New IPython release drops Python 2.7 support
A comment from a beginner python user -- but I need to rant ...<p>I&#x27;ve been doing a bit of python the last few weeks for some image processing&#x2F;computer vision tasks (using opencv and numpy).<p>I have to say, all together it&#x27;s a pretty miserable developer experience.<p>Python is incredibly slow - forcing pretty much all computation no matter how trivial into contortions via numpy incantations so that the inner loops can run in native extensions -- these Incantations have a lot of implicit not well documented magic.  Miss some details in the behavior of the magic and suddenly you have a major 10x slowdown -- but good luck finding where.  I would kill for an easy to use tool like xcodes Time Profiler ...<p>API usage errors (even those where invariants are checked at runtime) are ridiculously under informative -- opencv for example does quite a bit of runtime sanity checking on the shape and type of arguments to its methods -- but somehow even simple details as to which parameter is the cause of the error don&#x27;t get reported in the stack trace severely increasing the cognitive load required to identify the mismatch -- not fun when multiple arguments to an API are the result of a chain of numpy magic data munging.  This may be an opencv complaint more than python (aside: opencv is pretty terrible.)<p>I&#x27;m not sure what I&#x27;m doing wrong with python but I find the majority of my code to be sort of menial data munging -- and I haven&#x27;t figured out good patterns to organize this munging in any sensical way --with a static language d.r.y patterns to centralize such plumbing operations have the awesome effect of moving invariants into reasonable places -- in python without any ability to organjze guarantees, as the code base evolves I find myself needing to repeatedly check data shapes&#x2F;types -- there doesn&#x27;t seem to be an obviously useful way to organize verification of data types as the necessary invariants become apparent.  These issues are compounded by the fact that refactoring is an enormous pain in the ass!<p>I feel like all my python code is throwaway code.  Maybe that&#x27;s what I&#x27;m missing -- I need to just accept that all the python numeric code I write is pure one-off junk, embrace copy paste and never try to reuse any of it ...<p>Sorry for the rant!  I remember loving dynamic languages when I first discovered them - but right now, I really miss c++ (or even better swift).<p>I can&#x27;t imagine the number of hours wasted because of these overly dynamic tools -- and there is simply no decreasing that lost time in the future -- as these languages grow if the house of cards ecosystems they sit atop grow and motivates more use then ever more developer hours will be lost to avoidable triviality ...