I'm assuming you chose science for the basis of this analysis because scientists would be more likely to provide thoughtful replies, if any reply at all correct

I'm assuming you chose science for the basis of this analysis because scientists would be more likely to provide thoughtful replies, if any reply at all correct? I did like the analysis, but once the proselytizing kept popping up, it started to lose value and actually stoke some some of the existing tensions on this matter (we should stop teaching Python 2??) So now we have to come down from the clouds into reality. For one, having limited yourself to scientific fields (sort of) you have literally chosen the tip of the iceberg. Let's ignore the fact that the stats clearly show abysmal adoption of Python 3 among those who make a living by being on the cutting edge and can most afford to adopt. But 786 replies?? And we should stop Python 2 for THAT (even though ~700 in that set aren't using it)??? If you venture into the commercial world, this entire analysis becomes irrelevant. My field of finance and derivative trading is one of the big up and comers in the Python space for a number of reasons but likely to costs - rapid prototyping, powerful testing, ease of training, etc. And I can say with a fair degree of confidence that there are more Python developers at my firm than this entire set - and all of them use Python 2.6. Or at least they did until a multi year upgrade migration finally brought us to Python 2.7 just this year ( and cost millions to achieve). Most are still using 32 bit, develop in Windows (on in house built IDEs) and have some split of deployment between Window client side projects (GUIs) and Linux server deployment. This is not to say we are simpletons - we have vast and complex systems, globally distributed compute grids with tens of thousands of cores (and equivalent disaster recovery clusters), reactive caching graphs, time shifting time series, cutting edge data stores manipulating massive data sets in the tens of billions of rows and basically run huge swaths of the HUNDREDS OF TRILLIONS in notional derivatives that drive the entire global economy. These systems have BILLION dollar budgets. And mine is one firm out of thousands employing tens (if not hundreds) of thousands of well compensated software developers. If my point isn't abundantly clear by now, then to put it frankly: WE (and many other industries like ours) ARE the Python community. And it shifts all your stats to the point where Python 3 isn't even statistically significant. So perhaps it would be wise to work with the elephant in the room instead of trying to pull the rug out from under him. Because elephants are big and don't like that shit. Moreover, as a multitude of examples can attest to, any features left out of Python 2.X ultimately just get developed in house and become closed source, with a huge inefficiency in developing the wheel again and again but also locking up the critical knowledge on the best way to do it, backed by proven production deployments with big money at stake. I don't want to disway this sort of analytical review, but if it's going to be science, it should bear at least some resemblance to it.