dc
bcb8fde986
Review feedback on this PR. - The fallback list bypassed mergeColsRules, so col.TYPE was never set and every column reached the picker as char: char operators for numerics, and unquoted character values, which %mp_filtercheck rejects on the value list and on the submit alike. getcols.sas and the mock now emit TYPE in the client's vocabulary - char for C, num for N/DATE/DATETIME/TIME - and the cypress case no longer stops at selecting the variable: it sets a value, submits, and asserts the applied clause reads SITE_NAME = 'Bristol', so the quoting is the assertion. - The temporal exclusion is dropped, matching getdata.sas and viewdata.sas, whose cols payloads include those columns - the drop is on the data, not on the cols. The mock's getdata.js cols had the same divergence and is aligned; it keeps the exclusion for the rows. That also removes the SAS/mock disagreement on the excluded set, since there is no set. - client/.npmrc added with ignore-scripts and save-exact (plus legacy-peer-deps and fund, matching the root), so a local `cd client && npm i` is guarded the way the CI's is. Verified against the running mock: for MPE_CONFIG (TXTEMPORAL) getcols returns TX_FROM/TX_TO with TYPE=num and DDTYPE=DATETIME, the char columns as TYPE=char, and editors/getdata returns cols including both temporal columns while the rows still exclude them. row-cell-limits.cy.ts is 5/5.
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).