"""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


_a				:		int	   =       pytest.mark.integration
@require_faiss
class 						__A							(			SCREAMING_SNAKE_CASE_		):






     def    __A  (		self  ):
       _lowerCAmelCase						:	List[str]        =					Dataset.from_dict({"""filename""": ["""my_name-train""" + """_""" + str(a__  ) for x in np.arange(30  ).tolist()]}  )
       return dset






     def    __A  (		self  ):
       import faiss

       _lowerCAmelCase						:	Dataset        =					self._create_dummy_dataset()
       _lowerCAmelCase						:	str        =					dset.map(
           lambda a__    ,					a__  : {"vecs": i * np.ones(5    ,					dtype=np.floataa  )}    ,					with_indices=a__    ,					keep_in_memory=a__  )
       _lowerCAmelCase						:	Any        =					dset.add_faiss_index("""vecs"""    ,					batch_size=100    ,					metric_type=faiss.METRIC_INNER_PRODUCT  )
       _lowerCAmelCase      ,     _lowerCAmelCase						:	Dict        =					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  ):
       import faiss

       _lowerCAmelCase						:	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    ,					)
       _lowerCAmelCase      ,     _lowerCAmelCase						:	Any        =					dset.get_nearest_examples("""vecs"""    ,					np.ones(5    ,					dtype=np.floataa  )  )
       self.assertEqual(examples["""filename"""][0]    ,					"""my_name-train_29"""  )






     def    __A  (		self  ):
       import faiss

       _lowerCAmelCase						:	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=a__  ) as tmp_file:
         dset.save_faiss_index("""vecs"""    ,					tmp_file.name  )
         dset.load_faiss_index("""vecs2"""    ,					tmp_file.name  )
       os.unlink(tmp_file.name  )

       _lowerCAmelCase      ,     _lowerCAmelCase						:	str        =					dset.get_nearest_examples("""vecs2"""    ,					np.ones(5    ,					dtype=np.floataa  )  )
       self.assertEqual(examples["""filename"""][0]    ,					"""my_name-train_29"""  )






     def    __A  (		self  ):
       _lowerCAmelCase						:	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(a__    ,					partial(dset.get_nearest_examples    ,					"""vecs2"""    ,					np.ones(5    ,					dtype=np.floataa  )  )  )






     def    __A  (		self  ):
       from elasticsearch import Elasticsearch

       _lowerCAmelCase						:	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:
         _lowerCAmelCase						:	Optional[Any]        =					{"""acknowledged""": True}
         mocked_bulk.return_value([(True, None)] * 30  )
         _lowerCAmelCase						:	int        =					{"""hits""": {"""hits""": [{"""_score""": 1, """_id""": 29}]}}
         _lowerCAmelCase						:	Any        =					Elasticsearch()

         dset.add_elasticsearch_index("""filename"""    ,					es_client=a__  )
         _lowerCAmelCase      ,     _lowerCAmelCase						:	List[str]        =					dset.get_nearest_examples("""filename"""    ,					"""my_name-train_29"""  )
         self.assertEqual(examples["""filename"""][0]    ,					"""my_name-train_29"""  )







@require_faiss
class 						__A							(			SCREAMING_SNAKE_CASE_		):






     def    __A  (		self  ):
       import faiss

       _lowerCAmelCase						:	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    ,					10  )

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

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






     def    __A  (		self  ):
       import faiss

       _lowerCAmelCase						:	List[Any]        =					FaissIndex(string_factory="""Flat"""  )
       index.add_vectors(np.eye(5    ,					dtype=np.floataa  )  )
       self.assertIsInstance(index.faiss_index    ,					faiss.IndexFlat  )
       _lowerCAmelCase						:	int        =					FaissIndex(string_factory="""LSH"""  )
       index.add_vectors(np.eye(5    ,					dtype=np.floataa  )  )
       self.assertIsInstance(index.faiss_index    ,					faiss.IndexLSH  )
       with self.assertRaises(a__  ):
         _lowerCAmelCase						:	Any        =					FaissIndex(string_factory="""Flat"""    ,					custom_index=faiss.IndexFlat(5  )  )






     def    __A  (		self  ):
       import faiss

       _lowerCAmelCase						:	Optional[Any]        =					faiss.IndexFlat(5  )
       _lowerCAmelCase						:	Any        =					FaissIndex(custom_index=a__  )
       index.add_vectors(np.eye(5    ,					dtype=np.floataa  )  )
       self.assertIsInstance(index.faiss_index    ,					faiss.IndexFlat  )






     def    __A  (		self  ):
       import faiss

       _lowerCAmelCase						:	Optional[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=a__  ) as tmp_file:
         index.save(tmp_file.name  )
         _lowerCAmelCase						:	Tuple        =					FaissIndex.load(tmp_file.name  )
       os.unlink(tmp_file.name  )

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







@require_faiss
def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	Any     )	->				str:
  import faiss

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

  _lowerCAmelCase						:	Dict        =					"""index.faiss"""
  _lowerCAmelCase						:	Tuple        =					f"mock://{index_name}"
  index.save(_lowerCamelCase      ,storage_options=mockfs.storage_options     )
  _lowerCAmelCase						:	str        =					FaissIndex.load(_lowerCamelCase      ,storage_options=mockfs.storage_options     )

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






@require_elasticsearch
class 						__A							(			SCREAMING_SNAKE_CASE_		):






     def    __A  (		self  ):
       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:
         _lowerCAmelCase						:	str        =					Elasticsearch()
         _lowerCAmelCase						:	List[str]        =					{"""acknowledged""": True}
         _lowerCAmelCase						:	Union[str, Any]        =					ElasticSearchIndex(es_client=a__  )
         mocked_bulk.return_value([(True, None)] * 3  )
         index.add_documents(["""foo""", """bar""", """foobar"""]  )

         # single query
         _lowerCAmelCase						:	Dict        =					"""foo"""
         _lowerCAmelCase						:	int        =					{"""hits""": {"""hits""": [{"""_score""": 1, """_id""": 0}]}}
         _lowerCAmelCase      ,     _lowerCAmelCase						:	str        =					index.search(a__  )
         self.assertEqual(scores[0]    ,					1  )
         self.assertEqual(indices[0]    ,					0  )

         # single query with timeout
         _lowerCAmelCase						:	str        =					"""foo"""
         _lowerCAmelCase						:	int        =					{"""hits""": {"""hits""": [{"""_score""": 1, """_id""": 0}]}}
         _lowerCAmelCase      ,     _lowerCAmelCase						:	int        =					index.search(a__    ,					request_timeout=30  )
         self.assertEqual(scores[0]    ,					1  )
         self.assertEqual(indices[0]    ,					0  )

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

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





"""simple docstring"""




from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class 						__A							(			SCREAMING_SNAKE_CASE_		):






     def __init__(		self    ,					a__    ,					a__ = None    ,					a__ = None    ,					a__ = True    ,					a__ = None    ,					a__ = False    ,					a__ = None    ,					a__ = True    ,					a__ = "arrow"    ,					**a__    ,					):
       super().__init__(
           split=a__    ,					features=a__    ,					cache_dir=a__    ,					keep_in_memory=a__    ,					streaming=a__    ,					**a__    ,					)
       _lowerCAmelCase						:	List[Any]        =					load_from_cache_file
       _lowerCAmelCase						:	str        =					file_format
       _lowerCAmelCase						:	Dict        =					Spark(
           df=a__    ,					features=a__    ,					cache_dir=a__    ,					working_dir=a__    ,					**a__    ,					)






     def    __A  (		self  ):
       if self.streaming:
         return self.builder.as_streaming_dataset(split=self.split  )
       _lowerCAmelCase						:	Dict        =					None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
       self.builder.download_and_prepare(
           download_mode=a__    ,					file_format=self._file_format    ,					)
       return self.builder.as_dataset(split=self.split  )




