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Dictionary Dispatching

When we have a long list of if/elif or match-case blocks that simply return different values based on a single key, we can use a dictionary as a lookup table (or dispatch table). This maps keys directly to values or functions, making our code cleaner and easier to maintain.

Match-case Vs. Dictionary Lookup​

Compare these two approaches for handling discount codes. Using .get() provides a safe default if the key is missing.

The Verbose Way (match-case)​

user = {"coupon": "SAVE50"}

match user["coupon"]:
    case "SAVE20":
        discount = 0.20
    case "SAVE50":
        discount = 0.50
    case _:
        discount = 0.0

print(f"Discount: {discount}")

Output:

Discount: 0.5

The Pythonic Way (Dictionary Dispatch)​

user = {"coupon": "SAVE50"}

# Create a mapping once
coupon_map = {"SAVE20": 0.20, "SAVE50": 0.50}

# Perform the lookup in one line with a default of 0.0
discount = coupon_map.get(user["coupon"], 0.0)

print(f"Discount: {discount}")

Output:

Discount: 0.5

Practical Example: Bulk Processing​

Dictionary dispatching is extremely powerful when used inside loops to apply rules to a collection of data. Adding a new rule only requires adding one entry to the dictionary.

rules = {"gold": 0.20, "silver": 0.10, "bronze": 0.05}

customers = [
    {"name": "Alice", "tier": "gold", "total": 100},
    {"name": "Bob", "tier": "bronze", "total": 100}
]

for customer in customers:
    # Look up the discount rate based on tier
    rate = rules.get(customer["tier"], 0.0)
    final_price = customer["total"] * (1 - rate)

    print(f"{customer['name']} pays: ${final_price:.2f}")

Output:

Alice pays: $80.00
Bob pays: $95.00

Why It Scales Better​

If we need to add more rules, we just update the rules dictionary. The actual logic inside the for loop doesn't have to change at all, separating our data from our logic.