本篇內容主要講解“怎么加速python腳本”,感興趣的朋友不妨來看看。本文介紹的方法操作簡單快捷,實用性強。下面就讓小編來帶大家學習“怎么加速python腳本”吧!
因為近期要寫嵌套for循環,由于運算量有點大,耗時比較久。所以就在谷歌上搜了搜有沒有辦法可以提升python for loop的速度,然后就發現了非常好用的模塊:Numba
Numba makes Python code fast
官方網址:http://numba.pydata.org/
# download from tsinghua mirror sitewget https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-5.3.1-Linux-x86_64.sh# check the help messagebash Anaconda3-5.3.1-Linux-x86_64.sh -h# then install or install into Nonexistent Custom Directory by adding -pbash Anaconda3-5.3.1-Linux-x86_64.sh# add to the environmentecho ". /home/saber/anaconda3/etc/profile.d/conda.sh" >> ~/.bashrc
from numba import jit
import time
#define function A without numba
def func_A(a1,a2):
A_result=0
for i in range(a1,a2):
A_result+=i
return A_result
#define func A1 with numba
#just add the @jit
@jit
def func_A1(a1,a2):
A1_result=0
for i in range(a1,a2):
A1_result+=i
return A1_result
#record the elasped time
def time_func(func_A_i,*args):
start = time.time()
func_A_i(*args)
end = time.time()
print("Elasped time of func %s is %.4e"%(func_A_i.__name__,end-start))
time_func(func_A,1,10000000)
time_func(func_A,1,10000000)
print()
time_func(func_A1,1,10000000)
time_func(func_A1,1,10000000)
Elasped time of func func_A is 5.4757e-01
Elasped time of func func_A is 5.3267e-01
Elasped time of func func_A1 is 5.3686e-02
Elasped time of func func_A1 is 4.7684e-06
First, recall that Numba has to compile your function for the argument types given before it executes the machine code version of your function, this takes time. However, once the compilation has taken place Numba caches the machine code version of your function for the particular types of arguments presented. If it is called again the with same types, it can reuse the cached version instead of having to compile again.
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