# Open writing projects/Sage and cython a brief introduction

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This is a quick introduction to [[http://www.sagemath.org/index.html Sage]], a powerful new computational platform that builds on the strengths of Python. This article was directly inspired by Julius B. Lucks' [[http://openwetware.org/wiki/Julius_B._Lucks/Projects/Python_All_A_Scientist_Needs "Python: All A Scientist Needs"]]; I recommend reading it first as it explains some of the attractions of Python and biopython. | This is a quick introduction to [[http://www.sagemath.org/index.html Sage]], a powerful new computational platform that builds on the strengths of Python. This article was directly inspired by Julius B. Lucks' [[http://openwetware.org/wiki/Julius_B._Lucks/Projects/Python_All_A_Scientist_Needs "Python: All A Scientist Needs"]]; I recommend reading it first as it explains some of the attractions of Python and biopython. | ||

- | Sage | + | Sage is a free and open-source project for computation of all sorts that uses Python as its primary language and "glue". One of the goals of Sage is to provide a viable free and open-source alternative to Matlab, Maple, and Mathematica. Sage unifies a great deal of open-source mathematical and statistical software; it includes biopython as an optional package and the statistics language R by default. |

== Sage notebook interface == | == Sage notebook interface == | ||

(TODO: notebook interface screenshots, different computers, good 2-d graphics) | (TODO: notebook interface screenshots, different computers, good 2-d graphics) | ||

+ | |||

+ | A key feature of Sage is its notebook web-browser interface. | ||

+ | |||

+ | Jose Unpingco has made a [[http://sage.math.washington.edu/home/wdj/expository/unpingco/ good short introductory video]] on the notebook interface that may help get a sense of what its like. | ||

<syntax type="python"> | <syntax type="python"> |

## Revision as of 16:18, 1 May 2008

## Contents |

### Work in progress

Please check back later for the final version...

## Abstract

This is a quick introduction to [Sage], a powerful new computational platform that builds on the strengths of Python. This article was directly inspired by Julius B. Lucks' ["Python: All A Scientist Needs"]; I recommend reading it first as it explains some of the attractions of Python and biopython.

Sage is a free and open-source project for computation of all sorts that uses Python as its primary language and "glue". One of the goals of Sage is to provide a viable free and open-source alternative to Matlab, Maple, and Mathematica. Sage unifies a great deal of open-source mathematical and statistical software; it includes biopython as an optional package and the statistics language R by default.

## Sage notebook interface

(TODO: notebook interface screenshots, different computers, good 2-d graphics)

A key feature of Sage is its notebook web-browser interface.

Jose Unpingco has made a [good short introductory video] on the notebook interface that may help get a sense of what its like.

<syntax type="python"> def PStoRE(PrositePattern):

""" Converts a PROSITE regular expression to a python r.e. """ rePattern = PrositePattern rePattern = rePattern.replace('-',)rePattern = rePattern.replace(' ',)rePattern = rePattern.replace('x','.') rePattern = rePattern.replace('{','[^') rePattern = rePattern.replace('}',']') rePattern = rePattern.replace('(','{') rePattern = rePattern.replace(')','}') return rePattern

from Bio import Fasta import re import urllib2 as U @interact def re_scan(fasta_file_url = 'http://www.d.umn.edu/~mhampton/PlasProtsRef.fa', pat = input_box('G - x - P - [AG] - x(2) - [LIVM] - x - [IV] ', type = str, width = 60)):

re_pat = re.compile(PStoRE(pat)) parser = Fasta.RecordParser() prot_file = U.urlopen(fasta_file_url) fasta_iterator = Fasta.Iterator(prot_file, parser = parser) for record in fasta_iterator: matches = re_pat.findall(record.sequence) if len(matches) != 0: html(record.title) html(matches) print

## Cython

Sage initially used an alternative to SWIG (described in Julius's article) called Pyrex to compile Python code to C when performance concerns demanded it. Because they needed to extend Pyrex in various ways, they created a friendly fork of Pyrex called "Cython". I believe it is fair to say that Cython is the easiest way to create C code in Python.

(TODO: example of Cython usage)