Python Tutorial for Beginners and Advanced Programmers

Introduction to Python Programming

Python is a high-level, interpreted programming language. It’s widely used in web development, automation, data science, and artificial intelligence. Due to its clean syntax and readability, Python is perfect for both beginners and professionals.

Why Learn Python?

Python is versatile and easy to learn. It works across platforms and supports integration with other languages. It has a large community, countless libraries, and frameworks like Django, Flask, NumPy, and Pandas.

Installing Python

Download the latest version of Python from python.org. Follow the installation wizard. Don’t forget to check “Add Python to PATH” during installation.

Basic Python Syntax

• Python uses indentation to define blocks.
• Statements end with a newline, not semicolons.
• Use # for single-line comments and triple quotes for multi-line comments.

# This is a comment
print("Hello, Python!")

Python Variables and Data Types

Python supports dynamic typing. Variables do not need explicit declaration. Common data types include:

• Integers: int
• Floating-point: float
• Strings: str
• Boolean: bool
• Lists, Tuples, Sets, Dictionaries

name = "John"
age = 30
is_active = True

Python Operators

Python supports:

• Arithmetic: +, -, *, /, %
• Comparison: ==, !=, >, <
• Logical: and, or, not
• Assignment: =, +=, -=

Control Flow in Python

Use if, elif, and else for decisions:

if age > 18:
    print("Adult")
else:
    print("Minor")

Use for and while loops for iteration:

for i in range(5):
    print(i)

Python Functions

Functions allow reusability. Define functions using def:

def greet(name):
    return "Hello " + name

print(greet("Alice"))

Python Lists and Tuples

Lists are mutable; tuples are immutable.

my_list = [1, 2, 3]
my_tuple = (4, 5, 6)

Use slicing, indexing, and built-in methods like append(), pop(), sort().

Dictionaries in Python

Dictionaries store key-value pairs.

user = {"name": "Alice", "age": 25}
print(user["name"])

Methods include keys(), values(), items().

Object-Oriented Programming in Python

Python supports classes and objects:

class Dog:
    def __init__(self, name):
        self.name = name

    def bark(self):
        return self.name + " says Woof!"

d = Dog("Buddy")
print(d.bark())

File Handling in Python

Use built-in functions to read/write files:

with open("file.txt", "w") as f:
    f.write("Hello, file!")

Modes: 'r', 'w', 'a', 'b'

Exception Handling in Python

Handle errors using try, except, and finally:

try:
    result = 10 / 0
except ZeroDivisionError:
    print("Cannot divide by zero.")
finally:
    print("Done.")

Working with Modules

Use built-in/custom modules. Import with import:

import math
print(math.sqrt(16))

Use pip to install external packages.

Python for Data Science

Popular libraries:

• NumPy: Numeric computations
• Pandas: Data manipulation
• Matplotlib: Data visualization
• Scikit-learn: Machine learning

Python Web Development

Use frameworks like:

• Django: Full-stack
• Flask: Lightweight

Both support REST APIs and templating.

Automation with Python

Automate tasks using:

• os for system commands
• shutil for file operations
• selenium for browser automation
• schedule for task scheduling

Popular Python Projects for Practice

• Calculator
• To-Do List App
• Weather App using API
• Web scraper using BeautifulSoup
• Chatbot using NLP

Conclusion

Python is powerful and easy to learn. With practice, you can build web apps, automate tasks, analyze data, or dive into AI.

• Python is versatile and beginner-friendly.
• It supports multiple paradigms including OOP and functional programming.
• Libraries and frameworks make it ideal for web, data science, and automation.
• Regular practice and project-building are key to mastering Python.

Start coding today and unlock endless possibilities in the Python ecosystem.