Function recursion, anonymous function, built-in function

1. Function recursion
1. What is
a special form of nested call of function recursive function
refers specifically to calling itself in the process of calling a function, which is called function recursive call

def f1():             #在调用一个函数过程中直接调用自己
    print('from f1')
    f1()

2. Why use function recursion?
It will be more convenient and simple to use in certain situations

import sys
print(sys.getrecursionlimit()) #查看递归层级
sys.setrecursionlimit(2000)  #改变递归层级

def f1():       #在调用一个函数过程中间接调用自己
    print('fi')
    f2()
def f2():
    print('f2')
    f1()
f1()

Meaningful recursion should be able to end under certain conditions.
The process of a recursion should be divided into two stages:
1. Backtracking: call to the next level.
2. Recursion: return to the next level.
Example

def age(n):
    if n == 1:
        return 18
    return age(n-1) + 10

res = age(5)
print(res)

In what scenarios is recursion convenient?
Recursion is to use a function to implement a loop
example 1

nums = [1, [2, [3, [4, [5, [6, [7, [8, ]]]]]]]]

def func(nums):
    for item in nums:
        if type(item) is list:
            func(item)
        else:
            print(item)

func([1, [2, [3, [4, [5, [6, [7, [8, ]]]]]]]])

Example 2 Find the number is not in the list

nums = [-3, 1, 5, 7, 9, 11, 13, 18, 22, 38, 78, 98]

方法一（效率不高）
for num in nums:
    if num == find_num:
        print('find it')
        break
方法二（二分法，一种算法高效解决问题方法）
def search(find_num, nums):
    # print(nums)
    if len(nums) == 0:
        print('not exists')
        return
    mid_index = len(nums) // 2
    if find_num > nums[mid_index]:
        # in the right
        new_nums = nums[mid_index + 1:]
        search(find_num, new_nums)
    elif find_num < nums[mid_index]:
        # in the left
        new_nums = nums[:mid_index]
        search(find_num, new_nums)
    else:
        print('find it')

search(23, nums)

Two, anonymous function

res=(lambda x,y:x+y)(4,5)
print(res)

Common usage is to use together with other functions for
example (find out the person with the most salary in the dictionary)

salaries = {
    'axx':1000000,
    'zxx':3000,
    'egon':4000,
}

#介绍max  print(max([1,2,3,4]))  #max 传可迭代对象

def func(k):                   #只用一次可以用lambda代替
    return salaries[k]

print(max(salaries,key=func))   #用key可以改变比较依据

print(max(salaries,key=lambda k:salaries[k]))
print(min(salaries,key=lambda k:salaries[k]))
print(sorted(salaries,key=lambda k:salaries[k]))
print(sorted(salaries,))

Three, built-in function to understand
filter # (filter)

names = ['egon_nb',"lxx_sb","hxx_sb"]

res =(name for name in names if name.endswith('sb'))
print(res)

res = filter(lambda name:name.endswith('sb'),names)
print(res)
print(list(res))

map #映出

names = ['egon','lxx','zxx']

res = [name + "vip" for name in names]
print(res)

res = map(lambda name:name + "vip",names)
print(res)
print(list(res))

reduce #The module is summarized as

from functools import reduce

reduce(lambda x,y:x+y,[1,2,3,4,5,6],100)
res = reduce(lambda x,y:x+y,["a","b","c"])
print(res)