Mastering Intermediate Python: A Practical Guide

Take your Python skills to the next level with this structured, mobile-friendly tutorial for intermediate learners. Perfect for coders who’ve mastered the basics and are ready to build real-world skills.

1. Lambda Functions

square = lambda x: x * x
print(square(5))  # Output: 25

2. Map, Filter, Reduce

from functools import reduce

nums = [1, 2, 3, 4]
squared = list(map(lambda x: x**2, nums))
even = list(filter(lambda x: x % 2 == 0, nums))
product = reduce(lambda x, y: x * y, nums)

3. OOP: Classes and Inheritance

class Car:
    def __init__(self, brand):
        self.brand = brand

    def drive(self):
        print(f"{self.brand} is driving.")

class ElectricCar(Car):
    def drive(self):
        print(f"{self.brand} is silently driving.")

4. Error Handling

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

5. File Handling

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

6. Modules and Packages

# greetings.py
def hello(name):
    return f"Hello, {name}!"

# main.py
import greetings
print(greetings.hello("Alice"))

7. Decorators

def my_decorator(func):
    def wrapper():
        print("Before function call")
        func()
        print("After function call")
    return wrapper

@my_decorator
def greet():
    print("Hello!")

greet()

8. Generators

def countdown(n):
    while n > 0:
        yield n
        n -= 1

for num in countdown(5):
    print(num)

9. List and Dict Comprehensions

squares = [x**2 for x in range(10)]
squared_dict = {x: x**2 for x in [1, 2, 3]}

10. Virtual Environments

python -m venv myenv
source myenv/bin/activate  # macOS/Linux
myenv\Scripts\activate     # Windows

11. Pythonic Tips

# Swapping
x, y = 1, 2
x, y = y, x

# Truthy checks
if []:  # False
    print("Empty list")

12. Project Ideas

• To-Do CLI App
• Web Scraper with BeautifulSoup
• Weather Dashboard using APIs
• Password Manager
• Email Automation Bot

Conclusion

Congratulations! You now have the tools to build more robust, scalable Python applications. Keep practicing, and explore advanced topics like web development, data science, or automation.