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This module provides utility functions for generating test arrays and validating sorting algorithms.

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Functions

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rand_int_array

Generates an array of random integers. 
from dsa.sorttools import rand_int_array

array = rand_int_array(n, maxnum)
​
n
int
required
The number of integers to generate
​
maxnum
int
required
The maximum number in the range (0 to maxnum inclusive)
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array
list
Array of n random integers from 0 to maxnum
Example
from dsa.sorttools import rand_int_array

# Generate 10 random integers between 0 and 100
array = rand_int_array(10, 100)
print(array)  # [45, 23, 89, 12, 67, 34, 91, 5, 78, 56]

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filled_array

Generates a sorted array filled with integers from 0 to n-1. 
from dsa.sorttools import filled_array

array = filled_array(n)
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n
int
required
The number of integers to generate
​
array
list
Array filled with integers from 0 to n-1 in ascending order
Example
from dsa.sorttools import filled_array

# Generate array [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
array = filled_array(10)
print(array)  # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

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shuffle_array

Generates a shuffled array with integers from 0 to n-1. 
from dsa.sorttools import shuffle_array

array = shuffle_array(n)
​
n
int
required
The number of integers to generate
​
array
list
Randomly shuffled array containing integers from 0 to n-1
Example
from dsa.sorttools import shuffle_array

# Generate shuffled array of integers 0-9
array = shuffle_array(10)
print(array)  # [7, 2, 9, 0, 5, 3, 8, 1, 6, 4] (random order)

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is_sorted

Checks if an array is sorted in ascending order. 
from dsa.sorttools import is_sorted

result = is_sorted(array)
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array
list
required
The array to verify
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result
bool
True if the array is sorted in ascending order, False otherwise
from dsa.sorttools import is_sorted

array = [1, 2, 3, 4, 5]
print(is_sorted(array))  # True

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array_details

Returns a formatted string with array statistics. 
from dsa.sorttools import array_details

details = array_details(array)
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array
list
required
The array to analyze
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details
str
String containing count of elements, first 10 elements, and last 10 elements
Example
from dsa.sorttools import shuffle_array, array_details

array = shuffle_array(100)
details = array_details(array)
print(details)
# Count: 100 first 10: [7, 23, 45, ...] last 10: [..., 89, 12, 56]

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generate_almost_sorted_array

Generates an almost sorted array with a specified number of random swaps. 
from dsa.sorttools import generate_almost_sorted_array

array = generate_almost_sorted_array(size, swaps)
​
size
int
required
The size of the array to generate
​
swaps
int
required
The number of adjacent elements to swap to create disorder
​
array
list
Array of integers that is mostly sorted with specified local swaps
from dsa.sorttools import generate_almost_sorted_array

# Generate array that's almost sorted (only 5 swaps)
array = generate_almost_sorted_array(100, 5)
print(array[:20])  # [0, 1, 2, 3, 5, 4, 6, 7, 8, 10, 9, ...]
Performance Benchmarking:
  • Use rand_int_array() for average case testing
  • Use filled_array() for best case testing (already sorted)
  • Use shuffle_array() for worst case testing (completely random)
  • Use generate_almost_sorted_array() for testing adaptive algorithms
Validation:
  • Use is_sorted() to verify your sorting algorithm works correctly
  • Use array_details() to inspect large arrays without printing all elements
Example Test Suite:
from dsa.sorttools import (
    rand_int_array,
    shuffle_array,
    generate_almost_sorted_array,
    is_sorted
)

def test_sort_algorithm(sort_func):
    # Test random array
    array1 = rand_int_array(100, 1000)
    sort_func(array1)
    assert is_sorted(array1), "Failed on random array"
    
    # Test shuffled array
    array2 = shuffle_array(100)
    sort_func(array2)
    assert is_sorted(array2), "Failed on shuffled array"
    
    # Test almost sorted array
    array3 = generate_almost_sorted_array(100, 10)
    sort_func(array3)
    assert is_sorted(array3), "Failed on almost sorted array"
    
    print("All tests passed!")

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