---
id: azure-ml-component
version: "0.9.18.post2"
license: https://aka.ms/azureml-sdk-license
license_treatment: unclear
maintenance: abandoned
---

# azure-ml-component — Azure Machine Learning Component SDK

License: unclear · Maintenance: abandoned · Downloads: 127.2K/mo

## What it is and what it does

Azure-ml-component is a Python SDK for defining, registering, and orchestrating reusable components within Azure Machine Learning pipelines. It abstracts the authoring of ML workflows into composable, versioned components that can be shared and reused across projects. The package depends on azureml-core, azureml-telemetry, and a set of utility libraries (psutil, tqdm, pydash, ruamel.yaml, omegaconf, jinja2, bytecode, azure-core) to handle configuration, templating, and Azure service communication.

The package targets data scientists and ML engineers building production workflows on Azure. However, it has been abandoned for over three years (last release 2023-05-12), meaning no active maintenance, bug fixes, or compatibility updates are available. It supports Python 3.6 through 3.10, but future Python versions and Azure service changes are not guaranteed to be compatible.

Use it for:

- Define reusable ML components (data prep, training, evaluation) and compose them into multi-step pipelines
- Register and version components in Azure ML for team collaboration and reproducibility
- Automate end-to-end ML workflows by submitting component-based pipelines to Azure ML compute
- Migrate legacy Azure ML component definitions from older SDK versions into a standardized format

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Authoring, managing, and submitting Azure Machine Learning components and pipelines through a Python SDK.

No, unless you are maintaining legacy Azure ML pipelines already built with this package. The package is abandoned (no updates in 1190 days) and unlikely to work reliably with current Azure ML service versions. For new projects, use the current Azure ML Python SDK instead of this outdated component framework.

## Install

pip install azure-ml-component
uv add azure-ml-component
poetry add azure-ml-component

## Installing azure-ml-component

Before you install: Low install friction with a pure-Python wheel, but the package is abandoned as of 1190 days since last release. Maintenance status is inactive, so security patches and compatibility updates are unlikely.

License in practice: License treatment is unclear; the package points to a Microsoft proprietary license URL (https://aka.ms/azureml-sdk-license) without an SPDX identifier. Review the linked license before committing to production use.

Quickstart:

pip install azure-ml-component

from azure.ml.component import Component
# Define and register a component, then use it in a pipeline

Requires Azure ML workspace credentials and connectivity; the package is abandoned and may not work with current Azure ML service versions.

Verify before relying:

- Whether the package remains compatible with current Azure ML service APIs and authentication flows
- Whether the abandoned status affects support for modern Python versions beyond 3.10
- Whether existing Azure ML pipelines authored with this package can migrate to current Azure ML tooling

## Package facts

- License: https://aka.ms/azureml-sdk-license (unclear)
- Python support: supports_current
- Install friction: low
- Maintenance: abandoned
- Downloads: 127.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

azure machine learning components, azure ml pipeline authoring, azureml component sdk, azure ml workflow automation, machine learning pipeline management, azure ml component definition, azureml pipeline submission, azure-ml, abandoned, legacy

[View on SkillFed](https://skillfed.io/packages/azure-ml-component) · [View on PyPI](https://pypi.org/project/azure-ml-component/)