss_index		,     faiss.IndexFlat )







				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						import faiss

						A_		:    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=lowercase ) as tmp_file:
								index.save(tmp_file.name )
								A_		:    Union[str, Any]         =				FaissIndex.load(tmp_file.name )
						os.unlink(tmp_file.name )

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




@require_faiss
def     UpperCamelCase						(	__lowercase						:			List[str]     ):
		'''simple docstring'''




		import faiss

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

		A_		:    List[str]         =				'index.faiss'
		A_		:    Dict         =				f'''mock://{index_name}'''
		index.save(__lowercase						,storage_options=mockfs.storage_options     )
		A_		:    Union[str, Any]         =				FaissIndex.load(__lowercase						,storage_options=mockfs.storage_options     )

		A_		:    str         =				np.zeros(5						,dtype=np.floataa     )
		A_		:    Dict         =				1
		A_       ,      A_		:    Dict         =				index.search(__lowercase     )
		assert scores[0] > 0
		assert indices[0] == 1





@require_elasticsearch
class UpperCAmelCase						( __A  ):


				'''simple docstring'''






				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						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:
								A_		:    int         =				Elasticsearch()
								A_		:    List[Any]         =				{'acknowledged': True}
								A_		:    Tuple         =				ElasticSearchIndex(es_client=lowercase )
								mocked_bulk.return_value([(True, None)] * 3 )
								index.add_documents(['foo', 'bar', 'foobar'] )

								# single query
								A_		:    Tuple         =				'foo'
								A_		:    str         =				{'hits': {'hits': [{'_score': 1, '_id': 0}]}}
								A_       ,      A_		:    Dict         =				index.search(lowercase )
								self.assertEqual(scores[0]		,     1 )
								self.assertEqual(indices[0]		,     0 )

								# single query with timeout
								A_		:    Union[str, Any]         =				'foo'
								A_		:    Optional[int]         =				{'hits': {'hits': [{'_score': 1, '_id': 0}]}}
								A_       ,      A_		:    Tuple         =				index.search(lowercase		,     request_timeout=3_0 )
								self.assertEqual(scores[0]		,     1 )
								self.assertEqual(indices[0]		,     0 )

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

								# batched queries with timeout
								A_		:    int         =				['foo', 'bar', 'foobar']
								A_		:    Optional[int]         =				{'hits': {'hits': [{'_score': 1, '_id': 1}]}}
								A_       ,      A_		:    int         =				index.search_batch(lowercase		,     request_timeout=3_0 )
								A_		:    Optional[int]         =				[scores[0] for scores in total_scores]
								A_		:    List[str]         =				[indices[0] for indices in total_indices]
								self.assertGreater(np.min(lowercase )		,     0 )
								self.assertListEqual([1, 1, 1]		,     lowercase )







import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


_UpperCAmelCase            =		namedtuple(
    """_TestCommandArgs""",
    [
        """dataset""",
        """name""",
        """cache_dir""",
        """data_dir""",
        """all_configs""",
        """save_infos""",
        """ignore_verifications""",
        """force_redownload""",
        """clear_cache""",
    ],
    defaults=[None, None, None, False, False, False, False, False],
)




def     UpperCamelCase						(	__lowercase						:			Any						,__lowercase						:			str     ):
		'''simple docstring'''




		return (abs(source - target     ) / target) < 0.01




@pytest.mark.integration
def     UpperCamelCase						(	__lowercase						:			Dict     ):
		'''simple docstring'''




		A_		:    Optional[Any]         =				_TestCommandArgs(dataset=__lowercase						,all_configs=__lowercase						,save_infos=__lowercase     )
		A_		:    List[Any]         =				TestCommand(*__lowercase     )
		test_command.run()
		A_		:    Any         =				os.path.join(__lowercase						,'README.md'     )
		assert os.path.exists(__lowercase     )
		A_		:    Tuple         =				DatasetInfosDict.from_directory(__lowercase     )
		A_		:    Any         =				DatasetInfosDict(
		    {
		        'default': DatasetInfo(
		            features=Features(
		                {
		                    'tokens': Sequence(Value('string'     )     ),
		                    'ner_tags': Sequence(
		                        ClassLabel(names=['O', 'B-PER', 'I-PER', 'B-ORG', 'I-ORG', 'B-LOC', 'I-LOC']     )     ),
		                    'langs': Sequence(Value('string'     )     ),
		                    'spans': Sequence(Value('string'     )     ),
		                }     )						,splits=[
		                {
		                    'name': 'train',
		                    'num_bytes': 2_35_15_63,
		                    'num_examples': 1_00_00,
		                },
		                {
		                    'name': 'validation',
		                    'num_bytes': 23_84_18,
		                    'num_examples': 10_00,
		                },
		            ]						,download_size=3_94_06_80						,dataset_size=2_58_99_81						,)
		    }     )
		assert dataset_infos.keys() == expected_dataset_infos.keys()
		for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
				A_       ,      A_		:    Union[str, Any]         =				getattr(dataset_infos['default']						,__lowercase     ), getattr(expected_dataset_infos['default']						,__lowercase     )
				if key == "num_bytes":
						assert is_apercent_close(__lowercase						,__lowercase     )
				elif key == "splits":
						assert list(__lowercase     ) == list(__lowercase     )
						for split in result:
								assert result[split].name == expected[split].name
								assert result[split].num_examples == expected[split].num_examples
								assert is_apercent_close(result[split].num_bytes						,expected[split].num_bytes     )
				else:
						result == expected






