Constructors in Python
Destructors are called when an object gets destroyed. In Python, destructors are not needed as much as in C++ because Python has a garbage collector that handles memory management automatically.
The __del__() method is a known as a destructor method in Python. It is called when all references to the object have been deleted i.e when an object is garbage collected.
Syntax of destructor declaration :
def __del__(self): # body of destructor
Note : A reference to objects is also deleted when the object goes out of reference or when the program ends.
Example 1 : Here is the simple example of destructor. By using del keyword we deleted the all references of object ‘obj’, therefore destructor invoked automatically.
Python3
# Python program to illustrate destructorclass Employee: # Initializing def __init__(self): print('Employee created.') # Deleting (Calling destructor) def __del__(self): print('Destructor called, Employee deleted.')obj = Employee()del obj |
Employee created. Destructor called, Employee deleted.
Note : The destructor was called after the program ended or when all the references to object are deleted i.e when the reference count becomes zero, not when object went out of scope.
Example 2: This example gives the explanation of above-mentioned note. Here, notice that the destructor is called after the ‘Program End…’ printed.
Python3
# Python program to illustrate destructor class Employee: # Initializing def __init__(self): print('Employee created') # Calling destructor def __del__(self): print("Destructor called") def Create_obj(): print('Making Object...') obj = Employee() print('function end...') return obj print('Calling Create_obj() function...')obj = Create_obj()print('Program End...') |
Calling Create_obj() function... Making Object... Employee created function end... Program End... Destructor called
Example 3: Now, consider the following example :
Python3
# Python program to illustrate destructor class A: def __init__(self, bb): self.b = bb class B: def __init__(self): self.a = A(self) def __del__(self): print("die") def fun(): b = B() fun() |
die
In this example when the function fun() is called, it creates an instance of class B which passes itself to class A, which then sets a reference to class B and resulting in a circular reference.
Generally, Python’s garbage collector which is used to detect these types of cyclic references would remove it but in this example the use of custom destructor marks this item as “uncollectable”.
Simply, it doesn’t know the order in which to destroy the objects, so it leaves them. Therefore, if your instances are involved in circular references they will live in memory for as long as the application run.
NOTE : The problem mentioned in example 3 is resolved in newer versions of python, but it still exists in version < 3.4 .
Example: Destruction in recursion
In Python, you can define a destructor for a class using the __del__() method. This method is called automatically when the object is about to be destroyed by the garbage collector. Here’s an example of how to use a destructor in a recursive function:
Python
class RecursiveFunction: def __init__(self, n): self.n = n print("Recursive function initialized with n =", n) def run(self, n=None): if n is None: n = self.n if n <= 0: return print("Running recursive function with n =", n) self.run(n-1) def __del__(self): print("Recursive function object destroyed")# Create an object of the classobj = RecursiveFunction(5)# Call the recursive functionobj.run()# Destroy the objectdel obj |
('Recursive function initialized with n =', 5)
('Running recursive function with n =', 5)
('Running recursive function with n =', 4)
('Running recursive function with n =', 3)
('Running recursive function with n =', 2)
('Running recursive function with n =', 1)
Recursive function object destroyed
In this example, we define a class RecursiveFunction with an __init__() method that takes in a parameter n. This parameter is stored as an attribute of the object.
We also define a run() method that takes in an optional parameter n. If n is not provided, it defaults to the value of self.n. The run() method runs a recursive function that prints a message to the console and calls itself with n-1.
We define a destructor using the __del__() method, which simply prints a message to the console indicating that the object has been destroyed.
We create an object of the class RecursiveFunction with n set to 5, and call the run() method. This runs the recursive function, printing a message to the console for each call.
Finally, we destroy the object using the del statement. This triggers the destructor, which prints a message to the console indicating that the object has been destroyed.
Note that in this example, the recursive function will continue running until n reaches 0. When n is 0, the function will return and the object will be destroyed by the garbage collector. The destructor will then be called automatically.
Advantages of using destructors in Python:
- Automatic cleanup: Destructors provide automatic cleanup of resources used by an object when it is no longer needed. This can be especially useful in cases where resources are limited, or where failure to clean up can lead to memory leaks or other issues.
- Consistent behavior: Destructors ensure that an object is properly cleaned up, regardless of how it is used or when it is destroyed. This helps to ensure consistent behavior and can help to prevent bugs and other issues.
- Easy to use: Destructors are easy to implement in Python, and can be defined using the __del__() method.
- Supports object-oriented programming: Destructors are an important feature of object-oriented programming, and can be used to enforce encapsulation and other principles of object-oriented design.
- Helps with debugging: Destructors can be useful for debugging, as they can be used to trace the lifecycle of an object and determine when it is being destroyed.
Overall, destructors are an important feature of Python and can help to ensure that objects are properly cleaned up and resources are not wasted. They are easy to use and can be useful for enforcing encapsulation and other principles of object-oriented design.
