Ansys Python Manager – The Easiest Way to Set Up Your PyAnsys Machine

Naveen Kumar Begari
06:00 MINS
November 3, 2025

Python has established itself as one of the most versatile and widely used programming languages, powering applications across data science, machine learning, web development, and automation. In the realm of simulation and engineering, PyAnsys – a suite of open-source Python libraries—brings this same flexibility to Ansys products. For engineers and developers looking to streamline simulation workflows, understanding how to setup PyAnsys is essential to unlocking its full potential.

PyAnsys offers a Pythonic interface that enables engineers to automate complex workflows, run parametric studies, and efficiently post-process simulation results. It effectively bridges the gap between high-end simulation tools and modern programming practices, allowing users to extend Ansys capabilities with ease.

That said, setting up Python environments, managing dependencies, and ensuring compatibility between different Ansys and PyAnsys versions can sometimes be tricky. This is where the Ansys Python Manager proves invaluable, providing a streamlined and user-friendly solution for installing, configuring, and managing Python environments tailored for Ansys workflows.

What is the Ansys Python Manager?

Resource: Blog | Ansys Developer Portal

The Ansys Python Manager (APM) is a collaborative, open-source, Python Qt-based application developed by multiple teams within Ansys. It is designed to simplify the use of Python in engineering and simulation workflows, and it has quickly gained recognition for its ability to streamline environment management, package handling, and seamless integration with the broader PyAnsys ecosystem.

With the Ansys Python Manager, users can easily install Python, create and manage virtual environments, and launch their preferred Integrated Development Environments (IDEs) or development shells – all through an intuitive graphical interface.

This guide highlights the key capabilities of the Ansys Python Manager, including:

Installing and managing Python versions
Creating and maintaining virtual environments
Installing and updating PyAnsys packages
Simplifying dependency management
Accessing PyAnsys documentation directly within the app
Keeping the Ansys Python Manager up to date

Installing the Ansys Python Manager

To get started with Python environments for PyAnsys, follow these steps to install Ansys Python Manager:

1. Download the Installer

Ansys-Python-Manager-Setup-v*.exe

2. Run the Installer

3. Launch Ansys Python Manager

4. Start Managing Python Environments

Installing Python

To install Python using the Ansys Python Manager, follow these steps:

Once the installation is complete, your selected Python version will be ready to use for creating virtual environments and managing PyAnsys packages.

Configurable Options for the Installer

The Ansys Python Manager offers two installation options for Python:

Users can choose from the following Python versions:

These options allow you to tailor your Python environment to the needs of your projects and ensure compatibility with PyAnsys packages.

What is Virtual Environment?

A Python virtual environment is an isolated container that contains all the packages and dependencies needed for a specific project. It allows you to create multiple environments for different projects, keeping each project independent and avoiding conflicts between package versions. You can assign a specific Python version to each environment and install the exact package versions required for your project. This approach makes development workflows cleaner, more organized, and reproducible—particularly useful when managing complex projects or multiple PyAnsys setups.

Creating a Python Virtual Environment

To create a Python virtual environment using the Ansys Python Manager, follow these steps:

By default, the Ansys Python Manager creates virtual environments in the following locations:

If you want to customize the default path, go to File → Configure (or press Ctrl + D), enter your preferred path in the first text box, and click Save.

Delete a Virtual Environment

Launching Options

The following options are available for starting your Python environments:

Launch Console: Opens a console window where python points to the selected environment.
Launch VSCode: Starts Visual Studio Code. If VSCode is not installed, the manager provides installation instructions.
Launch JupyterLab: Opens a JupyterLab session. If not installed, the manager installs it automatically.

General Package Management options

Install Python Default Packages: Installs the latest compatible versions of essential libraries, including NumPy, SciPy, Pandas, Matplotlib, PyVista, and Scikit-learn.
Install PyAnsys: Installs the latest compatible PyAnsys metapackage, giving access to all the latest public PyAnsys libraries that work with the current Ansys products.
List Installed Packages: Displays all installed packages for the selected Python environment, helping you verify dependencies and identify potential issues.

This structure allows you to launch IDEs, manage packages, and maintain Python environments efficiently – all from a single, intuitive interface, making your workflow cleaner and more productive.

PyAnsys Package Management options

The PyAnsys Package Management section in the Ansys Python Manager provides a flexible and convenient interface for installing and managing both PyAnsys metapackages and individual PyAnsys components within your selected Python installation or virtual environment.

Using the drop-down menu, you can select the desired PyAnsys metapackage and its version. Once selected, click Install, and the Ansys Python Manager will automatically download and set up the chosen package. You can also install individual PyAnsys libraries, such as ansys-mechanical-core, ansys-mapdl-core, or ansys-fluent-core, depending on the specific requirements of your project.

Note: Installation time may vary depending on package size and your internet connection.

Updating the Ansys Python Manager

To ensure you are running the latest version, the Ansys Python Manager includes a built-in update feature. Simply go to the File menu and select Check for Updates. The application will verify if a newer version is available and guide you through the update process if needed. Keeping the manager up to date ensures full compatibility with the latest PyAnsys releases and new features.

Accessing PyAnsys Documentation

The Ansys Python Manager also provides direct access to PyAnsys documentation for quick reference. Through the Help menu, select your desired PyAnsys project from the drop-down list and click Open Website. This will take you to the official documentation page for that project, offering detailed guides, examples, and API references – all accessible with a single click.

This integrated documentation access allows you to quickly explore available functions, understand package capabilities, and accelerate your workflow development within the PyAnsys ecosystem.

Conclusion

This integrated documentation access allows you to quickly explore available functions, understand package capabilities, and accelerate your workflow development within the PyAnsys ecosystem. Whether you’re just starting out or optimizing advanced simulations, knowing how to setup PyAnsys ensures a smoother and more efficient experience.

The Ansys Python Manager simplifies Python setup for simulation and engineering workflows. It handles Python installations, virtual environments, and PyAnsys packages through an intuitive interface that keeps your workflow efficient. With flexible options to launch environments in various IDEs and shells, it lets engineers focus on innovation instead of setup. By leveraging its full potential, you can speed up PyAnsys development, maintain consistent environments, and reduce manual configuration.

So why wait? Download the Ansys Python Manager today and take your PyAnsys projects to the next level.

References

If you missed the previous post in this series, please check out Understanding gRPC-Based Python-Ansys Integration: Enabling Smart Engineering Solutions with PyAnsys.

Note: In the upcoming blog, we’ll focus on the core aspects of Mechanical, explore how to launch it using PyMechanical, and share some key insights about PyMechanical. Stay tuned!

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