Python 2x4

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Scientific Computing in Computer Science, Technische Universitat Munchen

Scientific Computing in Computer Science,Technische Universitat Munchen

Scripting with Python... and beyond

Compact Course @ GRS

Tobias Neckel

June 03 - 07, 2013

Tobias Neckel: Scripting with Python... and beyond

Compact Course @ GRS, June 03 - 07, 2013 1


Part I

Python Overview




What Python is all about. . .

Python Invented in 1990 as teaching language

Designed for clearness and readability

Named after Monty Python (not the snake)





Python is. . .

High-level (really high-level)

Truly object-oriented

Interpreted

Scalable

Extensible

Portable, available on Windows, Linux, Mac OS X, Amiga, HPCmachines and clusters, web servers, Palm and other Handhelds,Nokia Mobiles, .NET virtual machines, . . .

Versatile

Easy to learn, understand, use, and maintain (really!)

Free, open-source

. . .





Suitable for

OS scripting (Python beats Bash ;-))

Internet Programming

Scientific Computing (up to whole Tsunami Simulations)

Parallelisation

GUI (Tkinter)

Visualisation

Rapid prototype development

. . . and much, much more!





Some more features

Dynamically typed

Automatic garbage collection

Different programming paradigmes possible (procedural, OO,functional, aspect oriented, . . . )





Some more features

Dynamically typed

Automatic garbage collection

Different programming paradigmes possible (procedural, OO,

functional, aspect oriented, . . . )Note

Were assuming Python 2.5.X, 2.6.X, or 2.7.X

The current version Python 3.X requires few changes




Requirements

To be able to use all examples you require.. .

IPython (callipython)

NumPy and SciPy

Pylab (as it ships with Matplotlib)

Tkinter

swig (Simplified Wrapper and Interface Generator) independent of Python



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Part II

Hands On. . .




Lets get started. . .

Start the Python interpreter

At prompt >>> type command, press to confirm

python

P y t ho n 2 . 7 .3 ( d e fa u lt , A u g 1 2 0 12 , 0 5 : 14 : 3 9)

[ G C C 4 . 6 . 3 ] o n l i n ux 2

T y pe " h e l p " , " c o p y r ig h t " , " c r e d i t s " o r " l i c e ns e " f o r

mo re in fo rm at io n .

> > > h e lp

T y pe h e lp ( ) f o r i n t e r a c ti v e h el p , o r h e lp ( o b j e ct ) f o r

h e lp a b ou t o b j ec t .

> > > h e lp ( )

W el c om e t o P yt h on 2 .7 ! T hi s i s t h e o n l in e h e l p

u t i l i t y . [ . . . ]




Getting help

Vast online documentation at http://docs.python.org/

Interactive using

help()for interactive help, help(modules)for a list of all available modules help(object|command)for help on an object or command

Literature

David M. Beasley: Python - Essential Reference,Addison-Wesley Professional, 4th edition, 2009

Hans Petter Langtangen: A Primer on ScientificProgramming with Python, Springer, 2009




A first Hello World!

Python simplify your Code

Just type

>> > print " H e l l o W o r l d ! "

H e l lo W o rl d !

Compare with Java, e.g.:

p u b li c c l a ss H e l l o {

p u b li c s t a ti c v o id m a in ( S t r i n g a r g v [ ] ) {

S y s t e m . o u t . p r i n t l n ( " H e l l o W o r l d ! " );

}

}

j a v a c H e l l o . j a v a

j a va H e l lo

H e l lo W o rl d !




Statements and assignments

> > > 3 + 4 * * 2 / 8 + 1

> > > ( 6 * 3 . 5 ) * 2 - 5

> > > 1 0 e -4

> > > a = 1 7

> >> a

> > > a - 1 .5

> > > b = " H e l l o W o r l d ! "

>> > print b

>> > print a , b , ( 4 + 5 ** 0 . 5 )

assignment: variableName = expression (different to math. =)

Interactive session shows return values

printprints variables and expressions as string




3.5 Ways to Python

1. Start the Python interpreter with python

2. Use IPython: ipython

3. Run Python on a file

3.5. Execute as a script




2. IPython

i p y t h o n

P y t ho n 2 . 7. 3 ( d e fa u lt , A u g 1 2 0 12 , 0 5 : 14 : 3 9)

T y pe " c o p y ri g h t " , " c r e d i ts " o r " l i c en s e " f o r m o re

i n f o r m a t i o n .

I P y th o n 0 . 1 3. 2 . r c 2 - - A n e n h an c e d I n t e ra c t iv e P y t ho n .

? -> I nt ro du cti on and ov er vi ew of IPython s

f e a t u r e s .

% q u i c kr e f - > Q u ic k r e f er e n ce .

h el p - > P yth on s o wn he lp sy st em .

o b je c t ? - > D e t ai l s a b o ut o bj ec t . ? o b j ec t a ls o

w o rk s , ? ? p r i nt s m o re .

I n [ 1 ] : p r i nt " H e l lo W o r ld ! "

H e l lo W o rl d !




2. IPython

Highlights

Enhanced interactive shell

Additional shell syntax

magic functions, starting with % such as %psearchtosearch for function in namespace

Access shell commands %cd Run scripts with run filename.py Log session, define macros, . . . Pretty printing, toggle with %Pprint

Syntax highlighting

Tab completion, string completion

History

Access previous command blocks

Automatic indentation



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3. Run Python on a File

Filesquare_me.py:

print 6**2

Then run

p y t h o n s q u a r e _ m e . p y

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3.5. Execute as a Script

Shell script as before

Just tell shell to execute python:

# ! / u s r / b i n / p y t h o n

print 6**2

Then set executable flag and run

c h m od u + x s q u ar e _ me . p y

. / s q u a r e _ m e . p y

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Part III

Data Types and Control Structures




Built-in Python Types

Numeric Types bool boolean type

print T r ue , F a ls e

T r ue = = T r u e

T r ue ! = T r u e

int integer

1+5-12

Attention integer division: digits after the comma get lost!

> > > 5 / 3

1

long arbitrary-precision integer

1 2 3 4 5 * * 1 0 0




Numeric Types (cont.) float floating point (double precision)

3 . 1 4 1 5 9 2 6 5 * 5 . 6

1 . 5 e - 1 0

complex complex numbers

1 + 4 j

c = c o m pl e x ( 2 , 3)

print c

d = 2 * ( c * * 3 - 3 j )

print d

d . r e a l

d . i m a g

None type None special type (undefined)




General Remarks Everything is an object (int, float, tuple, classes, . . . ) Thus everything can have attributes and methods

c = c o m pl e x ( 2 , 3)

print c . r e al , c . i m ag

Dynamic typing: Type of a variable determined duringassignment

Automatic conversion where necessary and possible

a = 1 23 4

t y p e ( a )

b = 1 0 0

t y p e ( b )

a = 1 2 34 * *1 0 0

t y p e ( a )

b = b * 1. 0 # eq u al s b = fl o at ( b ) *1 .0

t y p e ( b )




Built-in Sequences

Strings stringtype Sequence of characters Single, double or triple double (multiline) quotes

" . . . t h e r e l i v e d a h o b b i t . "

" a h o b b i t "

a " h o b b i t "

a \ h o b b i t \ " "" I n a h ol e i n t he g r ou n d

t h er e " l i v ed " a h o b bi t " " "

Concatenation

s1 = " I n a h o l e i n t h e g r o u n d "

s2 = " t h e r e l i v e d a h o b b i t "

s = s 1 + + s2

print s




Built-in Sequences Strings (2)

Replication

" H i ! " *3

Indexing and Slicing (immutable sequence type)

s = " H e l l o H o b b i t "

s [ 3 ]

s [ - 2 ]

s [ 2 : 4 ]

s [ 6 : ]

s [ : 6 ]

s [ 0 : - 1 : 2 ] # s tr i de 2

s [ 0 : : 2 ]

s [2] = 4 # e r r or

l e n ( s )



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Built-in Sequences Strings (3)

String formatting using %

" B i l b o s % d . b i r t h d a y " % ( 1 11 )

" F r o d o , % s , a n d B i l b o a t e % f a p p l e s " %( " S a m " ,1.5)

Some format modifiers

% 0 5 d % ( 13 ) # f i l l 0

% - 5 d % ( 13 ) # l e ft j u s ti f i ed

% + 5 d % ( 13 ) # s ig n

% d % ( 1 3) # s ig n ed i n t eg e r

% e % ( 1 3) # f l o a ti n g p o in t e x p o n en t i a l

% g % g , % f % ( 13 , 1 e -6 , 1 e -6 )

% s % ( h i ) # s t r in g

% % # e s ca pe %




Built-in Sequences

Tuples

Sequences of arbitrary objects (,)

Immutable

Indexing and slicing as before

l = ( 1 , )

l = ( 1 , " t w o " , ( 3 , 4 , 5) )

l [ 0 ]

l [ - 1 ]

l [1] = 2 # e r r or

l e n ( l )

mi n (l ) # h e re : n u m be r s s m al l e r th a n s tr i n gs

l = ( " H e l l o " , " H o b b i t " )mi n (l )

ma x (l )

l 2 = l + ( 6 ,7 ,8 )




Built-in Sequences

Lists

Sequences of arbitrary objects [,]

Mutable

l = [ 1 , " t w o " , ( 3 ,4 , 5) , 5 ]

l [ 0 ]l [ - 1 ]

l [1 ] = 2 # w o rk s !

l e n ( l )

Operations on lists

l = [ 0 , 1 , 2 ,3 , 4 , 5 , 6 ,7 , 8 , 9]

l [ 2: 4 ] = [ 10 , 1 1]

l [ 1 :7 : 2] = [ -1 , - 2, - 3]

de l l [ : : 2 ]




Built-in Sequences

Lists (2) List methods

l = [ 0 ,1 , 2 ,3 ]

l . a p p e n d ( " f o u r " )

l . e x t e n d ( [ 5 , 6 , 7 , 8 , 9 ] )

l . i n s e r t ( 8 , " f o u r " )

l . c o u n t ( " f o u r " )

l . s o r t ( )

l . r e v e r s e ( )

l . r e m o v e ( " f o u r " )

l . p o p ( )

Integer ranges: rangefunction

r a n g e ( 1 0 )

r a n ge ( 5 , 1 0 )

r a n ge ( - 1 0 , 2 0 , 3 )




Control FlowGeneral

Indentation used to group blocks!

Code within same block has to be same level

Needs getting used to, but encourages readable code

if-statement

if x < y :

print " x i s s m a l l e r "

print x

elif x = = y :

print " b o t h a r e e q u a l "

else :

print " y i s s m a l l e r "

print y




Comparison and Equality

Check for equality

" B i l b o " == " F r o d o "

" B i l b o " != " F r o d o "

Comparison

" B i l b o " < " F r o d o "

" B i l b o " > " F r o d o "

" B i l b o " = " F r o d o "

isand in

" B i l b o " is " F r o d o " # o b j ec t i d e nt i t y

" B i l b o " in [ " F r o d o " , " S a m " , " B i l b o " ] # m e m b er s h i p




Comparison and Equality (2)

Combining and grouping (and, or,not)

if ( " B i l b o " != " F r o d o " a n d n o t (1 > 2 or 2 > 3 )) :

print " S a m w a s h e r e "




Control Flow - for

Pythons for iterates over the items of a sequence type

fo r i in r a n g e ( 5 , 1 0 ) :

print " l o o p i n d e x : " , i

a = ( "a " , " t u p l e " , " w i t h " , 5, " w o r d s " )

fo r i in a:

print i



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Control Flow - break and while

breakbreakes out of the enclosing loop (foror while) continuecontinues with the lext iteration of the loop

a = ( " l e t " , " u s " , " f i n d " , " B i l b o " , " a g a i n " )

fo r word in a :

if w o rd = = " B i l b o " :

print " f o u n d B i l b o "

break

print word

whileloops until condition isFalse

a = 2 04 8; ex p = 0

while a > 1:

a / = 2 # a = a / 2

exp+=1 # exp = exp + 1

print a , "= " , 2, "^ " , e xp




Functions (and Procedures)

Functions are defined using def No return statement means returning None Call by reference (Note: Assignment creates a new local object)

de f h i ( ) :

print " H e l l o W o r l d ! "

de f f a c t o r i a l ( n ) :

f a c = 1

fo r i in r a n g e ( 2 , n + 1 ) :

f ac = f ac * i

return fa c

Functions are objects and can be assigned, too

f = f a ct o ri a l

f ( 3 )




Functions (2)

Default arguments

de f p r i n t m e ( s = " F r o d o " ):

print s

p r i n t m e ( )p r i n t m e (" B i l b o " )

Keyword arguments

de f e xp ( b a s i s , e x p o n e n t ) :

return b a s i s * * e x p o n e n t

e x p ( b a s i s = 2 , e x p o n e n t = 1 0 )

e x p ( e x p o n e n t = 1 0 , b a s i s = 2 )




Up to now...

Variables

Numeric types Sequence types (str, tuple, list; more tomorrow)

if

comparison

for, while, break, continue

Functions and parameters




Part IV

More on Python




More on StringsSpecial string methods (excerpt)

s = " F r o d o a n d S a m a n d B i l b o "

s . i s l o w e r ( )

s . i s u p p e r ( )

s . s t a r t s w i t h ( " F r o d o " ) # t r y s . s t a r t s w it h ( " F r o do " , 2 )

s . e n d s w i t h ( " B i l b o " )

s = s . s tr i p ()

s . u p p e r ( )

s = s . l ow e r ()

s . c a p i t a l i z e ( ) # c a p it a l i ze f i r st c h a ra c t er

s = s . c e n te r ( l e n ( s )+ 4 )# c e n te r ( p a d di n g d e f au l t : s p a c e )

s . l s t r i p ( )

s . r s t r i p ( " " )

s = s . s tr i p ()

s . f i n d ( " s a m " )

s . r f i n d ( " a n d " )




More on Strings (2)

Searching, splitting and joining (excerpt)

s . f i n d ( " s a m " )

s . r f i n d ( " a n d " )

s . r e p l a c e ( " a n d " , " o r " )

s . s p l i t ( ) # o r s . s p l it ( N o n e ) ; a r b i tr a r y n u m b . w h i t e sp .

s . s p l i t ( " " )

s . s p l i t ( " a n d " )s . s p l i t ( " a n d " , 1)

s = " " " L i n e

by

L i n e " " "

s . s p l i t l i n e s ( )

" , " . j o i n ( [ " s e q u e n c e " , " o f " , " s t r i n g s " ])




More on Built-in Sequences

Dictionaries

Map keys to values, arbitrary types

Only immutable objects as keys

Can serve as database

d = {}

d[ " B i l b o " ] = " H o b b i t "

d[ " E l r o n d " ] = " E l f "d [ 42 ] = 1 23 4

d . h a s _ k e y ( " B i l b o " )

d . k e y s ( ) # u n o rd e r e d

d . i t e m s ( )

d . v a l u e s ( )

de l d [ 4 2 ]

d . c l e a r ( )



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More on Functions

Functions have to be defined before actually called for the firsttime

Note: Python is an interpreted language

Variables

Variables defined or assigned to in functions have local scope

Global variables (surrounding context) can be accessed

To modify global variables use global

c ou nt = 0

.. .

de f c o u n t _ i t ( n ) :global count

c o un t + = 1

In general: avoid global variables (pass as params instead)




Call by Reference vs. Call by value

Call by reference:address (id) of parameter is handed over

Call by value: value of parameter is handed over

In Python: always call by reference

But: assignment changes reference within function

>> > de f a d d _ o n e ( x ) :

> >> x = x + 1

>> >

> >> x = 3

> > > a d d _o n e ( x )

> >> x

3




Call by Reference vs. Call by value (2)

After assignment: local variable references to a new object.

Using methods, the original object can be modified.

>> > de f a p p e n d 1 ( l ) :>> > l = l + [4]

>> >

>> > de f a p p e n d 2 ( l ) :

> >> l . ap pe nd ( 4)

>> >

> > > l = [ 1 ,2 , 3]

> > > a p p e n d 1 ( l ); l

[ 1 , 2 , 3 ]

> > > a p p e n d 2 ( l ); l

[ 1 , 2 , 3 , 4 ]




More on Functions (2)

Return values

Functions can have multiple return values (returned as tuple)

de f g e t _ h o b b i t s ( ) :

return " B i l b o " , " F r o d o "h = g e t _ ho b b i ts ( )

( a , b ) = g e t _h o b b it s ( )

Assignment rules correspond to slice assignment

l = [ 4 , 2 ]

( a , b ) = l # i m p li c i t t y pe c o n v er s i o n

a , b = l

l [ 0 :3 ] = ( 3 , 2 ) # i m p li c i t t y pe c o n v er s i o n




More on Functions (3)

Docstrings

Functions (and classes, modules, ...) can provide help text

String after function header (can be multiline)

de f a n s w e r ( ) :

" R e t u r n s a n a n s w e r t o a q u e s t i o n "

print " a n s w e r "

h e l p ( a n s w e r )




Arithmetic Operations

Classical operations

x + y # A d d it i o n

x - y # S u b t ra c t i on

x * y # M u l t ip l i c at i o n

x / y # D i v is i o n

x / / y # T r u nc a t ed d i v i s io n

x * * y # E xp o n e nt i a t io n

x % y # M o d ul o

x -= 2 ; x *= 4; .. .

Division differs for int and float(Python < 3.0)

7/ 4

7.0/4




More Operations

General functions

a b s ( x )

d i v mo d ( x , y ) # ( x // y , x % y )

p o w (x , y [ , m o d ul o ] ) # x * * y % m o d ul o

r o u nd ( x , [ n ] ) # r ou n d t o 1 0* *( - n )

Operations on integers

x < < y # L ef t sh i ft

x > > y # R ig ht s h if t

x & y # B i t wi s e a n d

x | y # B it w is e o r

x ^ y # B i t wi s e x o r

~x # B i t wi s e n e g at i o n




File I/O

Opening files

Create file object (text files)

f d = o pe n (" t e s t f i l e . t x t " ) # r ea d

f d = o pe n (" t e s t f i l e . t x t " , r ) # r e ad

f d = o pe n (" t e s t f i l e . t x t " , w ) # w r i te

f d = o pe n (" t e s t f i l e . t x t " , a ) # a p p e nd

Create file object (binary files)

f d = o pe n (" t e s t f i l e . t x t " , r b ) # r e ad

f d = o pe n (" t e s t f i l e . t x t " , w b ) # w r i te

f d = o pe n (" t e s t f i l e . t x t " , a b ) # a p p e nd

openhas more options (encoding, how to handle newlines, . . . )



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File I/O (2)

Methods of file objects

Reading

f d . r e a d ( ) # a ll

f d . r e a d ( n ) # n B yt es

f d . r e a d l i n e ( ) # o n e l in e

f d . r e a d l i n e s ( ) #

Writing

f d . w r i t e ( " N e w T e x t \ n " )

f d . w r i t e l i n e s ( [ " f i r s t l i n e \ n " , " S e c o n d \ n " ])

Dont forget to write newlines

Closing

f d . c l o s e ( )




File I/O (3)

Iterating over textfile

forloop over file line by line

f d = o pe n (" f u l l t e x t . t x t " )

fo r line in fd : # r at h e r th a n : i n fd . r e a d li n e s ( )

print line

# o r:

while T r u e :

l i ne = f d . r e a dl i n e ( )

i f n ot l i n e :

break

print line




File I/O (3)

Iterating over textfile

forloop over file line by line

f d = o pe n (" f u l l t e x t . t x t " )

fo r line in fd : # r a th e r t ha n : in f d . r ea d l in e s ( )

print line# o r:

while T r u e :

l i ne = f d . r e ad l i ne ( )

i f n ot l i n e :

break

print line

Some more functions on file objects

fd.tell() get current file position

fd.seek(offset) set file to position

fd.flush() flush output buffer. Note: buffered for efficiency




Getting more. . .Modules

Outsource functionality in separate.py files Import them as library module Example (tools.py):

" " " T hi s m o du l e p r o vi d es s o me h e lp e r t o ol s .

T r y i t . " " "

c o un t e r = 4 2

de f r e a d f i l e ( f n a m e ) :

" R e a d t e x t f i l e . R e t u r n s l i s t o f l i n e s "

f d = o p en ( f n am e , r )

d a t a = f d . r e a d l i n es ( )

f d . c l o s e ( )

return data

de f d o _ n o t h i n g ( ) :

" D o r e a l l y n o t h i n g "

pass




Modules (2) Import module

import tools

t o o l s . d o _ n o t h i n g ( )

print t o o l s . c o u n t e r

Import module and change name

import t o ol s a s t

t . d o _ n o t h i n g ( )

Import selected symbols to current namespace

from tools import d o _ n o t hi n g , r e a d f i l e

from tools import c o u nt e r a s c n tr

d o _ n o t h i n g ( )

print cntr




Modules (3) Import all symbols to current namespace

from tools import *

d o _ n o t h i n g ( )

print c o u n t e r

Modules can control which symbols are imported byfrom module import *:

# m o d ul e t o o ls . p y

_ _ al l_ _ = [ r e a d f i l e , c o u n t e r ]

Then do_nothing()is unknown after import *




Modules (3)

Import all symbols to current namespace

from tools import *

d o _ n o t h i n g ( )

print counter

Modules can control which symbols are imported byfrom module import *:

# m o d ul e t o ol s . p y

_ _ al l __ = [ r e a d f i l e , c o u n t e r ]

Thendo_nothing()is unknown after import *

Inspect namespace Inspect namespace of module with

d i r ( t o o l s )




Modules (4)

Getting help

Access docstrings

import tools

h e l p ( t o o l s )

h e l p ( t o o l s . d o _ n o t h i n g )



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Modules (4)

Getting help

Access docstrings

import tools

h e l p ( t o o l s )

h e l p ( t o o l s . d o _ n o t h i n g )

Execute module as main program

tools.pyshould serve as program and module

# t o o ls . p y

.. .

if _ _ n a me _ _ = = _ _ m a i n _ _ :print " t o o l s . p y e x e c u t e d "

else :

print " t o o l s . p y i m p o r t e d a s m o d u l e "




Modules (5)

Reload module

When debugging a module reload with reload(Python

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Standard Input, Output, and Error

Module sys provides three standard file objects

sys.stdin read only sys.stdout,sys.stderr write only

import sy s

s y s . s t d o u t . w r i t e ( " E n t e r l i n e : \ n " ) # = p r in t " . . ."

l i ne = s y s . s td i n . r e ad l i ne ( )

# o r : l i n e = r a w _i n p ut ( " E n t er l i ne : \ n " )

if e r r o r :

s y s . s t d e r r . w r i t e ( " E r r o r ! \ n " )

writedoes not add newlines

raw_input([text])strips endling newline

Input and output buffered




More on Lists

List comprehension

Short notation to create lists

e v e n_ s q u ar e s = [ ]

fo r i in r a n g e ( 1 0 ) :

if i %2 = = 0 :

e v e n _ s q u a r e s . a p p e n d ( i * i )

e v e n_ s q u ar e s = [ i * * 2 fo r i in r a n g e ( 1 0 ) if i % 2 = = 0 ]

Compare:

i2 | i {0, . . . , 9}, ieven




More on Lists

List comprehension

Short notation to create lists

e v e n _s q u a re s = [ ]

fo r i in r a n g e ( 1 0 ) :

if i %2 = = 0 :

e v e n _ s q u a r e s . a p p e n d ( i * i )

e v e n _s q u a re s = [ i * * 2 fo r i in r a n g e ( 1 0 ) if i % 2 = = 0 ]

Compare:

i2 | i {0, . . . , 9}, ieven

Can contain more than one for ... in ... [if ...]

[ ( x , y . u p p e r ( ) ) fo r x in r a n g e ( 4 ) if x % 2 = = 0

fo r y in [ "a " , "b " , "c " ]]




More on Lists (2)

Advanced slice assignement Note: assigning slices of mutable sequences can change size

l = r an ge ( 5 )

l [ 1 : 3] = [ 7 , 8 , 9]

l [ 4 :6 ] = [ 6]




More on Lists (2)Advanced slice assignement

Note: assigning slices of mutable sequences can change size

l = r a ng e ( 5)

l [ 1 : 3] = [ 7 , 8 , 9]

l [ 4: 6 ] = [ 6]

range and xrange range([i,] j [, stride])creates list Memory allocated for whole list, even when only iterating over

them, especially in loops xrangeobject calculates values when accessed (generator)

fo r i in r a n g e ( 6 5 0 0 0 0 ) :

d o _ s o m e t h i n g ( )

fo r i in x r a n g e ( 6 5 0 0 0 0 ) :

d o _ s o m e t h i n g ( )




Even more on Built-in Sequencesset and frozenset

setis mutable,frozensetis not

s = s e t ([ 3 , 1 ,2 , 3 , " f o o " ,2])

l e n ( s )

l = [ 2 ,8 , 7] # a n y i t e ra b l e s e q ue n c e

s . d i f f e r e n c e ( l )

s . i n t e r s e c t i o n ( l )

s . u n i o n ( l )

s . s y m m e t r i c _ d i f f e r e n c e ( l )

s . i s s u b s e t ( [ 3 , " f o o " ])

s . i s s u p e r s e t ( [ 3 , " f o o " ])

Forset

s . a d d ( 4 2 )

s . r e m o v e ( 3 )s . i n t e r s e c t i o n _ u p d a t e ( l ) # a n d mo r e m et h o ds . . .




Even more on Functions

Anonymous functions

Can be defined using keywordlambda

Lambda functions allow functional programming

de f i n c ( i ) :

return i +1

i nc = lambda ( i ) : i + 1( lambda i : i + 1 ) ( 4)

Common use: map function on list items / filter list

l = r a ng e ( 10 )

ma p ( lambda x : x * x + 1 , l )

f i l t e r ( lambda x : x % 2= =0 , l )




Part V

Object Oriented Programming



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What is an object?




What is an object?

a car

a cat

a chair

...




What is an object?

a car

a cat

a chair

...

a molecule

a star

a galaxy

...




What is an object?

a car

a cat

a chair

...

a molecule

a star

a galaxy

...

anything that represents a real thing

anything that represents an abstract thing

anything which has some properties




How to Program Object Oriented

Change your way of thinking

Change your point of view

It is not just a technical question!

In Python?

You do it all the time

You just dont know it

In Python, everything is an object (event int)

a =4

a . _ _ s t r _ _ ( )




Theory: Classes and ObjectsClasses

A class is similiar to the definition of a type

Specifies properties of the objects to be created

Data to be stored once for all objects (class/static variable)

Data to be stored in each object (member variables)

Operations to be done with objects (methods)

Represents a class of things/objects




Theory: Classes and Objects

Classes

A class is similiar to the definition of a type

Specifies properties of the objects to be created

Data to be stored once for all objects (class/static variable)

Data to be stored in each object (member variables)

Operations to be done with objects (methods)

Represents a class of things/objectsInstances / Objects

An instance/object is a concrete thing of the type of a class

A class specifies properties, an object has specific values for thespecified properties

For each class, there can be an arbitrary number of objects

Each object belongs exactly to one class (exception:polymorphism)




Theory: Constructor, Destructor

When creating an instance ...

Memory is allocated A variable for storing the object is created Perhaps some things are initialized The initialisation is done with a constructor (__init__(self,...))

When a variable is not used any more ... Memory has to be freed

Perhaps some things have to be cleaned up The destructor (__del__(self,...)) is called BUT: No guarantee at which time it is called

class E x a m p l e :

de f _ _ i n i t_ _ ( s e l f , . . . ) :

d o _ s o m e t h i n g

de f _ _ d e l _ _ ( s e lf , . . . ) :




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First Class Example

# ! / u s r / b i n / p y t h o n

class G R S E m p l o y e e ( o b j e c t ) :

n u m _ em p l o ye e s = 0

de f _ _ i n i t_ _ ( s e l f , n a m e ) :

s e lf . n a m e = n a me

G R S E mp l o y ee . n u m _ e m pl o y ee s + = 1

de f g e t N a m e ( s e l f ) :

return s e l f . n a m e

@ s t a t i c m e t h o d

de f n u m P e o p l e ( ) :

return G R S E m p l o y e e . n u m _ e m p l o y e e s

p e r so n 1 = G R S Em p l o ye e ( " J o h n " )p e r so n 2 = G R S Em p l o ye e ( " M a r y " )

print p e r s o n 1 . g e t N a m e ( )

print G R S E m p l o y e e . n u m P e o p l e ( )




Theory: self

Usage of an object

Access to methods: object.method(...)

Example: list.append(x)

Access to variables: object.variable

Example: complex.real

Access witin methods

Concrete object is created outside the class definition

Methods of a class do not know the object name

All methods get additional formal parameter self

selfalways is the first formal parameter, but is skipped at a call(actual parameter)

Within methods: access to other methods and variables viaself.variableand self.method(), resp.




Theory: Methods

. . . implement the behaviour of objects.

. . . represent all types of changes of an object after initialisation.

accessor methods: give info on state of an object

mutator methods: change state of an object

change (at least) one object/member variable




Procedural Approach to Operate an Oven

# ! / u s r / b i n / p y t h o n

de f d o B a k i n g ( t e m p e r a t ur e , m o d e ) :


o v e n te m p e ra t u r e = 1 8 0

o v en m od e = 2

d o B a k i n g ( o v e n t e m p e r a tu r e , o v e n m o d e )

If ive got a whole bakery?

o v e n te m p e ra t u r es = [ ]

o v e nm o d es = [ ]

o v e n t e m p e r a t u r e s . a p p e n d ( 1 9 0 )

o v e n m o d e s . a p p e n d ( 2 )

.. .

fo r i in r a n g e ( l e n ( o v e n t e m p e r a t u r e s ) ) :

d o _ b a k i n g ( o v e n t e m p e r a t u r e s [ i ] , o v e n m o d e s [ i ] )




Object Oriented Approach to Operate an Oven

# ! / u s r / b i n / p y t h o n

class O v e n ( o b j e c t ) :

de f _ _ i n i t _ _ ( s e l f , t e m p e r at u r e , m o d e ) :

s e l f . t e m p e r a t u r e = t e m p e r a t u r e

s e l f . m o d e = m o d e

de f d o B a k i n g ( s e l f ) :


my Ov en = Ov en (1 80 ,2 )

my Ov en . do Ba ki ng ()

Again a whole bakery

o ve n s = [ ]

o v e n s . a p p e n d ( O v e n ( 1 9 0 , 2 ) )

.. .

fo r oven in o v e n s :o v e n . d o B a k i n g ( )




What Are the Differences?

Procedural approach

Procedures specify how to produce something

When implementing them, you have to think of actions

You have to care about storing the data yourself

Object oriented approach

Objects specify things (real or abstract)

When implementing them, you have to think of the thing and itsproperties

All data is stored in the object itself

Whenever lots of data elements are associated with an action,try to think object oriented




Inheritance

Classes can inherit from a base class / superclass This makes them a derived class / subclassof the superclass All classes can be specialized they become superclasses All classes together form a class hierarchy (taxonomy) Properties of the superclass can be taken over or can be

redefined

# ! / u s r / b i n / p y t h o n

class M a s t e r S t u d e n t ( G R S E m p l o y e e ) :de f _ _ i n i t __ ( s e lf , n am e , t h e si s ) :

s e lf . t h e s is = t h e si s

G R S E m p l o y e e . _ _ i n i t _ _ ( s e l f , n a m e )

de f p r i n t I n f o ( s e l f ) :

print " % s w o r k s o n % s " % ( s e lf . n a me , s e lf . t h e s is )

p e r so n 3 = M a s t er S t u de n t (" T e r r y " , " T e r r y s t h e s i s t o p i c " )

p e r s o n 3 . p r i n t I n f o ( )



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Module math (2)

Trigonometric functions assume radians

c o s ( x ); c o sh ( x ) ; a c os ( x )

s i n ( x ); . . .

t a n ( x ); . . .

d e g r e e s ( x ) # r a d - > d eg

r a d i a n s ( x ) # d e g - > r ad




Module math (2)


c o s ( x ); c o sh ( x ) ; a c os ( x )

s i n ( x ); . . .

t a n ( x ); . . .

d e g r e e s ( x ) # r ad - > d eg

r a d i a n s ( x ) # d eg - > r ad

inf/nan

f l o a t (" i n f " )

f l o a t (" - i n f " )

f l o a t (" n a n " )




Module math (2)


c o s ( x ); c o sh ( x ) ; a c os ( x )

s i n ( x ); . . .

t a n ( x ); . . .

d e g r e e s ( x ) # r a d - > d eg

r a d i a n s ( x ) # d e g - > r ad

inf/nan

f l o a t (" i n f " )

f l o a t (" - i n f " )

f l o a t (" n a n " )

Use module cmathfor complex numbers




Now to Real Maths. . .

Standard sequence types (list, tuple, . . . )

Can be used as arrays

Can contain different types of objects

Very flexible, but slow Loops are not very efficient either

For efficient scientific computing, other datatypes and methodsrequired




Now to Real Maths. . .

Standard sequence types (list,tuple, . . . )

Can be used as arrays

Can contain different types of objects

Very flexible, but slow Loops are not very efficient either

For efficient scientific computing, other datatypes and methodsrequired

Modules

NumPy

Matplotlib

SciPy




NumPy




Module numpy

Homogeneous arrays

NumPy provides arbitrary-dimensional homogeneous arrays

Example

from numpy import *

a = a r r ay ( [ [ 1 , 2 , 3] , [ 4 , 5 , 6 ]] )

print at y p e ( a )

a . s h a p e

print a [ 0 , 2 ]

a [ 0 ,2 ] = - 1

b = a * 2

print b




Array creation

Create from (nested) sequence type Direct access with method[]

a = a r ra y ( [ 1 ,2 , 3 , 4 , 5 , 6 , 7 ,8 ] )

a [ 1 ]

a = a r ra y ( [ [1 , 2 , 3 , 4 ] , [5 , 6 , 7 , 8 ]] )

a [ 1 , 1 ]

a = a r r a y ( [ [ [ 1 , 2 ] , [ 3 , 4 ] ] , [ [ 5 , 6 ] , [ 7 , 8 ] ] ] )

a [ 1 , 1 , 1 ]



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Array creation

Create from (nested) sequence type Direct access with method []

a = a r r ay ( [ 1 , 2 , 3 ,4 , 5 , 6 , 7 , 8] )

a [ 1 ]

a = a r r ay ( [ [ 1 , 2 ,3 , 4 ] , [ 5 ,6 , 7 , 8 ] ])

a [ 1 , 1 ]

a = a r r ay ( [ [ [ 1 , 2] , [ 3 , 4 ] ] , [[ 5 , 6 ] , [ 7 , 8] ] ])

a [ 1 , 1 , 1 ]

Properties of arrays

a . n d i m # n u m be r o f d i m e ns i o n s

a . s h a p e # d i m e ns i o n s

a . s i z e # n u m be r o f e l e me n t s

a . d t y p e # d at a t yp e

a . i t e m s i z e # n um b er o f b yt e s




Data Types

Exact, C/C++-motivated type of array elements can be specified

Otherwise, defaults are used

Some types (different storage requirements):

int_,int8,int16,int32,int64, float_,float8,float16,float32, float64, complex_,complex64, bool_, character, object_

Standard python type names result in default behaviour

a r r a y ( [ [ 1 , 2 , 3 ] , [ 4 , 5 , 6 ] ] , d t y p e = i n t )

a r r a y ( [ [ 1 , 2 , 3 ] , [ 4 , 5 , 6 ] ] , d t y p e = c o m p l e x )

a r r a y ( [ [ 1 , 2 , 3 ] , [ 4 , 5 , 6 ] ] , d t y p e = i n t 8 )a r r a y ( [ [ 1 , 2 , 3 ] , [ 4 , 5 , 1 0 0 0 ] ] , d t y p e = i n t 8 ) # w r o ng

a r r a y ( [ [ 1 , 2 , 3 ] , [ 4 , 5 , " h i " ] ] , d t y pe = o b j e ct )

Exception: object_stores pointers to objects




Create Arrays

(Some) default matrices (optional parameter: dtype)

a r a ng e ( [ a , ] b [ , s t r id e ] ) # a s r an ge , 1 D

z e ro s ( ( 3 , 4) )

o n es ( ( 1 , 3 , 4) )e m pt y ( ( 3 , 4) ) # u n i n it i a l iz e d ( f a s t )

l i ns p ac e ( a, b [ , n ] ) # n e q ui d is t an t i n [ a , b]

l o gs p ac e ( a, b [ , n ] ) # 1 0* * a t o 1 0* * b

i d e n t i t y ( n ) # 2d

f r o m f u n c t i o n ( lambda i , j : i + j , ( 3 , 4) , d t y pe = i n t )

de f f ( i , j ) :

return i+ j

f r o m fu n c t io n ( f , ( 3 , 4) , d t yp e = i n t )




Manipulate Arrays

Reshaping arrays

a = a r a ng e ( 1 2 )

b = a . r e s ha p e ( ( 3 , 4) )a . r e s i z e ( ( 3 , 4 ) ) # i n - p l ac e !

a . t r a n s p o s e ( )

a . f l a t t e n ( )

# E x a mp l e u se - c a s e :

a = a r a ng e ( 1 4 4)

a . r e s i z e ( ( 1 2 , 1 2 ) )




Create Arrays (2) Create/Copy from existing data

a = a r a ng e ( 1 2 ); a . r e s iz e ( ( 3 , 4 ))

c o p y ( a )

d i ag ( a ) ; t r il ( a ) ; t r iu ( a )

e m p t y _ l i k e ( a ) # c op y s ha p e

z e r o s _ l i k e ( a )

o n e s _ l i k e ( a )

a = l oa d tx t (" m a t r i x . t x t " ) # f r o m f i le ( ) i f b i n ar y

# p l e nt y o f o p t io n s : c o mm e nt s , d e li m . , u s ec o ls , . . .

Matrix output

a . t o l i s t ( )

s a v e t x t (" m a t r i x . t x t " , a) # t of il e() if b in ar y




Array Access and Manipulation

Typical slicing operations can be used

Separate dimensions by comma

a = a r a ng e ( 2 0 ); a . r e s iz e ( ( 4 , 5) )

a [ 1 ]

a [ 1 : 2 , : ]

a [ : , : : 2 ]

a [ : : 2 , : : 2 ]

a [ : : 2 , :: 2 ] = [ [0 , - 2 , - 4 ] , [ - 10 , - 12 , - 1 4] ]

a [ 1 : :2 , 1 : : 2 ] = - 1* a [ 1 : :2 , 1 : : 2]

Selective access

a [ a > 3 ]

a [a > 3 ] = -1




Array Access

Iterating over entries

fo r ro w in a:

print ro w

b = a r a ng e ( 3 0 ); b . r e s iz e ( ( 2 , 3 , 4) )

fo r ro w in b:fo r co l in r o w :

print co l

fo r entry in a . f l a t :

print entry




Computing with Arrays

Fast built-in methods working on arrays

a = a r a ng e ( 1 2 ); a . r e s iz e ( ( 3 , 4) )

3* a

a * * 2

a + a ^ 2

s i n ( a )

s q r t ( a )

p r o d ( a )s u m ( a )

i t = t r a ns p o s e ( a)

x = a r ra y ( [ 1 , 2 , 3] )

y = a r ra y ( [ 1 0 , 20 , 3 0 ] )

i n n er ( x , y )

d o t ( it , x )

c r o s s ( x , y )



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Computing with Arrays

There is much more. . .

var () cov () std ()

me an () me di an ()

mi n () ma x ()

s v d ( )

t e n s o r d o t ( )

.. .

Matrices (with mat) are subclasses of ndarray, but strictlytwo-dimensional, with additional attributes

m = ma t (a )

m. T # t r a n sp o s e

m. I # i n v er s e

m. A # as 2d ar ra y

m. H # c o n j ug a t e t r a n sp o s e




Submodules

Modulenumpy.random

Draw from plenty of different distributions

More powerful than module random

Work on and return arrays

from n u m p y . r a n d o m import *

b i n o m i a l ( 1 0 , 0 . 5 ) # 1 0 t ri a ls , s u c ce s s 5 0%

b i n om i a l ( 10 , 0 .5 , 1 5 )

r a n di n t ( 0 , 1 0 , 1 5 ) # [ 0 ,1 0) , i nt

r a n d ( ) # [ 0 , 1)r a n d ( 3 , 4 ) # (3 x4 ) array




Submodules (2)

Modulenumpy.linalg

Core linear algebra tools

n o rm ( a ) ; n o rm ( x )

i n v ( a )

s o lv e ( a , b ) # L A PA C K L U d e co m p .

d e t ( a )

e i g ( a )

c h o l e s k y ( a )




Submodules (2)

Modulenumpy.linalg


n o rm ( a ) ; n o rm ( x )

i n v ( a )

s o l ve ( a , b ) # L A PA C K L U d ec o mp .

d e t ( a )

e i g ( a )


Modulenumpy.fft

Fourier transforms




Submodules (2)

Modulenumpy.linalg


n o rm ( a ) ; n o rm ( x )

i n v ( a )

s o lv e ( a , b ) # L A PA C K L U d e co m p .

d e t ( a )

e i g ( a )


Modulenumpy.fft

Fourier transforms

There is more. . .




Matplotlib




Matplotlib

What is it?

Object-oriented library for plotting 2D

Designed to be similar to the matlab plotting functionality

Designed to plot scientific data, built on numpy datastructures

Version Mania

Numpy, scipy, ipython and matplotlib often used together

They somehow depend on each other (e.g. matplotlib usesarrays from numpy)

Pylab is a (unofficial) package containing all four

Depending on your linux distribution, you might have to installdifferent packages

This changes the module names from which you have to import




Several Ways to do the Same

python/ipython interactive

> i p y th o n

import s ci p y , m a t p l o t l i b . p y l a b

x = s c ip y . r a n dn ( 1 0 0 0 0)

ma tp lo tl ib . py la b . hi st (x , 10 0)

> i p y th o n

import n u m p y . r a n d om , m a t p l o t l i b . p y l a bx = n u mp y . r a n do m . r a n dn ( 1 0 0 0 0)

ma tp lo tl ib . py la b . hi st (x , 10 0)

ipython in pylab mode

> i p y th o n - p y la b

x = r a nd n ( 1 0 0 00 )

h i st ( x , 1 0 0)



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Example - First Plot

partially taken fromhttp://matplotlib.sourceforge.net/users/screenshots.html

from pylab import *

x = a r a ng e ( 0 .0 , 2 * pi , 0 . 01 )

y = s in ( x)

p l ot ( x , y , l i n ew i d th = 4 )

p l o t ( x , y )

x l a b e l ( L a b e l f o r x a x i s )

y l a b e l ( L a b e l f o r y a x i s )

t i t l e ( S i m p l e p l o t o f s i n )g r i d ( T r u e )

s h o w ( )




Example Using Subplots

from pylab import *

de f f ( t ) :

s 1 = c o s ( 2* p i * t )

e 1 = e xp ( - t)

return m u l t i p l y ( s 1 , e 1 )

t 1 = a r an g e (0 .0 , 5 .0 , 0 .1 )

t 2 = a r a ng e ( 0 .0 , 5 . 0 , 0 . 0 2 )

t 3 = a r a ng e ( 0 .0 , 2 . 0 , 0 . 0 1 )

s h o w ( ) # g i ve s e rr o r b u t h e lp s ; - )

s u b p l o t ( 2 , 1 , 1 ) # r o ws , c o lu m ns , w h i ch t o s h ow p l ot ( t 1 , f ( t 1 ) , g o , t 2 , f ( t 2 ), k - - )

s u b p l o t ( 2 , 1 , 2 )

p l o t ( t 3 , c o s ( 2 * p i * t 3 ) , r . )




Example Using Subplots

# p r e vi o u s s l i d e c o n t in u e d

s u b p l o t ( 2 , 1 , 1 )g r i d ( T r u e )

t i t l e ( A t a l e o f 2 s u b p l o t s )

y l a b e l ( D a m p e d o s c i l l a t i o n )

s u b p l o t ( 2 , 1 , 2 )

g r i d ( T r u e )

x l a b e l ( t i m e ( s ) )

y l a b e l ( U n d a m p e d )




Example - Histogram

# s ta rt i p yt h on - p yl ab o r u se i m po r ts :

# f r o m m a t p lo t l i b . m la b i m p or t *

# f r o m m a t p lo t l i b . p yp l o t i m p or t *

from numpy import *mu , si gm a = 10 0 , 15

x = m u + s i g ma * r a n d om . r a n d n ( 1 00 0 0 )

n , b in s , p at c he s = h is t (x , 5 0 , n o r me d =1 , \

f a c e c o l o r = g r e e n , a l ph a = 0 . 7 5)

# a dd a be st f it l in e

y = n o rm p df ( b in s , m u , s i g ma )

p l ot ( b i ns , y , r - - , l i n ew i d t h = 1)

a x is ( [ 4 0 , 1 6 0 , 0 , 0 . 0 3] )

p l t . s h o w ( )




SciPy




More than NumPy?

SciPy depends on NumPy

Built to work on NumPy arrays

Providing functionality for mathematics, science and engineering

Still under development

NumPy is mostly about (N-dimensional) arrays

SciPy comprises a large number of tools using these arrays

SciPy includes the NumPy functionality (only one importnecessary)

A lot more libraries for scientific computing are available, some ofthem using NumPy and SciPy

Here, just a short overview will be given

www.scipy.orgfor more material (incl. the content of thefollowing slides)




SciPy Organisation - Subpackages

cluster Clustering algorithmsconstants Physical and mathematical constantsfftpack Fast Fourier Transform routinesintegrate Integration and ordinary differential equation solversinterpolate Interpolation and smoothing splinesio Input and Outputlinalg Linear algebramaxentropy Maximum entropy methods

ndimage N-dimensional image processingodr Orthogonal distance regressionoptimize Optimization and root-finding routinessignal Signal processingsparse Sparse matrices and associated routinesspatial Spatial data structures and algorithmsspecial Special functionsstats Statistical distributions and functionsweave C/C++ integration




Special Functions

Airy functions

Elliptic functions

Bessel functions (+ Zeros, Integrals, Derivatives, Spherical,Ricatti-)

Struve functions

A large number of statistical functions

Gamma functions

Legendre functions

Orthogonal polynomials (Legendre, Chebyshev, Jacobi,...)

Hypergeometric functios

parabolic cylinder functions

Mathieu functions

Spheroidal wave functions

Kelvin functions

...



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Example: Interpolation - Linear

import n u mp y a s n p

import m a t p l o tl i b . p y pl o t a s p l t

from scipy import i n t e r p o l a t e

x = n p . a r an g e ( 0 , 10 )

y = n p . e xp ( - x / 3 .0 )

f = i n t e rp o l a te . i n t e r p1 d ( x , y )

x n ew = n p . a r an g e ( 0 , 9 , 0. 1 )

p l t . p l o t ( x , y , o , x n e w , f ( x n e w ) , - )

p l t . t i t l e ( L i n e a r i n t e r p o l a t i o n )p l t . s h o w ( )




Example: Interpolation - Cubic Spline

import n u mp y a s n p

import m a t p l o tl i b . p y p lo t a s p l t

from scipy import i n t e r p o l a t e

x = n p . a r an g e ( 0 , 2 . 2 5 * n p . pi , n p . pi / 4 )

y = n p . si n ( x)

s p l i n e = i n t e r p o l a t e . s p l r e p ( x , y , s = 0 )

x n e w = n p . a r a n g e ( 0 , 2 . 0 2 * n p . p i , n p . p i / 5 0 )

y n ew = i n t er p o l at e . s p l ev ( x n ew , s p l in e )

p l t . p l o t ( x , y , o , x n e w , y n e w )

p l t . l e g e n d ( [ L i n e a r , C u b i c S p l i n e ])p l t . a x i s ( [ - 0 . 0 5 , 6 . 3 3 , - 1 . 0 5 , 1 . 0 5 ] )

p l t . t i t l e ( C u b i c - s p l i n e i n t e r p o l a t i o n )

p l t . s h o w ( )




Part VII

Misc Modules, Functionality, and More




Module random

Compute and use pseudo-random numbers

from random import *

print r a n d o m ( )

print c h o i c e ( [ 1 , 4 , " H e l l o " ])

(Re)initialize random with seed([x])(def: time)




Module random

Compute and use pseudo-random numbers

from random import *

print r a n d o m ( )

print c h o i c e ( [ 1 , 4 , " H e l l o " ])

(Re)initialize random with seed([x])(def: time)

Random floats

r a n d o m ( ) # [ 0. 0 , 1 .0 )

u n i f o r m ( a , b ) # [ a, b )

e x p o v a r i a t e ( l a m b d ) # [ 0. 0 , + i n f )

n o r m a l v a r i a t e ( m u , s i g m a )

.. .




Module random (2)

Random integers

r a n di n t ( a , b ) # a

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Module subprocess (2)

Example: Call Gnuplot

# ! / u s r / b i n / p y t h o n

import s u b p ro c e s s a s s p

p = s p . Po pe n ( [" g n u p l o t " , " - p e r s i s t " ],

s t d i n = s p . P I P E , s t d o u t = s p . P I P E , s t d e r r = s p . S T D O U T )

p . s t d i n . w r i t e ( " p l o t s i n ( x ) \ n " )

p . s t d i n . f l u s h ( )

r a w _ i n p u t (" P r e s s E n t e r t o c o n t i n u e " )

p . s t d i n . w r i t e ( " p l o t s i n ( x ) , c o s ( x ) \ n " )

p . s t d i n . c l o s e ( )

File objects for stdin and stdout+stderr I/O bufferred (flush()if necessary)




Operating System Services

Moduleos

Interface to OS services Variables

import os

o s . e n v i r o n # e n v i ro n m en t v a r ia b le s , d i ct

o s . l i n e s e p # l i n e s e p ar a ti o n ; \ r \n w i n , \ n l i n ux

o s . n a m e # t o f in d o ut wh at sy s te m

Some general purpose methods

o s . g e t c w d ( )

o s . c h d i r ( p a t h )

o s . g e t g r o u p s ( ) # ( U NI X )

o s . u n a m e ( ) # s y s te m i n f or m a t io n ( U N IX )

o s . t i m e s ( ) # ( u sr , sy s , c _u sr , c _s ys , w ct )

.. .




Operating System Services (2)

Some methods related to files

o s . c h mo d ( p at h , m o de ) # c h m od

o s . c h m o d ( " t m p . p y " , 0 6 6 4) # f o u r d i g i t s r e q u ir e d

l i s t d i r ( p a t h ) # ls

mk di r ( pa th ) # m k d ir

ma ke di rs ( pa th ) # m k di r - p

r e n am e ( s rc , d s t ) # mv

r e m o v e ( p a t h ) # rm

r m d i r ( p a t h ) # r m d ir

r e m o v e d i r s ( p a t h ) # r m - rf

s t a t ( p a t h ) # s t at s ( a ti me , . .. )

w a lk ( p a t h [ , t o p do w n ] ) # t ra ve r se d ir r ec .

# ( d i r pa t h , d i rn a me s , f n a me s ) f o r e a ch d i r




Operating System Services (3)

Submoduleos.path

To manipulate pathnames and check for file properties

a b s p a t h ( p a t h )

b a s e n a m e ( p a t h )d i r n a m e ( p a t h )

e x i s t s ( p a t h )

i s f il e ( p a th ) ; i s di r ( p a th ) ; i s l in k ( p a th )

g e t s i z e ( p a t h )

g e t a t i m e ( p a t h )

j o in ( p a th 1 , p a th 2 , . . .)




Operating System Services (4)Example traversing a directory

# ! / u s r / b i n / p y t h o n

import os

de f p r i n t _ t r e e ( p a t h ) :

" " " P ri n t t h e c o n t e n t s o f t h e d i r e c t o ry s p e ci f i ed

i n p a t h a n d a l l i t s s u b d i r e c to r i e s . "" "

fo r ( d i r p a t h , d i r n a me s , f n a m e s ) in o s . w a l k ( p a t h ) :

# g et t he d i re c to r y l e ve l

l e v el = l e n ( d ir p a th . s p l i t ( os . s e p ) ) -1

# p r i nt d i r e ct o r y

print "| " * l e v e l + " + " + o s . p a t h . b a s e n a m e ( d i r p a t h )

# p r in t a ll f i le s

fo r f in f n a m e s :

print "| " * l e v el + " | " + f

p r i n t _ t r e e (" ." )




Regular ExpressionsPattern Syntax

Regular expressions should always be placed in a raw string E.g. r([^.]*.(.*))

. match any character but newline^ match start of the string match end of the string* match previous expression zero or more times (greedy)+ match previous expression one or more times (greedy)? match previous expression zero or one time (greedy)*?, +?, ?? non-greedy versions of *, +, ?{m} match previous expression m times{m,n} match previous expression m to n times (greedy){m,n}? non-greedy version of{m,n}[...] match any character from the enclosed set[^...] match any character not in the setA|B matches A or B (both regular expressions)(...) stores the contents of the match inside the backets




Character Escape Sequences

Characters with special meaning (., *, ...) can be used withtheir literal meaning by escaping them with a\, e.g. \., \*

Standard escape characters (\n, \t, ...) work as expected,e.g. r\n+matches one or more newlines

\number match the text matched by group number (starting from 1)

\d same as

[0-9]\D same as[^0-9]\s matches any whitespace (same as[\t\n\r\f\v]\S matches nonwhitespace\w matches any alphanumeric character\W matches nonalphanumeric characters\A matches the start of a string\Z matches the end of a string




Regular Expressions (cont.)

findall(patt, string) find all non-overlapping matches sub(patt, repl, string) replaces matches by repl

from re import *

r e gs t r = r \ d * \ . \ d * | \ d *

s = " 1 2 . 3 / 5 / 4 . 4 ; 5 . 7 ; 6 "

findall(regstr ,s)

r e gs t r = r ( \ d * \ . \ d * | \ d * )

s u b ( r e g s tr , r \ 1 x x x , s)

greedy vs. non-greedy

r e g _g r e e dy = r < . * >

s = " title "

m_ g = se ar ch ( re g_ gr ee dy ,s ) # w h o l e < H 1 > t i t le < / H 1 > m a t c h e d

r e g _ no n g r ee d y = r < . * ? > # m a tc h a s f ew c ha r s a s p o ss i bl e

m_ ng = se ar ch ( re g_ no ng re ed y , s) # o n l y < H1 > m a t ch e d

print m _ g . g r ou p ( ) + " , " + m _ ng . g r o u p ()



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Match Objects

Some re functions do not return strings, but match objects (m)

match(patt, string)returns MatchObject in case of match

search(patt, string)searches for first match

finditer(patt, string)like findall, but returns iterator

m.group([group1, group2]) returns subgroups of the match

import re

s = " d a t e s 0 5 / 0 2 / 2 0 1 0 - 0 5 / 1 4 / 2 0 1 0 "

p at t = r ( \ d + ) / ( \ d + ) / ( \ d + )

fo r m in f i n d i t e r ( p a t t , s ) :print m . g r o u p ( )

print ( " % s - % s " % ( m . g r ou p ( 2 ) , m . g r o up ( 3 ) ) )




Exceptions: Dealing with Errors

Consider the user enters characters:

x = r a w_ i np u t (" P l e a s e e n t e r a n u m b e r : " )

print f l o a t ( x )




Exceptions: Dealing with Errors

Consider the user enters characters:



Failed conversion raises anValueErrorexception

P l e as e e n te r a n u m be r : x y z

.. .

T r a ce b a c k ( m o s t r e c en t c a ll l a st ) :

File " < s t d i n > " , l in e 1 , in

V a l u eE r r o r : i n v al i d l i t er a l fo r f l o a t ( ): x y z

To deal with erroneous behaviour catch exception and handle it




Exceptions: Dealing with Errors (2)

Syntax is

tr y :

# d o s o m et h i ng except V a l u e E rr o r , e : # P y > 3. 0: " E x c ep t io n a s e "

# h a n dl e V a l u eE r r o r

except E x c e p t io n , e :

# h a nd l e a ll o t he r e r ro r s

else :

# w ha t t o d o i f n o e r r or o c cu r ed

f i n a l l y:

# c od e t ha t s h ou l d b e e xe c ut e d i n a ny c as e




Exceptions: Dealing with Errors (3) Back to the previous example

g o t _ an s w e r = F a l se

w h il e n o t g o t _ a n s w e r :


tr y :


g o t _ an s w e r = T r ue

except V a l u e E r ro r , e :

print " T h a t w a s n t a n u m b e r "

# d o s o me t hi n g w i t h e




Exceptions: Dealing with Errors (3) Back to the previous example

g o t _a n s we r = F a ls e

w h i le n o t g o t _ a n s w e r :


tr y :


g o t _ an s w er = T r ue

except V a l u e E r ro r , e :

print " T h a t w a s n t a n u m b e r "

# d o s o me t hi n g w it h e

To raise your own errors (use one of many default types or createyour own):

raise R u n t i m e E r r o r ( " O o o p s ! S o m e t h i n g w e n t w r o n g ! " )

raise I O E r r o r ( " F i l e n o t e x i s t e n t . . . " )




Built-in Exceptions

B a s e E x c e p t i o n # r oo t o f a ll e xc .

G e n e r a t o r E x i t

K e y b o a r d I n t e r r u p t # C tr l +C , e . g .

S y s t e m E x i t # P r o gr a m E x it ( s y s . e xi t ( ) )

E x c e p t i o n # B as e f or n on - e x it e xc .

S t o p I t e r a t i o n

S t a n d a r d E r r o r # o nl y P y th o n 2 . x

A r i t h m e t i c E r r o r

F l o a t i n g P o i n t E r r o r

Z e r o D e v i s i o n E r r o r

A s s e r t i o n E r r o r

A t t r i b u t e E r r o r

E n v i r o n m e n t E r r o r

I O E r r o r # o p en ( " f i l e . tx t " ) , e . g .

O S E r r o r

E O F E r r o r

I m p o r t E r r o r # m o du l n ot f ou nd , e . g .




L o o k u p E r r o r

I n d e x E r r o r # t u p el s / l i st s , e . g .

KeyError # d i c t i o n ar i e s , e . g .

M e m o r y E r r o r

N a m e E r r o r # n am e n ot f ou nd

U n b o u n d e d L o c a l E r r o r

R e f e r e n c e E r r o r

R u n t i m e E r r o r

N o t I m p l e m e n t e d E r r o r

S y n t a x E r r o r

I n d e n t a t i o n E r r o rTabError

S y s t e m E r r o r

T y p e E r r o r # t yp e e rr or ( 2 + " 3" )

V a l u e E r r o r # v a l ue e r r or r ( f l o at ( " t h r ee " ) )

U n i c o d e E r r o r

U n i c o d e D e c o d e E r r o r

U n i c o d e E n c o d e E r r o r

U n i c o d e T r a n s l a t e E r r o r



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Throw Built-in Exceptions

de f r e a d f l o a t 1 ( ) :

while T r u e :

tr y :

a = r a w_ i np u t (" N u m b e r b e t w e e n 0 . 0 a n d 1 . 0 : " )

a = f l oa t ( a)

if ( a < 0 . 0 or a > 1 . 0 ) :

raise V a l u e E r r o r ( " N u m b e r n o t i n [ 0 . 0 ; 1 . 0 ] " )

except V a l u eE r r or a s e :

print " E r r o r : % s " % e

else :

return a

At a = float(a), an error is thrown automatically; the rest of thetry Block is not being executed

If a convertable, the value range is checked and a new exceptionis possibly thrown




Module pickle

Serializing Python objects Save objects as they are (current state) to file

import pickle

f d = o pe n ( m y O b j e c t s , w b )

p i c kl e . d u mp ( x , f d )

p i c kl e . d u mp ( y , f d )

f d . c l o s e ( )

Most objects can be pickled Not valid for objects such as opened files




Module pickle

Serializing Python objects

Save objects as they are (current state) to file

import pickle

f d = o pe n ( m y O b j e c t s , w b )

p i c kl e . d u m p (x , f d )p i c kl e . d u m p (y , f d )

f d . c l o s e ( )

Most objects can be pickled Not valid for objects such as opened files Then load in same order

f d = o pe n ( m y O b j e c t s , r b )

x = p i c k l e . l o a d ( f d )

y = p i c k l e . l o a d ( f d )

f d . c l o s e ( )




Misc: Python 2 to 3

Which version to use? Seehttp://wiki.python.org/moin/Python2orPython3for hintsConverting from Python 2.x to Python 3.x

Convert your code to Python 2.6

To check, there is a Py3k warnings mode

p y t ho n - 3 s c r ip t n a me . p y




Misc: Python 2 to 3Which version to use? Seehttp://wiki.python.org/moin/Python2orPython3for hintsConverting from Python 2.x to Python 3.x

Convert your code to Python 2.6

To check, there is a Py3k warnings mode

p y t ho n - 3 s c r i pt n a me . p y

If no warnings remain, use 2to3tool

Ships with Python Converts many things automatically Cant do everything

Rest manually



Scientific Computing in Computer Science, Tec

Documents

Python 2x4