poliastro requires the following Python packages:
- NumPy, for basic numerical routines
- Astropy, for physical units and time handling
- numba (optional), for accelerating the code
- jplephem, for the planetary ephemerides using SPICE kernels
- matplotlib, for orbit plotting
- scipy, for root finding and numerical propagation
- pytest, for running the tests from the package
poliastro is usually tested on Linux, Windows and OS X on Python 3.5 and 3.6 against latest NumPy.
The easiest and fastest way to get the package up and running is to install poliastro using conda:
$ conda install poliastro --channel conda-forge
We encourage users to use conda and the conda-forge packages for convenience, especially when developing on Windows.
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
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 2 (two) extensions of JupyterLab to make your experience smooth.
$ jupyter labextension install @jupyter-widgets/jupyterlab-manager
$ jupyter labextension install @jupyterlab/plotly-extension
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.”