https://github.com/hansalemaos/cythonfastsort

C++ parallel sorting algorithms through Cython - up to 8 times faster than NumPy
https://github.com/hansalemaos/cythonfastsort

c cpp cython numpy parallel-computing parallel-programming python sorting

Last synced: about 2 months ago
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C++ parallel sorting algorithms through Cython - up to 8 times faster than NumPy

• Host: GitHub
• URL: https://github.com/hansalemaos/cythonfastsort
• Owner: hansalemaos
• License: mit
• Created: 2023-11-30T19:45:21.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-11-30T19:45:40.000Z (about 1 year ago)
• Last Synced: 2024-04-26T04:21:14.109Z (8 months ago)
• Topics: c, cpp, cython, numpy, parallel-computing, parallel-programming, python, sorting
• Language: Python
• Homepage: https://pypi.org/project/cythonfastsort
• Size: 22.5 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.MD
  • License: LICENSE

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README

        
# C++ parallel sorting algorithms through Cython - up to 8 times faster than NumPy 

## pip install cythonfastsort

### Tested against Windows / Python 3.11 / Anaconda

## Cython (and a C/C++ compiler) must be installed to use the optimized Cython implementation.

```python

import sys

import timeit

import numpy as np

from cythonfastsort import generate_random_arrays, sort_all

size = 10000000

arras = [

    (size, "float32", -555555555, 555555555),

    (size, "float64", -100000000000, 100000000000),

    (size, np.uint8, 0, 255),

    (size, np.int8, -120, 120),

    (size, np.int16, -30000, 30000),

    (size, np.int32, -555555555, 555555555),

    (size, np.int64, -(sys.maxsize-1)//2, (sys.maxsize-1)//2),

    (size, np.uint16, 0, 60000),

    (size, np.uint32, 0, 555555555),

    (size, np.uint64, 0, sys.maxsize-1),

]

reps = 3

for a in arras:

    arr = generate_random_arrays(*a)

    seq = generate_random_arrays(size // 10, *a[1:])

    s = """u=sort_all(arr)"""

    u = sort_all(arr)

    t1 = timeit.timeit(s, globals=globals(), number=reps) / reps

    print('c++ ', t1)

    s2 = """q=np.sort(arr)"""

    q = np.sort(arr)

    t2 = timeit.timeit(s2, globals=globals(), number=reps) / reps

    print('np ', t2)

    print(np.all(q == u))

    print("-----------------")

haystack = np.array(

    [

        b"Cumings",

        b"Heikkinen",

        b"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",

        b"aaa",

        b"bbbb()",

        b"Futrelle",

        b"Allen",

        b"Cumings, Mrs. John Bradley (Florence Briggs Thayer)q",

        b"Braund, Mr. Owen Harris",

        b"Heikkinen, Miss. Laina",

        b"Futrelle, Mrs. Jacques Heath (Lily May Peel)",

        b"Allen, Mr. William Henry",

        b"Braund",

    ],

    dtype="S",

)

arr = np.ascontiguousarray(np.concatenate([haystack for _ in range(200000)]))

reps = 5

s = """u=sort_all(arr)"""

u = sort_all(arr)

t1 = timeit.timeit(s, globals=globals(), number=reps) / reps

s = """u=np.sort(arr)"""

q = np.sort(arr)

t2 = timeit.timeit(s, globals=globals(), number=reps) / reps

print('c++ ', t1)

print('np ', t2)

print(np.all(q == u))

# c++  0.2110750000004676

# np  0.6982908999998472

# True

# -----------------

# c++  0.22871500000110245

# np  0.7115663999999621

# True

# -----------------

# c++  0.0869510999994721

# np  0.27525126666781335

# True

# -----------------

# c++  0.09770773333366378

# np  0.28797130000020843

# True

# -----------------

# c++  0.13066273333364128

# np  0.47454773333326256

# True

# -----------------

# c++  0.17967379999997016

# np  0.6125306666666196

# True

# -----------------

# c++  0.19168066666679806

# np  0.6346349666673632

# True

# -----------------

# c++  0.06744649999988421

# np  0.47243033333264367

# True

# -----------------

# c++  0.09263499999966977

# np  0.6186357666665572

# True

# -----------------

# c++  0.11886440000065097

# np  0.6260395666661983

# True

# -----------------

# c++  0.9570277200000419

# np  1.4337052399998356

# True

```