The latest stable version of Gammapy is listed at https://gammapy.org
Gammapy works with Python 3.6 or later.
Linux and Mac OS are fully supported.
Gammapy itself, and most analyses, work on Windows. However, two optional dependencies don’t support Windows yet: Sherpa (an optional fitting backend) and healpy (needed to work with HEALPix maps, which is common for all-sky analyses).
Gammapy is a Python package built on Numpy and Astropy, as well as a few other required dependencies. For certain functionality, optional dependencies are used. The recommended way to install Gammapy is via a conda environment which includes all required and optional dependencies (see Installation). If you want a more minimal installation, that is possible of course (see Gammapy conda installation).
Note that when you install Gammapy with conda (or actually any alternative distribution channel), you have a full package manager at your fingertips. You can conda or pip install any extra Python package you like (e.g. pip install pyjokes), upgrade or downgrade packages to other versions (very rarely needed) or uninstall any package you don’t like (almost never useful, unless you run out of disk space).
Required dependencies are automatically installed when using e.g.
install gammapy -c conda-forge or
pip install gammapy.
- numpy - nd-array, math functions
- scipy - numerical methods (interpolation, integration, convolution)
- Astropy - core package for Astronomy in Python
- regions - Astropy sky region package
- click - used for the
gammapycommand line tool
- PyYAML - support for YAML format (config and results files)
- jsonschema - support for json-schema.org (config file validation)
The optional dependencies listed here are the packages listed in the conda
environment specification (see Installation). This is a mix of packages that
make it convenient to use Gammapy (e.g.
jupyter), that add
extra functionality (e.g.
matplotlib to make plots,
naima for physical
SED modeling), and partly packages that aren’t used within Gammapy, only for
example data download (
parfive) or in one of the tutorials (
- ipython, jupyter and jupyterlab for interactive analysis
- matplotlib for plotting
- pandas for working with tables (not used within Gammapy)
- healpy for HEALPIX data handling
- reproject for image reprojection
- uncertainties for linear error propagation
- iminuit for fitting by optimization
- Sherpa for modeling and fitting
- naima for SED modeling
- emcee for fitting by MCMC sampling
- corner for MCMC corner plots
- parfive for example data and tutorial notebook download
Every stable version of Gammapy is compatible with a range of versions of it’s dependencies. E.g. Gammapy v0.13 was fully tested and is known to be compatible with Python 3.5, 3.6 and 3.7. Most likely it will be compatible with Python 3.8 when it comes out, or also with Python 4.0 if that ever comes out, but we can’t know for sure or guarantee that. With other dependencies it’s similar, e.g. Gammapy v0.13 was fully tested and known to work with Astropy 2.0 to 3.2, there were certain functions in Gammapy that didn’t work with older Astropy versions than 2.0, and for Astropy 4.0 or newer versions likely everything will work, but we can’t test or guarantee it before that comes out.
So for now, we have decided to ship and recommend the use of Gammapy conda environments with fixed and recent versions of all dependencies. This will give users a well-tested and known good reproducible execution environment (on any of the supported platforms: Linux, macOS and Windows). As an example, see gammapy-0.13-environment.yml.