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div.cell.tag_hide-cell details.above-input > summary, | ||
div.cell.tag_hide-input details.above-input > summary, | ||
div.cell.tag_hide-output details.below-input > summary{ | ||
background-color: var(--color-admonition-title-background--admonition-todo); | ||
color: var(--color-content-foreground); | ||
border: unset; | ||
border-left: 2px solid var(--mystnb-source-margin-color); | ||
opacity: unset; | ||
padding: 0.25em 0 0.25em 1em; | ||
} | ||
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div.cell.tag_hide-cell details.above-input > summary > span, | ||
div.cell.tag_hide-input details.above-input > summary > span, | ||
div.cell.tag_hide-output details.below-input > summary > span | ||
{ | ||
opacity: unset; | ||
} | ||
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div.cell details.above-input div.cell_input { | ||
border: unset; | ||
background-color: unset; | ||
border-left: 2px solid var(--mystnb-source-margin-color); | ||
} | ||
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div.cell details.above-input div.cell_input div.highlight { | ||
background: var(--color-admonition-background); | ||
} | ||
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.output.text_html pre { | ||
font-size: 0.8em; | ||
} |
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# interfaces | ||
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```{eval-rst} | ||
.. automodule:: numpydantic.testing.interfaces | ||
:members: | ||
:undoc-members: | ||
``` |
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# Code of Conduct | ||
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```{todo} | ||
jonny write the code of conduct | ||
``` |
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# Contributing | ||
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```{toctree} | ||
coc | ||
process | ||
interface | ||
testing | ||
``` |
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# Writing an Interface | ||
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```{todo} | ||
Jonny write the interface contrib docs | ||
``` |
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# Contribution Process | ||
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```{todo} | ||
Jonny write the contribution docs | ||
``` | ||
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### Issues | ||
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### Development Environment | ||
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### Testing | ||
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### Linting | ||
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### Pull Requests |
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--- | ||
file_format: mystnb | ||
mystnb: | ||
output_stderr: remove | ||
render_text_lexer: python | ||
render_markdown_format: myst | ||
myst: | ||
enable_extensions: ["colon_fence"] | ||
--- | ||
# Testing | ||
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```{code-cell} | ||
--- | ||
tags: [hide-cell] | ||
--- | ||
from pathlib import Path | ||
from rich.console import Console | ||
from rich.theme import Theme | ||
from rich.style import Style | ||
from rich.color import Color | ||
theme = Theme({ | ||
"repr.call": Style(color=Color.from_rgb(110,191,38), bold=True), | ||
"repr.attrib_name": Style(color="slate_blue1"), | ||
"repr.number": Style(color="deep_sky_blue1"), | ||
"repr.none": Style(color="bright_magenta", italic=True), | ||
"repr.attrib_name": Style(color="white"), | ||
"repr.tag_contents": Style(color="light_steel_blue"), | ||
"repr.str": Style(color="violet") | ||
}) | ||
console = Console(theme=theme) | ||
``` | ||
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```{note} | ||
Also see the [`numpydantic.testing` API docs](../api/testing/index.md) | ||
and the [Writing an Interface](../interfaces.md) guide | ||
``` | ||
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Numpydantic exposes a system for combinatoric testing across dtypes, shapes, | ||
and interfaces in the {mod}`numpydantic.testing` module. | ||
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These helper classes and functions are included in the distributed package | ||
so they can be used for downstream development of independent interfaces | ||
(though we always welcome contributions!) | ||
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## Validation Cases | ||
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Each test case is parameterized by a {class}`.ValidationCase`. | ||
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The case is intended to be able to be partially filled in so that multiple | ||
validation cases can be merged together, but also used independently | ||
by falling back on default values. | ||
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There are three major parts to a validation case: | ||
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- **Annotation specification:** {attr}`~.ValidationCase.annotation_dtype` and | ||
{attr}`~.ValidationCase.annotation_shape` specifies how the | ||
{class}`.NDArray` {attr}`.ValidationCase.annotation` that is used to test | ||
against is generated | ||
- **Array specification:** {attr}`~.ValidationCase.dtype` and {attr}`~.ValidationCase.shape` | ||
specify that array that will be generated to test against the annotation | ||
- **Interface specification:** An {class}`.InterfaceCase` that refers to | ||
an {class}`.Interface`, and provides array generation and other auxilary logic. | ||
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Typically, one specifies a dtype along with an annotation dtype or | ||
a shape along with an annotation shape (or implicitly against the defaults for either), | ||
along with a value for `passes` that indicates if that combination is valid. | ||
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```{code-cell} | ||
from numpydantic.testing import ValidationCase | ||
dtype_case = ValidationCase( | ||
id="int_int", | ||
dtype=int, | ||
annotation_dtype=int, | ||
passes=True | ||
) | ||
shape_case = ValidationCase( | ||
id="cool_shape", | ||
shape=(1,2,3), | ||
annotation_shape=(1,"*","2-4"), | ||
passes=True | ||
) | ||
merged = dtype_case.merge(shape_case) | ||
console.print(merged.model_dump(exclude={'annotation', 'model'}, exclude_unset=True)) | ||
``` | ||
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When merging validation cases, the merged case only `passes` if all the | ||
original cases do. | ||
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```{code-cell} | ||
from numpydantic.testing import ValidationCase | ||
dtype_case = ValidationCase( | ||
id="int_int", | ||
dtype=int, | ||
annotation_dtype=int, | ||
passes=True | ||
) | ||
shape_case = ValidationCase( | ||
id="uncool_shape", | ||
shape=(1,2,3), | ||
annotation_shape=(9,8,7), | ||
passes=False | ||
) | ||
merged = dtype_case.merge(shape_case) | ||
console.print(merged.model_dump(exclude={'annotation', 'model'}, exclude_unset=True)) | ||
``` | ||
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We provide a convenience function {func}`.merged_product` for creating a merged product of | ||
multiple sets of test cases. | ||
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For example, you may want to create a set of dtype and shape cases and validate | ||
against all combinations | ||
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```{code-cell} | ||
from numpydantic.testing.helpers import merged_product | ||
dtype_cases = [ | ||
ValidationCase(dtype=int, annotation_dtype=int, passes=True), | ||
ValidationCase(dtype=int, annotation_dtype=float, passes=False) | ||
] | ||
shape_cases = [ | ||
ValidationCase(shape=(1,2,3), annotation_shape=(1,2,3), passes=True), | ||
ValidationCase(shape=(4,5,6), annotation_shape=(1,2,3), passes=False) | ||
] | ||
iterator = merged_product(dtype_cases, shape_cases) | ||
console.print([i.model_dump(exclude_unset=True, exclude={'model', 'annotation'}) for i in iterator]) | ||
``` | ||
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You can pass constraints to the {func}`.merged_product` iterator to | ||
filter cases that match some value, for example to get only the cases that pass: | ||
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```{code-cell} | ||
iterator = merged_product(dtype_cases, shape_cases, conditions={"passes": True}) | ||
console.print([i.model_dump(exclude_unset=True, exclude={'model', 'annotation'}) for i in iterator]) | ||
``` | ||
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## Interface Cases | ||
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Validation cases can be paired with interface cases that handle | ||
generating arrays for the given interface from the specification in the | ||
validation case. | ||
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Since some array interfaces like Zarr have multiple possible forms | ||
of an array (in memory, on disk, in a zip file, etc.) an interface | ||
may have multiple cases that are important to test against. | ||
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The {meth}`.InterfaceCase.make_array` method does what you'd expect it to, | ||
creating an array, and returning the appropriate input type for the interface: | ||
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```{code-cell} | ||
from numpydantic.testing.interfaces import NumpyCase, ZarrNestedCase | ||
NumpyCase.make_array(shape=(1,2,3), dtype=float) | ||
``` | ||
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```{code-cell} | ||
ZarrNestedCase.make_array(shape=(1,2,3), dtype=float, path=Path("__tmp__/zarr_dir")) | ||
``` | ||
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Interface cases also define when an interface should skip a given test | ||
parameterization. For example, some array formats can't support arbitrary | ||
object serialization, and the video class can only support 8-bit arrays | ||
of a specific shape | ||
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```{code-cell} | ||
from numpydantic.testing.interfaces import VideoCase | ||
VideoCase.skip(shape=(1,1), dtype=float) | ||
``` | ||
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This, and the array generation methods are propagated up into | ||
a ValidationCase that contains them | ||
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```{code-cell} | ||
case = ValidationCase(shape=(1,2,3), dtype=float, interface=VideoCase) | ||
case.skip() | ||
``` | ||
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The {func}`.merged_product` iterator automatically excludes any | ||
combinations of interfaces and test parameterizations that should be skipped. | ||
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## Making Fixtures | ||
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Pytest fixtures are a useful way to re-use validation case products. | ||
To keep things tidy, you may want to use marks and ids when creating them | ||
so that you can run tests against specific interfaces or conditions | ||
with the `pytest -m mark` system. | ||
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```python | ||
import pytest | ||
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@pytest.fixture( | ||
params=( | ||
pytest.param( | ||
p, | ||
id=p.id, | ||
marks=getattr(pytest.mark, p.interface.interface.name) | ||
) | ||
for p in iterator | ||
) | ||
) | ||
def my_cases(request): | ||
return request.param | ||
``` |
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