Creating Python functions

def func2():
    print('haha')
    # Return value of function
    # Return value of function,No return defined None,
    # There is a return value that returns this object(You can return a function object),
    # More than one returns a tuple
    return 0

Calls to Python functions

func2()

Arguments to Python functions

def func3(x,y,z=5,*args,**kwargs):
    print(x)
    print(y)
    print(z)
func3(1,2,3)
#Actual parameters(Real reference):1,2,,3
#Formal parameter(Formal parameter):x,y,z
#Default parameters:z=5,(Must not be passed)

def func3(x,y,z=5,*args,**kwargs):
    print(x)
    print(y)
    print(z)
#Transfer of position parameters,Location characteristics:Need one-to-one correspondence
func3(1,2,3)
#Key parameter passing,Properties of keywords:No one-to-one correspondence
func3(x=1,y=2,z=3)
#Unfixed parameter:*args,**kwargs
#*args Receive the value of redundant position parameter,In tuple form
#**kwargs Receive value of extra key parameter,In a dictionary way
#Transfer of mixed parameters,Characteristic:Position parameter should precede key parameter,Inherited location and keyword properties
func3(1,y=2,z=3)

Python global and local variables

def test():
    name='xiaoming'#This is a local variable
global name #Define a global variable

Recursion of Python functions

Three characteristics of recursion: 1. There must be a clear ending condition; 2. The scale of each problem should be reduced; 3. The efficiency of recursion is not high

def calc(n):
    print(n)
    if n>0:
        return calc(int(n/2))
calc(10)

Python higher order functions

There are two kinds of higher-order functions (functions or variables): 1. When a function passes a parameter to another function, return returns the memory address of a function

#Function when parameter transfer
def add(a,b,i):
    res=i(a)+i(b)
    print(res)
add(1.222,2.111,int)
#Function when the return value returns
def func4():
    print('this is func4')
    return func5
def func5():
    print('this is func5')
func5=func4()
func5()

Nesting of Python functions

#Nesting of functions
def func6():
    print('this is func6')
    def func7():
        print('this is func7')
    func7()
func6()

Python decorator

Condition of decorator: nesting of higher order function + function

def logger(funcTest):   #Pass the memory address of the source code to the decorator
    def waps(*args,**kwargs): #Package interior finisher
        print('befor')        #Contents of decoration
        res=funcTest(*args,**kwargs)#Call source
        print('after')
        return res            #Return funcTest Results of
    return waps               #Return the encapsulated decorator
@logger #funcTest=logger(funcTest)
#Source code of decorated function
def funcTest(x):
    print('this is test file',x)
    return x
#funcTest=logger(funcTest) #The logger returns the memory address of waps,
x=funcTest(x=1) #The actual call is from the top waps,Through internal waps Called funcTest
print(x)

Python three tier decorator

def auth(auth_type): #Add decorator parameters to the third layer
    def out(func):
        def wrapper(*args,**kwargs):
            if auth_type=='localhost':
                if local_login():
                    print('Login successful')
                    return func(*args,**kwargs)
                else:
                    print('Login failed')
            elif auth_type=='file':
                if file_login():
                    pass    #File interface login
            else:
                print('There is no login interface')
        return wrapper
    return out
@auth(auth_type='localhost')
def index():
    print('welcome to index page')
index()