Differences between revisions 1 and 8 (spanning 7 versions)

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).

   1 >>> n_int = 135
   2 >>> n_int
   3 135
   4 >>> n_float = 10e-10
   5 >>> n_float
   6 10e-10

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

Boolean

The boolean

Lists and tuples

Dictionaries

Modules

Objects

Loops

None: Meetings/Delhi2012/Practicals/Practical_2/PyIntro (last edited 2012-10-12 13:53:26 by hassan)

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-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 
lange 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).
+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 [[http://docs.python.org/ | here]].
-Line 10:
+Line 7:
-We will be using {{{Python}}} from the {{{ScrumPy}}} environment.
+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}}}). 

{{{#!python
>>> n_int = 135
>>> n_int
135
>>> n_float = 10e-10
>>> n_float
10e-10
}}}

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
}}}

== Boolean ==

The boolean

== Lists and tuples ==

== Dictionaries ==

== Modules ==

== Objects ==

== Loops ==