This Python tutorial is perfect for beginners and experienced programmers alike. It covers all aspects of Python programming, from basics to advanced topics like web scraping and Django, with easy-to-understand examples.
What is Python?
Python is a popular, high-level programming language used in web development, machine learning, and various other cutting-edge technologies. It is favored by tech giants like Google, Amazon, and Facebook.
Getting Started with Python Programming
You can run Python programs in two ways: by writing a program in a file and running it, or by executing code line by line. We provide a Python 3 compiler where you can edit and compile code with just one click.
Setting up Python:
Learning Python Basics:
Welcome to the Python tutorial! Here we'll teach you the basics you need to get started with Python programming. From syntax and keywords to comments, variables, and indentation, we'll cover the core concepts behind Python development.
- Python basics
- Syntax and keywords
- Comments
- Variables
- Data types
- Indentation
Handling Input/Output in Python:
This segment delves into the fundamental aspects of Python input/output processing that are essential to user experience and efficient data processing. From mastering the versatile print() function to learning advanced formatting techniques and how to efficiently receive user input, this section will help you harness the power of Python to efficiently flow transparent data. Learn the skills needed to process.
- Python print() function
- f-string in Python
- Print without newline in Python
- Python | end parameter in print()
- Python | sep parameter in print()
- Python | Output Formatting
- Taking Input in Python
- Taking Multiple Inputs from users in Python
Python Data Types:
Python provides the ability to manipulate and manage data precisely and flexibly. Additionally, we'll dive into the dynamic world of data transformation using conversions, then explore the generic collections provided by Python, including lists, tuples, sets, dictionaries, and arrays.
After completing this section, you will not only understand the essence of Python data types, but you will be able to use them skillfully to confidently solve a wide range of programming problems.
- Strings
- Numbers
- Booleans
- Lists
- Tuples
- Sets
- Dictionaries
- Arrays
- Type casting
Python Operators:
It covers everything from performing basic arithmetic operations to evaluating complex logical expressions. We'll take a closer look at comparison operators for making conditional decisions, and then look at bitwise operators for low-level manipulation of binary data. It also describes complex assignment operators for efficiently assigning and updating variables. Finally, we demystify membership and identity operators, such as in and is, so you can validate collection membership and confidently compare object identifiers.
- Arithmetic operators
- Comparison operators
- Logical operators
- Bitwise operators
- Assignment operators
- Membership and identity operators
Python Conditional Statements:
These instructions are essential to programming and enable dynamic decision making and code branching. In this section of the Python tutorial, we'll take a look at conditional logic in Python, from basic if...else statements to nested conditionals to short ternary operators. In addition, we will submit a powerful declaration in a new game in Python 3.10. Finally, you can learn these concepts so that you can create a clear and effective code that reacts rationally to various scenarios. Let’s dive in and unlock the potential of Python’s conditional statements.
- if...else statements
- Nested if statements
- Ternary condition
- Match case statement (Python 3.10)
Python Loops:
We'll look at Python looping constructs such as for and while loops, and basic loop control statements such as Break, Continue, and Pass. Additionally, it reveals the concise elegance of understanding lists and dictionaries for efficient data manipulation. Mastering these looping techniques will optimize your code to improve readability and performance.
- for loop
- while loop
- Loop control statements (break, continue, pass)
- List and dictionary comprehensions
Python Functions:
Functions are the basis of organized and efficient Python code. Here we'll look at its syntax, parameter handling, return values, and variable scope. From basic concepts to advanced techniques such as closures and decorators. Along the way, we'll also introduce general-purpose functions such as range() and powerful tools such as *args and **kwargs for flexible parameter handling. We'll also dive deeper into functional programming using maps, filters, and lambda functions.
- Python Function syntax
- Arguments and Return Values in Python Function
- Python Function Global and Local Scope Variables
- Use of pass Statement in Function
- Return statemen in Python Function
- Python range() function
- *args and **kwargs in Python Function
- Python closures
- Python ‘Self’ as Default Argument
- Decorators in Python
- Python closures
- Map Function
- Filter Function
- Reduce Function
- Lambda Function
Python OOPs Concepts:
This segment covers the basics of object-oriented programming (OOP) in Python. From encapsulation to inheritance to polymorphism to abstract classes and iterators, we cover fundamental concepts that enable you to write code that is modular, reusable, and scalable.
- Classes and objects
- Polymorphism
- Inheritance
- Abstract classes
- Encapsulation
- Iterators
Python Exception Handling:
This section of the Python tutorial shows you how Python handles unexpected errors so you can write reliable, fault-tolerant code. Before we get into exception handling using Try and Except blocks, we'll look at file handling, including reading and writing files. You will also learn about user-defined exceptions and Python's built-in exception types.
- Python File Handling
- Python Read Files
- Python Write/Create Files
- Exception handling
- User defined Exception
- Built-in Exception
- Try and Except in Python
Python Packages or Libraries:
Python's greatest strength lies in its huge collection of standard libraries that can be used for the following purposes:
- Built-in modules
- Data structures and algorithms libraries
- Machine learning libraries
- GUI libraries
- Web scraping packages
- Game development packages
- Web frameworks like Django and Flask
- Image processing libraries like OpenCV and Pillow
Python Collections:
Let's take a look at the main data structures provided by Python's collections module. We'll cover everything from counting hits with Counter to efficiently manipulating queues with Deque. Mastering these collections will simplify your data management tasks in Python.
- Counters
- Heapq
- Deque
- OrderedDict
- Defaultdict
Applications of Python:
- Web development
- Data science and machine learning
- Artificial intelligence and natural language processing
- Game development
- Desktop applications
- Scripting and automation
- Web scraping and crawling
- Education and research