It is highly recommended to set the DCC_LAB and DCC_AWARD environment variables for
ease of use. These correspond to the lab and award identifiers given by the ENCODE
portal, e.g. /labs/foo/ and U00HG123456, respectively.
If you are accessioning workflows produced using the
Caper local backend, then installation is
complete. However, if using WDL metadata from pipeline runs on Google Cloud, you will
also need to authenticate with Google Cloud. Run the following two commands and follow
If you would like to be able to pass Caper workflow IDs or labels you will
need to configure access to the Caper server. If you are invoking accession from
a machine where you already have a Caper set up, and you have the Caper configuration
file available at ~/.caper/default.conf, then there is no extra setup required.
If the Caper server is on another machine, you will need so configure HTTP access to
it by setting the hostname and port values in the Caper conf file.
(Optional) Finally, to enable using Cloud Tasks to upload files from Google Cloud
Storage to AWS S3, set the following two environment variables. If one or more of them
is not set, then files will be uploaded using the same machine that the accessioning
code is run from. For more information on how to set up Cloud Tasks and the upload
service, see the docs for the gcs-s3-transfer-service
Please see the docs for greater detail on these input parameters.
Deploying on Google Cloud
First authenticate with Google Cloud via gcloud auth login if needed. Then install
the API client with pip install google-api-python-client, it is recommended to do
this inside of a venv. Finally, create the firewall rule and deploy the instance by
running python deploy.py –project $PROJECT. This will also install the accession
package. Finally, SSH onto the new instance and run gcloud auth login to
authenticate on the instance.
For Caper integration, once the instance is up, SSH onto it and create the Caper conf
file at ~/.caper/default.conf, use the private IP of the Caper VM instance as the
hostname and use 8000 for the port. For the connection to work the Caper VM
will need to have the tag caper-server. Also note that the deployment assumes the
Cromwell server port is set to 8000.
accession is released under the MIT license, documentation lives in readthedocs, code is hosted on github and the releases on PyPI.