The web application for GraphDB APIs
- Checkout or clone the project.
- Enter the project directory and execute
npm installin order to install all needed dependencies locally.
npm run start will bundle application and vendor code in memory and start a webpack
development server and proxy requests to
Unit tests can be run by executing
It's important to be noted that angular components in the application and the tests are built as AMD modules and all new tests must follow the same style.
Requirejs is used as a module loader. The test framework is Jasmine with Karma as test launcher. Karma is configured to watch source and tests files for changes and continuously re-executing the tests.
Cypress is used as a framework for writing functional tests which cover concrete UI components as
well as whole acceptance scenarios. The tests are executed against a GraphDB version as defined in
package.json#versions.graphdb which is run in a docker container.
There are two options for running the tests. One is a headless execution and the second is through the Cypress's dashboard application. Follow the steps described below:
- Ensure a GraphDB instance is running on
localhost:7200. One can be run by executing
docker-compose upin the
npm run startto build and run the workbench web application. In result it is published and served by webpack's web dev server.
- In terminal, go in
graphdb-workbench/test-cypressfolder and choose one of the options below:
npm run test- this will run the test suite in a headless mode and the outcome log will be seen in the terminal.
npm run startor the equivalent
npx cypress open- this will open the Cypress's dashboard application through which the tests can be run one by one or altogether and observing the outcome in the dashboard.
Release and publish
The workbench is regularly published as a package in the NPM registry.
When a newer version needs to be published:
- Increase the version in the
package.jsonby following the semantic versioning approach.
- Create a new PR and a tag through Github. Beware the version to follow the pattern
/v[0-9]+\.[0-9]+\.[0-9]+(-.*)?$/as defined in
.travis.yml. Any discrepancies will result in version being rejected as appropriate for publish in the NPM.
- If the build is successful which can be seen in https://travis-ci.com/Ontotext-AD/graphdb-workbench the workbench package is published in NPM which can be also verified on the site https://www.npmjs.com/package/graphdb-workbench.
Application can be built by executing the
npm run build command. In result, the application is
bundled, less files are processed and the code is minified. The result of the build command is
emitted in the
/dist folder. When the workbench is published, only the
/dist folder gets
published in the NPM registry. This is configured in
The repo includes sample Dockerfile that configures NGiNX for serving the workbench and proxying
requests to a GraphDB endpoint. This is configurable via the
GRAPHDB_URL environment variable.
docker run -d -p 8080:80 -e GRAPHDB_URL=10.131.2.176:7200 graphdb-workbench
For ease of use in local development with a locally running GraphDB at localhost:7200, there is also a
Docker compose that can be built and started with
docker-compose up --build. The compose requires
.env file in the root directory of the project where the
HOST_IP environment variable
must be specified, e.g.
HOST_IP=10.131.2.176. This is needed to proxy requests to locally running GraphDB.
Using GraphDB distribution
GraphDB exposes a configuration param
-Dgraphdb.workbench.home for overriding the bundled workbench.
This allows to easily point it to the
dist/ folder of the workbench after it has been bundled
npm run build.
Note: Wrongly configuring the parameter will result in GraphDb responding with HTTP 404.
GraphDB Docker distribution
The Docker distribution of GraphDB can also be configured to serve custom workbench, the only difference is that the workbench must be mounted, example:
docker run -d \ -p 7200:7200 \ -v /graphdb-workbench/dist:/workbench docker-registry.ontotext.com/graphdb-free:9.0.0 \ -Dgraphdb.workbench.home=/workbench
Note: Instead of mounting the workbench, this can be done in a custom Docker image using the GraphDB one as a base and then copy the custom workbench.