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Accept `np.ndarray` as a typehint for actions/properties

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
40/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
numpy, python
Domain
api, backend

Research direction

Start with the existing labthings_fastapi.types.numpy.NDArray type and the ThingClient path that reconstructs returned values. Trace how action and property type hints are converted for HTTP, then define what metadata is needed for shape, dtype, and flattened data. Done means np.ndarray is accepted and arrays can be serialized and reconstructed across the server and client.

Written by the indexing model from the issue text.

Description

We use numpy a lot, so it would be great to be able to type hint numpy properly.

Currently we have to use: from labthings_fastapi.types.numpy import NDArray which works for sending things over HTTP but means the type hints are wrong when using the action from within the server.

Proposal

  • Allow np.ndarray
  • On seeing np.ndarray LabThings should convert it to a pydantic model this model can have the necessary data to reconstruct the array including dimensions and types
class NDArrayModel(BaseModel):

    shape = list[int]
    d_type = Literal["bool"], Literal["int"], Literal["float"], Literal["uint8"], Literal["uint16"]
    data = list[int]|list[bool]|list[float]

This way we can serialise the data as a 1D list along with the information for how to contruct the correct array. In a ThingClient the array should be able to be reconstructed. In Javascript or any other language there is enough information to process the result.

Dominant language
Python
Stars
9
Forks
4
PR merge metrics
No merged PRs in 30d

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