Mise vs uv: Choosing the Right Python Package and Version Manager

Python's ecosystem splits package management and version management across different tools. While pip and venv remain standard for package handling, developers often add pyenv for version switching. The uv project attempts to unify these workflows through a single fast tool, while Mise takes a different approach by managing multiple languages alongside Python.

This comparison explores how each tool handles Python development to help you choose the one that matches your workflow.

What is uv?

uv rewrites Python's package and version management toolchain in Rust. Created by the team behind Ruff, uv combines the functionality of pip, pip-tools, pipx, pyenv, and virtualenv into a single command-line interface.

The tool installs packages and manages Python versions without requiring separate installations of pip or pyenv. This consolidation reduces the number of tools you need to learn and maintain while delivering faster execution times through compiled code.

uv focuses exclusively on Python. If your projects use Node.js, Ruby, or other languages alongside Python, you'll need additional version managers for those ecosystems, each with its own commands and configuration format.

What is Mise?

Mise (formerly rtx) manages multiple programming languages through one interface. Also built in Rust, Mise handles Python alongside Node.js, Ruby, Go, and dozens of other languages while adding environment variable management and task execution.

The tool reads configuration from various existing version files including .python-version from pyenv and .tool-versions from asdf. This compatibility lets you adopt Mise without converting existing projects or forcing your team to switch simultaneously.

Mise extends beyond version switching by managing project-specific environment variables and running tasks. This means fewer separate tools competing for shell integration and a more consistent experience across different project types.

Quick Comparison

Installation and setup

uv provides a standalone installer:

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

You can also install through pip, pipx, Homebrew, or other package managers. uv doesn't require shell integration, so you can start using it immediately after installation without modifying your shell configuration.

Mise installation works similarly:

curl https://mise.run | sh

After installing, add shell activation to your configuration file:

echo 'eval "$(mise activate bash)"' >> ~/.bashrc

This activation step enables automatic version switching when you navigate between projects. Without it, you'll need to manually activate versions.

Managing Python versions

uv treats Python version management as part of its core functionality:

# List available Python versions
uv python list

# Install a Python version
uv python install 3.12.0

# Pin project to a version
uv python pin 3.12

When you run uv commands in a project directory, the tool automatically uses the pinned Python version. Creating virtual environments with uv venv uses the pinned version by default.

Mise handles Python versions with the same commands it uses for other languages:

# List available Python versions
mise ls-remote python

# Install a Python version
mise install python@3.12.0

# Set global version
mise use --global python@3.12

# Set project version
mise use python@3.12

The mise use command creates a .mise.toml file in your project directory. Mise automatically switches to this Python version whenever you enter the directory. This works without additional commands or plugins.

Package management approaches

uv replaces pip entirely. Installing packages uses uv's own resolver and caching system:

# Initialize a project
uv init myproject
cd myproject

# Add packages
uv add requests pandas

# Install dependencies
uv sync

# Run commands in project environment
uv run python script.py

The tool maintains a uv.lock file that records exact package versions for reproducible installations. This lockfile format differs from pip's requirements.txt, though uv can still read and generate requirements files for compatibility.

Mise takes a different approach. Rather than replacing pip, Mise ensures the correct Python version is active and lets you use standard Python package tools:

# With Python version set by Mise
pip install requests pandas

# Or use poetry
poetry add requests pandas

# Or use pipenv
pipenv install requests pandas

This means Mise works with your existing package management workflow. If you've standardized on poetry or pipenv, you can continue using those tools while Mise handles version switching.

Project-specific configurations

uv stores configuration in pyproject.toml:

[project]
name = "myproject"
version = "0.1.0"
requires-python = ">=3.12"
dependencies = [
    "requests>=2.31.0",
    "pandas>=2.0.0",
]

Running uv sync reads this file and creates a virtual environment with the specified dependencies. The approach integrates well with modern Python packaging standards.

Mise uses .mise.toml for version configuration:

[tools]
python = "3.12.0"

The file supports multiple Python versions when needed:

[tools]
python = ["3.11.0", "3.12.0"]

Mise also reads .python-version files from pyenv, so projects already using pyenv work without changes. Team members can use either tool with the same project.

Virtual environment handling

uv creates and manages virtual environments automatically:

# Create a new virtual environment
uv venv

# Create with specific Python version
uv venv --python 3.11

# Commands run in environment automatically
uv run pytest

The uv run command activates the project's virtual environment and executes commands within it. This removes the need to manually activate environments before running scripts or tests.

Mise doesn't create or manage virtual environments directly. You use Python's standard venv module or tools like virtualenv:

# Create virtual environment with correct Python version
python -m venv .venv

# Activate as usual
source .venv/bin/activate

Because Mise sets the correct Python version automatically, the venv command uses that version without additional configuration. This approach gives you full control over virtual environment creation while ensuring version consistency.

Dependency resolution

uv includes a dependency resolver written in Rust. The resolver handles version conflicts and determines which package versions to install:

# Add a package with version constraints
uv add "django>=4.2,<5.0"

# Update all packages
uv lock --upgrade

The resolver runs significantly faster than pip's resolver, particularly for large dependency trees. The uv.lock file records the exact versions selected, enabling reproducible installations across different machines.

Mise doesn't resolve dependencies. When you install packages with pip, poetry, or another tool, that tool's resolver determines versions. Mise's role stops at ensuring the correct Python version runs when you execute these commands.

Beyond Python

uv exclusively manages Python. Projects combining Python with Node.js for frontend tooling, Ruby for deployment scripts, or other languages require separate version managers for each language.

This means installing and configuring: - nvm or volta for Node.js - rbenv or rvm for Ruby - goenv for Go - Multiple shell integrations

Mise manages all these languages with consistent commands:

mise install node@22.0.0
mise install ruby@3.3.0
mise install go@1.22.0

A single configuration file specifies all project tools:

[tools]
python = "3.12.0"
node = "22.0.0"
ruby = "3.3.0"

This unified approach particularly benefits full-stack projects that mix languages. Rather than remembering different commands for each version manager, you use the same interface everywhere.

Environment variable management

uv doesn't handle environment variables. Python projects typically use dotenv files loaded by libraries like python-dotenv, or tools like direnv for shell-level variable management.

Mise integrates environment variables directly into project configuration:

[tools]
python = "3.12.0"

[env]
DATABASE_URL = "postgresql://localhost/mydb"
REDIS_URL = "redis://localhost:6379"
DEBUG = "true"

These variables become available when you enter the project directory and disappear when you leave. The scoping prevents accidental use of one project's credentials in another without requiring separate tools.

Task execution

uv lacks task running functionality. Python projects typically define tasks in pyproject.toml using tools like invoke, make, or task runners built into frameworks like Django.

Mise includes task execution:

[tasks.test]
run = "pytest tests/"
description = "Run test suite"

[tasks.lint]
run = ["ruff check .", "mypy ."]
description = "Run linters"

[tasks.dev]
run = "python manage.py runserver"
description = "Start development server"

Running mise run test executes the task with all configured environment variables and tool versions active. This ensures consistent execution across team members without documenting setup steps separately.

Compatibility and migration

uv can read existing requirements.txt files and pyproject.toml configurations:

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

# Compile requirements to lock file
uv pip compile requirements.in -o requirements.txt

However, adopting uv fully means switching your workflow to uv add, uv sync, and uv.lock files. This transition requires buy-in from your entire team and may break existing CI/CD pipelines that expect traditional pip commands.

Mise maintains compatibility with existing version files: - .python-version from pyenv - .tool-versions from asdf - Language-specific version files

This compatibility means you can start using Mise immediately without converting projects. Team members using pyenv see the same Python versions you do, even though you're using different tools.

Final thoughts

This article explains how to choose between uv and Mise.

If your work is mostly in Python, uv is the better fit. It speeds up package installs and replaces multiple tools with a single interface for versions, packages, and virtual environments.

On the other hand, if you often switch between different languages, Mise makes more sense. It provides one consistent interface for Python, Node.js, Ruby, and more, while also handling version switching and environment variables.

In some cases, you don’t have to pick just one. You can let Mise manage versions across languages and use uv for Python’s package and environment management, combining

Got an article suggestion? Let us know

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.