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Python operator overloading

Provided by Python language It has the operator overloading function and enhances the flexibility of the language. This is somewhat similar to but somewhat different from C++. In view of its special nature, today we will discuss Python operator overloading.

The Python language itself provides many magic methods, and its operator overloading is achieved by rewriting these Python built-in magic methods. These magic methods all start and end with double underscores, similar to the form of __X__. Python intercepts operators through this special naming method to achieve overloading. When Python's built-in operations are applied to a class object, Python will search for and call the specified method in the object to complete the operation.

Classes can overload built-in operations such as addition and subtraction, printing, function calls, indexing, etc. Operator overloading makes our objects behave the same as built-in objects. Python will automatically call such a method when calling an operator. For example, if a class implements the __add__ method, this method will be called when an object of the class appears in the + operator.

Common operator overloading methods

## __add__/__sub__Addition and subtraction operations X+Y, X+=Y/X-Y, X-=Y__or__Operator|X|Y, X|=Y_repr__／__str__Print/Convertprint(X) , repr(X)／str(X)__call__Function callX(*args, **kwargs)##__getattr____setattr____delattr__X.any##__getitem____setitem__##__delitem____len__ __bool____le__, __ge__, le: less equal, ge: greater equal, Field (enhanced) additionIteration##__contains__Membership Test__index__Integer value__delete__Descriptor attribute__new__Create

##Method name	Overloading description	Operator calling method
__init__	Constructor	Object creation: X = Class(args)
__del__	Destructor	X object is recovered




##Attribute reference	X.undefined
Attribute assignment	X.any=value
Attribute deletion	del
Index operation	X[key],X[i:j]
Index assignment	X[key], X[i:j]=sequence
Index and shard deletion	del X[key], del X[i:j]
Length	len(X)
Boolean test	bool(X)	##__lt__ , __gt__,
__eq__, __ne__	Specific comparison	in sequence For XY, X<=Y, X>=Y, X==Y, greater than,
eq: equal, ne: not equal ）	__radd__	Addition on the right side other+X __iadd__
X+=Y(or else __add__)		__iter__, __next__
I=iter(X), next( )
item in X (X is any iterable object)
hex(X), bin(X), oct(X)	##__enter__, __exit__	Environment Manager
with obj as var:	##__get__, __set__,
X.attr, X.attr=value, del X.attr
Create the object before __init__	The following is an introduction to the use of commonly used operator methods. Constructor and destructor: __init__ and __del__ ## Their main function is to create and recycle objects. When instances When created, the __init__ constructor is called. When the instance object is reclaimed, the destructor __del__ is automatically executed. >>> class Human(): ... def __init__(self, n): ... self.name = n ... print("__init__ ",self.name) ... def __del__(self): ... print("__del__") ... >>> h = Human('Tim') __init__ Tim >>> h = 'a' __del__ Copy after login Addition and subtraction operations: __add__ and __sub__ Overload these two With this method, you can add the +- operator operation on ordinary objects. The following code demonstrates how to use the +- operator. If the __sub__ method is removed from the code and then the minus operator is called, an error will occur. >>> class Computation(): ... def __init__(self,value): ... self.value = value ... def __add__(self,other): ... return self.value + other ... def __sub__(self,other): ... return self.value - other ... >>> c = Computation(5) >>> c + 5 10 >>> c - 3 2 Copy after login String representation of the object: __repr__ and __str__ This Both methods are used to represent the string expression of the object: the print() and str() methods will call the __str__ method, and the print(), str() and repr() methods will call the __repr__ method. As can be seen from the following example, when two methods are defined at the same time, Python will first search and call the __str__ method. >>> class Str(object): ... def __str__(self): ... return "__str__ called" ... def __repr__(self): ... return "__repr__ called" ... >>> s = Str() >>> print(s) __str__ called >>> repr(s) '__repr__ called' >>> str(s) '__str__ called' Copy after login Index value acquisition and assignment: __getitem__, __setitem__ By implementing these two methods, You can get and assign values to objects in the form such as X[i], and you can also use slicing operations on objects. >>> class Indexer: data = [1,2,3,4,5,6] def __getitem__(self,index): return self.data[index] def __setitem__(self,k,v): self.data[k] = v print(self.data) >>> i = Indexer() >>> i[0] 1 >>> i[1:4] [2, 3, 4] >>> i[0]=10 [10, 2, 3, 4, 5, 6] Copy after login Set and access attributes: __getattr__, __setattr__ We can overload __getattr__ and __setattr_ _ to intercept access to object members. __getattr__ is automatically called when accessing a member that does not exist in the object. The __setattr__ method is used to call when initializing object members, that is, the __setattr__ method is called when setting the item of __dict__. The specific example is as follows: class A(): def __init__(self,ax,bx): self.a = ax self.b = bx def f(self): print (self.__dict__) def __getattr__(self,name): print ("__getattr__") def __setattr__(self,name,value): print ("__setattr__") self.__dict__[name] = value a = A(1,2) a.f() a.x a.x = 3 a.f() Copy after login The running results of the above code are as follows. From the results, it can be seen that __getattr_ will be called when accessing the non-existent variable x _method; when __init__ is called, the assignment operation also calls the __setattr__ method. __setattr__ __setattr__ {'a': 1, 'b': 2} __getattr__ __setattr__ {'a': 1, 'x': 3, 'b': 2} Copy after login Iterator object: __iter__, __next__ ## Iteration in Python can be done directly by repeating Load the __getitem__ method to achieve this, see the example below. >>> class Indexer: ... data = [1,2,3,4,5,6] ... def __getitem__(self,index): ... return self.data[index] ... >>> x = Indexer() >>> for item in x: ... print(item) ... 1 2 3 4 5 6 Copy after login Iteration can be achieved through the above method, but it is not the best way. Python's iteration operation will first try to call the __iter__ method, and then try __getitem__. The iterative environment is implemented by using iter to try to find the __iter__ method, which returns an iterator object. If this method is provided, Python will repeatedly call the iterator object's next() method until a StopIteration exception occurs. If __iter__ is not found, Python will try to use the __getitem__ mechanism. Let's look at an example of an iterator. class Next(object): def __init__(self, data=1): self.data = data def __iter__(self): return self def __next__(self): print("__next__ called") if self.data > 5: raise StopIteration else: self.data += 1 return self.data for i in Next(3): print(i) print("-----------") n = Next(3) i = iter(n) while True: try: print(next(i)) except Exception as e: break Copy after login The running result of the program is as follows: __next__ called 4 __next__ called 5 __next__ called 6 __next__ called ----------- __next__ called 4 __next__ called 5 __next__ called 6 __next__ called Copy after login It can be seen that the implementation After the __iter__ and __next__ methods, the object can be iterated through the for in method, or the object can be iterated through the iter() and next() methods. Thank you for reading, I hope it can help you, thank you for your support of this site!

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