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How to release plotly packages

There are 3 Python packages (plotly, plotly-geo and chart-studio) which need to be published to PyPI and conda, and 2 JS packages (jupyterlab-plotly and plotlywdiget) which need to be published to NPM. In addition, there are various changelogs, github releases and forum announcements to do :)

Release process - plotly package and extensions

This is the release process for releasing plotly.py version X.Y.Z with plotlywidget/jupyterlab-plotly with matching versions.

Note: it's easier to lock all three versions together, even if it means we occasionally push no-change versions to NPM/PyPI/Conda.

Create a release branch

After all of the functionality for the release has been merged into master, create a branch named release_X.Y.Z. This branch will become the final version

Finalize changelog

Review the contents of packages/python/plotly/CHANGELOG.md. We try to follow the keepachangelog guidelines. Make sure the changelog includes the version being published at the top, along with the expected publication date.

Use the Added, Changed, Deprecated, Removed, Fixed, and Security labels for all changes to plotly.py. If the version of plotly.js has been updated, include this as the first Updated entry. Call out any noteable changes as sub-bullets (new trace types in particular), and provide a link to the plotly.js CHANGELOG.

As the first entry in the changelog, include a JupyterLab Versions section. Here, document the versions of plotlywidget, @jupyter-widgets/jupyterlab-manager, jupyterlab, and @jupyterlab/plotly-extension that are known to be compatible with this version of plotly.py.

Note: Use the official (not release candidate) versions in the CHANGELOG.

Update README.md installation instructions

Update the installation instructions in the README to the new versions of all of the dependencies. Use the release candidate versions, this way we can point people to the README of the release_X.Y.Z as the instructions for trying out the release candidate.

Note that the conda installation instructions must include "-c plotly/label/test" rather than "-c plotly" in order to install the release candidate version.

Update the doc/python/getting-started.md file with the same version numbers.

Commit Changelog, README and getting-started updates.

Bump to release candidate version

  1. Manually update the versions to X.Y.Z-rc.1 in the files specified below.
  • packages/python/plotly/plotly/_widget_version.py:
    • Update __frontend_version__ to ^X.Y.Z-rc.1 (Note the ^ prefix)
  • packages/javascript/plotlywidget/package.json
    • Update "version" to X.Y.Z-rc.1
    • Ensure you're using node version 12 and npm version 6 to minimize diffs to package-lock.json
    • Run rm -rf node_modules && npm install && npm run build
  • packages/javascript/jupyterlab-plotly/package.json
    • Update "version" to X.Y.Z-rc.1
    • Ensure you're using node version 12 and npm version 6 to minimize diffs to package-lock.json
    • Run rm -rf node_modules && npm install && npm run build

  1. Commit the changes

  2. Tag this commit on the release branch as vX.Y.Zrc1

In both cases rc is the semantic versioning code for Release Candidate.

The number 1 means that this is the first release candidate, this number can be incremented if we need to publish multiple release candidates. Note that the npm suffix is -rc.1 and the PyPI suffix is rc1.

Publishing plotly.py and plotlywidget as release candidates allows us to go through the publication process, and test that the installed packages work properly before general users will get them by default. It also gives us the opportunity to ask specific users to test that their bug reports are in fact resolved before we pull the trigger on the official release.

Publish release candidate to PyPI

To upload to PyPI you'll also need to have twine installed:

(plotly_dev) $ pip install twine

And, you'll need to be a maintainer on PyPI. Then, from inside the repository:

(plotly_dev) $ cd packages/python/plotly
(plotly_dev) $ git checkout release_X.Y.Z
(plotly_dev) $ git stash
(plotly_dev) $ rm -rf dist
(plotly_dev) $ python setup.py sdist bdist_wheel
(plotly_dev) $ rm dist/*dirty*
(plotly_dev) $ twine upload dist/plotly-X.Y.Zrc1*

Note: this will intentionally fail if your current git tree is dirty, because we want the tag to reflect what is being released, and the version number comes from the tag and the dirty-state.

Publish release candidate of JS Extensions to NPM

Now, publish the release candidate of the extensions to NPM.

cd ./packages/javascript/plotlywidget
npm run build && npm publish --access public --tag next

The --tag next part ensures that users won't install this version unless they explicitly ask for the version or for the version wtih the next tag.

Do the same in the jupyterlab-plotly directory.

Publish release candidate to plotly anaconda channel

To publish package to the plotly anaconda channel you'll need to have the anaconda or miniconda distribution installed, and you'll need to have the anaconda-client package installed.

(plotly_dev) $ conda config --set anaconda_upload no
(plotly_dev) $ conda build recipe/

Next run anaconda login and enter the credentials for the plotly anaconda channel.

Then upload artifacts to the anaconda channel using the test label. Using the test label will ensure that people will only download the release candidate version if they explicitly request it.

$ anaconda upload --label test /path/to/anaconda3/conda-bld/noarch/plotly-*.tar.bz2

Then logout with anaconda logout

Manually test the release candidate

Create a fresh virtual environment (or conda environment) and install the release candidate by following the new README.md instructions (the instructions updated above to include the release candidate versions)

Run through the example notebooks at https://github.com/jonmmease/plotly_ipywidget_notebooks using the classic notebook and JupyterLab. Make sure FigureWidget objects are displayed as plotly figures, and make sure the in-place updates and callbacks work.

If appropriate, ask users who have submitted bug reports or feature requests that are resolved in this version to try out the release candidate.

If problems are found in the release candidate, fix them on the release branch and then publish another release candidate with the candidate number incremented.

Finalize CHANGELOG and README

Update CHANGELOG with release date and update README with final versions.

In the conda installation instructions, be sure to change the "-c plotly/label/test" argument to "-c plotly"

Update the doc/python/getting-started.md file with the same version numbers.

Commit Changelog, README and getting-started updates.

Finalize versions

When no problems are identified in the release candidate, remove the release candidate suffix from the following version strings:

  • plotly/_widget_version.py:
    • Update __frontend_version__ to ^X.Y.Z (Note the ^ prefix)
  • packages/javascript/plotlywidget/package.json
    • Update "version" to X.Y.Z
    • Ensure you're using node version 12 and npm version 6 to minimize diffs to package-lock.json
    • Run rm -rf node_modules && npm install && npm run build
  • packages/javascript/jupyterlab-plotly/package.json
    • Update "version" to X.Y.Z
    • Ensure you're using node version 12 and npm version 6 to minimize diffs to package-lock.json
    • Run rm -rf node_modules && npm install && npm run build
  • Run git diff and ensure that only the files you modified and the build artifacts have changed
  • Ensure that the diff in package-lock.json seems sane
  • Commit and push to the release branch.

Merge release into master

Make sure the integration tests are passing on the release branch, then merge it into master on GitHub.

Make sure tests also pass on master, then update your local master, tag this merge commit as vX.Y.Z (e.g. v3.1.1)

push the tag.

(plotly_dev) $ git checkout master
(plotly_dev) $ git stash
(plotly_dev) $ git pull origin master
(plotly_dev) $ git tag vX.Y.Z
(plotly_dev) $ git push origin vX.Y.Z

Publishing to PyPI

Publish the final version to PyPI

(plotly_dev) $ cd packages/python/plotly
(plotly_dev) $ rm -rf dist
(plotly_dev) $ python setup.py sdist bdist_wheel
(plotly_dev) $ rm dist/*dirty*
(plotly_dev) $ twine upload dist/plotly-X.Y.Z*

Note: this will intentionally fail if your current git tree is dirty, because we want the tag to reflect what is being released, and the version number comes from the tag and the dirty-state.

After it has uploaded, move to another environment and double+triple check that you are able to upgrade ok:

$ pip install plotly --upgrade

And ask one of your friends to do it too. Our tests should catch any issues, but you never know.

Publish JS Extensions to NPM

Finally, publish the final version of the extensions to NPM with:

cd packages/javascript/jupyterlab-plotly
npm run build && npm publish --access public
cd packages/javascript/plotlywidget
npm run build && npm publish --access public

Publishing to the plotly conda channel

Follow the anaconda upload instructions as described for the release candidate above, except:

  • Do not include the --label test argument when uploading
$ anaconda upload /path/to/anaconda3/conda-bld/noarch/plotly-*.tar.bz2

Add GitHub Release entry

Go to https://github.com/plotly/plotly.py/releases and "Draft a new release"

Enter the vX.Y.Z tag

Make "Release title" the same string as the tag.

Copy changelog section for this version as the "Describe this release"

Upgrade doc requirements and API doc

Files to be updated:

  • doc/apidoc/conf.py with new version number
  • doc/requirements.txt
  • binder/requirements.txt

Synchronize master and doc-prod branches

doc-prod should already have been merged on a regular basis into master, but start doing it first. Then merge master into doc-prod to deploy the doc related to features in the release.

Post announcement

Post an announcement to the Plotly Python forum, with links to the README installation instructions and to the CHANGELOG.

Release process - plotly-geo package

The plotly-geo package contains the shape file resources used by plotly.py. These files are relatively large and change infrequently so it is useful to release them in a separate package.

Update version

Update the version of the plotly-geo package in packages/python/plotly-geo/setup.py.

This version is not intended to match the version of plotly.py.

Update CHANGELOG

Add a new entry to the CHANGELOG at packages/python/plotly-geo/CHANGELOG.md and commit the changes.

Tag Release

Create a new tag for the release

(plotly_dev) $ git checkout master
(plotly_dev) $ git stash
(plotly_dev) $ git pull origin master
(plotly_dev) $ git tag plotly-geo-vX.Y.Z
(plotly_dev) $ git push origin plotly-geo-vX.Y.Z

Publishing to PYPI

Publish the final version to PyPI

(plotly_dev) $ cd packages/python/plotly-geo
(plotly_dev) $ python setup.py sdist bdist_wheel
(plotly_dev) $ twine upload dist/plotly-geo-X.Y.Z.tar.gz
(plotly_dev) $ twine upload dist/plotly_geo-X.Y.Z-py3-none-any.whl

Publish to plotly anaconda channel

From packages/python/plotly-geo, build the conda packge

(plotly_dev) $ conda build recipe/

Then upload to the plotly anaconda channel as described above

Release process - chart-studio package

The chart-studio package contains the utilities for interacting with Chart Studio (both Cloud or On-Prem).

Update version

Update the version of the chart-studio package in packages/python/chart-studio/setup.py.

This version is not intended to match the version of plotly.py.

Update CHANGELOG

Add a new entry to the CHANGELOG at packages/python/chart-studio/CHANGELOG.md and commit the changes.

Tag Release

Create a new tag for the release

(plotly_dev) $ git checkout master
(plotly_dev) $ git stash
(plotly_dev) $ git pull origin master
(plotly_dev) $ git tag chart-studio-vX.Y.Z
(plotly_dev) $ git push origin chart-studio-vX.Y.Z

Publishing to PYPI

Publish the final version to PyPI

(plotly_dev) $ cd packages/python/chart-studio
(plotly_dev) $ python setup.py sdist bdist_wheel
(plotly_dev) $ twine upload dist/chart-studio-X.Y.Z.tar.gz
(plotly_dev) $ twine upload dist/chart_studio-X.Y.Z-py3-none-any.whl

Publish to plotly anaconda channel

From packages/python/plotly-geo, build the conda packge

(plotly_dev) $ conda build recipe/

Then upload to the plotly anaconda channel as described above.