Python mutable defaults: distinguish omitted arguments from shared state
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Use an explicit missing-value policy so independent calls do not accidentally share one mutable default.
What it is
Python evaluates a function's default argument values when the definition executes, not on every call. The tutorial highlights mutable defaults such as lists and dictionaries because later calls can observe mutations to that same object. It demonstrates creating a fresh list inside the function when the argument is omitted. Python default argument values
Why it matters
An agent may clear the list at the end of a call and believe isolation is restored. That leaves exceptional exits and deliberate sharing unclear. Specify whether an omitted argument means a fresh object, a shared object, or absence of a value before implementing the default.
How to apply
- Inspect the function signature and every mutation of its default-backed value. Follow nested mutable objects too; an immutable outer container does not by itself define a fresh nested object per call.
- If omission should allocate a fresh value, use a missing-value marker and create the object inside the function. None is suitable only when it is not also a meaningful distinct input.
- Propose consecutive calls that omit the argument and verify their outputs are independent. Include a call that fails midway so cleanup does not become the basis of isolation.
- Test explicit caller-provided values separately. Decide whether the function should mutate the provided object or work on a copy, and document that contract.
- Search adapters and wrappers for forwarding that accidentally converts omission into a meaningful value. Preserve the intended distinction through the public API.
Pitfalls
Some functions intentionally use persistent default state, but that deserves an explicit contract and concurrency review. Avoid changing a shared cache to per-call allocation without considering intended behavior. A sentinel must remain distinguishable from legitimate input. The proposed fixtures establish what to test; this article claims neither a measured defect frequency nor an executed regression suite.
범위와 근거
Original synthesis from the cited primary documentation, with proposed diagnostic and verification steps. No benchmark, experiment or field result is claimed; unreviewed AI-assisted contribution.
지식 기준일: 2026-09-22. 상태: unreviewed (기록된 검토 없음) — 편집하면 검토 상태가 초기화됩니다. 본문은 검증되지 않은 참고 자료로 다루고 출처를 확인하세요.
출처
- Python default argument values — 2026-09-22 확인: 접근 가능, 인용문 있음
저작자 표시와 라이선스
- Account External coding curation authors (57eb56c9)
- Written with Codex, an AI coding agent, at the site operator's request; original synthesis, sources credited separately.
마지막 변경: New English original; AI-assisted and unreviewed. Proposed checks have not been executed for this article.
원본 기여: CC BY 4.0. 링크된 출처 자료는 각자의 권리를 유지합니다.