Nerdish.Org

🎯 Goal:

In this blog, you’ll build real Python classes to solve practical problems. Each one will stretch your understanding of:

• Class creation and methods
• Object interaction
• Inheritance
• Retail sales logic

If you’ve followed the previous posts, this is your moment to apply it all!

🛒 1. Build a Product Class

Every retail system starts with a product. Let’s model one!

Problem:
Create a class Product with the following:

• name, price, and stock as attributes
• A method sell(quantity) that reduces the stock
• A method get_info() that prints product name and remaining stock

Example:

p1 = Product("Ring", 1000, 10)
p1.sell(2)      # reduces stock to 8
p1.get_info()   # shows name + updated stock

💸 2. Add Discount Logic

Retail isn’t just about selling — it’s about pricing smartly.

Problem:
Add a method apply_discount(percent) to your Product class that updates the price after reducing it by the given percentage.

Update get_info() to also show the current price.

Example:

p1.apply_discount(10)  # price drops to 900
p1.get_info()          # shows updated price and stock

👥 3. Model an Employee Who Processes Sales

Let’s bring employees into the scene.

Problem:
Create a class Employee with:

• name and role
• A method process_sale(product, quantity)
  This method should call product.sell() and print a message showing who sold what.

Example:

e1 = Employee("Prince", "Sales Associate")
e1.process_sale(p1, 3)
# Prince sold 3 x Ring for $2700

📊 4. Track Each Sale as a Sale Object

We don’t just want to sell — we want to track each transaction.

Problem:
Create a Sale class that stores:

• The product, employee, and quantity
• Automatically calculates the total
• A summary() method that prints the full transaction

Example:

s1 = Sale(p1, e1, 2)
s1.summary()
# Prince sold 2 x Ring for $1800

🏪 5. Build a Store That Manages Inventory

Now let’s manage multiple products in a single place.

Problem:
Create a class Store with:

• A list of products
• A method add_product(product)
• A method list_inventory() that prints each product’s name and stock

Bonus: Add a method to find a product by name.

Example:

store = Store()
store.add_product(p1)
store.list_inventory()
# Ring - 5 in stock

✅ Summary

With these 5 problems, you’ve touched on:

• Object creation and method chaining
• Collaboration between classes
• Real-world use of OOP in retail
• The foundation for dashboards, APIs, and full apps

🎯 Goal:

By the end of this lesson, you’ll understand:

• What a class really is
• Why classes are needed for real-world applications
• When to use classes instead of plain functions and variables

🍪 1. What is a Class (Really)?

Think of a class as a blueprint or cookie cutter. It defines the structure and behavior of things you want to model — like a product, employee, or order in a retail store.

class Product:
    def __init__(self, name, price):
        self.name = name
        self.price = price

This is just the design. You still have to create actual products using it (called objects):

ring = Product("Diamond Ring", 2500)

Now you’ve made a real product — just like baking cookies from a mold.

🛠 2. The Problem Without Classes

Let’s say you’re selling a ring. Without using classes, here’s how you might track it:

product_name = "Diamond Ring"
product_price = 2500
product_stock = 10

def sell(quantity):
    global product_stock
    product_stock -= quantity

🧱 This works for one product. But what if you have 50?
You’d need:

• product_name1, product_name2, product_name3, …
• sell_product1(), sell_product2() … 😩

It becomes messy, repetitive, and hard to maintain.

✅ 3. Why Classes Are Better

Here’s how much cleaner and scalable it becomes:

class Product:
    def __init__(self, name, price, stock):
        self.name = name
        self.price = price
        self.stock = stock

    def sell(self, quantity):
        if quantity <= self.stock:
            self.stock -= quantity
            return f"Sold {quantity} x {self.name}"
        else:
            return f"Not enough stock for {self.name}"

Now you can do:

ring = Product("Diamond Ring", 2500, 10)
necklace = Product("Necklace", 1500, 5)
print(ring.sell(3))
print(necklace.sell(2))

🎉 No need for extra variables or duplicate logic. Every product has its own behavior and data.

🔁 4. When Should You Use Classes?

💡 5. OOP Powers You Unlock

Once you understand classes, you’ll soon be able to use:

• Inheritance (e.g. Manager inherits from Employee)
• Polymorphism (e.g. override behavior in different subclasses)
• Encapsulation (keep your code tidy and modular)

🧪 6. Practice Time

Try these in your blog_env:

• Create a Product class with name, price, and stock
• Add a method called discount() that reduces the price
• Create multiple product objects and print their updated prices

📘 Summary

• A class is a template that describes a type of object
• Objects created from classes are reusable and scalable
• OOP makes your code clean, efficient, and real-world ready
• It’s essential for any serious application like sales dashboards, inventory systems, or APIs

🎯 Goal:

By the end of this blog, you’ll be able to:

• Check and change your current working directory
• Save files to a custom folder like OneDrive
• Build platform-safe file paths (Windows or Mac)

📍 1. What is a Working Directory?

When you run a Python script or a notebook, Python has a “default folder” it operates in — this is called the working directory. Any file you read/write (like notes.txt) goes here unless you tell it otherwise.

Check it with:

import os
print(os.getcwd())

🧠 This will tell you where Python is currently reading or writing files from.

🔄 2. Changing the Directory

Let’s say you want to save your file inside a folder called PythonProjects inside your OneDrive.

🪟 On Windows:

import os

# Use raw string (r"...") to avoid errors with backslashes
onedrive_path = r"C:\Users\Prince\OneDrive\PythonProjects"
os.chdir(onedrive_path)
print("Now working in:", os.getcwd())

🍎 On Mac (if using OneDrive):

import os

onedrive_path = "/Users/princejohn/OneDrive/PythonProjects"
os.chdir(onedrive_path)
print("Now working in:", os.getcwd())

📄 3. Creating the Folder (If It Doesn’t Exist)

Just in case the folder doesn’t exist yet:

os.makedirs(onedrive_path, exist_ok=True)
os.chdir(onedrive_path)

🔐 exist_ok=True prevents Python from throwing an error if the folder is already there.

💾 4. Writing a File into OneDrive

Once your working directory is changed:

with open("notes.txt", "w") as file:
    file.write("Saved into OneDrive successfully!")

Now open your OneDrive and you’ll see notes.txt inside the PythonProjects folder.

🔧 5. Building Paths the Safe Way

Instead of manually typing slashes, use os.path.join() — it’s safer across Windows, Mac, and Linux.

filename = "notes.txt"
path = os.path.join(onedrive_path, filename)

with open(path, "w") as file:
    file.write("Cross-platform file writing!")

✅ Summary

• Use os.getcwd() to see where you’re working
• Use os.chdir() to move to folders like OneDrive
• Use os.makedirs() to create folders safely
• Use os.path.join() to write platform-friendly code

🎯 Goal:

By the end of this lesson, you’ll be able to:

• Read and write files in Python
• Handle errors using try-except
• Work with real data like CSV and JSON

📄 1. Reading and Writing Text Files

📝 Writing to a File

with open("notes.txt", "w") as file:
    file.write("This is your first file write in Python!\n")
    file.write("Welcome to the file world.")

"w" creates a new file or overwrites an existing one.

📖 Reading a File

with open("notes.txt", "r") as file:
    content = file.read()
    print(content)

🔁 Line-by-Line Reading

with open("notes.txt", "r") as file:
    for line in file:
        print(line.strip())

➕ Appending to a File

with open("notes.txt", "a") as file:
    file.write("\nAnother line added.")

🧾 2. Handling CSV Files

import csv

with open("data.csv", mode="w", newline="") as file:
    writer = csv.writer(file)
    writer.writerow(["Name", "Role"])
    writer.writerow(["Prince", "Analyst"])

Reading CSV:

with open("data.csv", "r") as file:
    reader = csv.reader(file)
    for row in reader:
        print(row)

🌐 3. JSON Basics (Web-Friendly Format)

import json

person = {"name": "Prince", "skills": ["Python", "SQL"]}
json_data = json.dumps(person)
print(json_data)  # convert to JSON string

# Save to file
with open("person.json", "w") as f:
    json.dump(person, f)

# Load from file
with open("person.json", "r") as f:
    loaded = json.load(f)
    print(loaded["name"])

⚠️ 4. Exception Handling

Errors happen — Python gives you a way to handle them gracefully.

Try-Except Block

try:
    result = 10 / 0
except ZeroDivisionError:
    print("Oops! Can't divide by zero.")

Catching Multiple Exceptions

try:
    x = int("abc")
except (ValueError, TypeError) as e:
    print(f"Error occurred: {e}")

Finally Block

try:
    f = open("test.txt", "r")
except FileNotFoundError:
    print("File not found!")
finally:
    print("Cleanup complete.")

✅ Practice Time

Try these in your blog_env:

• Write a list of your favorite books to a file
• Read from that file and print each book
• Create a CSV file with name, age, city
• Use try-except to catch file not found or zero division errors

📘 Summary

• You learned how to read/write files, handle CSV/JSON
• You handled exceptions cleanly with try-except
• You now have the tools to build real-world data scripts