Using Poetry Dependency Groups to Separate Dev, Test, and Production Dependencies
Learn how to define and use Poetry dependency groups to keep development, testing, and production packages isolated and reproducible.
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Developer tools · #poetry
pythonSolving the 'Works on My Machine' Problem with Poetry Lockfiles
Stop fighting 'dependency drift.' Learn how Poetry uses pyproject.toml and deterministic lockfiles to ensure your Python environments are identical across all stages.
Poetry Lockfiles: The Secret to Reproducible Python Builds
Poetry’s lockfile guarantees reproducible builds by capturing the exact dependency graph. This blog walks through how it works, shows a concrete example, discusses trade‑offs, and gives a checklist for teams to adopt deterministic dependency resolution.
Choosing Between Poetry Dependency Groups, Extras, and Markers for Environment-Specific Dependencies
Decide where each non-core dependency lives in a Poetry project: groups for internal tooling, extras for user-facing optional features, markers for platform conditions — with a concrete pyproject.toml layout, install commands per environment, and validation steps.
Does Poetry's default virtualenv location leave production containers without installed dependencies?
A Python service managed with Poetry (assuming the 1.8–2.x configuration model) needs a production image whose runtime interpreter actually contains the packages that poetry install resolves. On a developer workstation this is rarely visible, because the virtualenv is created and activated in place. By documented default, however, Poetry creates virtualenvs
dockerDoes a failed Poetry self update replace the previous binary atomically?
Goal I need to know whether a failed Poetry self-upgrade leaves the previous executable available or replaces it in place, and whether that depends on the installation method. Poetry updates itself through `poetry self update`, but it is unclear whether the update is atomic across the standalone installer, pipx, pip, or system package manager. A partial upda
Poetry network timeout coverage across dependency resolution and installation
Poetry documents config.virtualenvs.create-timeout for virtual environment creation, but that limit does not cover package downloads or dependency resolution. The resolver has no cooperative cancellation API, so SIGINT during resolution can abort ungracefully while leaving poetry.lock unchanged and the virtual environment partially populated. Because [[tool.
Can Poetry Auto‑Resolve Conflicting Dependencies When Adding a New Package?
Goal When a project already has a poetry.lock that pins specific dependency versions, a user may want to add a new package that introduces a version constraint that conflicts with one of those pinned dependencies. The intended outcome is to have Poetry reconcile the new requirement and update the lock file accordingly. Constraints and Uncertainty Poetry’s cu
poetry.lock strictness vs. pyproject.toml flexibility for dev-dependencies
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 d