"""simple docstring"""


import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch

import multiprocess
import numpy as np
import pytest

from datasets.utils.py_utils import (
    NestedDataStructure,
    asdict,
    iflatmap_unordered,
    map_nested,
    temp_seed,
    temporary_assignment,
    zip_dict,
)

from .utils import require_tf, require_torch






def 			__UpperCAmelCase    (	lowercase						):  # picklable for multiprocessing







  """simple docstring"""
  return x.sum()






def 			__UpperCAmelCase    (	lowercase						):  # picklable for multiprocessing







  """simple docstring"""
  return i + 1


@dataclass
class 				a :
    _snake_case   :     int
    _snake_case   :     str



class 				a (						__snake_case      ):


    def    lowerCAmelCase_     (    self		:     int    ):
      _UpperCAmelCase         =					{}
      _UpperCAmelCase         =					[]
      _UpperCAmelCase         =					1
      _UpperCAmelCase         =					[1, 2]
      _UpperCAmelCase         =					{"a": 1, "b": 2}
      _UpperCAmelCase         =					{"a": [1, 2], "b": [3, 4]}
      _UpperCAmelCase         =					{"a": {"1": 1}, "b": 2}
      _UpperCAmelCase         =					{"a": 1, "b": 2, "c": 3, "d": 4}
      _UpperCAmelCase         =					{}
      _UpperCAmelCase         =					[]
      _UpperCAmelCase         =					2
      _UpperCAmelCase         =					[2, 3]
      _UpperCAmelCase         =					{"a": 2, "b": 3}
      _UpperCAmelCase         =					{"a": [2, 3], "b": [4, 5]}
      _UpperCAmelCase         =					{"a": {"1": 2}, "b": 3}
      _UpperCAmelCase         =					{"a": 2, "b": 3, "c": 4, "d": 5}
      self.assertEqual(map_nested(A_      , A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_    )      , A_    )

      _UpperCAmelCase         =					2
      self.assertEqual(map_nested(A_      , A_      , num_proc=A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_      , num_proc=A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_      , num_proc=A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_      , num_proc=A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_      , num_proc=A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_      , num_proc=A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_      , num_proc=A_    )      , A_    )
      self.assertEqual(map_nested(A_      , A_      , num_proc=A_    )      , A_    )

      _UpperCAmelCase         =					{"a": np.eye(2    ), "b": np.zeros(3    ), "c": np.ones(2    )}
      _UpperCAmelCase         =					{"a": 2, "b": 0, "c": 2}
      _UpperCAmelCase         =					{
          "a": np.eye(2    ).astype(A_    ),
          "b": np.zeros(3    ).astype(A_    ),
          "c": np.ones(2    ).astype(A_    ),
      }
      self.assertEqual(map_nested(A_      , A_      , map_numpy=A_    )      , A_    )
      self.assertEqual(
          {k: v.tolist() for k, v in map_nested(A_      , A_      , map_numpy=A_    ).items()}      , {k: v.tolist() for k, v in expected_map_nested_sna_int.items()}      , )
      self.assertEqual(map_nested(A_      , A_      , map_numpy=A_      , num_proc=A_    )      , A_    )
      self.assertEqual(
          {k: v.tolist() for k, v in map_nested(A_      , A_      , map_numpy=A_      , num_proc=A_    ).items()}      , {k: v.tolist() for k, v in expected_map_nested_sna_int.items()}      , )
      with self.assertRaises(A_    ):  # can't pickle a local lambda
        map_nested(lambda __lowerCAmelCase    : x + 1      , A_      , num_proc=A_    )


    def    lowerCAmelCase_     (    self		:     Optional[Any]    ):
      _UpperCAmelCase         =					{"a": 1, "b": 2}
      _UpperCAmelCase         =					{"a": 3, "b": 4}
      _UpperCAmelCase         =					{"a": 5, "b": 6}
      _UpperCAmelCase         =					sorted([("""a""", (1, 3, 5)), ("""b""", (2, 4, 6))]    )
      self.assertEqual(sorted(zip_dict(A_      , A_      , A_    )    )      , A_    )


    def    lowerCAmelCase_     (    self		:     Any    ):


      class 				a :
          _snake_case   :     int   							=							'bar'



      _UpperCAmelCase         =					Foo()
      self.assertEqual(foo.my_attr      , """bar"""    )
      with temporary_assignment(A_      , """my_attr"""      , """BAR"""    ):
        self.assertEqual(foo.my_attr      , """BAR"""    )
      self.assertEqual(foo.my_attr      , """bar"""    )






@pytest.mark.parametrize(
    """iterable_length, num_proc, expected_num_proc"""      ,[
        (1, None, 1),
        (1, 1, 1),
        (2, None, 1),
        (2, 1, 1),
        (2, 2, 1),
        (2, 3, 1),
        (3, 2, 1),
        (16, 16, 16),
        (16, 17, 16),
        (17, 16, 16),
    ]      ,)
def 			__UpperCAmelCase    (	lowercase      ,lowercase      ,lowercase						):







  """simple docstring"""
  with patch("""datasets.utils.py_utils._single_map_nested"""						) as mock_single_map_nested, patch(
      """datasets.parallel.parallel.Pool"""						) as mock_multiprocessing_pool:
    _UpperCAmelCase         =					{f'''{i}''': i for i in range(_lowerCAmelCase						)}
    _UpperCAmelCase         =					map_nested(lambda lowercase						: x + 10      ,_lowerCAmelCase      ,num_proc=_lowerCAmelCase      ,parallel_min_length=16						)
    if expected_num_proc == 1:
      assert mock_single_map_nested.called
      assert not mock_multiprocessing_pool.called
    else:
      assert not mock_single_map_nested.called
      assert mock_multiprocessing_pool.called
      assert mock_multiprocessing_pool.call_args[0][0] == expected_num_proc


class 				a (						__snake_case      ):


    @require_tf
    def    lowerCAmelCase_     (    self		:     Optional[int]    ):
      import tensorflow as tf
      from tensorflow.keras import layers

      _UpperCAmelCase         =					layers.Dense(2    )

      def gen_random_output():
        _UpperCAmelCase         =					tf.random.uniform((1, 3)    )
        return model(A_    ).numpy()

      with temp_seed(42      , set_tensorflow=A_    ):
        _UpperCAmelCase         =					gen_random_output()
      with temp_seed(42      , set_tensorflow=A_    ):
        _UpperCAmelCase         =					gen_random_output()
      _UpperCAmelCase         =					gen_random_output()

      np.testing.assert_equal(A_      , A_    )
      self.assertGreater(np.abs(outa - outa    ).sum()      , 0    )


    @require_torch
    def    lowerCAmelCase_     (    self		:     Optional[int]    ):
      import torch

      def gen_random_output():
        _UpperCAmelCase         =					torch.nn.Linear(3      , 2    )
        _UpperCAmelCase         =					torch.rand(1      , 3    )
        return model(A_    ).detach().numpy()

      with temp_seed(42      , set_pytorch=A_    ):
        _UpperCAmelCase         =					gen_random_output()
      with temp_seed(42      , set_pytorch=A_    ):
        _UpperCAmelCase         =					gen_random_output()
      _UpperCAmelCase         =					gen_random_output()

      np.testing.assert_equal(A_      , A_    )
      self.assertGreater(np.abs(outa - outa    ).sum()      , 0    )


    def    lowerCAmelCase_     (    self		:     Optional[Any]    ):




      def gen_random_output():
        return np.random.rand(1      , 3    )

      with temp_seed(42    ):
        _UpperCAmelCase         =					gen_random_output()
      with temp_seed(42    ):
        _UpperCAmelCase         =					gen_random_output()
      _UpperCAmelCase         =					gen_random_output()

      np.testing.assert_equal(A_      , A_    )
      self.assertGreater(np.abs(outa - outa    ).sum()      , 0    )






@pytest.mark.parametrize("""input_data"""      ,[{}]						)
def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  _UpperCAmelCase         =					NestedDataStructure(_lowerCAmelCase						).data
  assert output_data == input_data






@pytest.mark.parametrize(
    """data, expected_output"""      ,[
        ({}, []),
        ([], []),
        ("""foo""", ["""foo"""]),
        (["""foo""", """bar"""], ["""foo""", """bar"""]),
        ([["""foo""", """bar"""]], ["""foo""", """bar"""]),
        ([[["""foo"""], ["""bar"""]]], ["""foo""", """bar"""]),
        ([[["""foo"""], """bar"""]], ["""foo""", """bar"""]),
        ({"""a""": 1, """b""": 2}, [1, 2]),
        ({"""a""": [1, 2], """b""": [3, 4]}, [1, 2, 3, 4]),
        ({"""a""": [[1, 2]], """b""": [[3, 4]]}, [1, 2, 3, 4]),
        ({"""a""": [[1, 2]], """b""": [3, 4]}, [1, 2, 3, 4]),
        ({"""a""": [[[1], [2]]], """b""": [[[3], [4]]]}, [1, 2, 3, 4]),
        ({"""a""": [[[1], [2]]], """b""": [[3, 4]]}, [1, 2, 3, 4]),
        ({"""a""": [[[1], [2]]], """b""": [3, 4]}, [1, 2, 3, 4]),
        ({"""a""": [[[1], [2]]], """b""": [3, [4]]}, [1, 2, 3, 4]),
        ({"""a""": {"""1""": 1}, """b""": 2}, [1, 2]),
        ({"""a""": {"""1""": [1]}, """b""": 2}, [1, 2]),
        ({"""a""": {"""1""": [1]}, """b""": [2]}, [1, 2]),
    ]      ,)
def 			__UpperCAmelCase    (	lowercase      ,lowercase						):







  """simple docstring"""
  _UpperCAmelCase         =					NestedDataStructure(_lowerCAmelCase						).flatten()
  assert output == expected_output






def 			__UpperCAmelCase    (	):







  """simple docstring"""
  _UpperCAmelCase         =					A(x=1      ,y="""foobar"""						)
  _UpperCAmelCase         =					{"x": 1, "y": "foobar"}
  assert asdict(_lowerCAmelCase						) == expected_output

  _UpperCAmelCase         =					{"a": {"b": A(x=10      ,y="""foo"""						)}, "c": [A(x=20      ,y="""bar"""						)]}
  _UpperCAmelCase         =					{"a": {"b": {"x": 10, "y": "foo"}}, "c": [{"x": 20, "y": "bar"}]}
  assert asdict(_lowerCAmelCase						) == expected_output

  with pytest.raises(_lowerCAmelCase						):
    asdict([1, A(x=10      ,y="""foo"""						)]						)






def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  return text.split()






def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  yield (time.time(), content)
  time.sleep(2						)
  yield (time.time(), content)






def 			__UpperCAmelCase    (	):







  """simple docstring"""
  with Pool(2						) as pool:
    _UpperCAmelCase         =					list(iflatmap_unordered(_lowerCAmelCase      ,_split_text      ,kwargs_iterable=[{"""text""": """hello there"""}] * 10						)						)
    assert out.count("""hello"""						) == 10
    assert out.count("""there"""						) == 10
    assert len(_lowerCAmelCase						) == 20

  # check multiprocess from pathos (uses dill for pickling)
  with multiprocess.Pool(2						) as pool:
    _UpperCAmelCase         =					list(iflatmap_unordered(_lowerCAmelCase      ,_split_text      ,kwargs_iterable=[{"""text""": """hello there"""}] * 10						)						)
    assert out.count("""hello"""						) == 10
    assert out.count("""there"""						) == 10
    assert len(_lowerCAmelCase						) == 20

  # check that we get items as fast as possible
  with Pool(2						) as pool:
    _UpperCAmelCase         =					[]
    for yield_time, content in iflatmap_unordered(
        _lowerCAmelCase      ,_aseconds_generator_of_aitems_with_timing      ,kwargs_iterable=[{"""content""": """a"""}, {"""content""": """b"""}]						):
      assert yield_time < time.time() + 0.1, "we should each item directly after it was yielded"
      out.append(_lowerCAmelCase						)
    assert out.count("""a"""						) == 2
    assert out.count("""b"""						) == 2
    assert len(_lowerCAmelCase						) == 4







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


__lowerCamelCase       :     Union[str, Any]   =     pytest.mark.integration



@require_faiss
class 					A__   (       __snake_case			):





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					Union[str, Any]       	=   Dataset.from_dict({"filename": ["my_name-train" + "_" + str(A_   ) for x in np.arange(30   ).tolist()]}   )
       return dset





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       import faiss

       UpperCamelCase	:					Dataset       	=   self._create_dummy_dataset()
       UpperCamelCase	:					List[Any]       	=   dset.map(
           lambda A_       ,							A_   : {"vecs": i * np.ones(5       ,							dtype=np.floataa   )}       ,							with_indices=A_       ,							keep_in_memory=A_   )
       UpperCamelCase	:					List[str]       	=   dset.add_faiss_index("vecs"       ,							batch_size=100       ,							metric_type=faiss.METRIC_INNER_PRODUCT   )
       UpperCamelCase	,    UpperCamelCase	:					Tuple       	=   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        __UpperCamelCase( self   ):
       '''simple docstring'''




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





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       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=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   )

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





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       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(A_       ,							partial(dset.get_nearest_examples       ,							"vecs2"       ,							np.ones(5       ,							dtype=np.floataa   )   )   )





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




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

        dset.add_elasticsearch_index("filename"       ,							es_client=A_   )
        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 					A__   (       __snake_case			):





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       import faiss

       UpperCamelCase	:					Optional[int]       	=   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	:					Any       	=   np.zeros(5       ,							dtype=np.floataa   )
       UpperCamelCase	:					Optional[Any]       	=   1
       UpperCamelCase	,    UpperCamelCase	:					Optional[Any]       	=   index.search(A_   )
       self.assertRaises(A_       ,							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	:					Tuple       	=   index.search_batch(A_   )
       self.assertRaises(A_       ,							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(A_   )       ,							0   )
       self.assertListEqual([4, 3, 2, 1, 0]       ,							A_   )





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       import faiss

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





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       import faiss

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





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       import faiss

       UpperCamelCase	:					str       	=   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   )
        UpperCamelCase	:					int       	=   FaissIndex.load(tmp_file.name   )
       os.unlink(tmp_file.name   )

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



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

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

 UpperCamelCase	:					List[Any]       	=   "index.faiss"
 UpperCamelCase	:					List[str]       	=   F"""mock://{index_name}"""
 index.save(_lowerCAmelCase							,   storage_options=mockfs.storage_options     )
 UpperCamelCase	:					List[str]       	=   FaissIndex.load(_lowerCAmelCase							,   storage_options=mockfs.storage_options     )

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



@require_elasticsearch
class 					A__   (       __snake_case			):





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

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

        # single query with timeout
        UpperCamelCase	:					Dict       	=   "foo"
        UpperCamelCase	:					Optional[Any]       	=   {"hits": {"hits": [{"_score": 1, "_id": 0}]}}
        UpperCamelCase	,    UpperCamelCase	:					str       	=   index.search(A_       ,							request_timeout=30   )
        self.assertEqual(scores[0]       ,							1   )
        self.assertEqual(indices[0]       ,							0   )

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

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