azure-mgmt-datalake-analytics

What it is and what it does

This package is the Microsoft Azure Data Lake Analytics Management Client Library for Python, providing programmatic access to manage Data Lake Analytics resources via the Azure Resource Manager (ARM) API. It allows you to create and configure Data Lake Analytics accounts, submit and monitor U-SQL jobs, manage data sources and storage, and interact with the catalog—all through Python code rather than the Azure portal.

The library depends on msrestazure, azure-common, and azure-mgmt-datalake-nspkg to handle REST communication, shared Azure utilities, and namespace packaging. It uses keyword-argument syntax for model objects and returns long-running operations as LROPoller instances for async job tracking. The package is tested against Python 2.7 and 3.4–3.6, though no explicit minimum version is enforced.

Use it for:

• Automate provisioning and configuration of Data Lake Analytics accounts as part of infrastructure-as-code workflows.
• Submit and monitor U-SQL batch jobs programmatically from Python applications or data pipelines.
• Query the Data Lake Analytics catalog to discover tables, databases, and schema information.
• Manage firewall rules, compute policies, and data source associations for Data Lake Analytics accounts.
• Build DevOps automation to scale or update Data Lake Analytics resources in response to workload demands.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Provides Python bindings to manage Azure Data Lake Analytics accounts, jobs, and catalog resources through the Azure Resource Manager API.

Yes, if you are actively managing Azure Data Lake Analytics resources via Python and are comfortable with a library last released in 2018. The package has low install friction, permissive licensing, and no known vulnerabilities. However, verify that it supports your authentication method and Python version before committing; consider checking the Azure SDK documentation for any newer or recommended alternatives for modern Azure deployments.

Install

azure-mgmt-datalake-analytics on PyPI

pip install azure-mgmt-datalake-analytics

uv add azure-mgmt-datalake-analytics

poetry add azure-mgmt-datalake-analytics

Installing azure-mgmt-datalake-analytics

Before you install

Low install friction with three stable runtime dependencies. Actively maintained repository with recent commits. However, the package has not received a release since 2018-06-26, despite the repository remaining active, which may indicate the library is in maintenance-only mode.

License in practice

MIT License permits commercial and private use with minimal restrictions, making it suitable for most deployment scenarios.

Quickstart

pip install azure-mgmt-datalake-analytics

from azure.mgmt.datalake.analytics import DataLakeAnalyticsAccountManagementClient
from msrestazure.azure_active_directory import UserPassCredentials

credentials = UserPassCredentials(username, password)
client = DataLakeAnalyticsAccountManagementClient(credentials, subscription_id)

Requires Azure subscription credentials and subscription ID; older Azure SDK versions (< 1.0) must be uninstalled first to avoid conflicts.

Verify before relying

• Current compatibility with Python versions beyond 3.6 (last tested version per description)
• Whether the library is actively developed or in maintenance-only status given the 2018 release date
• Support for modern Azure authentication methods beyond UserPassCredentials

Package facts

Evidence: azure_mgmt_datalake_analytics-0.6.0-py2.py3-none-any.whl

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