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Python 2.7.X to 2.7.Y compatibility

I want to develop and test my project on the up-to-date version of Python 2.7 (say 2.7.18), but I want my project to be still fully usable on earlier versions of 2.7 (say 2.7.7). Setting up many variants of 2.7 locally or/and on CI for testing can be redundant.
So there are the following questions about compatibility of 2.7.X.
Can there be any changes in syntax which make code not working?
Can there be any changes in available standard imports, for example, can some imports from __future__ be unavailable in earlier versions?
Since I have to distribute compiled Python files (.pyc, compiled via py_compile module), I'm also wondering if there can be any changes in Python bytecode which block code execution in earlier versions.
I guess if all the answers are "no", I can develop and test my project only on a single 2.7 version without worries.
I've tried to search it but there is no success. Please share your experience and/or links.
UPD 1: I should have clearly said from the beginning that it's not my desire to use 2.7, it's a requirement from the environment.

At least Python 2.7.9 introduced massive changes to the 'ssl' module, so trying to use code using SSL for 2.7.18 on Python older than 2.7.9 will fail. So a clear "yes" to number 2.
In general compatbility for most projects works the other way round, use the oldest version you need to support and work upwards from old to new, not downwards from newer to older. I do not know of any software project that makes the guarantees in the other direction.
Note that Python 2.7 dropped out of support with 2.7.18, so unless you use a compatible version like PyPy (https://www.pypy.org/) your freshly developed project will run on outdated Python versions from the start.
If you want to provide a shrink wrapped product, maybe have a look at the usual solution for this like pyinstaller (https://www.pyinstaller.org/) or freeze (https://wiki.python.org/moin/Freeze)
The #3 may work, if you study the list of bytecode opcodes which do not change that much over time (https://github.com/python/cpython/commits/2.7/Include/opcode.h) but no idea if the on-disk format changed.

For Python2 to Python3 code conversion, Which version of Python & Django best suited?

Currently I am working in big firm where we need to convert python2 old big Django project into python3 version so I have done lots of research related but still not able to find any perfect answer related to which version of Python and Django best suited for conversion.
Currently I am using Python : 2.7.16 & Django : 1.9.13 in my old version.
Anyone can suggest me best suited version of Python & Django for above old version for python2 to python3 conversion.

I thought I'd add a bit to the strategy advocated by Wim's answer - get the appropriate version of Django working on both 2.7 and 3.x first - and outline some tactics that worked for me.
Python 2.7 is your escape pod, until you pull the trigger on 3.x
your tests should run on both
don't use any 3.x specific features, like f-strings
first Python 3.x, then only later Django 2.x which doesn't run on 2.7
start early, don't over analyze, but avoid the big bang approach
file by file at first.
start with the lowest level code, like utility libraries, that you have test suites for.
if possible, try to gradually merge your changes to the 2.7 production branches and keep your 3.x porting code up to date with prod changes.
Which minor version of Django to start with?
My criteria here is that Django migrations can be fairly involved (and actually require more thinking than 2=>3 work). So I would move to the latest and greatest 1.11 that way you're already providing some value to your 2.7 users. There's probably a good number of pre-2.x compatibility shims on 1.11 and you'll be getting its 2.x deprecation warnings.
Which minor version of Python 3.x to start with?
Best to consider all angles, such as the availability of your 3rd party libs, support from your CI/devops suite and availability on your chosen server OS images. You could always install 3.8 and try a pip install of your requirements.txt by itself, for example.
Leverage git (or whatever scm you use) and virtualenv.
separate requirement.txt files, but...
if you have a file-based, git repo, you can point each venv at the same codeline with a pip install -e <your directory>. that means that, in 2 different terminals you can run 2.7 and 3.x against the same unittest(s).
you could even run 2.7 and 3.x Django servers side-by-side on different ports and point say Firefox and Chrome at them.
commit often (on the porting branch at least) and learn about git bisect.
make use of 2to3
Yes, it will break 2.7 code and Django if you let it. So...
run it in preview mode or against a single file. see what it breaks but also see what it did right.
throttle it to only certain conversions that don't break 2.7 or Django. print x=> print (x) and except(Exception) as e are 2 no-brainers.
This is what my throttled command looked like:
2to3 $tgt -w -f except -f raise -f next -f funcattrs -f print
run it file-by-file until you are really confident.
use sed or awk rather than your editor for bulk conversions.
The advantage is that, as you become more aware of your apps' specifics concerns, you can build a suite of changes that can be run on either 1 file or many files and do most of the work without breaking 2.7 or Django. Apply this after your suitably-throttled 2to3 pass. That leaves you with residual cleanups in your editor and getting your tests to pass.
(optional) start running black on 2.7 code.
black which is a code formatter, uses Python 3 ASTs to run its analysis. It doesn't try to run the code, but it will flag syntax errors that prevent it from getting to the AST stage. You will have to work some pip install global magic to get there though and you have to buy into black's usefulness.
Other people have done it - learn from them.
Listening to #155 Practical steps for moving to Python 3 should give you some ideas of the work. Look at the show links for it. They love to talk up the Instagram(?) move which involved a gradual adjustment of running 2.7 code to 3.x syntax on a common codebase, and on the same git branch, until pull-the-trigger day.
See also The Conservative Python 3 Porting Guide
and Instagram Makes a Smooth Move to Python 3 - The New Stack
Conclusion
Your time to Django 1.11 EOL (April 2020) is rather short, so if you have 2+ dev resources to throw at it, I'd consider doing the following in parallel:
DEV#1: start out on a Django 1.11 bump (the theory being that Django 1.11 is probably best positioned as a jump off point to Django 2.x), using 2.7.
DEV#2: get started on Python 3.6/3.7 of your non-Django utility code. Since the code is 2.7 compatible at this point, merge it into #1 as you go.
See how both tasks proceed, assess what the Django related project risk is and what the Python 3 pain looks like. You're already missing the Python 2.7 EOL, but an obsolete web framework is probably more dangerous than legacy Python 2.7, at least for a few months. So I wouldn't wait too long to start migrating off Django 1.9 and your work doing so won't be wasted. As you see the progress, you'll start seeing the project risks better.
Your initial 2to3 progress will be slow, but the tooling and guidance is good enough that you'll quickly pick up speed so don't overthink it before starting to gather experience. The Django side depends on your exposure to breaking changes in the framework which is why I think it's best to start early.
P.S. (controversial/personal opinion) I didn't use six or other canned 2-to-3 bridge libraries much.
It's not because I don't trust it - it's brilliant for 3rd party libs - but rather that I didn't want to add a complex permanent dependency (and I was too lazy to read its doc). I'd been writing 2.7 code in 3.x compatible syntax for a long time so I didn't really feel the need to use them. Your mileage may vary and don't set out on this path if it seems like a lot of work.
Instead, I created a py223.py (57 LOC incl. comments) with this type of content, most of which is concerned with workarounds for deprecations and name changes in the standard library.
try:
basestring_ = basestring
except (NameError,) as e:
basestring_ = str
try:
cmp_ = cmp
except (NameError,) as e:
# from http://portingguide.readthedocs.io/en/latest/comparisons.html
def cmp_(x, y):
"""
Replacement for built-in function cmp that was removed in Python 3
"""
return (x > y) - (x < y)
Then import from that py223 to work around those specific concerns. Later on I will just ditch the import and move those weird isinstance(x, basestr_) to isinstance(x, str) but I know in advance there is little to worry about.

My suggestion is to first upgrade to Django==1.11.26, which is the most recent version of Django that is supporting both Python 2 and Python 3. Stay on your current version of Python 2.7 for now.
Read carefully the release notes for 1.10.x and 1.11.x, checking for deprecations and fixing anything that stopped working from your 1.9.x code. Things WILL break. Django moves fast. For a large Django project, there may be many code changes required, and if you're using a lot of 3rd-party plugins or libraries you may have to juggle their versions around. Some of your 3rd-party dependencies will probably have been abandoned entirely, so you have to find replacements or remove the features.
To find the release notes for each version upgrade, just google "What's new in Django ". The hits will meticulously document all the deprecations and changes:
https://docs.djangoproject.com/en/2.2/releases/1.10/
https://docs.djangoproject.com/en/2.2/releases/1.11/
Once the webapp appears to be working fine on Django 1.11, with all tests passing (you do have a test suite, right?) then you can do the Python 3 conversion, whilst keeping the Django version the same. Django 1.11 supports up to Python 3.7, so that would be a good version to target. Expect unicode all over the place, since the implicit conversions between bytes and text is gone now and many Python 2 webapps relied upon that.
Once the project appears to be working fine on Django 1.11 and Python 3.7, then you can think about upgrading to Django 3.0, following the same process as before - reading the release notes, making the necessary changes, running the test suite, and checking out the webapp in a dev server manually.

I would upgrade to py3 first. You'll need to look at setup.py in the Django repo on the stable/1.9.x branch (https://github.com/django/django/blob/stable/1.9.x/setup.py) to figure out that the py3 versions supported are 3.4 (dead) and 3.5.
Once you're on py3.5 and Django 1.9 you can upgrade one at a time until you get to the version you want to end at. E.g. Django 1.11 supports py3.5 and py3.7, so
py27/dj19 -> py35/dj19 -> py35/dj1.11 -> py37/dj1.11 ... -> py37/dj2.2
dj2.2 is the first version supporting py3.8, but I would probably stop at py37/dj2.2 if you're working in a normally conservative environment.
If you have other packages you'll need to find version combinations that will work together on each step. Having a plan is key, and upgrading only one component at a time will usually end up saving you time.
The future library (https://python-future.org/) will help you with many icky situations while you need code to run on both py27 and 3.x. six is great too. I would avoid rolling your own compatibility layer (why reinvent the wheel?)
If at all possible, try to get your unit test coverage up to 75-85% before starting, and definitely set up automatic testing on both "from" and "to" versions for each upgrade step. Make sure you read and fix all warnings from Django before upgrading to the next version -- Django cares very little about backward compatibility, so I would normally suggest hitting every minor version on the upgrade path (or at least make sure you read the "backwards incompatibilities" and deprecation lists for each minor version).
Good luck (we're upgrading a 300+Kloc code base from py27/dj1.7 right now, so I feel your pain ;-)

I have same kind of issue with my project and I have tried python 3.7.5 with Django version 2.2.7.
You should not go with python latest version 3.8 or Django latest version 3.0 because you there may have been chances that for any kind of bug you may not able to get proper solution for latest versions.

You should try to shoot for the current versions. Python 3.8 and Django 3.0.The Six library will help with some convention changes. Either way you are going to have to do some refactoring so you might as well make it current.

Upgrade from Python 2.2.1 to 3.4

We have got a legacy application that runs on Python 2.2.1. Now we need to upgrade to the latest version of Python (3.4).
I would like to know a few details on the upgrade:
Would that be a direct upgrade for all of the associated files? I mean what libraries that have been used in the older code have to be changed to make it work in latest version?
How do we upgrade the .py files from the older to the newer version?
Everywhere it talks about upgrading 2.6 to 3 and nowhere does it cover 2.2.1 to 3. Is there any direct upgrade possible?

To expand on my comments, the PyPorting docs suggest a seven-step process that I think would be useful here too:
Only worry about supporting Python 2.7 - it will be easier for you to upgrade to 3 if you first make sure your code runs in the latest 2.x branch. If you're lucky, this won't require many changes!
Make sure you have good test coverage - crucial for any major change. If you can't be sure it's working now, how will you be sure it's working after the upgrade?
Learn the differences between Python 2 & 3 - per cdarke's comment, you will probably have to do some manual intervention, so will need to know what's changed. In your case, this may also involve learning the differences between 2.x versions. You can use What's new in Python x.x? to help.
Use Modernize or Futurize to update your code - automated tools to make your code 3.x-ready (the documentation notes that you can use 2to3 if you don't want to retain 2.x compatibility).
Use Pylint to help make sure you don’t regress on your Python 3 support - pylint will give you lots of helpful warnings to help improve the code generally.
Use caniusepython3 to find out which of your dependencies are blocking your use of Python 3 - you ask about updates to libraries; this tool can tell you what's 3.x compatible. You may need to find compatible replacements for some dependencies; see PyPI.
Use continuous integration to make sure you stay compatible with Python 2 & 3 - whatever versions you want to support, good CI can ensure that you stay compatible with all of them as you modify the code.

I would recommend that you take a look at something like: 2to3
The idea is that you can just run the program on your old file, and convert it to 3.4 compatible code. Best of luck!

Recommendations for Python development on a Mac?

I bought a low-end MacBook about a month ago and am finally getting around to configuring it for Python. I've done most of my Python work in Windows up until now, and am finding the choices for OS X a little daunting. It looks like there are at least five options to use for Python development:
"Stock" Apple Python
MacPython
Fink
MacPorts
roll-your-own-from-source
I'm still primarily developing for 2.5, so the stock Python is fine from a functionality standpoint. What I want to know is: why should I choose one over the other?
Update:
To clarify, I am looking for a discussion of the various options, not links to the documentation. I've marked this as a Community Wiki question, as I don't feel there is a "correct" answer. Thanks to everyone who has already commented for their insight.

One advantage I see in using the "stock" Python that's included with Mac OS X is that it makes deployment to other Macs a piece of cake. I don't know what your deployment scenario is, but for me this is important. My code has to run on any number of Macs at work, and I try to minimize the amount of work it takes to run my code on all of those systems.

I would highly recommend using MacPorts with Porticus for managing your Python installation. It takes a while to build everything, but the advantage is that whatever you build yourself will be built against the same libraries, so you won't have to futz around with statically linked shared objects, etc. if you want your Python stuff to work with Apache, PostgreSQL, etc.
If you choose to go this way, remember to install the python_select port and use it to make your system use the Python installed from MacPorts.
As an added bonus, MacPorts has packages for most main-stream Python eggs, so if you should be able to have MacPorts keep you up-to-date with the latest versions of all that stuff :)

Here's some helpful info to get you started. http://www.python.org/download/mac/

Depends what you are using python for. If you are using MacOS funitionality and things like PyObjC you are probably best of with MacPython or the python provided by Apple.
I use Python on my Mac mostly for development of server side applications which later will run on FreeBSD & Linux boxes. For that I have used fink python for a few years and ever since MacPorts python. With mac ports it is simple to add required c modules (like database driver etc). It's also easy to keep two python Versions (2.5 & 2.6 in my case) around.
I used "compile your own" python to test pre-3.0 python but generally I find managing dependencies to c modules painfull if done by hand.
Thanks to easy_install installing pure python modules is fast and easy for all the options mentioned above.
I was never very much an IDE person. For development I use command line subversion installed by MacPorts, Textmate and occasionaly Expandrive do directly access files on servers. I personally are very dependent on Bicyclerepairman for Textmade to handle my refactoring needs.
Others seem to be very happy with Eclipse & Pydev.

How about EPD from Enthought? Yes, it's large but it is a framework build and includes things like wxPython, vtk, numpy, scipy, and ipython built-in.

I recommend using Python Virtual environments, especially if you use a Timecapsule because Timecapsule will back everything up, except modules you added to Python!

Based on the number of bugs and omissions people have been encountering in Leopard python (just here on SO!), I couldn't recommend that version. e.g., see:
Why do I get wrong results for hmac in Python but not Perl?
Problems on select module on Python 2.5
I would choose MacPorts.
It does not eliminate your existing python supplied by Apple since it installs by default in /opt/local/bin (plays nice with it) and plus it is easy to download and install additional python modules (even binary modules that you need to compile!). I use Porticus GUI to maintain my MacPorts installed list of packages, including python.

In my windows environment I use Eclipse and PyDev, which works quite well together, even if it's a bit sparse. Apparently the exact same environment is available for the Mac as well, so I suggest downloading Eclipse and using the internal update software function to update PyDev with the URL http://pydev.sourceforge.net/updates/. To look further into PyDev, look here.

Apple's supplied python is quite old – my tiger install has 2.3.5. This may not be a problem for you, but you would be missing out on a lot. Also, there is a risk that Apple will update it. I'm not sure if moving from 2.3.5 to (say) 2.4 would cause code to break, but I guess it's possible. This happened to perl people recently: http://developers.slashdot.org/article.pl?sid=09/02/18/1435227
Macpython is a framework build (as is Apple's, I believe). To be honest, I'm not sure exactly what that means, but it's a prerequisite for some modules, in particular wxPython. If you get python from macports or fink, you will not be able to run wxPython (unless you run it through X11).

And guess what was forgotten by every answer here ... ActivePython.
No compilation required, even for third-party modules such as numpy, lxml, pyqt and thousands of others.

I recommend python (any python?) plus the ipython shell. My most recent experience with MacPython was MacPython 2.5, and I found IDLE frustrating to use as an editor. It's not very featureful, and its' very slow to scroll large quantities of output.

SQLite in Python 2.2.3

I've written a web-app in python using SQLite and it runs fine on my server at home (with apache and python 2.5.2). I'm now trying to upload it to my web host and there servers use python 2.2.3 without SQLite.
Anyone know of a way to use SQLite in python 2.2.3 e.g. a module that I can upload and import? I've tried butchering the module from newer versions of python, but they don't seem to be compatible.
Thanks,
Mike

There is no out-of-the-box solution; you either have to backport the SQLlite module from Python 2.5 to Python 2.2 or ask your web hoster to upgrade to the latest Python version.
Python 2.2 is really ancient! At least for security reasons, they should upgrade (no more security fixes for 2.2 since May 30, 2003!).
Note that you can install several versions of Python in parallel. Just make sure you use "/usr/bin/python25" instead of "/usr/bin/python" in your scripts. To make sure all the old stuff is still working, after installing Python 2.5, you just have to fix the two symbolic links "/usr/bin/python" and "/usr/lib/python" which should now point to 2.5. Bend them back to 2.2 and you're good.

Look here: http://oss.itsystementwicklung.de/download/pysqlite/
From the release notes (http://oss.itsystementwicklung.de/trac/pysqlite/browser/doc/install-source.txt)
Python:
Python 2.3 or later
You may not be able to do what you're trying to do.

If you have shell access to your web server, you can probably build you're own version of Python and SQLite. This will let you use the latest version. Download the source code, then when you configure it, do something like "./configure --prefix=$HOME/packages".
Next, fiddle around with your .profile, or .bashrc or whatever it is to make sure $HOME/packages/bin comes first in your path. This will cause your private Python to override the one installed by your web server.
This page might give you a little more information for how to do this on a server like Dreamhost: http://wiki.dreamhost.com/Python

In case anyone comes across this question, the reason why neither pysqlite nor APSW are available for Python 2.2 is because Python 2.3 added the simplified GIL API. Prior to Python 2.3 it required a lot of code to keep track of the GIL. (The GIL is the lock used by Python to ensure correct behaviour while multi-threading.)
Doing a backport to 2.2 would require ripping out all the threading code. Trying to make it also be thread safe under 2.2 would be a nightmare. There was a reason they introduced the simplified GIL API!
I am still astonished at just how popular older Python versions are. APSW for Python 2.3 is still regularly downloaded.