isinstance工作原理:

if isinstance(obj, MyClass): do_foo(obj)

但是，请记住:如果它看起来像鸭子，如果它听起来像鸭子，它就是鸭子。

编辑:对于None类型，你可以简单地做:

if obj is None: obj = MyClass()

我用type(x) == type(y)

例如，如果我想检查一个数组:

type( x ) == type( [] )

字符串检查:

type( x ) == type( '' ) or type( x ) == type( u'' )

如果您想检查None，请使用is

x is None

对于其他类型，请查看types模块:

>>> import types
>>> x = "mystring"
>>> isinstance(x, types.StringType)
True
>>> x = 5
>>> isinstance(x, types.IntType)
True
>>> x = None
>>> isinstance(x, types.NoneType)
True

注:类型检查是个坏主意。

要获取类型，使用__class__成员，如unknown_thing.__class__

Talk of duck-typing is useless here because it doesn't answer a perfectly good question. In my application code I never need to know the type of something, but it's still useful to have a way to learn an object's type. Sometimes I need to get the actual class to validate a unit test. Duck typing gets in the way there because all possible objects have the same API, but only one is correct. Also, sometimes I'm maintaining somebody else's code, and I have no idea what kind of object I've been passed. This is my biggest problem with dynamically typed languages like Python. Version 1 is very easy and quick to develop. Version 2 is a pain in the buns, especially if you didn't write version 1. So sometimes, when I'm working with a function I didn't write, I need to know the type of a parameter, just so I know what methods I can call on it.

这就是__class__参数派上用场的地方。这(据我所知)是获取对象类型的最佳方法(可能是唯一的方法)。

使用isinstance(object, type)。如上所述，如果你知道正确的类型，这很容易使用，例如，

isinstance('dog', str) ## gives bool True

但对于更深奥的对象，这可能很难使用。 例如:

import numpy as np 
a = np.array([1,2,3]) 
isinstance(a,np.array) ## breaks

但你可以用这个技巧:

y = type(np.array([1]))
isinstance(a,y) ## gives bool True 

所以我建议用你想检查的对象类型(例如，type(np.array())实例化一个变量(在本例中是y)，然后使用isinstance。

因为type返回一个对象，所以可以使用object.name访问对象的名称

例子:

years = 5
user = {'name':'Smith', 'age':20}

print(type(a).__name__) 

输出:“int”

print(type(b).__name__ )

输出:“东西”