Why You Should Switch to uv for Python Projects

By Yoonsoo Park | February 14, 2026 | 4 minutes

If you are a Python developer, you are likely familiar with the fragmented ecosystem of tooling. You use `pip` for installing packages, `venv` or `virtualenv` for environments, `pyenv` for managing Python versions, and maybe `poetry` or `pip-tools` for dependency resolution. It’s a lot to manage. Enter **uv**. Created by Astral (the team behind Ruff), `uv` is an extremely fast Python package and project manager written in Rust. It’s designed to be a drop-in replacement for `pip` and `pip-tools`, but it has evolved into a full-fledged project manager that challenges `poetry` and `pdm`. In this post, I’ll explain why `uv` is a game-changer and why you should consider switching today. ## Why `uv` is a Game Changer ### 1. Blazing Speed Yup, it is freaking fast. In many benchmarks, `uv` is **10-100x faster** than pip-tools or poetry for resolution. ### 2. Unified Toolchain `uv` consolidates multiple tools into one. You no longer need separate tools for: - **Package Installation** (`pip`) - **Environment Management** (`venv`, `virtualenv`) - **Python Version Management** (`pyenv`) - **Dependency Locking** (`pip-compile`, `poetry lock`) - **Script Running** (`pipx`) You can do it all with a single binary. ### 3. Automatic Python Version Management This is my favorite feature. If a project requires Python 3.12 but you only have 3.11 installed, tools like `poetry` will complain. You’d have to go to `pyenv`, install 3.12, and then tell poetry to use it. With `uv`, you just define the required python version in your project. `uv` will **automatically download and install** the correct Python version for that project if it's missing, in an isolated manner (in `.venv`). No more global Python version conflicts!! ## Comparison: uv vs Poetry If you are currently using Poetry, you might wonder if it’s worth the switch. | Feature | Poetry | uv | | :--- | :--- | :--- | | **Language** | Python | Rust | | **Speed** | Slow (dependency resolution can take minutes) | Instant (sub-second resolution) | | **Python Management** | Relies on external tools (pyenv/system) | Built-in (installs Python automatically) | | **Standards** | Uses `pyproject.toml` (standard) | Uses `pyproject.toml` (standard) | | **Lock File** | `poetry.lock` | `uv.lock` (cross-platform) | The biggest pain point with Poetry has always been the dependency resolver speed. `uv` solves this completely. ## Migrating from `requirements.txt` If you have a legacy project using `requirements.txt`, migrating to `uv` is EZ. You don't have to rewrite everything from scratch. `uv` supports installing directly from requirements files, and it gives you two ways to do it: ### 1. Using `uv pip` (The "pip" way) If you just want to use `uv` as a faster `pip` without changing your workflow: ```bash uv pip install -r requirements.txt ``` This installs packages into your current environment exactly like `pip install -r requirements.txt`, just much faster. ### 2. Using `uv add` (The "Project" way) If you are initializing a new `uv` project (`uv init`) and want to import your dependencies: ```bash uv add -r requirements.txt ``` This reads your `requirements.txt` and adds the dependencies to your `pyproject.toml` file, effectively migrating your project management to `uv`. ## Common Commands Cheat Sheet Here are the commands you will use 90% of the time: * **Initialize a project**: ```bash uv init ``` * **Add a dependency**: ```bash uv add requests ``` * **Run a script**: ```bash uv run main.py ``` *Note: `uv run` will automatically create a virtual environment, install dependencies, and run the script in that isolated environment.* * **Sync environment**: ```bash uv sync ``` *Ensures the virtual environment matches the `uv.lock` file.* ## `uv add` vs `uv pip install` It’s important to understand the difference between these two commands, as `uv` supports both "project" and "script" workflows. * **`uv add <package>`**: - Used for managing a **project**. - Updates `pyproject.toml` and `uv.lock`. - Ensures reproducible builds for your application. - Similar to `poetry add`. * **`uv pip install <package>`**: - Used for low-level environment modification. - **Does NOT** update `pyproject.toml`. - Useful for CI/CD pipelines or **ad-hoc** environments where you just need packages installed quickly without tracking them. - Similar to `pip install`. ## Caveats While `uv` is fantastic, it is moving very fast. - It is relatively new, so edge cases with obscure build backends might still exist. - If you rely heavily on Poetry plugins, `uv` might not have an equivalent yet. ## Conclusion Give it a try on your next project. You won’t want to go back. At least I won't. Cheers!

If you are a Python developer, you are likely familiar with the fragmented ecosystem of tooling. You use pip for installing packages, venv or virtualenv for environments, pyenv for managing Python versions, and maybe poetry or pip-tools for dependency resolution. It’s a lot to manage.

Enter uv.

Created by Astral (the team behind Ruff), uv is an extremely fast Python package and project manager written in Rust. It’s designed to be a drop-in replacement for pip and pip-tools, but it has evolved into a full-fledged project manager that challenges poetry and pdm.

In this post, I’ll explain why uv is a game-changer and why you should consider switching today.

Why `uv` is a Game Changer

1. Blazing Speed

Yup, it is freaking fast. In many benchmarks, uv is 10-100x faster than pip-tools or poetry for resolution.

2. Unified Toolchain

uv consolidates multiple tools into one. You no longer need separate tools for:

Package Installation (pip)
Environment Management (venv, virtualenv)
Python Version Management (pyenv)
Dependency Locking (pip-compile, poetry lock)
Script Running (pipx)

You can do it all with a single binary.

3. Automatic Python Version Management

This is my favorite feature. If a project requires Python 3.12 but you only have 3.11 installed, tools like poetry will complain. You’d have to go to pyenv, install 3.12, and then tell poetry to use it.

With uv, you just define the required python version in your project. uv will automatically download and install the correct Python version for that project if it’s missing, in an isolated manner (in .venv). No more global Python version conflicts!!

Comparison: uv vs Poetry

If you are currently using Poetry, you might wonder if it’s worth the switch.

Feature	Poetry	uv
Language	Python	Rust
Speed	Slow (dependency resolution can take minutes)	Instant (sub-second resolution)
Python Management	Relies on external tools (pyenv/system)	Built-in (installs Python automatically)
Standards	Uses `pyproject.toml` (standard)	Uses `pyproject.toml` (standard)
Lock File	`poetry.lock`	`uv.lock` (cross-platform)

The biggest pain point with Poetry has always been the dependency resolver speed. uv solves this completely.

Migrating from `requirements.txt`

If you have a legacy project using requirements.txt, migrating to uv is EZ. You don’t have to rewrite everything from scratch.

uv supports installing directly from requirements files, and it gives you two ways to do it:

1. Using `uv pip` (The “pip” way)

If you just want to use uv as a faster pip without changing your workflow:

1
uv pip install -r requirements.txt

This installs packages into your current environment exactly like pip install -r requirements.txt, just much faster.

2. Using `uv add` (The “Project” way)

If you are initializing a new uv project (uv init) and want to import your dependencies:

1
uv add -r requirements.txt

This reads your requirements.txt and adds the dependencies to your pyproject.toml file, effectively migrating your project management to uv.

Common Commands Cheat Sheet

Here are the commands you will use 90% of the time:

Initialize a project:
1
uv init
Add a dependency:
1
uv add requests
Run a script:
1
uv run main.py
Note: uv run will automatically create a virtual environment, install dependencies, and run the script in that isolated environment.
Sync environment:
1
uv sync
Ensures the virtual environment matches the uv.lock file.

`uv add` vs `uv pip install`

It’s important to understand the difference between these two commands, as uv supports both “project” and “script” workflows.

uv add <package>:
- Used for managing a project.
- Updates pyproject.toml and uv.lock.
- Ensures reproducible builds for your application.
- Similar to poetry add.
uv pip install <package>:
- Used for low-level environment modification.
- Does NOT update pyproject.toml.
- Useful for CI/CD pipelines or ad-hoc environments where you just need packages installed quickly without tracking them.
- Similar to pip install.

Caveats

While uv is fantastic, it is moving very fast.

It is relatively new, so edge cases with obscure build backends might still exist.
If you rely heavily on Poetry plugins, uv might not have an equivalent yet.

Conclusion

Give it a try on your next project. You won’t want to go back. At least I won’t. Cheers!

Why uv is a Game Changer