python-internals

问题 First of all, I understand how, in general, a decorator work. And I know @staticmethod strips off the instance argument in the signature, making class C(object): @staticmethod def foo(): print 'foo' C.foo //<function foo at 0x10efd4050> C().foo //<function foo at 0x10efd4050> valid. However, I don't understand how the sourcec code of staticmethod make this happen. It seems to me that when wrapping method foo in staticmethod , an instance of staticmethod is instantiated, then some magic

问题 Imports in an __init__.py seem to behave differently when the file is run, to when it is imported. If we have the following files: run.py : import test test/b.py : class B(object): pass test/__init__.py : from b import B print B print b If we run __init__.py we get an error as I expect: % python test/__init__.py <class 'b.B'> Traceback (most recent call last): File "test/__init__.py", line 6, in <module> print b NameError: name 'b' is not defined But if we run.py then we don't: % python run

问题 Building a string through repeated string concatenation is an anti-pattern, but I'm still curious why its performance switches from linear to quadratic after string length exceeds approximately 10 ** 6: # this will take time linear in n with the optimization # and quadratic time without the optimization import time start = time.perf_counter() s = '' for i in range(n): s += 'a' total_time = time.perf_counter() - start time_per_iteration = total_time / n For example, on my machine (Windows 10,

问题 This question already has answers here : compare object to empty tuple with the 'is' operator in Python 2.x (4 answers) Closed 2 years ago . I want to make my code more (memory-)efficient. Right now we have a lot of functions that take an iterable as parameter like: def foo(para,meter,iterable): #... pass and sometimes we have to provide it an empty list to do its work properly: foo(14,25,[]) . The problem is that each time a new list is constructed: it requires to allocate on the heap, and a

问题 This question already has answers here : compare object to empty tuple with the 'is' operator in Python 2.x (4 answers) Closed 2 years ago . I want to make my code more (memory-)efficient. Right now we have a lot of functions that take an iterable as parameter like: def foo(para,meter,iterable): #... pass and sometimes we have to provide it an empty list to do its work properly: foo(14,25,[]) . The problem is that each time a new list is constructed: it requires to allocate on the heap, and a

问题 I recently read somewhere that the special value None in python is a singleton object of its own class, specifically NoneType . This explained a lot, since most errors involving None in python produce AttributeError s instead of some special "NoneError" or something. Since all of these AttributeErrors reflected the attributes that NoneType lacked, I became intrigued by what attributes NoneType did have, if any. I decided to look into this NoneType and learn more about it. I've always found

问题 Inspired by this nice answer, Here's a benchmark: import timeit def test1(): a = [1,2,3] a.insert(0,1) def test2(): a = [1,2,3] a[0:0]=[1] print (timeit.timeit('test1()','from __main__ import test1')) print (timeit.timeit('test2()','from __main__ import test2')) For me, test2 is sligtly faster (~10%). Why is that the case? I would expect it to be slower since: slice assignment must be able to accept iterables of any length and therefore must be more general. in slice assignment, we need to

问题 A generator is a special kind of iterator, and it has some methods that an normal iterator doesn't have such as send() , close() ... etc. One can get a generator by using a genexp like below: g=(i for i in range(3)) the type of g will be a generator. But it seems weird to me that g is a generator because g.send will do nothing since g isn't returned by a function with yield keyword, and there would be no chance for one to catch the value passed by send method(not sure this is right), I don't

问题 I'm trying to write a class in Python that behaves as a generator object, particularly in that when it's garbage collected .close() is called on it. That's important because it means that when the generator is interrupted I can make sure it'll clean up after itself, for example closing files or releasing locks. Here's some explanatory code: If you interupt a generator, then when it's garbage collected, Python calls .close() on the generator object, which throws a GeneratorExit error into the

问题 I recently came across this question. import Object class Visitor(Object): def __init__(self): super(Visitor,self).__init__() def visit(self, obj): pass def getIsDone(self): return False isDone = property(fget =lambda self:self.getIsDone()) I get this error: TypeError: module.__init__() takes at most 2 arguments (3 given) and its answer: class A:pass print(A) #outputs <class '__main__.A'> import urllib print(urllib) #outputs <module 'urllib' from '/usr/lib/python3.2/urllib/__init__.py'> Your