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https://github.com/alfex4936/python-bigo-calculator
Python sorting functions time complexity calculator
https://github.com/alfex4936/python-bigo-calculator
algorithm calculator complexity python sorting-functions
Last synced: about 1 month ago
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Python sorting functions time complexity calculator
- Host: GitHub
- URL: https://github.com/alfex4936/python-bigo-calculator
- Owner: Alfex4936
- License: mit
- Created: 2020-08-28T12:25:33.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2023-01-07T06:51:32.000Z (almost 2 years ago)
- Last Synced: 2024-11-08T16:05:58.293Z (about 2 months ago)
- Topics: algorithm, calculator, complexity, python, sorting-functions
- Language: Python
- Homepage: https://pypi.org/project/big-O-calculator/
- Size: 269 KB
- Stars: 26
- Watchers: 2
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
## Table of Contents
* [Methods](https://github.com/Alfex4936/python-bigO-calculator#methods-parameters)
* [Usage](https://github.com/Alfex4936/python-bigO-calculator#usage)
* [QuickSort example](https://github.com/Alfex4936/python-bigO-calculator#quick-sort-example)
* [test_all() exmaple](https://github.com/Alfex4936/python-bigO-calculator#test_allmysort-example)
* [runtime() exmaple](https://github.com/Alfex4936/python-bigO-calculator#runtimemysort-example)
* [compare() exmaple](https://github.com/Alfex4936/python-bigO-calculator#comparemysort-thissort-example)
* [@isSorted decorator](https://github.com/Alfex4936/python-bigO-calculator#issorted)
* [Array generators](https://github.com/Alfex4936/python-bigO-calculator#array-generators)
* [Test arrays sample](https://github.com/Alfex4936/python-bigO-calculator#test-arrays-sample-size--20)
# Big-O Caculator
A big-O calculator to estimate time complexity of sorting functions.
inspired by : https://github.com/ismaelJimenez/cpp.leastsq
[](https://hits.seeyoufarm.com) [](https://pepy.tech/project/big-o-calculator)
## Installation
```bash
pip install big-O-calculator
```
## What it does
You can test time complexity, calculate runtime, compare two sorting algorithms
Results may vary.
(n : [10, 100, 1_000, 10_000, 100_000])
```py
Big-O calculator
Methods:
def test(function, array="random", limit=True, prtResult=True):
It will run only specified array test, returns Tuple[str, estimatedTime]
def test_all(function):
It will run all test cases, prints (best, average, worst cases), returns dict
def runtime(function, array="random", size, epoch=1):
It will simply returns execution time to sort length of size of test array, returns Tuple[float, List[Any]]
def compare(function1, function2, array, size, epoch=3):
It will compare two functions on {array} case, returns dict
```
## Methods parameters
```py
def test(**args):
function [Callable]: a function to call.
array [str]: "random", "big", "sorted", "reversed", "partial", "Ksorted", "string", "almost_equal", "equal", "hole".
limit [bool] = True: To break before it takes "forever" to sort an array. (ex. selectionSort)
prtResult [bool] = True: Whether to print result by itself
def test_all(**args):
function [Callable]: a function to call.
def runtime(**args):
function [Callable]: a function to call.
array: "random", "big", "sorted", "partial", "reversed", "Ksorted" ,
"hole", "equal", "almost_equal" or your custom array.
size [int]: How big test array should be.
epoch [int]: How many tests to run and calculte average.
prtResult (bool): Whether to print the result by itself. (default = True)
def compare(**args):
function1 [Callable]: a function to compare.
function2 [Callable]: a function to compare.
array [str]|[List]: "random", "big", "sorted", "partial", "reversed", "Ksorted",
"hole", "equal", "almost_equal", "all" or your custom array.
size [int]: How big test array should be.
```
Info:
To see the result of function, return the array.
These methods will also check if the function sorts correctly.
"K" in Ksorted uses testSize.bit_length().
## Usage
```py
from bigO import BigO
from bigO import algorithm
lib = BigO()
lib.test(bubbleSort, "random")
lib.test_all(bubbleSort)
lib.runtime(bubbleSort, "random", 5000)
lib.runtime(algorithm.insertSort, "reversed", 32)
lib.compare(algorithm.insertSort, algorithm.bubbleSort, "all", 5000)
```
## Quick Sort Example
```py
from bigO import BigO
from random import randint
def quickSort(array): # in-place | not-stable
"""
Best : O(nlogn) Time | O(logn) Space
Average : O(nlogn) Time | O(logn) Space
Worst : O(n^2) Time | O(logn) Space
"""
if len(array) <= 1:
return array
smaller, equal, larger = [], [], []
pivot = array[randint(0, len(array) - 1)]
for x in array:
if x < pivot:
smaller.append(x)
elif x == pivot:
equal.append(x)
else:
larger.append(x)
return quickSort(smaller) + equal + quickSort(larger)
lib = BigO()
complexity = lib.test(quickSort, "random")
complexity = lib.test(quickSort, "sorted")
complexity = lib.test(quickSort, "reversed")
complexity = lib.test(quickSort, "partial")
complexity = lib.test(quickSort, "Ksorted")
''' Result
Running quickSort(random array)...
Completed quickSort(random array): O(nlog(n))
Running quickSort(sorted array)...
Completed quickSort(sorted array): O(nlog(n))
Running quickSort(reversed array)...
Completed quickSort(reversed array): O(nlog(n))
Running quickSort(partial array)...
Completed quickSort(partial array): O(nlog(n))
Running quickSort(Ksorted array)...
Completed quickSort(ksorted array): O(nlog(n))
'''
```
## Selection Sort Example
```py
from bigO import BigO
def selectionSort(array): # in-place, unstable
'''
Best : O(n^2) Time | O(1) Space
Average : O(n^2) Time | O(1) Space
Worst : O(n^2) Time | O(1) Space
'''
currentIdx = 0
while currentIdx < len(array) - 1:
smallestIdx = currentIdx
for i in range(currentIdx + 1, len(array)):
if array[smallestIdx] > array[i]:
smallestIdx = i
array[currentIdx], array[smallestIdx] = array[smallestIdx], array[currentIdx]
currentIdx += 1
return array
lib = BigO()
complexity = lib.test(selectionSort, "random")
complexity = lib.test(selectionSort, "sorted")
complexity = lib.test(selectionSort, "reversed")
complexity = lib.test(selectionSort, "partial")
complexity = lib.test(selectionSort, "Ksorted")
''' Result
Running selectionSort(random array)...
Completed selectionSort(random array): O(n^2)
Running selectionSort(sorted array)...
Completed selectionSort(sorted array): O(n^2)
Running selectionSort(reversed array)...
Completed selectionSort(reversed array): O(n^2)
Running selectionSort(partial array)...
Completed selectionSort(partial array): O(n^2)
Running selectionSort(Ksorted array)...
Completed selectionSort(ksorted array): O(n^2)
'''
```
## test_all(mySort) Example
We can test all "random", "sorted", "reversed", "partial", "Ksorted", "almost_equal" at once,
and it shows, best, average and worst time complexity
```py
from bigO import BigO
lib = BigO()
lib.test_all(bubbleSort)
lib.test_all(insertSort)
result = lib.test_all(selectionSort)
print(result) # Dictionary
''' Result
Running bubbleSort(tests)
Best : O(n) Time
Average : O(n^2) Time
Worst : O(n^2) Time
Running insertSort(tests)
Best : O(n) Time
Average : O(n^2) Time
Worst : O(n^2) Time
Running selectionSort(tests)
Best : O(n^2) Time
Average : O(n^2) Time
Worst : O(n^2) Time
{'random': 'O(n^2)', 'sorted': 'O(n^2)', 'reversed': 'O(n^2)', 'partial': 'O(n^2)', 'Ksorted': 'O(n^2)'}
'''
```
## runtime(mySort) Example
array: "random", "big", "sorted", "partial", "reversed", "Ksorted",
"hole", "equal", "almost_equal" or your custom array.
```py
from bigO import BigO
from bigO import algorithm
lib = BigO()
timeTook, result = lib.runtime(algorithm.bubbleSort, "random", 5000)
custom = ["abc", "bbc", "ccd", "ef", "az"]
timeTook, result = lib.runtime(algorithm.bubbleSort, custom)
''' Result
Running bubbleSort(len 5000 random array)
Took 2.61346s to sort bubbleSort(random)
Running bubbleSort(len 5 custom array)
Took 0.00001s to sort bubbleSort(custom)
'''
```
## compare(mySort, thisSort) Example
array: "random", "big", "sorted", "partial", "reversed", "Ksorted",
"hole", "equal", "almost_equal", "all" or your custom array.
```py
lib = BigO()
result = lib.compare(algorithm.bubbleSort, algorithm.insertSort, "reversed", 5000)
result = lib.compare(algorithm.insertSort, algorithm.insertSortOptimized, "reversed", 5000)
result = lib.compare(algorithm.quickSort, algorithm.quickSortHoare, "reversed", 50000)
result = lib.compare(algorithm.timSort, algorithm.introSort, "reversed", 50000)
result = lib.compare(sorted, algorithm.introSort, "reversed", 50000)
result = lib.compare(algorithm.bubbleSort, algorithm.insertSort, "all", 5000)
print(result)
'''Result
bubbleSort is 3.6% faster than insertSort on reversed case
Time Difference: 0.04513s
insertSortOptimized is 5959.3% faster than insertSort on reversed case
Time Difference: 1.25974s
quickSortHoare is 153.6% faster than quickSort on reversed case
Time Difference: 0.09869s
introSort is 206.6% faster than timSort on reversed case
Time Difference: 0.12597s
sorted is 12436.9% faster than introSort on reversed case
Time Difference: 0.06862s
Running bubbleSort(tests) vs insertSort(tests)
insertSort is 32.6% faster than bubbleSort on 6 of 8 cases
Time Difference: 0.11975s
{'bubbleSort': 0.4875642249999998, 'insertSort': 0.3678110916666666}
'''
```
## @isSorted
If it sorts correctly, it shows: "mySort sorts correctly."
Otherwise, it shows like,
"mySort doesn't sort correctly."
"At N index: [...100, -72, 121...]
```py
from bigO import BigO
from bigO import utils
@utils.is_sorted
def bubbleSort(array): # in-place | stable
isSorted = False
counter = 1 # not correct
while not isSorted:
isSorted = True
for i in range(len(array) - 1 - counter):
if array[i] > array[i + 1]:
array[i], array[i + 1] = array[i + 1], array[i]
isSorted = False
counter += 1
return array
if __name__ == "__main__":
bubbleSort(BigO.gen_random_ints(100))
''' Result
bubbleSort doesn't sort correctly.
At 99 index: [...99, -76]
'''
```
## Array generators
```py
from bigO import BigO
lib = BigO()
arr = lib.gen_random_ints(100)
arr = lib.gen_random_big_ints(100)
arr = lib.gen_random_strings(100)
arr = lib.gen_sorted_ints(100)
arr = lib.gen_reversed_ints(100)
arr = lib.gen_partial_ints(100)
arr = lib.gen_ksorted_ints(100)
arr = lib.gen_equal_ints(100)
arr = lib.gen_almost_equal_ints(100)
arr = lib.gen_hole_ints(100)
```
## Test arrays sample (size = 20)
Results vary.
```py
random = [15, 15, -11, -16, -19, -16, -14, 14, 19, 2, 18, -10, 5, -17, -4, -2, 9, 12, 8, 12]
randomBig = [-996061023766482, 347955820115093, ...]
string = ['rwe55pi8hkwpjv5rhhoo', '5ecvybo5xi8p25wanh3t', ...]
sorted = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]
reversed = [19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
partial = [-18, 14, 7, -11, 17, 5, 6, 7, 8, 9, 14, 9, -13, 0, 14, -17, -18, -9, -16, 14]
Ksorted = [-4, -5, -6, -7, -8, -9, -10, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 9, 8]
almost_equal = [19, 19, 19, 20, 20, 19, 20, 20, 21, 19, 20, 21, 21, 19, 19, 21, 20, 19, 21, 19]
equal = [16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16]
hole = [-7, -7, -7, -7, -7, -7, -9999, -7, -7, -7, -7, -7, -7, -7, -7, -7, -7, -7, -7, -7]
```
## Built-in algorithms list
Visit [here](https://github.com/Alfex4936/python-bigO-calculator/blob/master/bigO/algorithm.py) to see codes
BinaryInsertSort, BubbleSort, CountSort, gnomeSort, heapSort,
InsertSort, InsertSortOptimized, IntroSort,
mergeSort, quickSort(random pivot), quickSortHoare(Hoare+Tail recur+InsertionSort), timSort(simplified)
## Benchmarks
Visit [here](https://github.com/Alfex4936/python-bigO-calculator/tree/master/benchmarks) for more results
