Python 性能优化Cython实战指南

pip install cython

# example.pyx
def fibonacci(int n):
    cdef int a = 0
    cdef int b = 1
    cdef int i
    for i in range(n):
        a, b = b, a + b
    return a

# setup.py
from setuptools import setup
from Cython.Build import cythonize
setup(
    ext_modules=cythonize("example.pyx")
)

def compute(int n):
    cdef double result = 0.0
    cdef int i
    for i in range(n):
        result += i * i
    return result

import numpy as np
cimport numpy as np
def array_sum(np.ndarray[np.float64_t, ndim=1] arr):
    cdef double total = 0.0
    cdef int i
    cdef int n = arr.shape[0]
    for i in range(n):
        total += arr[i]
    return total

from cython.parallel import prange
def parallel_sum(double[:] arr):
    cdef double total = 0.0
    cdef int i
    cdef int n = arr.shape[0]
    with nogil:
        for i in prange(n, schedule='static'):
            total += arr[i]
    return total

def matrix_multiply(double[:, :] A, double[:, :] B):
    cdef int i, j, k
    cdef int n = A.shape[0]
    cdef int m = B.shape[1]
    cdef int p = A.shape[1]
    cdef double[:, :] C = np.zeros((n, m))
    for i in range(n):
        for j in range(m):
            for k in range(p):
                C[i, j] += A[i, k] * B[k, j]
    return np.asarray(C)

def blur_image(np.ndarray[np.uint8_t, ndim=3] image):
    cdef int h = image.shape[0]
    cdef int w = image.shape[1]
    cdef int c = image.shape[2]
    cdef np.ndarray[np.uint8_t, ndim=3] result = np.zeros_like(image)
    cdef int i, j, k
    for i in range(1, h-1):
        for j in range(1, w-1):
            for k in range(c):
                result[i, j, k] = (
                    image[i-1, j, k] + image[i+1, j, k] +
                    image[i, j-1, k] + image[i, j+1, k]
                ) // 4
    return result