- cross-posted to:
- programmerhumor@lemmy.ml
- cross-posted to:
- programmerhumor@lemmy.ml
cross-posted from: https://lemmy.ml/post/24332731
StolenCross-posted from here: https://fosstodon.org/@foo/113731569632505985
cross-posted from: https://lemmy.ml/post/24332731
StolenCross-posted from here: https://fosstodon.org/@foo/113731569632505985
Please tell me you aren’t using floating points with money
Knowing not to use floating point with money is good use of that knowledge.
You’d be dismayed to find out how often I’ve seen people do that.
Yeah I shudder when I see floats and currency.
Eh, if you use doubles and you add 0.000314 (just over 0.03 cents) to ten billion dollars you have an error of 1/10000 of a cent, and thats a deliberately perverse transaction. Its not ideal but its not the waiting disaster that using single precision is.
That sounds like an explosive duo
How do you do money? Especially with stuff like some prices having three or four decimals
Instead of representing $1.102 as
1.102your store it as1012(or whatever precision you need) and divide by 1000 only for displaying it.So if you handle different precisions you also need to store the precision/exponent explicitly for every value. Or would you sanitise this at input and throw an exception if someone wants more precision than the program is made for?
It depends on the requirements of your app and what programming language you use. Sometimes you can get away with using a fixed precision that you can assume everywhere, but most common programming languages will have some implementation of a decimal type with variable precision if needed, so you won’t need to implement it on your own outside of university exercises.
Okay thank you. I was wondering because for stuff like buying electricity, gas or certain resources, parts etc. there is prices with higher precision in cents, but the precision would not be identical over all use cases in a large company.
No exponent, or at least a common fixed exponent. The technique is called “fixed point” as opposed to “floating point”. The rationale is always to have a known level of precision.