[Python-Dev] Caching float(0.0) (original) (raw)

Terry Reedy tjreedy at udel.edu
Tue Oct 3 02:05:28 CEST 2006

"Kristján V. Jónsson" <kristjan at ccpgames.com> wrote in message news:129CEF95A523704B9D46959C922A280002FE99A9 at nemesis.central.ccp.cc...

Anyway, Skip noted that 50% of all floats are whole numbers between -10 and 10 inclusive,

Please, no. He said something like this about non-floating-point applications (evidence unspecified, that I remember). But such applications, by definition, usually don't have enough floats for caching (or conversion time) to matter too much.

For true floating point measurements (of temperature, for instance), 'integral' measurements (which are an artifact of the scale used (degrees F versus C versus K)) should generally be no more common than other realized measurements.

Thirty years ago, a major stat package written in Fortran (BMDP) required that all data be stored as (Fortran 4-byte) floats for analysis. So a column of yes/no or male/female data would be stored as 0.0/1.0 or perhaps 1.0/2.0. That skewed the distribution of floats. But Python and, I hope, Python apps, are more modern than that.

and this is the code that I employ in our python build today:

[snip]

For the analysis of typical floating point data, this is all pointless and a complete waste of time. After a billion comversions or so, I expect the extra time might add up to something noticeable.

From: "Martin v. Löwis" [mailto:martin at v.loewis.de]

I'm worried about the penalty that this causes in terms of run-time cost.

Me too.

Also, how do you chose what values to cache?

At one time (don't know about today), it was mandatory in some Fortran circles to name the small float constants used in a particular program with the equivalent of C #defines. In Python, zero = 0.0, half = 0.5, one = 1.0, twopi = 6.29..., eee = 2.7..., phi = .617..., etc. (Note that naming is not restricted to integral or otherwise 'nice' values.)

The purpose then was to allow easy conversion from float to double to extended double. And in some cases, it also made the code clearer. With Python, the same procedure would guarantee only one copy (caching) of the same floats for constructed data structures.

Float caching strikes me a a good subject for cookbook recipies, but not, without real data and a willingness to slightly screw some users, for the default core code.

Terry Jan Reedy

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