Very simple Python
In this section of our short course on Python for Physics and Astronomy we take a short path to using Python easily.
Installing Python on your computer
Python is open source software availble for free from www.python.org. Version 2.7 is the current mature version that is widely supportly by other add-on modules, and is the one for which examples here are still written. Python 3 is now widely used and packages for specific disciplines that are maintained are usually compatible with it. New installations should favor Python 3, but there's not much loss of functionality with the older Python 2.7.
Python will already be installed on your computer. Use your package manager to update and add to the base installation. You will need NumPy, SciPy, and the parts they depend on. Also add "pip" if it is not installed, since that is the tool to allow you to add packages that may not be in your operating system's distribution. It is useful to check that pip and python commands on your system are for the version of python you want to use. Some systems have both.
For Windows there are several choices.
- Python.org provides installers for Windows. The web-based installer will update software components from the web. You may need administrator privileges to update system libraries.
- Enthought Canopy The academic subscription is free and requires a university email address. Enthought provides all the packages in one installation process, and support. Non-academic users pay a license fee.
- WinPython is a portable distribution, self-contained, and can be saved and used on different computers. It also includes several useful packages and is said to be easy to install. It is free.
- Python 2.7 comes installed with OSX. Try "python --version" from a terminal command line and see what happens. You can update this installation from Python.org (see next), or add package with pip given adminsitrative authority. Be aware of the potential Tkl library problem though.
- Python.org has installers for recent Mac OS variants. However, there are problems with the Tkl libraries provided in by Apple, particularly when used for graphics and in the development environment IDLE, which you should be aware of. Read the notice here.
- Enthought Canopy The academic subscription is free for Mac users too, and requires a university email address. Enthought provides all the packages in one installation process, and support. Non-academic users pay a license fee.
Those with an astronomical interest may benefit from Python4Astronomers
Most users would probably prefer running Python through the IDLE integrated development environment. This provides an editor and file management, along with help and syntax highlighting. It's named after Eric Idle, who does the "Galaxy Song" in Monty Python. On the command line you would simple run "idle" to get started.
Additional modules would have to be installed separately later if they are not part of the original installation. Python has its own system for adding features which makes that easy. The ones you will need for scientific programming are
- NumPy Test with "import numpy from within interactive Python or idle.
- SciPy Test with "import scipy".
- AstroPy This one for astronomers. Test with "import astropy".
and there are others, especially from Scikits
IDE's and Editors and Python environments
Keep in mind that Python itself is a programming language and system. It stands on its own, and it can be incorporated into other more complex, and potentially more useful interfaces. At a minimum you will need a text editor. With that you can read and write program files, and run them as a program either by having "python" read the file, or by making the file itself executable (on Linux and Mac). Most editors on these operating systems will be fine, but some are cumbersome for learning. Unless you happen to have the skill, avoid "vi" and even "emacs", two common editors of Unix-like systems like OSX and LInux, and use something with a lighter interface. The java-based "jedit" is free, easy to install, and has some helpful features. Siunce it is based on java, it runs on Mac, Windows and Linux with the same look and feel. You can obtain it from http://www.jedit.org/ and follow their installation instructions.
The IDE idle is also very nice to start with, and recommended. It may be present after you install Python, so try the command "idle" in a terminal window and see what happens. There are said to be problems with its use of the Tkl library and the Mac OSX installed libraries, but they should be solved in the most recent releases of Python and OSX.
Now widely used and with great potential, the Jupyter system has been under development for a decade and is mature. You can read about it and even preview its capabilities on the web. Keep in mind if you decide to start at that level, that the system is feature-filled, and that once you create content within the system it will require the system to use that content. That is, unlike a simple Python program, the notebooks created by Jupyter are truly bodies of work that include data and analysis. It can be very useful in a lab, for example.
Using Python in real time
The first step is to figure out how to start up Python on your computer after it is installed. In Linux you open a console and type "python" on the command line. You'll immediately see a prompt that looks like ">>" after which you can type Python code and see the results.
If you installed the Enthought distribution of Python on Windows or Mac, take a look at their release notes and website for additional advice on getting started.
If you installed from the python.org, then they have some additional pages to offer help. On Windows, its not necessarily as straightforward as Linux, but it can be. It will help to read this "frequently asked question" (FAQ) page about Python on Windows to help you at first, and also consult setup and usage guide. On a Macintosh OS X system using Python is very similar to other Unix platforms like Linux or BSD. There are some helpful notes at the Using Python on a Macintosh website.
Once you have a command line prompt you have access to all of Python's capabilities. We'll show you some simple examples here to test your installation and give you a quick sense of how to use it.
To exit Python in the interactive mode, use "Ctrl+d" or "exit()" from the command line, or the Exit menu entry if you are running IDLE.
Using Python code as a standalone program
You will usually edit a file that contains your Python program and then run that program by calling the Python interpreter. Therefore, the first thing is to pick an appropriate editor. One way is to use IDLE, which makes it especially easy on Windows systems and others to edit and test with a consistent interface. On Linux systems where the command line is more commonly used, an alternative is a standard graphical editor that is aware of Python syntax like gedit. Other alternatives are nedit and emacs. Python text files have a required format, and it generally not a good idea to embed tabs in the text so the tab function has to be set for spaces instead. On MacOS your could try emacs, BBEdit, or another one of your preferred editors. The Python website maintains a list of editors and their features for different operating systems with links to the editor websites if you need to download one.
For example, if your program is in the file "myprogram.py" you can run it from the command line with "python myprogram.py". On Windows systems, the file extension ".py" may be associated with this command, and in that case you can start a program by clicking on the icon or name in a window. On MacOS and Linux, you would first make the file executable with a command such as
chmod a+x myfile.py
and also see that the first line of the file is exactly
assuming that python is installed in /usr/bin/. With those changes, any file of Python code becomes an executable program. Simply type
Note that programs that interact with the window manager may need to be started with pythonw instead of python. For MacOS, see 4.1.1 How to run a Python script.
Examples of very simple Python
For examples of Python illustrating how to use it interactively and to write very simple programs, see the section Python examples.
An assignment to try out very simple Python
For the assigned homework to use very simple Python interactively and as a script, see the section Python assignments.