重写__new__
方法
>>> class CapStr(str):
def __new__(cls, value):
return super(CapStr, cls).__new__(cls, value.capitalize())
>>> a = CapStr('abc')
>>> a
'Abc'
单例实现
>>> class Singleton():
def __new__(cls):
if not hasattr(cls, 'instance'):
cls.instance = super(Singleton, cls).__new__(cls)
return cls.instance
>>> a = Singleton()
>>> b = Singleton()
>>> a is b
True
或者
>>> class Singleton():
instance = None
def __new__(cls):
if not cls.instance:
cls.instance = super(Singleton, cls).__new__(cls)
# 也可以 cls.instance = object.__new__(cls)
return cls.instance
递归碾平多维数组
>>> a = [[1, 2, 3, [7, 8, 9]], [3, 4], [5, 6]]
>>> func = lambda x: [y for t in x for y in func(t)] if type(x) is list else [x]
>>> print(func(a))
[1, 2, 3, 7, 8, 9, 3, 4, 5, 6]
默认参数坑
Python的默认参数在编译阶段就创建了,可变对象容易坑
>>> def myfunc(num, lst=[]):
lst.append(num)
print(lst)
>>> myfunc(1)
[1]
>>> myfunc(2)
[1, 2]
排序可以传多个参数
>>> sorted([1, 2, 3, 0, -1, -2, -3], key=lambda x:(x<0, abs(x)))
[0, 1, 2, 3, -1, -2, -3]
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