Cython 快速列表 / numpy 访问

Question

I have a Python function I'm trying to speed up, which just takes a line of tshark output, eg:

'1\t0.000000000\tTCP\t100.0.1.190,111.0.0.2\t35291\t55321\t\t\t56\t20\t··········S·\t36\n'

and assigns the data to variables like so:

            arr = line.strip('\n').split("\t")

            sip = arr[3].split(',')[0]
            dip = arr[3].split(',')[1]

            s_flag = 1 if 'S' in arr[10] else '0'
            a_flag = 1 if 'A' in arr[10] else '0'
            f_flag = 1 if 'F' in arr[10] else '0'
            r_flag = 1 if 'R' in arr[10] else '0'
            p_flag = 1 if 'P' in arr[10] else '0'
            u_flag = 1 if 'U' in arr[10] else '0'
            e_flag = 1 if 'E' in arr[10] else '0'
            c_flag = 1 if 'C' in arr[10] else '0'

What is a way to speed this up using Cython? I'm thinking of casting the results of line.strip('\n').split("\t") to a numpy array since I heard it's faster than Python lists in Cython? How else can I speed this up? eg:

import numpy
cimport numpy

arr = np.array(line.strip('\n').split("\t"))

Will this work? Thank you in advance!

Answer 1

Since you're dealing with lists of strings, numpy, and likely even cython won't help you much. The transformations you are looking for are so trivial, you can just clean up your python code a bit and move on:

FLAGS = np.array(list('SAFRPUEC'))

items = line.strip('\n').split("\t")
sip, dip = items[3].split(',')
flags = dict(zip(FLAGS, np.isin(FLAGS, list(items[10]))))