Kent Johnson wrote: >Orri Ganel wrote: > > >>Hello all, >> >>I've been working on a program for a week or two now that will convert >>all the wav files in a folder to mp3s, filling the id3 tags with the >>correct information as collected from gracenote.com. This part works >>fine. However, the actual conversion to mp3 takes between 30 and 50 >>seconds per song, so it's usually about 10 minutes per album. With this >>in mind, I thought, why not try to use threads so all the conversions >>happen simultaneously? That way, the whole album will take between 30 >>and 50 seconds. Unfortunately, I can't seem to get a working threaded >>version that significantly reduces the time involved . . . The >> >> > >The only part you are doing in a thread is the actual conversion. This is >likely to be CPU-intensive so running it in multiple threads may not help - >you still have only the one CPU to run on. To the extent that you can overlap >disk I/O in one conversion with processing in another you may get a win; on >the other hand you could just as well have contention for the disk as you try >to read and write a bunch of files at the same time. > >The fetch from gracenote.com seems like a better candidate for threading >because there is some latency...but the total time is still probably small >compared to the conversion time. > >Maybe if you have multiple CPUs you can get a speedup by using as many threads >as CPUs...I'm not sure how os.system() behaves in this case. You may have to >explicitly fork to get a new process. > >Hmm...come to think of it, os.system() may block other threads, I don't >know...you could try subprocess.Popen() instead. > >Kent > Thanks for the tip. Unfortunately, I only have 1 CPU and not the slightest idea how to code for multiple CPUs in any case. Looks like I'll just hafta deal with a 10-minute time per album.
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