What Is Operator Overloading in Python?

Programmers can straightaway use pre-defined operators like +, =, *, >, <, etc. on built-in data types to write programs. However, these operators fail to work in user-defined data types. Therefore, Python comes up with operator loading capability, allowing programmers to redefine operators when working on class objects.  

Operator overloading allows programmers to extend the meaning of pre-defined operators. Simply put, it provides an expanded definition over what is pre-defined, making it easier for programmers to work seamlessly with both basic data types and user-defined data types. 

For instance, operator ‘+’ will add two numbers, either by adding two ranges or combining two lists. You can do the same by overloading the ‘+’ operator with the int and str class. Users may have observed that the identical built-in operator or function exhibits a particular behaviour for components of any specific Python class named operator overloading. 

Considering two items depicting a specific class, where you have to insert two objects using the binary ‘+’ operator. Perhaps it will show an error the compiler does not understand how to add. So, we describe an operator mechanism named overloading of the operator. Python includes a magic feature to conduct operator overloading which is immediately activated once paired with this same specific operator. 

Output:  

Oops! The program is not working and perhaps displays a TypeError. Why? Because we have not yet expanded the code functionalities, and it is operating in built-in groups only. So, how can we enable these operators to run in our device class circles? 

Here the “magic techniques” enter the equation. In Python, magic methods include unique procedures that begin and finish with __init__(). The __str__() technique is also another magic method explicitly returning the spring representation of objects. 

Program to overload the + operator

Output: 

Let us look at one more example to understand overloading better: 

Program to subtract two complex numbers without overloading the – operator 

Output: 

Program to overload the ‘–‘ operator on a complex object 

Output: 

Many programming languages like C, C++, and Java have a standard library, allowing programmers to extract strings, numbers, and objects from text input stream with no hassle. Unfortunately, there is no availability for such a library for Python programmers. Python has a stream interface – classes that inherit from io.IOBase that provides facilities for line-oriented input. Perhaps if the user-inputs are arbitrary, the re-module must be the prime consideration. 

You may be familiar with increment and decrement operators shown by + + and –  – separately if you were acquainted with C, Java, or PHP. But in Python, there seem to be no operators for increment or decrement. 

It may sound weird, but we code + = or x = x+ 2 in Python if we are to increase variable value by 2, and we are applying – = or do x = x – 2 to decrease it by 2. 

Possible conceptual explanations why Python has no increase and decrement operators could be because the same outcome is obtained through + = or – = seamlessly. 

Output: 

Output: 

The assignment operator, as the name suggests, assigns value to the operand. They are also known as shortcut operators, as they have been used to allocate variable values. The operator allows assigning the value of the operand on the right side of the operator. For instance, a = 4 is a simple attribution operator that attributes the value 4, right to the left variable a. 

Note: Do not confuse in-place or shortcut operators. In Python, we have = = rational operators, which may look similar to including assignment operator.  

Note the difference: 

With the use of the assignment operator, the variable gets assigned with a value, 4. 

In a relational operator, the variable checks the condition and displays the output in the Boolean value. If the expression condition gets satisfied, the code output is True, else False. 

Arithmetic operators like addition, subtraction, multiplication, floor division, exponent (or power), and modulus are there by default in all the programming languages. In Python, all these arithmetic operators are binary, showing they are running on two controllers. Simply put, they run on two operators. 

Programmers apply these operators on numbers as well as on variables to perform corresponding operations. The regular primary concern level is given to binary arithmetic operations. Notice that certain non-numeric forms of these operations often occur. Besides the power user, just two components are available, one for multiple operators and one category for additive operators. 

Let’s understand binary arithmetic operators with the help of an example. Assigning a = 50, and b = 100, we get the following outputs. 

Relational operators in Python are also often called comparison operators. These should measure and test the relationship between the operands on both sides. A Boolean value occurs in the comparison performance. These operators are being used to discover the association among two operands in the program. They are useful for the comparison of the values. It responds either True or False, depending on the condition.  

Let us understand relational operators with the help of an example. Assigning a = 50, and b = 100, we get the following outputs. 

An array is a set of similar forms of components. Simply put, it stores many data of the same type collectively. They may be helpful if there is a need for exploitation for such data types. The sorting of items stored in the array can be, however, extensively restricted by the users.  

To create an array, we need to import an array module. 

Here is a code where we have created an array of type int. Notice the letter i is the type code. 

Output: 

Here is a code where we have created an array of type float. Notice the letter d is the type code. 

Output: 

Bitwise operators are operators in Python running at the binary level. That means these operators appear at the binary numbers or sections of an integer specifically. Much of this seems terrifying, but it is easy for bit operations. Compared with other operating systems, they are relatively fast since these procedures can be performed straightaway by the processor.  

Rather than words, bitwise operators are merely labelled with odd signs, making them look less wordy than you could see in Python. Bitwise operators include: 

When overloading operators, programmers are free to overload any arithmetic operators except = operator. The thumb rule says: Never try to overload = = operator, because it becomes strenuous, almost impossible to verify the test, whether the two objects are the same. Say you have an object x, which is from a custom class or is an integer, and you want to see if x is the number 500. If you set x = 500, then later test if x is 500, you will get False because of the way Python caches numbers.  

When there is a need to reverse the meaning of operand, we use the Boolean negation operator using the keyword not. This operator works by merely inverting the value of its operand. If the expression you have to write is True, placing the keyword ‘not’ before it will return False, and vice versa.

Let’s understand with the help of an example. 

Output: 

N.B: In the defined list named classroom, we had four students attending the class. When we checked whether “Bella” is present in the list or not, we got the output as Absent because she is present. Simply amazing how using the not keyword can reverse the entire meaning of the expression. 

One of the perks of using Python is to overload functions, besides overloading operators. Python allows to overload functions like long(), float(), abs(), and hex(). We may alter the importance of a Python operator inside the category by overloading the operator. Programmers can use these functions to convert a value of a user-defined type (object) to a value of another type. 

Program to overload hex() , oct(), and float() functions. 

Output: 

Conclusion: 

Coders can run without overloading operators as well. With operator and functional overloading, it is easy to write efficient codes in basis and built-in data-types. Perhaps you will see the real capabilities of operator overloading in scientific computing while computing the representation of mathematical objects with no hassle. Otherwise, it would make the computation complex, time-consuming, and demanding. 

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