docarray · anna-charlotte · Apr 27, 2023 · Apr 27, 2023 · Apr 27, 2023 · Apr 27, 2023
diff --git a/docarray/index/__init__.py b/docarray/index/__init__.py
@@ -1,7 +1,7 @@
 import types
 from typing import TYPE_CHECKING
 
-from docarray.index.backends.in_memory import InMemoryDocIndex
+from docarray.index.backends.in_memory import InMemoryExactNNIndex
 from docarray.utils._internal.misc import (
     _get_path_from_docarray_root_level,
     import_library,
@@ -14,7 +14,7 @@
     from docarray.index.backends.qdrant import QdrantDocumentIndex  # noqa: F401
     from docarray.index.backends.weaviate import WeaviateDocumentIndex  # noqa: F401
 
-__all__ = ['InMemoryDocIndex']
+__all__ = ['InMemoryExactNNIndex']
 
 
 def __getattr__(name: str):

diff --git a/docarray/index/backends/in_memory.py b/docarray/index/backends/in_memory.py
@@ -38,9 +38,9 @@
 TSchema = TypeVar('TSchema', bound=BaseDoc)
 
 
-class InMemoryDocIndex(BaseDocIndex, Generic[TSchema]):
+class InMemoryExactNNIndex(BaseDocIndex, Generic[TSchema]):
     def __init__(self, docs: Optional[DocList] = None, **kwargs):
-        """Initialize InMemoryDocIndex"""
+        """Initialize InMemoryExactNNIndex"""
         super().__init__(db_config=None, **kwargs)
         self._runtime_config = self.RuntimeConfig()
         self._docs = (
@@ -78,13 +78,13 @@ def build(self, *args, **kwargs) -> Any:
 
     @dataclass
     class DBConfig(BaseDocIndex.DBConfig):
-        """Dataclass that contains all "static" configurations of InMemoryDocIndex."""
+        """Dataclass that contains all "static" configurations of InMemoryExactNNIndex."""
 
         pass
 
     @dataclass
     class RuntimeConfig(BaseDocIndex.RuntimeConfig):
-        """Dataclass that contains all "dynamic" configurations of InMemoryDocIndex."""
+        """Dataclass that contains all "dynamic" configurations of InMemoryExactNNIndex."""
 
         default_column_config: Dict[Type, Dict[str, Any]] = field(
             default_factory=lambda: defaultdict(
@@ -139,7 +139,8 @@ def _get_items(
         If no document is found, a KeyError is raised.
 
         :param doc_ids: ids to get from the Document index
-        :return: Sequence of Documents, sorted corresponding to the order of `doc_ids`. Duplicate `doc_ids` can be omitted in the output.
+        :return: Sequence of Documents, sorted corresponding to the order of `doc_ids`.
+            Duplicate `doc_ids` can be omitted in the output.
         """
         indices = []
         for i, doc in enumerate(self._docs):
@@ -149,7 +150,7 @@ def _get_items(
 
     def execute_query(self, query: List[Tuple[str, Dict]], *args, **kwargs) -> Any:
         """
-        Execute a query on the InMemoryDocIndex.
+        Execute a query on the InMemoryExactNNIndex.
 
         Can take two kinds of inputs:
 

diff --git a/docs/API_reference/doc_index/backends/in_memory.md b/docs/API_reference/doc_index/backends/in_memory.md
@@ -1,3 +1,3 @@
-# InMemoryDocIndex
+#InMemoryExactNNIndex
 
-::: docarray.index.backends.in_memory.InMemoryDocIndex
+::: docarray.index.backends.in_memory.InMemoryExactNNIndex
diff --git a/docs/user_guide/storing/index_in_memory.md b/docs/user_guide/storing/index_in_memory.md
@@ -1,22 +1,22 @@
 # In-Memory Document Index
 
 
-[InMemoryDocIndex][docarray.index.backends.in_memory.InMemoryDocIndex] stores all Documents in DocLists in memory. 
+[InMemoryExactNNIndex][docarray.index.backends.in_memory.InMemoryExactNNIndex] stores all Documents in DocLists in memory. 
 It is a great starting point for small datasets, where you may not want to launch a database server.
 
-For vector search and filtering the InMemoryDocIndex utilizes DocArray's [`find()`][docarray.utils.find.find] and 
+For vector search and filtering the InMemoryExactNNIndex utilizes DocArray's [`find()`][docarray.utils.find.find] and 
 [`filter_docs()`][docarray.utils.filter.filter_docs] functions.
 
 ## Basic usage
 
-To see how to create a [InMemoryDocIndex][docarray.index.backends.in_memory.InMemoryDocIndex] instance, add Documents,
+To see how to create a [InMemoryExactNNIndex][docarray.index.backends.in_memory.InMemoryExactNNIndex] instance, add Documents,
 perform search, etc. see the [general user guide](./docindex.md).
 
 You can initialize the index as follows:
 
 ```python
 from docarray import BaseDoc, DocList
-from docarray.index.backends.in_memory import InMemoryDocIndex
+from docarray.index.backends.in_memory import InMemoryExactNNIndex
 from docarray.typing import NdArray
 
 
@@ -26,20 +26,20 @@ class MyDoc(BaseDoc):
 
 docs = DocList[MyDoc](MyDoc() for _ in range(10))
 
-doc_index = InMemoryDocIndex[MyDoc]()
+doc_index = InMemoryExactNNIndex[MyDoc]()
 doc_index.index(docs)
 
 # or in one step:
-doc_index = InMemoryDocIndex[MyDoc](docs)
+doc_index = InMemoryExactNNIndex[MyDoc](docs)
 ```
 
 ## Configuration
 
-This section lays out the configurations and options that are specific to [InMemoryDocIndex][docarray.index.backends.in_memory.InMemoryDocIndex].
+This section lays out the configurations and options that are specific to [InMemoryExactNNIndex][docarray.index.backends.in_memory.InMemoryExactNNIndex].
 
 ### RuntimeConfig
 
-The `RuntimeConfig` of [InMemoryDocIndex][docarray.index.backends.in_memory.InMemoryDocIndex] contains only one entry:
+The `RuntimeConfig` of [InMemoryExactNNIndex][docarray.index.backends.in_memory.InMemoryExactNNIndex] contains only one entry:
 the default mapping from Python types to column configurations.
 
 You can see in the [section below](#field-wise-configurations) how to override configurations for specific fields.
@@ -95,7 +95,7 @@ When using the index, you can define multiple fields and their nested structure.
 ```python
 import numpy as np
 from docarray import BaseDoc
-from docarray.index.backends.in_memory import InMemoryDocIndex
+from docarray.index.backends.in_memory import InMemoryExactNNIndex
 from docarray.typing import ImageUrl, VideoUrl, AnyTensor
 from pydantic import Field
 
@@ -118,7 +118,7 @@ class YouTubeVideoDoc(BaseDoc):
     tensor: AnyTensor = Field(space='cosine_sim')
 
 
-doc_index = InMemoryDocIndex[YouTubeVideoDoc]()
+doc_index = InMemoryExactNNIndex[YouTubeVideoDoc]()
 index_docs = [
     YouTubeVideoDoc(
         title=f'video {i+1}',
@@ -134,7 +134,7 @@ doc_index.index(index_docs)
 
 ## Search Documents
 
-To search Documents, the `InMemoryDocIndex` uses DocArray's [`find`][docarray.utils.find.find] function.
+To search Documents, the `InMemoryExactNNIndex` uses DocArray's [`find`][docarray.utils.find.find] function.
 
 You can use the `search_field` to specify which field to use when performing the vector search. 
 You can use the dunder operator to specify the field defined in nested data. 
@@ -157,7 +157,7 @@ docs, scores = doc_index.find(query, search_field='video__tensor', limit=3)
 
 ## Filter Documents
 
-To filter Documents, the `InMemoryDocIndex` uses DocArray's [`filter_docs()`][docarray.utils.filter.filter_docs] function.
+To filter Documents, the `InMemoryExactNNIndex` uses DocArray's [`filter_docs()`][docarray.utils.filter.filter_docs] function.
 
 You can filter your documents by using the `filter()` or `filter_batched()` method with a corresponding  filter query. 
 The query should follow the query language of the DocArray's [`filter_docs()`][docarray.utils.filter.filter_docs] function.
@@ -174,7 +174,7 @@ class Book(BaseDoc):
 
 
 books = DocList[Book]([Book(title=f'title {i}', price=i * 10) for i in range(10)])
-book_index = InMemoryDocIndex[Book](books)
+book_index = InMemoryExactNNIndex[Book](books)
 
 # filter for books that are cheaper than 29 dollars
 query = {'price': {'$lte': 29}}

diff --git a/tests/index/in_memory/test_in_memory.py b/tests/index/in_memory/test_in_memory.py
@@ -3,7 +3,7 @@
 from pydantic import Field
 
 from docarray import BaseDoc, DocList
-from docarray.index.backends.in_memory import InMemoryDocIndex
+from docarray.index.backends.in_memory import InMemoryExactNNIndex
 from docarray.typing import NdArray
 
 
@@ -26,7 +26,7 @@ def docs():
 
 
 def test_indexing(docs):
-    doc_index = InMemoryDocIndex[SchemaDoc]()
+    doc_index = InMemoryExactNNIndex[SchemaDoc]()
     assert doc_index.num_docs() == 0
 
     doc_index.index(docs)
@@ -35,7 +35,7 @@ def test_indexing(docs):
 
 @pytest.fixture
 def doc_index(docs):
-    doc_index = InMemoryDocIndex[SchemaDoc]()
+    doc_index = InMemoryExactNNIndex[SchemaDoc]()
     doc_index.index(docs)
     return doc_index