Yury Selivanov wrote:
> I think the Motivation section is pretty weak.
I have normally wished for this when I was (semi-
interactively) exploring a weakly structured dataset.
Often, I start with a string, split it into something
hopefully like records, and then start applying filters
and transforms. I would prefer to write a comprehension
instead of a for loop. Alas, without pre-editing, I
can be fairly confident that the data is dirty.
Sometimes I can solve it with a filter (assuming
that I remember and don't mind the out-of-order
evaluation):
# The "if value" happens first,
# so the 1/value turns out to be safe.
[1/value for value in working_list if value]
Note that this means dropping the bad data, so that
items in this list will have different indices than
those in the parent working_list.
I would rather have written:
[1/value except (TypeError, ZeroDivisionError): None]
which would keep the matching indices, and clearly
indicate where I now had missing/invalid data.
Sometimes I solve it with a clumsy workaround:
sum((e.weight if hasattr(e, 'weight') else 1.0)
for e in working_list)
But the "hasattr" implies that I am doing some sort of
classification based on whether or not the element has
a weight.
The true intent was to recognize that while every element
does have a weight, the representation that I'm starting
from didn't always bother to store it -- so I am repairing
that before processing.
sum(e.weight except AttributeError: 1)
Often I give up, and create a junky helper function, or several.
But to avoid polluting the namespace, I may leave it outside
the class, or give it a truly bad name:
def __only_n2(worklist):
results = []
for line in worklist:
line=line.strip()
if not line: # or maybe just edit the input file...
continue
split1=line.split(", ")
if 7 != len(split1):
continue
if "n2" == split1[3]:
results.append(split1)
return results
worklist_n2 = __only_n2(worklist7)
In real life code, even after hand-editing the input data
to fix a few cases, I recently ended up with:
class VoteMark:
...
@classmethod
def from_property(cls, voteline):
# print (voteline)
count, _junk, prefs = voteline.partition(": ")
return cls(count, prefs)
... # module level scope
def make_votes(vs=votestring):
return [VoteMark.from_property(e) for e in vs.splitlines()]
vs=make_votes()
You can correctly point out that I was being sloppy, and that I
*should* have gone back to clean it up. But I wouldn't have had
to clean up either the code or the data (well, not as much), if
I had been able to just keep the step-at-a-time transformations
I was building up during development:
vs=[(VoteMark(*e.strip().split(": "))
except (TypeError, ValueError): None)
for e in votestring.splitlines()]
Yes, the first line is still doing too much, and might be
worth a helper function during cleanup.
But it is already better than an alternate constructor that
exists only to simplify a single (outside the class) function
that is only called once.
Which in turn is better than the first draft that was so
ugly that I actually did fix it during that same work session.
> Inconvenience of dict[] raising KeyError was solved by
> introducing the dict.get() method. And I think that
> dct.get('a', 'b')
> is 1000 times better than
> dct['a'] except KeyError: 'b'
I don't.
dct.get('a', default='b')
would be considerably better, but it would still imply
that missing values are normal. So even after argclinic
is fully integrated, there will still be times when I
prefer to make it explicit that I consider this an
abnormal case. (And, as others have pointed out, .get
isn't a good solution when the default is expensive to
compute.)
>> Consider this example of a two-level cache::
>> for key in sequence:
>> x = (lvl1[key] except KeyError: (lvl2[key] except KeyError: f(key)))
> I'm sorry, it took me a minute to understand what your
> example is doing. I would rather see two try..except blocks
> than this.
Agreed -- like my semi-interactive code above, it does too much
on one line. I don't object as much to:
for key in sequence:
x = (lvl1[key]
except KeyError: (lvl2[key]
except KeyError: f(key)))
>> Retrieve an argument, defaulting to None::
>> cond = args[1] except IndexError: None
>>
>> # Lib/pdb.py:803:
>> try:
>> cond = args[1]
>> except IndexError:
>> cond = None
> cond = None if (len(args) < 2) else args[1]
This is an area where tastes will differ.
I view the first as saying that not having a cond
would be unusual, or at least a different kind of
call.
I view your version as a warning that argument
parsing will be complex, and that there may be
specific combinations of arguments that are only
valid depending on the values of other arguments.
Obviously, not everyone will share that intuition,
but looking at the actual code, the first serves
me far better. (It is a do_condition method,
and falsy values -- such as None -- trigger a
clear rather than a set.)
>> Attempt a translation, falling back on the original::
>> e.widget = self._nametowidget(W) except KeyError: W
>>
>> # Lib/tkinter/__init__.py:1222:
>> try:
>> e.widget = self._nametowidget(W)
>> except KeyError:
>> e.widget = W
Note that if the value were being stored in a
variable instead of an attribute, it would often be
written more like:
try:
W=_nametowidget(W)
except:
pass
> I'm not sure this is a good example either.
...
> Your new syntax just helps to work with this error prone api.
Exactly.
You think that is bad, because it encourages use of a
sub-optimal API.
I think it is good, because getting an external API fixed
is ... unlikely to happen.
> # sys.abiflags may not be defined on all platforms.
> _CONFIG_VARS['abiflags'] = sys.abiflags except AttributeError: ''
> Ugly.
> _CONFIG_VARS['abiflags'] = getattr(sys, 'abiflags', '')
> Much more readable.
Again, tastes differ.
To me, getattr looks too much like internals, and I
wonder if I will need to look up getattribute or
__getattr__, because maybe this code is doing something
strange. After an unpleasant pause, I realize that, no,
it really is safe. Then later, I wonder if _CONFIG_VARS
is some odd mapping with special limits. Then I see that
it doesn't matter, because that isn't what you're passing
to getattr. Then I remember that sys often is a special
case, and start wondering if I need extra tests around
this. Wait, why was I looking at this code again? (And
as others pointed out, getattr with a constant has its
own code smell.)
The "except" form clearly indicates that sys.abiflags
*ought* to be there, and the code is just providing
some (probably reduced) services to oddball systems,
instead of failing.
>> Retrieve an indexed item, defaulting to None (similar to dict.get)::
>> def getNamedItem(self, name):
>> return self._attrs[name] except KeyError: None
> _attrs there is a dict (or at least it's something that quaks
> like a dict, and has [] and keys()), so
> return self._attrs.get(name)
Why do you assume it has .get? Or that .get does what a
python mapping normally does with .get?
The last time I dove into code like that, it was written
that way specifically because the DOM (and _attrs in
particular) might well be created by some other program,
in support of a very unpythonic API. Note that the
method itself is called getNamedItem, rather than just get;
that also suggests an external source of API expectations.
>> Translate numbers to names, falling back on the numbers::
>> g = grp.getgrnam(tarinfo.gname)[2] except KeyError: tarinfo.gid
>> u = pwd.getpwnam(tarinfo.uname)[2] except KeyError: tarinfo.uid
>>
>> # Lib/tarfile.py:2198:
>> try:
>> g = grp.getgrnam(tarinfo.gname)[2]
>> except KeyError:
>> g = tarinfo.gid
>> try:
>> u = pwd.getpwnam(tarinfo.uname)[2]
>> except KeyError:
>> u = tarinfo.uid
> This one is a valid example, but totally unparseable by
> humans. Moreover, it promotes a bad pattern, as you
> mask KeyErrors in 'grp.getgrnam(tarinfo.gname)' call.
Do you find the existing try: except: code any better,
or are you just worried that it doesn't solve enough
of the problem?
FWIW, I think it doesn't matter where the KeyError
came from; even if the problem were finding the getgrnam
method, the right answer (once deployed, as opposed to
during development) would still be to fall back to
the best available information.
>> Perform some lengthy calculations in EAFP mode, handling division by
>> zero as a sort of sticky NaN::
>> value = calculate(x) except ZeroDivisionError: float("nan")
vs
>> try:
>> value = calculate(x)
>> except ZeroDivisionError:
>> value = float("nan")
> I think all of the above more readable with try statement.
I don't, though I would wrap the except.
The calculation is important; everything else is boilerplate,
and the more you can get it out of the way, the better.
> Yes, some examples look neat. But your syntax is much easier
> to abuse, than 'if..else' expression, and if people start
> abusing it, Python will simply loose it's readability
> advantage.
This is also an argument for mandatory parentheses.
()-continuation makes it easier to wrap the except clause out
of the way.
(((( )) (() ()) ))-proliferation provides pushback when the
expressions start to get too complicated.
-jJ
--
If there are still threading problems with my replies, please
email me with details, so that I can try to resolve them. -jJ
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