


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


snake_case				:    List[str]       				=     pytest.mark.integration







@require_faiss
class 		_snake_case  (      _snake_case							):




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:Union[str, Any] 							=       Dataset.from_dict({'''filename''': ['''my_name-train''' + '''_''' + str(_lowerCamelCase    ) for x in np.arange(30    ).tolist()]}    )
       return dset




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       import faiss

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

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




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       import faiss

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




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						: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(_lowerCamelCase					,  partial(dset.get_nearest_examples					,  '''vecs2'''					,  np.ones(5					,  dtype=np.floataa    )    )    )




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       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						:Tuple 							=       {'''acknowledged''': True}
             mocked_bulk.return_value([(True, None)] * 30    )
             a						:List[str] 							=       {'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 29}]}}
             a						:Tuple 							=       Elasticsearch()

             dset.add_elasticsearch_index('''filename'''					,  es_client=_lowerCamelCase    )
             a							,				a						:Dict 							=       dset.get_nearest_examples('''filename'''					,  '''my_name-train_29'''    )
             self.assertEqual(examples['''filename'''][0]					,  '''my_name-train_29'''    )







@require_faiss
class 		_snake_case  (      _snake_case							):




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       import faiss

       a						:Dict 							=       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
       a						:Tuple 							=       np.zeros(5					,  dtype=np.floataa    )
       a						:str 							=       1
       a							,				a						:int 							=       index.search(_lowerCamelCase    )
       self.assertRaises(_lowerCamelCase					,  index.search					,  query.reshape(-1					,  1    )    )
       self.assertGreater(scores[0]					,  0    )
       self.assertEqual(indices[0]					,  1    )

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




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       import faiss

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




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       import faiss

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




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       import faiss

       a						: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=_lowerCamelCase    ) as tmp_file:
             index.save(tmp_file.name    )
             a						:int 							=       FaissIndex.load(tmp_file.name    )
       os.unlink(tmp_file.name    )

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







@require_faiss
def 				__lowerCamelCase						( UpperCAmelCase_						:		Optional[int]						):




      """simple docstring"""





      import faiss

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

      a						:Optional[Any] 							=       '''index.faiss'''
      a						:Union[str, Any] 							=       F'''mock://{index_name}'''
      index.save(UpperCAmelCase_ ,  storage_options=mockfs.storage_options						)
      a						:List[str] 							=       FaissIndex.load(UpperCAmelCase_ ,  storage_options=mockfs.storage_options						)

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







@require_elasticsearch
class 		_snake_case  (      _snake_case							):




 def        SCREAMING_SNAKE_CASE__				(		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:
             a						:Any 							=       Elasticsearch()
             a						:Optional[Any] 							=       {'''acknowledged''': True}
             a						:Union[str, Any] 							=       ElasticSearchIndex(es_client=_lowerCamelCase    )
             mocked_bulk.return_value([(True, None)] * 3    )
             index.add_documents(['''foo''', '''bar''', '''foobar''']    )

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

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

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

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









def 				__lowerCamelCase						( UpperCAmelCase_						:		int = 100_0000						):




      """simple docstring"""





      a						:Any 							=       set(range(3 ,  UpperCAmelCase_ ,  2						)						)
      primes.add(2						)
      for p in range(3 ,  UpperCAmelCase_ ,  2						):
            if p not in primes:
                  continue
            primes.difference_update(set(range(p * p ,  UpperCAmelCase_ ,  UpperCAmelCase_						)						)						)

      a						:Union[str, Any] 							=       [float(UpperCAmelCase_						) for n in range(limit + 1						)]

      for p in primes:
            for n in range(UpperCAmelCase_ ,  limit + 1 ,  UpperCAmelCase_						):
                  phi[n] *= 1 - 1 / p

      return int(sum(phi[2:]						)						)


if __name__ == "__main__":
     print(F"""{solution() = }""")





