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Merge pull request #198 from asmeurer/dev-docs-updates
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Some updates to the dev docs
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asmeurer authored Nov 12, 2024
2 parents 7d3c73c + 720fa06 commit c8b24db
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14 changes: 14 additions & 0 deletions docs/_static/custom.css
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Expand Up @@ -10,3 +10,17 @@ body {
html {
scroll-behavior: auto;
}

/* Make checkboxes from the tasklist extension ('- [ ]' in Markdown) not add bullet points to the checkboxes.
This can be removed once https://github.com/executablebooks/mdit-py-plugins/issues/59 is addressed.
*/

.contains-task-list {
list-style: none;
}

/* Make the checkboxes indented like they are bullets */
.task-list-item-checkbox {
margin: 0 0.2em 0.25em -1.4em;
}
3 changes: 2 additions & 1 deletion docs/conf.py
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Expand Up @@ -38,7 +38,8 @@
templates_path = ['_templates']
exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']

myst_enable_extensions = ["dollarmath", "linkify"]
myst_enable_extensions = ["dollarmath", "linkify", "tasklist"]
myst_enable_checkboxes = True

napoleon_use_rtype = False
napoleon_use_param = False
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14 changes: 14 additions & 0 deletions docs/dev/implementation-notes.md
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Expand Up @@ -47,3 +47,17 @@ identical PyTorch uses a similar layout in `array_api_compat/torch/`, but it
differs enough from NumPy/CuPy that very few common wrappers for those
libraries are reused. Dask is close to NumPy in behavior and so most Dask
functions also reuse the NumPy/CuPy common wrappers.

Occasionally, a wrapper implementation will need to reference another wrapper
implementation, rather than the base `xp` version. The easiest way to do this
is to call `array_namespace`, like

```py
wrapped_xp = array_namespace(x)
wrapped_xp.wrapped_func(...)
```

Also, if there is a very minor difference required for wrapping, say, CuPy and
NumPy, they can still use a common implementation in `common/_aliases.py` and
use the `is_*_namespace()` or `is_*_function()` [helper
functions](../helper-functions.rst) to branch as necessary.
129 changes: 89 additions & 40 deletions docs/dev/releasing.md
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@@ -1,59 +1,108 @@
# Releasing

To release, first make sure that all CI tests are passing on `main`.
- [ ] **Create a PR with a release branch**

Note that CuPy must be tested manually (it isn't tested on CI). Use the script
This makes it easy to verify that CI is passing, and also gives you a place
to push up updates to the changelog and any last minute fixes for the
release.

```
./test_cupy.sh
```
- [ ] **Double check the release branch is fully merged with `main`.**

on a machine with a CUDA GPU.
(e.g., if the release branch is called `release`)

Once you are ready to release, create a PR with a release branch, so that you
can verify that CI is passing. You must edit
```
git checkout main
git pull
git checkout release
git merge main
```

```
array_api_compat/__init__.py
```
- [ ] **Make sure that all CI tests are passing.**

and update the version (the version is not computed from the tag because that
would break vendorability). You should also edit
Note that the GitHub action that publishes to PyPI does not check if CI is
passing before publishing. So you need to check this manually.

```
docs/changelog.md
```
This does mean you can ignore CI failures, but ideally you should fix any
failures or update the `*-xfails.txt` files before tagging, so that CI and
the CuPy tests fully pass. Otherwise it will be hard to tell what things are
breaking in the future. It's also a good idea to remove any xpasses from
those files (but be aware that some xfails are from flaky failures, so
unless you know the underlying issue has been fixed, an xpass test is
probably still xfail).

with the changes for the release.
- [ ] **Test CuPy.**

Once everything is ready, create a tag
CuPy must be tested manually (it isn't tested on CI, see
https://github.com/data-apis/array-api-compat/issues/197). Use the script

```
git tag -a <version>
```
```
./test_cupy.sh
```

(note the tag names are not prefixed, for instance, the tag for version 1.5 is
just `1.5`)
on a machine with a CUDA GPU.

and push it to GitHub

```
git push origin <version>
```
- [ ] **Update the version.**

Check that the `publish distributions` action on the tag build works. Note
that this action will run even if the other CI fails, so you must make sure
that CI is passing *before* tagging.
You must edit

This does mean you can ignore CI failures, but ideally you should fix any
failures or update the `*-xfails.txt` files before tagging, so that CI and the
cupy tests pass. Otherwise it will be hard to tell what things are breaking in
the future. It's also a good idea to remove any xpasses from those files (but
be aware that some xfails are from flaky failures, so unless you know the
underlying issue has been fixed, an xpass test is probably still xfail).
```
array_api_compat/__init__.py
```

If the publish action fails for some reason and didn't upload the release to
PyPI, you will need to delete the tag and try again.
and update the version (the version is not computed from the tag because
that would break vendorability).

After the PyPI package is published, the conda-forge bot should update the
feedstock automatically.
- [ ] **Update the [changelog](../changelog.md).**

Edit

```
docs/changelog.md
```

with the changes for the release.

- [ ] **Create the release tag.**

Once everything is ready, create a tag

```
git tag -a <version>
```

(note the tag names are not prefixed, for instance, the tag for version 1.5 is
just `1.5`)

- [ ] **Push the tag to GitHub.**

*This is the final step. Doing this will build and publish the release!*

```
git push origin <version>
```

This will trigger the [`publish
distributions`](https://github.com/data-apis/array-api-compat/actions/workflows/publish-package.yml)
GitHub Action that will build the release and push it to PyPI.

- [ ] **Check that the [`publish
distributions`](https://github.com/data-apis/array-api-compat/actions/workflows/publish-package.yml)
action build on the tag worked.** Note that this action will run even if the
other CI fails, so you must make sure that CI is passing *before* tagging.

If it failed for some reason, you may need to delete the tag and try again.

- [ ] **Merge the release branch.**

This way any changes you made in the branch, such as updates to the
changelog or xfails files, are updated in `main`. This will also make the
docs update (the docs are published automatically from the sources on
`main`).

- [ ] **Update conda-forge.**

After the PyPI package is published, the conda-forge bot should update the
feedstock automatically after some time. The bot should automerge, so in
most cases you don't need to do anything here, unless some metadata on the
feedstock needs to be updated.

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