einsteinpy

EinsteinPy is an open-source pure Python package dedicated to the study of problems arising
in General Relativity and gravitational physics. Using EinsteinPy, it is possible to approach
problems symbolically as well as numerically. On the symbolic side, EinsteinPy provides a robust
API, which allows users to access several predefined metrics or to define custom metrics and perform
symbolic calculations on them. Computation of quantities, such as terms of metric tensors,
Christoffel symbols, Riemann Curvature tensor, Ricci tensor, stress-energy tensor and more are
all supported and extensible, since the symbolic modules are built on top of SymPy. On
the numerical side, EinsteinPy provides tools to calculate and visualize geodesics, metric
singularities and hypersurface embeddings in certain spacetimes. We hope to extend the package to
include more features in the future. EinsteinPy is released under the MIT license.

Documentation

|docslatest| |docsstable|

Complete documentation, including a user guide and an API reference, can be perused on
the wonderful Read the Docs_.

… _Read the Docs: https://docs.einsteinpy.org/en/latest/

Examples

… |mybinder| image:: https://img.shields.io/badge/launch-binder-e66581.svg?style=flat-square
:target: https://mybinder.org/v2/gh/einsteinpy/einsteinpy/main?filepath=docs/source/examples/index.ipynb

|mybinder|

Several tutorial Jupyter notebooks on specific applications of EinsteinPy can be found
in the examples_ directory. You can launch a Jupyter notebook instance in the cloud
using binder_ to run and edit these notebooks without installing anything. Try it out!

… _examples: https://github.com/einsteinpy/einsteinpy/tree/main/docs/source/examples
… _binder: https://mybinder.org/v2/gh/einsteinpy/einsteinpy/main?filepath=docs/source/examples/index.ipynb

Requirements

EinsteinPy requires the following Python packages:

NumPy, for basic numerical routines
SciPy, for solving ordinary differential equations
SymPy, for symbolic calculations
Astropy, for handling conversion between physical units
Matplotlib, for producing static visualizations
Plotly, for producing interactive visualizations
Numba, for accelerating the code

EinsteinPy is currently tested on Linux, Windows and macOS on Python 3.7 and 3.8, against the latest NumPy.

Installation

Currently, the recommended way to install EinsteinPy is using pip
from PyPI <https://pypi.org/project/einsteinpy/>_::

$ pip install einsteinpy

Or, you can install the package using conda <https://anaconda.org/conda-forge/einsteinpy>_::

$ conda install einsteinpy --channel conda-forge

Note that the package on conda-forge is currently a version behind PyPI. We are working on updating it.

For Debian/Ubuntu/Mint users, the package is installable via apt <https://packages.debian.org/sid/python3-einsteinpy>_ (Ubuntu 19.04 onwards)::

$ sudo apt install python3-einsteinpy

If you prefer to install from source to stay on the latest but likely unstable version,
you can do so using the method described here <https://docs.einsteinpy.org/en/latest/installation.html#latest-version>_.

Problems

If the installation fails or you find something that doesn’t work as expected,
please open an issue in the issue tracker_.

… _issue tracker: https://github.com/einsteinpy/einsteinpy/issues

Contributing

EinsteinPy is a community project. Hence, all contributions are more than
welcome! For more information, head to CONTRIBUTING_ or see the developer guide_.

… _CONTRIBUTING: https://github.com/einsteinpy/einsteinpy/blob/main/CONTRIBUTING.rst
… _developer guide: https://docs.einsteinpy.org/en/latest/dev_guide.html

Support

Please join our [matrix]_ channel or Gitter_ chat room for general discussions and further queries.

… _[matrix]: https://matrix.to/#/#einsteinpy:matrix.org
… _Gitter: https://gitter.im/EinsteinPy-Project/EinsteinPy

Release announcements take place on our mailing list_. Feel free to join!

… _mailing list: https://groups.io/g/einsteinpy-dev

If you still have a doubt, write to us directly at [email protected] <mailto:[email protected]>_.

Citing

If you use EinsteinPy in your project, please drop us a line <mailto:[email protected]>_.
You can also use the DOI to cite it in your publications. This is the latest one:

|doi|

And this is an example citation format:

Shreyas Bapat et al (2021). EinsteinPy 0.4.0 (v0.4.0). Zenodo. https://doi.org/10.5281/zenodo.2582387

License

|license|

EinsteinPy is released under the MIT license, thereby allowing commercial
use of the library. Please refer to COPYING_ for more details.

… _COPYING: https://github.com/einsteinpy/einsteinpy/blob/main/COPYING

FAQ

Why “EinsteinPy”?

EinsteinPy borrows the name of the famous physicist, Nobel laureate and revolutionary
human, Dr. Albert Einstein. This is a small tribute on our part for the amazing work
he did for humanity!

Can I do <`insert nerdy thing`> with EinsteinPy?

EinsteinPy is focused on general relativity. One can always discuss probable features in discussion
forums and the mailing list and also work with the maintainers to try to implement them.
We welcome every contribution to EinsteinPy. Please see CONTRIBUTING_ for more details.

What’s the future of the project?

EinsteinPy is actively maintained and we hope to receive an influx of new contributors.
The best way to get an idea about the roadmap is to view the milestones_ of
the project.

… _Milestones: https://github.com/einsteinpy/einsteinpy/milestones

Inspiration

The documentation and code structure is shamelessly inspired by poliastro_. We wholeheartedly thank the poliastro
developers that made this possible. EinsteinPy is nothing without its supporters and community.

… _poliastro: https://docs.poliastro.space/