Introduction to Python
The metabolic modelling we will be using, ScrumPy, is written in Python. Python is a high-level, object-oriented, interpreted programming language, it has a large standard library, and supports multiple programming paradigms. It is also syntactically clear and easy to learn. This is a very brief introduction to some of the basic features of the language, for a more complete introduction to the topic, see Lutz & Ascher, "Learning Python" O'Reilly Media inc. (Edition 2 or greater). A good source of Python documentation can be found here.
Getting started
We will be using Python from the ScrumPy environment. To start a new ScrumPy session open a terminal and type "ScrumPy":
user@machine:~$ ScrumPy &
which will launch the ScrumPy window.
Data types
Numbers
The numerical types we will be dealing with are integers, int, and floating-point numbers float. Integers are written as a sequence of digits. Floats are written as digits with a decimal point in the sequence, and an optional exponent (e or E).
The type of a given data object can be checked using the built-in function type().
>>> type(n_int) <type 'int'> >>>type(n_float) <type 'float'>
Floats and integers can be interconverted using the constructors int() or float().
>>> n_int2float=float(n_int) >>> n_int2float 135.0 >>> type(n_int2float) <type 'float'> #n_int is still an integer
The common matematical operators (+,-,/,*) work as expected, note that x**y means x^y.
Boolean
Booleans are a subtype of integers. A boolean type is either True or False, and can be very useful when writing conditional statements, i.e. if something is True, do something. Also, the integer 0 is False.
>>> val=True >>> if val: print 'val is true' val is true >>> val=False >>> if val: print 'val is true' >>>
Strings
Lists and tuples
Dictionaries
Modules
Objects