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why to become a Pyologist
Perl is for plumbers – Python is for biologists
Stefan Maetschke
Teasdale Group
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why
why, why, why …
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Biologists suffer for no good reason
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Perl is difficult to write and read
Perl gives weak error feedback
Perl obscures basic concepts
Limited understanding of principles
Low productivity
Reduced research scope
Perl is for plumbers - Python is for scientists
I want to have an easy life
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plumbers and others
spectrum of tasks, tools and roles
sys admin
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scientist
plumbing
vi
awk/Perl
grep/diff
SW developer
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designing
Emacs/IDE
C/C++/Java
UML/Unit test
Python
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equals(
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)
Python
Perl
Guido van Rossum
Larry Wall
1991
1987
Cross-platform, open-source, scripting language,
multi-paradigm, dynamic typing, statement ratio: 6
There should be one way
There’s more than one way
Easy
Difficult
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you must be joking!
list = [ [‘a’, ’b’, ’c’], [1, 2, 3] ]
print list[0]
@list = ( [‘a’, ’b’, ’c’], [1, 2, 3] );
print “@{$list[0]}\n”;
list = ['a', 'b', 'c']
hash = {}
hash[‘letters'] = list
print hash[‘letters']
my @list = ('a', 'b', 'c');
my %hash;
$hash{‘letters'} = \@list;
print "@{$hash{‘letters'}}\n";
class Person:
def __init__(self, age):
self.age = age
package Person;
use strict;
sub new {
my $class = shift;
my $age = shift or die "Must pass age";
my $rSelf = {'age' => $age};
bless ($rSelf, $class);
return $rSelf;
}
http://www.strombergers.com/python/
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More Perl bashing…
def add(a, b):
return a + b
sub add {
$_[0] + $_[1];
}
sub add {
my ($a, $b) = _@;
return $a + $b;
}
def diff(a, b):
return len(a) - len(b)
http://www.strombergers.com/python/
sub add($, $) {
local ($a, $b) = _@;
return $a + $b;
}
sub add {
my $a = shift;
my $b = shift;
return $a + $b;
}
sub diff {
my ($aref, $bref) = _@;
my (@a) = @$aref;
my (@b) = @$bref;
return scalar(@a) + scalar(@b);
}
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complexity wall
everything you can do in Python you can do in Perl but you don’t
simple scripts
≈ 100 lines
=> fun stops
Higher order
concepts
Data structures
Functions
Classes
=> Python allows you to break through the complexity wall
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googliness
X language
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C
Java
C++
C#
Perl
Python
Ruby
Scala
Haskell
kilo-hits, May 2008
53,000
7,760
1,290
1,020
1,150
527
470
394
212
X load file
1,820
2,890
3,100
794
685
798
806
354
323
X bioinformatics
572
320
231
161
101
199
186
69
74
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and the winner is…
<- without Psyco
http://shootout.alioth.debian.org/
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damn lies and stats
sourceforge projects
 Perl declining, Python increasing ?
 May 2008, keyword search : Perl 3474, Python 4063
http://rengelink.textdriven.com/blog/
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see the light…
classify Iris plants
Three species:
• Iris setosa
• Iris versicolor
• Iris virginica
Four attributes:
• sepal length
• sepal width
• petal length
• petal width
Fisher, R.A.
"The use of multiple measurements in taxonomic problems"
Annual Eugenics, 7, Part II, 179-188 (1936)
http://archive.ics.uci.edu/ml/datasets/Iris
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Iris – convert data
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Iris – correlation
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Iris – do stats
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Iris – linear regression
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Iris – plot data
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libs for life science
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Scientific computing: SciPy, NumPy, matplotlib
Bioinformatics: BioPython
Phylogenetic trees: Mavric, Plone, P4, Newick
Microarrays: SciGraph, CompClust
Molecular modeling: MMTK, OpenBabel, CDK, RDKit, cinfony,
mmLib
Dynamic systems modeling: PyDSTools
Protein structure visualization: PyMol, UCSF Chimera
Networks/Graphs: NetworkX, PyGraphViz
Symbolic math: SymPy, Sage
Wrapper for C/C++ code: SWIG, Pyrex, Cython
R/SPlus interface: RSPython, RPy
Java interface: Jython
Fortran to Python: F2PY
…
Check also out:
and:
http://www.scipy.org/Topical_Software
http://pypi.python.org/pypi
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last words
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Perl perfect for plumbing
Python excellent for scientific programming
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Easy to learn, write and maintain
Suited for scripting and mid-size projects
Huge number of scientific libraries
Python is an attractive alternative to Matlab/R
Easy integration of Java, C/C++ or Fortran code
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questions
isn’t Python lovely…
Interest:
Python Course?
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links
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Wikipedia – Python
http://en.wikipedia.org/wiki/Python
Instant Python
http://hetland.org/writing/instant-python.html
How to think like a computer scientist
http://openbookproject.net//thinkCSpy/
Dive into Python
http://www.diveintopython.org/
Python course in bioinformatics
http://www.pasteur.fr/recherche/unites/sis/formation/python/index.html
Beginning Python for bioinformatics
http://www.onlamp.com/pub/a/python/2002/10/17/biopython.html
SciPy Cookbook
http://www.scipy.org/Cookbook
Matplotlib Cookbook
http://www.scipy.org/Cookbook/Matplotlib
Biopython tutorial and cookbook
http://www.bioinformatics.org/bradstuff/bp/tut/Tutorial.html
Huge collection of Python tutorial
http://www.awaretek.com/tutorials.html
What’s wrong with Perl
http://www.garshol.priv.no/download/text/perl.html
20 Stages of Perl to Python conversion
http://aspn.activestate.com/ASPN/Mail/Message/python-list/1323993
Why Python
http://www.linuxjournal.com/article/3882
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some papers
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Bassi S. (2007)
A Primer on Python for Life Science Researchers.
PLoS Comput Biol 3(11): e199. doi:10.1371/journal.pcbi.0030199
Mangalam H. (2002)
The Bio* toolkits--a brief overview.
Brief Bioinform. 3(3):296-302.
Fourment M., Gillings MR. (2008)
A comparison of common programming languages used in bioinformatics.
BMC Bioinformatics 9:82.
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to whom it may concern
NP = Non-Programmer
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NPs who don’t use Perl yet
NPs who want to see the light
NPs who want to give their code away
without being rightfully ashamed
Matlab aficionados
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one of ten Perl myths
http://www.perl.com/pub/a/2000/01/10PerlMyths.html
“…we can happily consign the idea that ‘Perl is hard’ to mythology.”
Swap two sections of a string: “aaa:bbb” -> “bbb:aaa”
“…Perl works the way you do…”
while (<>) {
s/(.*):(.*)/$2:$1/;
print;
}
while (<>) {
chomp;
($first, $second) = split /:/;
print $second, ":", $first, "\n";
}
“…That's one, fairly natural way to think about it…”
for line in file:
line = line.strip()
first, second = line.split(‘:’)
print second+’:’+first
from re import sub
for line in file:
print sub(‘(.*):(.*)’, r’\2:\1’, line)
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camel chaos
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does not scale well
complex syntax
cryptic commands
does not encourage clear code
difficult to read/maintain
hard to understand the principles
error prone
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no check of subroutine arguments
variables are global by default
…
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why Python
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overcome the complexity wall
many, excellent scientific libraries
clear, easy to learn syntax
hard to do it wrong
does not require prior suffering/experience
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my bias
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R&D: C/C++ ->
applied ML in robotics, image processing, quality control
SW Development: Java ->
Speech Processing, Data Mining
Computational Biology: Java, Python
Other languages I played with:
Ada, APL, Basic, MatLab, Modula, Pascal, Perl, Prolog, R,
Groovy, Forth, Fortran, Scala, Assembly code
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