




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								=					pytest.mark.integration





@require_faiss
class 			__lowerCamelCase	(   a__   ):




    """simple docstring"""

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


    def        a				(	self					:					int       )				->	Optional[Any]:
         import faiss

         lowerCAmelCase__          =			self._create_dummy_dataset()
         lowerCAmelCase__          =			dset.map(
             lambda SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       : {"vecs": i * np.ones(5       ,     dtype=np.floataa       )}       ,     with_indices=SCREAMING_SNAKE_CASE__       ,     keep_in_memory=SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			dset.add_faiss_index("vecs"       ,     batch_size=100       ,     metric_type=faiss.METRIC_INNER_PRODUCT       )
         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        a				(	self					:					int       )				->	int:
         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=100       ,     metric_type=faiss.METRIC_INNER_PRODUCT       ,     )
         lowerCAmelCase__          =			dset.get_nearest_examples("vecs"       ,     np.ones(5       ,     dtype=np.floataa       )       )
         self.assertEqual(examples["filename"][0]       ,     "my_name-train_29"       )


    def        a				(	self					:					Tuple       )				->	Any:
         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=SCREAMING_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__          =			dset.get_nearest_examples("vecs2"       ,     np.ones(5       ,     dtype=np.floataa       )       )
         self.assertEqual(examples["filename"][0]       ,     "my_name-train_29"       )


    def        a				(	self					:					Dict       )				->	Union[str, Any]:
         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(SCREAMING_SNAKE_CASE__       ,     partial(dset.get_nearest_examples       ,     "vecs2"       ,     np.ones(5       ,     dtype=np.floataa       )       )       )


    def        a				(	self					:					Dict       )				->	str:
         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=SCREAMING_SNAKE_CASE__       )
              lowerCAmelCase__          =			dset.get_nearest_examples("filename"       ,     "my_name-train_29"       )
              self.assertEqual(examples["filename"][0]       ,     "my_name-train_29"       )






@require_faiss
class 			__lowerCamelCase	(   a__   ):




    """simple docstring"""

    def        a				(	self					:					int       )				->	Optional[Any]:
         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__          =			index.search(SCREAMING_SNAKE_CASE__       )
         self.assertRaises(SCREAMING_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__          =			index.search_batch(SCREAMING_SNAKE_CASE__       )
         self.assertRaises(SCREAMING_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(SCREAMING_SNAKE_CASE__       )       ,     0       )
         self.assertListEqual([4, 3, 2, 1, 0]       ,     SCREAMING_SNAKE_CASE__       )


    def        a				(	self					:					Optional[int]       )				->	Dict:
         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(SCREAMING_SNAKE_CASE__       ):
              lowerCAmelCase__          =			FaissIndex(string_factory="Flat"       ,     custom_index=faiss.IndexFlat(5       )       )


    def        a				(	self					:					Optional[Any]       )				->	List[str]:
         import faiss

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


    def        a				(	self					:					Union[str, Any]       )				->	List[str]:
         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=SCREAMING_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__          =			index.search(SCREAMING_SNAKE_CASE__       )
         self.assertGreater(scores[0]       ,     0       )
         self.assertEqual(indices[0]       ,     1       )






@require_faiss
def 							_A       (						lowerCAmelCase_					: str      ):
     """simple docstring"""

     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(_lowerCamelCase       ,    storage_options=mockfs.storage_options      )
     lowerCAmelCase__          =			FaissIndex.load(_lowerCamelCase       ,    storage_options=mockfs.storage_options      )

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






@require_elasticsearch
class 			__lowerCamelCase	(   a__   ):




    """simple docstring"""

    def        a				(	self					:					Dict       )				->	Union[str, Any]:
         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=SCREAMING_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__          =			index.search(SCREAMING_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__          =			index.search(SCREAMING_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__          =			index.search_batch(SCREAMING_SNAKE_CASE__       )
              lowerCAmelCase__          =			[scores[0] for scores in total_scores]
              lowerCAmelCase__          =			[indices[0] for indices in total_indices]
              self.assertGreater(np.min(SCREAMING_SNAKE_CASE__       )       ,     0       )
              self.assertListEqual([1, 1, 1]       ,     SCREAMING_SNAKE_CASE__       )

              # batched queries with timeout
              lowerCAmelCase__          =			["foo", "bar", "foobar"]
              lowerCAmelCase__          =			{"hits": {"hits": [{"_score": 1, "_id": 1}]}}
              lowerCAmelCase__          =			index.search_batch(SCREAMING_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(SCREAMING_SNAKE_CASE__       )       ,     0       )
              self.assertListEqual([1, 1, 1]       ,     SCREAMING_SNAKE_CASE__       )












from math import pi, sqrt



def 							_A       (						lowerCAmelCase_					: float      ):
     """simple docstring"""

     if num <= 0:
          raise ValueError("math domain error"      )
     if num > 171.5:
          raise OverflowError("math range error"      )
     elif num - int(lowerCAmelCase_      ) not in (0, 0.5):
          raise NotImplementedError("num must be an integer or a half-integer"      )
     elif num == 0.5:
          return sqrt(lowerCAmelCase_      )
     else:
          return 1.0 if num == 1 else (num - 1) * gamma(num - 1      )



def 							_A       (						):
     """simple docstring"""

     assert gamma(0.5      ) == sqrt(lowerCAmelCase_      )
     assert gamma(1      ) == 1.0
     assert gamma(2      ) == 1.0


if __name__ == "__main__":
     from doctest import testmod

     testmod()
     UpperCamelCase								=					1.0
     while num:
          UpperCamelCase								=					float(input('Gamma of: '))
          print(F"""gamma({num}) = {gamma(num)}""")
          print('\nEnter 0 to exit...')
