Thanks robert for the praise. It feels nice.
I may be bold, but I really hate to come empty handed to a discussion. So this lib is nothing more than doing my homework when I don't have a PhD.
Actually, science (in my opinion) is about measuring. What I propose is nothing more than (if you add Vector traits) giving native metrics to objects (having coded in Perl for too long I still see objects as a hierarchy of blessed MutableMappings, I am sorry). And I think that measurements are a corner stone of science, thus of data science. (my opinion you may not share).
As an everyday coder, this behaviour does solve problems I can illustrate with code (like aggregating data, or measuring if I might have doubon in a set of dataset, transforming objects into objects).
I do not want to force feed the community with my "brilliant" ideas, I much more would like to plead my case on how adopting "consistent geometric behaviours" at the language level would ease our lives as coders, if this is not inappropriate.
Please don't look at the lib. Look at the idea of making operators
behave in a consistent way that gives the property of well known
mathematic
constructions to the core of the language.
It also enables parallelisation without side effects (aka the map reduce of the poors), which are a first order consequence of the linear algebrae.
I may not be gifted with writing long dissertations, however, I have a pragmatic mind. So I don't mind being challenged a tad, as long as we talk about stuffs like : how does it profit python coders to be standard, can you show me real life example ?
However, if a "no (answer)" is a "no", I do understand. I like python the way it is, and I don't want to introduce friction in the process of improving python by being off topic.
Thus if no one is interested, I still have a last word : keep up the good work! And thank you all for what you bring us.