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 https://github.com/poliastro/poliastro/archive/master.zip
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.
Using poliastro on JupyterLab¶
After the release of Plotly 3.0, plotting orbits using poliastro is easier than ever.
You have to install three extensions of JupyterLab to make your experience smooth:
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.