Question
poetry.lock strictness vs. pyproject.toml flexibility for dev-dependencies
Nia Nea
0 reputation · 17 Nov 2024, 20:45 UTC
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0 reputation · 17 Nov 2024, 20:45 UTC
When managing a project with Poetry (v1.x+), there is a fundamental tension between ensuring absolute reproducibility in production and maintaining agility during the development phase. The deterministic resolver ensures that poetry install adheres strictly to the poetry.lock file, which prevents version drift across environments.
However, in collaborative development settings, strict adherence to the lock file can hinder the adoption of critical security patches or minor updates for development-only tools unless a full poetry update is performed, which may inadvertently shift other stable dependencies.
The goal is to determine the most stable strategy for updating specific development dependencies without compromising the integrity of the production dependency graph.
poetry update <package> to surgically modify the lock file for specific dev-tools?poetry install would otherwise prevent?35275 reputation · 18 Nov 2024, 07:32 UTC
Yes, developers can rely on poetry update <package> to surgically modify the lockfile for a specific dev‑tool. The command rewrites only the entry for that package and its direct dependencies, leaving the rest of the graph untouched. It does not trigger a full re‑resolution, so other dependencies stay at the versions recorded in poetry.lock.
However, if the goal is to keep dev‑dependencies flexible while preserving a strict production graph, the recommended pattern is:
python
poetry[tool.poetry.group.dev.dependencies].
poetry lock --no-dev so only production packages are recorded.
poetry install --with dev (or simply poetry install without --no-dev) to pull the latest compatible versions of the dev group. This resolves against the production lockfile but can update individually when poetry update dev is run.This keeps the production install deterministic while allowing dev‑tools to stay up‑to‑date without affecting the locked graph.
poetry update <package> can still be safeThe resolver re‑evaluates only the target package and its direct dependencies. It will not pull in newer versions of unrelated packages unless the target’s constraints allow it. Therefore, the risk of implicit shifts is low, but it is still wise to run poetry check and poetry show --tree after the update to confirm no surprises.
In those cases, keep the dev‑tool locked via the lockfile and use poetry update only for the whole graph.
Use comments to ask for clarification. Post a solution as an answer.
6,680 reputation · 17 Nov 2024, 21:12 UTC
While poetry update <package> is effective for targeted updates, it is important to clarify how the resolver handles transitive dependencies. When you update a specific dev-tool, Poetry doesn't just update that package; it may also update any of its dependencies to the latest versions allowed by the constraints in pyproject.toml.
If a dev-tool shares a transitive dependency with a production package, a surgical update could potentially shift the version of that shared dependency in the poetry.lock file. To verify that a dev-update hasn't inadvertently altered production pins, you can use the following workflow (assuming Poetry v1.x+):
poetry update <package>.git diff poetry.lock to inspect exactly which versions changed.This manual diff is the most reliable way to ensure that "surgical" updates remain isolated from the production graph.