Lecture 09.pptx

Mohammad Hassan
Array, Tuples, Dictionary, Exception

Objectives
Arrays;
Sequence Type & Mutability;
Understand the need of Tuples;
Solve problems by using Tuples;
 Get clear idea about Tuple functions;
Understand the difference between list, dictionary and
tuples; and
Exceptions

Arrays are used to store multiple values in one single variable:
cars = ["Ford", "Volvo", "BMW"]
An array is a special variable, which can hold more than one value at a time.
If you have a list of items (a list of car names, for example), storing the cars in
single variables could look like this:
car1 = "Ford"
car2 = "Volvo"
car3 = "BMW“
what if you want to loop through the cars and find a specific one? And what if
you had not 3 cars, but 300?
The solution is an array!
An array can hold many values under a single name, and you can access the
values by referring to an index number.
ARRAY

Access the Elements of an Array
Get the value of the first array item:
x = cars[0]
print(x)
This will give output:
Ford

Modify the value of the first array
Modify the value of the first array item:
cars[0] = "Toyota"
print(cars)
['Toyota', 'Volvo', 'BMW']

The Length of an Array
Use the len() method to return the length of an array (the number of
elements in an array).
Return the number of elements in the cars array:
x = len(cars)
print(x)
3
The length of an array is always one more than the highest
array index.

Looping Array Elements
Print each item in the cars array:
for x in cars:
print(x)
Ford
Volvo
BMW

WHAT IS TUPLE?
A tuple is essentially an immutable list. Below is a list with three
elements and a tuple with three elements:
L = [1,2,3]
t = (1,2,3)
Tuples are enclosed in parentheses, though the parentheses are
actually optional.
Indexing and slicing work the same as with lists.
As with lists, you can get the length of the tuple by using the len
function, and, like lists, tuples have count and index
methods.However, since a tuple is immutable, it does not have any
of the other methods that lists have, like sort or reverse, as those
change the list.

Adding Array Elements
You can use the append() method to add an element to an
array.
Add one more element to the cars array:
cars.append("Honda")
print(cars)
['Ford', 'Volvo', 'BMW', 'Honda']

Removing Array Elements
You can use the pop() method to remove an element from the array.
Delete the second element of the cars array:
cars.pop(1)
print(cars)
['Ford', 'BMW’]
You can also use the remove() method to remove an element from the array.
Delete the element that has the value "Volvo":
cars.remove("Volvo")
print(cars)
['Ford', 'BMW']

Array Methods
Python has a set of built-in methods that you can
use on lists/arrays.

Sequence Type & Mutability
A sequence type is a type of data in Python which is
able to store more than one value (or less than one, as a
sequence may be empty), and these values can be
sequentially (hence the name) browsed, element by
element.
As the for loop is a tool especially designed to iterate
through sequences, we can express the definition as: a
sequence is data which can be scanned by
the for loop.
Mutability is a property of any Python data that
describes its readiness to be freely changed during
program execution. There are two kinds of Python
data: mutable and immutable.

Mutable data can be freely updated at any time − we call
such an operation in situ.
In situ is a Latin phrase that translates as literally in position.
For example, the following instruction modifies the data in situ:
list.append(1)
Immutable data cannot be modified in this way.
Imagine that a list can only be assigned and read over. You
would be able neither to append an element to it, nor remove
any element from it. This means that appending an element to
the end of the list would require the recreation of the list from
scratch.
You would have to build a completely new list, consisting of the
Sequence Type & Mutability

A tuple is a sequence of values, which can be of any type and they
are indexed by integer. Tuples are just like list, but we can’t change
values of tuples in place.
A tuple is an immutable sequence type. It can behave like a list,
but it can't be modified in situ.
The index value of tuple starts from 0.
A tuple consists of a number of values separated by commas.
tuple_1 = (1, 2, 4, 8)
tuple_2 = 1., .5, .25, .125
print(tuple_1)
print(tuple_2)
The output:
(1, 2, 4, 8)
(1.0, 0.5, 0.25, 0.125)
Each tuple element may be of a different type (floating-point,
integer, or any other not-as-yet-introduced kind of data).
WHAT IS TUPLE?

CREATING EMPTY TUPLE
It is possible to create an empty tuple – parentheses
are required then:

If you want to create a one-element tuple, you have to take
into consideration the fact that, due to syntax reasons (a
tuple has to be distinguishable from an ordinary, single
value), you must end the value with a comma:
one_element_tuple_1 = (1, )
one_element_tuple_2 = 1.,
Removing the commas won't spoil the program in any
syntactical sense, but you will instead get two single
variables, not tuples.
CREATING TUPLE

ACCESSING TUPLE
If you want to get the elements of a tuple in order to read
them over, you can use the same conventions to which
you're accustomed while using lists.
The similarities may be misleading − don't try to modify a
tuple's contents! It's not a list!

ACCESSING TUPLE USING LOOPS
OUTPUT

You cannot remove or delete or update items in a
tuple.
Tuples are unchangeable, so you cannot remove
items from it, but you can delete the tuple completely:
NOTE: TUPLES ARE IMMUTABLE
REMOVING A TUPLE

Python provides two built-in methods that you can
use on tuples.
1. count() Method
2. index() Method
TUPLE METHODS

1. count() Method
Return the number of times the value appears in the
tuple
Count()
method
returns
total no
times
‘banana’
present in
the given
tuple
TUPLE METHODS

What else can tuples do for you?
•the len() function accepts tuples, and returns the
number of elements contained inside;
•the + operator can join tuples together (we've shown
you this already)
•the * operator can multiply tuples, just like lists;
•the in and not in operators work in the same way as in
lists.

my_tuple = (1, 10, 100)
t1 = my_tuple + (1000, 10000)
t2 = my_tuple * 3
print(len(t2))
print(t1)
print(t2)
print(10 in my_tuple)
print(-10 not in my_tuple)
The output should look
as follows:
9
(1, 10, 100, 1000,
10000)
(1, 10, 100, 1, 10, 100,
1, 10, 100)
True
True

•One of the most useful tuple properties is their ability
to appear on the left side of the assignment operator.
• A tuple's elements can be variables, not only literals.
Moreover, they can be expressions if they're on the right side
of the assignment operator.
var = 123
t1 = (1, )
t2 = (2, )
t3 = (3, var)
t1, t2, t3 = t2, t3, t1
print(t1, t2, t3)

2. index() Method
index() Method returns index of
“banana” i.e 1
index()
Method
TUPLE METHODS

LIST TUPLE
Syntax for list is slightly
different comparing with
tuple
Syntax for tuple is slightly
different comparing with lists
Weekdays=[‘Sun’,’Mon’,
‘wed’,46,67]
type(Weekdays)
class<‘lists’>
twdays = (‘Sun’, ‘mon', ‘tue',
634)
type(twdays)
class<‘tuple’>
List uses [ and ] (square
brackets) to bind the
elements.
Tuple uses rounded brackets(
and ) to bind the elements.
DIFFERENCE BETWEEN LIST AND TUPLE

LIST TUPLE
List can be edited once it
is created in python. Lists
are mutable data
structure.
A tuple is a list which one
cannot edit once it is created in
Python code. The tuple is an
immutable data structure
More methods or functions
are associated with lists.
Compare to lists tuples have
Less methods or functions.
DIFFERENCE BETWEEN LIST AND TUPLE

Dictionaries
The dictionary is another Python data structure. It's not a
sequence type (but can be easily adapted to sequence processing)
and it is mutable.
Dictionaries are not lists - they don't preserve the order of their
data, as the order is completely meaningless (unlike in real, paper
dictionaries).
In Python 3.6x dictionaries have become ordered collections by
default. Your results may vary depending on what Python version
you're using. The order in which a dictionary stores its data is
completely out of your control, and your expectations.

In Python's world, the word you look for is named a key. The word
you get from the dictionary is called a value.
This means that a dictionary is a set of key-value pairs. Note:
•each key must be unique − it's not possible to have more than one
key of the same value;
•a key may be any immutable type of object: it can be a number
(integer or float), or even a string, but not a list;
•a dictionary is not a list − a list contains a set of numbered values,
while a dictionary holds pairs of values;
•the len() function works for dictionaries, too − it returns the number
of key-value elements in the dictionary;
•a dictionary is a one-way tool − if you have an English-French
dictionary, you can look for French equivalents of English terms, but
not vice versa.
Dictionaries

How to use a dictionary
dictionary = {"cat": "chat", "dog": "chien", "horse": "cheval"}
phone_numbers = {'boss' : 5551234567, 'Suzy' : 22657854310}
empty_dictionary = {}
print(dictionary['cat'])
print(phone_numbers['Suzy’])
Getting a dictionary's value resembles indexing, especially thanks to the brackets
surrounding the key's value.
Note:
•if the key is a string, you have to specify it as a string;
•keys are case-sensitive: 'Suzy' is something different from 'suzy'.
The snippet outputs two lines of text:
chat
5557654321
you mustn't use a non-existent key.

Dictionary methods and functions
Can dictionaries be browsed using the for loop, like lists or tuples?
No and yes.
No, because a dictionary is not a sequence type − the for loop is
useless with it.
Yes, because there are simple and very effective tools that can adapt
any dictionary to the for loop requirements (in other words,
building an intermediate link between the dictionary and a temporary
sequence entity).

The keys() method
keys(), is possessed by each dictionary. The
method returns an iterable object consisting of all
the keys gathered within the dictionary. Having a
group of keys enables you to access the whole
dictionary in an easy and handy way. dictionary =
{"cat": "chat", "dog": "chien", "horse": "che
val"}
for key in dictionary.keys():
print(key, "->", dictionary[key]

The items() method
items() method returns tuples (this is the first example where
tuples are something more than just an example of
themselves) where each tuple is a key-value pair.
dictionary =
{"cat": "chat", "dog": "chien", "horse": "cheval"}
for english, french in dictionary.items():
print(english, "->", french)
Note the way in which the tuple has been used as a for loop
variable.

Modifying and adding values in Dictionary
Assigning a new value to an existing key is simple - as
dictionaries are fully mutable, there are no obstacles to
modifying them.
We're going to replace the value "chat" with "minou", which is
not very accurate, but it will work well with our example.
dictionary =
dictionary['cat'] = 'minou'
print(dictionary)
The output is:
{'cat': 'minou', 'dog': 'chien', 'horse': 'cheval'}

Do you want it sorted? Just enrich the for loop to get such a form:
for key in sorted(dictionary.keys()):
There is also a method called values(), which works similarly
to keys(), but returns values.
Here is a simple example:
dictionary =
for french in dictionary.values():
print(french)
As the dictionary is not able to automatically find a key for a given
value, the role of this method is rather limited.
Modifying and adding values in Dictionary

Adding a new key-value pair to a dictionary is as simple as changing a
value – you only have to assign a value to a new, previously non-
existent key.
Note: this is very different behavior compared to lists, which don't allow
you to assign values to non-existing indices.
Let's add a new pair of words to the dictionary − a bit weird, but still valid:
dictionary =
dictionary['swan'] = 'cygne'
print(dictionary)
The example outputs:
{'cat': 'chat', 'dog': 'chien', 'horse': 'cheval', 'swan': '
cygne’}
Adding a new key in Dictionary

You can also insert an item to a dictionary by using
the update() method, e.g.:
dictionary =
{"cat": "chat", "dog": "chien", "horse": "che
val"}
dictionary.update({"duck": "canard"})
print(dictionary)
Adding a new key in Dictionary

Removing a key in Dictionary
Can you guess how to remove a key from a dictionary?
Note: removing a key will always cause the removal of the associated
value. Values cannot exist without their keys.
This is done with the del instruction.
Here's the example:
dictionary = {"cat": "chat", "dog": "chien", "horse": "cheval"}
del dictionary['dog']
print(dictionary)
Note: removing a non-existing key causes an error.
The example outputs:
{'cat': 'chat', 'horse': 'cheval’}

To remove the last item in a dictionary, you can use
the popitem() method:
dictionary =
{"cat": "chat", "dog": "chien", "horse": "cheval"
}
dictionary.popitem()
print(dictionary) # outputs: {'cat': 'chat',
'dog': 'chien’}
In the older versions of Python, i.e., before 3.6.7,
the popitem() method removes a random item from a
dictionary.
Removing a key in Dictionary

TUPLE DICTIONARY
Order is maintained. Ordering is not guaranteed.
They are immutable. Values in a dictionary can be
changed.
They can hold any type,
and types can be mixed.
Every entry has a key and a
value.
DIFFERENCE BETWEEN TUPLE AND
DICTIONARY
Tuples and dictionaries can work together

TUPLE DICTIONARY
Elements are accessed via
numeric (zero based)
indices
Elements are accessed using
key's values
There is a difference in
syntax and looks easy to
define tuple
Differ in syntax, looks bit
complicated when compare
with Tuple or lists
DIFFERENCE BETWEEN TUPLE AND
DICTIONARY

Python Exceptions Handling
Python provides a very important features to handle any unexpected error in
your Python programs and to add debugging capabilities in them:
 Exception Handling: This would be covered in this tutorial.
What is Exception?
An exception is an event, which occurs during the execution of a program,
that disrupts the normal flow of the program's instructions.
In general, when a Python script encounters a situation that it can't cope with,
it raises an exception. An exception is a Python object that represents an
error.
When a Python script raises an exception, it must either handle the exception
immediately otherwise it would terminate and come out.

Handling an exception
If you have some suspicious code that may raise an exception, you can
defend your program by placing the suspicious code in a try: block.
After the try: block, include an except: statement, followed by a block of code
which handles the problem as elegantly as possible.
Syntax:
try:
You do your operations here;
......................
except Exception I:
If there is ExceptionI, then execute this block.
except Exception II:
If there is ExceptionII, then execute this block.
......................
else:
If there is no exception then execute this block.

Here are few important points above the above mentioned syntax:
A single try statement can have multiple except statements. This is useful
when the try block contains statements that may throw different types of
exceptions.
You can also provide a generic except clause, which handles any exception.
After the except clause(s), you can include an else-clause. The code in the
else-block executes if the code in the try: block does not raise an exception.
The else-block is a good place for code that does not need the try: block's
protection.

Example:
try:
fh = open("testfile", "w")
fh.write("This is my test file for exception
handling!!")
except IOError: print "Error: can't find file or read
data"
else: print "Written content in the file successfully"
fh.close()
This will produce following result:
Written content in the file successfully

The except clause with no exceptions:
You can also use the except statement with no exceptions defined as follows:
try:
......................
except:
If there is any exception, then execute this block.
......................
else:
This kind of a try-except statement catches all the exceptions that occur. Using this
kind of try-except statement is not considered a good programming practice, though,
because it catches all exceptions but does not make the programmer identify the root
cause of the problem that may occur.

The except clause with multiple exceptions:
You can also use the same except statement to handle multiple
exceptions as follows:
try:
......................
except(Exception1[, Exception2[,...ExceptionN]]]):
If there is any exception from the given exception
list, then execute this block
.......................
else:

Standard Exceptions
Here is a list standard Exceptions available in Python: Standard
Exceptions
The try-finally clause:
You can use a finally: block along with a try: block. The finally block
is a place to put any code that must execute, whether the try-block raised an
exception or not. The syntax of the try-finally statement is this:
try:
......................
Due to any exception, this may be skipped.
finally:
This would always be executed.
......................
Note that you can provide except clause(s), or a finally clause, but
not both. You can not use else clause as well along with a finally clause.

Example:
try:
fh = open("testfile", "w")
fh.write("This is my test file for exception
handling!!")
finally:
print "Error: can't find file or read data"
If you do not have permission to open the file in writing mode then this
will produce following result:
Error: can't find file or read data
Standard Exceptions

Argument of an Exception
An exception can have an argument, which is a value that gives
additional information about the problem. The contents of the argument vary
by exception. You capture an exception's argument by supplying a variable in
the except clause as follows:
try:
......................
except ExceptionType, Argument:
You can print value of Argument here...
If you are writing the code to handle a single exception, you can have a
variable follow the name of the exception in the except statement. If you are
trapping multiple exceptions, you can have a variable follow the tuple of the
exception.
This variable will receive the value of the exception mostly containing the
cause of the exception. The variable can receive a single value or multiple
values in the form of a tuple. This tuple usually contains the error string, the
error number, and an error location.

Example:
Following is an example for a single exception:
def temp_convert(var):
try:
return int(var)
except ValueError, Argument:
print "The argument does not contain
numbersn", Argument
temp_convert("xyz");
This would produce following result:
The argument does not contain numbers
invalid literal for int() with base 10: 'xyz'
Argument of an Exception

Raising an exceptions
You can raise exceptions in several ways by using the raise
statement. The general syntax for the raise statement.
Syntax:
raise [Exception [, args [, traceback]]]
Here Exception is the type of exception (for example, NameError) and
argument is a value for the exception argument. The argument is optional; if
not supplied, the exception argument is None.
The final argument, traceback, is also optional (and rarely used in practice),
and, if present, is the traceback object used for the exception
Example:
def functionName( level ):
if level < 1:
raise "Invalid level!", level
# The code below to this would not be executed
# if we raise the exception

Note: In order to catch an exception, an "except" clause must refer to
the same exception thrown either class object or simple string. For
example to capture above exception we must write our except clause
as follows:
try:
Business Logic here...
except "Invalid level!":
Exception handling here...
else:
Rest of the code here...
Raising an exceptions

User-Defined Exceptions
Python also allows you to create your own exceptions by deriving classes
from the standard built-in exceptions.
Here is an example related to RuntimeError. Here a class is created that is
subclassed from RuntimeError. This is useful when you need to display more
specific information when an exception is caught.
In the try block, the user-defined exception is raised and caught in the except
block. The variable e is used to create an instance of the class Networkerror.
class Networkerror(RuntimeError):
def __init__(self, arg):
self.args = arg
So once you defined above class, you can raise your exception as follows:
try:
raise Networkerror("Bad hostname")
except Networkerror,e:
print e.args

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