dc
8ed51607a8
Six findings from the review of #510, each checked against the synthetic estate's own public/getddl response before being changed: - the download is an application/text attachment, not octet-stream, and the filename is unquoted: the estate sends `content-type: application/text` and `content-disposition: attachment; filename=<libref>_<ds>.ddl` - the DDL header timestamp is the session's local time, as %sysfunc(datetime(), datetime19.) is, not UTC - the estate answers 07NOV2025:22:27 where UTC getters give 21:27, and the projection masks the comment, so nothing else could see the drift - the headers are written after the DDL is generated, as %mp_streamfile runs after %mp_ds2ddl, so nothing is sent before a request that cannot produce a file has aborted - the refusal of an unknown flavour was invented: getddl.sas passes it to mp_ds2ddl, which has branches for SAS, TSQL and PGSQL only and leaves the file holding its opening comment. The estate answers that as a 200 download, and the mock now does too; a new parity scenario, unknown_flavour, pins it - the "all forty control tables" claim in the DDL comment overstated what the committed goldens show: MPE_TABLES is the table recorded, in three flavours - getcols: drop the dead `libref = knownLib` assignment Tests: node --test sas/mocks/test/*.test.js - 133 pass, 0 fail, and parity/check.js reports 0 differences for every getddl scenario.
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).