Why Python Developers Rarely Worry About Garbage Collection (And How It Works)

In computer science, GC is an automatic memory management mechanism that releases memory when it is no longer needed.

Python programmers rarely need to worry about memory management because CPython implements its own garbage collector.

Python's GC is based on reference counting: each object has a count that increments when a reference is created and decrements when a reference is destroyed; when the count reaches zero, the memory is freed.

Reference counting cannot reclaim cyclic references, so Python also uses a mark-and-sweep algorithm and generational collection to handle cycles.

Mark-and-sweep works by copying the reference counts to a temporary structure, modifying that copy, and then clearing cycles without affecting the actual object lifetimes.

Generational collection groups objects into three generations (0, 1, 2). New objects start in generation 0; objects that survive a collection are promoted to older generations. Thresholds (default (700, 10, 10)) control when each generation is collected.

Usually the default thresholds need not be changed, but they can be inspected with gc.get_threshold() and adjusted if necessary.

In performance‑critical code that creates many temporary objects, developers may temporarily disable GC with gc.disable() or set the threshold to zero using gc.set_threshold(0), then re‑enable it after the critical section.

import gc
gc.get_threshold()

gc.disable()
# do something

gc.enable()