I have been profiling my code lately trying to improve performance, especially at startup. I am not too experienced with the ins and outs of pyglet and image data in general, but after profiling it seems a big chunk of time is spent on loading my large atlas files. They range anywhere from 1024-2048 width or height.
In my profiling it took 0.818 seconds on a Core i5 processor to load 5 of them. I can only image how long it takes on a slower machine. After digging deeper it seems a majority of the time is spent in pyglet.image._convert, specifically the re.findall portion (over 90% of the time is spent on that). Since I doubt we can improve the speed of a default library, I looked at the comment where the findall is found and it says: "Pitch is wider than pixel data, need to go row-by-row." which forces it to do a findall. Is this because of my image format (PNG) or size? Would a different format produce better results or a way around needing for it to findall? Any input is appreciated, thanks. -- You received this message because you are subscribed to the Google Groups "pyglet-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/pyglet-users. For more options, visit https://groups.google.com/d/optout.
