harijay wrote:
I want to quickly bzip2 compress several hundred gigabytes of data
using my 8 core , 16 GB ram workstation.
Currently I am using a simple python script to compress a whole
directory tree using bzip2 and a system call coupled to an os.walk
call.
I see that the bzip2 only uses a single cpu while the other cpus
remain relatively idle.
I am a newbie in queue and threaded processes . But I am wondering how
I can implement this such that I can have four bzip2 running threads
(actually I guess os.system threads ), each using probably their own
cpu , that deplete files from a queue as they bzip them.
Thanks for your suggestions in advance
[snip]
Try this:
import os
import sys
from threading import Thread, Lock
from Queue import Queue
def report(message):
mutex.acquire()
print message
sys.stdout.flush()
mutex.release()
class Compressor(Thread):
def __init__(self, in_queue, out_queue):
Thread.__init__(self)
self.in_queue = in_queue
self.out_queue = out_queue
def run(self):
while True:
path = self.in_queue.get()
sys.stdout.flush()
if path is None:
break
report("Compressing %s" % path)
os.system("bzip2 %s" % path)
report("Done %s" % path)
self.out_queue.put(path)
in_queue = Queue()
out_queue = Queue()
mutex = Lock()
THREAD_COUNT = 4
worker_list = []
for i in range(THREAD_COUNT):
worker = Compressor(in_queue, out_queue)
worker.start()
worker_list.append(worker)
for roots, dirlist, filelist in os.walk(os.curdir):
for file in [os.path.join(roots, filegot) for filegot in filelist]:
if "bz2" not in file:
in_queue.put(file)
for i in range(THREAD_COUNT):
in_queue.put(None)
for worker in worker_list:
worker.join()
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