The advanced function of Python learning

1. Namespace Python has three namespaces built-in namespaces:  the execution of the print (sum) print (max) global namespace:  file generates a global namespace as the Python interpreter launches. Refers to a file-level definition name that will be placed in that space X = 11if x == 11:    print (x) Local namespace:  A local namespace is generated when the function is called, and is only temporarily bound when the function is called, and is unbound at the end of the call X = 1000def foo ():     x = 1     print (x) foo () print (x) Scope:     1. Global scope:  built-in namespace, global namespace, globally valid, can be accessed in any location to,     unless del is deleted, otherwise surviving to the end of the file.     2. Local scope:  Local namespace, locally valid, can only be called at local scope, the call end is invalidated. First Name lookup order:  Local namespace--global namespace--built-in namespace X = 1000def func ():     x =  2    print (Locals ())      #locals () view names in local scopes print (Globals ())      #globals () View names in global Scopes 2. Function Object     1. Can be referenced     2.     3 can be passed as a parameter. The return value can be a function     4. can be used as a container type element       Example:     &nbsP;def foo ():          print ("From foo")       func = foo     print (foo)       Print (func)      foo ()      func ()            def foo ():          print ("From foo")      def bar (func):          print (func)          func ()       bar (foo)           def foo ():          print ("From foo")      dic = {' func ':  foo}     print (dic[' func '])      dic[' func '] ()                 3. Closure function      Closure:       1. defined in the intrinsic function       2. Contains references to external scopes rather than global scopes    the intrinsic function is called a closure function    Example:   def f1 ():     x = 1    def &NBSP;F2 ():      #f2称作闭包函数       print (x)    &NBSP;&NBSP;RETURN&NBSP;F2&NBSP;&NBSP;F&NBSP;=&NBSP;F1 ()   print (f)     #打印f2函数的内存地址   f ()      #打印1      Example:   from  Urllib.request import urlopen   def index (URL):        def get ():           return  Urlopen (URL). Read ()        return get   oldboy =  index (' http://www.baidu.com ')    p rint (Oldboy (). Decode (' Utf-8 '))    print (oldboy.__closure__[0].cell_contents)       #打印外部引用而非全局引用对象    4. Decorators      tools that decorate other objects, decorate add features, and tools refer to functions. The      adorner itself is any callable object, and the object being decorated can be any object that can be called. Why do          use adorners? The      open closure principle, which is closed for modification, is open to expansion. The      decorator is designed to add new functionality to a decorated object without modifying its source code and calling method          Adorner equivalent to closure implementation          Example:    import time     def timmer (func):         def wrapper (*args ,  **kwargs):             start_time =  time.time ()             res = func ( *args, **kwargs)             Stop_time = time.time ()             print ("run time is {0}". Format (stop_time - start_time))          return wrapper            @ timmer         #相当于index  = timmer (index)      def index ():         time.sleep (3)          print ("Welcome to index")          Return 1            index ()       #其实相当于执行了timmer (Index)          Example:     import  time    def timmer (func):         def  wrapper (*args, **kwargs):            start_time =  Time.time ()             res = func (*args,  **kwargs)             stop_time =  Time.time ()             print ("run time  IS&NBSP;{0} ". Format (stop_time - start_time))         return  wrapper            def index ():         time.sleep (3)         print (" Welcome to index ")         f = timmer (Index)      print (f)     f ()          #f () <= ====>wrapper ()              Authenticated User Login     login_user  = {' user ': none,  ' status ':  false}    def auth (func):         def wrapper (*args, **kwargs):             if login_user[' user '] and login_user[' status ':                 res =  func (*args, **kwargs)                  return res            else:                 name =  input ("Please enter Name:")                  passwd = iNput ("Please enter password:")                  if name ==  "Hyh"  and passwd ==  "123":                     login_user[' user '] =   "Hyh"                      login_user[' status '] = true                     print ("\033[45mlogin successful\ 033[0m ")                      res = func (*args, **kwargs)                      return res                 else:                     print ("\033[45mlogin err\033[0m")         return wrapper             @auth    def index ():        Print ("Welcome to index page")            @auth    def home (name):        print ("%s welcome to  home page " %  (name))             Index ()    home ("Hyh")    5. Iterator      iterator concept:  The result of repeating the last iteration is the initial value of the next iteration, and the repeating process is called Iteration,     one iteration at a time         Why do   have iterators?      onFor data types that do not have an index, you must provide an iterative approach that does not depend on the index          iterate objects:  built-in __iter__ methods are iterative objects     [1,2].__iter__ ()      ' Hello '. __iter__ ()      ( ). __iter__ ()     {"a":1,  "B":  2}.__iter__ ()     {1,2,3}.__iter __ ()          iterator:  executes the __iter__ () method, and the result is an iterator with an iterator __next__ () method   &NBSP;&NBSP;&NBSP;I&NBSP;=&NBSP;[1,2,3].__ITER__ ()     print (i.__next__ ())           #打印1     print (i.__next__ ())           #打印2     print (i.__next__ ())           #打印3     print (i.__next__ ())      #抛出异常     &NBSP;&NBSP;&NBSP;&NBSP;&NBSP;I__ITER__ ()  <==>iter (i)     i__next__ ()  <= =>next (i)          how to tell if an object is an iterative object or an iterator object     from collections  Import iterable, iterator    print (isinstance (' abc ', iterable))      print (Isinstance ([],iterable))     print (Isinstance ((), iterable))      print (Isinstance ({' A ': 1},iterable))     print (Isinstance ({1,2},iterable))      f=open (' A.txt ', ' W ')     f.__iter__ ()     print (Isinstance (F, iterable)      #只有文件是迭代器对象          iterative objects: only __iter__ Method that executes the method to get the iterator object      iteration Protocol:         object has __next__  The         object has __iter__, and for an iterator object, the __iter__ method is executed, and the result is still itself               advantages and disadvantages of iterators           Advantages:            1. Provides an iterative approach that does not rely on subscript              2. In terms of the drop iterator itself, it saves memory          disadvantage:             1.  cannot get the length of an iterator object              2.  is not as flexible as the sequence type, is a one-time, can only be taken back to the value, not forward

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The advanced function of Python learning