Python Versions

Virtuozzo Application Management supports several Python engine versions for both Apache Python and Python Engine application servers. Select the required version when creating an environment or change it later through container redeployment.

In this article

Available Python versions
Create a Python environment
Change the Python version
Expected result

Available Python Versions

The currently documented Python engine releases are:

Python Version	Supported Application Servers	Selection Method
3.10.20	Apache Python and Python Engine	Environment creation or container redeployment
3.11.15	Apache Python and Python Engine	Environment creation or container redeployment
3.12.13	Apache Python and Python Engine	Environment creation or container redeployment
3.13.14	Apache Python and Python Engine	Environment creation or container redeployment
3.14.6	Apache Python and Python Engine	Environment creation or container redeployment

Check the latest stack list

The available release list is updated regularly. Review the Software Stack Versions document before creating or updating a production environment.

Create a Python Environment

Open the topology wizard

Click New Environment at the top of the platform dashboard.

Select the application server

Open the Python tab and choose either Apache Python or Python Engine.

Select the engine version

Choose the required Python version from the engine-version list.

Select a Python version in the topology wizard — Choose Apache Python or Python Engine and select the required Python release.

Complete the environment settings

Adjust the Cloudlet limits, public IPs, region, environment name, and other required settings, then click Create.

The Python environment is provisioned and becomes available in the dashboard within approximately one minute.

Change the Python Version

Use container redeployment to change the Python engine version for an existing node or a complete application-server layer.

Open the redeployment dialog

Use either of the following methods:

Open Change Environment Topology and select the existing Python stack or version.
Click Redeploy Container(s) beside the required node or layer.

Redeploy Python nodes through the topology wizard — Open the container update controls through Change Environment Topology.

Configure the redeployment

Review and configure the following options:

Tag: Select the required Python engine version.
Keep volumes data: Preserve data stored in mounted volumes.
Simultaneous deployment: Redeploy all containers in a scaled layer at the same time.
Sequential deployment with delay: Redeploy scaled containers one by one.

Python container redeployment settings — Choose the Python tag, volume-data option, and deployment sequence.

✓

Scaled environments

Use sequential deployment for multi-node layers when reducing downtime is more important than completing the update as quickly as possible.

Redeploy the containers

Click Redeploy and confirm the action in the pop-up dialog.

Confirm Python container redeployment — Confirm the Python engine version update.

The selected Python version is applied to the container or layer within a few minutes.

Expected Result

A new Apache Python or Python Engine environment runs with the selected Python release, or an existing container is redeployed to another supported version while preserving the selected volume data.

Important Notes

Confirm that the application and its dependencies support the selected Python version.
Review the current Software Stack Versions document before a production update.
Enable Keep volumes data when persistent volume data must remain available.
Simultaneous redeployment can temporarily stop every node in a scaled layer.
Sequential redeployment reduces interruption for multi-node applications.
Review deployment and application logs after changing the Python version.

Common Issues and Solutions

Issue	Solution
The required Python version is not listed	Check the current Software Stack Versions document and confirm that the selected application server supports the required release.
The application fails after redeployment	Review Python compatibility, dependency files, compiled extensions, startup configuration, and application logs.
Persistent files are missing	Restore the files from backup and use the Keep volumes data option during future redeployment.
All nodes become unavailable during the update	Use sequential deployment with delay instead of simultaneous redeployment.
The redeployment option is unavailable	Wait for other environment tasks to finish and confirm that the selected node or layer supports redeployment.