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Refactoring

As explained in Learn AI-Assisted Python Programming, Second Edition

Code refactoring is the restructuring of existing code to improve its readability or maintainability without changing its intended behavior.

Refactoring improves code design, readability, or organization without changing its intended behavior. It often replaces a large task with smaller, clearer functions. section 11.6 section 11.8

Useful refactoring moves include:

  • Break a process into smaller functions, such as verifying an order, calculating totals, applying discounts, and generating an invoice. section 7.8
  • Extract repeated subtasks, such as returning nonempty words from a string, into reusable helper functions. section 11.6
  • Move changeable decisions, such as feature weights, to a higher-level function where they are easier to find and modify. section 11.6
def process_orders(orders):
    total_price = 0
    for order in orders:
        price = order['price']
        quantity = order['quantity']
        total_price += price * quantity
    tax = total_price * 0.08
    total_price_with_tax = total_price + tax
    report = f"Total price: ${total_price:.2f}\n"
    report += f"Tax: ${tax:.2f}\n"
    if total_price_with_tax > 100:
        discount = total_price_with_tax * 0.1
        total_price_with_tax -= discount
        report += f"Discount: ${discount:.2f}\n"
    report += f"Total price with tax: ${total_price_with_tax:.2f}\n"
    print(report)

a = {'price': 20, 'quantity': 5}
lst = [a]
process_orders(lst)

Use the order-processing example to identify separate calculation and reporting responsibilities while preserving the original output. section 7.8

How Learn AI-Assisted Python Programming, Second Edition covers it

How deep it goes
Explains decomposition and reorganization through examples, but stops short of detailed implementation internals.
Examples
Uses order processing, word extraction, signature calculation, and configurable feature weights.
What you can do after
Apply it by splitting functions, extracting repeated tasks, relocating decisions, and checking that behavior remains unchanged.
How it connects
Connects top-down design with functions, code repetition, and debugging.

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This explainer was generated by Manning's knowledge graph from the text of Learn AI-Assisted Python Programming, Second Edition. The section links point to the parts of the book it draws on.