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Brahe is a modern satellite dynamics library for research and engineering applications designed to be easy-to-learn, high-performance, and quick-to-deploy. The north-star of the development is enabling users to solve meaningful problems and answer questions quickly, easily, and correctly.

Project description

Brahe

Brahe - Practical Astrodynamics

Docs Tests Crate PyPi License arXiv


Documentation: https://duncaneddy.github.io/brahe/latest

Rust Library Reference: https://docs.rs/crate/brahe/latest

Source Code: https://github.com/duncaneddy/brahe


Brahe

Brahe is a modern satellite dynamics library for research and engineering applications. It is designed to be quick-to-deploy, composable, extensible, and easy-to-learn. The north-star of the development is enabling users to solve meaningful problems quickly and correctly.

Brahe is permissively licensed under an MIT License to enable people to use and build on the work without worrying about licensing restrictions. We want people to be able to stop reinventing the astrodynamics "wheel" because commercial licenses are expensive and open-source options are hard to use.

We try to prioritize making the software library easy to learn, use, and verify. Many astrodynamics libraries are written with many layers of abstraction for flexibility that can make it challenging for new users to understand where the actual logic and algorithms are being executed. Brahe is written in a modern style with an emphasis on code clarity and modularity to make it easier to understand what individual functions are actually doing. This approach has the added benefit of making it easier to verify and validate the correctness of the implementation.

If you do find this useful, please consider starring the repository on GitHub to help increase its visibility. If you're using Brahe for school, research, a commercial endeavour, or flying a mission. I'd love to know about it.

We hope you find Brahe useful for your work!

Going Further

If you want to learn more about how to use the package the documentation is structured in the following way:

  • Getting Started: The getting started guide provides a high-level overview of the main concepts and components of Brahe, along with a quick introduction to using it. It is designed to help new users get up to speed quickly and understand the core ideas behind Brahe before diving into the more detailed documentation in the other sections. If you are new to Brahe, this is a great place to start!
  • User Guide: The user guide provides more comprehensive module-by-module documentation covering the capabilities each module provides with examples on how to use it.
  • Examples: This section contains a collection of worked examples that demonstrate how to use Brahe to solve various problems or accomplish specific tasks. The examples are designed to be practical and cover a range of use cases, from basic to more advanced.
  • Python API Reference: Provides detailed reference documentation of the Python API, including all public classes, functions, and methods organized by module.
  • Rust API Reference: Provides detailed reference documentation of the Rust API, including all public structs, traits, functions, and methods organized by module.

Quick Start

Python

To install the latest release of brahe for Python, simply run:

pip install brahe

You can then import the package in your Python code with:

import brahe as bh

And do something fun like calculate the orbital-period of a satellite in low Earth orbit:

import brahe as bh

# Define the semi-major axis of a low Earth orbit (in meters)
a = bh.constants.R_EARTH + 400e3  # 400 km altitude

# Calculate the orbital period
T = bh.orbital_period(a)

print(f"Orbital Period: {T / 60:.2f} minutes")
# Outputs:
# Orbital Period: 92.56 minutes

or find the when the ISS will next pass overhead:

import brahe as bh

bh.initialize_eop()

# Download ISS TLE and create a propagator
client = bh.celestrak.CelestrakClient()
iss = client.get_sgp_propagator(catnr=25544, step_size=60.0)

# Propagate for 24 hours
epoch_start = iss.epoch
epoch_end = epoch_start + 24 * 3600.0
iss.propagate_to(epoch_end)

# Compute upcoming passes over San Francisco
passes = bh.location_accesses(
    bh.PointLocation(-122.4194, 37.7749, 0.0),  # San Francisco
    iss,
    epoch_start,
    epoch_end,
    bh.ElevationConstraint(min_elevation_deg=10.0),
)
print(f"Number of passes in next 24 hours: {len(passes)}")
# Example Output: Number of passes in next 24 hours: 5

If you want to see more examples of how to use brahe, you can find even more with full source code in the Examples section of the documentation.

Citing Brahe

If you use Brahe in your work, please cite the following paper:

@article{eddy2026brahe,
      title={{Brahe: A Modern Astrodynamics Library for Research and Engineering Applications}}, 
      author={Duncan Eddy and Mykel J. Kochenderfer},
      year={2026},
      eprint={2601.06452},
      archivePrefix={arXiv},
      primaryClass={astro-ph.IM},
      url={https://arxiv.org/abs/2601.06452}, 
}

Versioning

[!WARNING] Brahe follows a versioning scheme modeled on NumPy's policy rather than strict SemVer. Versions are PEP 440 compliant and take the form major.minor.bugfix:

  • Major releases (X.0.0) are rare and signal significant API or ABI breaks.
  • Minor releases (1.Y.0) contain new features, deprecations, and removals of previously deprecated code.
  • Bugfix releases (1.2.Z) contain only fixes — no new features, deprecations, or removals.

Deprecation policy (transitional): The long-term target — matching NumPy — is that backwards-incompatible API changes emit a DeprecationWarning for at least two minor releases before removal. While Brahe is in its early adoption phase, a deprecation may occur and be removed within a single minor release. This window will expand to multiple minor releases with deprecation warnings as adoption grows.

Pinning: For most projects brahe>=1.2 is sufficient. If you need guaranteed stability during the transitional deprecation period, pin to a specific major.minor.patch version (e.g., 1.2.3) rather than using a floating specifier (e.g., ^1.2.0 or >=1.2.0). See the versioning docs for details, including guidance on treating DeprecationWarning as an error in CI.

License

The project is licensed under the MIT License - see the LICENSE file for details.

We want to make it easy for people to use and build on the work without worrying about licensing restrictions!

Additionally, brahe uses cargo-deny to confirm that all dependencies are permissively licensed and compatible with commercial use. The permitted licenses can be found in the cargo-deny configuration file.

Contributing

If you find a bug, have a feature request, want to contribute, please open an issue or a pull request on the GitHub repository. Contributions are welcome and encouraged! If you see something missing, but don't know how to start contributing, please open an issue and we can discuss it. We are building software to help everyone on this planet explore the universe. We encourage you to bring your unique perspective to help make us stronger. We appreciate contributions from everyone, no prior space experience is needed to participate.

AI Usage

The development of Brahe has roots in 2014 when I first started writing astrodynamics software for my PhD. The main algorithms and code structure evolved over the years based on my own experience applying the software to both research problems and operational space missions. The core functionality of the library (time handling, reference frames, reference frame transformations, coordinate transformations) were all developed before the usage of AI tools. AI tools have since been intentionally adopted to help with improving and expanding capabilities that were on the nice-to-have feature list. They have also been used to help with writing documentation and improve code coverage. All results and outputs are manually reviewed, run, tested, and verified manually before being merged into the main branch, we expect the same from all contributions to the codebase. We are committed to maintaining the same standards of code clarity, modularity, and correctness for all contributions regardless of whether they were AI-assisted or not.

The use of AI-assisted coding in brahe is itself a bit of an expertiment. We are interesting in seeing how it can be used to help with the development of the library, however we will not compromise on the quality of the codebase overall. While we may get it wrong at times, times, producing correct, accurate, maintainable code is more important than producing code quickly.

For new contributions, we allow the use of AI-assited coding, however we expect that PRs will be manually reviewed and tested before being submitted and that all PRs follow the same standards of code clarity, modularity, and correctness as the rest of the codebase.

Sponsors

We are pleased to acknowledge the following sponsors for their support:

Northwood Space

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