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It doesn’t matter how many patterns and algorithms you know about – you need to know how to use them to be effective enough to do transitions. There is only one acceptable upgrade scheme any software developer should ever use, regardless of app/lib popularity: That’s it – following this procedure will let you never get into legacy trouble.
One project that adopted this approach in a way is Guzzle.
What I mean by that is: there should be absolutely zero reason to keep implementing the functions you’re adding to the new version retroactively into the old version, just because some people are still using it, even if the people using it are a vast majority.
To clarify: bugfixing legacy versions until their long term support contract runs out or you feel like it if you’re in charge, yes.
It’s far too often that I see people shying away from newest technologies in the spirit of backwards compatibility.
If you’ve done anything on , you know it’s a slightly less dense vortex of antipatterns, but still a vortex of antipatterns and bloat – but what I’m trying to say here is – huge upgrades and total rewrites can happen, if capable people are behind them.
On the other hand, those who “braved the rift” and upgraded to 3 without much hesitation, rewriting crucial modules themselves and adapting the language to their needs instead of the other way around will have a much easier time transitioning to newer versions.
This BC break effectively cut off the lazy and prepared the Python landscape for a new generation of developers.
By taking the “support everything for as long as we can” approach, you’re burying yourself in a bottomless pit and looking at stretching yourself so thin several years down the line when you find yourself having to maintain four different versions, you’ll be banging your head into the wall wondering why you didn’t cut the V1 and V2 users loose when you still could have.
In an attempt to maintain a bigger audience, developers often go out of their way to help users of past versions, for the sole purpose of keeping them around.