Change log#

0.11.0 (2024-04-24)#

Bug fixes#

  • Nublado v3 requires gid as well as uid, and both uid and gid should be int rather than str

0.10.0 (2024-03-26)#

New features#

  • Add a NOTEBURST_WORKER_MAX_CONCURRENT_JOBS environment variable configuration to limit the number of concurrent jobs a worker can run. The default is 3. Previously this was 10. This should be set to be equal or less than the number of CPUs available to the JupyterLab pod.

  • The notebook execution client now waits as long as possible for the /execution endpoint in the JupyterLab pod to return the executed notebook. Previously the client would wait for a fixed amount of time, which could be too short for long-running notebooks. The JupyterLab server may still time-out the request, though.

Bug fixes#

  • Improved handling of the XSRF token when authenticated to JupyterHub and JupyterLab pods. This is required in JupyterLab 4.1.

0.9.1 (2024-03-21)#

Bug fixes#

  • Fix Slack error messaging in the nbexec worker function.

  • Extract and use the actual XSRF token when communicating with the Hub and Lab.

0.9.0 (2024-03-13)#

New features#

  • Add formatted errors when a job is not found for the GET /v1/notebooks/:job_id endpoint.

  • Errors and uncaught exceptions are now sent to Slack via a Slack webhook. The webhook URL is set via the SLACK_WEBHOOK_URL environment variable.

Other changes#

  • The code base now uses Ruff for linting and formatting, replacing black, isort, and flake8. This change is part of the ongoing effort to standardize SQuaRE code bases and improve the developer experience.

0.8.0 (2024-01-04)#

New features#

  • The response to GET /notebooks/:job_id now includes an ipynb_error field that contains structured information about any exception that occurred when executing the notebook. As well, if an exception occurred, the resultant notebook is still included in the response. That is, notebook failures are no longer considered failed jobs.

  • The job_id is now included in log messages when running the nbexec job under arq.

  • The user guide includes a new tutorial for using the Noteburst web API.

Other changes#

  • Update to Pydantic 2

  • Adopt FastAPI’s lifespan feature

  • Adopt scriv for changelog management

  • Update GitHub Actions workflows, including integrating Neophile for dependency updates.

  • Update to Python 3.12.

0.7.1 (2023-07-23)#

Bug fixes#

  • Add additional logging of JupyterLab spawning failures in workers.

Other changes#

  • Added documentation for configuration environment variables.

  • Added OpenAPI docs, rendered by Redoc, to the Sphinx documentation site.

0.7.0 (2023-05-22)#

New features#

  • The JupyterHub service’s URL path prefix is now configurable with the NOTEBURST_JUPYTERHUB_PATH_PREFIX environment variable. The default is /nb/, which is the existing value.

  • The Nublado JupyterLab Controller service’s URL path prefix is configurable with the NOTEBURST_NUBLADO_CONTROLLER_PATH_PREFIX environment variable. The default is /nublado, which is the existing value.

0.6.3 (2023-04-20)#

Bug fixes#

  • Fix how failed notebook executions are handled. Previously failed notebooks would prevent Noteburst from getting the results of the execution job. Now the job is shown as concluded but unsuccessful by the /v1/notebooks/{job_id} endpoint.

  • Structure uvicorn server logging.

0.6.2 (2023-04-12)#

Bug fixes#

  • Stop following redirects from the hub/login endpoint.

  • Explicitly shut down the lab pod on worker shutdown.

0.6.1 (2023-03-28)#

Bug fixes#

  • Additional updates for JupyterLab Controller image API endpoint.

0.6.0 (2023-02-16)#

New features#

  • Migrated from the Cachemachine API to the new JupyterLab Controller API for obtaining the list of available Docker images for JupyterLab workers.

Other changes#

  • Migrated to Python 3.11

  • Adopted pyproject.toml for project metadata and dropped setup.cfg.

0.5.0 (2022-07-04)#

New features#

  • Its now possible to skip retries on notebook execution failures in the nbexec task by passing an enable_retry=False keyword argument. This is useful for applications that use Noteburst for continuous integration.

0.4.0 (2022-06-15)#

New features#

  • The worker identity configuration can now omit the uid field for environments where Gafaelfawr is able to assign a UID (e.g. through an LDAP backend).

  • New configurations for workers:

    • The new NOTEBURST_WORKER_TOKEN_LIFETIME environment variable enables you to configure the lifetime of the workers’ authentication tokens. The default matches the existing behavior, 28 days.

    • NOTEBURST_WORKER_TOKEN_SCOPES environment variable enables you to set what token scopes the nublado2 bot users should have, as a comma-separated list.

    • NOTEBURST_WORKER_IMAGE_SELECTOR allows you to specify what stream of Nublado image to select. Can be recommended, weekly or reference. If the latter, you can specify the specific Docker image with NOTEBURST_WORKER_IMAGE_REFERENCE.

    • The NOTEBURST_WORKER_KEEPALIVE configuration controls whether the worker keep alive function is run (to defeat the Nublado pod culler), and at what frequency. Set to disabled to disable; fast to run every 30 seconds; or normal to run every 5 minutes.

  • Noteburst now uses the arq client and dependency from Safir 3.2, which was originally developed from Noteburst.

0.3.0 (2022-05-24)#

New features#

Improved handling of the JupyterLab pod for noteburst workers:

  • If the JupyterLab pod goes away (such as if it is culled), the Noteburst workers shuts down so that Kubernetes creates a new worker with a new JupyterLab pod. A lost JupyterLab pod is detected by a 400-class response when submitting a notebook for execution.

  • If a worker starts up and a JupyterLab pod already exists for an unclaimed identity, the noteburst worker will continue to cycle through available worker identities until the JupyterLab start up is successful. This handles cases where a Noteburst worker restarts, but the JupyterLab pod did not shut down and thus is “orphaned.”

  • Each JupyterLab worker runs a “keep alive” function that exercises the JupyterLab pod’s Python kernel. This is meant to counter the “culler” that deletes dormant JupyterLab pods in the Rubin Science Platform. Currently the keep alive function runs every 30 seconds.

  • The default arq job execution timeout is now configurable with the NOTEBURST_WORKER_JOB_TIMEOUT environment variable. By default it is 300 seconds (5 minutes).

0.2.0 (2022-03-14)#

New features#

  • Initial version of the /v1/ HTTP API.

  • Migration to Safir 3 and its database framework.

  • Noteburst is now cross-published to the GitHub Container Registry, ghcr.io/lsst-sqre/noteburst.

  • Migration to Python 3.10.

0.1.0 (2021-09-29)#

New features#

  • Initial development version of Noteburst.