Tools in Data Science

Python tools: uv#

uv is a fast Python package and project manager that’s becoming the standard for running Python scripts. It replaces tools like pip, conda, pipx, poetry, pyenv, twine, and virtualenv into one, enabling:

Python Version Management: uv installs and manages multiple Python versions, allowing developers to specify and switch between versions seamlessly.
Virtual Environment Handling: It automates the creation and management of virtual environments, ensuring isolated and consistent development spaces for different projects.
Dependency Management: With support for the pyproject.toml format, uv enables precise specification of project dependencies. It maintains a universal lockfile, uv.lock, to ensure reproducible installations across different systems.
Project Execution: The uv run command allows for the execution of scripts and applications within the managed environment, streamlining development workflows.

Here are some commonly used commands:

# Replace python with uv. This automatically installs Python and dependencies.
uv run script.py

# Run a Python script directly from the Internet
uv run https://example.com/script.py

# Run a Python script without installing
uvx ruff

# Use a specific Python version
uv run --python 3.11 script.py

# Add dependencies to your script
uv add httpx --script script.py

# Create a virtual environment at .venv
uv venv

# Install packages to your virtual environment
uv pip install httpx

Here are some useful tools you can run with uvx without installation:

uvx --from jupyterlab jupyter-lab   # Jupyter notebook
uvx marimo      # Interactive notebook
uvx llm         # Chat with LLMs from the command line
uvx openwebui   # Chat with LLMs via the browser
uvx httpie      # Make HTTP requests
uvx datasette   # Browse SQLite databases
uvx markitdown  # Convert PDF to Markdown
uvx yt-dlp      # Download YouTube videos
uvx asciinema   # Record your terminal and play it

uv uses inline script metadata for dependencies. This eliminates the need for requirements.txt or virtual environments. For example:

# /// script
# requires-python = ">=3.11"
# dependencies = [
#   "httpx",
#   "pandas",
# ]
# ///