For pull requests which affect generated output, please do not include the actual regenerated service code, only commit the updates to the generator and related configuration.
This ensures the Continuous Integration process is the single source of truth for generated code changes, and keeps pull requests readable and focused on actual generator code/logic changes.
The configuration for the generation step of each individual service endpoint lives
under ./configs/services/g
. The naming matches the Google Discovery Service naming of endpoints,
which are vendored under ./configs/models
.
Rather than actually crawling the Discovery Service, the Google API Go Client
is vendored under ./vendor
, and the JSON service definitions are copied to ./configs/models
to ensure reproducibility of the generation steps and the abilitry to diff across versions.
To add a new endpoint, first create the related JSON configuration in the ./configs/services/g
directory.
Since the Cloud Dataproc API is called dataproc-api.json
in the Google Discovery API,
you would create the configuration ./configs/services/g/dataproc.json
with the following contents:
{
"library": "dataproc",
"canonicalName": "Dataproc"
}
Then, the Makefile
is used:
make clean
make
This will build the ./bin/gogol-gen
binary, and will generate a Haskell library
for each API that has matching ./configs/services/g/*.json
configuration.
For the above example, the result would be a ../gogol-dataproc
directory at the
top-level of the project containing the generated API client.
make full-clean
can be used to cause a complete re-download of all (including new) service models.
Individual clients/SDKs can be generated by passing a specific
MODELS
environment variable to themake
command, for example:MODELS=configs/models/admin/directory/v1/admin-api.json make