Package: einsteinpy
Name:EinsteinPyWebsite:https://einsteinpy.org/Version:0.4.0EinsteinPyis an open source pure Python package dedicated to problems arising
in General Relativity and gravitational physics, such as geodesics plotting for
Schwarzschild, Kerr and Kerr Newman space-time model, calculation of Schwarzschild
radius, calculation of Event Horizon and Ergosphere for Kerr space-time. Symbolic
Manipulations of various tensors like Metric, Riemann, Ricci, Ricci Scalar, Weyl,
Schouten, Stress-Energy-Momentum, Einstein and Christoffel Symbols is also possible
using the library. EinsteinPy also features Hypersurface Embedding of Schwarzschild
space-time, which will soon lead to modelling of Gravitational Lensing!
It is released under the MIT license.DocumentationComplete documentation, including a user guide and an API reference, can be read on
the wonderfulRead the Docs.https://docs.einsteinpy.org/ExamplesIn the examples directory, you can find several Jupyter notebooks with specific
applications of einsteinpy. You can consider theses Jupyter Notebooks as tutorials for einsteinpy.
You can launch a cloud Jupyter server usingbinderto edit
the notebooks without installing anything. Try it out!https://beta.mybinder.org/v2/gh/einsteinpy/einsteinpy/main?filepath=index.ipynbRequirementsEinsteinPy requires the following Python packages:NumPy, for basic numerical routinesAstropy, for physical units and time handlingMatplotlib, for static geodesics plotting and visualizations.Plotly, for interactive geodesics plotting and visualizations.SciPy, for solving ordinary differential equations.SymPy, for symbolic calculations related to GR.Numba, for accelerating the codeEinsteinPy is usually tested on Linux, Windows and macOS on Python 3.7 and 3.8, against latest NumPy.PlatformSiteStatusLinuxCircleCIOS XGithub ActionsWindows x64AppveyorInstallationThe easiest and fastest way to get the package up and running is to
install EinsteinPy usingconda:$ conda install einsteinpy --channel conda-forgeOr you can simply install it fromPyPI:$ pip install einsteinpyOr for Debian/Ubuntu/Mint users, the package is installable (Ubuntu 19.04 onwards) fromapt:$ sudo apt install python3-einsteinpyPlease note that the package version in Debian Repositories might not be the latest.
But it will be definitely the most stable version of EinsteinPy available till date.Please check out theguide for alternative installation methods.ProblemsIf the installation fails or you find something that doesn’t work as expected,
please open an issue in theissue tracker.ContributingEinsteinPy is a community project, hence all contributions are more than
welcome! For more information, head toCONTRIBUTING.rst.Developers Documentation can be found here.SupportRelease announcements and general discussion take place on ourmailing list.
Feel free to join!https://groups.io/g/einsteinpy-devPlease join our[matrix]channel orgitterchat room for further queries.If you still have a doubt, write a mail directly toall@einsteinpy.org.CitingIf you use EinsteinPy on your project, pleasedrop us a line.You can also use the DOI to cite it in your publications. This is the latest
one:And this is an example citation format:Shreyas Bapat et al.. (2019). EinsteinPy: einsteinpy 0.1.0. Zenodo. 10.5281/zenodo.2582388LicenseEinsteinPy is released under the MIT license, hence allowing commercial
use of the library. Please refer toCOPYING.FAQWhy Einstein-Py?EinsteinPy comes from the name of the famous physicist, Nobel laureate, revolutionary person, Prof. Albert Einstein.
This is a small tribute from our part for the amazing work he did for the humanity!Can I do <insert nerdy thing> with EinsteinPy?EinsteinPy is focused on general relativity.  One can always discuss probable features on the mailing list and try to implement it.
We welcome every contribution and will be happy to include it in EinsteinPy.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 of the roadmap is to see theMilestonesof
the project.InspirationThe whole documentation and code structure is shamelessly inspired bypoliastro. We really thank the poliastro
developers to make this possible. EinsteinPy is nothing without it’s supporters.