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This sounds like a good idea - nice work! I don’t feel that I am capable of really assessing all pros and cons for developers, but I’d still like to say this: speed is essential and everything that helps to ensure that feature creep doesn’t slow Koha down over
time is welcome.
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<div>I’m going out on a limb here, but would it also be relevant to (at some distant point in the future) hook this up with the ideas about Koha being able to ”call home” if you allow it in order to keep track of how many installations there are worldwide?
I’d like to see larger data sets in order to follow the general trend and it might help in identifying hardware or OS-distros having atypical problems with a specific patch. </div>
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<div>Regards/Viktor </div>
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<b style="font-size: 11pt; "><span style="font-size: 10pt; font-family: Arial, sans-serif; ">Viktor</span></b><span style="font-size: 10pt; font-family: Arial, sans-serif; "> <b>Sarge</b></span></div>
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<span style="font-size: 10pt; font-family: Arial, sans-serif; ">Regionbibliotek Halland<br>
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<b><span style="font-size: 10pt; font-family: Arial, sans-serif; ">TFN: </span></b><span style="font-size: 10pt; font-family: Arial, sans-serif; ">035-17 98 73<b><br>
E-POST: </b><a href="mailto:Viktor.Sarge@regionhalland.se" style="color: purple; ">Viktor.Sarge@regionhalland.se</a><b><br>
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<div>18 mar 2014 kl. 11:34 skrev Magnus Enger <<a href="mailto:magnus@enger.priv.no">magnus@enger.priv.no</a>>:</div>
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<blockquote type="cite">Dear Community,<br>
<br>
I spent the last day of the hackfest in Marseille hacking together a<br>
"proof of concept" script for checking changes in the performance of<br>
Koha over time:<br>
<br>
<a href="https://github.com/digibib/kohaprofile">https://github.com/digibib/kohaprofile</a><br>
<br>
The idea is to step x commits back in time, run a bunch of timed<br>
tests/benchmarks on Koha, take one step forwards in time, run the<br>
tests again etc. Hopefully this might be able to show us what the<br>
general trends are, and if there are any changes that lead to<br>
noticeable increases in response times.<br>
<br>
If you run the same benchmark a few times in a row, the response times<br>
vary quite a bit. Perhaps there is too much "noise" for this to be<br>
really useful. (To mitigate this, the script can run the tests y<br>
number of times and record the average time. Perhaps there are better<br>
ways to deal with the statistics of this, like removing the fastest<br>
and the slowest time etc.)<br>
<br>
This is a "proof of concept", so I would be really interested in<br>
hearing your thoughts on it. If the concensus is that it does not<br>
yield interesting data, I'll abandon the project. If people think it<br>
has some merit I would be more than happy to accept pull requests for<br>
improving it. :-)<br>
<br>
See the README for some ideas for improvements.<br>
<br>
Does anyone know if there are tools that can do what I'm trying to<br>
accomplish here (specifically the idea of stepping through Git history<br>
to check performance) already?<br>
<br>
Best regards,<br>
Magnus<br>
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bugs : http://bugs.koha-community.org/<br>
</blockquote>
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