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Some material adapted 
from Upenn cmpe391 
slides and other sources

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• History
• Installing & Running Python
• Names & Assignment
• Sequences types: Lists, Tuples, and

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• Invented in the Netherlands, early 90s

• Named after Monty Python
• Open sourced from the beginning
• Considered a scripting language, but is

• Scalable, object oriented and functional

• Used by Google from the beginning
• Increasingly popular

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“Python is an experiment in 
how  much freedom program-
mers need.  Too much freedom 
and nobody can read another's 
code; too little and expressive-
ness is endangered.”

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http://docs.python.org/
Overview — Python v2.6.1 documentation

000
http://docs.pvthon org/
Overview — python
r'. V2.6.1
Overview —
Python v2.6.1 dcxumentation
Q. coogle
I Widex
these dcxuments
mher resources
FAQs
Intrcxiuctbns
Gues Essays
New-style Classes
PEP Index
Guide
Topic Guidæ
List
AudWVisual Taks
Other Collætbns
Previous versions
Quick search
Go
seÜch ta•rns a
clæs fuEtim rune.
Python v2.6.1 documentation
Welcome! This is the cm.lrnentation for Python 2.6.1 , last updated Jan 29,
Parts of the documentation:
What's new in Python 2.6?
or all What's new dæuments sinæ 2. O
Tutorial
start here
Using Python
how to Python on different platforms
Language Reference
syntax and language elements
Library Reference
keep this under your pillow
Python HOWTOs
in-depth documents on topics
Indices and tables:
Global Module Index
quick acæss to all
General Index
all functions, classes, terms
Glossary
the most terms explained
Extending and Embedding
tutorial for C/C++ programmers
Python/C API
reference for C/C++ programmers
Installing Python Modules
information for installers & sys-admins
Distributing Python Modules
sharing with others
Documenting Python
guide for documentation authors
Search page
this dæumentatön
Complete Table of Contents
lists all and subsections

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The Python tutorial is good!
The Python Tutorial —
on v2.6.1 documentation

e 00
The Python Tutorial —
Python v2.6.1 documentation
http://d0CS•python.org/tutoriaWindex.html
The Tutorial — Pyt.
e Python v2.6.1 documventation »
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The Python Tutorial
Release: 2.6
Date:
January 04, 2009
Python is an easy to learn, powerful programming language. It has efficient high-
level data structures and a simple but effective approach to object-oriented
programming. Python's elegant syntax and dynamic typing, together with its
interpreted nature, make it an ideal language for scripting and rapid application
development in many areas on most platforms.
The Python interpreter and the extensive standard library are freely available in
source or binary form for all major platforms from the Python Web site,
http://www.python.org/, and may be freely distributed. The same site also contains
distributions of and pointers to many free third party Python modules, programs and
tools, and additional documentation.
The Python interpreter is easily extended with new functions and data types
implemented in C or C++ (or other languages callable from C). Python is also
suitable as an extension language for customizable applications.
This tutorial introduces the reader informally to the basic concepts and features of
the Python language and system. It helps to have a Python interpreter handy for
hands-on experience, but all examples are self-contained, so the tutorial can be
read off-line as well.
For a description of standard objects and modules, see the Python Library

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• Interactive interface to Python with a

[finin@linux2 ~]$ python
Python 2.4.3 (#1, Jan 14 2008, 18:32:40) 
[GCC 4.1.2 20070626 (Red Hat 4.1.2-14)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> def square(x):
...   return x * x
... 
>>> map(square, [1, 2, 3, 4])
[1, 4, 9, 16]
>>>

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• Python is pre-installed on most Unix systems,

• The pre-installed version may not be the most

recent one (2.6.2 and 3.1.1 as of Sept 09)

• Download from http://python.org/download/
• Python comes with a large library of standard

• IDLE – works well with Windows
• Emacs with python-mode or your favorite text editor
• Eclipse with Pydev (http://pydev.sourceforge.net/)

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• IDLE is an Integrated DeveLopment Environ-

ment for Python, typically used on Windows

highlighting, auto-completion, smart indent 
and other.

• Python shell with syntax highlighting.
• Integrated debugger

with stepping, persis-
tent breakpoints,
and call stack visi-
bility

Elle Ed,'
Python 2.3. 4 (#53,
Type copy i g h t
May 25 2004,
[MSC
v. 1200 32 bit (Intel) ]
the IDLE
makes to its subprocess using this computer's internal Xoopback
interface. This connection is not v i3ibIe on any external
to o E f the
IDLE 1-0
in [x* *2
for
for
x
range (5) ]
range ]
stop [ ,
step))
1is t
x n tegers

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• Emacs python-mode has good support for editing

Python, enabled enabled by default for .py files

• Features: completion, symbol help, eldoc, and inferior

— 80x23
ile Edit
Terminal — ssh
ions Buffers IM—
/usr/bin/ python
primes N will print the primes N
from math import sqrt
from sys import argv
if len(argv) < 2:
print "usage: primes N"
exit( )
else:
max
def
returns True if n is a prime number"""
for i in range(2, l+sqrt(n)):
return False
return True
for n in
: ri—s.
mark set

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• Python prompts with ‘>>>’. 
• To exit Python (not Idle):

• In Unix, type CONTROL-D
• In Windows, type CONTROL-Z + <Enter>
• Evaluate exit()

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• Call python program via the python interpreter

• Make a python file directly executable by

• Adding the appropriate path to your python

interpreter as the first line of your file
#!/usr/bin/python

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"""Returns the factorial of its argument, assumed to be a posint"""
if x == 0:

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• When you call a python program from the

command line the interpreter evaluates each 
expression in the file

• Familiar mechanisms are used to provide

command line arguments and/or redirect 
input and output

• Python also has mechanisms to allow a

python program to act both as a script and as 
a module to be imported and used by another 
python program

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#! /usr/bin/python
""" reads text from standard input and outputs any email

# a regular expression ~ for a valid email address
pat = re.compile(r'[-\w][-.\w]*@[-\w][-\w.]+[a-zA-Z]')

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python> python email0.py <email.txt
bill@msft.com
gates@microsoft.com
steve@apple.com
bill@msft.com
python>

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pat = re.compile(r'[-\w][-.\w]*@[-\w][-\w.]+[a-zA-Z]’)
# found is an initially empty set (a list w/o duplicates)
found = set( )
for line in stdin.readlines():

# sorted() takes a sequence, returns a sorted list of its elements
for address in sorted(found):

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python> python email2.py <email.txt
bill@msft.com
gates@microsoft.com
steve@apple.com
python>

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"""factorial done recursively and iteratively"""

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671> python
Python 2.5.2 …
>>> import ex
>>> ex.fact1(6)
1296
>>> ex.fact2(200)
78865786736479050355236321393218507…000000L
>>> ex.fact1
<function fact1 at 0x902470>
>>> fact1
Traceback (most recent call last):

NameError: name 'fact1' is not defined
>>>

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x = 34 - 23            # A comment.
y = “Hello”
# Another one.

z = 3.45    
if z == 3.45 or y == “Hello”:

x = x + 1
y = y + “ World”
# String concat.

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• Block structure indicated by indentation

• First assignment to a variable creates it

• Variable types don’t need to be declared.
• Python figures out the variable types on its own.

• Assignment is = and comparison is ==
• For numbers + - * / % are as expected

• Special use of + for string concatenation and % for

• Logical operators are words (and, or,

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• Can use “” or ‘’ to specify with “abc” ==

• Unmatched can occur within the string:

• Use triple double-quotes for multi-line strings or

strings than contain both ‘ and “ inside of them:  
“““a‘b“c”””

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Whitespace is meaningful in Python: especially 
indentation and placement of newlines
•Use a newline to end a line of code

Use \ when must go to next line prematurely

•No braces {} to mark blocks of code, use 
consistent indentation instead

• First line with less indentation is outside of the block
• First line with more indentation starts a nested block

•Colons start of a new block in many constructs, 
e.g. function definitions, then clauses

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• Start comments with #, rest of line is ignored
• Can include a “documentation string” as the

first line of a new function or class you define

• Development environments, debugger, and

other tools use it: it’s good style to include one

“““fact(n) assumes n is a positive 
integer and returns facorial of n.”””
assert(n>0)
return 1 if n==1 else n*fact(n-1)

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• Binding a variable in Python means setting a name to

• Assignment creates references, not copies

• Names in Python do not have an intrinsic type,

• Python determines the type of the reference automatically

• You create a name the first time it appears on the left

• A reference is deleted via garbage collection after

any names bound to it have passed out of scope

• Python uses reference semantics (more later)

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• Names are case sensitive and cannot start

with a number.  They can contain letters, 
numbers, and underscores.

and, assert, break, class, continue, 
def, del, elif, else, except, exec, 
finally, for, from, global, if, 
import, in, is, lambda, not, or, 
pass, print, raise, return, try, 
while

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The Python community has these recommend-
ed naming conventions
•joined_lower for functions, methods and, 
attributes
•joined_lower or ALL_CAPS for constants
•StudlyCaps for classes
•camelCase only to conform to pre-existing 
conventions
•Attributes: interface, _internal, __private

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•You can assign to multiple names at the

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Accessing a name before it’s been properly 
created (by placing it on the left side of an 
assignment), raises an error

File "<pyshell#16>", line 1, in -toplevel-

NameError: name ‘y' is not defined
>>> y = 3
>>> y
3

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• A simple immutable ordered sequence of

• Items can be of mixed types, including

• Immutable
• Conceptually very much like a tuple

3. List: [1, 2, ‘john’, (‘up’, ‘down’)]

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strings, and lists) share much of the 
same syntax and functionality.

• Tuples and strings are immutable
• Lists are mutable

can be applied to all sequence types
• most examples will just show the

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• Define tuples using parentheses and commas

>>> tu = (23, ‘abc’, 4.56, (2,3), ‘def’)

• Define lists are using square brackets and

• Define strings using quotes (“, ‘, or “““).

>>> st = “Hello World”
>>> st = ‘Hello World’
>>> st = “““This is a multi-line
string that uses triple quotes.”””

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• Access individual members of a tuple, list, or

string using square bracket “array” notation

>>> tu = (23, ‘abc’, 4.56, (2,3), ‘def’)
>>> tu[1]     # Second item in the tuple.

>>> li = [“abc”, 34, 4.34, 23]
>>> li[1]      # Second item in the list.

>>> st = “Hello World”
>>> st[1]   # Second character in string.

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>>> t = (23, ‘abc’, 4.56, (2,3), ‘def’)
Positive index: count from the left, starting with 0

Negative index: count from right, starting with –1

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>>> t = (23, ‘abc’, 4.56, (2,3), ‘def’)

Return a copy of the container with a subset of 
the original members.  Start copying at the first 
index, and stop copying before second.

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>>> t = (23, ‘abc’, 4.56, (2,3), ‘def’)
Omit first index to make copy starting from 
beginning of the container

Omit second index to make copy starting at first 
index and going to end

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• [ : ] makes a copy of an entire sequence

>>> t[:] 
(23, ‘abc’, 4.56, (2,3), ‘def’)

• Note the difference between these two lines

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• Boolean test whether a value is inside a container:

>>> t = [1, 2, 4, 5]
>>> 3 in t
False
>>> 4 in t
True
>>> 4 not in t
False

>>> a = 'abcde'
>>> 'c' in a
True
>>> 'cd' in a
True
>>> 'ac' in a
False

• Be careful: the in keyword is also used in the syntax

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The + operator produces a new tuple, list, or 
string whose value is the concatenation of its 
arguments.

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• The * operator produces a new tuple, list, or

string that “repeats” the original content.

>>> (1, 2, 3) * 3
(1, 2, 3, 1, 2, 3, 1, 2, 3)

>>> [1, 2, 3] * 3
[1, 2, 3, 1, 2, 3, 1, 2, 3]

>>> “Hello” * 3
‘HelloHelloHello’

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>>> li = [‘abc’, 23, 4.34, 23]
>>> li[1] = 45 
>>> li

• We can change lists in place.
• Name li still points to the same memory

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>>> t = (23, ‘abc’, 4.56, (2,3), ‘def’)
>>> t[2] = 3.14

File "<pyshell#75>", line 1, in -toplevel-

TypeError: object doesn't support item assignment

•You can’t change a tuple. 
•You can make a fresh tuple and assign its

reference to a previously used name.
>>> t = (23, ‘abc’, 3.14, (2,3), ‘def’)

•The immutability of tuples means they’re faster

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>>> li.insert(2, ‘i’)
>>>li
[1, 11, ‘i’, 3, 4, 5, ‘a’]

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• + creates a fresh list with a new memory ref
• extend operates on list li in place.

>>> li.extend([9, 8, 7])           
>>> li
[1, 2, ‘i’, 3, 4, 5, ‘a’, 9, 8, 7]

•
append takes a singleton as an argument.

>>> li.append([10, 11, 12])
>>> li
[1, 2, ‘i’, 3, 4, 5, ‘a’, 9, 8, 7, [10,

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Lists have many methods, including index, count, 
remove, reverse, sort 
>>> li = [‘a’, ‘b’, ‘c’, ‘b’]
>>> li.index(‘b’)  # index of 1st occurrence
1
>>> li.count(‘b’)  # number of occurrences
2
>>> li.remove(‘b’) # remove 1st occurrence
>>> li

Introduction to Python

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