Guy Griffiths

General purpose interpreted programming language

Widely used by scientists and programmers of all stripes

Supported by many 3rd-party libraries (currently 21,054 on the main python package website)

Free!

Standardisation of programming language to teach to students

The Met Office is moving towards Python

Big user communityPublication-quality plots

An integrated graphical environment like Matlab (although there are tools which put it in one – e.g. Spyder)

Specifically designed for scientists/mathematicians (but the 3rd-party libraries for plotting/numerical work are some of the best around)

High performance (but it is very easy to wrap C/Fortran libraries in Python code)

Met OfficeYahoo Maps/GroupsGoogleNASAESRIYouTubeLinux distros reddit

The best way to understand syntax is to look at some examples

Matlab Python

Indexing starts at 1 Indexing starts at 0

Spaces aren’t very important Spaces indicate loops and blocks

1 externally-visible function per file

Functions can be defined anywhere

Result of each line output by default, suppressed by ;

No output unless specifically asked for

Comes with an IDE (but can be run without one)

Doesn’t come with an IDE (but several are available)

Functions are globally present if they’re in the path

Most functions must be imported before being used

Namespaces are awkward and rarely used

Namespaces are inherent

Numpy Numerical library for python Written in C, wrapped by python Fast

Scipy Built on top of numpy and BLAS/LAPACK (i.e.

fast) Common maths, science, engineering routines

Matplotlib Hugely flexible plotting library Similar syntax to Matlab Produces publication-quality output

Numpy arrays behave slightly differently to Python lists They cannot hold mixed data types But they’re a lot faster than lists For numerical work, always use Numpy

arrays Convert a list to an array with np.array(list)

Numpy functions all return arrays, so often nothing specific needs doing

Matplotlib has very similar syntax to Matlab

Lots of examples: http://matplotlib.org/gallery.html http://matplotlib.org/basemap/users/

examples.htmlUsing documentation and examples

makes it easy to do almost any plot you could want

NetCDF Use python-netcdf

CSV np.recfromcsv()

GRIB Use python-grib, python-grib2, or cf-python

PP cf-python

Matlab .mat scipy.io.loadmat(‘filename.mat’)

Others If it’s a common format, someone will probably

have written an adapter If it’s text based, use np.genfromtxt()

Spyder is most Matlab-like Contains inline help, variable inspector,

interactive console & editor IPython is powerful console-based

interpreter Not an IDE, but highly recommended for

experimenting with prior to actual scripting Eclipse + Pydev make a very powerful

Python IDE Quite heavyweight Good for very large projects, probably overkill

otherwise

Online HTML documentation is generated from

code comments In console:

help(np.array) In IPython console:

np.array? np.array()?

In Spyder: Start typing, and function help appears in

the help window

Let’s put all that into action with an example: Reading from a NetCDF file and creating

a plot of mean and standard deviation

Firstly, get version 2.7.x. Python 3 will work but numerical libraries are less widely supported.

Windows – Python(x,y) [www.pythonxy.com]This is a scientific/engineering oriented distribution of python. It includes everything you need to get started

Linux – it’s already there! Unless you’re running a very unusual distro (in which case you probably already know what you’re doing).

Mac – it’s already there on OS X, but it’s old. Get a more up-to-date one [www.python.org]

The official python tutorial:http://docs.python.org/tutorial/

Software Carpentry:http://software-carpentry.org/

Dive into Python:http://www.diveintopython.net/

Learn Python the Hard Way:http://learnpythonthehardway.org/

A Byte of Python:http://www.ibiblio.org/g2swap/byteofpython/read/

http://www.scipy.org/NumPy_for_Matlab_Users This is the most useful Matlab -> Python

I’ve come across. Contains key differences, things to note,

and a big list of examples in both Matlab and Python

Python Essential Reference David M. Beazley (Addison Wesley)

Programming in Python 3: A Complete Introduction to the Python LanguageMark Summerfield (Addison Wesley)

Learning PythonMark Lutz (O’Reilly Media)

Go away and try it! Convert existing Matlab code (easy) Convert existing Fortran code (harder) Experiment with something new

Then come back in 3 weeks’ time for a workshop, bringing any questions/problems No planned lecture Will go through common problems people

have Join the met-python mailing list

Thanks for listening