Hi - We've been using IronPython successfully to allow extensibility of our application.
Overall we are happy with the performance, with the exception of BeautifulSoup which seems to run very slowly: x5 or more time to execute compared to CPython. Most of the time seems to be spent during __init__() of BS, where the markup is parsed. We suspect this has to do with the fact that our CPython env is executing .pyc files and can precompile its libs, while the IronPython environment compiles each iteration. We couldn't find a way to pre-compile the libs and then introduce them into the code, but in any case this will result in a large management overhead since the amount of CPython libs we expose to our users contains 100's of modules. Any ideas on how to optimize? Thanks, -Birsch Note: we're using FePy/IPCE libs with regular IP v1.1.1 runtime DLLs (this was done to overcome library incompatibilities and network errors). However, the relevant slow .py code (mainly SGMLParser and BeautifulSoup) is the same.
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