Python Full Stack Web Developer Course

Common List Patterns in Web Development

Let's explore some typical patterns you'll encounter when working with Python lists in web development:

Processing Form Data

# Processing multiple checkbox selections from a form
selected_options = ["option1", "option3", "option5"]
all_options = ["option1", "option2", "option3", "option4", "option5"]

# Create a list of checkbox states (checked/unchecked)
checkbox_states = [opt in selected_options for opt in all_options]
print(checkbox_states)  # [True, False, True, False, True]

# Create a mapping of options to their selected state
option_map = {opt: opt in selected_options for opt in all_options}
print(option_map)  
# {'option1': True, 'option2': False, 'option3': True, 'option4': False, 'option5': True}

Working with JSON Data

import json

# Sample JSON data from an API response
json_data = '''
{
    "users": [
        {"id": 1, "username": "alice", "active": true, "role": "admin"},
        {"id": 2, "username": "bob", "active": false, "role": "user"},
        {"id": 3, "username": "charlie", "active": true, "role": "user"},
        {"id": 4, "username": "diana", "active": true, "role": "moderator"}
    ]
}
'''

# Parse JSON and extract user information
data = json.loads(json_data)
users = data["users"]

# Get all active usernames
active_users = [user["username"] for user in users if user["active"]]
print(active_users)  # ['alice', 'charlie', 'diana']

# Create a mapping of user IDs to usernames
user_lookup = {user["id"]: user["username"] for user in users}
print(user_lookup)  # {1: 'alice', 2: 'bob', 3: 'charlie', 4: 'diana'}

# Group users by role
users_by_role = {}
for user in users:
    role = user["role"]
    if role not in users_by_role:
        users_by_role[role] = []
    users_by_role[role].append(user["username"])
    
print(users_by_role)  
# {'admin': ['alice'], 'user': ['bob', 'charlie'], 'moderator': ['diana']}

Building HTML Elements

# Creating a navigation menu
menu_items = [
    {"text": "Home", "url": "/", "active": True},
    {"text": "Products", "url": "/products", "active": False},
    {"text": "Services", "url": "/services", "active": False},
    {"text": "About", "url": "/about", "active": False},
    {"text": "Contact", "url": "/contact", "active": False}
]

# Generate HTML for menu items
menu_html = [
    f"<li class='{item['active'] and 'active' or ''}'><a href='{item['url']}'>{item['text']}</a></li>"
    for item in menu_items
]

# Join the HTML items into a complete menu
nav_html = "<ul class='nav'>" + "".join(menu_html) + "</ul>"
print(nav_html)
# 
Home
Products
...

Database Query Processing

# Simulated database query results
query_results = [
    (1, "Product A", 29.99, "Electronics"),
    (2, "Product B", 49.99, "Home & Kitchen"),
    (3, "Product C", 15.50, "Electronics"),
    (4, "Product D", 99.99, "Electronics"),
    (5, "Product E", 35.25, "Clothing")
]

# Transform query results to dictionaries
products = [
    {
        "id": row[0],
        "name": row[1],
        "price": row[2],
        "category": row[3]
    }
    for row in query_results
]

# Filter for electronics products
electronics = [p for p in products if p["category"] == "Electronics"]
print(electronics)

# Calculate average price by category
categories = set(p["category"] for p in products)
avg_prices = {
    category: sum(p["price"] for p in products if p["category"] == category) / 
              sum(1 for p in products if p["category"] == category)
    for category in categories
}
print(avg_prices)
# {'Electronics': 48.49, 'Home & Kitchen': 49.99, 'Clothing': 35.25}