##  [04. PyRocky vs Ansys Rocky PrePost Scripting](/blog/04-pyrocky-vs-ansys-rocky-prepost-scripting) 

A common question from **Ansys Rocky** users is:

**What is the difference between PyRocky and Ansys Rocky PrePost Scripting?**

The most accurate answer is that **PyRocky** should not be understood as a complete replacement for Ansys Rocky’s native automation capabilities. Instead, **PyRocky** provides a Python client layer that enables users to interact remotely with **Ansys Rocky** via the **Ansys** **Rocky PrePost Scripting**.

In other words, **PyRocky** makes **Ansys Rocky** automation more accessible from external **Python** environments while still relying on **Ansys Rocky’s** established scripting capabilities.

**Ansys Rocky PrePost Scripting** is the core **Python** based automation mechanism for creating, modifying, running, analyzing, and exporting simulation data from **Ansys Rocky** projects. It is directly connected to **Ansys Rocky’s** internal simulation objects and is especially useful for users who already understand **Ansys Rocky’s**data structure.

**PyRocky** extends this workflow by allowing users to control **Ansys Rocky** from **Python** environments outside the **Ansys Rocky**application. This makes it easier to integrate **Ansys Rocky** with the broader **Python** ecosystem and with other **PyAnsys** libraries.

A practical comparison is shown below.

**Aspect****PyRocky****Ansys Rocky PrePost Scripting**Primary purposeControl Ansys Rocky remotely from PythonAutomate Ansys Rocky model setup, simulation execution, and post-processingExecution contextUsed from external Python environmentsTypically used from Ansys Rocky scripting environmentsMain interface`RockyClient` and `RockyClient.api`Ansys Rocky PrePost scripting objects and methodsLevel of abstractionPython client layer over Ansys Rocky scripting capabilitiesDirect access to Ansys Rocky scripting capabilitiesIntegration with Python toolsMore natural integration with NumPy, Pandas, Matplotlib, Jupyter, and other Python toolsPossible, but more tied to Ansys Rocky’s scripting environmentIntegration with PyAnsysDesigned as part of the PyAnsys ecosystemNot the focusBest suited forWorkflow automation, batch execution, remote scripting, data pipelines, and reproducible studiesDirect Ansys Rocky automation and users familiar with Ansys Rocky scriptingTherefore, the relationship between the two is complementary.

**Ansys Rocky PrePost Scripting** provides an underlying automation capability. **PyRocky** provides a **Pythonic** access layer that makes this capability easier to use in modern automation workflows.

This distinction is important because users should not expect every **PyRocky** command to behave like a completely new high-level API. In its current form, many operations are performed through the same **Ansys** **Rocky PrePost Scripting** methods that **Ansys Rocky** users may already know.

For experienced **Ansys Rocky** users, this is an advantage: existing scripting knowledge can be transferred to **PyRocky** workflows.

For **Python** users, **PyRocky** provides a more familiar, scalable environment for building scripts, notebooks, automation tools, and engineering data pipelines.

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- [Previous: 03. How to Get Started with PyRocky](https://developer.synopsys.com/blog/03-how-get-started-pyrocky)
- [Next: 05. Foundation for AI-Enabled DEM Workflows](https://developer.synopsys.com/blog/05-foundation-ai-enabled-dem-workflows)