mirror of
https://github.com/p2p-ld/numpydantic.git
synced 2024-09-19 23:44:28 +00:00
120 lines
3.9 KiB
Python
120 lines
3.9 KiB
Python
"""
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Test custom features of the pydantic generator
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Note that since this is largely a subclass, we don't test all of the functionality of the generator
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because it's tested in the base linkml package.
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"""
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import re
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import sys
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import typing
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import numpy as np
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import pytest
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from pydantic import BaseModel
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def test_arraylike(imported_schema):
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"""
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Arraylike classes are converted to slots that specify nptyping arrays
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array: Optional[Union[
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NDArray[Shape["* x, * y"], Number],
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NDArray[Shape["* x, * y, 3 z"], Number],
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NDArray[Shape["* x, * y, 3 z, 4 a"], Number]
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]] = Field(None)
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"""
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# check that we have gotten an NDArray annotation and its shape is correct
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array = imported_schema["core"].MainTopLevel.model_fields["array"].annotation
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args = typing.get_args(array)
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for i, shape in enumerate(("* x, * y", "* x, * y, 3 z", "* x, * y, 3 z, 4 a")):
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assert isinstance(args[i], NDArrayMeta)
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assert args[i].__args__[0].__args__
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assert args[i].__args__[1] == np.number
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# we shouldn't have an actual class for the array
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assert not hasattr(imported_schema["core"], "MainTopLevel__Array")
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assert not hasattr(imported_schema["core"], "MainTopLevelArray")
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def test_inject_fields(imported_schema):
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"""
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Our root model should have the special fields we injected
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"""
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base = imported_schema["core"].ConfiguredBaseModel
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assert "hdf5_path" in base.model_fields
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assert "object_id" in base.model_fields
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def test_linkml_meta(imported_schema):
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"""
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We should be able to store some linkml metadata with our classes
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"""
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meta = imported_schema["core"].LinkML_Meta
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assert "tree_root" in meta.model_fields
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assert imported_schema["core"].MainTopLevel.linkml_meta.default.tree_root == True
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assert imported_schema["core"].OtherClass.linkml_meta.default.tree_root == False
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def test_skip(linkml_schema):
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"""
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We can skip slots and classes
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"""
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modules = generate_and_import(
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linkml_schema,
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split=False,
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generator_kwargs={
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"SKIP_SLOTS": ("SkippableSlot",),
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"SKIP_CLASSES": ("Skippable", "skippable"),
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},
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)
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assert not hasattr(modules["core"], "Skippable")
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assert "SkippableSlot" not in modules["core"].MainTopLevel.model_fields
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def test_inline_with_identifier(imported_schema):
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"""
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By default, if a class has an identifier attribute, it is inlined
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as a string rather than its class. We overrode that to be able to make dictionaries of collections
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"""
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main = imported_schema["core"].MainTopLevel
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inline = main.model_fields["inline_dict"].annotation
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assert typing.get_origin(typing.get_args(inline)[0]) == dict
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# god i hate pythons typing interface
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otherclass, stillanother = typing.get_args(
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typing.get_args(typing.get_args(inline)[0])[1]
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)
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assert otherclass is imported_schema["core"].OtherClass
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assert stillanother is imported_schema["core"].StillAnotherClass
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def test_namespace(imported_schema):
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"""
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Namespace schema import all classes from the other schema
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Returns:
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"""
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ns = imported_schema["namespace"]
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for classname, modname in (
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("MainThing", "test_schema.imported"),
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("Arraylike", "test_schema.imported"),
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("MainTopLevel", "test_schema.core"),
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("Skippable", "test_schema.core"),
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("OtherClass", "test_schema.core"),
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("StillAnotherClass", "test_schema.core"),
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):
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assert hasattr(ns, classname)
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if imported_schema["split"]:
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assert getattr(ns, classname).__module__ == modname
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def test_get_set_item(imported_schema):
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"""We can get and set without explicitly addressing array"""
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cls = imported_schema["core"].MainTopLevel(array=np.array([[1, 2, 3], [4, 5, 6]]))
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cls[0] = 50
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assert (cls[0] == 50).all()
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assert (cls.array[0] == 50).all()
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cls[1, 1] = 100
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assert cls[1, 1] == 100
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assert cls.array[1, 1] == 100
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