Programming with Python - Week 2

Programming with
Python
Week 2
Dept. of Electrical Engineering and Computer Science
Academic Year 2010-2011

Week 1 - Highlights

• In Python, everything is an object.
• In Python, you never explicitly specify the datatype
of anything.
• Based on what value you assign, Python keeps track
of the datatype internally.

Week 1 - Highlights
• just indent and get on with your life.
• indentation is a language requirement. not a matter of
style.
• Python uses carriage return to separate statements.
• Python uses a colon and indentation to separate code
blocks.
:
...

Mannerism: Dropbox usage

• Use Shared Dropbox folder more responsibly.
• Think of your friends.
• Think before you act.

3.1 Introducing
Dictionaries

• Dictionary is a built-in datatype of Python.
• It deﬁnes a one-to-one relationship between keys and
values.
• One-to-one relationship? Let’s see with a useful
example.

One-to-one relationship?

• http://maps.google.com/maps/place?
cid=12784366278796637370&q=Wells+Fargo+Bank
+near+Union+Street,+SF,+CA,+United
+States&hl=en&dtab=0&sll=37.798984,-122.421915&ssp
n=0.006295,0.03601&ie=UTF8&ll=37.817446,-122.4536
13&spn=0,0&z=14
Relationship: shortened to by

• http://bit.ly/f2bSMH

Takeaway I: It's much easier to include

Key --> Value the shorter link in an email or Twitter
post without it breaking or taking up
space.

Takeaway II: bit.ly works by issuing a "301 redirect". When you shorten a link with bit.ly,
you are redirecting a click from bit.ly to the destination URL. A 301 redirect is the most
efﬁcient and search engine-friendly method for webpage redirection.

3.1.1 Deﬁning Dictionaries

• >>> d = {“bruce”: “lee”, “mortal”: “kombat”}
}
{
• >>> d
{'bruce': 'lee', 'mortal': 'kombat'}
• >>> d["bruce"]
'lee'

Rules, rules, rules
• You can not have duplicate keys in a dictionary. Assigning
a value to an existing key will wipe out the old value.
• You can add new key-value pairs at any time. This syntax
is identical to modifying existing values.
• Be careful: you may be adding new values but are
actually just modifying the same value over and over
because your key isn't changing the way you think it is.
• Dictionaries are unordered.
• Dictionary keys are case-sensitive.

3.1.2 Modifying dictionaries
& case-sensitivity

K
• >>> d = {}
• >>> d = {“key” : “value”}
• >>> d

k
{'key': 'value'}
• >>> d[“Key”] = “Value”
• >>> d
{'Key': 'Value', 'key': 'value'}

Shepherd’s
salad of datatypes
• >>> d={"bruce":"lee","mortal":"kombat"}
• >>> d["air force"] = 1
• >>> d
{'bruce': 'lee', 'air force': 1, 'mortal': 'kombat'}
• >>> d[2]="two"
• >>> d
{'bruce': 'lee', 2: 'two', 'air force': 1, 'mortal': 'kombat'}

Dictionaries

• Dictionaries are NOT just for strings.
• Dictionary values can be any datatype. Within a single
dictionary, you can have values of different datatypes.
• Dictionary keys are more restricted: strings and
integers are mostly used (note: there are some others
too).

3.1.3 Deleting Items
from Dictionaries
• >>> d
{'bruce': 'lee', 2: 'two', 'air force': 1, 'mortal': 'kombat'}
• >>> del d[2]
• >>> d
{'bruce': 'lee', 'air force': 1, 'mortal': 'kombat'}
• >>> d.clear()
• >>> d
{}

3.2 Introducing Lists

• Shopping cart is a list.

3.2.1 Deﬁning Lists
• >>> li=["armani watch","hunting with the
moon","amazon kindle","iphone 4"]
• >>> li
['armani watch', 'hunting with the moon', 'amazon
kindle', 'iphone 4']
• >>> li[0]
'armani watch'
• >>> li[3]
'iphone 4'

Lists are

, , ,]
• ordered. [
• enclosed in square brackets.
• having their ﬁrst element start at index 0.

Two way access
• Forward:
li[0] li[3]

li = ["armani watch","hunting with the moon","amazon kindle","iphone 4"]

• Backward:
li[-1] li[-4]

Slicing a list

:3 ]
• Reading the list from left to right:
[ 1
i. the first slice index specifies the first element you
want,
ii. the second slice index specifies the first element you
don't want,
iii. the return value is everything in between.

Slicing at work

• >>> li
• >>> li[1:3]
['hunting with the moon', 'amazon kindle']
• >>> li[0:0] Ask in class...

Assuming list length is n

• li[:3] is the same as li[0:3].
• li[3:] is the same as li[3:n], where n is the length of the
list.
• li[:n] will always return the ﬁrst n elements.
• li[:] is shorthand for making a complete copy of a list: all
elements of the original list are included. But this is not
the same as the original li list; it is a new list that has the
same elements.

3.2.1 Adding elements to
Lists

• >>> li
• >>> li.append("ipad 32gb wiﬁ+3g")
• >>> li
kindle', 'iphone 4', 'ipad 32gb wiﬁ+3g']

Lists

• >>> li
kindle', 'iphone 4', 'ipad 32gb wiﬁ+3g']
• >>> li.insert(1,”macbook pro”)
• >>> li
['armani watch', 'macbook pro', 'hunting with the moon',
'amazon kindle', 'iphone 4', 'ipad 32gb wiﬁ+3g']

Lists
• >>> li
'amazon kindle', 'iphone 4', 'ipad 32gb wiﬁ+3g']
• >>> li.extend(["zoolander dvd","v for vendetta
dvd","gladiator dvd"])
• >>> li
'amazon kindle', 'iphone 4', 'ipad 32gb wiﬁ+3g',
'zoolander dvd', 'v for vendetta dvd', 'gladiator dvd']

Difference between extend
and append
• >>> li=["a","b","c"] • >>> del li[3]
• >>> li • >>> li
['a', 'b', 'c'] ['a', 'b', 'c']

• >>> li.append • >>> li.extend(["d","e"])
• >>> li.append(["d","e"]) • >>>'b', 'c', 'd', 'e']
['a',
li

• >>> li
['a', 'b', 'c', ['d', 'e']]

3.2.3 Searching a List
• >>> li • >>> “c” in li
['a', 'b', 'c', 'd', 'e'] True
• >>> li • >>> “f” in li
['a', 'b', 'c', 'd', 'e'] False
• >>> li.index("a") • >>> li.index(“g”) call last):
0 Traceback (most recent
File "<pyshell#47>", line 1, in
• >>> li.index("e") <module>
li.index("g")
4
ValueError: list.index(x): x not in list
• >>> “c” in li

3.2.4 Deleting List elements
• >>> li
['a', 'b', 'c', 'd', 'e']

• >>> li.remove("a")

• >>> li
['b', 'c', 'd', 'e']

• >>> li.remove("f")
Traceback (most recent call last): File "<pyshell#51>", line 1, in
<module> li.remove("f") ValueError: list.remove(x): x not in list

• >>> li.pop()
'e'

3.2.5 Using List operators

• >>> li
['b', 'c', 'd']
• >>> li = ["a"] + li
• >>> li
['a', 'b', 'c', 'd']
• >>> li += ["e","f"]
• >>> li
['a', 'b', 'c', 'd', 'e', 'f']

3.2.5 Using List operators
extend
• >>> li
['b', 'c', 'd']
ext
fas
larg ter is
end
• >>> li = ["a"] + li an e li for
• >>> li sts
in- . it
['a', 'b', 'c', 'd']
op pla is
• >>> li += ["e","f"] era ce
• >>> li tio
['a', 'b', 'c', 'd', 'e', 'f'] n.

3.3 Introducing Tuples

,)
• A tuple is an immutable list.

, ,
• A tuple cannot be changed once it is created.

(

Tuples have no methods

immutable

Tuples are good for?

• Tuples are faster than lists.
• Working with read-only data makes your code safer.
Implicit write-protection.
• Note that tuples can be converted into lists and vice-
versa.

3.4 Declaring Variables

• Python has local and global variables like most other
languages, but it has no explicit variable
declarations.
• Variables spring into existence by being assigned a
value, and they are automatically destroyed when they
go out of scope.
• Python will not allow you to reference a variable that
has never been assigned a value; trying to do so will
raise an exception.

VARIABLES

VALUE
= 1
ASSIGNMENT

3.4.2 Assigning
multiple values at once

• >>> tuple_t = ('eecs',211)
• >>> (dept,course_code)=tuple_t
• >>> dept
'eecs'
• >>> course_code
211

Tuples are good for?

• Tuples are used in multi-variable assignment.

3.5 Formatting Strings

• >>> m = “mortal”
• >>> k = “kombat”
• >>> “%s %s” % (m,k)
'mortal kombat'

• note the usage of tuples here as well.
%

String formatting vs.
String concatenation

• >>> li
['a', 'b', 'c', 'd', 'e', 'f']
• >>> len(li)
6
%d
• >>> print "The length of the list is: %d" % (len(li),)
The length of the list is: 6

String concatenation

+
• >>> print "The length of the list is: " + (len(li))
Traceback (most recent call last):
File "<pyshell#74>", line 1, in <module>
print "The length of the list is: " + (len(li))
TypeError: cannot concatenate 'str' and 'int' objects
• >>> print “mortal” + “ kombat”
mortal kombat
• string concatenation works only when everything is
already a string.

Formatting numbers
%f
• >>> print "Today's stock price: %f" % 50.4625
Today's stock price: 50.462500
• >>> print "Today's stock price: %.2f" % 50.4625
Today's stock price: 50.46
• >>> print "Change since yesterday: %+.2f" % 1.5
Change since yesterday: +1.50

3.6 Mapping Lists

• One of the most powerful features of Python is the list
comprehension, which provides a compact way of
mapping a list into another list by applying a function
to each of the elements of the list.
• >>> l_numbers = [1,2,3,4]
• >>> [element*2 for element in l_numbers]
[2, 4, 6, 8]

List comprehension
step by step
• >>> params = {"server":"mpilgrim", "database":"master", "uid":"sa",
"pwd":"secret"}

• >>> params.items()
[('pwd', 'secret'), ('database', 'master'), ('uid', 'sa'), ('server', 'mpilgrim')]

• >>> [k for k, v in params.items()]

•
['pwd', 'database', 'uid', 'server']
>>> [v for k, v in params.items()]
tuples
['secret', 'master', 'sa', 'mpilgrim']

• >>> ["%s=%s" % (k, v) for k, v in params.items()]
['pwd=secret', 'database=master', 'uid=sa', 'server=mpilgrim']

3.7 Joining Lists and
Splitting Strings

• To join any list of strings into a single string, use the join
method of a string object.
• >>> ";".join(["%s=%s" % (k, v) for k, v in params.items()])
'pwd=secret;database=master;uid=sa;server=mpilgrim'
• join works only on lists of strings; it does not do any
type coercion. Joining a list that has one or more non-
string elements will raise an exception.

3.7 Joining Lists and
Splitting Strings
• >>> li = ";".join(["%s=%s" % (k, v) for k, v in
params.items()])
• >>> li
'pwd=secret;database=master;uid=sa;server=mpilgrim'
• >>> li.split(";")
['pwd=secret', 'database=master', 'uid=sa',
'server=mpilgrim']
• Ask in class.. what do you notice?

Remember Your First
Python Program

odbchelper.py

Dr. Ahmet Bulut took this picture in NYC during when he was
interning at IBM T.J.Watson Research Center in August 2004.

Programming with Python - Week 2

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