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Add start run by name
🛠 DevTools 🛠
Install mlflow from this PR
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/11896/merge
Checkout with GitHub CLI
gh pr checkout 11896
Related Issues/PRs
Resolve https://github.com/mlflow/mlflow/issues/11783
What changes are proposed in this pull request?
Creates new function to start an mlflow run start_run_by_name
.
Similarly to start_run
this will attempt to resume a run (by performing an exact name lookup), if no runs exist with the specified name, a new run will be created.
In case lookup returns multiple runs with the specified name, an exception is raised
How is this PR tested?
- [X] Existing unit/integration tests
- [X] New unit/integration tests
- [ ] Manual tests
Does this PR require documentation update?
- [ ] No. You can skip the rest of this section.
- [X] Yes. I've updated:
- [X] Examples
- [ ] API references
- [ ] Instructions
Release Notes
Is this a user-facing change?
- [ ] No. You can skip the rest of this section.
- [X] Yes. Give a description of this change to be included in the release notes for MLflow users.
Adds start_run_by_name
function to make it easier to resume existing runs.
What component(s), interfaces, languages, and integrations does this PR affect?
Components
- [ ]
area/artifacts
: Artifact stores and artifact logging - [ ]
area/build
: Build and test infrastructure for MLflow - [ ]
area/deployments
: MLflow Deployments client APIs, server, and third-party Deployments integrations - [ ]
area/docs
: MLflow documentation pages - [ ]
area/examples
: Example code - [ ]
area/model-registry
: Model Registry service, APIs, and the fluent client calls for Model Registry - [ ]
area/models
: MLmodel format, model serialization/deserialization, flavors - [ ]
area/recipes
: Recipes, Recipe APIs, Recipe configs, Recipe Templates - [ ]
area/projects
: MLproject format, project running backends - [ ]
area/scoring
: MLflow Model server, model deployment tools, Spark UDFs - [ ]
area/server-infra
: MLflow Tracking server backend - [X]
area/tracking
: Tracking Service, tracking client APIs, autologging
Interface
- [ ]
area/uiux
: Front-end, user experience, plotting, JavaScript, JavaScript dev server - [ ]
area/docker
: Docker use across MLflow's components, such as MLflow Projects and MLflow Models - [ ]
area/sqlalchemy
: Use of SQLAlchemy in the Tracking Service or Model Registry - [ ]
area/windows
: Windows support
Language
- [ ]
language/r
: R APIs and clients - [ ]
language/java
: Java APIs and clients - [ ]
language/new
: Proposals for new client languages
Integrations
- [ ]
integrations/azure
: Azure and Azure ML integrations - [ ]
integrations/sagemaker
: SageMaker integrations - [ ]
integrations/databricks
: Databricks integrations
How should the PR be classified in the release notes? Choose one:
- [ ]
rn/none
- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section - [ ]
rn/breaking-change
- The PR will be mentioned in the "Breaking Changes" section - [X]
rn/feature
- A new user-facing feature worth mentioning in the release notes - [ ]
rn/bug-fix
- A user-facing bug fix worth mentioning in the release notes - [ ]
rn/documentation
- A user-facing documentation change worth mentioning in the release notes
Should this PR be included in the next patch release?
Yes
should be selected for bug fixes, documentation updates, and other small changes. No
should be selected for new features and larger changes. If you're unsure about the release classification of this PR, leave this unchecked to let the maintainers decide.
What is a minor/patch release?
- Minor release: a release that increments the second part of the version number (e.g., 1.2.0 -> 1.3.0). Bug fixes, doc updates and new features usually go into minor releases.
- Patch release: a release that increments the third part of the version number (e.g., 1.2.0 -> 1.2.1). Bug fixes and doc updates usually go into patch releases.
- [ ] Yes (this PR will be cherry-picked and included in the next patch release)
- [X] No (this PR will be included in the next minor release)
@m-blasiak Thank you for the contribution! Could you fix the following issue(s)?
⚠ DCO check
The DCO check failed. Please sign off your commit(s) by following the instructions here. See https://github.com/mlflow/mlflow/blob/master/CONTRIBUTING.md#sign-your-work for more details.
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@harupy what do you think about this? it looks fine to me (after lint errors are fixed). it's basically to add a convenience function to allow resuming a run by name (see discussion in #11783, the run_name
param in the existing mlflow.start_run()
only allows you to create a new run, not resume an existing one).
@daniellok-db @harupy Any chance to get it reviewed soon? The lint errors should be fixed now
After some discussion, the team decided that since this function serves a fairly specific purpose, it's better if this is kept as user code, rather than being included in the library. Sorry for the delays on this!