Today we're looking at Sympy, which is a computer algebra system for doing symbolic calculation or symbolic programming, which basically allows you to define equations and formulas, and then interact with them without resolving the answer to the end - perhaps because the actual numeric value isn't what's interesting.
Correction: Sympy reached out and mentioned:
Just to be clear on something you said near the end, functions like sympify() and parse_expr() that convert strings into sympy expressions are NOT sandboxed. You shouldn't use them on untrusted input without sandboxing the Python process.
I've been using this pretty heavily recently to do some maths around radios, with field equations etc, and looking at how different properties affect different things, and I think this library might not be the 'best (in that it suffers from a little bit of bloat), but it really is a bit unique compared to other maths libraries which are more about data sets, or dealing with large amounts of calculations in parallel rather than sometimes just pure maths - and I mean 'pure maths' here in both senses.
It's not the fastest lib either, but in the right use case, this is a really great tool to add to your arsenal of code.
