python 函数中的递归lambda map reduce 等详解

Posted 2020-10-17

 

举例说明

#例1：
###递归函数求和
from traitlets.traitlets import Instance
def mysum(L):
    print(L)
    if not L:
        return 0
    else:
        return L[0] + mysum(L[1:])  #调用自己 call myself

sum1 = mysum([1,2,3,4])
print(sum1)


# 编写替代方案
def mysum1(L):
    return 0 if not L else L[0] + mysum1(L[1:])
print(‘#改写方案1‘)
sum1 = mysum1([1,2,3,4,5,6,7])
print(sum1)    

#改写方案2
def mysum2(L):
    return L[0] if len(L) ==1 else L[0] + mysum2(L[1:])
sum2 = mysum2([1,2,3])
print(‘改写方案2‘)
print(sum2)

#改写方案3
def mysum3(L):
    first,*rest = L 
    return first if not rest else first + mysum3(rest) ##python3 扩展序列 ext seq 
sum3 = mysum3([1,2,3,4,5])
print(‘改写方案3‘)
print(sum3)
### 用while 循环实现
L = [1,2,3,4,5]
sum2 = 0
while L:
    sum2 += L[0]
    L = L[1:]
print(‘用while 循环实现‘)
print(sum2)

##用for 循环实现
L = [1,2,3,4,5,6]
sum3 =0
for x in L:
    sum3 += x   
print(‘用for循环实现‘) 
print(sum3)


# 处理任意结构

def sumtree(L):
    tot = 0
    for x in L:
        if not isinstance(x,list):
            tot += x
        else:
            tot +=sumtree(L[1:])
    return tot
L = [1,[2,[3,4],5],6,[7,8]]
print(‘##任意结构‘)
print(sumtree(L))

##间接函数调用
def echo(message):
    print(message)


def indirect(func,args):
    func(args)
indirect(echo, ‘shixingwen‘)

schedule1=[ (echo,‘Spam！‘),(echo,‘Ham!‘) ]
for (func,args) in schedule1:
    func(args)
    
print(‘##间接调用函数‘)
print(echo.__name__)

###python 函数注解

def func(a:‘spam‘,b:(1,3),c:float):
    return a + b+c
print(‘##函数注释‘)
print(func(1,2,3))
zhushi = func.__annotations__
    
print(zhushi,‘\n‘)
for args in zhushi:
    print(args ,‘=>‘, zhushi[args])
    
    
##map 在序列中映射函数
counter = [1,2,3,4]
update = []
for i in counter:
    update.append(i+10)
print(‘##for循环实现‘)
print(update)


def inc(i):return i +10
print(‘##map 在序列中映射函数‘)
print(list(map(inc,counter)))
print(‘####lambda 也能实现‘)
print(list(map(lambda i:i +10,counter)))

##
from functools import reduce
re=reduce(lambda x, y: x+y, [1, 2, 3, 4, 5])
print(re)

import functools
print(‘查询reduce用法‘)
help(functools.reduce)

##或者
from functools import reduce
help(reduce)

上述结果如下

[1, 2, 3, 4]
[2, 3, 4]
[3, 4]
[4]
[]
10
#改写方案1
28
改写方案2
6
改写方案3
15
用while 循环实现
15
用for循环实现
21
##任意结构
43
shixingwen
Spam！
Ham!
##间接调用函数
echo
##函数注释
6
{‘c‘: <class ‘float‘>, ‘a‘: ‘spam‘, ‘b‘: (1, 3)} 

c => <class ‘float‘>
a => spam
b => (1, 3)
##for循环实现
[11, 12, 13, 14]
##map 在序列中映射函数
[11, 12, 13, 14]
####lambda 也能实现
[11, 12, 13, 14]
15
查询reduce用法
Help on built-in function reduce in module _functools:

reduce(...)
    reduce(function, sequence[, initial]) -> value
    
    Apply a function of two arguments cumulatively to the items of a sequence,
    from left to right, so as to reduce the sequence to a single value.
    For example, reduce(lambda x, y: x+y, [1, 2, 3, 4, 5]) calculates
    ((((1+2)+3)+4)+5).  If initial is present, it is placed before the items
    of the sequence in the calculation, and serves as a default when the
    sequence is empty.

Help on built-in function reduce in module _functools:

reduce(...)
    reduce(function, sequence[, initial]) -> value
    
    Apply a function of two arguments cumulatively to the items of a sequence,
    from left to right, so as to reduce the sequence to a single value.
    For example, reduce(lambda x, y: x+y, [1, 2, 3, 4, 5]) calculates
    ((((1+2)+3)+4)+5).  If initial is present, it is placed before the items
    of the sequence in the calculation, and serves as a default when the
    sequence is empty.