Managing Dependency Intent with Poetry Groups and Locked Builds
Stop shipping dev tools to production. Learn how to use Poetry dependency groups and locked builds to separate runtime intent and ensure reproducible CI environments.
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Stop shipping dev tools to production. Learn how to use Poetry dependency groups and locked builds to separate runtime intent and ensure reproducible CI environments.
Poetry's dependency groups let you keep one lock file while installing only the packages a given environment needs. Learn how --only, --with, and --without work across Poetry 1.x and 2.x.
Choose Poetry dependency groups for internal tooling and extras for consumer-facing optional features. Compare the trade-offs, see a concrete pyproject.toml layout, and validate the result.
When pip cannot find a version to install, the resolver has rejected every candidate on the index. This guide walks through ordered checks to find whether the cause is a name typo, interpreter mismatch, platform tag gap, or index misconfiguration.
Learn how PyPI’s Trusted Publishing feature lets you automate package uploads from CI pipelines using short‑lived OIDC tokens, eliminating the need for long‑term API keys. The blog walks through a GitHub Actions setup, explains the token flow, and highlights trade‑offs.
Poetry's lockfile pins exact package versions and hashes for reproducible installs. Learn when to use poetry lock --no-update and how to verify your dependency tree.
Poetry's lock file pins exact versions and hashes while dependency groups separate runtime from dev tooling. Here's how to use both for reproducible installs and slim production images.
Learn how to securely publish Python packages to PyPI using pyproject.toml, the build module, and Twine with API tokens to avoid common distribution errors.
Use Poetry dependency groups to keep pytest, black, and mypy out of production while one committed lock file keeps every environment reproducible. Covers group syntax, install flags, and verification.