Why? not x means x isNoneorlen(x) == 0 for lists. len(x) == 0 will raise an exception if x is None. In most cases, the distinction between None and [] isn’t important, and if it is, I’d expect separate checks for those (again, for explicitness) since you’d presumably handle each case differently.
In short:
if the distinction between None and [] is important, have separate checks
if not, not x should be your default, since that way it’s a common pattern for all types
I try to avoid having the same variable with different types I find it is often the cause of difficult to debug bugs. I struggle to think of a case where u would be performing a check that could be an empty list or None where both are expected possible values.
I like the exception being raised their is no reason I should be passing in None to the function it means I’ve fucked up the value of whatever I’m passing in at some point.
In complex cases where speed is less important than maintainability, I tend to agree.
In this case, a simple comment would suffice. And in fact nothing at all would be okay for any half-competent Python coder, as testing if lists are empty with if not is super-standard.
I think the explicitness of checking length is worth the performance cost. If ur writing code for speed ur not using python.
Why?
not xmeansx is None or len(x) == 0for lists.len(x) == 0will raise an exception ifxis None. In most cases, the distinction betweenNoneand[]isn’t important, and if it is, I’d expect separate checks for those (again, for explicitness) since you’d presumably handle each case differently.In short:
Noneand[]is important, have separate checksnot xshould be your default, since that way it’s a common pattern for all typesI try to avoid having the same variable with different types I find it is often the cause of difficult to debug bugs. I struggle to think of a case where u would be performing a check that could be an empty list or None where both are expected possible values.
Really? I get that all the time. I do web dev, and our APIs have a lot of optional fields.
Theirs ur problem.
But in all seriousness I think if u def some_func(*args, kwarg=[]) Is a more explicit form of def some_func(*args, kwarg=None)
Don’t do this:
def fun(l=[]): l.append(len(l)) return l fun() # [0] fun() # [0, 1] fun(l=[]) # [0] fun() # [0, 1, 2] fun(l=None) # raise AttributeError or TypeError if len(l) comes firstThis can be downright cryptic if you’re passing things dynamically, such as:
def caller(*args, **kwargs): fun(*args, **kwargs)It’s much safer to do a simple check at the beginning:
if not l: l = []I like the exception being raised their is no reason I should be passing in None to the function it means I’ve fucked up the value of whatever I’m passing in at some point.
Oh no a stray None! Take cover …
Robust codebase should never fail from a stray None
Chaos testing is specifically geared towards bullet proofing code against unexpected param types including None.
The only exception is for private support function for type specific checking functions. Where it’s obviously only for one type ever.
We live in clownworld, i’m a clown and keep the company of shit throwing monkeys.
Ur function args if fucked up should always throw an error that’s the entire point of python type hints
In complex cases where speed is less important than maintainability, I tend to agree.
In this case, a simple comment would suffice. And in fact nothing at all would be okay for any half-competent Python coder, as testing if lists are empty with
if notis super-standard.