TODO¶
v2¶
We will be moving away from using nptyping in v2.0.0.
It was written for an older era in python before the dramatic changes in the Python type system and is no longer actively maintained. We will be reimplementing a syntax that extends its array specification syntax to include things like ranges and extensible dtypes with varying precision (and is much less finnicky to deal with).
Validation¶
Todo
Support pydantic value/range constraints - less than, greater than, etc.
Todo
Support different precision modes - eg. exact precision, or minimum precision where specifying a float32 would also accept a float64, etc.
Metadata¶
Todo
Use names in nptyping annotations in generated JSON schema metadata
All TODOs¶
Todo
To better support static type hinting and inspection (ie. so the type checker
is not only aware of the union of all return_types, but the specific array
type that was passed on model instantiation, as well as potentially
do shape and dtype checks during type checking (eg. so a wrongly shaped or dtyped
array assignment will be highlighted as wrong), we will be exploring adding
mypy/pylance/pyright hooks for dynamic type evaluation.
Todo
NWB Compatibility
Precision: NWB allows for a sort of hierarchy of type specification - a less precise type also allows the data to be specified in a more precise type
Todo
Sorry this is unreadable, need to recall how to change the theme for generated mermaid diagrams but it is very late and i want to push this.
Todo
Future versions will support interfaces providing type maps for declaring equality between dtypes that may be specific to that library but should be considered equivalent to numpy or other library’s dtypes.
Todo
Future versions will also support declaring minimum or maximum precisions, so one might say “at least a 16-bit float” and also accept a 32-bit float.
Todo
numpydantic currently does not support structured dtypes or numpy.recarray
specifications like nptyping does. It will in future versions.
Todo
numpydantic also does not support the variable shape definition form like
Shape['Dim, Dim']
where there are two dimensions of any shape as long as they are equal
because at the moment it appears impossible to express dynamic constraints
(ie. minItems/maxItems that depend on the shape of another array)
in JSON Schema. A future minor version will allow them by generating a JSON
schema with a warning that the equal shape constraint will not be represented.
See: https://github.com/orgs/json-schema-org/discussions/730
Todo
Support pydantic value/range constraints - less than, greater than, etc.
Todo
Support different precision modes - eg. exact precision, or minimum precision where specifying a float32 would also accept a float64, etc.
Todo
Use names in nptyping annotations in generated JSON schema metadata