Earlier quoted context omitted.
Assuming you want your money to actually add up correctly, then floats are always the wrong choice. If you’re not interested in accurate accounting, the. Sure floats are fine, but when you’re working with money, accurate accounting tends to be the expectation.
Addition is one of those things that does work pretty predictably and error free with floats. The problem with 0.30000000000000004 etc is usually that the things you are adding are not what you expect (float(0.1) != 0.1), i.e. the difficulty usually is string float conversions rather than float arithmetic itself.
If you’re doing money operations at a scale where the computational difference between using true number type with infinite precision vs floats is worth thinking about, then you’re also in the territory where tiny floating point errors really stack up into a problem.
As a consequence, there’s very few scenarios where using floats for money actually makes sense. Either your computation is so simple there’s no real benefit to using floats rather than infinite precision number types, or your computation is so large, that floating point errors sum to meaningful amounts.
The only scenario I can think of where floats might be the right choice is on tiny embedded system where computational power and memory is very limited, and working with infinite precision types is a real problem. But in that scenario, you probably don’t need to be educated on the issues with floats. But if you’re the kind of person who unsure if you should use floats for money, then the answer is almost certainly a resounding “No. Do not use floats for money values”.