---
id: azureml-train-restclients-hyperdrive
version: "1.62.0"
license: https://aka.ms/azureml-sdk-license
license_treatment: unclear
maintenance: active
---

# azureml-train-restclients-hyperdrive — Contains classes needed to create HyperDriveRuns with azureml-train-core.

License: unclear · Maintenance: active · Downloads: 267.5K/mo

## What it is and what it does

azureml-train-restclients-hyperdrive is a REST client library that bridges Azure ML's hyperparameter tuning (HyperDrive) functionality with the core training framework. It provides the low-level classes needed to construct and manage HyperDrive runs—Azure's service for automated hyperparameter optimization—when used alongside azureml-train-core. The package is built on standard HTTP clients (requests, msrest, msrestazure) to communicate with Azure ML's remote services.

This is a specialized component within the broader Azure ML SDK, not a standalone tool. It is typically installed as a dependency of higher-level Azure ML packages or when you need direct control over HyperDrive run configuration. The package is actively maintained and carries no known security vulnerabilities, making it a stable choice for teams already committed to the Azure ML platform.

Use it for:

- Programmatically create and submit hyperparameter tuning jobs to Azure ML from local or remote compute.
- Integrate hyperparameter optimization into Azure ML training pipelines using HyperDrive REST APIs.
- Build custom hyperparameter sweep workflows that require direct control over HyperDrive run objects.
- Extend Azure ML training scripts with automated tuning without manually managing search space and sampling.
- Deploy hyperparameter optimization as part of MLOps workflows on Azure infrastructure.

## Worth the install?

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

Provides REST client classes for creating and managing HyperDrive hyperparameter tuning runs within the Azure ML SDK ecosystem.

Yes, if you are already using Azure ML and need programmatic control over HyperDrive hyperparameter tuning. The package has low install friction, no known vulnerabilities, and active maintenance. However, clarify whether you need it directly or if a higher-level Azure ML package already includes it as a dependency—it is a specialized component, not a general-purpose tool. The unclear license treatment warrants a quick review of Microsoft's terms before use in restricted environments.

## Install

pip install azureml-train-restclients-hyperdrive
uv add azureml-train-restclients-hyperdrive
poetry add azureml-train-restclients-hyperdrive

## Installing azureml-train-restclients-hyperdrive

Before you install: Low install friction with a pure-Python wheel and three common dependencies (requests, msrest, msrestazure). Actively maintained as of the latest release in February 2026.

License in practice: License treatment is unclear—the package points to a Microsoft URL (https://aka.ms/azureml-sdk-license) rather than declaring a standard SPDX identifier, so you should review the actual license terms before use in proprietary or restricted contexts.

Quickstart:

pip install azureml-train-restclients-hyperdrive

from azureml.train.hyperdrive import HyperDriveRun
# Use HyperDriveRun classes with azureml-train-core

Requires Python 3.7 or later (supports up to Python <4). Azure ML workspace and environment setup (per Microsoft's documentation) is a prerequisite for meaningful use.

Verify before relying:

- Exact scope of HyperDrive functionality provided by this package versus azureml-train-core
- Whether this package is intended for direct use or primarily as a transitive dependency
- Performance characteristics or limits on hyperparameter sweep scale

## Package facts

- License: https://aka.ms/azureml-sdk-license (unclear)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 267.5K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

azure ml hyperparameter tuning, hyperdrive rest client, azure ml hyperparameter optimization, azureml hyperdrive runs, azure machine learning tuning, hyperparameter sweep azure, azureml-train-core integration, azure-ml, hyperparameter-tuning, rest-client

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