pysorting.utils

Exceptions

InvalidElementTypeError	Custom exception raised when elements are not strings or lists of strings.
NonUniformTypeError	Custom exception raised when elements are not strings or lists of strings.
InvalidAscendingTypeError	Custom exception raised when 'ascending' is not a boolean.

Functions

timer(func)	A decorator function that measures and prints the execution time of a given function.
sorting_time(sorting_function, data)	Measures the execution time of a given sorting function.
find_fastest_sorting_function(data, *sorting_functions)	Determines the fastest sorting function by measuring execution time.
is_sorted(lst[, ascending])	Determines whether a list is sorted in ascending or descending order.
validate_list_elements(elements)	Validates whether all elements in a list are of the same type: either all numerical (int or float)

Module Contents

exception pysorting.utils.InvalidElementTypeError(message='All elements must be either a string or a list of strings.')

Bases: Exception

Custom exception raised when elements are not strings or lists of strings.

message = 'All elements must be either a string or a list of strings.'

exception pysorting.utils.NonUniformTypeError(message='Elements are not of the same type.')

Bases: Exception

Custom exception raised when elements are not strings or lists of strings.

message = 'Elements are not of the same type.'

exception pysorting.utils.InvalidAscendingTypeError(message="The parameter 'ascending' must be a boolean value.")

Bases: Exception

Custom exception raised when ‘ascending’ is not a boolean.

message = "The parameter 'ascending' must be a boolean value."

pysorting.utils.timer(func)

A decorator function that measures and prints the execution time of a given function.

This decorator records the start and end time of the function execution, calculates the elapsed time, and prints the time taken in seconds. The result of the wrapped function along with the execution time is returned.

Parameters:

funcfunction

The function whose execution time is to be measured.

Returns:

function

A wrapper function that executes the given function and measures its execution time.

Notes:

• The execution time is measured using the time module.

• The function returns both the result of the original function and the time taken for execution.

• This decorator can be used to evaluate the performance of sorting algorithms and other time-sensitive functions.

Examples:

Using the timer decorator on a sorting function:

>>> @timer
... def sample_sort(arr):
...     return sorted(arr)

>>> sample_sort([5, 2, 8, 1, 3])
Function 'sample_sort' executed in 0.000002 seconds.
([1, 2, 3, 5, 8], 2e-06)

pysorting.utils.sorting_time(sorting_function, data)

Measures the execution time of a given sorting function.

This function wraps the specified sorting function using the timer decorator to measure how long it takes to sort the provided dataset.

Parameters:

sorting_functionfunction

The sorting function whose execution time needs to be measured. It should accept a list as input and return a sorted list.

datalist

The list of values to be sorted. A copy of this list is passed to the sorting function to prevent modification of the original data.

Returns:

float

The execution time (in seconds) of the sorting function.

Notes:

• The function uses the timer decorator to record execution time.

• A copy of the input data is passed to the sorting function to avoid side effects.

• Useful for benchmarking different sorting algorithms.

Examples:

Measuring the execution time of a sorting function:

>>> test_data = [5, 2, 8, 1, 3]
>>> sorting_time(quick_sort, test_data)
Function 'quick_sort' executed in 0.000002 seconds.
0.0000024567

pysorting.utils.find_fastest_sorting_function(data, *sorting_functions)

Determines the fastest sorting function by measuring execution time.

This function tests multiple sorting functions on the same dataset, measures their execution times, and identifies the fastest one. The execution times for all sorting functions are displayed in a formatted table.

Parameters:

datalist

The list of values to be sorted. A copy of this list is passed to each sorting function to ensure that the original data remains unmodified.

sorting_functionstuple of functions

A variable number of sorting functions to be tested. Each function should accept a list as input and return a sorted list.

Returns:

tuple

A tuple containing: - fastest_function (function): The sorting function with the shortest execution time. - fastest_time (float): The execution time (in seconds) of the fastest function.

Notes:

• Each sorting function is wrapped using the timer decorator to measure execution time.

• The execution times of all tested functions are displayed in a table format using tabulate.

• The function automatically selects the sorting function with the minimum execution time.

Examples:

Comparing multiple sorting functions:

>>> test_data = [5, 2, 8, 1, 3]
>>> fastest_function, fastest_time = find_fastest_sorting_function(test_data, bubble_sort, quick_sort)
┏━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓
┃ Function      ┃ Time taken (s)  ┃
┡━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩
├ bubble_sort   │ 0.0000253456    │
├ quick_sort    │ 0.0000024567    │
└───────────────┴────────────────┘
>>> print(f"The fastest function is {fastest_function.__name__} with a time of {fastest_time:.6f} seconds.")
The fastest function is quick_sort with a time of 0.000002 seconds.

pysorting.utils.is_sorted(lst, ascending=True)

Determines whether a list is sorted in ascending or descending order.

This function checks if the elements in the list are in non-decreasing (ascending) or non-increasing (descending) order, based on the ascending parameter.

Parameters:

lstlist

The list of elements to check. The function assumes the elements are comparable.

ascendingbool, optional

If True (default), checks whether the list is sorted in ascending order. If False, checks whether the list is sorted in descending order.

Returns:

bool

True if the list is sorted in the specified order, False otherwise.

Raises:

TypeError

If the list contains elements that cannot be compared.

Notes:

• An empty list or a list with a single element is considered sorted.

• The function performs a pairwise comparison to verify sorting order.

Examples:

Checking if a list is sorted in ascending order (default):

>>> is_sorted([1, 2, 3, 4, 5])
True

Checking if a list is sorted in descending order:

>>> is_sorted([5, 4, 3, 2, 1], ascending=False)
True

Checking an unsorted list:

>>> is_sorted([1, 3, 2, 4, 5])
False

pysorting.utils.validate_list_elements(elements)

Validates whether all elements in a list are of the same type: either all numerical (int or float) or all strings.

This function checks if a given list contains only numeric values (int or float) or only string values. If the list contains mixed data types, it is considered invalid.

Parameters:

elementslist

The list of elements to validate.

Returns:

bool

True if all elements in the list are either numerical (integers or floats) or all strings. False if the list contains mixed data types.

Raises:

TypeError

If the input is not a list.

Notes:

• An empty list is considered valid.

• The function does not check for None values explicitly.

• Useful for data validation in sorting, filtering, or numerical operations.

Examples:

Checking a valid list with numbers:

>>> validate_list_elements([1, 2, 3, 4.5])
True

Checking a valid list with strings:

>>> validate_list_elements(["apple", "banana", "cherry"])
True

Checking an invalid list with mixed types:

>>> validate_list_elements([1, "banana", 3.5])
False

Checking an empty list:

>>> validate_list_elements([])
True