Lecture Notes: Python Arrays

Introduction to Arrays

• Arrays are similar to lists but require all elements to be of the same type.
• Unlike lists, arrays cannot have mixed data types; all elements must be integers, floats, or another single type.
• Arrays are dynamic in size, meaning they can expand or shrink as needed.

Advantages of Arrays

• Flexibility in size (can add or remove elements).
• Methods to manipulate arrays, such as append() to add elements and index() to find elements.

When to Use Arrays

• Useful when dealing with large amounts of data of the same type, such as student grades.

How to Create an Array

• Import the array module: import array
• Syntax: array.array(typecode, [elements])
  • typecode specifies the data type of the array.
  • Example: int, float, unicode.

Type Codes and Memory

• Different type codes determine how much memory each element uses.
  • b for signed integers (1 byte).
  • B for unsigned integers (1 byte).
  • i for regular integers (2 bytes).
  • f for floats (4 bytes).
  • d for double precision floats (8 bytes).
  • u for Unicode characters (2 bytes).

Creating Integer Arrays

• Example: vals = array.array('i', [5, 9, 8, 4, 2])
• Arrays must contain only integers if typecode is 'i'.
• Attempting to add a float will result in an error.

Working with Arrays

• Arrays support various operations similar to lists.
  • Reverse an Array: vals.reverse()
  • Print Elements: Use loops to iterate through elements.
    • For loop with range(): for i in range(len(vals)): print(vals[i])
    • Enhanced for loop directly on array: for val in vals: print(val)

Creating a New Array

• Copying an array: new_array = array.array(vals.typecode, (a*a for a in vals))
  • This creates a new array with squared values of the original.

Using While Loops

• While loops can also iterate over arrays, but require manual management of index and loop controls.
  • Example:

    i = 0
    while i < len(new_array):
      print(new_array[i])
      i += 1
    

Summary

• Arrays are powerful when dealing with homogeneous data types in Python.
• The choice between using lists or arrays depends on the requirement of type consistency and memory management.