Mutable defaults & pure updates

Debug a value that survives between calls

Lesson 19 of 20 · 13 min · Module 6: Reliable inputs & practical reports

Default argument expressions are evaluated when the function is defined. A mutable default can therefore outlive one call and surprise the next caller.

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Explain when defaults are evaluated
Test repeated calls and input ownership

The idea

Use None as the default sentinel, and create a fresh list inside the function. A new result also protects an explicitly supplied history from unexpected edits.

def append_badly(value, history=[]):
    history.append(value)
    return history

# The same default list can accumulate across calls.

01Reproduce the smallest sequence

Call the starter once, then again without passing history. The second result reveals data that a single-call test could miss.

02Separate default creation from a call

The default list belongs to the function definition. Using None lets the body create a fresh list for the current call.

03Protect explicit arguments too

Changing the default alone does not prevent mutation of a list the caller passes. Return a new list to satisfy that part of the contract.

Your turn

Repair remember_topic(topic, history=None). Return a new list containing the old history followed by topic. Calls without a history must be independent, and a supplied list must remain unchanged.

What the checks look for

Independent default calls contain only their own topic
Extends an explicit history without editing it
Returns a separate list for explicit empty input

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Take this with you

Repeated-call tests uncover state that a single successful example cannot reveal.

Go a little further

Add a clear_history helper that returns a new empty list without altering an older reference.