Octavian

Octavian is a Python-first astrodynamics / trajectory-optimization toolkit built on ASSET (asset_asrl).

This MVP includes:

• Two-impulse rendezvous with bounded free final time.
• Two-impulse rendezvous with bounded variable pre-coast.
• Composable coast phases with continuous or impulsive links.
• Terminal state, terminal delta-v, path, and orbital-element constraints.
• Finite chemical-burn phases with mass depletion and three thrust-direction controls.
• J2 perturbation support in the composable ASSET backend.
• Central-body selection, CWH relative motion, and relative safety geometry.
• Finite-thrust and low-thrust phases with mass depletion and spiral seeding.
• Optional schema-versioned JSON and YAML mission configuration.
• Lambert-Izzo seed sweeps across time of flight, longway, and multi-rev cases.
• Plotly HTML visualization with maneuver markers.

octavian declares ASSET (asset_asrl) as a runtime dependency because the solver-backed workflows rely on it.

Install

For daily development on Linux x86_64 (glibc 2.31 or newer), use a repository-local virtual environment:

python3.12 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install --no-user -e ".[dev]"
python -m octavian.diagnostics

After activation, use normal commands such as python examples/quick/01_two_impulse_free_time.py and pytest.

For local development and ASSET-backed workflows on Windows, use the recommended Conda environment. It installs ASSET and its native runtime inside one isolated prefix:

conda env create --file environment.yml
conda run --name octavian-dev python -m pip install --no-user -e ".[dev]"
conda run --name octavian-dev python -m octavian.diagnostics

See Development Environment for the platform support boundary, daily commands, dependency tiers, and the recommended environment pattern for other projects. Windows also supports a repository-local pip + venv setup:

py -3.12 -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
python -m pip install --no-user -e ".[dev]"
python -m octavian.diagnostics

For a standard installed package with the Plotly examples:

pip install "octavian[viz]"

For solver and astrodynamics code without visualization, pip install octavian is the smaller dependency set. Add YAML support only when needed:

pip install "octavian[yaml]"

Before running solver-backed examples, verify ASSET imports in the active environment:

python -c "import asset_asrl; print(asset_asrl.__file__)"

Examples

python examples/quick/01_two_impulse_free_time.py
python examples/quick/02_two_impulse_precoast_impulsive_link.py
python examples/composable/08_chemical_burn_j2.py
python -m octavian.config examples/config/01_two_impulse_transfer.json

JSON works without another dependency. Install octavian[yaml] to load YAML mission files. Both formats construct the same Python mission objects and use the same solvers as ordinary mission scripts.

See the MkDocs site for tutorial-style walkthroughs of every example and mission pattern.

Documentation

The docs are built with MkDocs and publish through GitHub Pages.

pip install -e ".[dev]"
python -m mkdocs serve
python -m mkdocs build

When GitHub Pages is enabled for the repository with Source: GitHub Actions, the docs workflow publishes the site from pushes to dev.

Development

conda run --name octavian-dev python -m pip install --no-user -e ".[dev]"
conda run --name octavian-dev pre-commit install
conda run --name octavian-dev python -m build
conda run --name octavian-dev python -m pytest

Studies

Use octavian.study.grid to run parameter sweeps and optionally save results to disk.

Releasing

Release versions are published from Git tags such as v0.1.5 by GitHub Actions. Maintainer steps are documented in RELEASING.md.