David Hutto, 21.12.2010 16:11:
On Tue, Dec 21, 2010 at 10:03 AM, Stefan Behnel wrote:
I meant
uncompressing the data *while* parsing it. Just like you have to decode it
for parsing, it's just an additional step to decompress it before decoding.
Depending on the performance relation between I/O speed and decompression
speed, it can be faster to load the compressed data and decompress it into
the parser on the fly. lxml.etree (or rather libxml2) internally does that
for you, for example, if it detects compressed input when parsing from a
file.
Note that these performance differences are tricky to prove in benchmarks,
Tricky and proven, then tell me what real time, and this is in
reference to a recent c++ discussion, is python used in ,andhow could
it be utilized in....say an aviation system to avoid a collision when
milliseconds are on the line?
I doubt that there are many aviation systems that send around gigabytes of
compressed XML data milliseconds before a collision.
I even doubt that air plane collision detection is time critical anywhere
in the milliseconds range. After all, there's a pilot who has to react to
the collision warning, and he or she will certainly need more than a couple
of milliseconds to react, not to mention the time that it takes for the air
plane to adapt its flight direction. If you plan the system in a way that
makes milliseconds count, you can just as well replace it by a
jack-in-the-box. Oh, and that might even speed up the reaction of the pilot. ;)
So, no, if these systems ever come close to a somewhat recent state of
technology, I wouldn't mind if they were written in Python. The CPython
runtime is pretty predictable in its performance characteristics, after all.
Stefan
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