递归函数,匿名函数
先来看一下函数的执行流程:
http://pythontutor.com/visualize.html#mode=edit #这个网站可以帮到你;
def foo1(b, b1=3) print("foo1 called", b, b1) def foo2(c): foo3(c) print("foo2 called", c) def foo3(d): print("foo3 called", d) def main(): print("main called") foo1(100, 101) foo2(200) print("main ending") main()
全局帧中生成foo1,foo2,foo3,main函数对象;
main函数调用;查找内建函数print压栈,将常量字符串压栈,调用函数,执行完成后弹出栈顶;
main中全局查找函数foo1压栈,将常量100,101压栈,调用函数foo1,创建栈帧,print函数压栈,字符串和变量b,b1压栈,调用函数,执行完成后弹出栈顶;
main中全局查找foo2函数压栈,讲常量200压栈,调用foo2,创建栈帧,foo3函数压栈,变量c引用压栈,调用foo3,创建栈帧,foo3完成print函数调用完成后弹出;foo2恢复调用,print执行完成后弹出栈顶;main中foo2调用结束弹出栈顶;main继续执行print函数调用,弹出栈顶,main函数返回;
简单说下我的理解:
函数嵌套时,外层函数调用压栈,在调用内层函数时压栈外层函数的进度,创建新的栈帧,后续依然,执行完成以后一层一层弹出;
递归函数
函数直接或间接调用自身就是递归;
递归需要有退出条件;
递归调用深度不宜过深,python对递归调用深度做了限制,默认是1000,超过递归深度限制,抛出:RecursionError: maxinum recursion depth exceeded
可以通过sys模块下的sys.getrecursionlimit()来更改;
递归调用对比:
import datetime # Fib Seq start = datetime.datetime.now() pre = 0 cur = 1 # No1 print(pre, cur, end=' ') n = 35 # loop for i in range(n-1): pre, cur = cur, pre + cur print(cur, end=' ') delta = (datetime.datetime.now() - start).total_seconds() print(delta) # Fib Seq start = datetime.datetime.now() pre = 0 cur = 1 # No1 print(pre, cur, end=' ') # recursion def fib1(n, pre=0,cur=1): pre, cur = cur, pre + cur print(cur, end=' ') if n == 2: return fib1(n-1, pre, cur) fib1(n) delta = (datetime.datetime.now() - start ).total_seconds() print(delta) start = datetime.datetime.now() def fib2(n): if n < 2: return 1 return fib2(n-1) + fib2(n-2) for i in range(n): print(fib2(i), end=' ') delta = (datetime.datetime.now() - start).total_seconds() print(delta)
递归性能(菲波那切数列):
递归:
import datetime n = 35 start = datetime.datetime.now() def fib(n): return 1 if n < 2 else fib(n-1) + fib(n-2) for i in range(n): print(fib(i), end=' ') delta = (datetime.datetime.now() -start).total_seconds() print(delta)
for循环:
import datetime start = datetime.datetime.now() pre = 0 cur = 1 # No1 print(pre, cur, end=' ') n = 35 for i in range(n-1): pre, cur = cur, pre + cur print(cur, end=' ') delta = (datetime.datetime.now() -start).total_seconds() print(delta)
递归改进:
pre = 0 cur = 1 # No1 print(pre, cur, end=' ') def fib(n, pre=0,cur=1): # recursion pre, cur = cur, pre + cur print(cur, end=' ') if n == 2: return fib(n-1, pre, cur) fib(n)
#fib函数和循环的思想类似,参数n是边界条件,用n来计算;上一次的计算结果直接作为函数实参.和循环比较,性能相近;
递归练习:
求n的阶乘
n = 10 def fac(n): if n == 1: return 1 return n * fac(n-1) print(fac(n)) n = 10 def fac1(n,p = 1): if n == 1: return p p *= n #print(p) fac1(n-1,p) return p print(fac1(n)) n = 10 def fac2(n,m = None): if m is None: m = [1] if n == 1: return m[0] m[0] *= n #print(m[0]) fac2(n-1, m) return m print(fac2(n))
将一个数逆序放入列表中,例如123=>[4,3,2,1]
def revert(x): if x == -1: return '' return data[x] + revert(x-1) print(revert(len(data)-1)) def revert(n,lst=None): if lst is None: lst = [] x,y = divmod(n,10) lst.append(y) if x == 0: return lst return revert(x,lst) print(revert(12345)) num = 123456 def revert(num,target=[]): if num: target.append(num[len(num)-1]) #target.append(num[-1:]) revert(num[:len(num)-1]) return target print(revert(str(num)))
猴子吃桃:猴子第一天摘下若干个桃子,当即吃了一半,不过瘾,又多吃了一个,第二天早上又将剩下的桃子吃掉一半,又多吃一个,以后每天早上都吃前一天剩下的一半零一个,第十天时,只剩下一个桃子,问第一天一共摘下多少个桃子
假设猴子摘了x个桃子
d1 x//2 -1
d2 d1//2 -1
d3 d2//2 -1
...
d9 d8//2 -1
d10 = 1
def peach(days = 1): if days == 10: return 1 return (peach(days+1)+1)*2 print(peach()) def peach(days = 10): if days == 1: return 1 return (peach(days - 1)+1)*2 print(peach())
匿名函数:
匿名函数即没有名字的函数,python借助lambda表达式构建匿名函数;
格式:
lambda 参数列表: 表达式
lambda x : x ** 2
(lambda x : x ** 2)(4) #调用
foo = lambda x : x ** 2 #不推荐这么用
匿名函数参数列表不需要小括号;冒号用来分割参数列表和表达式;不需要使用return,表达式的值,就是匿名函数的返回值;lambda表达式(匿名函数)只能写在一行上,被称为单行函数,主要用于高阶函数传参数,可以简化代码;
print((lambda :0)()) print((lambda x, y=3: x + y)(5)) print((lambda x, y=3: x + y)(5, 6)) print((lambda x, *, y=30: x + y)(5)) print((lambda x, *, y=30: x + y)(5, y=10)) print((lambda *args: (x for x in args))(*range(5))) print((lambda *args: [x+1 for x in args])(*range(5))) print((lambda *args: {x+2 for x in args})(*range(5))) [x for x in (lambda *args: map(lambda x: x+1, args))(*range(5))] # 高阶函数 [x for x in (lambda *args: map(lambda x: (x+1,args), args))(*range(5))]