Walrus operator IMO is a huge mistake. It saves fuck all time/space, but introduces an entire new operator that probably added more complexity, edge cases and quirks than the benefits it provides. Terrible idea.
Worse, no one uses it. I've yet to come across anyone that advocates it or remembers it.
I actually just used it to what I would say was a perfect example of where it legitimately improved code readability while maintaining pythonic constructs:
values = [
value
for line in buffer.readlines()
if (value := line.strip())
]
Previously, I would have needed to either duplicate effort like:
values = [
line.strip()
for line in buffer.readlines()
if line.strip()
]
Or used a sub-generator:
values = [
value
for value in (
line.strip() for line buffer.readlines()
)
if value
]
Or rewritten it altogether using a (slower) for loop calling append each time:
values = []
for line in buffer.readlines():
line = line.strip()
if line:
values.append(line)
The assignment expression is perfect for this sort of use case, and is a clear win over the alternatives IMO.
FWIW, that version ends up being slower, because you're constructing and iterating over a tuple for every iteration, which incurs a similar cost to running `.strip()` twice. The sub-generator example I gave is better because you're only constructing the generator expression once, and requires less overhead for each iteration.
But the second version needs to run `.strip` twice. It might not make much of a difference for `strip` -- but it still hurts my eyes, and could be an actual performance issue for other operations.
Running strip twice makes it more explicit and readable IMHO - it's then abundantly clear that it's being run as a check and as a way of populating the list.
open("file", "r").readlines.
map{|line| line.strip}.
filter{|line| line != ""}
or some smarter but less readable ways.
I prefer the left-to-right transformations style to Python's list comprehension and inside-to-outside function composition. The reason is that it reminds me of how data flow into *nix pipelines. I spent decades working with them and I've been working with Ruby for the last half of that time. With Python in the last quarter of my career.
It's a matter of choices and preferences of the original designed of the language. Both ways work.
What does `filter` do with `None`? Would it not be an error? This seems not so readable, possibly relying on weird behavior of `filter`. If I had to guess, I would say: Maybe filter with `None` will give the empty list or the whole list, because either no list item matches a `None` condition, or all match it, since there is no condition.
But in both cases the usage does not seem to make any sense. So it must be something else. Maybe when the argument is not a lambda, it will compare directly with the given argument? But then we would get only `None`. Nah, still makes no sense.
I am at a loss, what this `filter` call is doing, without trying it out.
I suspect the question was rhetorical. The point is, every reader is going to have that question pop into their head and have to look it up. Better to use code that doesn't raise any questions, even if it's a few more characters.
> Better to use code that doesn't raise any questions, even if it's a few more characters.
Certainly, I agree; I would usually use:
(x for x in xs if x)
Or, if I know more about the kind of falsy values xs actually needs removed, something more explicit like:
(x for x in xs if x is not None)
Because Python’s multiplicity of falsy values can also be something of a footgun (particularly, when dealing with something a collection of Optionals where the substantive type has a falsy value like 0 or [] included.)
Instead of:
filter(None, xs)
Which is terse but potentially opaque.
Though it's additional syntax, I kind of wish genexp/list/set comprehensions could use something like “x from” as shorthand for “x for x in”, which would be particularly nice for filtering comprehensions.
Not sure if this was your intention or not, but to me that proves the usefulness of the walrus operator: the first snippet in the parent comment seems far clearer to me, even though I'm fairly familiar with the functional operators.
I was careful to pre-empt this exact response in my original comment: I do know what it does. The fact remains that it's less readable (IMO) because of the density of line noise and the lack of common structural elements (like if and for - I suppose filter and map fulfill this but their parameter separate out elements that ought to be next to each other). I do think that my preference, however slight, would remain no matter how much time I spent with the functional versions.
The question one has to ask is whether it is worth the additional complexity and a dedicated operator. I am sure it is ever so slightly useful, but I am not convinced it is worth the trouble.
Feature creep is programming language's worse enemy after a certain maturity level.
I absolutely love Go in this matter. They took forever to add Generics and generally sides with stability over features.
Sure it's "tidier" if by that you mean smaller. Someone who doesn't work in Python all the time and isn't aware of these kinds of operators is going to have to spend a decent amount of time unpacking what the hell that all means whereas someone can take one look at the standard while loop, see the logic laid out plainly, understand what's happening, and make changes, if necessary, fairly easily. Unless there's a performance benefit to an operator like this I'll forgo "tidy" for clear any day of the week. Then again I'm just a senior dev whose only professional experience with Python was maintaining other people's Python projects who never had to touch them again after they wrote them, and who used Python for things Python should not have been used for just because it's "easy" to write.
Walrus avoids stuttering in constructs like comprehensions/genexps which greatly improves readability. (And avoids using less basically readable constructs, like explicit imperative loops, to avoid the visual noise of stuttering.)
Worse, no one uses it. I've yet to come across anyone that advocates it or remembers it.