What is Python?
Python is a modern programming language that fits all your purposes (general purpose), and is a high-level programming language. The Python programming language is interpreted and supports object-oriented programming. It was developed by Guido van Rossum.
If you are an aspiring data scientist, or Machine learning engineer, Web developer, Scripting and automation enthusiast, Python is the language for you! It is a highly versatile language capable of almost everything you would like to perform with it. It has a plethora of libraries and packages that aid you with your tasks related to data manipulation, statistical calculations, web development and so many more.
You can embark on your Python programming journey effortlessly with the help of our Python tutorial or you can also explore Scaler's Learn Python App. This app is an intuitive platform designed to make Python mastery a seamless experience via free downloadable content, present inside the app for offline consumption.
Why Learn Python Programming?
Before we get to why you should learn python programming, or why you should even read this python tutorial further, let's talk about Python - one of the most common programming languages.
The Need to Learn Python Programming
We figured out that the python programming language is definitely a very widely used versatile language, but what is the need?
The first and foremost big reason to learn python programming is the career opportunities that would open for you that come with huge salary prospects. Not to miss the high demand for python developers which is increasing dramatically by the year. 29.72 % of the total requirements are for python developers!
Take a sneak peek into the average salary of a python developer, which is around $92,000 / yr! The range of salaries is from $60k to $137k on average.
Another reason for learning Python is the vast community that has built packages and frameworks for everything from web development (Django, Flask) to Machine Learning (Tensorflow, PyTorch, OpenCV)
Surely that's enough motivation needed to learn the python programming language! Not convinced? Let's talk about the importance of Python.
Importance of Python Programming
To make a pithy statement, Python is very important and we saw some reasons above. Here are some more to convince you:
- A broad standard library: This is one of the Python's greatest strengths - the Python standard library is portable and is cross platform compatible on Windows, Mac, and UNIX.
- Interactive: Python is an interactive programming language, which means that you can sit at a python prompt, and interact with it's interpreter to write your programs directly.
- Beginner Friendly: Python is a beginner's language.
- Maintainable: Easy to maintain code
- Portable: Python has the capability of running on a wide variety of hardware platforms while having the same interface on all of them.
- Scalable: Writing code in python means a better code structure, and support for large programs as opposed to shell scripting
Python Programming Jobs
Python programming is widely used in a variety of industries due to its simplicity, versatility, and readability. Python's flexibility makes it an ideal choice for various tasks, such as data analysis, web development, artificial intelligence, and automation. Here are some of the most common Python programming jobs:
- Python Developer: Python developers use Python to design and develop software applications such as web applications, desktop applications, mobile applications, and games.
- Data Scientist: Data scientists use Python to analyze and extract insights from large data sets. They may work on projects such as customer segmentation, sentiment analysis, recommendation systems, and fraud detection.
- Machine Learning Engineer: Machine learning engineers use Python to develop algorithms and models that enable machines to learn from data and make predictions. They may work on projects such as image recognition, speech recognition, natural language processing, and autonomous vehicles.
- Automation Engineer: Automation engineers use Python to automate various processes and tasks, such as testing, deployment, and monitoring. They may work in industries such as software development, manufacturing, and healthcare.
- Web Developer: Web developers use Python to develop web applications such as e-commerce sites, social networks, and content management systems. They may work on projects such as designing web interfaces, testing and debugging code, and collaborating with other developers and stakeholders to deliver high-quality products.
Python Basic Syntax
Python syntax is the set of rules that define how Python code is written and structured. It includes statements, comments, variables, data types, operators, and control structures. Following these basic syntax rules is essential to write effective Python code. To Learn more refer here.
Python was created by Guido van Rossum in the late 1980s and released in 1991. Python 1.0 was released in 1994, Python 2.0 in 2000, and Python 3.0 in 2008. Python is widely used in web development, data science, and artificial intelligence. The language continues to evolve with new versions and features.
Career Opportunities in Python
- Data Scientist: Python is the go-to language for data scientists to analyze and interpret large datasets.
- Software Developer: Python can be used for web development, game development, and software development. It is also used in automation, testing, and scientific computing.
- DevOps Engineer: Python is often used for scripting and automation, making it a useful skill for DevOps engineers who manage infrastructure and deploy software.
- Cybersecurity Analyst: Python can be used for cybersecurity purposes such as penetration testing, network scanning, and analyzing malware.
- Technical Writer: Python's popularity and versatility create opportunities for technical writers with expertise in Python to create documentation, tutorials, and training materials for developers. These are just a few examples of the many career opportunities available for those with Python expertise. Python's popularity in various fields ensures that there are many career paths available, making it a valuable skill to learn.
How to Learn Python Programming?
You are surely now convinced that Python is an irreplaceable language, and are motivated to study it. The best way to start is by reading on! Go through all the modules in this Python course hub, and you'll be a pro at Python by the end of it.
About this Python Tutorial
This Python tutorial is divided into ten modules that cover the basics of Python programming, including installation on various operating systems and the differences between Python 2 and 3. The course covers essential constructs such as variables, keywords, literals, and control flow statements like if-else, while and for loops. It also teaches handling exceptions and file handling. Additionally, the course covers more advanced topics like object-oriented programming, data structures, functions, and advanced constructs such as modules, packages, collections, regular expressions, and datetime.
Applications of Python Programming
After you have mastered the programming language, here is the broad application set of the language:
- Data Science
- Creating Desktop applications
- Creating console based applications
- Creating Mobile apps
- Software Development
- Artificial Intelligence
- Web applications
- Enterprise Applications
- Machine learning
- Computer Vision
The above are just some of the plethora of applications of the Python programming language. Use the tutorial wisely and master the language!
Python installation involves downloading and installing the Python interpreter and associated tools on your computer. You can download Python from the official Python website and select the appropriate installer for your operating system. Once the installer is downloaded, you can run it to begin the installation process. The installer will guide you through the installation process and ask you to select the installation location and any additional components you want to install. After the installation is complete, you can run Python from the command line or an integrated development environment (IDE) to start writing and running Python code. To learn more -:
Python 2 Vs. Python 3
- Syntax: Python 2 and Python 3 have slightly different syntax. Python 3 requires parentheses around the print statement, while Python 2 does not.
- Unicode Support: Python 3 provides better support for Unicode, whereas Python 2 requires additional modules to support Unicode.
- Print Function: In Python 2, the print statement is used to print output, while in Python 3, the print function is used.
- Division: In Python 2, dividing two integers results in an integer, while in Python 3, dividing two integers results in a float.
- Library Support: Python 3 has a larger and more active community, and many libraries are now available only for Python 3.
- Backward Compatibility: Python 3 is not backward compatible with Python 2. This means that code written in Python 2 may need to be modified to work in Python 3. Refer here to learn more.
Variables in Python
In Python, variables are used to store data values. They are created when a value is assigned to them using the assignment operator "=" and can be of any data type. Python uses dynamic typing, which means that the type of a variable is determined at runtime based on the value assigned to it. Variables can be reassigned to new values at any time, and their values can be printed or used in operations within a Python program. Read here to know more
Data Types in Python
In Python, data types refer to the types of values that can be stored in variables. The common data types in Python include integer, float, boolean, string, list, tuple, and dictionary. Each data type has its own properties and methods, and Python automatically assigns the appropriate data type based on the value assigned to a variable. For example, if a variable is assigned a whole number value, it is automatically assigned an integer data type. Similarly, if a variable is assigned a value in quotes, it is assigned a string data type. Read here to know more
OOPs Concepts in Python
OOPs in Python is a programming paradigm based on the concept of objects. It provides the features of classes, objects, methods, and attributes. Encapsulation, inheritance, and polymorphism are some of the key features of OOP in Python that allow for more organized, reusable, and maintainable code. Encapsulation hides the implementation details of a class from other parts of the program, while inheritance and polymorphism help to reduce code duplication and make the code more flexible. OOP in Python is a powerful tool that can make programming easier and more efficient by promoting modularity, reusability, and maintainability of code.
Numbers in Python
Python provides three main types of numbers: integers, floating-point numbers, and complex numbers. Integers are whole numbers with no decimal points, while floating-point numbers include decimal points or scientific notation. Complex numbers consist of real and imaginary parts. Read here to know more
Python supports all basic arithmetic operations and includes many built-in mathematical functions in its math module. It also supports various number systems, such as binary, octal, and hexadecimal.
Python is a popular choice for scientific and numerical computing because of its powerful capabilities for handling large datasets, machine learning, and artificial intelligence.
User-defined functions are created using the "def" keyword in Python, allowing for the creation of reusable code. Functions can accept input parameters, return values, or modify global variables. Properly designed functions improve code organization and readability, reduce code duplication, and simplify debugging. Python also supports passing functions as arguments to other functions and returning functions, enabling the creation of more flexible and reusable code.
Exception handling in Python allows for handling runtime errors that may occur during program execution. The try-except block catches and handles exceptions that are created when an error occurs. Multiple except blocks can be used to handle different types of exceptions. The finally block executes regardless of whether an exception occurred or not and is typically used for cleanup tasks. The raise keyword allows for manually raising exceptions for indicating error conditions or triggering specific types of exceptions. Exception handling is crucial for writing reliable and error-free Python code, and it greatly enhances the overall usability and reliability of software applications. Read to know more
There are no strict prerequisites for learning Python, as it is a beginner-friendly language. However, having some basic programming knowledge, such as familiarity with programming concepts and logic, can be helpful.
It is also recommended to have some understanding of computer science fundamentals, including algorithms and data structures. Additionally, having knowledge of basic mathematics, such as algebra and calculus, can be useful for numerical and scientific computing applications.
- This tutorial will be helpful to computer science and IT students who are curious about learning basic to advanced concepts of Python.
- It will also act as a handbook for graduates and professionals (application programmers, database administrators, software engineers, product managers and end-users) who would like to delve deep into the domain.