azure-batch
Microsoft Corporation Azure Batch Client Library for Python
Decision gist · record as of 2026-08-14
Yes. azure-batch is actively maintained, has low install friction, supports current Python versions (3.9–3.13), and carries no known vulnerabilities. It is the standard way to interact with Azure Batch from Python. Install it if you need to run distributed batch workloads on Azure; the main consideration is that v15.x is a significant departure from v14.x, so review the migration guide if upgrading from an older version.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later, an Azure subscription, a Batch account with a linked Storage account, and appropriate Azure credentials.
- Low install friction with a pure-Python wheel distribution.
- The package is actively maintained with a recent release and supports modern Python versions (3.9–3.13).
License · maintenance · safety
(unclear)
last release 2026-05-01 (105 days) · last repo commit 2026-08-14 · 5,587 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 28,054,691 downloads/mo, #841 on PyPI
Alternatives
Verify before relying
pip install azure-batch
from azure.batch import BatchClient
from azure.core.credentials import AzureNamedKeyCredential
credentials = AzureNamedKeyCredential(account_name, account_key)
client = BatchClient(
endpoint='https://<account>.eastus.batch.azure.com',
credential=credentials
)- Whether license_raw and license_spdx being null indicates an undeclared or default license rather than a true licensing gap.
- Whether authentication workflows typically require additional Azure SDK components beyond the listed runtime dependencies.
- Whether v15.x migration from v14.x introduces breaking changes that affect existing deployments.
What it is and what it does
azure-batch is the official Python client library for Azure Batch, Microsoft's service for running large-scale parallel and high-performance computing workloads on Azure infrastructure. It allows developers to programmatically create compute pools, submit batch jobs, define tasks, and monitor execution across distributed compute nodes. The library handles the low-level communication with the Azure Batch REST API and provides object models for pools, jobs, tasks, and nodes.
The package is designed for workloads that require coordinated execution of many independent or loosely-coupled tasks across multiple compute resources—typical use cases include scientific simulations, data processing pipelines, rendering farms, and machine learning training jobs. It supports both synchronous and asynchronous clients and integrates with Azure identity services for authentication. The description notes that v15.x introduces significant changes from earlier versions.
Use it for
- Submit and manage large-scale parallel compute jobs across Azure-hosted compute pools without manual infrastructure provisioning.
- Orchestrate multi-task batch workflows where individual tasks run independently on different compute nodes and report results back.
- Monitor job progress, task status, and compute node health in real time via the Batch API.
- Scale compute resources up or down based on workload demand using Azure Batch's autoscaling formulas.
- Retrieve task output files and logs after job completion for post-processing or analysis.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
azure-batch is actively maintained, has low install friction, supports current Python versions (3.9–3.13), and carries no known vulnerabilities. It is the standard way to interact with Azure Batch from Python. Install it if you need to run distributed batch workloads on Azure; the main consideration is that v15.x is a significant departure from v14.x, so review the migration guide if upgrading from an older version.
Install
azure-batch on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. The package is actively maintained with a recent release and supports modern Python versions (3.9–3.13). Three lightweight runtime dependencies (isodate, azure-core, typing-extensions) keep the dependency footprint minimal.
Requires Python 3.9 or later, an Azure subscription, a Batch account with a linked Storage account, and appropriate Azure credentials.
Quickstart
pip install azure-batch
from azure.batch import BatchClient
from azure.core.credentials import AzureNamedKeyCredential
credentials = AzureNamedKeyCredential(account_name, account_key)
client = BatchClient(
endpoint='https://<account>.eastus.batch.azure.com',
credential=credentials
)Verify before relying
- Whether license_raw and license_spdx being null indicates an undeclared or default license rather than a true licensing gap.
- Whether authentication workflows typically require additional Azure SDK components beyond the listed runtime dependencies.
- Whether v15.x migration from v14.x introduces breaking changes that affect existing deployments.
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesisodateazure-coretyping-extensions |
| Maintenance | Actively maintained 105 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 28,054,691 / month, #841 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9 |
Evidence: azure_batch-15.1.0-py3-none-any.whl
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See also azure-mgmt-batchai · azure-mgmt-batch · azure-storage-queue · azure-storage-blob · codeflare-sdk · msgraph-sdk · azure-mgmt-containerregistrytasks · azure-mgmt-compute · azure-monitor-querymetrics · locust