module 4 –python and regular expressionstodd/cse330/cse330_lecture4.pdf · what is python?...

Extensible Networking Platform 11 - CSE 330 – Creative Programming and Rapid Prototyping

Module 4 – Python and Regular Expressions

• Module 4 contains only an individual assignment

• Due Monday July 6th

• Do not wait until the last minute to start on this module

• Read the WIKI before starting along with a few Python tutorials

• Portions of today’s slides came from– Marc Conrad

• University of Luton– Paul Prescod

• Vancouver Python Users’ Group– James Casey

• Opscode– Tim Finin

• Univeristy of Maryland

1


What is Python?

• Python is an easy to learn, powerful programming language– Efficient high-level data structures– Simple approach to object-oriented

programming.– Elegant syntax and dynamic typing– Up-and-coming language in the open source

world

• We are using Python version 3.4 or later in this course

2


Usability Features

• Very clear syntax• Obvious way to do most things• Huge amount of free code and libraries• Interactive• Only innovative where innovation is really

necessary– Better to steal a good idea than invent a bad one!

3


Python “Hello world"

print (“Hello, World”)

4


Python Interpreter

• Just type:

• Todds-MacBook-Air:~ todd$ python3• Python 3.6.1 (default, Apr 4 2017, 09:40:21)• [GCC 4.2.1 Compatible Apple LLVM 8.1.0 (clang-802.0.38)]

on darwin• Type "help", "copyright", "credits" or "license" for more

information.

5


Features of the Interpreter

• Lines start with “>>>”. You can recognize Python interpreter transcripts anywhere you see them.

• Expressions that return a value display the value.>>> 5+3*417

• This saves you from excessive “print”ing

6


Interactive Interpreters

• Windows command line• OS X• Linux/Unix • Graphical command lines: “IDLE”, “PythonWin”, “MacPython”, …

• Jython• And many more…

7


Python scripts

• Sometimes you want to run the same program more than once!

• Make a file with Python statements in it:foo.py:print (“hello world”)

todd$ python3 foo.pyhello worldtodd$ python3 foo.pyhello world

8


Python is dynamically typed

width = 20print (width) height = 5 * 9print (height)print (width * height) width = "really wide"print (width)

9


Experiment in the Interpreter

• Any Python variable can hold any value.

>>> width = 20>>> height = 5 * 9>>> print (width * height)900>>> width = "really wide">>> print (width)really wide

10


Dynamic Type Checking

test_sqrt.py:import math

def square_root(num):return math.sqrt(num)

def goodfunc():print (square_root(10))

def badfunc():print (square_root("10"))

goodfunc()badfunc()

11


Multiple statements on a line

• You can combine multiple simple statements on a line:

>>> a = 5;print (a); a = 6; print (a)

5

6

12


Indentation

• Python uses indentation for scoping:

if this_function(that_variable):

do_something()

else:

do_something_else()

13


Indentation

• Tabs and spaces look the same in most editors.

• If your editor uses a different conversion rate between tabs and spaces than “standard”, your Python code may not parse properly.

• Three easy solutions:1. Only use tabs or spaces in a file: don’t mix them.2. Use an editor that knows about Python.3. Configure editor to use the same tab/space rules as Python, vi, emacs,

notepad, edit, etc. : 8 spaces per tab

14


Compared to PHP/Javascript

• Excellent for Web apps (PHP on server, Javascripton client) but not much else.

• Python can be used for your Web apps, your complicated algorithms, your GUIs, your COM components, an extension language for Java programs

• Even in Web apps, Python handles complexity better.

15


Compared to Java

• Java is more difficult for amateur programmers.

• Static type checking can be inconvenient and inflexible.

• Bottom line: Java can make projects harder than they need to be.

16


Python Limitations

• Not the fastest executing programming language:– C/C++ is naturally fast– Perl’s regular expressions and IO are a little faster– Some Java implementations have good JITs– But Python also has some speed advantages:

• Fast implementations of built-in data structures• Pyrex compiles Python code to C

• Dynamic type checking requires more care in testing.

• Language changes (relatively) quickly: this is a strength and a weakness.

17


Objects All the Way Down

• Everything in Python is an object• Integers are objects.• Characters are objects.• Complex numbers are objects.• Booleans are objects.• Functions are objects.• Methods are objects.• Modules are objects

18


Object Type and Identity

• You can find out the type of any object:>>> print (type(1))<type 'int'>>>> print (type(1.0))<type 'float'>

• Every object also has a unique identifier (usually only for debugging purposes)>>> print (id(1))7629640>>> print (id("1"))7910560

19


None

• “None” represents the lack of a value.• Like “NULL” in some languages or in databases.• For instance:

>>> if y!=0:... fraction = x/y... else:... fraction = None

20


File Objects

• Represent opened files:>>> infile = open( "catalog.txt", "r" )>>> data = infile.read()>>> infile.close()>>> outfile = open( "catalog2.txt", "w" )>>> data = data+ "more data">>> outfile.write( data )>>> outfile.close()

• You may sometimes see the name “open” used to create files.

21


Basic Flow Control

• if/elif/else (test condition)

• while (loop until condition changes)

• for (iterate over iteraterable object)

22


if Statement

if j=="Hello":doSomething()

elif j=="World":doSomethingElse()

else:doTheRightThing()

23


while Statement

str=""while str!="quit":

str=raw_input()print (str)

print "Done"

24


for Statement

myList = ["a", "b", "c", "d", "e"]for i in myList:

print (i)

for i in range( 10 ):print (i)

for i in range( len( myList ) ):if myList[i]=="c":

myList[i]=None

• Can “break” out of for-loops.• Can “continue” to next iteration.

25


Python Modules

26


What is a Module?

- A file containing some Python code

OR

- A .dll (.so on Unix) containing compiled code which follows some guidelines

- A namespace

27


A Python Module

def hello_world():print (“Hello world”)

• Save this as “myModule.py” Now we can use it:>>> import myModule>>> myModule.hello_world()

• Or:>>> from myModule import hello_world>>> hello_world()

28


Other Built-in Protocols

• FTP• XML-RPC• Telnet• POP• IMAP• MIME• NNTP• HTTP

• SSL• Sockets• CGI• Gopher• URL Parsing

• Plus downloadable modules for every other protocol in the universe!

29


Regular Expressions

30


Regular Expressions

• Regular expressions are a powerful string manipulation tool

• All modern languages have similar library packages for regular expressions

• Use regular expressions to:– Search a string (search and match)– Replace parts of a string (sub)– Break strings into smaller pieces (split)

31


Regular Expression Syntax

• Most characters match themselvesThe regular expression “test”matches the string ‘test’, and only that string

• [x] matches any one of a list of characters“[abc]”matches ‘a’,‘b’,or ‘c’

• [^x] matches any one character that is not included in x“[^abc]”matches any single character except‘a’,’b’,or ‘c’

32



• “.”matches any single character

• Parentheses can be used for grouping“(abc)+”matches ’abc’, ‘abcabc’, ‘abcabcabc’, etc.

• x|y matches x or y“this|that”matches ‘this’ and ‘that’, but not ‘thisthat’.

33



• x* matches zero or more x’s“a*”matches ’’, ’a’, ’aa’, etc.

• x+ matches one or more x’s“a+”matches ’a’,’aa’,’aaa’, etc.

• x? matches zero or one x’s“a?”matches ’’ or ’a’

• x{m, n} matches i x‘s, where m<i< n“a{2,3}”matches ’aa’ or ’aaa’

34



• “\d”matches any digit; “\D” any non-digit

• “\s”matches any whitespace character; “\S” any non-whitespace character

• “\w”matches any alphanumeric character; “\W” any non-alphanumeric character

• “^”matches the beginning of the string;“$” the end of the string

35


Debuggex Example

36


Search and Match in Python RegEx

• The two basic functions are re.search and re.match– Search looks for a pattern anywhere in a string– Match looks for a match starting at the beginning

• Both return None (logical false) if the pattern isn’t found and a “match object” instance if it is>>> import re>>> pat = "a*b”>>> re.search(pat,"fooaaabcde")<_sre.SRE_Match object at 0x809c0>>>> re.match(pat,"fooaaabcde")>>>

37


What’s a match object?

• An instance of the match class with the details of the match result

>>> r1 = re.search("a*b","fooaaabcde")>>> r1.group() # group returns string matched

'aaab'>>> r1.start() # index of the match start

3>>> r1.end() # index of the match end7>>> r1.span() # tuple of (start, end)(3, 7)

38


What got matched?

• Here’s a pattern to match simple email addresses\w+@(\w+\.)+(com|org|net|edu)

>>> pat1 = "\w+@(\w+\.)+(com|org|net|edu)">>> r1 = re.match(pat1,"[email protected]")>>> r1.group()’[email protected]’

• We might want to extract the pattern parts, like the email name and host

39


What got matched?

• We can put parentheses around groups we want to be able to reference

>>> pat2 = "(\w+)@((\w+\.)+(com|org|net|edu))">>> r2 = re.match(pat2,”[email protected]")>>> r2.group(1)’todd'>>> r2.group(2)’arl.wustl.edu'>>> r2.groups()r2.groups()(’todd', ’arl.wustl.edu', ’wustl.', 'edu’)

• Note that the ‘groups’ are numbered in a preorder traversal

40


What got matched?

• We can ‘label’ the groups as well… >>> pat3 ="(?P<name>\w+)@(?P<host>(\w+\.)+(com|org|net|edu))"

>>> r3 = re.match(pat3,"[email protected]")>>> r3.group('name')’todd'>>> r3.group('host')’arl.wustl.edu’

• And reference the matching parts by the labels

41


More re functions

• re.split() is like split but can use patterns>>> re.split("\W+", “This... is a test,

short and sweet, of split().”)['This', 'is', 'a', 'test', 'short’,

'and', 'sweet', 'of', 'split’, ‘’]

• re.sub substitutes one string for a pattern>>> re.sub('(blue|white|red)', 'black', 'blue socks and red shoes')

'black socks and black shoes’

• re.findall() finds all matches>>> re.findall("\d+”,"12 dogs,11 cats, 1 egg")['12', '11', ’1’]

42


Compiling regular expressions• If you plan to use a re pattern more than once, compile it

to a re object• Python produces a special data structure that speeds up

matching>>> cpat3 = re.compile(pat3)>>> cpat3<_sre.SRE_Pattern object at 0x2d9c0>>>> r3 = cpat3.search("[email protected]")

>>> r3<_sre.SRE_Match object at 0x895a0>>>> r3.group()’[email protected]'

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