





"""simple docstring"""
import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


__UpperCamelCase     :						int						       =  pytest.mark.integration

@pytest.mark.parametrize('path'  ,     ['paws', 'csv']			)
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Dict  ,     _UpperCAmelCase					:    Optional[int]			):
 inspect_dataset(_UpperCAmelCase  ,     _UpperCAmelCase			)
 lowerCAmelCase    				= path + '.py'
 assert script_name in os.listdir(_UpperCAmelCase			)
 assert "__pycache__" not in os.listdir(_UpperCAmelCase			)

@pytest.mark.filterwarnings('ignore:inspect_metric is deprecated:FutureWarning'			)
@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'			)
@pytest.mark.parametrize('path'  ,     ['accuracy']			)
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Any  ,     _UpperCAmelCase					:    int			):
 inspect_metric(_UpperCAmelCase  ,     _UpperCAmelCase			)
 lowerCAmelCase    				= path + '.py'
 assert script_name in os.listdir(_UpperCAmelCase			)
 assert "__pycache__" not in os.listdir(_UpperCAmelCase			)

@pytest.mark.parametrize(
    'path, config_name, expected_splits'  ,     [
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    str  ,     _UpperCAmelCase					:    Any  ,     _UpperCAmelCase					:    Union[str, Any]			):
 lowerCAmelCase    				= get_dataset_config_info(_UpperCAmelCase  ,     config_name=_UpperCAmelCase			)
 assert info.config_name == config_name
 assert list(info.splits.keys()			) == expected_splits

@pytest.mark.parametrize(
    'path, config_name, expected_exception'  ,     [
        ('paws', None, ValueError),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Optional[int]  ,     _UpperCAmelCase					:    List[str]  ,     _UpperCAmelCase					:    List[Any]			):
 with pytest.raises(_UpperCAmelCase			):
  get_dataset_config_info(_UpperCAmelCase  ,     config_name=_UpperCAmelCase			)

@pytest.mark.parametrize(
    'path, expected'  ,     [
        ('squad', 'plain_text'),
        ('acronym_identification', 'default'),
        ('lhoestq/squad', 'plain_text'),
        ('lhoestq/test', 'default'),
        ('lhoestq/demo1', 'lhoestq--demo1'),
        ('dalle-mini/wit', 'dalle-mini--wit'),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    List[str]  ,     _UpperCAmelCase					:    Union[str, Any]			):
 lowerCAmelCase    				= get_dataset_config_names(_UpperCAmelCase			)
 assert expected in config_names

@pytest.mark.parametrize(
    'path, expected_configs, expected_splits_in_first_config'  ,     [
        ('squad', ['plain_text'], ['train', 'validation']),
        ('dalle-mini/wit', ['dalle-mini--wit'], ['train']),
        ('paws', ['labeled_final', 'labeled_swap', 'unlabeled_final'], ['train', 'test', 'validation']),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    List[Any]  ,     _UpperCAmelCase					:    Any  ,     _UpperCAmelCase					:    List[str]			):
 lowerCAmelCase    				= get_dataset_infos(_UpperCAmelCase			)
 assert list(infos.keys()			) == expected_configs
 lowerCAmelCase    				= expected_configs[0]
 assert expected_config in infos
 lowerCAmelCase    				= infos[expected_config]
 assert info.config_name == expected_config
 assert list(info.splits.keys()			) == expected_splits_in_first_config

@pytest.mark.parametrize(
    'path, expected_config, expected_splits'  ,     [
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Any  ,     _UpperCAmelCase					:    Optional[Any]  ,     _UpperCAmelCase					:    str			):
 lowerCAmelCase    				= get_dataset_infos(_UpperCAmelCase			)
 assert expected_config in infos
 lowerCAmelCase    				= infos[expected_config]
 assert info.config_name == expected_config
 assert list(info.splits.keys()			) == expected_splits




@pytest.mark.parametrize(
    'path, config_name, expected_exception'  ,     [
        ('paws', None, ValueError),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Tuple  ,     _UpperCAmelCase					:    Tuple  ,     _UpperCAmelCase					:    Union[str, Any]			):
 with pytest.raises(_UpperCAmelCase			):
  get_dataset_split_names(_UpperCAmelCase  ,     config_name=_UpperCAmelCase			)












"""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


__UpperCamelCase     :						Optional[int]						       =  pytest.mark.integration







@require_faiss
class       a							(   a__  ):



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  lowerCAmelCase    				= Dataset.from_dict({'filename': ['my_name-train' + '_' + str(_snake_case     ) for x in np.arange(30     ).tolist()]}     )
  return dset



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  import faiss

  lowerCAmelCase    				= self._create_dummy_dataset()
  lowerCAmelCase    				= dset.map(
      lambda _snake_case				,       _snake_case     : {"vecs": i * np.ones(5				,       dtype=np.floataa     )}				,       with_indices=_snake_case				,       keep_in_memory=_snake_case     )
  lowerCAmelCase    				= dset.add_faiss_index('vecs'				,       batch_size=1_00				,       metric_type=faiss.METRIC_INNER_PRODUCT     )
  lowerCAmelCase				,lowerCAmelCase    				= 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

  lowerCAmelCase    				= 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=1_00				,       metric_type=faiss.METRIC_INNER_PRODUCT				,       )
  lowerCAmelCase				,lowerCAmelCase    				= 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

  lowerCAmelCase    				= 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=_snake_case     ) 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    				= 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"""






  lowerCAmelCase    				= 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(_snake_case				,       partial(dset.get_nearest_examples				,       'vecs2'				,       np.ones(5				,       dtype=np.floataa     )     )     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  from elasticsearch import Elasticsearch

  lowerCAmelCase    				= 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    				= {'acknowledged': True}
   mocked_bulk.return_value([(True, None)] * 30     )
   lowerCAmelCase    				= {'hits': {'hits': [{'_score': 1, '_id': 29}]}}
   lowerCAmelCase    				= Elasticsearch()

   dset.add_elasticsearch_index('filename'				,       es_client=_snake_case     )
   lowerCAmelCase				,lowerCAmelCase    				= dset.get_nearest_examples('filename'				,       'my_name-train_29'     )
   self.assertEqual(examples['filename'][0]				,       'my_name-train_29'     )







@require_faiss
class       a							(   a__  ):



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  import faiss

  lowerCAmelCase    				= 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    				= np.zeros(5				,       dtype=np.floataa     )
  lowerCAmelCase    				= 1
  lowerCAmelCase				,lowerCAmelCase    				= index.search(_snake_case     )
  self.assertRaises(_snake_case				,       index.search				,       query.reshape(-1				,       1     )     )
  self.assertGreater(scores[0]				,       0     )
  self.assertEqual(indices[0]				,       1     )

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



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  import faiss

  lowerCAmelCase    				= FaissIndex(string_factory='Flat'     )
  index.add_vectors(np.eye(5				,       dtype=np.floataa     )     )
  self.assertIsInstance(index.faiss_index				,       faiss.IndexFlat     )
  lowerCAmelCase    				= FaissIndex(string_factory='LSH'     )
  index.add_vectors(np.eye(5				,       dtype=np.floataa     )     )
  self.assertIsInstance(index.faiss_index				,       faiss.IndexLSH     )
  with self.assertRaises(_snake_case     ):
   lowerCAmelCase    				= FaissIndex(string_factory='Flat'				,       custom_index=faiss.IndexFlat(5     )     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  import faiss

  lowerCAmelCase    				= faiss.IndexFlat(5     )
  lowerCAmelCase    				= FaissIndex(custom_index=_snake_case     )
  index.add_vectors(np.eye(5				,       dtype=np.floataa     )     )
  self.assertIsInstance(index.faiss_index				,       faiss.IndexFlat     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  import faiss

  lowerCAmelCase    				= 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=_snake_case     ) as tmp_file:
   index.save(tmp_file.name     )
   lowerCAmelCase    				= FaissIndex.load(tmp_file.name     )
  os.unlink(tmp_file.name     )

  lowerCAmelCase    				= np.zeros(5				,       dtype=np.floataa     )
  lowerCAmelCase    				= 1
  lowerCAmelCase				,lowerCAmelCase    				= index.search(_snake_case     )
  self.assertGreater(scores[0]				,       0     )
  self.assertEqual(indices[0]				,       1     )


@require_faiss
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Dict			):
 import faiss

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

 lowerCAmelCase    				= 'index.faiss'
 lowerCAmelCase    				= F'mock://{index_name}'
 index.save(_UpperCAmelCase  ,     storage_options=mockfs.storage_options			)
 lowerCAmelCase    				= FaissIndex.load(_UpperCAmelCase  ,     storage_options=mockfs.storage_options			)

 lowerCAmelCase    				= np.zeros(5  ,     dtype=np.floataa			)
 lowerCAmelCase    				= 1
 lowerCAmelCase				,lowerCAmelCase    				= index.search(_UpperCAmelCase			)
 assert scores[0] > 0
 assert indices[0] == 1







@require_elasticsearch
class       a							(   a__  ):



 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:
   lowerCAmelCase    				= Elasticsearch()
   lowerCAmelCase    				= {'acknowledged': True}
   lowerCAmelCase    				= ElasticSearchIndex(es_client=_snake_case     )
   mocked_bulk.return_value([(True, None)] * 3     )
   index.add_documents(['foo', 'bar', 'foobar']     )

   # single query
   lowerCAmelCase    				= 'foo'
   lowerCAmelCase    				= {'hits': {'hits': [{'_score': 1, '_id': 0}]}}
   lowerCAmelCase				,lowerCAmelCase    				= index.search(_snake_case     )
   self.assertEqual(scores[0]				,       1     )
   self.assertEqual(indices[0]				,       0     )

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

   # batched queries
   lowerCAmelCase    				= ['foo', 'bar', 'foobar']
   lowerCAmelCase    				= {'hits': {'hits': [{'_score': 1, '_id': 1}]}}
   lowerCAmelCase				,lowerCAmelCase    				= index.search_batch(_snake_case     )
   lowerCAmelCase    				= [scores[0] for scores in total_scores]
   lowerCAmelCase    				= [indices[0] for indices in total_indices]
   self.assertGreater(np.min(_snake_case     )				,       0     )
   self.assertListEqual([1, 1, 1]				,       _snake_case     )

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





