我正在自学Python,我最近的一课是Python不是Java,所以我刚刚花了一段时间把我所有的Class方法变成了函数。

我现在意识到,我不需要使用Class方法来做我在Java中使用静态方法所做的事情,但现在我不确定什么时候我会使用它们。我能找到的所有关于Python类方法的建议都是,像我这样的新手应该避开它们,而标准文档在讨论它们时是最不透明的。

谁有一个在Python中使用类方法的好例子,或者至少有人能告诉我什么时候可以合理地使用类方法吗?


当前回答

@classmethod对于从外部资源轻松实例化该类的对象非常有用。考虑以下几点:

import settings

class SomeClass:
    @classmethod
    def from_settings(cls):
        return cls(settings=settings)

    def __init__(self, settings=None):
        if settings is not None:
            self.x = settings['x']
            self.y = settings['y']

然后在另一个文件中:

from some_package import SomeClass

inst = SomeClass.from_settings()

访问inst.x将得到与settings['x']相同的值。

其他回答

Think about it this way: normal methods are useful to hide the details of dispatch: you can type myobj.foo() without worrying about whether the foo() method is implemented by the myobj object's class or one of its parent classes. Class methods are exactly analogous to this, but with the class object instead: they let you call MyClass.foo() without having to worry about whether foo() is implemented specially by MyClass because it needed its own specialized version, or whether it is letting its parent class handle the call.

当您在创建实际实例之前进行设置或计算时,类方法是必不可少的,因为在实例存在之前,您显然不能将实例用作方法调用的调度点。在SQLAlchemy源代码中可以看到一个很好的例子;在下面的链接中查看dbapi()类方法:

https://github.com/zzzeek/sqlalchemy/blob/ab6946769742602e40fb9ed9dde5f642885d1906/lib/sqlalchemy/dialects/mssql/pymssql.py#L47

You can see that the dbapi() method, which a database backend uses to import the vendor-specific database library it needs on-demand, is a class method because it needs to run before instances of a particular database connection start getting created — but that it cannot be a simple function or static function, because they want it to be able to call other, supporting methods that might similarly need to be written more specifically in subclasses than in their parent class. And if you dispatch to a function or static class, then you "forget" and lose the knowledge about which class is doing the initializing.

我最近想要一个非常轻量级的日志类,它可以根据可编程设置的日志级别输出不同数量的输出。但我不想每次输出调试消息、错误或警告时都实例化这个类。但是我还想封装这个日志记录工具的功能,并使其在不声明任何全局变量的情况下可重用。

所以我使用类变量和@classmethod装饰器来实现这一点。

使用简单的Logging类,我可以做到以下几点:

Logger._level = Logger.DEBUG

然后,在我的代码中,如果我想输出一堆调试信息,我就必须编写代码

Logger.debug( "this is some annoying message I only want to see while debugging" )

错误是可以改正的

Logger.error( "Wow, something really awful happened." )

在“生产”环境中,我可以指定

Logger._level = Logger.ERROR

现在,将只输出错误消息。调试消息将不会被打印。

这是我的班级:

class Logger :
    ''' Handles logging of debugging and error messages. '''

    DEBUG = 5
    INFO  = 4
    WARN  = 3
    ERROR = 2
    FATAL = 1
    _level = DEBUG

    def __init__( self ) :
        Logger._level = Logger.DEBUG

    @classmethod
    def isLevel( cls, level ) :
        return cls._level >= level

    @classmethod
    def debug( cls, message ) :
        if cls.isLevel( Logger.DEBUG ) :
            print "DEBUG:  " + message

    @classmethod
    def info( cls, message ) :
        if cls.isLevel( Logger.INFO ) :
            print "INFO :  " + message

    @classmethod
    def warn( cls, message ) :
        if cls.isLevel( Logger.WARN ) :
            print "WARN :  " + message

    @classmethod
    def error( cls, message ) :
        if cls.isLevel( Logger.ERROR ) :
            print "ERROR:  " + message

    @classmethod
    def fatal( cls, message ) :
        if cls.isLevel( Logger.FATAL ) :
            print "FATAL:  " + message

还有一些代码可以稍微测试一下:

def logAll() :
    Logger.debug( "This is a Debug message." )
    Logger.info ( "This is a Info  message." )
    Logger.warn ( "This is a Warn  message." )
    Logger.error( "This is a Error message." )
    Logger.fatal( "This is a Fatal message." )

if __name__ == '__main__' :

    print "Should see all DEBUG and higher"
    Logger._level = Logger.DEBUG
    logAll()

    print "Should see all ERROR and higher"
    Logger._level = Logger.ERROR
    logAll()

它允许您编写可与任何兼容类一起使用的泛型类方法。

例如:

@classmethod
def get_name(cls):
    print cls.name

class C:
    name = "tester"

C.get_name = get_name

#call it:
C.get_name()

如果你不使用@classmethod,你可以用self关键字来做,但它需要一个Class的实例:

def get_name(self):
    print self.name

class C:
    name = "tester"

C.get_name = get_name

#call it:
C().get_name() #<-note the its an instance of class C

当用户登录我的网站时,user()对象从用户名和密码实例化。

如果我需要一个没有用户在那里登录的用户对象(例如,一个管理用户可能想要删除另一个用户帐户,所以我需要实例化该用户并调用它的delete方法):

我有类方法来获取用户对象。

class User():
    #lots of code
    #...
    # more code

    @classmethod
    def get_by_username(cls, username):
        return cls.query(cls.username == username).get()

    @classmethod
    def get_by_auth_id(cls, auth_id):
        return cls.query(cls.auth_id == auth_id).get()

这是一个有趣的话题。我对它的理解是,python的classmethod操作起来像一个单例而不是一个工厂(它返回一个类的生成实例)。它是单例的原因是存在一个公共对象(字典),但只为类生成一次,但由所有实例共享。

为了说明这一点,这里有一个例子。注意,所有实例都有一个对单个字典的引用。这不是我理解的工厂模式。这可能是python独有的。

class M():
 @classmethod
 def m(cls, arg):
     print "arg was",  getattr(cls, "arg" , None),
     cls.arg = arg
     print "arg is" , cls.arg

 M.m(1)   # prints arg was None arg is 1
 M.m(2)   # prints arg was 1 arg is 2
 m1 = M()
 m2 = M() 
 m1.m(3)  # prints arg was 2 arg is 3  
 m2.m(4)  # prints arg was 3 arg is 4 << this breaks the factory pattern theory.
 M.m(5)   # prints arg was 4 arg is 5