nextflow.config

profiles {
    standard {
        env.PROJECT_NAME = "$PROJECT_NAME"
        env.AWS_ACCESS_KEY_ID = "$AWS_ACCESS_KEY_ID"
        env.AWS_SECRET_ACCESS_KEY = "$AWS_SECRET_ACCESS_KEY"
        env.MLFLOW_S3_ENDPOINT_URL = "$MLFLOW_S3_ENDPOINT_URL"
        env.ARANGO_ROOT_PASSWORD = "$ARANGO_ROOT_PASSWORD"
        
        report.enabled = true
        report.overwrite = true

        dag.enabled = true
        dag.overwrite = true
        dag.file = 'pipeline_dag.html'

        trace.enabled = true
        trace.overwrite = true
        
        timeline.enabled = true
        timeline.file = 'pipeline_trace.txt'
        timeline.fields = 'task_id,name,status,exit,realtime,%cpu,rss'
    }

    conda {
        conda.enabled = true
    }

    docker {
        docker.enabled = true
        docker.remove = true
        process.container = 'ghcr.io/jbris/nextflow-graph-machine-learning:1.0.0'
        docker.runOptions = '-u $(id -u):$(id -g) -v $PWD:$PWD --network=${PROJECT_NAME}'
    }
}