Nothing about python versioning is easy. It’s a disaster and the key reason I do not start any projects in python.
And it is quite clear that that choice was not based on accurate estimates and insights.
The original e.o.l. was laughably short and then had to be doubled. It was quite clear they based their choice on the assumption that consumers would have all switched to e at a time when 2 was still used by 80%.
They made that choice based on what can only be seen as complete ignorance of the cost of rewriting software.
Right now, the biggest reason to drop Python 2 for most serious consumers is not any of the improvements that Python 3 brings, but that it is e.o.l..
I want to understand what was so hard about porting code from Python 2 to 3. I ported a few tens of thousand lines of Python 2 code to Python 3 and it was pretty trivial. In my experience the only thing that made porting code hard was when a package you depended on was not ported to Python 3 yet. But maybe my experience does not reflect some other cases. Can you eloborate on what was so hard about porting code from Python 2 to 3?
Python code is inherently almost-untestable and fragile. These days, when coding something critical and non-trivial, I choose a memory-safe language with static typing and type inference, ADTs, pattern matching and try to write simple yet pure functional code with well defined semantics, that works almost by definition.
Well yes, sure, of course.
And like you said, maybe Python isn't the right language in the first place for mission-critical life-is-on-the-line software.
But if you have already gotten yourself into a position where some piece of your business infrastructure is dependent on an obscure bit of hard-to-port-to-Python-3-and-maintain-exact-behaviour Python code, then it is exactly the "2to3 transition that's shaking up your house of cards", no?
And, furthermore, like you said, if you find yourself in this position, you should be looking at some other language entirely rather than porting to Py3, eh?
I was referring to untestable code with a myriad of edge-cases, in which case you have a problem that will surface sooner or later, be it 2to3 transition or something else.
If the code is truly static, you can ignore the transition and deprecation. Otherwise you should probably work on documentation/testing/refactoring and/or porting to another language.
2to3 transition was handled badly, up to about 2.7 and 3.4 or so, but the pains described here seem mostly self-inflicted, and I don't see it as an argument against the needed changes.
I have Python code dating back to when I was an undergrad. It's sad to see the Python team decide to nuke that. My C code from then (mostly) runs fine still.
The team decided to externalize a massive cost on its community without much benefit. That was sad to see at the time, and it continue to be sad to see.
They targeted business; it came to be adopted by business; and then they were surprised that business was not enthusiastic about updating currently working code with all the potential regressions and downtime that might come from it.
As I recall, Python was designed for the Amoeba operating system, and drew on experience from implementing ABC; ABC was definitely designed for education.
But ABC != Python. Checking now, the first Usenet post for Python 0.9 says:
> Python can be used instead of shell, Awk or Perl scripts, to write prototypes of real applications, or as an extension language of large systems, you name it.
See https://groups.google.com/g/comp.sys.sgi/c/7r8kVgQ84j0 .
It doesn't specifically mention using Python for education.
https://news.ycombinator.com/item?id=25890126
How do I regression test five different pieces of DAQ hardware? My best plan is to pull them working systems and deal with them missing. I don’t think it’s a good use of resources to buy extra DAQ cards just for a regression test bed.
Regardless of that, moving from python 2.5 to 2.7 is not trivial because not all used libraries were even updated to 2.7 from 2.5. Some that were broke backwards compatibility. How far do I have to bend backward just to get in the right place to update to python 3? I see many comments trivializing the effort needed to update to python 3 because they know of narrow use cases and expect large amounts of resources to maintain code. That isn’t the reality for most users.