sagemaker-mlflow 0.5.0

AWS Plugin for MLflow with SageMaker

SageMaker MLflow Plugin

What does this Plugin do?

This plugin generates Signature V4 headers in each outgoing request to the Amazon SageMaker with MLflow capability, determines the URL of capability to connect to tracking servers, and registers models to the SageMaker Model Registry. It generates a token with the SigV4 Algorithm that the service will use to conduct Authentication and Authorization using AWS IAM.

Installation

To install this plugin (lightweight, depends on mlflow-skinny):

pip install sagemaker-mlflow

To install with the full mlflow dependency set:

pip install sagemaker-mlflow[full]

To install from source:

pip install .

Custom AWS session

By default, the plugin signs requests using credentials from the boto3 default credential chain (environment variables, shared config, instance role, etc.). Callers that need to sign with a specific boto3.Session — for example a non-default profile or per-tenant credentials in a shared process — can inject one without mutating os.environ:

import boto3
import mlflow
import sagemaker_mlflow

custom = boto3.Session(profile_name="my-profile")

with sagemaker_mlflow.use_session(custom):
    mlflow.MlflowClient().search_experiments(max_results=1)

use_session is a context manager scoped to the current thread / asyncio task; the previous session is restored on exit (including on exception). sagemaker_mlflow.set_session(session) is also available for setting a default that lasts for the rest of the context. Resolution order inside AuthBoto: explicit boto3_session= kwarg → use_session/set_session → boto3.Session().

Development details

setup.py

setup.py Contains the primary entry points for the sdk. install_requires Installs mlflow-skinny (lightweight) by default. The [full] extra installs the full mlflow package. entry_points Contains the entry points for the sdk. See https://mlflow.org/docs/latest/plugins.html#defining-a-plugin for more details.

Running tests

Setup

To run tests using tox, run:

pip install tox

Installing tox will enable users to run multi-environment tests. On the other hand, if running individual tests in a single environment, feel free to continue to use pytest instead.

Running format checks

tox -e flake8,black-check,typing,twine

Formatting code to comply with format checks

tox -e black-format

Running unit tests

tox --skip-env "black.*|flake8|typing|twine" -- test/unit

Running integration tests

tox --skip-env "black.*|flake8|typing|twine" -- test/integration

Available test environments by default

tox.ini contains support for:

• Python 3.9: mlflow 2.8., 2.9., 2.10., 2.11., 2.12., 2.13., 2.16.*, 3.0.0
• Python 3.10/3.11: mlflow 2.8., 2.9., 2.10., 2.11., 2.12., 2.13., 2.16.*, 3.0.0, 3.4.0, 3.10.0

To add test environments on tox for additional versions of python or mlflow, modify the environment configs in envlist, as well as deps and depends in [testenv].