:sparkles: kedro-mlflow now uses the default configuration (ignoring mlflow.yml) if an active run already exists in the process where the pipeline is started, and uses this active run for logging. This enables using kedro-mlflow with an orchestrator which starts mlflow itself before running kedro (e.g. airflow, the mlflow run command, AzureML...) (#358)
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Release 0.11.5
[0.11.5] - 2022-12-12
Added
:sparkles: Added an extra server.mlflow_registry_uri key in mlflow.yml to set the mlflow registry uri. (#260)
:sparkles: Add support for authorization with expiring tokens by adding an extra server.request_header_provider entry in mlflow.yml (#357)
Fixed
:bug: MlflowArtifactDataSet.load() now correctly loads the artifact when both artifact_path and run_id arguments are specified. Previous fix in 0.11.4 did not work because when the file already exist locally, mlflow did not download it again so tests were incorrectly passing (#362)
Removed
:fire: :boom: Remove reload_kedro_mlflow line magic for notebook because kedro will deprecate the entrypoint in 0.18.3. It is still possible to access the mlflow client associated to the configuration in a notebook with context.mlflow.server._mlflow_client (#349). This is not considered as a breaking change since apparently no one uses it according to a discussion with kedro's team.
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Release 0.11.4
[0.11.4] - 2022-10-04
Fixed
:bug: MlflowArtifactDataSet.load() now correctly loads the artifact when both artifact_path and run_id arguments are specified instead of raising an error (#362)
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Release 0.11.3
[0.11.3] - 2022-09-06
Changed
:loud_sound: kedro-mlflow has its default logging level set to INFO. This was the default for kedro<=0.18.1. For kedro>=0.18.2, you can change the level in logging.yml (#348)
Fixed
:bug: kedro-mlflow now use the package_name as experiment name by default if it is not specified. This is done to ensure consistency with the behaviour with no mlflow.yml file (#328)
:memo: Update broken links to the most recent kedro and mlflow documentation
:sparkles: kedro-mlflow now uses the default configuration (ignoring mlflow.yml) if an active run already exists in the process where the pipeline is started, and uses this active run for logging. This enables using kedro-mlflow with an orchestrator which starts mlflow itself before running kedro (e.g. airflow, the mlflow run command, AzureML...) (#358)
[0.11.5] - 2022-12-12
Added
:sparkles: Added an extra server.mlflow_registry_uri key in mlflow.yml to set the mlflow registry uri. (#260)
:sparkles: Add support for authorization with expiring tokens by adding an extra server.request_header_provider entry in mlflow.yml (#357)
Fixed
:bug: MlflowArtifactDataSet.load() now correctly loads the artifact when both artifact_path and run_id arguments are specified. Previous fix in 0.11.4 did not work because when the file already exist locally, mlflow did not download it again so tests were incorrectly passing (#362)
Removed
:fire: :boom: Remove reload_kedro_mlflow line magic for notebook because kedro will deprecate the entrypoint in 0.18.3. It is still possible to access the mlflow client associated to the configuration in a notebook with context.mlflow.server._mlflow_client (#349). This is not considered as a breaking change since apparently no one uses it according to a discussion with kedro's team.
[0.11.4] - 2022-10-04
Fixed
:bug: MlflowArtifactDataSet.load() now correctly loads the artifact when both artifact_path and run_id arguments are specified instead of raising an error (#362)
[0.11.3] - 2022-09-06
Changed
:loud_sound: kedro-mlflow has its default logging level set to INFO. This was the default for kedro<=0.18.1. For kedro>=0.18.2, you can change the level in logging.yml (#348)
Fixed
:bug: kedro-mlflow now uses the package_name as experiment name by default if it is not specified. This is done to ensure consistency with the behaviour with no mlflow.yml file (#328)
:memo: Update broken links to the most recent kedro and mlflow documentation
[0.11.2] - 2022-08-28
Changed
:sparkles: kedro-mlflow now runs even without a mlflow.yml file in your conf/<env> folder. As a consequence, running kedro mlflow init is now optional and should be only used for advanced configuration. (#328)
Commits
e2afa95 :rocket: Bump version and CHANGELOG for release 0.11.6 (#389)
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dependabot[bot]
commented
1 year ago
Bumps kedro-mlflow from 0.11.1 to 0.11.6.
Release notes
Sourced from kedro-mlflow's releases.
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Changelog
Sourced from kedro-mlflow's changelog.
Commits
e2afa95:rocket: Bump version and CHANGELOG for release 0.11.6 (#389)3fdc5ea:arrow_up: Update sphinx requirement645d278:arrow_up: Bump isort from 5.11.1 to 5.11.4503f65c:sparkles: Use active mlflow run if it was started before the kedro run to en...e44fcff:rocket: Bump version and CHANGELOG for release 0.11.5 (#384)289e886:arrow_up: Bump isort from 5.10.1 to 5.11.19895f2b:construction_worker: Update CI dependencies and change defaults3b71b1a:mag: Nudge users to star the repoe009fee:pencil2: Remove duplicated PyPI classifiers entrieseb15432:wrench: Update isort configuration to most recent styleDependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting
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