Data Gibberish

Data Gibberish

Share this post

Data Gibberish
Data Gibberish
Meet uv: The Blazing-Fast Python Package Manager Data Engineers Love
Copy link
Facebook
Email
Notes
More

Meet uv: The Blazing-Fast Python Package Manager Data Engineers Love

Say goodbye to sluggish dependency management. uv is a modern, high-performance package manager designed for Python power users. Here’s everything you need to know to get started.

Yordan Ivanov's avatar
Yordan Ivanov
Mar 19, 2025
∙ Paid
9

Share this post

Data Gibberish
Data Gibberish
Meet uv: The Blazing-Fast Python Package Manager Data Engineers Love
Copy link
Facebook
Email
Notes
More
2
Share
A comic book-style illustration of a data engineer in an office. The engineer is wearing a yellow safety helmet and dark sunglasses, sitting at a desk with a computer. He is confidently typing code with two python snakes wrapped gently around his arms, their heads looking curious. The scene is colorful and dynamic, with vibrant tones, bold dark lines, and a whimsical atmosphere. Office elements like monitors, coffee cups, and sticky notes are in the background. The character looks focused and cool, embodying a mix of tech and adventure.

Upgrade Your Experience


Greetings, Data Engineer,

You and I know Python is the backbone of data engineering. But there’s one thing that slows us all down—installing and managing Python packages.

If you’ve ever waited minutes for a pip install pandas or wrestled with broken environments, you know what I mean. Managing them shouldn’t take longer than running the actual jobs.

Today, I will introduce you to uv. It’s Built for speed. Designed to solve problems you deal with every day.

Loading...

🚀 What is uv and Why Should You Care?

uv is a next-generation Python package manager that focuses on speed and reliability.

🌐 Explain uv

At its core, uv handles:

  • Installing Python packages.

  • Managing virtual environments.

  • Resolving dependency conflicts.

  • Locking versions for reproducibility.

All in one tool. And fast. Like really fast.

Here’s what installing pandas looks like with uv:

uv add polars

Done in seconds. No waiting. No spinning wheels.

🏎️ Why it matters for data engineers

As a data engineer, you install big packages—polars, numpy, pyarrow, dbt, airflow. These are not lightweight.

Imagine this:

  • You clone a data pipeline repo.

  • You need to install everything from pyproject.toml.

  • With uv, this happens in a blink.

uv sync

Suddenly you’re ready to work. Not tomorrow. Today.

🔄 How uv is different from pip/poetry

Let’s get real. pip is slow.

  • pip resolves dependencies in a way that can take a lot of time, especially with conflicting packages.

  • pipenv tries to fix this but often feels bloated and confusing.

  • poetry is great for locking, but still not as fast as uv.

uv does it all:

  • Installs and manages packages.

  • Creates virtual environments.

  • Locks your dependencies.

  • And it’s blazing fast because it’s written in Rust, not Python.

You get a single tool, not three different ones.

🧑‍💻 Who is building uv

uv comes from the creators of Ruff, the lightning-fast Python linter that everyone in the Python world is talking about. If you trust Ruff, you’ll love uv.

The team behind uv knows what Python developers and data engineers need: speed, simplicity, and reliability. uv is built to give you all three.


🔑 Key Concepts to Understand

Before you and I jump into using uv, let’s unpack a few ideas. These are the things that make uv powerful—and knowing them helps you avoid frustration later.

This post is for paid subscribers

Already a paid subscriber? Sign in
© 2025 Yordan Ivanov
Privacy ∙ Terms ∙ Collection notice
Start writingGet the app
Substack is the home for great culture

Share

Copy link
Facebook
Email
Notes
More