This is a guide to the process of creating a new release, and is meant for the maintainers of Raster Vision.
The following instructions assume that Python 3 is the default Python on your local system. Using Python 2 will not work.
Minor or Major Version Release#
It’s a good idea to update any major dependencies before the release.
Update the docs if needed. See the docs README for instructions.
masterbranch, re-build the docker image (
docker/build), and push it to ECR (
Execute all tutorial notebooks and make sure they work correctly. Do not commit output changes unless code behavior has changed.
Run all Examples and check that evaluation metrics are close to the scores from the last release. (For each example, there should be a link to a JSON file with the evaluation metrics from the last release.) This stage often uncovers bugs, and is the most time consuming part of the release process. There is a script to help run the examples and collect their outputs. See the associated README for details.
Collect all model bundles, and check that they work with the
predictcommand and sanity check output in QGIS.
Update the Model Zoo by uploading model bundles and sample images to the right place on S3. If you use the
collectcommand (described here), you should be able to sync the
Update the notebooks that use models from the model zoo so that they use the latest version and re-run.
Update tiny_spacenet.py if needed and ensure the line numbers in every
literalincludeof that file are correct. Tip: you can find all instances by searching the repo using the regex:
\.\. literalinclude:: .+tiny_spacenet\.py$.
Test Installation and Quickstart instructions and make sure they work.
Test examples from Writing pipelines and plugins.
rastervision run inprocess rastervision.pipeline_example_plugin1.config1 -a root_uri /opt/data/pipeline-example/1/ --splits 2 rastervision run inprocess rastervision.pipeline_example_plugin1.config2 -a root_uri /opt/data/pipeline-example/2/ --splits 2 rastervision run inprocess rastervision.pipeline_example_plugin2.config3 -a root_uri /opt/data/pipeline-example/3/ --splits 2
Test examples from Bootstrap new projects with a template.
Update the the changelog, and point out API changes.
Fix any broken badges on the GitHub repo readme.
Update the version number. This occurs in several places, so it’s best to do this with a find and replace over the entire repo.
Make a PR to the
masterbranch with the preceding updates. In the PR, there should be a link to preview the docs. Check that they are building and look correct.
Make a git branch with the version as the name, and push to GitHub.
Ensure that the docs are building correctly for the new version branch on readthedocs. You will need to have admin access on your RTD account. Once the branch is building successfully, Under Versions -> Activate a Version, you can activate the version to add it to the sidebar of the docs for the latest version. (This might require manually triggering a rebuild of the docs.) Then, under Admin -> Advanced Settings, change the default version to the new version.
GitHub Actions is supposed to publish an image whenever there is a push to a branch with a version number as the name. If this doesn’t work or you want to publish it immediately, then you can manually make a Docker image for the new version and push to Quay. For this you will need an account on Quay.io under the Azavea organization.
./docker/build docker login quay.io docker tag raster-vision-pytorch:latest quay.io/azavea/raster-vision:pytorch-<version> docker push quay.io/azavea/raster-vision:pytorch-<version>
Make a GitHub tag and release using the previous release as a template.
Publish all packages to PyPI. This step requires twine which you can install with
pip install twine
To store settings for PyPI you can setup a
[pypi] username = azavea
Once packages are published they cannot be changed so be careful. (It’s possible to practice using testpypi.) Navigate to the
raster-visionrepo on your local filesystem. With the version branch checked out, run something like the following to publish each plugin, and then the top-level package.
cd $RV/rastervision_pipeline python setup.py sdist bdist_wheel twine upload dist/*
cd $RV/rastervision_aws_batch python setup.py sdist bdist_wheel twine upload dist/*
cd $RV/rastervision_aws_s3 python setup.py sdist bdist_wheel twine upload dist/*
cd $RV/rastervision_core python setup.py sdist bdist_wheel twine upload dist/*
cd $RV/rastervision_pytorch_learner python setup.py sdist bdist_wheel twine upload dist/*
cd $RV/rastervision_pytorch_backend python setup.py sdist bdist_wheel twine upload dist/*
cd $RV/rastervision_gdal_vsi python setup.py sdist bdist_wheel twine upload dist/*
cd $RV python setup.py sdist bdist_wheel twine upload dist/*
Announce new release in our forum, and with blog post if it’s a big release.
Make a PR to the master branch that updates the version number to the next development version. For example, if the last release was
0.20.1, update the version to
Bug Fix Release#
This describes how to create a new bug fix release, using incrementing from 0.8.0 to 0.8.1 as an example. This assumes that there is already a branch for a minor release called
To create a bug fix release (version 0.8.1), we need to backport all the bug fix commits on the
masterbranch that have been added since the last bug fix release onto the
0.8branch. For each bug fix PR on
master, we need to create a PR against the
0.8branch based on a branch of
0.8that has cherry-picked the commits from the original PR. The title of the PR should start with [BACKPORT].
Make and merge a PR against
master) that increments the version in each
0.8.1. Then wait for the
0.8branch to be built by GitHub Actions and the
0.8Docker images to be published to Quay. If that is successful, we can proceed to the next steps of actually publishing a release.
Using the GitHub UI, make a new release. Use
0.8.1as the tag, and the
0.8branch as the target.
Publish the new version to PyPI. Follow the same instructions for PyPI that are listed above for minor/major version releases.