A solo-authored production-level Angular 10 biomanufacturer (undisclosed) lab tool for compiling molecular DNA and protein sequence databases during the molecular antibody fabrication process. Actively used daily by lab technicians and scientists. Employs four levels of Angular environment configurations to accommodate CI/CD, specifically using in-memory-web-db for code implementation, Docker Desktop for phasing more advanced development with real-end-point simulation, and the staging/production automated deployment environments. Interfaced to various PostgreSQL-based REST back-ends. Angular Material was employed throughout, but advanced styling was limited due to the utilitarian priority of this software. The UI is also extensively responsive to support both monitors and tablets. Finally, Angular purity has been maintained: no unnecessary third-party dependencies such as Bootstrap and jQuery have been used.
This project was generated with Angular CLI version 10.0.5. It has since been upgraded to version 10.1.2.
Run ng serve for a dev server. Navigate to http://localhost:4200/. The app will automatically reload if you change any of the source files.
Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|guard|interface|enum|module.
Run ng build to build the project. The build artifacts will be stored in the dist/ directory. Use the --prod flag for a production build.
Run ng test to execute the unit tests via Karma.
Run ng e2e to execute the end-to-end tests via Protractor.
Note: There is NO application-specific end-to-end testing implemented other than the default one provided by the Angular CLI.
To get more help on the Angular CLI use ng help or go check out the Angular CLI README.
To build a docker image containing a production build of this application, run:
docker build --file Dockerfile-prod -t ptdbfe10 .
To test the production build, you can run:
docker run -dit -p 8001:8001 ptdbfr10
To run your dev environment out of a Docker container instead of using your local environment, run:
docker build -t ptdbfe10 .
docker run -v .:/app -p 4200:4200 -it ptdbfe10