As our series on python classes continues we will delve into a simple example of how to leverage two dunder methods covered in the previous article, which are used "under the hood" to perform much of the day-to-day business logic in Python.

This series on classes in Python continues. This article introduces "dunder" methods and how they might apply to classes.

Here we are with Part 7 in this series on classes in Python. This article covers setters (the method on a class that sets a property) and getters (which gets the property).

Part six of ten in this series on classes in Python covers the levels of obfuscation available in Python: private and super-private.

Python is quite good at reading, writing and finding things in text files. This allows us to develop tools that can be used to find data in NASTRAN inputs files and create the ANSYS APDL equivalent.

PyWorkbench is a powerful client library that enhances the Ansys Workbench platform for engineering simulations. This guide introduces key concepts and practical strategies for using PyWorkbench, making your engineering simulations more efficient and effective.

This series continues by exploring two notable exceptions to the self parameter for methods, classmethod and staticmethod.

This article walks users through creating coordinate systems from the coordinates of three non-colinear points, and then using two coordinate systems to align the external imported data with the current Mechanical model. This tool allows users to eliminate the guesswork from the alignment process and improve the accuracy of data alignment.

Part-four of this series sees us move from the "basic" knowledge required to understand classes and into more "intermediate" topics - starting with mutability of dataclasses.