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Implement issue-5507 - add search_runs_by_name #5564
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Signed-off-by: Nikolay Ulmasov <ulmasov@hotmail.com>
refactor tests update docs Signed-off-by: Nikolay Ulmasov <ulmasov@hotmail.com>
Is there a way to re-run the job? ci/circleci: build_doc job failed but I don't see what's wrong there. Same happened on my mac - it failed on first run but was OK on the subsequent few runs with or without additional changes |
The doc string failed to resolve with Sphinx: /home/circleci/project/mlflow/init.py:docstring of mlflow.tracking.fluent.search_runs:3: WARNING: Inline literal start-string without end-string. You can troubleshoot locally by navigating to the make clean
make rsthtml SPHINXOPTS="-W --keep-going -n -T" Although the |
Signed-off-by: Nikolay Ulmasov <ulmasov@hotmail.com>
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Thanks for the changes! LGTM!
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LGTM with one tiny docs comment. Thanks a bunch, @r3stl355 !
Signed-off-by: Nikolay Ulmasov <ulmasov@hotmail.com>
all the changes implemented, ready to merge |
Signed-off-by: Nikolay Ulmasov ulmasov@hotmail.com
What changes are proposed in this pull request?
Implement a function that searches for runs given the experiment name
How is this patch tested?
Added 2 dedicated tests
Does this PR change the documentation?
ci/circleci: build_doc
check. If it's successful, proceed to thenext step, otherwise fix it.
Details
on the right to open the job page of CircleCI.Artifacts
tab.docs/build/html/index.html
.Release Notes
Is this a user-facing change?
Using newly added
experiment_names
inmlflow.search_runs
allows searching for runs with a single call instead of callingmlflow.get_experiment_by_name
followed by a call tomlflow.search_runs
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts
: Artifact stores and artifact loggingarea/build
: Build and test infrastructure for MLflowarea/docs
: MLflow documentation pagesarea/examples
: Example codearea/model-registry
: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models
: MLmodel format, model serialization/deserialization, flavorsarea/projects
: MLproject format, project running backendsarea/scoring
: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra
: MLflow Tracking server backendarea/tracking
: Tracking Service, tracking client APIs, autologgingInterface
area/uiux
: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker
: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy
: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows
: Windows supportLanguage
language/r
: R APIs and clientslanguage/java
: Java APIs and clientslanguage/new
: Proposals for new client languagesIntegrations
integrations/azure
: Azure and Azure ML integrationsintegrations/sagemaker
: SageMaker integrationsintegrations/databricks
: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/breaking-change
- The PR will be mentioned in the "Breaking Changes" sectionrn/none
- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/feature
- A new user-facing feature worth mentioning in the release notesrn/bug-fix
- A user-facing bug fix worth mentioning in the release notesrn/documentation
- A user-facing documentation change worth mentioning in the release notes