Truthiness in Python is occasionally confusing. Obviously, False is false and True is true, but beyond that, what then?

None is always false–though this doesn’t mean that False == None, which is a mistake I made early in my Python career. I was confused by how a nonexistant list and an empty list were both falsey, and somewhere in my mind I thought that they were both None as well. Not so much.

>>> a = None
>>> bool(a)
False
>>> b = []
>>> bool(b)
False
>>> bool(a is None)
True
>>> bool(b is None)
False

A stylistic note here: since None is a singleton (i.e. there exists only one instance of it), the proper syntax is foo is None, rather than foo == None. But I digress.

The empty values of data structures are always falsey. Hence:

>>> bool([])
False
>>> bool("")
False
>>> bool({})
False

And perhaps most confusingly:

>>> bool(0)
False
>>> bool(1)
True
>>> bool(2)
True
>>> bool(-31.4)
True

I mean, this makes sense because we know that 0 is false and 1 is true… but if you think about it, this also means that 0 is the empty value of an int (which means that 0 is false, but every other value of int or float is true) This doesn’t mean much in Python, of course, but I’ve been playing with Go lately, in which you have to initialize your variables before you can do anything with them, and suddenly the idea of an empty value makes a lot more sense (and the empty value for an int is indeed zero).

Conversely, every non-zero value of a data structure is true. That means that a string with stuff in it, a dict. with stuff in it, a list with stuff in it, etc. is true no matter what the stuff is. And so:

>>> hip = False
>>> bool(hip)
False
>>> bool([hip, hip])
True

Proving conclusively, as we all knew, that hips don’t lie.

(Ba-bm-psh.)

Extra credit: do you know what ["hip", "hip"] is?

…(wait for it)…

It’s a hip hip array.

(Womp womp.)