Comments (4)
@damamaty That seems okay to me. Does "cpl mins" mean "couple of minutes"? Anyway, I don't quite see this as a serious problem.
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Yes, sorry, "couple minutes". It can take longer depending on the list size.
Reported it because it was a reason of bad performance in our case. Can be avoided by e.g. using wrappers around list/dict with redefined repr, but from my point of view it is unexpected that the library does that.
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@damamaty Huh? What does __repr__
have to do with it? Should I know what you expected to happen? As it turns out, I don't.
Why would anyone create a list with a billion elements and then expose that in a sandboxed interpreter?
Performance is just not a high priority here, but you may recall that there is this thing called numpy
.
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Closing this, I cannot reproduce. FWIW
>>> x = [1]*1_000_000_000 # takes a couple of seconds for me
>>> import asteval
>>> aeval1 = asteval.Interpreter({'x': x}) # much less than 1 sec
>>> aeval2 = asteval.Interpreter() # much less than 1 sec
>>> aeval2.symtable['x'] = x # much less than 1 sec
>>> aeval2('len(x)') # much less than 1 sec
1000000000
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from asteval.