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10 Principles for Data Science Code Review #26

Closed aakankshaduggal closed 2 years ago

aakankshaduggal commented 2 years ago

Overview In this session, the speaker will talk about how code reviews are different for the Data Science Projects and share the 10 best practices for reviewing the Data Science Code.

Speakers @aakankshaduggal

What conference(s) are you submitting this proposal to? Devconf.cz 2022 (#10)

Project repo link, or other relevant resources https://github.com/aicoe-aiops/data-science-workflows

Link to abstract Abstract

Was this proposal accepted?

sesheta commented 2 years ago

Issues go stale after 90d of inactivity. Mark the issue as fresh with /remove-lifecycle stale. Stale issues rot after an additional 30d of inactivity and eventually close.

If this issue is safe to close now please do so with /close.

/lifecycle stale

sesheta commented 2 years ago

Stale issues rot after 30d of inactivity. Mark the issue as fresh with /remove-lifecycle rotten. Rotten issues close after an additional 30d of inactivity.

If this issue is safe to close now please do so with /close.

/lifecycle rotten

sesheta commented 2 years ago

Rotten issues close after 30d of inactivity. Reopen the issue with /reopen. Mark the issue as fresh with /remove-lifecycle rotten.

/close

sesheta commented 2 years ago

@sesheta: Closing this issue.

In response to [this](https://github.com/AICoE/content-pipeline/issues/26#issuecomment-1073416652): >Rotten issues close after 30d of inactivity. >Reopen the issue with `/reopen`. >Mark the issue as fresh with `/remove-lifecycle rotten`. > >/close Instructions for interacting with me using PR comments are available [here](https://git.k8s.io/community/contributors/guide/pull-requests.md). If you have questions or suggestions related to my behavior, please file an issue against the [kubernetes/test-infra](https://github.com/kubernetes/test-infra/issues/new?title=Prow%20issue:) repository.