8 posts tagged with "uv"

Every time you train a model, you change something: the number of trees, a setting, the data. A week later nobody remembers which change gave the best result. MLflow remembers it for you. In this first part you install MLflow, start your own tracking server, and log your first machine learning experiment from Python.

The MLflow tracking server is the place your training runs go: a small web server that stores every run and shows them in the MLflow UI. You don't need a cloud account or a database server to run one; MLflow 3.18 brings everything, including a SQLite database. This guide starts a server on your own computer, explains every line it prints, checks that it's ready, and stops it safely.

MLflow installs like any Python package, but it brings a lot with it: a web server, a database layer and the most common data science libraries. Installing it into a uv project keeps all of that inside the project and records the exact versions. This guide installs MLflow 3.18.0, checks it, and explains which of MLflow's three packages you need.

Hard-coding a port, a database address or a password into your code means editing the code for every computer it runs on. pydantic-settings reads those values from environment variables and a .env file instead, checks them, and gives your code typed values. This guide explains the syntax first, then builds the settings of a small demo app and shows, with real output, which source wins and what happens when a value is wrong.

Before you follow a guide, report a bug or upgrade, you need to know exactly which version of a package your project runs. In a uv project the answer is in the project's own environment, not in your computer's Python. This guide gives the syntax of four ways to read it first, then uses each one on a small hello-world project, with real output from uv 0.13.8.

You added a package with uv, ran your script with python3, and got ModuleNotFoundError. The package is installed, just not in the Python you started. uv run runs everything inside the project's own environment, and brings that environment up to date first. This guide explains the command's syntax first, then runs a small script, a project command and a tool in a hello-world project, with real output from uv 0.13.8.

uv add installs a package into your project and records it, all in one step. It updates pyproject.toml, writes the exact versions to uv.lock, and installs everything into the project's own environment. This guide explains the command's syntax first, then adds a package and two development tools to a small hello-world project, with real output from uv 0.13.8.

uv init turns a folder into a complete Python project in about a second: a pyproject.toml, a pinned Python version, a source folder, a .gitignore and a Git repository. This guide explains the command's syntax first, then creates a small hello-world project and walks through every file uv writes, with real output from uv 0.13.8.