# ADR-001: Python with uv

## Status

Accepted

## Context

The project needs a programming language and build toolchain. The PoC was
written in Python using PyTorch, sklearn, and transformers. A Rust port using
burn/cubecl was attempted but failed — the ML framework ecosystem in Rust is
not yet mature enough for this type of work.

The project needs a fast path to a usable system. The PoC already works in
Python. Modern Python packaging (uv, pyproject.toml, src layout) provides a
professional project structure that was not available even a few years ago.

## Decision

Use Python 3.10+ with uv as the package manager and build tool. Use uv_build
as the build backend. Use src/ layout for the package.

## Consequences

**Positive**:
- Fast path to working system — PoC code is already Python
- Rich ML ecosystem (PyTorch, transformers, sklearn, safetensors)
- uv provides 10-100x faster dependency management than pip
- Modern packaging standards (pyproject.toml, PEP 735 dependency groups)
- Easy distribution via PyPI with `pip install alknet-firewall[torch]`
- Type checking via mypy provides strong correctness guarantees

**Negative**:
- Python is slower than Rust for non-ML code (SVD projection, data wrangling)
- PyTorch is a large optional dependency (200MB-2.5GB)
- Rust port remains a future goal (Phase 3, speculative)

## References

- [modern-python-project-setup.md](../research/modern-python-project-setup.md)
- [python-ml-packaging.md](../research/python-ml-packaging.md)