Python 2 isn't going anywhere anytime soon. Tools and libraries which drop support for Python 2 will suffer and will either revert their decision or be replaced with something else.
Joking aside, Python 3 is the only Python. The only people who should use Python 2 are those supporting legacy codebases, and even they should start migrating.
This is fine as far as wishful thinking goes, but simply doesn't correspond to reality. Over the past 15 years or so I have been working with and consulting large corporations using Python, all over the world. And I can tell you for a fact: Python 3 is simply not an option in most cases. I HAVE worked on transitioning several large codebases from 2 to 3 and in each case this has been months of work, incurring completely unjustified costs. The benefits have been practically negligible. I would never advise a client with an existing codebase to move on to Python 3, unless there were damn good reasons for it.
For new, smaller projects, that don't have too many external dependencies - Python 3 is fine. Again, even in these cases, the benefits are largely superficial.
Making new release of Open-Source & free library python 3 only does not prevent your clients to still use the old versions. Those will never become incompatible. If the want longer support they then can consider giving some money to the Open-Source project they use. The switching at this point for many of the libraries/project that make these decision is almost 0 cost, and number of benefits. Especially when these libraries are maintained by Night and Week-end contributors. I think many contributors to these library would love to be hired to work on it, and many of these library would love8 to get funding to hire their contributor. I'm actually seating to 2 of these people that were hired by such kind of funds, and are now looking for more funding to hire more dev.
Saying new versions will not be Python 2 compatible is not a request for Companies to upgrades. It's just a statement that they will be stuck on old version of libraries, unless they buy* support for a vendor.
We (the IPython team) have no objection if Continuum or Enthought provide a Paying version of IPython 6.x that is Python 2 compatible, but that's their problem. It does not prevent either the core developer of the Python-3 only project to consult on potential Python 2 internal fork.
I honestly think that this would be a much sane model that would make both sides of the Py2vsPy3 battle happy.
> I HAVE worked on transitioning several large codebases from 2 to 3 and in each case this has been months of work, incurring completely unjustified costs
Out of interest whats the biggest time sink while doing this? I've had a lot of luck using 2to3 and with decent test coverage and a UAT environment that people can access, its not exactly months and months of work changing "xrange" to "range", and "print" to "print()"
The unicode/bytes change it the most time consuming in my experience. Second comes the fact that you can't sort arbitrary types anymore and that None is no longer smaller than any other value.
In order to ease porting, I've created a modified Python 3.6 interpreter that generates warnings in a lot of the cases that real Python 3 would generate an exception. See https://github.com/nascheme/ppython .
The goal is to have a 2to3 script that generates something that will run, with warnings, under me modified Python. Once you fix all the warnings, your code should run correctly in Python 3.
> Second comes the fact that you can't sort arbitrary types anymore
Surely that's a bug in the system that you've just uncovered and fixed? Py2 used to use the memory address of the object when comparing by default, which is just... crazy, especially for a language with so few WTFs:
> In order to ease porting, I've created a modified Python 3.6 interpreter
That looks amazing! We're going to end up porting a fairly large + critical Django app to py3 and I definitely think this could ease some of the pain. I'm going to give it a go when I get the chance.
> Py2 used to use the memory address of the object when comparing by default, which is just... crazy,
Its true that that's crazy, but, OTOH, everything-can-be-sorted is a useful feature (which Erlang has, for instance). Py3 could conceptually have retained it with a different implementation (this would probably still have been a breaking change from Py2, but not a feature loss.)
True, I didn't consider the cost of updating packages (and any associated API changes). But in my experience there are very few packages that simply don't support Python 3, and the ones that don't are just dead.
Absolutely. If you live in a world of ascii, then maybe python 2 is adequate. But I always deal with unicode, and python 3 is a big benefit just for that.
Python 2.x support ends in 4 years. It seems irresponsible to not be planning for a move now. Large firms do take longer but that's why now is a good time to begin.
The cost is justified if you want to use a supported language.
I can't think of a way that this makes any difference, or see any reason why anyone should be bothered by python 2 support "ending". I don't even understand what this means, I mean it sounds like a scare tactic without substance. At the end of the day, if the PSF won't support it, I will (and I'll happily take the money for it).
Big companies aren't going to gamble their future without support. And they probably don't want to deal with a single guy they find on the Internet for security/bug fixes in a forked version of Python.
Obviously when I say "I will support it", I don't mean myself, single-handedly. I mean my company. Or someone else's company. The point is, commercially speaking, nobody cares about official PSF support. The world will go on unaffected, with or without it.
A few weeks back I surveyed my 3,500 members at PyDataLondon (London-based Python data scientists) about their Python version usage. At work 60% use Python 2.7, 33% use Python 3.4+. At home 44% use Python 2.7, 49% use Python 3.4+. I'm predicting 50% at-work usage of Python 3.4+ this time next year for my London community:
http://ianozsvald.com/2016/06/20/results-for-which-version-o...
Note - I'm the co-chair for PyDataLondon (and the local conference series). I regularly poll my monthly meetup audience to see how many folk upgrade each month. Normally 1-10 per month stick their hand up, nobody sticks their hand up if I ask "how many downgraded from Python 3 this month?".
Many people use Python 2 for the sole reason it's the default system Python. I assume a lot of them will instantaneously move to Python 3 the moment typing "python" on the command line will invoke the Python 3 REPL.
All my python 2 only code explicitly invokes python 2 on the shebang line.
Though, more likely they'll find that typing "python" returns "command not found", and in that case they might find it easier to just type apt-get/dnf install python.
I don't do this kind of work (agency) but I find it strange that ongoing maintenance isn't discussed and priced into the statement of work right from the beginning.
Something like 2 days maintenance every 9 months to stay current, or 4 days every 2-3 years to go from LTS to LTS. If a customer doesn't understand why they need to be paying maintenance every x months or years, isn't that your fault for not making that clear in the beginning? Sorry if it seems like I'm picking on you, but I've seen this kind of comment quite a lot, and I've never asked the question before.
I actually agree and I should factor that in more.
However for many reasons it's often tricky:
1. This is something you have to address in the initial stages of a client relationship and with price-sensitive clients unused to software development if you're not careful it can sound like you're just rent-seeking.
2. 'Big but infrequent' changes are difficult to cost. Django LTS upgrades are every 5 years. Breaking changes like Python 2 to 3 are even rarer. What figure would I have proposed during the sales process that would have correctly covered me for these? I'm almost certain I would have significantly underestimated.
3. It's not always clear if you're entering into a long-term relationship with the client. They might expect the website to be completely replaced in a year or so, they might be intending to bring development in-house or various other things that make 'saving for a rainy day' a tricky proposition.
> 3. It's not always clear if you're entering into a long-term relationship with the client.
I've also found that clients will often be acquired, go through management changes, etc that make having these things built in become unstable. One of my clients was acquired by Merck, then Merck sent a letter saying they were terminating all contracts. 18 months later, I get a frantic e-mail from some low-level people asking why I was no longer updating things for them.
The median life of many companies makes building in release->release upgrade support difficult in practice.
I personally charge my clients with a flat monthly maintenance fee which includes upgrades, but also minor bug fixes. In some ways it's a guarantee that the website will keep running, though without an actual SLA. It means I don't need to spend time selling the client on the upgrade.
1. Yes. I always put the on-going fee in the initial project estimate, so there's no surprises.
2. Yes, it requires some guess-work. I've also found that it saves time to take one feature migration (like removing django's url patterns() function) and making that change to all projects at the same time (rather than making all the upgrades to one project at once). I also have found it helpful to reduce the number of 3rd party dependencies. (Fewer things to upgrade, and fewer things that may potentially stop getting supported.)
(Also "Django LTS upgrades are every 5 years" - I was going to correct that to 2 years, but I suppose you can completely skip an LTS line if you time it just right (like, jump from 1.8 directly to 2.0). But you still need to upgrade every _4_ years. Right?)
I'm coming from the Java world, but as a consultant for enterprise customers, I'll say that they only understand two kinds of ongoing maintenance:
1. Dollars over time (e.g. licenses)
2. Purpose-specific hire (i.e. hire a guy to do nothing but support this new thing between now and forever)
In other words, they understand continuous maintenance, but not continual maintenance. Anything else is either too awkward to write on a budget. If you suggest that it needs periodic review, they'll think you just need to "do it right the first time, so this isn't an issue going forward", whether or not that makes any sense.
How about car oil changes for an analogy? You could probably drive for several oil change periods without apparent issues, until eventually there would be big issues. Django upgrades are similar, not "that" difficult, and it's a good idea not to fall too far back in versions, running into more and more incompatibilities.
Py 2 -> 3 is a bigger one, so maybe like a timing belt change? ;-)
Joking aside, Python 3 is the only Python. The only people who should use Python 2 are those supporting legacy codebases, and even they should start migrating.