modern-python-toolchain

Modern Python Toolchain

A guide for setting up Python projects with modern, fast tooling: uv (package/project manager), ruff (linter/formatter), and pyright (type checker).

Installing uv

uv is an extremely fast Python package and project manager. It replaces pip, pip-tools, pipx, pyenv, virtualenv, poetry, etc.

# macOS / Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows (PowerShell)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

# Homebrew (macOS)
brew install uv

After installation, restart your shell or run source $HOME/.local/bin/env (the installer prints the exact command).

For detailed information: https://docs.astral.sh/uv/

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uv basics

Python version

Pin a single Python minor version. The recommended default is 3.12 (broadest ecosystem support — PyTorch, CUDA images, downstream libraries). Python 3.14 is the latest stable; prefer it for new projects unless you depend on packages that haven't added 3.14 support yet.

# pyproject.toml
requires-python = "==3.12.*"

Install Python via uv (no system Python needed):

uv python install 3.12

Creating a new project

uv init                       # Create new project with pyproject.toml
uv init -p 3.12               # Specify Python version

Common commands

uv add requests               # Add dependency
uv add --dev ruff "pyright[nodejs]"  # Add dev dependencies
uv remove requests            # Remove dependency
uv sync                       # Install from lockfile
uv run COMMAND                # Run command in project environment
uv run script.py              # Run a script
uv run python -c "..."        # Run Python one-liner
uvx TOOL ARGS                 # Run a tool without installing it

Rules

• Never use pip in uv projects — always uv add for packages.
• Never run python script.py directly — always uv run script.py to ensure the correct environment. For one-liners use uv run python -c "...".
• Don't manually manage environments with python -m venv or source .venv/bin/activate — uv handles this automatically.
• uvx runs tools from PyPI by package name without installing them permanently.

Project types

For library projects (uv init --lib) or packaged apps (uv init --package), uv_build is used as the default build backend automatically:

[build-system]
# auto-generated by uv init; version bound tracks your installed uv (here: 0.11.28)
requires = ["uv_build>=0.11.28,<0.12.0"]
build-backend = "uv_build"

For application projects with an entry point:

[project.scripts]
myapp = "myapp.__main__:main"

If the project does not use src layout, just run uv run main.py.

---

ruff

Ruff is an extremely fast Python linter and code formatter. It replaces Flake8, isort, Black, pyupgrade, autoflake, and more.

For detailed information: https://docs.astral.sh/ruff/

When to use

Always use ruff for Python linting and formatting. Prefer uv run ruff when ruff is a dev dependency; otherwise fall back to uvx ruff.

Configuration

Add to pyproject.toml:

[tool.ruff.lint]
extend-select = [
    "UP",  # pyupgrade
    "I",   # isort
]

Do not enable the full E category or other formatter-conflicting rules (E1xx, E501, W191, Q, COM); ruff format owns layout.

Post-edit workflow

After modifying Python code, run both:

uv run ruff check --fix path/to/changed_file.py
uv run ruff format path/to/changed_file.py

Use --diff to preview changes without applying.

---

pyright

Pyright is a fast type checker for Python. Only use it when the project lists it as a dev dependency or explicitly uses type checking.

Install with the nodejs extra so Node.js is bundled automatically (no system node required):

uv add --dev "pyright[nodejs]"

Run type checking:

uv run pyright path/to/changed_file.py    # check specific files
uv run pyright src/                        # check all code

Usually only check the files you modified. For broad changes (base classes, shared types), check the full tree.

---

Coding style

Type annotations

Use modern Python 3.12+ syntax:

# Good — builtin generics, union syntax
def fetch(url: str, timeout: float = 30.0) -> list[dict[str, str | None]]:
    ...

# Bad — legacy typing imports
from typing import List, Dict, Optional
def fetch(url: str, timeout: float = 30.0) -> List[Dict[str, Optional[str]]]:
    ...

Always annotate function parameters. Local variables can rely on inference unless the type is ambiguous:

items: list[tuple[str, int]] = []    # annotate — empty literal
config: dict[str, Any] = {}          # annotate — empty literal
result = some_api()                  # inference is fine

pydantic v2

Use the modern class-based API:

• model_config = ConfigDict(...) at class body level, not class Config.
• RootModel with root: SomeType for single-root schemas.

typer (CLI)

Recommended for CLI entry points over argparse:

import typer
from typing import Annotated

cli = typer.Typer(add_completion=False)

@cli.command()
def main(name: Annotated[str, typer.Argument(help="Your name")]) -> None:
    typer.echo(f"Hello {name}")

if __name__ == "__main__":
    cli()