This issue tracker has been migrated to GitHub, and is currently read-only.
For more information, see the GitHub FAQs in the Python's Developer Guide.

Author vstinner
Recipients mark.dickinson, martin.panter, ned.deily, rhettinger, steven.daprano, tim.peters, vstinner
Date 2016-08-17.08:31:24
SpamBayes Score -1.0
Marked as misclassified Yes
Message-id <>
"Just for fun, here's a recipe for a correctly-rounded nth root operation for positive finite floats. I'm not suggesting using this in the business logic: it's likely way too slow (especially for large n), but it may have a use in the tests."

I don't know well the statistics module, but it looks like it doesn't use directly floats, more a somehow higher level type of numbers to try to reduce rounding errors. For me, the math module is a thin wrapper on C library math functions, except of a few functions specific to Python like math.factorial. But the statistics module is at a higher level. Maybe we should draw a line between accuracy and speed. For example, explain in the statistics module that the module is designed for accuracy?

Sorry if I completly misunderstood the design of the statistics module :-)
Date User Action Args
2016-08-17 08:31:24vstinnersetrecipients: + vstinner, tim.peters, rhettinger, mark.dickinson, ned.deily, steven.daprano, martin.panter
2016-08-17 08:31:24vstinnersetmessageid: <>
2016-08-17 08:31:24vstinnerlinkissue27761 messages
2016-08-17 08:31:24vstinnercreate