Tuesday, May 31, 2022 From rOpenSci (https://ropensci.org/blog/2022/05/31/chatops-review-system-github/). Except where otherwise noted, content on this site is licensed under the CC-BY license.
Anyone can contribute a software package to the rOpenSci suite as long as it fits our scope (research lifecycle software and statistical software) for a transparent, constructive, nonadversarial and open review. In practice, the review steps are all recorded in GitHub issue threads (example). Software peer-review involves coordinating and tracking many moving parts: software submissions (new issues), testing and diagnostics, assignment of editors and reviewers, and logging the progression of submissions through revisions and acceptance.
Our editorial workflow has been significantly enhanced with the use of ✨ automation ✨ .
To ensure that a package meets our compliance standards, we would previously clone the repository locally, install dependencies, run manual checks, gather the results, and copy-paste them into the issue thread. Now we can accomplish the same outcome with just a simple command into a GitHub issue comment:
@ropensci-review-bot check package
Similarly, we can use the following command to register a reviewer named in the submission issue metadata (filling YAML data) as well as in our Airtable database.
@ropensci-review-bot add @maelle to reviewers
Feeling inspired? Maybe you run a submission process (of papers, software, conference abstracts) that is handled in GitHub issue (or pull request) threads (or could be moved there)?
In that case, maybe you could benefit from the same toolset as us: chat-ops where a GitHub “bot” account performs actions dictated by human-typed commands, orchestrated by a Ruby app deployed on a cloud platform.
In this post, we explain how to assess whether that app framework, the editorial bot generator Buffy, might be right for you. We detail the steps involved in setting up “chat-ops” with Buffy for your own needs.
The editorial bot generator Buffy is the tool that supports the aforementioned commands. It is a Ruby codebase that can be
Every time a new issue is opened, every time an issue comment is created, its contents are sent to the deployed app. If it corresponds to the regular expression of a registered command, predefined steps are launched: a check is launched somewhere, a database is updated, information is copied back to the GitHub issue, etc.
The “visible” bot is the GitHub account used as bot face: commands are addressed to it, and it uses a “Personal” Access to post GitHub issue comments.
The Journal of Open Source Software (JOSS) has developed an initial list of possible commands/actions, also known as responders. One can create new responders by writing Ruby code following documented instructions. Note that one of the responders allows launching a GitHub Action Workflow which can circumvent the absence of Ruby knowledge on a team – although a pure Ruby responder might be faster. You can also send a call to any API, so if you can build an external API, you can really implement many things.
Journal of Open Source Software (JOSS) – original instigators of Buffy!
JuliaCon is migrating soon.
We shall first show how Buffy usage works, afterwards, we shall go into details about how to get there. The following diagram represents the whole automation toolset we use for rOpenSci software peer-review.
We can observe, on the left, a GitHub issue thread corresponding to a submission. The submission has
Every time an issue is created or updated with a new comment, information about that event is sent to the central app via a webhook. There on Heroku, if the comment corresponds to a registered command, actions (the formerly tedious steps 🙂) are made accordingly. Possible actions include filling an Airtable base via Airtable API, launching an external software check on a plumber API, inviting the author to the ropensci GitHub organization, posting a comment back into the GitHub issue thread with some results or confirmation.
How does one achieve this?
Follow Buffy installation instructions.
ropensci. The organization does not have to be where the review repository also lives.
As mentioned in the docs, at this stage in your test review repository you can write the following comment (replace the username with your bot account username)
What if it does not work?
Now comes the time to adapt your Buffy version to your needs! Good news: you can keep doing this forever depending on how your needs evolve. Bad news: you will keep doing this forever as you’ll always see opportunities for improvement. 😉
To configure your Buffy installation you will be making changes in these places
/config/settings-production.ymlfile of the branch of your buffy fork;
.github/ISSUE_TEMPLATE) or PR templates (
.github/PULL_REQUEST_TEMPLATE) and buffy templates
.buffy/templatesof your review repository (or repositories, if you created a test review repository for experimenting with Buffy, which we’d recommend). Indeed, issue or PR templates will contain placeholders/wrappers for HTML variables like
<!--editor--> <!--end-editor-->– otherwise the bot won’t be able to fill this information. buffy templates are for comments you will want the bot to post, for instance, a checklist at the end of the review process.
Follow Buffy docs on configuration.
You will be adding (registering) responders by adding them to the YAML file
/config/settings-production.yml, with subfields indicating some options.
For instance, you might want to use the “assign editor” responder to store the editor username in the issue comment without assigning the issue to them so you’ll set
You’ll find responders and their parameters in Buffy docs. You can also check out the readthedocs website of rOpenSci’s version of Buffy in case some of our custom responders are relevant for you (they are at the bottom of the list, with rOpenSci in front of their name).
After each responder addition or configuration, try it out by creating issues (or pull requests if that’s your process) and typing comments in them. If it works, you will be convinced you have added one feature to your system, congratulations!
Afterward, the feature should be officially released by telling actors of your system about it. In our case, we wrote announcements in the slack channel we have for editors, and we updated our dev guide. Updating guidance is particularly rewarding as bot commands typically replace lines of tedious task descriptions. 😁
In this post, we presented the editorial bot generator Buffy. We hope to make it easier for you to choose whether to adopt it for your own submission system and to know how to adopt it. The costs linked to Buffy usage are:
In our experience, adopting Buffy has been worth it as once it’s well adopted, it
Feel free to comment with any questions you might have about Buffy!