Clean up imports in mlflow/__init__.py for more efficient code navigation

[harupy]

Signed-off-by: harupy hkawamura0130@gmail.com

Related Issues/PRs

#xxx

What changes are proposed in this pull request?

Clean up imports in mlflow/init.py for more efficient code navigation.

Before

code-navigation-before.mov

• We can't directly jump to the log_artifact definition.
• We can't jump to mlflow/artifacts.py.

After

code-navigation-after.mov

• We can directly jump to the log_artifact definition.
• We can jump to mlflow/artifacts.py.

I think we should how jump-to-definition works on different code editors.

How is this patch tested?

• I have written tests (not required for typo or doc fix) and confirmed the proposed feature/bug-fix/change works.

Does this PR change the documentation?

• No. You can skip the rest of this section.
• Yes. Make sure the changed pages / sections render correctly by following the steps below.

1. Click the Details link on the Preview docs check.
2. Find the changed pages / sections and make sure they render correctly.

Release Notes

Is this a user-facing change?

• No. You can skip the rest of this section.
• Yes. Give a description of this change to be included in the release notes for MLflow users.

(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger change.)

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/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/pipelines: Pipelines, Pipeline APIs, Pipeline configs, Pipeline 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
• 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/breaking-change - The PR will be mentioned in the "Breaking Changes" section
• 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/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

[harupy]

This import statement creates a namespace mlflow.artifacts in mlflow:

>>> import mlflow
>>> mlflow.mlflow
<module 'mlflow' from '/home/haru/Desktop/repositories/mlflow/mlflow/__init__.py'>
>>> mlflow.mlflow.artifacts
<module 'mlflow.artifacts' from '/home/haru/Desktop/repositories/mlflow/mlflow/artifacts/__init__.py'>

[harupy]

With the updated __init__.py:

>>> import mlflow
>>> mlflow.mlflow
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: module 'mlflow' has no attribute 'mlflow'

[BenWilson2]

LGTM! Nice cleanup