ML4GW / ML4GW/DeepClean

Branching and release cycles

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Dominant language
Python
Stars
10
Forks
6
PR merge metrics
No merged PRs in 30d

Description

Once DeepClean is put into production, new code should be released at a fixed, infrequent cadence (say, monthly), with complete guarantees of stability and correctness. This code should be kept in the main branch, which should trigger a release build every time it gets pushed to.

However, we'll likely want to update ongoing experiments and other libraries more frequently to share among all forks. I propose we maintain a dev branch (or some similar name) on the upstream repo to which forked PRs are submitted. For each release, this branch submits a PR to main, which runs extensive testing and QA of the production pipeline, and then merges it.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No files, tests, or automation entry points are named. Start by locating the repository's current branch and release-build configuration, then compare it with the proposed dev-to-main PR flow; done means an agreed cadence and a documented, validated release process.

Written by the indexing model from the issue text.

Assessment

Tech stack
git, github
Domain
ci-cd, devops, release
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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