Development setup

This page walks you through getting a working OpenRAL development environment from scratch — whether on a local Ubuntu machine, inside a dev container, or in a GitHub Codespace. It also covers the day-to-day commands you'll use while contributing.

System requirements

Requirement	Minimum	Recommended
OS	Ubuntu 22.04 or 24.04	Ubuntu 24.04 (ROS 2 Jazzy)
Python	3.12 (only — `pyproject.toml` pins `>=3.12,<3.13`)	3.12
RAM	8 GB	16 GB
Disk	20 GB free	40 GB free
GPU	CPU-only (limited)	NVIDIA, 8 GB VRAM
Docker	24+ (for dev container)	26+

macOS 14+ is supported for Python/tooling work. ROS 2 on macOS runs inside the dev container.

Option A — Local Ubuntu machine (fastest iteration)

1. Clone and bootstrap

git clone https://github.com/OpenRAL/openral
cd OpenRAL
just bootstrap          # installs uv, ROS 2, system deps (~5–10 min)
source /opt/ros/jazzy/setup.bash   # or 'humble' on Ubuntu 22.04
uv sync --all-packages  # install Python workspace deps

The bootstrap script auto-detects Ubuntu 22.04 (→ ROS 2 Humble) or 24.04 (→ ROS 2 Jazzy).

2. Verify the install

just test            # full unit suite, <30 s
just lint            # ruff + mypy --strict; expect no errors
uv run openral doctor     # diagnose host environment

just test should run the full unit suite and complete in well under 30 s. The current inventory (file + LOC counts, gaps, follow-ups) is in tests/README.md.

uv run openral doctor is the canonical environment probe — see the README's "Quick start" section for a sample output table; that one is the single source of truth. Each row will read ok / info / absent / missing depending on which deps you have installed.

Option B — Dev container (VS Code / Docker Desktop)

Prerequisites

VS Code with the Dev Containers extension
Docker Desktop 24+ running locally

1. Open in container

F1  →  "Dev Containers: Reopen in Container"

VS Code will build Dockerfile.dev (first build ~8 min; subsequent builds use the layer cache) and run uv sync --all-packages automatically.

2. Or use docker-compose directly

docker compose -f docker-compose.dev.yml up -d openral-dev
docker compose -f docker-compose.dev.yml exec openral-dev bash
# inside container:
uv sync --all-packages
just test

The compose file also starts a Jaeger container for OpenTelemetry traces at http://localhost:16686.

Hardware access

The dev container is started with --privileged and /dev mounted. On Linux hosts this gives USB access to connected robots. On macOS/Windows Docker Desktop, hardware passthrough is limited — use Option A (native Ubuntu) for hardware-in-the-loop work.

Option C — GitHub Codespaces (browser / no local install)

On the GitHub repo page: Code → Codespaces → Create codespace on main.
Wait for the container to build and uv sync --all-packages to complete (~5 min).
Open a terminal and run just test.

Note

Hardware mounts (/dev, /run/udev) are not available in Codespaces. All unit and sim tests work; HIL tests require a self-hosted runner.

Day-to-day commands

All commands use just as the task runner. Run just (no arguments) to list all targets.

Python tests

just test                   # all tests in tests/unit/
just test-k so100           # filter by keyword
uv run pytest tests/unit/test_schemas_fuzz.py -v   # run a specific file

Linting and formatting

just lint       # ruff check + ruff format --check + mypy --strict (CI parity)
just fmt        # auto-fix: ruff format + ruff check --fix

Schema export

just schema-export          # regenerate docs/reference/schemas/*.json
uv run python tools/schema_export.py --check   # CI drift-check (exit 1 on drift)

If you change any Pydantic model in python/core/, run just schema-export and commit the updated JSON files.

ROS 2 build and test

source /opt/ros/jazzy/setup.bash
just ros2-build             # colcon build --merge-install
source install/setup.bash
just ros2-test              # colcon test + colcon test-result --verbose

Sim evals (closed-loop, opt-in — needs HF weights ± GPU)

just sim-eval scenes/<name>.yaml   # canonical entry point (ADR-0002)
just sim-libero                              # SmolVLA × LIBERO
just sim-xvla-libero                         # xVLA × LIBERO
just sim-pi05-libero                         # π0.5 × LIBERO (≥8 GB VRAM)
just sim-metaworld --task reach-v3           # SmolVLA × MetaWorld MT50
just sim-act-aloha                           # ACT × gym-aloha bimanual cube
just sim-diffusion-pusht                     # Diffusion Policy × gym-pusht (CPU)

Docs

just docs                   # serve at http://localhost:8000 (live-reload)
just docs-build             # full build (CI parity, strict mode)

Repository layout (quick reference)

python/core/         openral_core         — Pydantic v2 schemas (normative)
python/cli/          openral_cli          — `openral` CLI entry point
python/hal/          openral_hal          — HAL Protocol + per-robot adapters
                                                  (so100_sim, so100_follower, franka_panda,
                                                   ur5e/ur10e, ros_control)
python/sensors/      openral_sensors      — sensor catalog + vendor adapters
python/world_state/  openral_world_state  — WorldStateAggregator (30 Hz snapshot)
python/rskill/        openral_rskill        — Skill ABC, rSkill loader, runtimes,
                                                  SmolVLA adapter
python/sim/          openral_sim          — openral sim run registry/runner; LIBERO/MetaWorld
packages/msgs/                                — ROS 2 IDL (.msg, .action)
packages/world_state/                         — WorldState lifecycle node
packages/openral_hal_*/                   — per-robot lifecycle nodes (so100, ur5e,
                                                  ur10e, franka)
robots/                                       — canonical RobotDescription manifests
                                                  (so100_follower, franka_panda, sawyer,
                                                   aloha_bimanual, pusht_2d,
                                                   ur5e, ur10e); auto-discovered
                                                   by openral_sim at import.
skills/                                       — rSkill packages (manifest + eval/)
                                                  (smolvla-libero, smolvla-metaworld,
                                                   pi05-libero-nf4,
                                                   pi05-robocasa365-human300-nf4,
                                                   xvla-libero, act-aloha,
                                                   act-aloha-insertion,
                                                   diffusion-pusht)
examples/                                     — runnable end-to-end demos +
                                                  scenes/ SceneEnvironment YAMLs
tests/unit/                                   — pytest unit tests (<30 s total)
tests/integration/                            — launch_testing multi-node tests
tests/sim/                                    — closed-loop sim (CUDA + HF weights, opt-in)
tests/hil/                                    — hardware-in-the-loop (lab runners)
tools/schema_export.py                        — JSON Schema generator + drift check
tools/rskill_publisher.py                      — rSkill packaging / publish helper
docs/                                         — mkdocs-material site

Most directories carry a per-package README.md with usage examples and links back to the canonical schemas — start with the package matching the layer you're touching.

Full architecture is in docs/architecture/overview.md. For a per-module status canvas (working / in-dev / planned / out-of-scope, with inputs, outputs, and schemas), open docs/architecture/repo-state-map.html — keep it in sync per CLAUDE.md §4.3.

Making a pull request

Create a branch: git switch -c feat/your-feature.
Make your changes. Run just lint && just test before pushing.
If you changed a Pydantic schema, run just schema-export and commit the updated JSON files.
Open a PR. The title should follow Conventional Commits — e.g. feat(core): add FooSchema.
All CI checks must be green before merge. See .github/workflows/ for what runs.

The full PR checklist is in the repo-root CLAUDE.md (not linked from docs — open it directly in your editor).

Troubleshooting

`uv sync` fails with "package not found"

Run uv sync --all-packages instead of plain uv sync. The workspace has multiple member packages and the root manifest does not list them as direct dependencies.

`mypy` reports "missing library stubs or py.typed"

Both openral_core and openral_cli ship py.typed markers. If mypy still complains, make sure you ran uv sync --all-packages and that your interpreter is the workspace venv (which python should point into .venv/).

`openral doctor` shows ROS 2 as "missing" after bootstrap

Source the ROS 2 setup file:

source /opt/ros/jazzy/setup.bash   # Ubuntu 24.04
# or
source /opt/ros/humble/setup.bash  # Ubuntu 22.04

Add this line to your ~/.bashrc for permanent effect.

Docker build fails copying `python/core/pyproject.toml`

Make sure you're building from the repo root (the docker-compose.dev.yml sets context: .). Building directly with docker build -f Dockerfile.dev . from the repo root also works.

Pre-commit hooks fail

Install the hooks once after cloning:

just install-hooks

Then git commit runs ruff, ruff-format, mypy, codespell, and the conventional-commit check on changed files automatically, plus DCO auto-sign-off.

Use just install-hooks rather than pre-commit install: the repo pins core.hooksPath=.githooks (for DCO sign-off), and pre-commit install refuses to run while core.hooksPath is set. just install-hooks instead wires the committed .githooks/ wrappers (which call pre-commit run) and pre-builds the hook environments.