Modern Python Project Management: Poetry vs. uv

Modern Python Project Management: Poetry vs. uv

Managing Python dependencies has evolved significantly over the years. In 2025, two tools stand out for modern workflows: Poetry and uv. This article compares both, explores their pros and cons, and outlines best practices for managing Python projects efficiently.

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What is Poetry?

Poetry is an all-in-one tool for dependency management and packaging. It uses pyproject.toml to define and manage your project’s dependencies, metadata, and build instructions. It simplifies creating and publishing Python packages.

# Create a new project with Poetry
poetry new my_project
cd my_project

# Add a dependency
poetry add requests

# Install dependencies
poetry install

What is uv?

uv is a next-generation Python package manager built by the creators of Ruff. It focuses on speed, determinism, and compatibility with pyproject.toml. While it doesn’t yet offer full package publishing, it’s blazing fast for installs and dependency resolution.

# Create a virtual environment with uv
uv venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows

# Install dependencies from pyproject.toml
uv pip install -r requirements.txt

# or use Poetry lockfile directly
uv pip install -r poetry.lock

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Poetry vs. uv: Feature Comparison

Feature	uv	poetry
Dependency resolution	Ultra-fast	Slower
Lockfile support	Yes (poetry.lock)	Yes
Virtualenv management	Yes (uv venv)	Yes (automatic)
Packaging and publishing	No (planned)	Yes
CLI simplicity	Minimal	Rich and descriptive
Editable installs	Yes (--editable)	Yes
Cross-platform support	Yes	Yes

Pros and Cons

Poetry

Pros:

• Full packaging and publishing support
• Clear CLI for managing dependencies
• Automatically handles virtual environments

Cons:

• Slower installs and resolution
• Can be heavyweight
• Complex projects may hit edge cases

uv

Pros:

• Incredibly fast installs and resolution
• Compatible with existing pyproject.toml and poetry.lock
• Lightweight and simple to use

Cons:

• No publishing features yet
• Not ideal as a standalone tool for new projects
• Requires a separate tool (like Poetry or PDM) to define dependencies

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Best Practices for Dependency Management (2025 Edition)

1. Use pyproject.toml as the single source of truth.
   • Avoid requirements.txt if possible; use it only for CI builds.
2. Use Poetry for dependency definition and publishing.
   • Define your dependencies and build instructions using poetry add and poetry build.
3. Use uv for fast installations and CI.
   • Replace poetry install with uv pip install -r poetry.lock for blazing-fast installs.
4. Always commit your lockfile.
   • Ensures reproducibility across environments.
5. Use .venv for local environments.

   poetry config virtualenvs.in-project true
   uv venv
   

6. Don’t mix tools.
   • Avoid combining pip, poetry, conda, or manual editing.
7. Use uv to validate install speed.

   uv pip install -r poetry.lock  # Fast and deterministic
   

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Conclusion

Both Poetry and uv bring great advantages to modern Python workflows. Use Poetry when you need full project management, packaging, and publishing. Use uv when speed and minimalism are essential—especially in CI/CD.

Best of both worlds? Use Poetry to define, uv to install.

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Happy coding in Python 3.12 and beyond!