I’m in Shanghai, and before I left to teach this morning, I decided to check the weather. I knew that it would be hot, but I wanted to double-check that it wasn’t going to rain — a rarity during Israeli summers, but not too unusual in Shanghai.
I entered “shanghai weather” into DuckDuckGo, and got the following:
Never mind that it gave me a weather report for the wrong Chinese city. Take a look at the humidity reading! What’s going on there? Am I supposed to worry that it’s ever-so-slightly more humid than 55%?
The answer, of course, is that many programming languages have problems with floating-point numbers. Just as there’s no terminating decimal number to represent 1/3, lots of numbers are non-terminating when you use binary, which computers do.
As a result floats are inaccurate. Just add 0.1 + 0.2 in many programming languages, and prepare to be astonished. Wait, you don’t want to fire up a lot of languages? Here, someone has done it for you: http://0.30000000000000004.com/ (I really love this site.)
If you’re working with numbers that are particularly sensitive, then you shouldn’t be using floats. Rather, you should use integers, or use something like Python’s decimal.Decimal, which guarantees accuracy at the expense of time and space. For example:
>> from decimal import Decimal
>>> x = Decimal('0.1')
>>> y = Decimal('0.2')
>>> x + y
Decimal('0.3')
>>> float(x+y)
0.3
Of course, you should be careful not to create your decimals with floats:
>> x = Decimal(0.1)
>>> y = Decimal(0.2)
>>> x + y
Decimal('0.3000000000000000166533453694')
Why is this the case? Let’s take a look:
>> x
Decimal('0.1000000000000000055511151231257827021181583404541015625')
>>> y
Decimal('0.200000000000000011102230246251565404236316680908203125')
So, if you’re dealing with sensitive numbers, be sure not to use floats! And if you’re going outside in Shanghai today, it might be ever-so-slightly less humid than your weather forecast reports.