Getting started


poliastro requires a number of Python packages, notably:

  • Astropy, for physical units and time handling

  • NumPy, for basic numerical routines

  • jplephem, for the planetary ephemerides using SPICE kernels

  • matplotlib, for static orbit plotting

  • numba (when using CPython), for accelerating the code

  • Plotly, for interactive orbit plotting

  • SciPy, for root finding and numerical propagation

poliastro is usually tested on Linux and Windows on Python 3.7 and 3.8 against latest NumPy. It should work on OS X without problems.


The easiest and fastest way to get the package up and running is to install poliastro using conda:

$ conda install -c conda-forge poliastro=0.14


We encourage users to use conda and the conda-forge packages for convenience, especially when developing on Windows. It is recommended to create a new environment.

If the installation fails for any reason, please open an issue in the issue tracker.

Alternative installation methods

If you don’t want to use conda you can install poliastro from PyPI using pip:

$ pip install numpy  # Run this one first for pip 9 and older!
$ pip install poliastro[jupyter] pytest

Finally, you can also install the latest development version of poliastro directly from GitHub:

$ pip install

This is useful if there is some feature that you want to try, but we did not release it yet as a stable version. Although you might find some unpolished details, these development installations should work without problems. If you find any, please open an issue in the issue tracker.


It is recommended that you never ever use sudo with distutils, pip, setuptools and friends in Linux because you might seriously break your system [1][2][3][4]. Options are per user directories, virtualenv or local installations.

Using poliastro on JupyterLab

After the release of Plotly 3.0, plotting orbits using poliastro is easier than ever.

You need to install the jupyterlab, which will install the necessary dependencies, including plotly. You can do this using pip:

$ pip install jupyterlab

And then start the jupyter-lab with:

$ jupyter lab

And as the documentation of JupyterLab Extensions states:

“In order to install JupyterLab extensions, you need to have Node.js version 4 or later installed.”

If you face any further issues, you can refer to the installation guide by Plotly.

Problems and suggestions

If for any reason you get an unexpected error message or an incorrect result, or you want to let the developers know about your use case, please open a new issue in the issue tracker and we will try to answer promptly.