Wow, it's been months, hasn't it? Our last Python Foundations entry talked about how the Boolean operators and and or work in Python, including their short-circuting behavior. But what if you don't want short-circuiting? What if you want both operands of and or or to be fully evaluated even when the first operand's value is sufficient to determine the expression's truth value?
Here, we can take advantage of the fact that Booleans are a special kind of integer in Python (see IDKTAP #2: Booleans as fancy integers), and perform math on them.
If you create a table of the results of adding the various combinations of 0 and 1, which are the integer values of False and True in Python:
+ | 0 1
0 | 0 1
1 | 1 2
It bears a striking resemblance to the results of the Boolean or operator: the result is truthy (see PF #1: Truth and Consequences) if either of the operands is truthy.
Similarly, the multiplication operator is a dead ringer for Boolean and:
* | 0 1
0 | 0 0
1 | 0 1
Zero times anything is zero, just as False and anything is False.
If you have studied digital electronics, you may recognize this as Boolean arithmetic: arithmetic using only the values 0 and 1, where and is in fact equivalent to multiplication and or is equivalent to addition. The result of addition is "clamped" to 1 (that is, the highest result an addition can be is 1), and the only valid operations are addition and multiplication. It may seem like a toy arithmetic, but it's the foundation of everything a computer does.
We can use this equivalence of logical and arithmetic operations to implement non-short-circuiting ("long-circuiting"?) and and or in Python. To support truthy and falsy values, which may not actually be integers, we convert the operands to proper Booleans first using the bool() constructor.
bool(x) + bool(y) + bool(z) # x or y or z
bool(x) * bool(y) * bool(z) # x and y and z
Here, x, y, and z are always fully evaluated. If one of them is, say, a function call, the function is always called. In the equivalent expression using Boolean operators, remember, the expression will short-circuit as soon as it can, and may not evaluate all arguments. We explored how to exploit this behavior for fun and profit in PF #2.
Conveniently, multiplication has precedence over (is performed before) addition, just as and has precedence over or, so an expression like the following works exactly as you would expect:
bool(a) * bool(b) + bool(x) * bool(y) # a and b or x and y
In fact, this is an easy way to remember which Boolean operator has precedence: because and is equivalent to multiplication, it has precedence over or, which is equivalent to addition. This is a rule I had trouble remembering when I started programming.
So far, what we've discussed isn't really specific to Python; you can do the same non-short-circuiting Boolean math in virtually any language with only minor syntax changes. We can, however, use Python's any() and all() functions to help make our non-short-circuiting Boolean operators a little more readable. Both functions operate on a sequence.
- any() - Returns True if any element is truthy (equivalent to Boolean or)
- all() - Returns True if all elemens are truthy (equivalent to Boolean and)
However, the short-circuiting behavior is apparent only with generators, which "lazily" calculates a sequence one element at a time. (There will surely be a Python Foundations entry on generators in the future!) If you pass a sequence (i.e., a list or a tuple) to any() or all(), all the elements of the sequence will be fully evaluated when the sequence is constructed, before any() or all() is even involved. The fact that any() and all() short-circuit is then merely a performance optimization. Useful, in other words, but not exploitable for side effects as with and and or.
And so we can use any() and all() as non-short-circuiting or and and, respectively. x, y, and z below may be expressions of arbitrary complexity, and will be evaluated fully.
any([x, y]) # x or y
all([x, y]) # x and y
any([x, y, z]) # x or y or z (any number of arguments)
all((x, y, z)) # you may use a tuple instead of a list
As for the last example, I personally prefer using the square brackets and passing a list since it stands out more and makes it clearer what is happening, but constructing a tuple is faster, a fact which may be useful in some circumstances.
any() and all() can be nested to implement compound non-short-circuiting Boolean operations:
any([all([a, b]), all([x, y]]) # a and b or x and y
However, this gets difficult to read pretty quickly (unless, perhaps, you have experience with Lisp, where all operations are prefix).. Fortunately, any() and all() always return True or False (not the deciding element from the sequence, which may be merely truthy or falsy), so you can easily combine their results with + and *.
all([a, b]) + all([x, y]) # a and b or x and y, as above
We're almost finished here; this has become rather more in-depth than I intended! But while were talking about any() and all(), I should mention that it is something of a shame that neither returns the value that made the decision (i.e., the first truthy value for any() or the first falsy value for all()). This keeps them from being used to actually find the first truthy or falsy value in a sequence, which is especially a pity when you're using them with a generator because that value, having been consumed within any()/all(), is forever lost.
You can write your own versions of these functions that do return the deciding value, but because they are implemented in Python rather than in C, they will be slower than the built-ins. Still, here are such implementations.
for item in iterable:
if not item: return item
for item in iterable:
if item: return item