Switching from Rye to uv: A Faster Python Toolchain

December 15, 2024 5 min read

If you’ve been using Rye for your Python projects, you’ve already experienced the appeal of modern Python tooling—no more wrestling with virtual environments, struggling with dependency conflicts, or dealing with the limitations of traditional pip. But as the Python packaging ecosystem evolves, new players emerge, and one tool that’s been generating significant buzz lately is uv.

Developed by Astral (the same team behind Ruff), uv promises even faster performance and a more streamlined experience. Having made the switch myself on macOS, I want to share why uv might be your next Python tooling upgrade.

Why Move Beyond Rye?

First, let’s acknowledge what Rye gets right. It’s a fantastic tool that simplified Python project management with its built-in virtual environment management, dependency resolution, and seamless Python version handling. However, uv takes these concepts and pushes them further with:

  • Blazing-fast installation powered by Rust
  • Drop-in compatibility with existing pip and pip-tools workflows
  • Integrated project management that feels familiar but faster

The Installation Switch

On macOS, installing uv is straightforward:

curl -LsSf https://astral.sh/uv/install.sh | sh

This installs uv to ~/.cargo/bin/uv, so make sure that directory is in your PATH. Alternatively, if you’re using Homebrew:

brew install uv

Once installed, you can safely remove Rye if you wish, though I recommend testing the waters first.

Migrating Your Projects

Virtual Environments and Dependencies

Where Rye used rye init and rye sync, uv employs similar but distinct commands. Here’s how you’d migrate a typical project:

# Instead of rye init
uv init my-project
cd my-project

# Instead of rye add
uv add requests pandas numpy

# Instead of rye sync
uv sync

The uv sync command is particularly impressive—it handles both virtual environment creation and dependency installation in one go, with resolution speeds that feel almost instantaneous compared to traditional tools.

Python Version Management

Rye excelled at Python version management, and uv follows suit with a similar approach:

# Set Python version for current project
uv python pin 3.11

# Or use system Python
uv python pin system

Under the hood, uv downloads and manages Python versions much like Rye, storing them in ~/.uv/python/ on macOS.

Performance Gains You’ll Actually Notice

The most immediate benefit you’ll observe is speed. uv’s dependency resolver is written in Rust and leverages advanced caching strategies. Here’s a comparison from my workflow:

Before (Rye):

$ time rye sync
...
real    0m4.23s

After (uv):

$ time uv sync
...
real    0m1.07s

That’s nearly four times faster for a medium-sized project. For larger codebases with complex dependency trees, the difference becomes even more dramatic.

Advanced Workflow Enhancements

Scripts and Task Running

uv introduces uv run for executing commands in your project’s context:

# Instead of rye run
uv run python main.py
uv run pytest tests/

# You can even define scripts in pyproject.toml
uv run my-script

Dependency Management Nuances

uv handles dependency specification with precision. The uv add command includes smart default behaviours:

# Add with specific version
uv add "django>=4.2,<5.0"

# Add as development dependency
uv add --dev pytest black mypy

# Group dependencies (uv 0.2+)
uv add --group docs sphinx myst-parser

The group functionality is particularly useful for organizing dependencies beyond the basic dev/non-dev split.

Integration with Existing Tools

One of uv’s strengths is its compatibility layer. You can use uv alongside existing requirements files:

# Install from requirements.txt
uv pip install -r requirements.txt

# Or generate a lock file from them
uv lock requirements.txt

macOS-Specific Considerations

On macOS, you’ll want to ensure optimal performance:

  1. Storage Optimization: uv caches aggressively. If disk space is a concern, periodically run uv cache clean to prune unnecessary files.
  2. ARM64 Performance: If you’re on Apple Silicon, uv’s Rust foundation means you get native ARM64 binaries without Rosetta overhead.
  3. Shell Completions: For faster workflows, install shell completions:
uv generate-shell-completion zsh > ~/.zsh/completions/_uv

Potential Migration Hurdles

The transition isn’t entirely frictionless. Be aware of:

  • Different Lock File Format: uv uses its own uv.lock format instead of Rye’s requirements.lock
  • Tool Integration: Some editor integrations or CI scripts might need updating
  • Workflow Adjustments: Commands like rye fmt become uv run black or direct tool calls

The Verdict

After several months with uv across multiple projects, the performance benefits alone justify the switch. The 2-4x speedup in dependency resolution transforms the development experience, especially when working with large codebases or frequently updating dependencies.

uv feels like the natural evolution of what Rye started—taking the concept of an integrated Python toolchain and refining it with exceptional performance and thoughtful UX decisions.

The migration path is straightforward enough that I’ve moved all my active projects to uv without regret. The slight initial investment in learning new commands pays dividends in daily productivity gains.

Next Steps: Start with a non-critical project, get comfortable with the workflow, and gradually migrate your more important codebases. The uv documentation is excellent, and the tool’s design makes experimentation safe and reversible.

Welcome to the next generation of Python tooling.