1.2.0 - shape ranges

update docs, bump version

docs/api/shape.md

@@ -0,0 +1,7 @@
+# shape
+
+```{eval-rst}
+.. automodule:: numpydantic.shape
+    :members:
+    :undoc-members:
+```

docs/changelog.md

@@ -2,6 +2,10 @@
 
 ## 1.*
 
+### 1.2.0 - 24-06-13 - Shape ranges
+
+- Add ability to specify shapes as ranges - see [shape ranges](shape-ranges)
+
 ### 1.1.0 - 24-05-24 - Instance Checking
 
 https://github.com/p2p-ld/numpydantic/pull/1

docs/index.md

@@ -491,6 +491,7 @@ api/maps
 api/meta
 api/monkeypatch
 api/schema
+api/shape
 api/types
 
 ```

docs/syntax.md

@@ -61,6 +61,24 @@ For a 2-dimensional, 3 x any-shaped array:
 Shape["3, *"]
 ```
 
+(shape-ranges)=
+### Ranges
+
+Dimension sizes can also be specified as ranges[^ranges].
+Ranges must have no whitespace, and may use integers or wildcards.
+Range specifications are **inclusive** on both ends.
+
+For an array whose...
+- First dimension can be of length 2, 3, or 4
+- Second dimension is 2 or greater
+- Third dimension is 4 or less
+
+```python
+Shape["2-4, 2-*, *-4"]
+```
+
+[^ranges]: This is an extension to nptyping's syntax, and so using `nptyping.Shape` is unsupported - use {class}`numpydantic.Shape`
+
 ### Labels
 
 Dimensions can be given labels, and in future versions these labels will be 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "numpydantic"
-version = "1.1.0"
+version = "1.2.0"
 description = "Type and shape validation and serialization for numpy arrays in pydantic models"
 authors = [
     {name = "sneakers-the-rat", email = "sneakers-the-rat@protonmail.com"},

src/numpydantic/shape.py

@@ -58,6 +58,14 @@ class ShapeMeta(ContainerMeta, implementation="Shape"):
         dim_string_without_labels = remove_labels(dim_strings)
         return {"prepared_args": dim_string_without_labels}
 
+    def __setattr__(cls, key: str, value: Any) -> None:  # pragma: no cover
+        """just for documentation generation - allow __annotations__"""
+
+        if key not in ("_abc_impl", "__abstractmethods__", "__annotations__"):
+            raise NPTypingError(f"Cannot set values to nptyping.{cls.__name__}.")
+        else:
+            object.__setattr__(cls, key, value)
+
 
 class Shape(NPTypingType, ABC, metaclass=ShapeMeta):
     """