Move linting configuration to .cicd-env file #13
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If we add a file like this, we also need to include it in For clarity, this change is mainly for compatibility with |
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Good to know, I'll get it added to |
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Description
This is a super-simple change that moves the linting configuration from the GitHub workflow file to a new
.cicd-envfile. There are no "real" changes to this package.I added a flag to skip the "no repositories named
public-orprivate-" test. For backwards compatibility that test currently only produces a warning, but once we either rename or add specific ignore rules to each offending repo we can properly enable it.This change enables the new
bllintscript from https://github.com/uclahs-cds/docker-CICD-base/pull/60 to lint a checked-out copy of this repository for easier development.Checklist
This PR does NOT contain Protected Health Information (PHI). A repo may need to be deleted if such data is uploaded.
Disclosing PHI is a major problem1 - Even a small leak can be costly2.
This PR does NOT contain germline genetic data3, RNA-Seq, DNA methylation, microbiome or other molecular data4.
.png, .jpeg),.pdf,.RData,.xlsx,.doc,.ppt, or other output files.To automatically exclude such files using a .gitignore file, see here for example.
I have read the code review guidelines and the code review best practice on GitHub check-list.
I have set up or verified the
mainbranch protection rule following the github standards before opening this pull request.The name of the branch is meaningful and well formatted following the standards, using [AD_username (or 5 letters of AD if AD is too long)]-[brief_description_of_branch].
I have added the major changes included in this pull request to the
CHANGELOG.mdunder the next release version or unreleased, and updated the date.Footnotes
UCLA Health reaches $7.5m settlement over 2015 breach of 4.5m patient records ↩
The average healthcare data breach costs $2.2 million, despite the majority of breaches releasing fewer than 500 records. ↩
Genetic information is considered PHI.
Forensic assays can identify patients with as few as 21 SNPs ↩
RNA-Seq, DNA methylation, microbiome, or other molecular data can be used to predict genotypes (PHI) and reveal a patient's identity. ↩