Speeding Up Your Python Deployments: How UV Turbocharges CI/CD

In the world of CI/CD, every second saved can have a significant impact on your workflow. If you’re working with Python projects, you’ve probably noticed that installing dependencies with pip can be a major time sink. However, there’s a powerful solution that can drastically cut down on this time—UV.

UV is a drop-in replacement for pip that optimizes the installation process, making it significantly faster and more efficient. In this post, we’ll explore how UV works, how it can speed up your deployments, and the benefits it brings to your CI/CD pipeline.

Why Use UV?

UV wraps around pip and introduces several enhancements that are especially valuable in CI/CD environments. These include caching wheels, parallel installations, and more efficient management of virtual environments. Behind the scenes, UV harnesses some of the speed and safety advantages of Rust, a systems programming language known for its performance. This helps UV perform its tasks faster and more reliably.

Comparing Installations: Traditional Pip vs. UV

To understand the impact of UV, let’s compare two Dockerfile commands that install dependencies.

Traditional `pip` Installation

RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

This command is straightforward: pip installs all the dependencies listed in requirements.txt without using a cache and upgrades them if necessary. However, in our CI/CD pipeline, this step can take around 63 seconds.

Optimized Installation with UV

RUN uv venv && . .venv/bin/activate && uv pip install --system -r /code/requirements.txt

Here’s what’s happening with UV:

uv venv creates a virtual environment efficiently.
. .venv/bin/activate activates this environment.
uv pip install --system -r /code/requirements.txt uses UV’s optimized pip to install the dependencies.

With this setup, the installation time drops significantly to around 23 seconds. That’s a savings of 40 seconds per build—a huge improvement when you consider how frequently deployments occur. Over the course of multiple deploys, this time savings becomes even more impactful, directly accelerating our product’s development cycle and time-to-market.

How UV Enhances CI/CD

The performance gains with UV stem from a few key optimizations, with Rust playing a supporting role:

Efficient Caching: UV intelligently caches wheels and other artifacts, reducing the need to recompile packages that haven’t changed. This avoids redundant work and speeds up subsequent installs.
Parallel Installations: By leveraging parallelism, UV can install multiple packages simultaneously, making full use of available system resources and cutting down install times.
Optimized Environment Management: UV streamlines the creation and activation of virtual environments, making this process faster and more consistent across different builds.

These optimizations translate into faster, more reliable deployments, allowing your CI/CD pipeline to run more smoothly and efficiently. Rust contributes to these enhancements by providing a fast and safe foundation for UV’s operations, but it’s UV’s smart design that really makes the difference.

Conclusion: A Faster, More Reliable CI/CD Pipeline

Switching from pip to UV for dependency installation is a simple yet powerful optimization for your CI/CD pipeline. UV not only speeds up your deployments but also makes them more reliable and consistent. It’s like upgrading your guitar strings to a set that tunes faster, sounds better, and lasts longer.

In our own product’s CI/CD pipeline, we’ve seen deployment times shrink by 40 seconds per build—a substantial improvement that enhances our ability to deploy quickly and consistently. If you’re looking to shave time off your deploys and CI processes, give UV a try—you’ll likely notice a significant performance boost.

Speeding Up Your Python Deployments: How UV Turbocharges CI/CD