Type Casting with Python

Type Casting with Python

Type Casting with Python

Built-in Types

Every programming language comes with built-in data types. These help us to handle different types of data including numerical data and textual data.

According to the official Python Standard Library documentation, Python has provided us many different Built-in Types. In this article we will only be discussing the Numeric Types “-int and float-” and the Text Sequence Type “-str-”.

Type Conversion

Type conversion -as the name implies- is converting data of one type to another. This either happens implicitly or can be done explicitly.
Implicit type conversion is done by Python to convert smaller types to larger types.

int < float < str

Explicit Type Conversion (Type Casting) is done by the developer to convert larger types to smaller types.

str > float > int

Why Type Conversion?

Let’s understand how each of these two works by creating a simple calculator program.

In order to read user input, Python uses input() function. The function returns the user input value as a str type value. Following example shows how this causes an issue when we want to add numbers.

number1 = input("Enter 1st number: ")
number2 = input("Enter 2nd number: ")

print(f"{number1} + {number2} = {number1 + number2}")

print(f"type of number1: {type(number1)}")
print(f"type of number2: {type(number2)}")

Explicit Type Conversion

This is where we have to explicitly convert type to fix this issue. Explicit type conversion is done to prevent run time errors (exceptions).

We can use the int() constructor to convert str values to int values. Modify your code as follows and run your code.

number1 = input("Enter 1st number: ")
number2 = input("Enter 2nd number: ")

number1 = int(number1)
number2 = int(number2)

print(f"{number1} + {number2} = {number1 + number2}")
print(f"type of number1: {type(number1)}")
print(f"type of number2: {type(number2)}")

You may reduce your keystrokes by using conversion in the same line with input function.

number1 = int(input("Enter 1st number: "))
number2 = int(input("Enter 2nd number: "))

Alternatively, you may choose to keep the original input as of str type and cast the operand values when you use them in a calculation. However, this might not be a good approach if you have to use input values in multiple calculations.

number1 = input("Enter 1st number: ")
number2 = input("Enter 2nd number: ")
		
print(f"{number1} + {number2} = {int(number1) + int(number2)}")
print(f"type of number1: {type(number1)}")
print(f"type of number2: {type(number2)}")

Note: if the user inputs fractional values, casting to int type throws a run time error (exception). We have to use float() constructor instead of int() to avoid this.

Implicit Type Conversion

Python will implicitly convert smaller data types to higher data types to prevent data loss.

Following code shows that Python implicitly converts division answer to a float value even though input values are of int type. This is done to prevent losing remainder value incase user inputs a dividend which is not divisible by the divisor without a remainder.

number1 = int(input("Enter 1st number: "))
number2 = int(input("Enter 2nd number: "))

answer = number1 / number2
		
print(f"{number1} / {number2} = {answer}")
print(f"type of number1: {type(number1)}")
print(f"type of number2: {type(number2)}")
print(f"type of answer: {type(answer)}")

Simple Calculator

Now that we know how to implement type casting, let’s implement out complete calculator program with casting input values to float type, so that we can input both integer and fractional values. Additionally, let’s use the round() function to round our answers to two decimal places.

number1 = float(input("Enter 1st number: "))
number2 = float(input("Enter 2nd number: "))

add = round(number1 + number2, 2)
subtract = round(number1 - number2, 2)
multiply = round(number1 * number2, 2)
divide = round(number1 / number2, 2)

print(f"{number1} + {number2} = {add}")
print(f"{number1} - {number2} = {subtract}")
print(f"{number1} * {number2} = {multiply}")
print(f"{number1} / {number2} = {divide}")

Comments

Post a Comment

Popular posts from this blog

OOP with Python - Part 2

OOP with Python - Part 2 OOP with Python - Part 2 We covered the basics of Object-Oriented Programming (OOP) , including Classes and Objects, Encapsulation, and Inheritance in OOP with Python - Part 1 . In this second part, we will discuss the remaining two key principles of OOP; Abstraction and Polymorphism . Abstraction Abstraction is the concept of hiding the complex implementation details of a system and exposing essential features of an object. This allows us to focus on what an object does but not how it is done. This can reduce programming complexity and enhance code maintainability. In Python, abstraction can be achieved using abstract classes and methods provided by the abc module. An abstract class is a class that cannot be instantiated and typically contains one or more abstract methods. An abstract method is a method that is declared but contains no implementation. Subclasses of the abstract class must provide implementations for all abstract m...
Read more

Data Structures - Part 2

Data Structures - Part 2 Data Structures (Abstract Data Types) - Part 2 (Linked List) Refer this article for Part 1 (Array) of the series. 2. Linked List A linked list is a linear data structure where elements are stored in nodes. Each node consists of two parts: data (which holds the value) and a reference (or pointer) to the next node in the sequence. In contrast to arrays, elements (nodes) in a linked list are not stored in contiguous memory locations but instead are connected via pointers. Unlike arrays, linked lists are dynamic and can grow or shrink in size as needed. They do not have a built-in length property, though such feature can be implemented in custom classes. To determine the number of elements in a linked list, we typically need to traverse the entire list and count the nodes. This structure which involves updating pointers, makes insertions and deletions faster since it avoids the need to shift elements, in contrast to arrays. However, lin...
Read more

OOP with Python - Part 1

OOP with Python - Part 1 OOP with Python - Part 1 OOP ( Object Oriented Programming ) is a programming paradigm (a design style or an approach with its related design principles and techniques) which considers objects as the primary building block of a software program. In our previous articles, we were following a procedural approach where we were writing our code in a sequential manner. As compared to the procedural approach, OOP provides benefits like modularity, ease of maintenance, flexibility, scalability and reusability which makes it ideal for large scale real world projects. Python, being a general purpose language, supports both procedural and OOP paradigms. So, in this article let’s talk about the basics of OOP and how to implement them in Python. Class & Object An object is a real world entity with properties (aka attributes or data or members) and behaviors (aka methods or functions). For instance, a cat is an object. It has a name, color ...
Read more