Python Tutorial | Learn Python Programming Language
Python Tutorial - Python is one of the most popular programming languages today, known for its simplicity, extensive features and library support. Its clean and straightforward syntax makes it beginner-friendly, while its powerful libraries and frameworks makes it perfect for developers. Python is:
- A versatile, high-level programming language.
- Easy-to-learn syntax, perfect for beginners and experts.
- Known for its readability and extensive library support.
Why to Learn Python?
- Python requires fewer lines of code compared to other programming languages.
- Python is in high demand as it provides many job opportunities in Software Development, Data Science and AI/ML.
- Python provides popular Web Development, AI/ML, Data Science and Data Analysis Libraries like Django, Flask, Pandas, Tensorflow, Scikit-learn and many more.
- Python is an object oriented programming language which encapsulates code within object.
- Python is cross-platform which works on Windows, Mac and Linux without major changes.
- Python is used by big companies like Google, Netflix and NASA.
First Python Program
Here is a simple Python code, printing a string. We recommend we to edit the code and try to print our own name.
print("Hello World")
Output
Hello World
1. Python Basics
In this section, we’ll cover the basics of Python programming, including installing Python, writing first program, understanding comments and working with variables, keywords and operators. These are essential building blocks to get started with Python coding.
Before starting to learn python we need to install python on our system.
- Introduction
- Input and Output
- Variables
- Operators
- Quiz: Basics, I/O
- Keywords
- Data Types
- Quiz: Data Types, Numbers, Boolean
- Conditional Statements
- Python Loops
- Quiz : Control Flow, Loops
2. Python Functions
Python Functions are the backbone of organized and efficient code in Python. Here, in this section of Python 3 tutorial we'll explore their syntax, parameter handling, return values and variable scope. From basic concepts to advanced techniques like closures and decorators. Along the way, we'll also introduce versatile functions like range(), map, filter and lambda functions.
- def keyword
- Use of pass Statement in Function
- Return statement
- Global and Local Variables
- Recursion in Python
- *args and **kwargs in Function
- ‘Self’ as Default Argument
- First Class Function
- Lambda Function
- Map, Reduce and Filter Function
- Inner Function
- Decorators
- Quiz: Functions
3. Python Data Structures
Python offers versatile collections of data types, including lists, string, tuples, sets, dictionaries and arrays. In this section, we will learn about each data types in detail.
- Strings
- List
- Quiz: List, String
- Tuples
- Dictionary
- Quiz: Tuples, Dictionary
- Sets
- Arrays
- List Comprehension
- Quiz: Sets, Arrays, List Comprehension
Python's collections module offers essential data structures, including the following:
To learn data structure and algorithm with python in detail, you can refer to our DSA with Python Tutorial.
4. Python OOPs Concepts
In this section of Python OOPs, we'll explore the core principles of object-oriented programming (OOP) in Python. From encapsulation to inheritance, polymorphism, abstract classes and iterators, we'll cover the essential concepts that empower you to build modular, reusable and scalable code.
5. Python Exception Handling
In this section of Python Tutorial, we'll explore Python Exception Handling that how Python deals with unexpected errors, enabling us to write robust and fault-tolerant code. We'll cover file handling, including reading from and writing to files.
6. File Handling
In this section, we will cover file handling, including reading from and writing to files.
- File Handling
- Different File Modes
- Read Files
- Write/Create Files
- OS Module
- pathlib Module
- Directory Management
- Quiz: File Handling
7. Python Database Handling
In this section we will learn how to access and work with MySQL and MongoDB databases
8. Python Packages or Libraries
The biggest strength of Python is a huge collection of Python Packages standard libraries which can be used for the following:
9. Data Science with Python
1. Foundational Libraries: These are the core libraries that form the base for all data science workflows. Start here to build a strong foundation.
2. Advanced Visualization and Statistical Tools: Once you’re comfortable with basic data handling and visualization, move to creating cleaner visuals and performing statistical analysis.
3. Machine Learning Libraries: After mastering data manipulation and visualization, step into machine learning, starting with simpler models and moving to advanced ones.
4. Deep Learning Frameworks: If you’re interested in AI and deep learning, these libraries will allow you to build and train neural networks.
To learn more, you can refer to Python for Data Science.
10. Web Development with Python
1. Core Web Frameworks (Backend Development with Python): These are the primary tools for building Python-based web applications.
2. Database Integration: Learn how to connect Python web frameworks to databases for storing and retrieving data.
3. Front-End and Backend Integration: Learn how to connect Python backends with front-end technologies to create dynamic, full-stack web applications.
4. API Development: Learn to build APIs (Application Programming Interfaces) for connecting your backend with front-end apps or other services.
To learn more, you can refer to Python for Web Development.
Python Quizzes
Python quiz page covers topics including variables, data types and how to manage output effectively. You'll explre operators and control flow to structure our code, along with loops (for and while) for repetitive tasks. Additionally, you'll gain knowledge with Python data structures such as lists, tuples, dictionaries and sets.
Python Practice
The Python Coding Practice Problems page offers exercises for all skill levels, covering basics, loops, functions and OOP. You'll work with lists, strings, dictionaries, sets and advanced structures like heaps and deques. These problems help build a strong foundation and boost confidence in solving real-world coding challenges.
Features of Python
Python stands out because of its simplicity and versatility, making it a top choice for both beginners and professionals. Here are some key features or characteristics:
- Easy to Read and Write: Python’s syntax is clean and simple, making the code easy to understand and write. It is suitable for beginners.
- Interpreted Language: Python executes code line by line, which helps in easy debugging and testing during development.
- Object-Oriented and Functional: Python supports both object-oriented and functional programming, giving developers flexibility in how they structure their code.
- Dynamically Typed: You don’t need to specify data types when declaring variables; Python figures it out automatically.
- Extensive Libraries: Python has a rich collection of libraries for tasks like web development, data analysis, machine learning and more.
- Cross-Platform: Python can run on different operating systems like Windows, macOS and Linux without modification.
- Community Support: Python has a large, active community that continuously contributes resources, libraries and tools, making it easier to find help or solutions.
This Python tutorial is updated based on latest Python 3.13.1 version.
Applications of Python
- Web Development: Frameworks like Django and Flask can be used to create dynamic websites and web applications quickly and efficiently.
- Data Science & Analysis: Python is most preferred language for data analysis, visualization and handling large datasets. Because of extensive libraries like Pandas, NumPy and Matplotlib.
- Machine Learning & AI: Python is popular in AI and machine learning because of its powerful libraries like TensorFlow, Keras and Scikit-learn.
- Scripting & Automation: Python’s simplicity makes it ideal for writing scripts that automate tasks in different systems, from server management to file handling. Python is commonly used to automate repetitive tasks, making processes faster and more efficient.
- Web Scraping: Libraries like Beautiful Soup and Scrapy.
- Desktop App Development: Python can be used to build desktop applications using frameworks like Tkinter and PyQt. Python is also used for game development, with libraries like Pygame to create simple games.
Python vs. Other Programming Languages
Below is the comparison of Python with C, C++ and Java:
| Feature | Python | C | C++ | Java |
|---|---|---|---|---|
| Type | Interpreted | Compiled | Compiled | Compiled and Interpreted |
| Paradigm | Multi-paradigm (object-oriented, procedural, functional) | Procedural, structured | Multi-paradigm (procedural, object-oriented, generic) | Object-oriented, structured |
| Memory Management | Automatic | Manual | Manual | Automatic |
| Syntax | Simple | Complex | Complex | Complex |
| Use Cases | Web development, data analysis, machine learning | System programming, embedded systems, game development | System programming, game development, high-performance applications | Large-scale applications, enterprise software |
| Notable Frameworks/Libraries | Django, Flask | Standard Library | Standard Library, Boost | Spring, Hibernate |
| Community Support | Strong | Strong | Strong | Strong |
| Job Market | Abundant | Abundant | Abundant | Abundant |
List of Companies Using Python
These are some Popular companies that use Python in their workflow:
| Company | Description |
|---|---|
| Uses Python for various applications, including their search engine and machine learning projects. | |
| The backend of Instagram is built using Python, enabling it to handle millions of users efficiently. | |
| Spotify | Python is used for data analysis and backend services, helping improve user recommendations. |
| Dropbox | Python powers the desktop client of Dropbox, making it easy to sync files across devices. |
| Netflix | Python helps Netflix with data analysis and managing its content recommendation algorithms. |
| One of the largest online communities, Reddit, uses Python for its core functionalities. | |
| Uber | Uber uses Python for various features, including dynamic pricing and data analysis. |
| Python plays a key role in the backend of Pinterest, helping scale and manage user content. |
Career & Jobs in Python
Python offer diverse opportunities across industries, here we have listed all the best career opportunity that anyone can pursue after learning Python.
| Career | Average Salary (INR) Per Annum | Average Salary (USD) Per Annum |
|---|---|---|
| Python Developer | ₹500,000 – ₹1,200,000 | $60,000 – $110,000 |
| Data Scientist | ₹600,000 – ₹1,500,000 | $70,000 – $130,000 |
| Machine Learning Engineer | ₹700,000 – ₹1,800,000 | $75,000 – $140,000 |
| Full Stack Developer | ₹600,000 – ₹1,300,000 | $65,000 – $120,000 |
| DevOps Engineer | ₹800,000 – ₹2,000,000 | $80,000 – $140,000 |
| Automation Engineer | ₹500,000 – ₹1,200,000 | $55,000 – $100,000 |
| Data Analyst | ₹400,000 – ₹900,000 | $50,000 – $90,000 |
| Software Engineer | ₹500,000 – ₹1,500,000 | $65,000 – $120,000 |
| Backend Developer | ₹600,000 – ₹1,300,000 | $70,000 – $125,000 |
| AI Engineer | ₹900,000 – ₹2,500,000 | $90,000 – $160,000 |
Python Latest & Upcoming Features
Python 3.13 is the most recent stable release of the programming language, featuring a blend of updates to its syntax, implementation and standard library. Key enhancements include the introduction of a revamped interactive interpreter, experimental capabilities for operating in a free-threaded mode (as outlined in PEP 703) and the addition of a Just-In-Time (JIT) compiler (detailed in PEP 744).
The upcoming version of Python is Python 3.14 and it is expected to include the following notable updates: UTF-8 Mode Default (PEP 686), Shorthand Syntax for Keyword Arguments, Enhanced f-strings, JSON-based Simple API (PEP 691).
--> In this tutorial, we've provided the latest Python 3.13 version compiler where you can edit and compile your written code directly with just one click of the RUN Button. So test yourself with Python first exercises.
Python Programming Language - FAQs
What is Python?
Python is a high-level, general-purpose and very popular programming language which was created by Guido van Rassum and released in 1991. Python programming language (latest Python 3) is being used in web development and Machine Learning, Mathematics and System Scripting. Python language is being used by almost all tech-giant companies like – Google, Amazon, Facebook, Instagram, Dropbox, Uber… etc.
Is it easy to learn Python?
Yes, Python is considered one of the easiest programming languages to learn, especially for beginners.
Is Python enough to get a job?
Yes, knowing Python can be enough to get a job, especially in certain fields. Python is a versatile programming language widely used across various industries and it is highly valued for its simplicity, readability and powerful libraries. Doing specialization is always preferred, you can go for high demand domains like Data Science, AI or Web development.
What is the salary of Python Developer?
Due to high demand of domains like Data science and web dev, Python developer can get good package for India or countries like United States. The estimated salary for a Python Developer is ₹500,000 – ₹1,200,000 per year. For countries like USA, estimated pay for a Python Developer is $60,000 – $110,000 per Year.
What are job opportunity with Python?
After completing Python you and opt for various careers like:
- Python Developer
- Web Developer
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- AI Researcher
- Automation Engineer
- Software Engineer
- DevOps Engineer
What are the key advantages of learning Python?
There are multiple key advantages of learning Python programming language and they are:
- Easy to Learn: Simple syntax, perfect for beginners.
- Versatile: Used in web development, data science, AI and more.
- In-Demand: High job market demand with strong salaries.
- Rich Libraries: Extensive libraries for diverse tasks.
- Cross-Platform: Runs on all major operating systems.
