dc
f0e3117540
Three values reached `run:` blocks through `${{ }}`, so the runner pasted them
into the script before the shell ever saw it - which makes the value part of the
code rather than an argument to it.
- `BASE="${{ github.base_ref }}"` (build.yaml, lighthouse.yaml) - a ref name in
the script.
- `echo ${{ secrets.SHEET_PWD }} | gpg --passphrase-fd 0` (all four workflows) -
a passphrase in the script. A quote in it ends the quoting, and a command
substitution in it runs.
- two `replace-in-files --replacement=...${{ secrets.CYPRESS_* }}...` lines
(build.yaml, release.yaml) - the same, inside a replacement string.
Each now arrives as a step `env:` value and is expanded as `"$VAR"`, so the shell
only ever sees data. Checked the replacement lines side by side with the old form:
identical for an ordinary value, and the new form keeps a value containing a space
intact where the old one word-splits it, and survives a value containing a single
quote where the old one is a shell syntax error.
The passphrase pipe also moves from `echo` to `printf '%s\n'`, so the byte the
decryption sees does not depend on how the shell's `echo` treats backslashes.
Data Controller for SAS
Control your manual data modifications!
Alternatives to Data Controller include:
- 💾 Developing / testing / deploying / scheduling overnight batch jobs to load files from shared drives
- 🔒 Opening (and locking) datasets in Enterprise Guide or SAS® Table Viewer to perform direct updates
- ❓ Asking a #DBA to run validated code after a change management process
- 🌐 Building & maintaining your own custom web application
- 🏃 Running #SAS or #SQL updates in production
Problems with the above include:
- Legacy 'black box' solutions with little to no testing, documentation or support
- End users requiring direct write access to critical data sources in production
- Upload routines that must be manually modified when the data model changes
- Breaches due to unnecessary parties having access to the data
- Inability to trace who made a change, when, and why
- Reliance on key individuals to perform updates
- Building bespoke ETL for every new data source
- High risk of manual error / data corruption
Data Controller for SAS® solves all these issues in a simple-to-install, user-friendly, secure, documented, battle-tested web application. Available on Viya, SAS 9 EBI, and SASjs Server.
An individual Viya deploy can be done in just 2 lines of #SAS code!
filename dc url "https://git.datacontroller.io/dc/dc/releases/download/latest/viya.sas";
%inc dc;
For a multi-user deploy, using a shared system account, please see deploy docs.
For further information:
- Main site: https://datacontroller.io
- Docs: https://docs.datacontroller.io
- Code: https://code.datacontroller.io
For support, contact support@4gl.io or reach out on Matrix!
Development
Lighthouse CI
This project includes automated Lighthouse performance and accessibility checks that run on pull requests. The checks ensure:
- Accessibility Score: Minimum 1.0 (100%) median score across all tested pages
The Lighthouse CI workflow:
- Sets up the development environment with SASjs server and mocked services
- Builds and serves the Angular frontend
- Installs Chrome and runs
lhci autorun(Lighthouse CI) against key pages - Uploads results as artifacts for review
To run Lighthouse checks locally:
cd client
npm install
npm run lighthouse
Configuration is in client/lighthouserc.js (URL list, desktop preset, Chrome flags, assertions).