I remember my CompSci professor saying never to use floats for currency.

The reason for that is how the IEEE specification defines floats in binary format. Basically, it stores sign, fraction and exponent to represent a Float. It's like a scientific notation for binary (something like `+1.43*10^2`

). Because of that, it is impossible to store fractions and decimals in Float exactly.

That's why there is a Decimal format. If you do this:

`irb:001:0> "%.47f" % (1.0/10) => "0.10000000000000000555111512312578270211815834045" # not "0.1"! `

whereas if you just do

`irb:002:0> (1.0/10).to_s => "0.1" # the interprer rounds the number for you `

So if you are dealing with small fractions, like compounding interests, or maybe even geolocation, I would highly recommend Decimal format, since in decimal format `1.0/10`

is exactly 0.1.

However, it should be noted that despite being less accurate, floats are processed faster. Here's a benchmark:

`require "benchmark" require "bigdecimal" d = BigDecimal.new(3) f = Float(3) time_decimal = Benchmark.measure{ (1..10000000).each { |i| d * d } } time_float = Benchmark.measure{ (1..10000000).each { |i| f * f } } puts time_decimal #=> 6.770960 seconds puts time_float #=> 0.988070 seconds `

## Answer

Use **float** when you don't care about precision too much. For example, some scientific simulations and calculations only need up to 3 or 4 significant digits. This is useful in trading off accuracy for speed. Since they don't need precision as much as speed, they would use float.

Use **decimal** if you are dealing with numbers that need to be precise and sum up to correct number (like compounding interests and money-related things). Remember: if you need precision, then you should always use decimal.