Macports is a general package manager inspired by BSD Unix's ports system, and it includes increasingly good support for astronomical python routines among the many thousands of installable packages.See the python4astronomers tutorial for detailed instructions for using this. It's probably equally as good as Anaconda for most purposes. Enthought Canopy (formerly Enthough Python Distribution, EPD) is another binary distribution including all the standard modules, also free to academic users.It comes with a large library of modules including the complete scientific python stack, is free to academic users, and is becoming the most widely recommended Python version for scientific work. Anaconda is a binary distribution provided by one of the leading scientific python commercial developers.See the python4astronomers installation options list for a cross platform comparison. So, how can you get Python going? The following options are ranked loosely based on one author's subjective impression of how useful each is for a typical user. For almost all astronomers, Python 2.7 is the most useful and recommended language version. Overgeneralizing broadly, Python 3 is the future, Python 2 is the present. ![]() Most importantly, there is ongoing development of Python 3, which due to some changes in the language syntax is not back-compatible with code for any version of Python 2. In addition to various different installation methods, there are different versions of Python itself. If you will be using IRAF, then Scisoft is also highly recommended. However, if you are already using the Macports package manager to install other Unix-related tools, then Macports is also an excellent choice for Python. Most new users on Macs should select the either Anaconda or Enthought Canopy (formerly Enthought Python Distribution). ![]() The goal of this page is to list all your choices, and a few sentences about their various pros and cons. Many of the existing guides elsewhere advocate one particular method or another. There are many different ways to get to a functioning Python install for astronomy. For a slightly more recent (March 2012) take on how best to install scientific Python, see Note: The below guide was last updated in Fall 2011. Cautionary Note: This page may be out of date
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