azure-ai-ml-py
Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.
Azure Machine Learning SDK v2 for Python
Client library for managing Azure ML resources: workspaces, jobs, models, data, and compute.
Installation
pip install azure-ai-ml
Environment Variables
AZURE_SUBSCRIPTION_ID=<your-subscription-id>
AZURE_RESOURCE_GROUP=<your-resource-group>
AZURE_ML_WORKSPACE_NAME=<your-workspace-name>
Authentication
from azure.ai.ml import MLClient
from azure.identity import DefaultAzureCredential
ml_client = MLClient(
credential=DefaultAzureCredential(),
subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"],
resource_group_name=os.environ["AZURE_RESOURCE_GROUP"],
workspace_name=os.environ["AZURE_ML_WORKSPACE_NAME"]
)
From Config File
from azure.ai.ml import MLClient
from azure.identity import DefaultAzureCredential
# Uses config.json in current directory or parent
ml_client = MLClient.from_config(
credential=DefaultAzureCredential()
)
Workspace Management
Create Workspace
from azure.ai.ml.entities import Workspace
ws = Workspace(
name="my-workspace",
location="eastus",
display_name="My Workspace",
description="ML workspace for experiments",
tags={"purpose": "demo"}
)
ml_client.workspaces.begin_create(ws).result()
List Workspaces
for ws in ml_client.workspaces.list():
print(f"{ws.name}: {ws.locSubscribers only
The full skill, its 1 bundled files and every download is included with every paid Complete AI plan.
Details
| Source | community |
|---|---|
| License | — |
| Risk label | critical ("critical" means the skill may run commands or touch files — read before use) |
| Files | SKILL.md |
| Added | 2026-02-27 |
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