



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         =			pytest.mark.integration


@require_faiss
class   snake_case_ (lowercase__  ):




       """simple docstring"""






       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Dict				      =		Dataset.from_dict({"filename": ["my_name-train" + "_" + str(lowercase) for x in np.arange(30).tolist()]})
             return dset



       def  A_   (     self):

             """simple docstring"""





             import faiss

             UpperCAmelCase_  :	Dataset				      =		self._create_dummy_dataset()
             UpperCAmelCase_  :	List[Any]				      =		dset.map(
                 lambda lowercase     ,lowercase: {"vecs": i * np.ones(5     ,dtype=np.floataa)}     ,with_indices=lowercase     ,keep_in_memory=lowercase)
             UpperCAmelCase_  :	Optional[Any]				      =		dset.add_faiss_index("vecs"     ,batch_size=100     ,metric_type=faiss.METRIC_INNER_PRODUCT)
             UpperCAmelCase_      ,      UpperCAmelCase_  :	str				      =		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):

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



       def  A_   (     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=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)

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



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



       def  A_   (     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_  :	Optional[int]				      =		{"acknowledged": True}
                   mocked_bulk.return_value([(True, None)] * 30)
                   UpperCAmelCase_  :	List[str]				      =		{"hits": {"hits": [{"_score": 1, "_id": 29}]}}
                   UpperCAmelCase_  :	Dict				      =		Elasticsearch()

                   dset.add_elasticsearch_index("filename"     ,es_client=lowercase)
                   UpperCAmelCase_      ,      UpperCAmelCase_  :	Union[str, Any]				      =		dset.get_nearest_examples("filename"     ,"my_name-train_29")
                   self.assertEqual(examples["filename"][0]     ,"my_name-train_29")


@require_faiss
class   snake_case_ (lowercase__  ):




       """simple docstring"""






       def  A_   (     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_  :	int				      =		np.zeros(5     ,dtype=np.floataa)
             UpperCAmelCase_  :	List[Any]				      =		1
             UpperCAmelCase_      ,      UpperCAmelCase_  :	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
             UpperCAmelCase_  :	Optional[int]				      =		np.eye(5     ,dtype=np.floataa)[::-1]
             UpperCAmelCase_      ,      UpperCAmelCase_  :	Dict				      =		index.search_batch(lowercase)
             self.assertRaises(lowercase     ,index.search_batch     ,queries[0])
             UpperCAmelCase_  :	Tuple				      =		[scores[0] for scores in total_scores]
             UpperCAmelCase_  :	Any				      =		[indices[0] for indices in total_indices]
             self.assertGreater(np.min(lowercase)     ,0)
             self.assertListEqual([4, 3, 2, 1, 0]     ,lowercase)



       def  A_   (     self):

             """simple docstring"""





             import faiss

             UpperCAmelCase_  :	Any				      =		FaissIndex(string_factory="Flat")
             index.add_vectors(np.eye(5     ,dtype=np.floataa))
             self.assertIsInstance(index.faiss_index     ,faiss.IndexFlat)
             UpperCAmelCase_  :	Optional[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):
                   UpperCAmelCase_  :	Union[str, Any]				      =		FaissIndex(string_factory="Flat"     ,custom_index=faiss.IndexFlat(5))



       def  A_   (     self):

             """simple docstring"""





             import faiss

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



       def  A_   (     self):

             """simple docstring"""





             import faiss

             UpperCAmelCase_  :	Optional[int]				      =		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)
                   UpperCAmelCase_  :	List[str]				      =		FaissIndex.load(tmp_file.name)
             os.unlink(tmp_file.name)

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







@require_faiss
def    _snake_case (       __snake_case    )     ->     Optional[Any]:






      '''simple docstring'''







      import faiss

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

      UpperCAmelCase_  :	Optional[Any]				      =		"index.faiss"
      UpperCAmelCase_  :	Any				      =		F"""mock://{index_name}"""
      index.save(__snake_case					,  storage_options=mockfs.storage_options    )
      UpperCAmelCase_  :	Any				      =		FaissIndex.load(__snake_case					,  storage_options=mockfs.storage_options    )

      UpperCAmelCase_  :	Dict				      =		np.zeros(5					,  dtype=np.floataa    )
      UpperCAmelCase_  :	Optional[int]				      =		1
      UpperCAmelCase_      ,      UpperCAmelCase_  :	Tuple				      =		index.search(__snake_case    )
      assert scores[0] > 0
      assert indices[0] == 1





@require_elasticsearch
class   snake_case_ (lowercase__  ):




       """simple docstring"""






       def  A_   (     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_  :	int				      =		Elasticsearch()
                   UpperCAmelCase_  :	Union[str, Any]				      =		{"acknowledged": True}
                   UpperCAmelCase_  :	Optional[Any]				      =		ElasticSearchIndex(es_client=lowercase)
                   mocked_bulk.return_value([(True, None)] * 3)
                   index.add_documents(["foo", "bar", "foobar"])

                   # single query
                   UpperCAmelCase_  :	Any				      =		"foo"
                   UpperCAmelCase_  :	Union[str, Any]				      =		{"hits": {"hits": [{"_score": 1, "_id": 0}]}}
                   UpperCAmelCase_      ,      UpperCAmelCase_  :	Dict				      =		index.search(lowercase)
                   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_  :	Optional[int]				      =		index.search(lowercase     ,request_timeout=30)
                   self.assertEqual(scores[0]     ,1)
                   self.assertEqual(indices[0]     ,0)

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

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





def    _snake_case (       __snake_case					,  __snake_case    )     ->     str:






      '''simple docstring'''







      if a < 0 or b < 0:
            raise ValueError("the value of both inputs must be positive"    )

      UpperCAmelCase_  :	List[Any]				      =		str(bin(__snake_case    )    )[2:]  # remove the leading "0b"
      UpperCAmelCase_  :	int				      =		str(bin(__snake_case    )    )[2:]  # remove the leading "0b"

      UpperCAmelCase_  :	Optional[int]				      =		max(len(__snake_case    )					,  len(__snake_case    )    )

      return "0b" + "".join(
          str(int(char_a == "1" and char_b == "1"    )    )
          for char_a, char_b in zip(a_binary.zfill(__snake_case    )					,  b_binary.zfill(__snake_case    )    )    )


if __name__ == "__main__":
   import doctest

   doctest.testmod()
