前言 / Introduction

Why I Switched to uv Instead of Anaconda

Recently, I discovered uv — a lightning-fast Python package and environment manager built in Rust. After trying it out in a few projects, I realized: Anaconda is not useful to me anymore. Here’s why I made the switch and how it improved my Python workflow.

最近我發現了uv，一個由Rust編寫的輕量化Python 套件與環境管理器。嘗試在我的幾個小專案使用後，竟發現：Anaconda 不會再是我的首選。 所以這篇文章想和大家聊聊，我為什麼選擇轉換，以及uv帶來哪些實際改善。

The Problem with Anaconda (for Me)

  1. Anaconda’s installation is heavy - even Miniconda is too bulky
  2. Package installation with pip install is painfully slow
  3. Unable to change Python versions in existing virtual environments
  4. Virtual environments can’t be easily shared across different workspaces

基於上面幾個痛點，總是讓我對Anaconda恨得牙癢癢的，但又離不開它，直到我遇見了uv。

Enter uv

uv 是由Astral建立的現代Python環境管理器，透過輕快且乾淨的特色，讓許多人留下美好的印象。下面列了幾點我喜歡的特色:

  • Lightning-fast environment & dependency setup

    It installs everything in seconds — no exaggeration.

  • Drop-in replacement for pip & venv

    I can keep my workflows, just faster.

  • Perfect for testing environments

    Ideal for my QA work, especially when setting up test dependencies quickly.

How I Migrated

轉換非常簡易 (陣痛期短)，就下面簡單幾個步驟:

  1. Created a pyproject.toml (or used one from Poetry/pip tools)
  2. Ran uv venv to create the environment
  3. Installed dependencies via uv pip install
  4. Done!

That’s it — no base environment, no conda init, no channel headaches.

Final Thoughts

不是說Anaconda不好用，它還是有許多使用情境，並且我相信多數人第一次接觸也是Anaconda (新人教練 東巴)，但考慮到快速開發，以及加速docker image的建構，uv真的是值得考慮的。

如果你也曾被 Anaconda 的體積與安裝速度卡住，不妨試試看 uv。對我來說，它是 Python 開發環境的「輕盈革命」。

PS: 中間也有使用pyenv + poetry，但就是沒有很方便，所以始終沒有去進行替換。

Reference