Pydantic Model integration of the NumPy array
Reason this release was yanked:
Numpy version constraints are incorrect.
Project description
pydantic-numpy
Integrate NumPy into Pydantic, and provide tooling! NumpyModel
make it possible to dump and load np.ndarray
within model fields!
Install
pip install pydantic-numpy
Usage
For more examples see test_ndarray.py
import pydantic_numpy.dtype as pnd
from pydantic_numpy import NDArray, NDArrayFp32, NumpyModel
class MyPydanticNumpyModel(NumpyModel):
K: NDArray[float, pnd.float32]
C: NDArrayFp32 # <- Shorthand for same type as K
# Instantiate from array
cfg = MyPydanticNumpyModel(K=[1, 2])
# Instantiate from numpy file
cfg = MyPydanticNumpyModel(K={"path": "path_to/array.npy"})
# Instantiate from npz file with key
cfg = MyPydanticNumpyModel(K={"path": "path_to/array.npz", "key": "K"})
cfg.K
# np.ndarray[np.float32]
cfg.dump("path_to_dump_dir", "object_id")
cfg.load("path_to_dump_dir", "object_id")
NumpyModel.load
requires the original mode, use model_agnostic_load
when you have several models that may be the right model.
Data type (dtype) support!
This package also comes with pydantic_numpy.dtype
, which adds subtyping support such as NDArray[float, pnd.float32]
. All subfields must be from this package as numpy dtypes have no Pydantic support, which is implemented in this package through the generic class workflow.
Considerations
You can install from cheind's repository if you want Python 3.8
support, but this version only support Pydantic V1 and will not work with V2.
Licensing notice
As of version 3.0.0
the license has moved over to BSD-4. The versions prior are under the MIT license.
History
The original idea originates from this discussion, and forked from cheind's repository.
Project details
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