问题
Suppose I have some Python code like the following:
input = open("input.txt")
x = (process_line(line) for line in input)
y = (process_item(item) for item in x)
z = (generate_output_line(item) + "\n" for item in y)
output = open("output.txt", "w")
output.writelines(z)
This code reads each line from the input file, runs it through several functions, and writes the output to the output file. Now I know that the functions process_line, process_item, and generate_output_line will never interfere with each other, and let's assume that the input and output files are on separate disks, so that reading and writing will not interfere with each other.
But Python probably doesn't know any of this. My understanding is that Python will read one line, apply each function in turn, and write the result to the output, and then it will read the second line only after sending the first line to the output, so that the second line does not enter the pipeline until the first one has exited. Do I understand correctly how this program will flow? If this is how it works, is there any easy way to make it so that multiple lines can be in the pipeline at once, so that the program is reading, writing, and processing each step in parallel?
回答1:
You can't really parallelize reading from or writing to files; these will be your bottleneck, ultimately. Are you sure your bottleneck here is CPU, and not I/O?
Since your processing contains no dependencies (according to you), it's trivially simple to use Python's multiprocessing.Pool class.
There are a couple ways to write this, but the easier w.r.t. debugging is to find independent critical paths (slowest part of the code), which we will make run parallel. Let's presume it's process_item.
…And that's it, actually. Code:
import multiprocessing.Pool
p = multiprocessing.Pool() # use all available CPUs
input = open("input.txt")
x = (process_line(line) for line in input)
y = p.imap(process_item, x)
z = (generate_output_line(item) + "\n" for item in y)
output = open("output.txt", "w")
output.writelines(z)
I haven't tested it, but this is the basic idea. Pool's imap method makes sure results are returned in the right order.
来源：https://stackoverflow.com/questions/5684992/how-can-i-parallelize-a-pipeline-of-generators-iterators-in-python