An array is a collection of memory locations that store elements of the same data type. Arrays have a fixed size and elements are accessed using an index. This document discusses array implementation using Python's array module. It describes how to create an array, access elements, insert/delete elements, search, update values, and traverse through an array. The key differences between arrays and lists in Python are that arrays have a fixed size and can only contain same-type elements, while lists can grow/shrink and hold mixed types.

1. UNIT 1- LINEAR DATA
STRUCTURES
ARRAY BASED
IMPLEMENTATION

2. Introduction
• An Array is a collection of memory locations.
• The memory locations cannot be split from
each other, so if there is some empty space, it
just goes waste.
• Arrays cannot be interchanged.
• A array is a collection of variables of same
type.

3. • Some points to be noted about an array:
1. It is a continuous chunk of memory with equally
sized blocks.
2. The subscript always begins with ‘0’ and goes until
‘n-1’ which is also continuous.
3.Any memory location can be directly accessed using
its subscript.
4. Static arrays have issues, such as memory wastage
and memory leak, and also have constraints over the
size. These are overcome by using dynamic arrays.
5. Since it is a continuous chunk of memory, it has
internal issues such as fragmentation and memory
leaks.

4. Why do we study Arrays?
• The array structure looks very similar to Python's list
structure.
• But there are two major differences between the array and
the list.
1. array has a limited number of operations whereas Lists
provides a large number of operations for working with the
contents of the list.
2. lists can grow and shrink during execution as elements are
added or removed while the size of an array cannot be
changed after it has been created.
• The array is best suited for problems requiring a sequence
in which the maximum number of elements are known up
front, whereas the list is the better choicewhen the size of
the sequence needs to change after it has been created.

5. Array Abstract Data Type
• Definition: A one-dimensional array is a
collection of contiguous elements in which
individual elements are identified by a unique
integer subscript starting with zero. Once an
array is created, its size cannot be changed.

6. • Array( size ): Creates a one-dimensional array consisting of
size elements with each element initially set to None. size
must be greater than zero.
• length (): Returns the length or number of elements in the
array.
• getitem ( index ): Returns the value stored in the array at
element position index. The index argument must be within
the valid range. Accessed using the subscript operator.
• setitem ( index, value ): Modifies the contents of the array
element at position index to contain value. The index must
be within the valid range. Accessed using the subscript
operator.
• clearing( value ): Clears the array by setting every element
to value.
• iterator (): Creates and returns an iterator that can be used
to traverse the elements of the array.

7. Basic operations of Arrays
Array( size ):
Creates a one-dimensional array consisting of size elements with each
element initially set to None. size must be greater than zero.
length (): Returns the length or number of elements in the array.
getitem ( index )
Returns the value stored in the array at element position index. The
index argument must be within the valid range. Accessed using the
subscript operator.
setitem ( index, value )
Modifies the contents of the array element at position index to contain
value. The index must be within the valid range. Accessed using the
subscript operator.
clearing( value ) Clears the array by setting every element to value.
iterator ()
Creates and returns an iterator that can be used to traverse the elements
of the array.

8. The ctypes Module
• Many of the data types and classes available in Python are actually
implemented using appropriate types from the C language.
• While Python does not provide the array structure as part of the
language itself, it now includes the ctypes module as part of the
Python Standard Library.
• The ctypes module provides the capability to create hardware-
supported arrays just like the ones used to implement Python's
string, list, tuple, and dictionary collection types.
• But the ctypes module is not meant for everyday use in Python
programs.
• Thus, the technique provided by the module for creating an array
should not typically be used directly within a Python program.
• But we can use it within our Array class to provide the functionality
defined by the Array ADT.

9. Concept of Arrays

10. Syntax of Arrays

11. Creating an Array in Python
• In Python, arrays are different from lists; lists can have array
items of data types, whereas arrays can only have items of the
same data type.
• Python has a separate module for handling arrays called array,
which you need to import before you start working on them.

12. Ways to create Arrays
• You can declare an array in Python while initializing it using
the following syntax.

13. • Identifier: specify a name like
usually, you do for variables
• Module: Python has a special
module for creating arrays,
called "array" – you must
import it before using it
• Method: the array module has
a method for initializing the
array. It takes two arguments,
typecode, and elements.
• Type Code: specify the data
type using the typecodes
available.
• Elements: specify the array
elements within the square
brackets, for example
[130,450,103]

14. Accessing an Array value

15. Array Operations - Insertion

16. Array Operations- Deletion

17. Array Operations - Searching

18. Array Operations- Update

19. Array Operations - Traverse