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https://github.com/p2p-ld/numpydantic.git
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118 lines
3.3 KiB
Python
118 lines
3.3 KiB
Python
import pdb
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import json
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import pytest
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from pydantic import BaseModel, ValidationError
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from numpydantic.interface import H5Interface
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from numpydantic.interface.hdf5 import H5ArrayPath
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from numpydantic.exceptions import DtypeError, ShapeError
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from tests.conftest import ValidationCase
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def hdf5_array_case(case: ValidationCase, array_func) -> H5ArrayPath:
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"""
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Args:
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case:
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array_func: ( the function returned from the `hdf5_array` fixture )
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Returns:
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"""
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if issubclass(case.dtype, BaseModel):
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pytest.skip("hdf5 cant support arbitrary python objects")
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return array_func(case.shape, case.dtype)
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def _test_hdf5_case(case: ValidationCase, array_func):
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array = hdf5_array_case(case, array_func)
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if case.passes:
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case.model(array=array)
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else:
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with pytest.raises((ValidationError, DtypeError, ShapeError)):
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case.model(array=array)
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def test_hdf5_enabled():
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assert H5Interface.enabled()
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def test_hdf5_check(interface_type):
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if interface_type[1] is H5Interface:
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if interface_type[0].__name__ == "_hdf5_array":
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interface_type = (interface_type[0](), interface_type[1])
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assert H5Interface.check(interface_type[0])
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if isinstance(interface_type[0], H5ArrayPath):
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# also test that we can instantiate from a tuple like the H5ArrayPath
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assert H5Interface.check((interface_type[0].file, interface_type[0].path))
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else:
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assert not H5Interface.check(interface_type[0])
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def test_hdf5_check_not_exists():
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"""We should fail a check for a nonexistent hdf5 file"""
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spec = ("./fakefile.h5", "/fake/array")
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assert not H5Interface.check(spec)
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def test_hdf5_check_not_hdf5(tmp_path):
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"""Files that exist but aren't actually hdf5 files should fail a check"""
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afile = tmp_path / "not_an_hdf.h5"
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with open(afile, "w") as af:
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af.write("hey")
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spec = (afile, "/fake/array")
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assert not H5Interface.check(spec)
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def test_hdf5_shape(shape_cases, hdf5_array):
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_test_hdf5_case(shape_cases, hdf5_array)
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def test_hdf5_dtype(dtype_cases, hdf5_array):
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if dtype_cases.dtype is str:
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pytest.skip("hdf5 cant do string arrays")
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_test_hdf5_case(dtype_cases, hdf5_array)
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def test_hdf5_dataset_not_exists(hdf5_array, model_blank):
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array = hdf5_array()
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with pytest.raises(ValueError) as e:
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model_blank(array=H5ArrayPath(file=array.file, path="/some/random/path"))
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assert "file located" in e
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assert "no array found" in e
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def test_assignment(hdf5_array, model_blank):
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array = hdf5_array()
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model = model_blank(array=array)
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model.array[1, 1] = 5
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assert model.array[1, 1] == 5
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model.array[1:3, 2:4] = 10
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assert (model.array[1:3, 2:4] == 10).all()
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def test_to_json(hdf5_array, array_model):
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"""
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Test serialization of HDF5 arrays to JSON
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Args:
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hdf5_array:
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Returns:
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"""
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array = hdf5_array((10, 10), int)
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model = array_model((10, 10), int)
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instance = model(array=array) # type: BaseModel
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json_str = instance.model_dump_json()
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json_dict = json.loads(json_str)["array"]
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assert json_dict["file"] == str(array.file)
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assert json_dict["path"] == str(array.path)
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assert json_dict["attrs"] == {}
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assert json_dict["array"] == instance.array[:].tolist()
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