flask decorators

normal objects, and can be assigned to other variables, which can be used as return values and can be defined within another function.1 Import Time2 3 defTiming (fun):4 5 defDeco (*ARG, * *kwarg):6 7Start_time =time.time ()8 9Fun (*arg, * *Kwarg)Ten OneStop_time =time.time () A - Print('The func run time is:%s'% (Stop_time-start_time)) - the returndeco - - @Timing - defTar (name, age): + -Time.sleep (2) + A Print('In the tar:', name, age) at -Tar'HK', 18)Operation Res

Complete with the adorner: (1) Index login does not need authentication, home and BBS login needs authentication function; (2) Home login with local authentication, BBS login with LDAP authentication1 __author__="Csy"2 Import Time3 4USER,PASSWD ='Csy','123456'5 6 defAuth (auth_type): #最外层auth用于传递auth_type认证类型7 Print("auth func", Auth_type)8 defOuter_wrapper (func):9 defWrapper (*args, * *Kwargs):Ten Print("wrapper func args", *args,**Kwargs) One ifAuth_typ

, to execute the inner function, you must first execute the outer function, in order to call into the inner function, then there are:def timer (parameter): # print ("In the Auth:", parameter) def Outer_deco (func): # Print ("in the Outer_wrapper : ", parameter) def deco (*args, **kwargs): Return deco return Outer_decoFirst timer (parameter), receive the parameter parameter= ' TASK1/2 ', and @timer (parameter) also happens to have parentheses, then will execute this function, then is equivalent t

() print‘end‘ return _deco@decodef foo(): print‘In foo‘foo()foo()Output:startIn fooendstartIn fooendAdorner with parametersYou need to return the adorner with the function as a parameter. In other words, Decomaker () did something with Deco_args and returnedA function object, which is an adorner with Foo as its argument. Simply put: foo = Decomaker (Deco_args) (foo)Instance defdeco(ARG): def wrapper(func): def _deco(x): Print "Get param is:", x func (x)retu

Usage scenarios:Think of the question: How can you add new functionality to the original module for a production system, with minimal modifications? This can be accomplished with the adorner.The adorner has two standards:1, do not modify the original code and the original call mode;2, can add new functions;For example, we have a method func1, in which we print two messages and sleep for 1 seconds. Def func1 (): Print ("This was inthe func1 Methord") Time.sleep (1) Print

, b):returnA-bdefAdd (A, b):returnA +bPrintSub (3,4) Dec= Pre_str ('_') Add=Dec (add)PrintAdd (3, 4)This is also a good understanding of the bar, our decorative running mode and step-by call is the same effect.This implements the adorner syntax transfer parameters, the effect is good.Class DecoratorSee below for an example:defDecorator (aclass):classNewclass:def __init__(self, Age): Self.total_display=0 self.wrapped=AClass (age)defdisplay (self): Self.total_display+ = 1Print "Total display:%s"%s

, in the middle of each result, suspends the function state so that the next time it continues to return.　　2, Generator expression : Generates a Generator object, produces the result on demand, or produces a specific value when iterating. 1, generator function def Gensquares (n): for i in range (n): Span style= "COLOR: #0000ff" >yield i * * 2obj = gensquares (5" print (obj) # Span style= "COLOR: #008000" > print (Next (obj)) # 0 print (Next (obj)) # 1 print (Next (ob

0Next (G)#Output 1Next (I1)#Output 4 #(2) The generator does not retain the result after the iterationGen = (i forIinchRange (4)) inchGen#returns TrueinchGen#returns TrueinchGen#return False, in fact, when detecting 2, 1 is not in the generator, that is, 1 has been iterated, the same 2, 3 is not2. Generator expressionsLimitations: only suitable for simple algorithmsExample: for in range (1,10))print(next Test)print(test). __next__())3. Generator function yieldExample of the Fibonacci func

)Time.sleep (0.3)Print (' wash more healthily ... ')Login (2,3) # inner (2,3)@timmer # Register = timmer (register)def register (a):Time.sleep (0.2)Print (' wash more health 22 ... ')Register (1) # inner (1)def func1 (x):x = 0Print (x)Func1 (0)function with return value of adorner (Universal adorner)Def Timmer (f): # f = Login function namedef inner (*args,**kwargs): # args (2, 3)Start_time = Time.time ()ret = f (*args,**kwargs) # login () * (2, 3) 2,3End_time = Time.time ()Print (' Execution ti

() # python2.5 demo6.py say something...in func　　In fact, we can achieve the same effect without decorator at all, only minor changes to demo6.py.# Cat demo7.py def should_say (FN): def Say (*args): print ("Say something ...") fn (*args) return saydef Func (): print ("in func") func = Should_say (func) func () # python2.5 demo7.py say something...in func　　You will find that the output of demo6.py and demo7.py is the same. In fact, based on the above analysis of the closur

example defines a square () function, but immediately passes it as a parameter to the trace () and replaces the returned object with the original square. Adorners as the name implies is to add some decorations to the original function, for example, we here the trace function can do some extra things, the last object returned can be a function containing square, that is, our square function "decorate"Let's look at an example of the usual use:enable_tracing = Trueif enable_tracing: debug_log =

Well, the basics are good, talk decorator, first look at this code:defSayhi (name):return "How is you {0}, Good morning". Format (name)defDecoator (func):deffunc_wrapper (name):return "". Format (func (name))returnFunc_wrapperhi=decoator (Sayhi)PrintHi"Allen")Don't you think it's particularly handy when we call the Hi () method every time?Many people will ask, why use Decoator? Consider whether it is more convenient to add a function that returns Okay, here's a little syntax sugar, with the @ fu

, which is the iteratorIterators are suitable for iterative objects3. What is an iterative object?Every object in Python that has a built-in __iter__ method is an iterative objectAn iterative object contains: strings, lists, tuples, dictionaries, collections, and files4. What is an iterator object?An iterator object refers to an object that has a built-in __iter__ method and a built-in __next__ method.The __iter__ method that executes an iterative object gets the built-in iterator objectThe file

Print the difference between args and *args1 # Printing Time difference 2 def outer (*args, * *Kwargs):3 print(args) # output: (1, 2, 3, 4)4 print(*args) # output: 1 2 3456 Outer (1,2,3,4)1 #difference between function calls2 defOuter (*args, * *Kwargs):3 Print(args)4 Print(*args)#also called the function, which is called the print function5 6Outer ([1,2,3,4])#Output results: ([1, 2, 3, 4],)7 #[1, 2, 3, 4]8 9Outer (*[1,2,3,4])#Output results

x is deleted, it is actually captured by __del__, and this time the incoming instance is a2). Some students say this descriptor is useless.Here's a small example of how it can be done, like we're designing a class, and we want it to do type checking on their instance properties like c,c++:P=person ()P.name= ' Jack ' #名字必须是strP.age=18 #年龄必须是intP=person ()P.name= ' Lily 'Print (' Name: ', p.name)>>Name:lilyIf writtenP.name=123>>Raise TypeError (' expected an {} '. Format (Self.your_type))typeerro

Closed PackageClosures: two nested functions, external functions return references to intrinsic functions, external functions must have parametersdef external function (parameter):def intrinsic function ():Passreturn intrinsic functionThe difference between him and the function:1. Format two nested functions2. Parameters of the closure external function can be persisted in memoryDecorative DeviceWhat the adorner is: Closure plus @xxxThe role of the adorner: adding additional functionality withou

modificationPrint (' My first decorator ', args)Return (' Nihao ', args)MyFunc (' Wangkai ') #调用被装饰的函数MyFunc (' Kevin ')info = MyFunc (' Gonghui ')Print (info) ★ decorated with: def Decowithargs (ARG):"" "because the decorator function with parameters only uses the parameters when applied and does not receive the decorated function as arguments,Therefore, a decorator function must be returned, which encapsulates the decorated function ""def Newdeco (func): #定义一个新的decorator函数def repl

template:importtimedefrun_time (func):# The outermost function name is replaced by your decorator's name defwrapper (*args,**kwargs): "Run time of function to calculate parameters" t=time.time () # here to replace your code snippet res=func (*args,**kwargs) # the same sentence print (Time.time () -t) # Here's your code snippet returnres# that's not the same thing. returnwrapper@run_timedefsleep (n): "Wait n seconds after run" print ("Waitfor%dseconds"%n) time.sleep (n) return "END" Print (

value.There are also times when we need to give the decorator a pass-through for internal use. Solution look below.High-level case--to the adornerImport timedef Timer (temp): print (' This was ', temp) #这里是加进来的参数 def Out (func): def deco (*args,**kwargs ): start_time = time.time () res = func (*args,**kwargs) stop_time = Time.time () print (' The Func run time Is%s '% (stop_time-start_time)) return res return deco re

The function return value is the built-in function name:def sum(*args): def sum_in():Ax = 0For N in args:AX = ax + Nreturn AXreturn sum_inWhen we call sum() , we return the SUM function instead of summing the result:>>> f = sum(1, 3, 5, 7, 9)>>> ffunction sum.locals>.sum_in at 0x101c6ed90>When the function is called f , the result of the sum is really computed:>>> f()2525In this example, we define the function in the function sum sum , and the intrinsic function sum_in can refer to sum the param