graphdb-workbench
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The web application for GraphDB APIs
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# graphdb-workbench
The web application for GraphDB APIs
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### Setup Environment
* Checkout or clone the project.
* Enter the project directory and execute `npm install` in order to install all
needed dependencies locally.
## Development
### Developers guide
https://ontotext-ad.github.io/graphdb-workbench/developers-guide
### Dev server
Running `npm run start` will bundle application and vendor code in memory and start a webpack
development server and proxy requests to `localhost:7200` (default).
## Testing
### Unit tests
Unit tests can be run by executing `npm test`.
> 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.
### Acceptance/functional 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.
> Some tests may require a GraphDB Enterprise Edition license file. The file must be named graphdb.license
and put in the `test-cypress/fixtures` folder. In case you don't have such license, you can ignore the
failing tests.
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 up` in the `graphdb-workbench/test-cypress` folder.
* In `graphdb-workbench` folder execute `npm run start` to 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-cypress` folder and choose one of the options below:
* Execute `npm run test` - this will run the test suite in a headless mode and the outcome log
will be seen in the terminal.
* Execute `npm run start` or 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.
### Build
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 `package.json#files` property.
## Deploying
### Standalone (Docker)
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.
Example:
`docker run -d -p 8080:80 -e GRAPHDB_URL=10.131.2.176:7200 graphdb-workbench`
#### Local development
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
to have `.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
with `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.
## License
[LICENSE](licenses/LICENSE)