I'm confused. Are you saying it's unpythonic but you like it anyway?
So, my reasoning is that I surely must end up liking it, if it ended up accepted despite breaking every rule in the book. They wouldn't accept it for something that wasn't incredibly useful. My first impression is that it's incredibly ugly, unpythonic, and unreadable (what does it even do?), and this is pretty "obvious".
So arguing based on what I know about Python design philosophy, and the fact that this has been so deeply discussed, it must be absolutely fantastic.
I wouldn't think it's great (if you gave me the syntax), I'd recite all the Python Values it breaks -
https://en.m.wikipedia.org/wiki/Zen_of_Python :
- Beautiful is better than ugly.
Nope, this is very ugly.
- Simple is better than complex.
Nope, this isn't simple.
- Flat is better than nested.
Nope, this explicitly exists to let you nest something.
- Sparse is better than dense.
Nope, this explicitly exists to make code denser.
- Readability counts.
Nope: this is literally not readable. You don't know what the first code example I gave does. Normally with Python you just "write pseudocode and make sure you indent it properly."
- Special cases aren't special enough to break the rules.
This is a special case.
but here we get to the next rule, which trumps ALL of the above:
Although practicality beats purity.
- There should be one—and preferably only one—obvious way to do it.
This is broken, as now you can do it on two lines or one line.
- If the implementation is hard to explain, it's a bad idea.
It's kind of hard to explain, look at all our comments.
- If the implementation is easy to explain, it may be a good idea.
This isn't the case here.
I will grant that this is extremely explicit syntax. In this sense it is MUCH better than overloading = based on different contexts or something. As I mentioned above, anyone who sees := knows that it's a "known unknown" -- WTF is this?
So we are left with a single solitary Pythonic value:
- Practicality beats purity.
Based on this alone, I reason that it must be great to have been accepted. It must be extremely practical. It must save a lot of time.
I am quite disposed to thinking (honestly!) that it must be pretty darn great. It will save a lot of time.
There's no way that it made it into the language if it didn't, since it's so obviously ugly and unpythonic.
But practicality beats purity. I'm sure I'll love it!
if reductor := dispatch_table.get(cls):
rv = reductor(x)
elif reductor := getattr(x, "__reduce_ex__", None):
rv = reductor(4)
elif reductor := getattr(x, "__reduce__", None):
rv = reductor()
else:
raise Error("un(shallow)copyable object of type %s" % cls)
reductor = dispatch_table.get(cls)
if reductor:
rv = reductor(x)
else:
reductor = getattr(x, "__reduce_ex__", None)
if reductor:
rv = reductor(4)
else:
reductor = getattr(x, "__reduce__", None)
if reductor:
rv = reductor()
else:
raise Error("un(shallow)copyable object of type %s" % cls) def f(F, *args):
f.reductor = F(*args)
return bool(f.reductor)
if f(dispatch_table.get, cls)):
rv = f.reductor(x)
elif f(getattr, x, "__reduce_ex__", None):
rv = f.reductor(4)
elif f(getattr, x, "__reduce__", None):
rv = f.reductor()
else:
raise Error("un(shallow)copyable object of type %s" % cls)
Once you abstract the patterns you can drive towards data-driven code:
K = (
(dispatch_table.get, (cls,), (x,)),
(getattr, (x, "__reduce_ex__", None), (4,)),
(getattr, (x, "__reduce__", None), ()),
)
for F, a, b in K:
reductor = F(*a)
if reductor:
rv = reductor(*b)
break
else:
raise Error("un(shallow)copyable object of type %s" % cls)
At runtime, your second example is actually significantly less explicit because so much is hidden away in mutable state.
I started to agree with that but then I realized: I don't think you can get getattr to raise an error here at all. The keys are strings, the default value is provided, I don't think there's a fault path here.
In general though, I totally agree with you. I use less-cute code shamelessly when it will aid debugging. I write for the debugger. ;-)
> At runtime, your second example is actually significantly less explicit because so much is hidden away in mutable state.
Yeah, I see what you mean. You don't know which "F" or "reductor" triggered the error because it doesn't show up in the traceback because each assignment doesn't have its own line in the code. That's a good point. I've been there, and it sucks.
In this specific case I would actually most likely write out the three if.. else.. chain. If there were four or more I would use the gadget style. It's right on the borderline, and I would suspect that there won't be a fourth option in the future (although usually that would be a bad assumption; in this case I speculate the the object model isn't going to change any time soon.)
Of course you can ;) __getattr__ could invoke a network request that fails for all you know.
But yes this was more a general comment on this layout. The data-driven layout, while very explicit in code, is actually awful when you encounter issues at runtime, for exactly the reasons you describe.
While I'm not a fan of this PEP's syntax, I will say that I do think it someone helps here, it reduces the boilerplate from 3-4 lines in some cases to a single line, which in practice makes this more visually declarative, and keeps tracebacks sane.
That said this pattern is rare enough for me that I don't think I'll be using this tool anytime soon.
OMG! Yes, of course, but at that point your traceback has bigger problems. :-)
All this for the small cost of learning a few simple scoping rules and the negligible cost of occasionally discovering the special cases in which the new syntax cannot be used.
def get_reductor_value(cls, x):
reductor = dispatch_table.get(cls)
if reductor:
return reductor(x)
reductor = getattr(x, "__reduce_ex__", None)
if reductor:
return reductor(4)
reductor = getattr(x, "__reduce__", None)
if reductor:
return reductor()
raise Error("un(shallow)copyable object of type %s" % cls)