v4.0.1 Release. (#2982)

python/deeplake/__init__.py

@@ -1,19 +1,23 @@
 import os
 from typing import Callable, Any, Dict
 
+import numpy
+
 import deeplake
 from ._deeplake import *
 from ._deeplake import _deepcopy
 
-__version__ = "4.0.0"
+__version__ = "4.0.1"
 
 __all__ = [
     "__version__",
     "FutureVoid",
     "Future",
     "Tag",
+    "TagView",
     "TagNotFoundError",
     "Tags",
+    "TagsView",
     "ColumnDefinition",
     "ColumnDefinitionView",
     "ColumnView",
@@ -29,6 +33,7 @@
     "UnevenUpdateError",
     "ColumnMissingAppendValueError",
     "ColumnAlreadyExistsError",
+    "ColumnDoesNotExistError",
     "InvalidColumnValueError",
     "GcsStorageProviderFailed",
     "History",

python/deeplake/__init__.pyi

@@ -11,8 +11,10 @@ __all__ = [
     "FutureVoid",
     "Future",
     "Tag",
+    "TagView",
     "TagNotFoundError",
     "Tags",
+    "TagsView",
     "ColumnDefinition",
     "ColumnDefinitionView",
     "ColumnView",
@@ -28,6 +30,7 @@ __all__ = [
     "UnevenUpdateError",
     "ColumnMissingAppendValueError",
     "ColumnAlreadyExistsError",
+    "ColumnDoesNotExistError",
     "InvalidColumnValueError",
     "GcsStorageProviderFailed",
     "History",
@@ -321,8 +324,52 @@ class Tag:
         """
         ...
 
+    def open_async(self) -> Future:
+        """
+        Asynchronously fetches the dataset corresponding to the tag and returns a Future object.
+        """
+        ...
+
     def __repr__(self) -> str: ...
 
+class TagView:
+    """
+    Describes a read-only tag within the dataset.
+
+    Tags are created using [deeplake.Dataset.tag][].
+    """
+
+    @property
+    def id(self) -> str:
+        """
+        The unique identifier of the tag
+        """
+
+    @property
+    def name(self) -> str:
+        """
+        The name of the tag
+        """
+
+    @property
+    def version(self) -> str:
+        """
+        The version that has been tagged
+        """
+
+    def open(self) -> ReadOnlyDataset:
+        """
+        Fetches the dataset corresponding to the tag
+        """
+        ...
+
+    def open_async(self) -> Future:
+        """
+        Asynchronously fetches the dataset corresponding to the tag and returns a Future object.
+        """
+        ...
+
+    def __repr__(self) -> str: ...
 
 class TagNotFoundError(Exception):
     pass
@@ -361,6 +408,34 @@ class Tags:
 
     ...
 
+class TagsView:
+    """
+    Provides access to the tags within a dataset.
+
+    It is returned by the [deeplake.Dataset.tags][] property on a [deeplake.ReadOnlyDataset][].
+    """
+
+    def __getitem__(self, name: str) -> TagView:
+        """
+        Return a tag by name
+        """
+        ...
+
+    def __len__(self) -> int:
+        """
+        The total number of tags in the dataset
+        """
+        ...
+
+    def __repr__(self) -> str: ...
+
+    def names(self) -> list[str]:
+        """
+        Return a list of tag names
+        """
+
+    ...
+
 
 class ColumnDefinition:
     def __repr__(self) -> str: ...
@@ -1329,9 +1404,9 @@ class ReadOnlyDataset(DatasetView):
     def __repr__(self) -> str: ...
 
     @property
-    def tags(self) -> Tags:
+    def tags(self) -> TagsView:
         """
-        The collection of [deeplake.Tags][] within the dataset
+        The collection of [deeplake.TagsView][] within the dataset
         """
         ...
 
@@ -1437,6 +1512,10 @@ class ColumnAlreadyExistsError(Exception):
     pass
 
 
+class ColumnDoesNotExistError(Exception):
+    pass
+
+
 class InvalidColumnValueError(Exception):
     pass
 

python/deeplake/types.py

@@ -26,6 +26,7 @@
     "BoundingBox",
     "BinaryMask",
     "SegmentMask",
+    "TypeKind",
     "TextIndexType",
     "QuantizationType",
     "Binary",

python/deeplake/types.pyi

@@ -28,6 +28,7 @@ __all__ = [
     "BoundingBox",
     "BinaryMask",
     "SegmentMask",
+    "TypeKind",
     "TextIndexType",
     "QuantizationType",
     "Binary",
@@ -144,6 +145,10 @@ class Type:
     def is_sequence(self) -> bool:
         ...
 
+    @property
+    def kind(self) -> TypeKind:
+        ...
+
     @property
     def shape(self) -> list[int] | None:
         """
@@ -152,6 +157,66 @@ class Type:
         ...
 
 
+class TypeKind:
+    """
+    Members:
+    
+      Generic
+    
+      Text
+    
+      Dict
+    
+      Embedding
+    
+      Sequence
+    
+      Image
+    
+      BoundingBox
+    
+      BinaryMask
+    
+      SegmentMask
+    """
+    BinaryMask: typing.ClassVar[TypeKind]
+    BoundingBox: typing.ClassVar[TypeKind]
+    Dict: typing.ClassVar[TypeKind]
+    Embedding: typing.ClassVar[TypeKind]
+    Generic: typing.ClassVar[TypeKind]
+    Image: typing.ClassVar[TypeKind]
+    SegmentMask: typing.ClassVar[TypeKind]
+    Sequence: typing.ClassVar[TypeKind]
+    Text: typing.ClassVar[TypeKind]
+    __members__: typing.ClassVar[dict[str, TypeKind]]
+    def __eq__(self, other: typing.Any) -> bool:
+        ...
+    def __getstate__(self) -> int:
+        ...
+    def __hash__(self) -> int:
+        ...
+    def __index__(self) -> int:
+        ...
+    def __init__(self, value: int) -> None:
+        ...
+    def __int__(self) -> int:
+        ...
+    def __ne__(self, other: typing.Any) -> bool:
+        ...
+    def __repr__(self) -> str:
+        ...
+    def __setstate__(self, state: int) -> None:
+        ...
+    def __str__(self) -> str:
+        ...
+    @property
+    def name(self) -> str:
+        ...
+    @property
+    def value(self) -> int:
+        ...
+
+
 @typing.overload
 def Array(dtype: DataType | str, dimensions: int) -> DataType: ...
 
@@ -250,6 +315,7 @@ def Embedding(size: int, dtype: DataType | str = "float32", quantization: Quanti
         size: The size of the embedding
         dtype: The datatype of the embedding. Defaults to float32
         quantization: How to compress the embeddings in the index. Default uses no compression, but can be set to [deeplake.types.QuantizationType.Binary][]
+
     Examples:
          >>> ds.add_column("col1", types.Embedding(768))
          >>> ds.add_column("col2", types.Embedding(768, quantization=types.QuantizationType.Binary))