The Speed Trap: Performance Isn’t Everything #
Yes, UV is faster than Poetry – sometimes dramatically so. But here’s the thing: Poetry’s performance is already adequate for the vast majority of Python projects. Unless you’re managing massive monorepos with hundreds of dependencies, the difference between a 30 second and 5 second dependency installation is rarely the bottleneck in your development workflow. For me stability and reliability is far more important, that is why I don’t like the motto of go fast and break everything.
Then again why do you have hundreds of dependencies in your mono repos ?, you need vet all of those dependencies and it makes your software vulnerable to supply chain attacks.
Funding model #
Poetry is backed by a stable opensource community with predictable governance. Astral the company behind UV is owned and developed by a VC backed fund. Sooner or later, they may expect a return on this investment and try to monetize it. Maybe somebody may fork it or build a better package manager on this experience.
Maturity Matters #
Poetry has been battletested in production environments since 2018, with over 7 years of active development and millions of successful deployments. I have been using it in Linux since 2022 and then Mac in 2023 when I migrated from a mix of venv, pipx and I have made close to a hundred projects using it. The tool has evolved through realworld challenges, edge cases, and enterprise requirements that only come with time.
One of the only gripes I had with Poetry is that it was very painful to setup inside windows and VScode atleast when I did it in for the first time in 2023, It is super easy to setup inside Linux and Mac. I hope it got better but then again I am moving all my development to Linux, maybe it really does not matter.
Poetry’s dependency resolver is conservative. It takes time to explore the entire solution space, but this thoroughness prevents dependency conflicts that could break your application in production. When it fails at some point, I can destroy the env, started over again. Additionally, Poetry generates universal lock files that work across all platforms when I switch between Linux and Windows. UV creates platform specific lockfiles, adding complexity to multiplatform development and deployment scenarios.
UV’s resolver prioritizes speed, which can miss edge cases in complex dependency graphs. While this works fine, I still like the thoroughness of Poetry. UV, despite its impressive Rust powered performance, is less than 2 years old. Early adopters report frequent API changes and breaking updates that require constant configuration adjustments. For me, this instability translates to CI/CD pipeline failures, constantly changing APIs, Integration issues with existing toolchains and workflows.
Practical Recommendation: Sticking with Poetry #
The promise of faster dependency resolution isn’t worth the risks, costs, and complexity of migrating to an immature tool. Maybe I can revisit in 2026 or 2027. I feel it will inspire a new set of package managers that will be much better and I can move to that.
A quote which is with me for a very long time: Your development workflow should be boring and reliable, not exciting and unpredictable. Poetry delivers exactly that – which is why it remains the smart choice for Python package management in 2025.