Our Work

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run them…

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run themselves in Terra. The most common reason for this is that the pipeline accesses proprietary data that users are not allowed to access directly, but that may be used as e.g. a reference panel for imputation. Supported pipelines Current supported pipelines are: Array Imputation with the All of Us + AnVIL Reference Panel Architecture Architecture Doc Architecture Diagram Development This codebase is in initial development. Requirements Technical This service is written in Java 17, and uses Postgres 15. To run locally, you'll also need: jq - install with brew install jq Java 17 - can be installed manually or through IntelliJ which will do it for you when importing the project Postgres 15 - multiple solutions here as long as you have a postgres instance running on localhost:5432 the local app will connect appropriately. Be sure to use Postgres 15 (as of Feb 2025, Postgres 17 did not work) Download Postgres.app (recommended) from https://postgresapp.com/ Brew https://formulae.brew.sh/formula/postgresql@15 External Services Terra services Sam Used to authn users connecting to the service and authz users for admin endpoints Rawls Used to handle workspace interactions creating methods data tables workflow submission Cromwell Used through Rawls to run submissions Thurloe Used to send notification emails to users Tech stack Java 17 temurin Postgres 15 Gradle - build automation tool SonarQube - static code security and coverage Trivy - security scanner for docker images Jib - docker image builder for Java Local development To run locally: Make sure you have the requirements installed from above. We recommend IntelliJ as an IDE. Clone the repo (if you see broken inputs build the project to get the generated sources) Spin up a local postgres instance (NOTE: use version 15) Run the commands in scripts/postgres-init.sql in your local postgres instance. You will need to be authenticated to access GSM. Run scripts/write-config.sh Run ./gradlew bootRun to spin up the server. Navigate to http://localhost:8080/# If this is your first time deploying to any environment, be sure to use the admin endpoint /api/admin/v1/pipelines/{pipelineName}/{pipelineVersion} to set your pipeline's workspace id. To run this endpoint, you need to be authenticated using your firecloud test account. A list of accounts that developers typically need is here. Further, a list of resources that are generally useful is stored here This endpoint requires two parameters directly, and three in the message body: pipelineName can be retrieved by querying the /api/pipelines/v1 endpoint. pipelineVersion can also be retrieved from the /api/pipelines/v1 endpoint. workspaceBillingProject is listed in the Teaspoons Resources document linked above workspaceName is also listed in the Teaspoons Resources document, and can be found through the Terra UI workspace dashboard wdlMethodVersion is found for the specific workflow as listed in the Terra UI page for workflows. Back up local Postgres databases before testing/refactors Before running local migrations/refactors, take backups of both local databases so you can restore quickly. Defaults in this repo (see service/src/main/resources/application.yml and scripts/postgres-init.sql): host 127.0.0.1, port 5432 pipelines_db user/pass: dbuser / dbpwd teaspoons_stairway_db user/pass: stairwayuser / stairwaypwd Backup and verify: ts="$(date +%Y%m%d_%H%M%S)" backup_dir="$HOME/teaspoons-db-backups/$ts" mkdir -p "$backup_dir" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_dump -Fc -f "$backup_dir/pipelines_db.dump" pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_dump -Fc -f "$backup_dir/teaspoons_stairway_db.dump" teaspoons_stairway_db pg_restore -l "$backup_dir/pipelines_db.dump" | head pg_restore -l "$backup_dir/teaspoons_stairway_db.dump" | head echo "Backups written to: $backup_dir" Restore later (replace <admin_password>): PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O dbuser pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_restore --clean --if-exists --no-owner -d pipelines_db "$backup_dir/pipelines_db.dump" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O stairwayuser teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_restore --clean --if-exists --no-owner -d teaspoons_stairway_db "$backup_dir/teaspoons_stairway_db.dump" Local development with the UI When running terra-ui locally against a local teaspoons backend, CORS-related errors can arise. To get around this, run the following command to copy a configuration file that allows requests from localhost: ./scripts/local-dev/copy_web_config.sh Note that this file at the destination path (next to App.java) is ignored via .gitignore, since it should not be used in deployed environments. Local development with debugging If using Intellij (only IDE we use on the team), you can run the server with a debugger. Follow the steps above but instead of running ./gradlew bootRun to spin up the server, you can run (debug) the App.java class through intellij and set breakpoints in the code. Be sure to set the GOOGLE_APPLICATION_CREDENTIALS=config/teaspoons-sa.json in the Run/Debug configuration Environment Variables. Testing the CLI locally If you make changes to openapi.yml, you should test the CLI locally. To create the autogenerated Python client files locally, run ./gradlew :python-client:openApiGenerate The files will be generated in python-client/generated and are ignored from being checked into the repo. (Note: the unqualified ./gradlew openApiGenerate now regenerates all four codegen modules — python-client, rawls-client, client, and service — so qualify the task when you only want the Python client.) To test with the CLI, follow the instructions in the CLI repo: DataBiosphere/terra-scientific-pipelines-service-cli. Running Tests Locally Run ./gradlew service:test to run tests Note: If you encounter errors indicating a failure to load the ApplicationContext due to an error while preparing a database cluster caused by a missing Docker environment, this may be related to newer Docker versions (for example, 29.0.0 and above). To resolve this issue, override the Docker API version in the $HOME/.docker-java.properties file. If the file does not already exist, create it and add the following line: api.version=1.44 If the file mentioned already exists with above line, and the tests are still failing in the same way, try restarting Docker. Running Linter Locally Run ./gradlew spotlessCheck to run linter checks Run ./gradlew :service:spotlessApply to apply fix any issues the linter finds (Optional) Install pre-commit hooks [scripts/git-hooks/pre-commit] has been provided to help ensure all submitted changes are formatted correctly. To install all hooks in [scripts/git-hooks], run: git config core.hooksPath scripts/git-hooks Running SonarQube locally SonarQube is a static analysis code that scans code for a wide range of issues, including maintainability and possible bugs. Get more information from DSP SonarQube Docs If you get a build failure due to SonarQube and want to debug the problem locally, you need to get the sonar token from GSM before running the gradle task. export SONAR_TOKEN=$(gcloud secrets versions access latest --project="broad-dsde-dev" --secret="teaspoons-sonarcloud" | jq '.sonar_token') ./gradlew sonarqube Running this task produces no output unless your project has errors. To generate a report, run using --info: ./gradlew sonarqube --info Connecting to the database To connect to the Teaspoons database, we have a script in dsp-scripts that does all the setup for you. Clone that repo and make sure you're either on Broad Internal wifi or connected to the VPN. Then run the following command: ./db/psql-connect.sh dev teaspoons Deploying to dev Upon merging to main, the dev environment will be automatically deployed via the GitHub Action Bump, Tag, Publish, and Deploy (that workflow is defined here). The two tasks report-to-sherlock and set-version-in-dev will prompt Sherlock to deploy the new version to dev. You can check the status of the deployment in Beehive and in ArgoCD. For more information about deployment to dev, check out DevOps' excellent documentation. Tracing We use OpenTelemetry for tracing, so that every request has a tracing span that can be viewed in Google Cloud Trace. See this DSP blog post for more info. Running the BEE end-to-end tests The end-to-end test that runs against a BEE is specified in .github/workflows/run-bee-e2e-tests.yaml. It calls the workflow defined in the terra-github-workflows repo. The end-to-end test is automatically run nightly on the dev environment. To run the test against a specific feature branch: Grab the image tag for your feature branch. If you've opened a PR, you can find the image tag as follows: go to the Bump, Tag, Publish, and Deploy workflow that's triggered each time you push to your branch From there, go to the tag-publish-docker-deploy task Expand the "Construct docker image name and tag" step The first line should contain the image tag, something like "0.0.81-6761487". Navigate to the e2e-test GHA workflow Click on the "Run workflow" button and select your branch from the dropdown Enter the image tag from step 1 in the "Custom image tag" field If you've updated the end-to-end test in the dsp-resuable-workflows repo, enter either a commit hash or your git branch name. If you don't need to change the test, leave the default as main. Click the green "Run workflow" button. Python clients We publish a "thin", auto-generated Python client that wraps the Teaspoons APIs. This client is published to PyPi and can be installed with pip install teaspoons_client, although this is not meant to be user-facing. The thin api client is generated from the OpenAPI spec in the openapi directory. Publishing occurs automatically when a new version of the service is deployed, via the release-python-client GHA. We also have a user-facing, "thick" CLI whose code lives in a separate repository: DataBiosphere/terra-scientific-pipelines-service-cli.

Artistools is collection of plotting, analysis, and file format conversion tools for the ARTIS radiative transfer code.

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run them…

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run themselves in Terra. The most common reason for this is that the pipeline accesses proprietary data that users are not allowed to access directly, but that may be used as e.g. a reference panel for imputation. Supported pipelines Current supported pipelines are: Array Imputation with the All of Us + AnVIL Reference Panel Architecture Architecture Doc Architecture Diagram Development This codebase is in initial development. Requirements Technical This service is written in Java 17, and uses Postgres 15. To run locally, you'll also need: jq - install with brew install jq Java 17 - can be installed manually or through IntelliJ which will do it for you when importing the project Postgres 15 - multiple solutions here as long as you have a postgres instance running on localhost:5432 the local app will connect appropriately. Be sure to use Postgres 15 (as of Feb 2025, Postgres 17 did not work) Download Postgres.app (recommended) from https://postgresapp.com/ Brew https://formulae.brew.sh/formula/postgresql@15 External Services Terra services Sam Used to authn users connecting to the service and authz users for admin endpoints Rawls Used to handle workspace interactions creating methods data tables workflow submission Cromwell Used through Rawls to run submissions Thurloe Used to send notification emails to users Tech stack Java 17 temurin Postgres 15 Gradle - build automation tool SonarQube - static code security and coverage Trivy - security scanner for docker images Jib - docker image builder for Java Local development To run locally: Make sure you have the requirements installed from above. We recommend IntelliJ as an IDE. Clone the repo (if you see broken inputs build the project to get the generated sources) Spin up a local postgres instance (NOTE: use version 15) Run the commands in scripts/postgres-init.sql in your local postgres instance. You will need to be authenticated to access GSM. Run scripts/write-config.sh Run ./gradlew bootRun to spin up the server. Navigate to http://localhost:8080/# If this is your first time deploying to any environment, be sure to use the admin endpoint /api/admin/v1/pipelines/{pipelineName}/{pipelineVersion} to set your pipeline's workspace id. To run this endpoint, you need to be authenticated using your firecloud test account. A list of accounts that developers typically need is here. Further, a list of resources that are generally useful is stored here This endpoint requires two parameters directly, and three in the message body: pipelineName can be retrieved by querying the /api/pipelines/v1 endpoint. pipelineVersion can also be retrieved from the /api/pipelines/v1 endpoint. workspaceBillingProject is listed in the Teaspoons Resources document linked above workspaceName is also listed in the Teaspoons Resources document, and can be found through the Terra UI workspace dashboard wdlMethodVersion is found for the specific workflow as listed in the Terra UI page for workflows. Back up local Postgres databases before testing/refactors Before running local migrations/refactors, take backups of both local databases so you can restore quickly. Defaults in this repo (see service/src/main/resources/application.yml and scripts/postgres-init.sql): host 127.0.0.1, port 5432 pipelines_db user/pass: dbuser / dbpwd teaspoons_stairway_db user/pass: stairwayuser / stairwaypwd Backup and verify: ts="$(date +%Y%m%d_%H%M%S)" backup_dir="$HOME/teaspoons-db-backups/$ts" mkdir -p "$backup_dir" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_dump -Fc -f "$backup_dir/pipelines_db.dump" pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_dump -Fc -f "$backup_dir/teaspoons_stairway_db.dump" teaspoons_stairway_db pg_restore -l "$backup_dir/pipelines_db.dump" | head pg_restore -l "$backup_dir/teaspoons_stairway_db.dump" | head echo "Backups written to: $backup_dir" Restore later (replace <admin_password>): PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O dbuser pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_restore --clean --if-exists --no-owner -d pipelines_db "$backup_dir/pipelines_db.dump" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O stairwayuser teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_restore --clean --if-exists --no-owner -d teaspoons_stairway_db "$backup_dir/teaspoons_stairway_db.dump" Local development with the UI When running terra-ui locally against a local teaspoons backend, CORS-related errors can arise. To get around this, run the following command to copy a configuration file that allows requests from localhost: ./scripts/local-dev/copy_web_config.sh Note that this file at the destination path (next to App.java) is ignored via .gitignore, since it should not be used in deployed environments. Local development with debugging If using Intellij (only IDE we use on the team), you can run the server with a debugger. Follow the steps above but instead of running ./gradlew bootRun to spin up the server, you can run (debug) the App.java class through intellij and set breakpoints in the code. Be sure to set the GOOGLE_APPLICATION_CREDENTIALS=config/teaspoons-sa.json in the Run/Debug configuration Environment Variables. Testing the CLI locally If you make changes to openapi.yml, you should test the CLI locally. To create the autogenerated Python client files locally, run ./gradlew :python-client:openApiGenerate The files will be generated in python-client/generated and are ignored from being checked into the repo. (Note: the unqualified ./gradlew openApiGenerate now regenerates all four codegen modules — python-client, rawls-client, client, and service — so qualify the task when you only want the Python client.) To test with the CLI, follow the instructions in the CLI repo: DataBiosphere/terra-scientific-pipelines-service-cli. Running Tests Locally Run ./gradlew service:test to run tests Note: If you encounter errors indicating a failure to load the ApplicationContext due to an error while preparing a database cluster caused by a missing Docker environment, this may be related to newer Docker versions (for example, 29.0.0 and above). To resolve this issue, override the Docker API version in the $HOME/.docker-java.properties file. If the file does not already exist, create it and add the following line: api.version=1.44 If the file mentioned already exists with above line, and the tests are still failing in the same way, try restarting Docker. Running Linter Locally Run ./gradlew spotlessCheck to run linter checks Run ./gradlew :service:spotlessApply to apply fix any issues the linter finds (Optional) Install pre-commit hooks [scripts/git-hooks/pre-commit] has been provided to help ensure all submitted changes are formatted correctly. To install all hooks in [scripts/git-hooks], run: git config core.hooksPath scripts/git-hooks Running SonarQube locally SonarQube is a static analysis code that scans code for a wide range of issues, including maintainability and possible bugs. Get more information from DSP SonarQube Docs If you get a build failure due to SonarQube and want to debug the problem locally, you need to get the sonar token from GSM before running the gradle task. export SONAR_TOKEN=$(gcloud secrets versions access latest --project="broad-dsde-dev" --secret="teaspoons-sonarcloud" | jq '.sonar_token') ./gradlew sonarqube Running this task produces no output unless your project has errors. To generate a report, run using --info: ./gradlew sonarqube --info Connecting to the database To connect to the Teaspoons database, we have a script in dsp-scripts that does all the setup for you. Clone that repo and make sure you're either on Broad Internal wifi or connected to the VPN. Then run the following command: ./db/psql-connect.sh dev teaspoons Deploying to dev Upon merging to main, the dev environment will be automatically deployed via the GitHub Action Bump, Tag, Publish, and Deploy (that workflow is defined here). The two tasks report-to-sherlock and set-version-in-dev will prompt Sherlock to deploy the new version to dev. You can check the status of the deployment in Beehive and in ArgoCD. For more information about deployment to dev, check out DevOps' excellent documentation. Tracing We use OpenTelemetry for tracing, so that every request has a tracing span that can be viewed in Google Cloud Trace. See this DSP blog post for more info. Running the BEE end-to-end tests The end-to-end test that runs against a BEE is specified in .github/workflows/run-bee-e2e-tests.yaml. It calls the workflow defined in the terra-github-workflows repo. The end-to-end test is automatically run nightly on the dev environment. To run the test against a specific feature branch: Grab the image tag for your feature branch. If you've opened a PR, you can find the image tag as follows: go to the Bump, Tag, Publish, and Deploy workflow that's triggered each time you push to your branch From there, go to the tag-publish-docker-deploy task Expand the "Construct docker image name and tag" step The first line should contain the image tag, something like "0.0.81-6761487". Navigate to the e2e-test GHA workflow Click on the "Run workflow" button and select your branch from the dropdown Enter the image tag from step 1 in the "Custom image tag" field If you've updated the end-to-end test in the dsp-resuable-workflows repo, enter either a commit hash or your git branch name. If you don't need to change the test, leave the default as main. Click the green "Run workflow" button. Python clients We publish a "thin", auto-generated Python client that wraps the Teaspoons APIs. This client is published to PyPi and can be installed with pip install teaspoons_client, although this is not meant to be user-facing. The thin api client is generated from the OpenAPI spec in the openapi directory. Publishing occurs automatically when a new version of the service is deployed, via the release-python-client GHA. We also have a user-facing, "thick" CLI whose code lives in a separate repository: DataBiosphere/terra-scientific-pipelines-service-cli.

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run them…

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run themselves in Terra. The most common reason for this is that the pipeline accesses proprietary data that users are not allowed to access directly, but that may be used as e.g. a reference panel for imputation. Supported pipelines Current supported pipelines are: Array Imputation with the All of Us + AnVIL Reference Panel Architecture Architecture Doc Architecture Diagram Development This codebase is in initial development. Requirements Technical This service is written in Java 17, and uses Postgres 15. To run locally, you'll also need: jq - install with brew install jq Java 17 - can be installed manually or through IntelliJ which will do it for you when importing the project Postgres 15 - multiple solutions here as long as you have a postgres instance running on localhost:5432 the local app will connect appropriately. Be sure to use Postgres 15 (as of Feb 2025, Postgres 17 did not work) Download Postgres.app (recommended) from https://postgresapp.com/ Brew https://formulae.brew.sh/formula/postgresql@15 External Services Terra services Sam Used to authn users connecting to the service and authz users for admin endpoints Rawls Used to handle workspace interactions creating methods data tables workflow submission Cromwell Used through Rawls to run submissions Thurloe Used to send notification emails to users Tech stack Java 17 temurin Postgres 15 Gradle - build automation tool SonarQube - static code security and coverage Trivy - security scanner for docker images Jib - docker image builder for Java Local development To run locally: Make sure you have the requirements installed from above. We recommend IntelliJ as an IDE. Clone the repo (if you see broken inputs build the project to get the generated sources) Spin up a local postgres instance (NOTE: use version 15) Run the commands in scripts/postgres-init.sql in your local postgres instance. You will need to be authenticated to access GSM. Run scripts/write-config.sh Run ./gradlew bootRun to spin up the server. Navigate to http://localhost:8080/# If this is your first time deploying to any environment, be sure to use the admin endpoint /api/admin/v1/pipelines/{pipelineName}/{pipelineVersion} to set your pipeline's workspace id. To run this endpoint, you need to be authenticated using your firecloud test account. A list of accounts that developers typically need is here. Further, a list of resources that are generally useful is stored here This endpoint requires two parameters directly, and three in the message body: pipelineName can be retrieved by querying the /api/pipelines/v1 endpoint. pipelineVersion can also be retrieved from the /api/pipelines/v1 endpoint. workspaceBillingProject is listed in the Teaspoons Resources document linked above workspaceName is also listed in the Teaspoons Resources document, and can be found through the Terra UI workspace dashboard wdlMethodVersion is found for the specific workflow as listed in the Terra UI page for workflows. Back up local Postgres databases before testing/refactors Before running local migrations/refactors, take backups of both local databases so you can restore quickly. Defaults in this repo (see service/src/main/resources/application.yml and scripts/postgres-init.sql): host 127.0.0.1, port 5432 pipelines_db user/pass: dbuser / dbpwd teaspoons_stairway_db user/pass: stairwayuser / stairwaypwd Backup and verify: ts="$(date +%Y%m%d_%H%M%S)" backup_dir="$HOME/teaspoons-db-backups/$ts" mkdir -p "$backup_dir" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_dump -Fc -f "$backup_dir/pipelines_db.dump" pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_dump -Fc -f "$backup_dir/teaspoons_stairway_db.dump" teaspoons_stairway_db pg_restore -l "$backup_dir/pipelines_db.dump" | head pg_restore -l "$backup_dir/teaspoons_stairway_db.dump" | head echo "Backups written to: $backup_dir" Restore later (replace <admin_password>): PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O dbuser pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_restore --clean --if-exists --no-owner -d pipelines_db "$backup_dir/pipelines_db.dump" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O stairwayuser teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_restore --clean --if-exists --no-owner -d teaspoons_stairway_db "$backup_dir/teaspoons_stairway_db.dump" Local development with the UI When running terra-ui locally against a local teaspoons backend, CORS-related errors can arise. To get around this, run the following command to copy a configuration file that allows requests from localhost: ./scripts/local-dev/copy_web_config.sh Note that this file at the destination path (next to App.java) is ignored via .gitignore, since it should not be used in deployed environments. Local development with debugging If using Intellij (only IDE we use on the team), you can run the server with a debugger. Follow the steps above but instead of running ./gradlew bootRun to spin up the server, you can run (debug) the App.java class through intellij and set breakpoints in the code. Be sure to set the GOOGLE_APPLICATION_CREDENTIALS=config/teaspoons-sa.json in the Run/Debug configuration Environment Variables. Testing the CLI locally If you make changes to openapi.yml, you should test the CLI locally. To create the autogenerated Python client files locally, run ./gradlew :python-client:openApiGenerate The files will be generated in python-client/generated and are ignored from being checked into the repo. (Note: the unqualified ./gradlew openApiGenerate now regenerates all four codegen modules — python-client, rawls-client, client, and service — so qualify the task when you only want the Python client.) To test with the CLI, follow the instructions in the CLI repo: DataBiosphere/terra-scientific-pipelines-service-cli. Running Tests Locally Run ./gradlew service:test to run tests Note: If you encounter errors indicating a failure to load the ApplicationContext due to an error while preparing a database cluster caused by a missing Docker environment, this may be related to newer Docker versions (for example, 29.0.0 and above). To resolve this issue, override the Docker API version in the $HOME/.docker-java.properties file. If the file does not already exist, create it and add the following line: api.version=1.44 If the file mentioned already exists with above line, and the tests are still failing in the same way, try restarting Docker. Running Linter Locally Run ./gradlew spotlessCheck to run linter checks Run ./gradlew :service:spotlessApply to apply fix any issues the linter finds (Optional) Install pre-commit hooks [scripts/git-hooks/pre-commit] has been provided to help ensure all submitted changes are formatted correctly. To install all hooks in [scripts/git-hooks], run: git config core.hooksPath scripts/git-hooks Running SonarQube locally SonarQube is a static analysis code that scans code for a wide range of issues, including maintainability and possible bugs. Get more information from DSP SonarQube Docs If you get a build failure due to SonarQube and want to debug the problem locally, you need to get the sonar token from GSM before running the gradle task. export SONAR_TOKEN=$(gcloud secrets versions access latest --project="broad-dsde-dev" --secret="teaspoons-sonarcloud" | jq '.sonar_token') ./gradlew sonarqube Running this task produces no output unless your project has errors. To generate a report, run using --info: ./gradlew sonarqube --info Connecting to the database To connect to the Teaspoons database, we have a script in dsp-scripts that does all the setup for you. Clone that repo and make sure you're either on Broad Internal wifi or connected to the VPN. Then run the following command: ./db/psql-connect.sh dev teaspoons Deploying to dev Upon merging to main, the dev environment will be automatically deployed via the GitHub Action Bump, Tag, Publish, and Deploy (that workflow is defined here). The two tasks report-to-sherlock and set-version-in-dev will prompt Sherlock to deploy the new version to dev. You can check the status of the deployment in Beehive and in ArgoCD. For more information about deployment to dev, check out DevOps' excellent documentation. Tracing We use OpenTelemetry for tracing, so that every request has a tracing span that can be viewed in Google Cloud Trace. See this DSP blog post for more info. Running the BEE end-to-end tests The end-to-end test that runs against a BEE is specified in .github/workflows/run-bee-e2e-tests.yaml. It calls the workflow defined in the terra-github-workflows repo. The end-to-end test is automatically run nightly on the dev environment. To run the test against a specific feature branch: Grab the image tag for your feature branch. If you've opened a PR, you can find the image tag as follows: go to the Bump, Tag, Publish, and Deploy workflow that's triggered each time you push to your branch From there, go to the tag-publish-docker-deploy task Expand the "Construct docker image name and tag" step The first line should contain the image tag, something like "0.0.81-6761487". Navigate to the e2e-test GHA workflow Click on the "Run workflow" button and select your branch from the dropdown Enter the image tag from step 1 in the "Custom image tag" field If you've updated the end-to-end test in the dsp-resuable-workflows repo, enter either a commit hash or your git branch name. If you don't need to change the test, leave the default as main. Click the green "Run workflow" button. Python clients We publish a "thin", auto-generated Python client that wraps the Teaspoons APIs. This client is published to PyPi and can be installed with pip install teaspoons_client, although this is not meant to be user-facing. The thin api client is generated from the OpenAPI spec in the openapi directory. Publishing occurs automatically when a new version of the service is deployed, via the release-python-client GHA. We also have a user-facing, "thick" CLI whose code lives in a separate repository: DataBiosphere/terra-scientific-pipelines-service-cli.

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run them…

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run themselves in Terra. The most common reason for this is that the pipeline accesses proprietary data that users are not allowed to access directly, but that may be used as e.g. a reference panel for imputation. Supported pipelines Current supported pipelines are: Array Imputation with the All of Us + AnVIL Reference Panel Architecture Architecture Doc Architecture Diagram Development This codebase is in initial development. Requirements Technical This service is written in Java 17, and uses Postgres 15. To run locally, you'll also need: jq - install with brew install jq Java 17 - can be installed manually or through IntelliJ which will do it for you when importing the project Postgres 15 - multiple solutions here as long as you have a postgres instance running on localhost:5432 the local app will connect appropriately. Be sure to use Postgres 15 (as of Feb 2025, Postgres 17 did not work) Download Postgres.app (recommended) from https://postgresapp.com/ Brew https://formulae.brew.sh/formula/postgresql@15 External Services Terra services Sam Used to authn users connecting to the service and authz users for admin endpoints Rawls Used to handle workspace interactions creating methods data tables workflow submission Cromwell Used through Rawls to run submissions Thurloe Used to send notification emails to users Tech stack Java 17 temurin Postgres 15 Gradle - build automation tool SonarQube - static code security and coverage Trivy - security scanner for docker images Jib - docker image builder for Java Local development To run locally: Make sure you have the requirements installed from above. We recommend IntelliJ as an IDE. Clone the repo (if you see broken inputs build the project to get the generated sources) Spin up a local postgres instance (NOTE: use version 15) Run the commands in scripts/postgres-init.sql in your local postgres instance. You will need to be authenticated to access GSM. Run scripts/write-config.sh Run ./gradlew bootRun to spin up the server. Navigate to http://localhost:8080/# If this is your first time deploying to any environment, be sure to use the admin endpoint /api/admin/v1/pipelines/{pipelineName}/{pipelineVersion} to set your pipeline's workspace id. To run this endpoint, you need to be authenticated using your firecloud test account. A list of accounts that developers typically need is here. Further, a list of resources that are generally useful is stored here This endpoint requires two parameters directly, and three in the message body: pipelineName can be retrieved by querying the /api/pipelines/v1 endpoint. pipelineVersion can also be retrieved from the /api/pipelines/v1 endpoint. workspaceBillingProject is listed in the Teaspoons Resources document linked above workspaceName is also listed in the Teaspoons Resources document, and can be found through the Terra UI workspace dashboard wdlMethodVersion is found for the specific workflow as listed in the Terra UI page for workflows. Back up local Postgres databases before testing/refactors Before running local migrations/refactors, take backups of both local databases so you can restore quickly. Defaults in this repo (see service/src/main/resources/application.yml and scripts/postgres-init.sql): host 127.0.0.1, port 5432 pipelines_db user/pass: dbuser / dbpwd teaspoons_stairway_db user/pass: stairwayuser / stairwaypwd Backup and verify: ts="$(date +%Y%m%d_%H%M%S)" backup_dir="$HOME/teaspoons-db-backups/$ts" mkdir -p "$backup_dir" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_dump -Fc -f "$backup_dir/pipelines_db.dump" pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_dump -Fc -f "$backup_dir/teaspoons_stairway_db.dump" teaspoons_stairway_db pg_restore -l "$backup_dir/pipelines_db.dump" | head pg_restore -l "$backup_dir/teaspoons_stairway_db.dump" | head echo "Backups written to: $backup_dir" Restore later (replace <admin_password>): PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O dbuser pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_restore --clean --if-exists --no-owner -d pipelines_db "$backup_dir/pipelines_db.dump" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O stairwayuser teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_restore --clean --if-exists --no-owner -d teaspoons_stairway_db "$backup_dir/teaspoons_stairway_db.dump" Local development with the UI When running terra-ui locally against a local teaspoons backend, CORS-related errors can arise. To get around this, run the following command to copy a configuration file that allows requests from localhost: ./scripts/local-dev/copy_web_config.sh Note that this file at the destination path (next to App.java) is ignored via .gitignore, since it should not be used in deployed environments. Local development with debugging If using Intellij (only IDE we use on the team), you can run the server with a debugger. Follow the steps above but instead of running ./gradlew bootRun to spin up the server, you can run (debug) the App.java class through intellij and set breakpoints in the code. Be sure to set the GOOGLE_APPLICATION_CREDENTIALS=config/teaspoons-sa.json in the Run/Debug configuration Environment Variables. Testing the CLI locally If you make changes to openapi.yml, you should test the CLI locally. To create the autogenerated Python client files locally, run ./gradlew :python-client:openApiGenerate The files will be generated in python-client/generated and are ignored from being checked into the repo. (Note: the unqualified ./gradlew openApiGenerate now regenerates all four codegen modules — python-client, rawls-client, client, and service — so qualify the task when you only want the Python client.) To test with the CLI, follow the instructions in the CLI repo: DataBiosphere/terra-scientific-pipelines-service-cli. Running Tests Locally Run ./gradlew service:test to run tests Note: If you encounter errors indicating a failure to load the ApplicationContext due to an error while preparing a database cluster caused by a missing Docker environment, this may be related to newer Docker versions (for example, 29.0.0 and above). To resolve this issue, override the Docker API version in the $HOME/.docker-java.properties file. If the file does not already exist, create it and add the following line: api.version=1.44 If the file mentioned already exists with above line, and the tests are still failing in the same way, try restarting Docker. Running Linter Locally Run ./gradlew spotlessCheck to run linter checks Run ./gradlew :service:spotlessApply to apply fix any issues the linter finds (Optional) Install pre-commit hooks [scripts/git-hooks/pre-commit] has been provided to help ensure all submitted changes are formatted correctly. To install all hooks in [scripts/git-hooks], run: git config core.hooksPath scripts/git-hooks Running SonarQube locally SonarQube is a static analysis code that scans code for a wide range of issues, including maintainability and possible bugs. Get more information from DSP SonarQube Docs If you get a build failure due to SonarQube and want to debug the problem locally, you need to get the sonar token from GSM before running the gradle task. export SONAR_TOKEN=$(gcloud secrets versions access latest --project="broad-dsde-dev" --secret="teaspoons-sonarcloud" | jq '.sonar_token') ./gradlew sonarqube Running this task produces no output unless your project has errors. To generate a report, run using --info: ./gradlew sonarqube --info Connecting to the database To connect to the Teaspoons database, we have a script in dsp-scripts that does all the setup for you. Clone that repo and make sure you're either on Broad Internal wifi or connected to the VPN. Then run the following command: ./db/psql-connect.sh dev teaspoons Deploying to dev Upon merging to main, the dev environment will be automatically deployed via the GitHub Action Bump, Tag, Publish, and Deploy (that workflow is defined here). The two tasks report-to-sherlock and set-version-in-dev will prompt Sherlock to deploy the new version to dev. You can check the status of the deployment in Beehive and in ArgoCD. For more information about deployment to dev, check out DevOps' excellent documentation. Tracing We use OpenTelemetry for tracing, so that every request has a tracing span that can be viewed in Google Cloud Trace. See this DSP blog post for more info. Running the BEE end-to-end tests The end-to-end test that runs against a BEE is specified in .github/workflows/run-bee-e2e-tests.yaml. It calls the workflow defined in the terra-github-workflows repo. The end-to-end test is automatically run nightly on the dev environment. To run the test against a specific feature branch: Grab the image tag for your feature branch. If you've opened a PR, you can find the image tag as follows: go to the Bump, Tag, Publish, and Deploy workflow that's triggered each time you push to your branch From there, go to the tag-publish-docker-deploy task Expand the "Construct docker image name and tag" step The first line should contain the image tag, something like "0.0.81-6761487". Navigate to the e2e-test GHA workflow Click on the "Run workflow" button and select your branch from the dropdown Enter the image tag from step 1 in the "Custom image tag" field If you've updated the end-to-end test in the dsp-resuable-workflows repo, enter either a commit hash or your git branch name. If you don't need to change the test, leave the default as main. Click the green "Run workflow" button. Python clients We publish a "thin", auto-generated Python client that wraps the Teaspoons APIs. This client is published to PyPi and can be installed with pip install teaspoons_client, although this is not meant to be user-facing. The thin api client is generated from the OpenAPI spec in the openapi directory. Publishing occurs automatically when a new version of the service is deployed, via the release-python-client GHA. We also have a user-facing, "thick" CLI whose code lives in a separate repository: DataBiosphere/terra-scientific-pipelines-service-cli.

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run them…

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run themselves in Terra. The most common reason for this is that the pipeline accesses proprietary data that users are not allowed to access directly, but that may be used as e.g. a reference panel for imputation. Supported pipelines Current supported pipelines are: Array Imputation with the All of Us + AnVIL Reference Panel Architecture Architecture Doc Architecture Diagram Development This codebase is in initial development. Requirements Technical This service is written in Java 17, and uses Postgres 15. To run locally, you'll also need: jq - install with brew install jq Java 17 - can be installed manually or through IntelliJ which will do it for you when importing the project Postgres 15 - multiple solutions here as long as you have a postgres instance running on localhost:5432 the local app will connect appropriately. Be sure to use Postgres 15 (as of Feb 2025, Postgres 17 did not work) Download Postgres.app (recommended) from https://postgresapp.com/ Brew https://formulae.brew.sh/formula/postgresql@15 External Services Terra services Sam Used to authn users connecting to the service and authz users for admin endpoints Rawls Used to handle workspace interactions creating methods data tables workflow submission Cromwell Used through Rawls to run submissions Thurloe Used to send notification emails to users Tech stack Java 17 temurin Postgres 15 Gradle - build automation tool SonarQube - static code security and coverage Trivy - security scanner for docker images Jib - docker image builder for Java Local development To run locally: Make sure you have the requirements installed from above. We recommend IntelliJ as an IDE. Clone the repo (if you see broken inputs build the project to get the generated sources) Spin up a local postgres instance (NOTE: use version 15) Run the commands in scripts/postgres-init.sql in your local postgres instance. You will need to be authenticated to access GSM. Run scripts/write-config.sh Run ./gradlew bootRun to spin up the server. Navigate to http://localhost:8080/# If this is your first time deploying to any environment, be sure to use the admin endpoint /api/admin/v1/pipelines/{pipelineName}/{pipelineVersion} to set your pipeline's workspace id. To run this endpoint, you need to be authenticated using your firecloud test account. A list of accounts that developers typically need is here. Further, a list of resources that are generally useful is stored here This endpoint requires two parameters directly, and three in the message body: pipelineName can be retrieved by querying the /api/pipelines/v1 endpoint. pipelineVersion can also be retrieved from the /api/pipelines/v1 endpoint. workspaceBillingProject is listed in the Teaspoons Resources document linked above workspaceName is also listed in the Teaspoons Resources document, and can be found through the Terra UI workspace dashboard wdlMethodVersion is found for the specific workflow as listed in the Terra UI page for workflows. Back up local Postgres databases before testing/refactors Before running local migrations/refactors, take backups of both local databases so you can restore quickly. Defaults in this repo (see service/src/main/resources/application.yml and scripts/postgres-init.sql): host 127.0.0.1, port 5432 pipelines_db user/pass: dbuser / dbpwd teaspoons_stairway_db user/pass: stairwayuser / stairwaypwd Backup and verify: ts="$(date +%Y%m%d_%H%M%S)" backup_dir="$HOME/teaspoons-db-backups/$ts" mkdir -p "$backup_dir" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_dump -Fc -f "$backup_dir/pipelines_db.dump" pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_dump -Fc -f "$backup_dir/teaspoons_stairway_db.dump" teaspoons_stairway_db pg_restore -l "$backup_dir/pipelines_db.dump" | head pg_restore -l "$backup_dir/teaspoons_stairway_db.dump" | head echo "Backups written to: $backup_dir" Restore later (replace <admin_password>): PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O dbuser pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_restore --clean --if-exists --no-owner -d pipelines_db "$backup_dir/pipelines_db.dump" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O stairwayuser teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_restore --clean --if-exists --no-owner -d teaspoons_stairway_db "$backup_dir/teaspoons_stairway_db.dump" Local development with the UI When running terra-ui locally against a local teaspoons backend, CORS-related errors can arise. To get around this, run the following command to copy a configuration file that allows requests from localhost: ./scripts/local-dev/copy_web_config.sh Note that this file at the destination path (next to App.java) is ignored via .gitignore, since it should not be used in deployed environments. Local development with debugging If using Intellij (only IDE we use on the team), you can run the server with a debugger. Follow the steps above but instead of running ./gradlew bootRun to spin up the server, you can run (debug) the App.java class through intellij and set breakpoints in the code. Be sure to set the GOOGLE_APPLICATION_CREDENTIALS=config/teaspoons-sa.json in the Run/Debug configuration Environment Variables. Testing the CLI locally If you make changes to openapi.yml, you should test the CLI locally. To create the autogenerated Python client files locally, run ./gradlew :python-client:openApiGenerate The files will be generated in python-client/generated and are ignored from being checked into the repo. (Note: the unqualified ./gradlew openApiGenerate now regenerates all four codegen modules — python-client, rawls-client, client, and service — so qualify the task when you only want the Python client.) To test with the CLI, follow the instructions in the CLI repo: DataBiosphere/terra-scientific-pipelines-service-cli. Running Tests Locally Run ./gradlew service:test to run tests Note: If you encounter errors indicating a failure to load the ApplicationContext due to an error while preparing a database cluster caused by a missing Docker environment, this may be related to newer Docker versions (for example, 29.0.0 and above). To resolve this issue, override the Docker API version in the $HOME/.docker-java.properties file. If the file does not already exist, create it and add the following line: api.version=1.44 If the file mentioned already exists with above line, and the tests are still failing in the same way, try restarting Docker. Running Linter Locally Run ./gradlew spotlessCheck to run linter checks Run ./gradlew :service:spotlessApply to apply fix any issues the linter finds (Optional) Install pre-commit hooks [scripts/git-hooks/pre-commit] has been provided to help ensure all submitted changes are formatted correctly. To install all hooks in [scripts/git-hooks], run: git config core.hooksPath scripts/git-hooks Running SonarQube locally SonarQube is a static analysis code that scans code for a wide range of issues, including maintainability and possible bugs. Get more information from DSP SonarQube Docs If you get a build failure due to SonarQube and want to debug the problem locally, you need to get the sonar token from GSM before running the gradle task. export SONAR_TOKEN=$(gcloud secrets versions access latest --project="broad-dsde-dev" --secret="teaspoons-sonarcloud" | jq '.sonar_token') ./gradlew sonarqube Running this task produces no output unless your project has errors. To generate a report, run using --info: ./gradlew sonarqube --info Connecting to the database To connect to the Teaspoons database, we have a script in dsp-scripts that does all the setup for you. Clone that repo and make sure you're either on Broad Internal wifi or connected to the VPN. Then run the following command: ./db/psql-connect.sh dev teaspoons Deploying to dev Upon merging to main, the dev environment will be automatically deployed via the GitHub Action Bump, Tag, Publish, and Deploy (that workflow is defined here). The two tasks report-to-sherlock and set-version-in-dev will prompt Sherlock to deploy the new version to dev. You can check the status of the deployment in Beehive and in ArgoCD. For more information about deployment to dev, check out DevOps' excellent documentation. Tracing We use OpenTelemetry for tracing, so that every request has a tracing span that can be viewed in Google Cloud Trace. See this DSP blog post for more info. Running the BEE end-to-end tests The end-to-end test that runs against a BEE is specified in .github/workflows/run-bee-e2e-tests.yaml. It calls the workflow defined in the terra-github-workflows repo. The end-to-end test is automatically run nightly on the dev environment. To run the test against a specific feature branch: Grab the image tag for your feature branch. If you've opened a PR, you can find the image tag as follows: go to the Bump, Tag, Publish, and Deploy workflow that's triggered each time you push to your branch From there, go to the tag-publish-docker-deploy task Expand the "Construct docker image name and tag" step The first line should contain the image tag, something like "0.0.81-6761487". Navigate to the e2e-test GHA workflow Click on the "Run workflow" button and select your branch from the dropdown Enter the image tag from step 1 in the "Custom image tag" field If you've updated the end-to-end test in the dsp-resuable-workflows repo, enter either a commit hash or your git branch name. If you don't need to change the test, leave the default as main. Click the green "Run workflow" button. Python clients We publish a "thin", auto-generated Python client that wraps the Teaspoons APIs. This client is published to PyPi and can be installed with pip install teaspoons_client, although this is not meant to be user-facing. The thin api client is generated from the OpenAPI spec in the openapi directory. Publishing occurs automatically when a new version of the service is deployed, via the release-python-client GHA. We also have a user-facing, "thick" CLI whose code lives in a separate repository: DataBiosphere/terra-scientific-pipelines-service-cli.

This dataset contains the de-identified participant data, a data dictionary and the complete analysis code for the randomised controlled trial “Effect of Corrective Multisport Training on Static…

This dataset contains the de-identified participant data, a data dictionary and the complete analysis code for the randomised controlled trial “Effect of Corrective Multisport Training on Static Trunk and Pelvic Posture in Healthy Children: A Randomised Controlled Trial” (ClinicalTrials.gov NCT07886749). In this single-centre trial, 398 children aged 4–11 years were randomised (1:1, stratified by sex) to a nine-month corrective multisport programme (CMS), in which a 20-min corrective exercise block replaced part of each multisport session, or to a time-matched multisport programme (CON). Ten static postural variables of the trunk and pelvis were assessed with 3D photogrammetry (Contemplas 3D Posture Compact) before and after the intervention. Contents: (1) data/cms_posture_rct_data.csv – one row per randomised child (group, sex, age, educational setting, training group, attendance, anthropometry, ten postural variables at baseline and post-intervention); (2) data/data_dictionary.csv – description, unit and coding of every variable; (3) code/ – Python scripts reproducing all analyses reported in the article (multiple imputation, intention-to-treat mixed models, tipping-point analysis, nonparametric and multivariate permutation tests, cluster bootstrap, measurement error, sensitivity analyses and figures); (4) outputs/ – results of all analyses as CSV files and figures. See README.md for instructions.  

This technical supplement provides explicit Cartesian expressions for finite-basis Correction velocity fields in the Structured Admissible Velocity Field (SAVF) formulation for quarter-domain plane-st…

This technical supplement provides explicit Cartesian expressions for finite-basis Correction velocity fields in the Structured Admissible Velocity Field (SAVF) formulation for quarter-domain plane-strain compression. The document supplements the study presented at the JSME Yamanashi District Conference 2026 by providing detailed velocity-field equations that could not be included in the conference paper due to space limitations. Part I presents expanded expressions for 4-DOF basis sets, while Part II illustrates higher-order extensions through 8-DOF expressions, including the coupled Q9G13 construction. The Q, G, FC, LEG, BERN, CHEB, and JAC basis families are covered using SYM, ASYM, and FULL constructions.

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run them…

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run themselves in Terra. The most common reason for this is that the pipeline accesses proprietary data that users are not allowed to access directly, but that may be used as e.g. a reference panel for imputation. Supported pipelines Current supported pipelines are: Array Imputation with the All of Us + AnVIL Reference Panel Architecture Architecture Doc Architecture Diagram Development This codebase is in initial development. Requirements Technical This service is written in Java 17, and uses Postgres 15. To run locally, you'll also need: jq - install with brew install jq Java 17 - can be installed manually or through IntelliJ which will do it for you when importing the project Postgres 15 - multiple solutions here as long as you have a postgres instance running on localhost:5432 the local app will connect appropriately. Be sure to use Postgres 15 (as of Feb 2025, Postgres 17 did not work) Download Postgres.app (recommended) from https://postgresapp.com/ Brew https://formulae.brew.sh/formula/postgresql@15 External Services Terra services Sam Used to authn users connecting to the service and authz users for admin endpoints Rawls Used to handle workspace interactions creating methods data tables workflow submission Cromwell Used through Rawls to run submissions Thurloe Used to send notification emails to users Tech stack Java 17 temurin Postgres 15 Gradle - build automation tool SonarQube - static code security and coverage Trivy - security scanner for docker images Jib - docker image builder for Java Local development To run locally: Make sure you have the requirements installed from above. We recommend IntelliJ as an IDE. Clone the repo (if you see broken inputs build the project to get the generated sources) Spin up a local postgres instance (NOTE: use version 15) Run the commands in scripts/postgres-init.sql in your local postgres instance. You will need to be authenticated to access GSM. Run scripts/write-config.sh Run ./gradlew bootRun to spin up the server. Navigate to http://localhost:8080/# If this is your first time deploying to any environment, be sure to use the admin endpoint /api/admin/v1/pipelines/{pipelineName}/{pipelineVersion} to set your pipeline's workspace id. To run this endpoint, you need to be authenticated using your firecloud test account. A list of accounts that developers typically need is here. Further, a list of resources that are generally useful is stored here This endpoint requires two parameters directly, and three in the message body: pipelineName can be retrieved by querying the /api/pipelines/v1 endpoint. pipelineVersion can also be retrieved from the /api/pipelines/v1 endpoint. workspaceBillingProject is listed in the Teaspoons Resources document linked above workspaceName is also listed in the Teaspoons Resources document, and can be found through the Terra UI workspace dashboard wdlMethodVersion is found for the specific workflow as listed in the Terra UI page for workflows. Back up local Postgres databases before testing/refactors Before running local migrations/refactors, take backups of both local databases so you can restore quickly. Defaults in this repo (see service/src/main/resources/application.yml and scripts/postgres-init.sql): host 127.0.0.1, port 5432 pipelines_db user/pass: dbuser / dbpwd teaspoons_stairway_db user/pass: stairwayuser / stairwaypwd Backup and verify: ts="$(date +%Y%m%d_%H%M%S)" backup_dir="$HOME/teaspoons-db-backups/$ts" mkdir -p "$backup_dir" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_dump -Fc -f "$backup_dir/pipelines_db.dump" pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_dump -Fc -f "$backup_dir/teaspoons_stairway_db.dump" teaspoons_stairway_db pg_restore -l "$backup_dir/pipelines_db.dump" | head pg_restore -l "$backup_dir/teaspoons_stairway_db.dump" | head echo "Backups written to: $backup_dir" Restore later (replace <admin_password>): PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O dbuser pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_restore --clean --if-exists --no-owner -d pipelines_db "$backup_dir/pipelines_db.dump" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O stairwayuser teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_restore --clean --if-exists --no-owner -d teaspoons_stairway_db "$backup_dir/teaspoons_stairway_db.dump" Local development with the UI When running terra-ui locally against a local teaspoons backend, CORS-related errors can arise. To get around this, run the following command to copy a configuration file that allows requests from localhost: ./scripts/local-dev/copy_web_config.sh Note that this file at the destination path (next to App.java) is ignored via .gitignore, since it should not be used in deployed environments. Local development with debugging If using Intellij (only IDE we use on the team), you can run the server with a debugger. Follow the steps above but instead of running ./gradlew bootRun to spin up the server, you can run (debug) the App.java class through intellij and set breakpoints in the code. Be sure to set the GOOGLE_APPLICATION_CREDENTIALS=config/teaspoons-sa.json in the Run/Debug configuration Environment Variables. Testing the CLI locally If you make changes to openapi.yml, you should test the CLI locally. To create the autogenerated Python client files locally, run ./gradlew :python-client:openApiGenerate The files will be generated in python-client/generated and are ignored from being checked into the repo. (Note: the unqualified ./gradlew openApiGenerate now regenerates all four codegen modules — python-client, rawls-client, client, and service — so qualify the task when you only want the Python client.) To test with the CLI, follow the instructions in the CLI repo: DataBiosphere/terra-scientific-pipelines-service-cli. Running Tests Locally Run ./gradlew service:test to run tests Note: If you encounter errors indicating a failure to load the ApplicationContext due to an error while preparing a database cluster caused by a missing Docker environment, this may be related to newer Docker versions (for example, 29.0.0 and above). To resolve this issue, override the Docker API version in the $HOME/.docker-java.properties file. If the file does not already exist, create it and add the following line: api.version=1.44 If the file mentioned already exists with above line, and the tests are still failing in the same way, try restarting Docker. Running Linter Locally Run ./gradlew spotlessCheck to run linter checks Run ./gradlew :service:spotlessApply to apply fix any issues the linter finds (Optional) Install pre-commit hooks [scripts/git-hooks/pre-commit] has been provided to help ensure all submitted changes are formatted correctly. To install all hooks in [scripts/git-hooks], run: git config core.hooksPath scripts/git-hooks Running SonarQube locally SonarQube is a static analysis code that scans code for a wide range of issues, including maintainability and possible bugs. Get more information from DSP SonarQube Docs If you get a build failure due to SonarQube and want to debug the problem locally, you need to get the sonar token from GSM before running the gradle task. export SONAR_TOKEN=$(gcloud secrets versions access latest --project="broad-dsde-dev" --secret="teaspoons-sonarcloud" | jq '.sonar_token') ./gradlew sonarqube Running this task produces no output unless your project has errors. To generate a report, run using --info: ./gradlew sonarqube --info Connecting to the database To connect to the Teaspoons database, we have a script in dsp-scripts that does all the setup for you. Clone that repo and make sure you're either on Broad Internal wifi or connected to the VPN. Then run the following command: ./db/psql-connect.sh dev teaspoons Deploying to dev Upon merging to main, the dev environment will be automatically deployed via the GitHub Action Bump, Tag, Publish, and Deploy (that workflow is defined here). The two tasks report-to-sherlock and set-version-in-dev will prompt Sherlock to deploy the new version to dev. You can check the status of the deployment in Beehive and in ArgoCD. For more information about deployment to dev, check out DevOps' excellent documentation. Tracing We use OpenTelemetry for tracing, so that every request has a tracing span that can be viewed in Google Cloud Trace. See this DSP blog post for more info. Running the BEE end-to-end tests The end-to-end test that runs against a BEE is specified in .github/workflows/run-bee-e2e-tests.yaml. It calls the workflow defined in the terra-github-workflows repo. The end-to-end test is automatically run nightly on the dev environment. To run the test against a specific feature branch: Grab the image tag for your feature branch. If you've opened a PR, you can find the image tag as follows: go to the Bump, Tag, Publish, and Deploy workflow that's triggered each time you push to your branch From there, go to the tag-publish-docker-deploy task Expand the "Construct docker image name and tag" step The first line should contain the image tag, something like "0.0.81-6761487". Navigate to the e2e-test GHA workflow Click on the "Run workflow" button and select your branch from the dropdown Enter the image tag from step 1 in the "Custom image tag" field If you've updated the end-to-end test in the dsp-resuable-workflows repo, enter either a commit hash or your git branch name. If you don't need to change the test, leave the default as main. Click the green "Run workflow" button. Python clients We publish a "thin", auto-generated Python client that wraps the Teaspoons APIs. This client is published to PyPi and can be installed with pip install teaspoons_client, although this is not meant to be user-facing. The thin api client is generated from the OpenAPI spec in the openapi directory. Publishing occurs automatically when a new version of the service is deployed, via the release-python-client GHA. We also have a user-facing, "thick" CLI whose code lives in a separate repository: DataBiosphere/terra-scientific-pipelines-service-cli.

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run them…

Terra Scientific Pipelines Service Overview Terra Scientific Pipelines Service, or Teaspoons, facilitates running a number of defined scientific pipelines on behalf of users that users can't run themselves in Terra. The most common reason for this is that the pipeline accesses proprietary data that users are not allowed to access directly, but that may be used as e.g. a reference panel for imputation. Supported pipelines Current supported pipelines are: Array Imputation with the All of Us + AnVIL Reference Panel Architecture Architecture Doc Architecture Diagram Development This codebase is in initial development. Requirements Technical This service is written in Java 17, and uses Postgres 15. To run locally, you'll also need: jq - install with brew install jq Java 17 - can be installed manually or through IntelliJ which will do it for you when importing the project Postgres 15 - multiple solutions here as long as you have a postgres instance running on localhost:5432 the local app will connect appropriately. Be sure to use Postgres 15 (as of Feb 2025, Postgres 17 did not work) Download Postgres.app (recommended) from https://postgresapp.com/ Brew https://formulae.brew.sh/formula/postgresql@15 External Services Terra services Sam Used to authn users connecting to the service and authz users for admin endpoints Rawls Used to handle workspace interactions creating methods data tables workflow submission Cromwell Used through Rawls to run submissions Thurloe Used to send notification emails to users Tech stack Java 17 temurin Postgres 15 Gradle - build automation tool SonarQube - static code security and coverage Trivy - security scanner for docker images Jib - docker image builder for Java Local development To run locally: Make sure you have the requirements installed from above. We recommend IntelliJ as an IDE. Clone the repo (if you see broken inputs build the project to get the generated sources) Spin up a local postgres instance (NOTE: use version 15) Run the commands in scripts/postgres-init.sql in your local postgres instance. You will need to be authenticated to access GSM. Run scripts/write-config.sh Run ./gradlew bootRun to spin up the server. Navigate to http://localhost:8080/# If this is your first time deploying to any environment, be sure to use the admin endpoint /api/admin/v1/pipelines/{pipelineName}/{pipelineVersion} to set your pipeline's workspace id. To run this endpoint, you need to be authenticated using your firecloud test account. A list of accounts that developers typically need is here. Further, a list of resources that are generally useful is stored here This endpoint requires two parameters directly, and three in the message body: pipelineName can be retrieved by querying the /api/pipelines/v1 endpoint. pipelineVersion can also be retrieved from the /api/pipelines/v1 endpoint. workspaceBillingProject is listed in the Teaspoons Resources document linked above workspaceName is also listed in the Teaspoons Resources document, and can be found through the Terra UI workspace dashboard wdlMethodVersion is found for the specific workflow as listed in the Terra UI page for workflows. Back up local Postgres databases before testing/refactors Before running local migrations/refactors, take backups of both local databases so you can restore quickly. Defaults in this repo (see service/src/main/resources/application.yml and scripts/postgres-init.sql): host 127.0.0.1, port 5432 pipelines_db user/pass: dbuser / dbpwd teaspoons_stairway_db user/pass: stairwayuser / stairwaypwd Backup and verify: ts="$(date +%Y%m%d_%H%M%S)" backup_dir="$HOME/teaspoons-db-backups/$ts" mkdir -p "$backup_dir" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_dump -Fc -f "$backup_dir/pipelines_db.dump" pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_dump -Fc -f "$backup_dir/teaspoons_stairway_db.dump" teaspoons_stairway_db pg_restore -l "$backup_dir/pipelines_db.dump" | head pg_restore -l "$backup_dir/teaspoons_stairway_db.dump" | head echo "Backups written to: $backup_dir" Restore later (replace <admin_password>): PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O dbuser pipelines_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=dbuser PGPASSWORD=dbpwd \ pg_restore --clean --if-exists --no-owner -d pipelines_db "$backup_dir/pipelines_db.dump" PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> dropdb --if-exists teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=postgres PGPASSWORD=<admin_password> createdb -O stairwayuser teaspoons_stairway_db PGHOST=127.0.0.1 PGPORT=5432 PGUSER=stairwayuser PGPASSWORD=stairwaypwd \ pg_restore --clean --if-exists --no-owner -d teaspoons_stairway_db "$backup_dir/teaspoons_stairway_db.dump" Local development with the UI When running terra-ui locally against a local teaspoons backend, CORS-related errors can arise. To get around this, run the following command to copy a configuration file that allows requests from localhost: ./scripts/local-dev/copy_web_config.sh Note that this file at the destination path (next to App.java) is ignored via .gitignore, since it should not be used in deployed environments. Local development with debugging If using Intellij (only IDE we use on the team), you can run the server with a debugger. Follow the steps above but instead of running ./gradlew bootRun to spin up the server, you can run (debug) the App.java class through intellij and set breakpoints in the code. Be sure to set the GOOGLE_APPLICATION_CREDENTIALS=config/teaspoons-sa.json in the Run/Debug configuration Environment Variables. Testing the CLI locally If you make changes to openapi.yml, you should test the CLI locally. To create the autogenerated Python client files locally, run ./gradlew :python-client:openApiGenerate The files will be generated in python-client/generated and are ignored from being checked into the repo. (Note: the unqualified ./gradlew openApiGenerate now regenerates all four codegen modules — python-client, rawls-client, client, and service — so qualify the task when you only want the Python client.) To test with the CLI, follow the instructions in the CLI repo: DataBiosphere/terra-scientific-pipelines-service-cli. Running Tests Locally Run ./gradlew service:test to run tests Note: If you encounter errors indicating a failure to load the ApplicationContext due to an error while preparing a database cluster caused by a missing Docker environment, this may be related to newer Docker versions (for example, 29.0.0 and above). To resolve this issue, override the Docker API version in the $HOME/.docker-java.properties file. If the file does not already exist, create it and add the following line: api.version=1.44 If the file mentioned already exists with above line, and the tests are still failing in the same way, try restarting Docker. Running Linter Locally Run ./gradlew spotlessCheck to run linter checks Run ./gradlew :service:spotlessApply to apply fix any issues the linter finds (Optional) Install pre-commit hooks [scripts/git-hooks/pre-commit] has been provided to help ensure all submitted changes are formatted correctly. To install all hooks in [scripts/git-hooks], run: git config core.hooksPath scripts/git-hooks Running SonarQube locally SonarQube is a static analysis code that scans code for a wide range of issues, including maintainability and possible bugs. Get more information from DSP SonarQube Docs If you get a build failure due to SonarQube and want to debug the problem locally, you need to get the sonar token from GSM before running the gradle task. export SONAR_TOKEN=$(gcloud secrets versions access latest --project="broad-dsde-dev" --secret="teaspoons-sonarcloud" | jq '.sonar_token') ./gradlew sonarqube Running this task produces no output unless your project has errors. To generate a report, run using --info: ./gradlew sonarqube --info Connecting to the database To connect to the Teaspoons database, we have a script in dsp-scripts that does all the setup for you. Clone that repo and make sure you're either on Broad Internal wifi or connected to the VPN. Then run the following command: ./db/psql-connect.sh dev teaspoons Deploying to dev Upon merging to main, the dev environment will be automatically deployed via the GitHub Action Bump, Tag, Publish, and Deploy (that workflow is defined here). The two tasks report-to-sherlock and set-version-in-dev will prompt Sherlock to deploy the new version to dev. You can check the status of the deployment in Beehive and in ArgoCD. For more information about deployment to dev, check out DevOps' excellent documentation. Tracing We use OpenTelemetry for tracing, so that every request has a tracing span that can be viewed in Google Cloud Trace. See this DSP blog post for more info. Running the BEE end-to-end tests The end-to-end test that runs against a BEE is specified in .github/workflows/run-bee-e2e-tests.yaml. It calls the workflow defined in the terra-github-workflows repo. The end-to-end test is automatically run nightly on the dev environment. To run the test against a specific feature branch: Grab the image tag for your feature branch. If you've opened a PR, you can find the image tag as follows: go to the Bump, Tag, Publish, and Deploy workflow that's triggered each time you push to your branch From there, go to the tag-publish-docker-deploy task Expand the "Construct docker image name and tag" step The first line should contain the image tag, something like "0.0.81-6761487". Navigate to the e2e-test GHA workflow Click on the "Run workflow" button and select your branch from the dropdown Enter the image tag from step 1 in the "Custom image tag" field If you've updated the end-to-end test in the dsp-resuable-workflows repo, enter either a commit hash or your git branch name. If you don't need to change the test, leave the default as main. Click the green "Run workflow" button. Python clients We publish a "thin", auto-generated Python client that wraps the Teaspoons APIs. This client is published to PyPi and can be installed with pip install teaspoons_client, although this is not meant to be user-facing. The thin api client is generated from the OpenAPI spec in the openapi directory. Publishing occurs automatically when a new version of the service is deployed, via the release-python-client GHA. We also have a user-facing, "thick" CLI whose code lives in a separate repository: DataBiosphere/terra-scientific-pipelines-service-cli.