文章标题

Python’s super() considered super!
引自https://rhettinger.wordpress.com/2011/05/26/super-considered-super/
If you aren’t wowed by Python’s super() builtin, chances are you don’t really know what it is capable of doing or how to use it effectively.

Much has been written about super() and much of that writing has been a failure. This article seeks to improve on the situation by:

providing practical use casesgiving a clear mental model of how it worksshowing the tradecraft for getting it to work every timeconcrete advice for building classes that use super()favoring real examples over abstract ABCD diamond diagrams.

The examples for this post are available in both Python 2 syntax and Python 3 syntax.

Using Python 3 syntax, let’s start with a basic use case, a subclass for extending a method from one of the builtin classes:

class LoggingDict(dict):
def setitem(self, key, value):
logging.info(‘Settingto %r’ % (key, value))
super().setitem(key, value)

This class has all the same capabilities as its parent, dict, but it extends the setitem method to make log entries whenever a key is updated. After making a log entry, the method uses super() to delegate the work for actually updating the dictionary with the key/value pair.

Before super() was introduced, we would have hardwired the call with dict.setitem(self, key, value). However, super() is better because it is a computed indirect reference.

One benefit of indirection is that we don’t have to specify the delegate class by name. If you edit the source code to switch the base class to some other mapping, the super() reference will automatically follow. You have a single source of truth:

class LoggingDict(SomeOtherMapping): # new base class
def setitem(self, key, value):
logging.info(‘Settingto %r’ % (key, value))
super().setitem(key, value) # no change needed

In addition to isolating changes, there is another major benefit to computed indirection, one that may not be familiar to people coming from static languages. Since the indirection is computed at runtime, we have the freedom to influence the calculation so that the indirection will point to some other class.

The calculation depends on both the class where super is called and on the instance’s tree of ancestors. The first component, the class where super is called, is determined by the source code for that class. In our example, super() is called in the LoggingDict.setitem method. That component is fixed. The second and more interesting component is variable (we can create new subclasses with a rich tree of ancestors).

Let’s use this to our advantage to construct a logging ordered dictionary without modifying our existing classes:

class LoggingOD(LoggingDict, collections.OrderedDict):
pass

The ancestor tree for our new class is: LoggingOD, LoggingDict, OrderedDict, dict, object. For our purposes, the important result is that OrderedDict was inserted after LoggingDict and before dict! This means that the super() call in LoggingDict.setitem now dispatches the key/value update to OrderedDict instead of dict.

Think about that for a moment. We did not alter the source code for LoggingDict. Instead we built a subclass whose only logic is to compose two existing classes and control their search order.

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Search Order

What I’ve been calling the search order or ancestor tree is officially known as the Method Resolution Order or MRO. It’s easy to view the MRO by printing the mro attribute:

pprint(LoggingOD.mro)
(