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some docs
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31
docs/_static/css/notebooks.css
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docs/_static/css/notebooks.css
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div.cell.tag_hide-cell details.above-input > summary,
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div.cell.tag_hide-input details.above-input > summary,
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div.cell.tag_hide-output details.below-input > summary{
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background-color: var(--color-admonition-title-background--admonition-todo);
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color: var(--color-content-foreground);
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border: unset;
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border-left: 2px solid var(--mystnb-source-margin-color);
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opacity: unset;
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padding: 0.25em 0 0.25em 1em;
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}
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div.cell.tag_hide-cell details.above-input > summary > span,
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div.cell.tag_hide-input details.above-input > summary > span,
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div.cell.tag_hide-output details.below-input > summary > span
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{
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opacity: unset;
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}
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div.cell details.above-input div.cell_input {
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border: unset;
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background-color: unset;
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border-left: 2px solid var(--mystnb-source-margin-color);
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}
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div.cell details.above-input div.cell_input div.highlight {
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background: var(--color-admonition-background);
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}
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.output.text_html pre {
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font-size: 0.8em;
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}
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@ -2,7 +2,18 @@
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Utilities for testing and 3rd-party interface development.
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See also the [narrative testing docs](../../contributing/testing.md)
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```{toctree}
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:maxdepth: 2
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cases
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helpers
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interfaces
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```
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```{eval-rst}
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.. automodule:: numpydantic.testing
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:members:
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:undoc-members:
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```
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7
docs/api/testing/interfaces.md
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7
docs/api/testing/interfaces.md
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# interfaces
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```{eval-rst}
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.. automodule:: numpydantic.testing.interfaces
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:members:
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:undoc-members:
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```
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@ -49,6 +49,7 @@ intersphinx_mapping = {
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html_theme = "furo"
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html_static_path = ["_static"]
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html_css_files = ["css/notebooks.css"]
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# autodoc
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autodoc_pydantic_model_show_json_error_strategy = "coerce"
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5
docs/contributing/coc.md
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5
docs/contributing/coc.md
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# Code of Conduct
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```{todo}
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jonny write the code of conduct
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```
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docs/contributing/index.md
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docs/contributing/index.md
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# Contributing
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```{toctree}
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coc
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process
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interface
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testing
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```
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docs/contributing/interface.md
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5
docs/contributing/interface.md
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# Writing an Interface
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```{todo}
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Jonny write the interface contrib docs
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```
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docs/contributing/process.md
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15
docs/contributing/process.md
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# Contribution Process
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```{todo}
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Jonny write the contribution docs
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```
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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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213
docs/contributing/testing.md
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213
docs/contributing/testing.md
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@ -0,0 +1,213 @@
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---
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file_format: mystnb
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mystnb:
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output_stderr: remove
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render_text_lexer: python
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render_markdown_format: myst
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myst:
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enable_extensions: ["colon_fence"]
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---
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# Testing
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```{code-cell}
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---
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tags: [hide-cell]
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---
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from pathlib import Path
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from rich.console import Console
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from rich.theme import Theme
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from rich.style import Style
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from rich.color import Color
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theme = Theme({
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"repr.call": Style(color=Color.from_rgb(110,191,38), bold=True),
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"repr.attrib_name": Style(color="slate_blue1"),
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"repr.number": Style(color="deep_sky_blue1"),
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"repr.none": Style(color="bright_magenta", italic=True),
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"repr.attrib_name": Style(color="white"),
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"repr.tag_contents": Style(color="light_steel_blue"),
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"repr.str": Style(color="violet")
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})
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console = Console(theme=theme)
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```
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```{note}
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Also see the [`numpydantic.testing` API docs](../api/testing/index.md)
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and the [Writing an Interface](../interfaces.md) guide
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```
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Numpydantic exposes a system for combinatoric testing across dtypes, shapes,
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and interfaces in the {mod}`numpydantic.testing` module.
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These helper classes and functions are included in the distributed package
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so they can be used for downstream development of independent interfaces
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(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
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validation cases can be merged together, but also used independently
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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
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{attr}`~.ValidationCase.annotation_shape` specifies how the
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{class}`.NDArray` {attr}`.ValidationCase.annotation` that is used to test
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against is generated
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- **Array specification:** {attr}`~.ValidationCase.dtype` and {attr}`~.ValidationCase.shape`
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specify that array that will be generated to test against the annotation
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- **Interface specification:** An {class}`.InterfaceCase` that refers to
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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
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a shape along with an annotation shape (or implicitly against the defaults for either),
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along with a value for `passes` that indicates if that combination is valid.
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```{code-cell}
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from numpydantic.testing import ValidationCase
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dtype_case = ValidationCase(
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id="int_int",
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dtype=int,
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annotation_dtype=int,
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passes=True
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)
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shape_case = ValidationCase(
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id="cool_shape",
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shape=(1,2,3),
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annotation_shape=(1,"*","2-4"),
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passes=True
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)
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merged = dtype_case.merge(shape_case)
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console.print(merged.model_dump(exclude={'annotation', 'model'}, exclude_unset=True))
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```
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When merging validation cases, the merged case only `passes` if all the
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original cases do.
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```{code-cell}
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from numpydantic.testing import ValidationCase
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dtype_case = ValidationCase(
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id="int_int",
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dtype=int,
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annotation_dtype=int,
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passes=True
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)
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shape_case = ValidationCase(
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id="uncool_shape",
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shape=(1,2,3),
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annotation_shape=(9,8,7),
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passes=False
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)
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merged = dtype_case.merge(shape_case)
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console.print(merged.model_dump(exclude={'annotation', 'model'}, exclude_unset=True))
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```
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We provide a convenience function {func}`.merged_product` for creating a merged product of
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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
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against all combinations
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```{code-cell}
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from numpydantic.testing.helpers import merged_product
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dtype_cases = [
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ValidationCase(dtype=int, annotation_dtype=int, passes=True),
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ValidationCase(dtype=int, annotation_dtype=float, passes=False)
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]
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shape_cases = [
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ValidationCase(shape=(1,2,3), annotation_shape=(1,2,3), passes=True),
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ValidationCase(shape=(4,5,6), annotation_shape=(1,2,3), passes=False)
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]
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iterator = merged_product(dtype_cases, shape_cases)
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console.print([i.model_dump(exclude_unset=True, exclude={'model', 'annotation'}) for i in iterator])
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```
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You can pass constraints to the {func}`.merged_product` iterator to
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filter cases that match some value, for example to get only the cases that pass:
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```{code-cell}
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iterator = merged_product(dtype_cases, shape_cases, conditions={"passes": True})
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console.print([i.model_dump(exclude_unset=True, exclude={'model', 'annotation'}) for i in iterator])
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```
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## Interface Cases
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Validation cases can be paired with interface cases that handle
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generating arrays for the given interface from the specification in the
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validation case.
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Since some array interfaces like Zarr have multiple possible forms
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of an array (in memory, on disk, in a zip file, etc.) an interface
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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,
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creating an array, and returning the appropriate input type for the interface:
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```{code-cell}
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from numpydantic.testing.interfaces import NumpyCase, ZarrNestedCase
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NumpyCase.make_array(shape=(1,2,3), dtype=float)
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```
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```{code-cell}
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ZarrNestedCase.make_array(shape=(1,2,3), dtype=float, path=Path("__tmp__/zarr_dir"))
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```
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Interface cases also define when an interface should skip a given test
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parameterization. For example, some array formats can't support arbitrary
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object serialization, and the video class can only support 8-bit arrays
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of a specific shape
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```{code-cell}
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from numpydantic.testing.interfaces import VideoCase
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VideoCase.skip(shape=(1,1), dtype=float)
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```
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This, and the array generation methods are propagated up into
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a ValidationCase that contains them
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```{code-cell}
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case = ValidationCase(shape=(1,2,3), dtype=float, interface=VideoCase)
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case.skip()
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```
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The {func}`.merged_product` iterator automatically excludes any
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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.
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To keep things tidy, you may want to use marks and ids when creating them
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so that you can run tests against specific interfaces or conditions
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with the `pytest -m mark` system.
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```python
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import pytest
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@pytest.fixture(
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params=(
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pytest.param(
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p,
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id=p.id,
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marks=getattr(pytest.mark, p.interface.interface.name)
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)
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for p in iterator
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)
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)
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def my_cases(request):
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return request.param
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```
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@ -514,6 +514,7 @@ api/meta
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api/schema
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api/serialization
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api/types
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api/testing/index
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```
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@ -523,6 +524,7 @@ api/types
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:hidden: true
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changelog
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contributing/index
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development
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todo
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```
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@ -83,6 +83,9 @@ SHAPE_CASES = (
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id="Union incorrect both",
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),
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)
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"""
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Base Shape cases
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"""
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DTYPE_CASES = [
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annotation_dtype=UNION_TYPE, dtype=str, passes=False, id="union-type-str"
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),
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]
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"""
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Base Dtype cases
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"""
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if YES_PIPE:
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ValidationCase(interface=ZarrNestedCase, id="zarr_nested"),
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ValidationCase(interface=VideoCase, id="video"),
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]
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"""
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All the interface cases
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"""
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DTYPE_AND_SHAPE_CASES = merged_product(SHAPE_CASES, DTYPE_CASES)
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"""
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Merged product of dtype and shape cases
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"""
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DTYPE_AND_SHAPE_CASES_PASSING = merged_product(
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SHAPE_CASES, DTYPE_CASES, conditions={"passes": True}
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)
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"""
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Merged product of dtype and shape cases that are valid
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"""
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DTYPE_AND_INTERFACE_CASES = merged_product(INTERFACE_CASES, DTYPE_CASES)
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"""
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Merged product of dtype and interface cases
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"""
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DTYPE_AND_INTERFACE_CASES_PASSING = merged_product(
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INTERFACE_CASES, DTYPE_CASES, conditions={"passes": True}
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)
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"""
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Merged product of dtype and interface cases that pass
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"""
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ALL_CASES = merged_product(SHAPE_CASES, DTYPE_CASES, INTERFACE_CASES)
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"""
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Merged product of all cases - dtype, shape, and interface
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"""
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ALL_CASES_PASSING = merged_product(
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SHAPE_CASES, DTYPE_CASES, INTERFACE_CASES, conditions={"passes": True}
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)
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"""
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Merged product of all cases, but only those that pass
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"""
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