2. Python Overview
Scripting Language
Object-Oriented
Portable
Powerful
Easy to learn and use
Mixes good features from Java, Perl and
Scripting
3. Major Uses of Python
System Utilities
GUIs (Tkinter, gtk, Qt, Windows)
Internet Scripting
Embedded Scripting
Database Programming
Artificial Intelligence
Image Processing
Cloud Computing(Open Stack)
5. Compiler vs Interpreter
A compiler is a program that converts a program
written in a programming language into a program in
the native language, called machine language, of the
machine that is to execute the program.
An alternative to a compiler is a program called an
interpreter. Rather than convert our program to the
language of the computer, the interpreter takes our
program one statement at a time and executes a
corresponding set of machine instructions.
9. Common Statements
Assignment - curly, moe, larry = 'good', 'bad', 'ugly'
Calls - stdout.write("spam, ham, toastn")
Print - print 'The Killer', joke
If/elif/else - if "python" in text: print text
For/else - for X in mylist: print X
While/else - while 1: print 'hello'
Break, Continue - while 1: if not line: break
Try/except/finally -
try: action() except: print 'action error'
10. Common Statements
Raise - raise endSearch, location
Import, From - import sys; from sys import stdin
Def, Return - def f(a, b, c=1, d): return a+b+c+d
Class - class subclass: staticData = []
Global - function(): global X, Y; X = 'new'
Del - del data[k]; del data [i:j]; del obj.attr
Exec - yexec "import" + modName in gdict, ldict
Assert - assert X > Y
11. Common List Methods
● list.sort() # "sort" list contents in-place
● list.reverse() # reverse a list in-place
● list.append() # append item to list
● list.remove/pop() # remove item(s) from list
● list.extend() # extend a list with another one
● list.count() # return number of item occurrences
● list.index() # lowest index where item is found
● list.insert() # insert items in list
13. Dictionaries
● Mappings of keys to values
● Mutable, resizable hash tables
● Keys are scalar (usually strings or numbers)
● Values are arbitrary Python objects
Operations :
d.keys() # iterable: keys of d
d.values() # iterable: values of d
d.items() # list of key-value pairs
d.get() # return key's value (or default)
d.pop() # remove item from d and return
d.update() # merge contents from another dict
15. Regular Expression in Python
import re
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)
16. The match Function
re.match(pattern, string, flags=0)
Parameter Description
pattern This is the regular expression to be matched.
string This is the string, which would be searched to match
the pattern at the beginning of string.
flags You can specify different flags using bitwise OR (|).
These are modifiers, which are listed in the table
below.
17. The match Function
#!/usr/bin/python
import re
line = "Cats are smarter than dogs"
matchObj = re.match( r'(.*) are (.*?) .*', line, re.M|re.I)
if matchObj:
print "matchObj.group() : ", matchObj.group()
print "matchObj.group(1) : ", matchObj.group(1)
print "matchObj.group(2) : ", matchObj.group(2)
else:
print "No match!!"
Output :
matchObj.group() : Cats are smarter than dogs
matchObj.group(1) : Cats
matchObj.group(2) : smarter
18. Matching Versus Searching
Python offers two different primitive operations based on regular expressions:
match checks for a match only at the beginning of the string, while search checks
for a match anywhere in the string.
19. Matching Versus Searching
#!/usr/bin/python
import re
line = "Cats are smarter than dogs";
matchObj = re.match( r'dogs', line, re.M|re.I)
if matchObj:
print "match --> matchObj.group() : ", matchObj.group()
else:
print "No match!!"
searchObj = re.search( r'dogs', line, re.M|re.I)
if searchObj:
print "search --> searchObj.group() : ", searchObj.group()
else:
print "Nothing found!!“
Output :
No match!!
search --> matchObj.group() : dogs
20. Search and Replace
Syntax
re.sub(pattern, repl, string, max=0)
This method replaces all occurrences of the RE pattern in string with repl, substituting all
occurrences unless max provided. This method returns modified string.
Example
#!/usr/bin/python
import re
phone = "2004-959-559 # This is Phone Number"
# Delete Python-style comments
num = re.sub(r'#.*$', "", phone)
print "Phone Num : ", num
# Remove anything other than digits
num = re.sub(r'D', "", phone)
print "Phone Num : ", num
When the above code is executed, it produces the following result −
Phone Num : 2004-959-559
Phone Num : 2004959559
21. Defining a Function
You can define functions to provide the required functionality. Here are
simple rules to define a function in Python.
Function blocks begin with the keyword def followed by the function
name and parentheses ( ( ) ).
Any input parameters or arguments should be placed within these
parentheses. You can also define parameters inside these parentheses.
The first statement of a function can be an optional statement - the
documentation string of the function or docstring.
The code block within every function starts with a colon (:) and is
indented.
The statement return [expression] exits a function, optionally passing
back an expression to the caller. A return statement with no arguments
is the same as return None.
22. Defining a Function
Syntax
def functionname( parameters ):
"function_docstring"
function_suite
return [expression]
Example
The following function takes a string as input parameter and prints it on
standard screen.
def printme( str ):
"This prints a passed string into this function"
print str
return
23. Defining a Function
Pass by reference vs value
All parameters (arguments) in the Python language are passed by reference. It means if you
change what a parameter refers to within a function, the change also reflects back in the calling
function.
For example −
# Function definition is here
def changeme( mylist ):
"This changes a passed list into this function"
mylist.append([1,2,3,4]);
print "Values inside the function: ", mylist
return
# Now you can call changeme function
mylist = [10,20,30];
changeme( mylist );
print "Values outside the function: ", mylist
Output :
Values inside the function: [10, 20, 30, [1, 2, 3, 4]]
Values outside the function: [10, 20, 30, [1, 2, 3, 4]]
24. Defining a Function
#!/usr/bin/python
# Function definition is here
def changeme( mylist, listCnt = 0 ):
"This changes a passed list into this function"
mylist = [1,2,3,4]; # This would assig new reference in mylist
print "Values inside the function: ", mylist
return
# Now you can call changeme function
mylist = [10,20,30];
changeme( mylist );
print "Values outside the function: ", mylist
The parameter mylist is local to the function changeme. Changing mylist within the function
does not affect mylist. The function accomplishes nothing and finally this would produce the
following result:
Values inside the function: [1, 2, 3, 4]
Values outside the function: [10, 20, 30]
25. References
Python homepage: http://www.python.org/
Jython homepage: http://www.jython.org/
Programming Python and Learning Python:
http://python.oreilly.com/
This presentation is available from
http://milly.rh.rit.edu/python/
