[Michael]
Here are my thoughts, just as untutored as yours. I'm working primarily from hursley's spec here...
For the alpha, I've left all of the traps off except for ConversionSyntax. The reasoning that the numeric model is otherwise self-contained. Dividing by zero usefully gives Infinity. NaNs result from non-sensical operations. NaNs can even have diagnositic information associated with them. Let's let people experience what the standard has to offer. By way of comparison, look at MS Excel. Rather than bomb-out, it has values such as N/A and #DIV/0 which are all part of the model and flow through calculations if necessary. Though decimals play nice with many other Python tools, we shouldn't hide that the model is different and that many of those differences are for the better: - Calculations taking place within a user settable context - Special values such as NaNs and Infinities - Negative zero - Signals can be ignored, inspected (flag), or raised (trapped) - Notion of significance: 1.25 + 1.75 --> 3.00 with two trailing zeroes Raymond