Jenner compatibility tests for 3 scripts

[lwsinclair]

Jenneranalytics.com provides an API that runs SAS code, with support for more than 200 SAS procedures. You can also use it with Anthropic Claude Code AI in a collaborative workspace. It's available for Mac on the Apple App Store, and by license for Windows and Linux. The Superfund contaminant analysis and the ACS census cleaning/merge steps from this team's code run on it, and this PR adds them as bundles so you can see for yourself.

Yes, AI was used to develop this PR as is most code in modern businesses today.

We support the larger community by

(1) increasing access to SAS-compatible systems,
(2) by providing test coverage and a test coverage framework to public SAS repos in order to encourage the use of best practices in software engineering.

This PR is our way of giving back to the developers whose code we use to validate the SAS-compatible Jenner system. We test against all SAS code in the world to validate our compatibility. These tests are the way we build our product. But we do not want to just keep them for ourselves: we share some of those tests with the repo owner so that they benefit from the automated test coverage as well.

Everything new lives in a single jenner-check/ directory and touches nothing else in the repo:

jenner-check/
├── README.md
├── run_jenner.sh / run_jenner.bat / run_jenner.sas   # runners
├── t001_superfund_analyses/   # from Superfund_Analyses_v2.sas
├── t002_acs_add_pct/          # from ACS2013_2017_Data_Add_Pct_v2.sas
└── t003_clean_merge_acs/      # from "Cleaning and Merging ACS Data v3.sas"

Each bundle carries the script, a small sample of the same data it reads, and a snapshot of the run. To try one: cd jenner-check && ./run_jenner.sh t001_superfund_analyses (or ./run_jenner.sh --all); there's a one-line curl form in the README if you'd rather not install anything.

I enjoyed reading through this one — the way you flag each contaminant into its own indicator, count it by zip code, and then turn those counts into percentages with divide() is a clean way to sidestep the divide-by-zero trap, and it lines up nicely with joining the EPA Superfund records to the ACS demographics to map exposure by community. The per-year map datasets make the choropleths in the repo easy to follow.

No action needed on your side — merge, close, or ignore as you see fit, and no response is expected. If you'd prefer not to receive PRs like this, just say no-more-prs in any comment or open an issue titled jenner-check: opt out and we'll skip the repo.

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Lawrence W. Sinclair
CEO / Jenner Analytics Ltd
jenneranalytics.com
linkedin.com/in/lwsinclair/