Immutable Data Structures (Data That Cannot Be Modified After Creation)

Immutability means values cannot change after creation—Python strings, tuples, frozensets. Benefits: safe hashing, simpler reasoning, easy aliasing without spooky action at a distance.

Why this shows up in the real world

Configuration objects loaded once and shared read-only across threads. Blockchain anchors immutable history.

Core idea (explained for students)

Return new objects instead of mutating shared state. Use frozenset as dict keys when you need set-shaped keys.

Try this in Python

def add_point(pts: frozenset[tuple[int, int]], p: tuple[int, int]) -> frozenset[tuple[int, int]]:
    return pts | {p}


base = frozenset({(0, 0)})
print(add_point(base, (1, 1)))

Common mistakes

• Tuple with mutable list inside—tuple is immutable but contents still change.
• Accidentally rebinding a name thinking you copied data.

Key takeaways

• Prefer immutables for hashable keys and concurrent read paths.
• When you need updates, pair immutable snapshots with cheap diffs.