Python中实现参数类型检查的简单方法
时间:2021-11-29 16:22 作者:admin610456
python/' target='_blank'>python是一门弱类型语言,很多从C/C++转过来的朋友起初不是很适应。比如,在声明一个函数时,不能指定参数的类型。用C做类比,那就是所有参数都是void*类型!void类型强制转换在C++中被广泛地认为是个坏习惯,不到万不得已是不会使用的。
Python自然没有类型强制转换一说了,因为它是动态语言。首先,所有对象都从Object继承而来,其次,它有强大的内省,如果调用某个不存在的方法会有异常抛出。大多数情况,我们都不需要做参数类型栓查,除了一些特殊情况。例如,某个函数接受一个str类型,结果在实际调用时传入的是unicode,测试过程中又没有代码覆盖到,这样问题就比较严重了。解决方法也很简单,借助Python的内省,很容易就能判断出参数的类型。但是每个地方都写检查代码会很累赘,何况它带来的实际价值并不高。一个好的解决方法是使用装饰器。
''' >>> NONE, MEDIUM, STRONG = 0, 1, 2 >>> >>> @accepts(int, int, int) ... def average(x, y, z): ... return (x + y + z) / 2 ... >>> average(5.5, 10, 15.0) TypeWarning: 'average' method accepts (int, int, int), but was given (float, int, float) 15.25'''def accepts(*types, **kw): """ Function decorator. Checks that inputs given to decorated function are of the expected type. Parameters: types -- The expected types of the inputs to the decorated function. Must specify type for each parameter. kw -- Optional specification of 'debug' level (this is the only valid keyword argument, no other should be given). debug = ( 0 | 1 | 2 ) """ if not kw: # default level: MEDIUM debug = 1 else: debug = kw['debug'] try: def decorator(f): def newf(*args): if debug == 0: return f(*args) assert len(args) == len(types) argtypes = tuple(map(type, args)) if argtypes != types: msg = info(f.__name__, types, argtypes, 0) if debug == 1: print >> sys.stderr, 'TypeWarning: ', msg elif debug == 2: raise TypeError, msg return f(*args) newf.__name__ = f.__name__ return newf return decorator except KeyError, key: raise KeyError, key + "is not a valid keyword argument" except TypeError, msg: raise TypeError, msgdef info(fname, expected, actual, flag): """ Convenience function returns nicely formatted error/warning msg. """ format = lambda types: ', '.join([str(t).split("'")[1] for t in types]) expected, actual = format(expected), format(actual) msg = "'%s' method " % fname \ + ("accepts", "returns")[flag] + " (%s), but " % expected\ + ("was given", "result is")[flag] + " (%s)" % actual return msg
本质上讲,这也是一种运行时检查,但效果已经不错了。
更多有趣的装饰器的使用,可以参考这篇文章http://wiki.python.org/moin/PythonDecoratorLibrary
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