*args和**kwargs是什么意思?
def foo(x, y, *args):
def bar(x, y, **kwargs):
*args和**kwargs是什么意思?
def foo(x, y, *args):
def bar(x, y, **kwargs):
当前回答
*和**在函数参数列表中有特殊用法*表示参数是列表,**表示参数是一本字典。这允许函数接受任意数量的论据
其他回答
除了函数调用之外,*args和**kwargs在类层次结构中也很有用,并且还可以避免在Python中编写__init__方法。类似的用法可以在Django代码等框架中看到。
例如
def __init__(self, *args, **kwargs):
for attribute_name, value in zip(self._expected_attributes, args):
setattr(self, attribute_name, value)
if kwargs.has_key(attribute_name):
kwargs.pop(attribute_name)
for attribute_name in kwargs.viewkeys():
setattr(self, attribute_name, kwargs[attribute_name])
子类可以是
class RetailItem(Item):
_expected_attributes = Item._expected_attributes + ['name', 'price', 'category', 'country_of_origin']
class FoodItem(RetailItem):
_expected_attributes = RetailItem._expected_attributes + ['expiry_date']
然后将子类实例化为
food_item = FoodItem(name = 'Jam',
price = 12.0,
category = 'Foods',
country_of_origin = 'US',
expiry_date = datetime.datetime.now())
此外,具有仅对该子类实例有意义的新属性的子类可以调用基类__init__来卸载属性设置。这是通过*args和**kwargs完成的。kwargs主要用于使用命名参数使代码可读。例如
class ElectronicAccessories(RetailItem):
_expected_attributes = RetailItem._expected_attributes + ['specifications']
# Depend on args and kwargs to populate the data as needed.
def __init__(self, specifications = None, *args, **kwargs):
self.specifications = specifications # Rest of attributes will make sense to parent class.
super(ElectronicAccessories, self).__init__(*args, **kwargs)
其可以被初始化为
usb_key = ElectronicAccessories(name = 'Sandisk',
price = '$6.00',
category = 'Electronics',
country_of_origin = 'CN',
specifications = '4GB USB 2.0/USB 3.0')
完整的代码在这里
上下文
python 3.x使用打开包装**与字符串格式一起使用
与字符串格式一起使用
除了本主题中的答案之外,还有一个其他地方没有提到的细节。这扩展了Brad Solomon的答案
使用python str.format时,使用**解包也很有用。
这有点类似于使用python f-string f-string所做的操作,但增加了声明dict以保存变量的开销(f-string不需要dict)。
快速示例
## init vars
ddvars = dict()
ddcalc = dict()
pass
ddvars['fname'] = 'Huomer'
ddvars['lname'] = 'Huimpson'
ddvars['motto'] = 'I love donuts!'
ddvars['age'] = 33
pass
ddcalc['ydiff'] = 5
ddcalc['ycalc'] = ddvars['age'] + ddcalc['ydiff']
pass
vdemo = []
## ********************
## single unpack supported in py 2.7
vdemo.append('''
Hello {fname} {lname}!
Today you are {age} years old!
We love your motto "{motto}" and we agree with you!
'''.format(**ddvars))
pass
## ********************
## multiple unpack supported in py 3.x
vdemo.append('''
Hello {fname} {lname}!
In {ydiff} years you will be {ycalc} years old!
'''.format(**ddvars,**ddcalc))
pass
## ********************
print(vdemo[-1])
此表便于在函数构造和函数调用中使用*和**:
In function construction In function call
=======================================================================
| def f(*args): | def f(a, b):
*args | for arg in args: | return a + b
| print(arg) | args = (1, 2)
| f(1, 2) | f(*args)
----------|--------------------------------|---------------------------
| def f(a, b): | def f(a, b):
**kwargs | return a + b | return a + b
| def g(**kwargs): | kwargs = dict(a=1, b=2)
| return f(**kwargs) | f(**kwargs)
| g(a=1, b=2) |
-----------------------------------------------------------------------
这真的只是用来概括洛林·霍希斯坦的答案,但我觉得它很有用。
相关地:在Python 3中扩展了星形/splat运算符的用法
def foo(param1,*param2):是一个可以接受任意数量的*param2值的方法,def bar(param1,**param2):是一种方法,可以接受任意数量的带有*param2键的值param1是一个简单的参数。
例如,在Java中实现varargs的语法如下:
accessModifier methodName(datatype… arg) {
// method body
}
*args(或*any)表示每个参数
def any_param(*param):
pass
any_param(1)
any_param(1,1)
any_param(1,1,1)
any_param(1,...)
注意:不能将参数传递给*args
def any_param(*param):
pass
any_param() # will work correct
*参数的类型为元组
def any_param(*param):
return type(param)
any_param(1) #tuple
any_param() # tuple
用于访问不使用的元素*
def any(*param):
param[0] # correct
def any(*param):
*param[0] # incorrect
**千瓦时
**kwd或**任何这是字典类型
def func(**any):
return type(any) # dict
def func(**any):
return any
func(width="10",height="20") # {width="10",height="20")