
Porting Python 2 Code to Python 3
*********************************

author:
   Brett Cannon


Abstract
^^^^^^^^

With Python 3 being the future of Python while Python 2 is still in
active use, it is good to have your project available for both major
releases of Python. This guide is meant to help you figure out how
best to support both Python 2 & 3 simultaneously.

If you are looking to port an extension module instead of pure Python
code, please see *Porting Extension Modules to Python 3*.

If you would like to read one core Python developer's take on why
Python 3 came into existence, you can read Nick Coghlan's Python 3 Q &
A.

If you prefer to read a (free) book on porting a project to Python 3,
consider reading Porting to Python 3 by Lennart Regebro which should
cover much of what is discussed in this HOWTO.

For help with porting, you can email the python-porting mailing list
with questions.


The Short Version
=================

* Decide what's the oldest version of Python 2 you want to support
  (if at all)

* Make sure you have a thorough test suite and use continuous
  integration testing to make sure you stay compatible with the
  versions of Python you care about

* If you have dependencies, check their Python 3 status using
  caniusepython3 (command-line tool, web app)

With that done, your options are:

* If you are dropping Python 2 support, use *2to3* to port to Python
  3

* If you are keeping Python 2 support, then start writing Python
  2/3-compatible code starting **TODAY**

  * If you have dependencies that have not been ported, reach out to
    them to port their project while working to make your code
    compatible with Python 3 so you're ready when your dependencies
    are all ported

  * If all your dependencies have been ported (or you have none), go
    ahead and port to Python 3

* If you are creating a new project that wants to have 2/3
  compatibility, code in Python 3 and then backport to Python 2


Before You Begin
================

If your project is on the Cheeseshop/PyPI, make sure it has the proper
trove classifiers to signify what versions of Python it **currently**
supports. At minimum you should specify the major version(s), e.g.
"Programming Language :: Python :: 2" if your project currently only
supports Python 2. It is preferrable that you be as specific as
possible by listing every major/minor version of Python that you
support, e.g. if your project supports Python 2.6 and 2.7, then you
want the classifiers of:

   Programming Language :: Python :: 2
   Programming Language :: Python :: 2.6
   Programming Language :: Python :: 2.7

Once your project supports Python 3 you will want to go back and add
the appropriate classifiers for Python 3 as well. This is important as
setting the "Programming Language :: Python :: 3" classifier will lead
to your project being listed under the Python 3 Packages section of
PyPI.

Make sure you have a robust test suite. You need to make sure
everything continues to work, just like when you support a new
minor/feature release of Python. This means making sure your test
suite is thorough and is ported properly between Python 2 & 3
(consider using coverage to measure that you have effective test
coverage). You will also most likely want to use something like tox to
automate testing between all of your supported versions of Python. You
will also want to **port your tests first** so that you can make sure
that you detect breakage during the transition. Tests also tend to be
simpler than the code they are testing so it gives you an idea of how
easy it can be to port code.

Drop support for older Python versions if possible. Python 2.5
introduced a lot of useful syntax and libraries which have become
idiomatic in Python 3. Python 2.6 introduced future statements which
makes compatibility much easier if you are going from Python 2 to 3.
Python 2.7 continues the trend in the stdlib. Choose the newest
version of Python which you believe can be your minimum support
version and work from there.

Target the newest version of Python 3 that you can. Beyond just the
usual bugfixes, compatibility has continued to improve between Python
2 and 3 as time has passed. E.g. Python 3.3 added back the "u" prefix
for strings, making source-compatible Python code easier to write.


Writing Source-Compatible Python 2/3 Code
=========================================

Over the years the Python community has discovered that the easiest
way to support both Python 2 and 3 in parallel is to write Python code
that works in either version. While this might sound counter-intuitive
at first, it actually is not difficult and typically only requires
following some select (non-idiomatic) practices and using some key
projects to help make bridging between Python 2 and 3 easier.


Projects to Consider
--------------------

The lowest level library for supporting Python 2 & 3 simultaneously is
six. Reading through its documentation will give you an idea of where
exactly the Python language changed between versions 2 & 3 and thus
what you will want the library to help you continue to support.

To help automate porting your code over to using six, you can use
modernize. This project will attempt to rewrite your code to be as
modern as possible while using six to smooth out any differences
between Python 2 & 3.

If you want to write your compatible code to feel more like Python 3
there is the future project. It tries to provide backports of objects
from Python 3 so that you can use them from Python 2-compatible code,
e.g. replacing the "bytes" type from Python 2 with the one from Python
3. It also provides a translation script like modernize (its
translation code is actually partially based on it) to help start
working with a pre-existing code base. It is also unique in that its
translation script will also port Python 3 code backwards as well as
Python 2 code forwards.


Tips & Tricks
-------------

To help with writing source-compatible code using one of the projects
mentioned in Projects to Consider, consider following the below
suggestions. Some of them are handled by the suggested projects, so if
you do use one of them then read their documentation first to see
which suggestions below will taken care of for you.


Support Python 2.7
~~~~~~~~~~~~~~~~~~

As a first step, make sure that your project is compatible with Python
2.7. This is just good to do as Python 2.7 is the last release of
Python 2 and thus will be used for a rather long time. It also allows
for use of the "-3" flag to Python to help discover places in your
code where compatibility might be an issue (the "-3" flag is in Python
2.6 but Python 2.7 adds more warnings).


Try to Support Python 2.6 and Newer Only
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

While not possible for all projects, if you can support Python 2.6 and
newer **only**, your life will be much easier. Various future
statements, stdlib additions, etc. exist only in Python 2.6 and later
which greatly assist in supporting Python 3. But if you project must
keep support for Python 2.5 then it is still possible to
simultaneously support Python 3.

Below are the benefits you gain if you only have to support Python 2.6
and newer. Some of these options are personal choice while others are
**strongly** recommended (the ones that are more for personal choice
are labeled as such).  If you continue to support older versions of
Python then you at least need to watch out for situations that these
solutions fix and handle them appropriately (which is where library
help from e.g. six comes in handy).


"from __future__ import print_function"
"""""""""""""""""""""""""""""""""""""""

It will not only get you used to typing "print()" as a function
instead of a statement, but it will also give you the various benefits
the function has over the Python 2 statement (six provides a function
if you support Python 2.5 or older).


"from __future__ import unicode_literals"
"""""""""""""""""""""""""""""""""""""""""

If you choose to use this future statement then all string literals in
Python 2 will be assumed to be Unicode (as is already the case in
Python 3). If you choose not to use this future statement then you
should mark all of your text strings with a "u" prefix and only
support Python 3.3 or newer. But you are **strongly** advised to do
one or the other (six provides a function in case you don't want to
use the future statement **and** you want to support Python 3.2 or
older).


Bytes/string literals
"""""""""""""""""""""

This is a **very** important one. Prefix Python 2 strings that are
meant to contain bytes with a "b" prefix to very clearly delineate
what is and is not a Python 3 text string (six provides a function to
use for Python 2.5 compatibility).

This point cannot be stressed enough: make sure you know what all of
your string literals in Python 2 are meant to be in Python 3. Any
string literal that should be treated as bytes should have the "b"
prefix. Any string literal that should be Unicode/text in Python 2
should either have the "u" literal (supported, but ignored, in Python
3.3 and later) or you should have "from __future__ import
unicode_literals" at the top of the file. But the key point is you
should know how Python 3 will treat every one one of your string
literals and you should mark them as appropriate.

There are some differences between byte literals in Python 2 and those
in Python 3 thanks to the bytes type just being an alias to "str" in
Python 2. See the Handle Common "Gotchas" section for what to watch
out for.


"from __future__ import absolute_import"
""""""""""""""""""""""""""""""""""""""""

Discussed in more detail below, but you should use this future
statement to prevent yourself from accidentally using implicit
relative imports.


Supporting Python 2.5 and Newer Only
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If you are supporting Python 2.5 and newer there are still some
features of Python that you can utilize.


"from __future__ import absolute_import"
""""""""""""""""""""""""""""""""""""""""

Implicit relative imports (e.g., importing "spam.bacon" from within
"spam.eggs" with the statement "import bacon") do not work in Python
3. This future statement moves away from that and allows the use of
explicit relative imports (e.g., "from . import bacon").

In Python 2.5 you must use the __future__ statement to get to use
explicit relative imports and prevent implicit ones. In Python 2.6
explicit relative imports are available without the statement, but you
still want the __future__ statement to prevent implicit relative
imports. In Python 2.7 the __future__ statement is not needed. In
other words, unless you are only supporting Python 2.7 or a version
earlier than Python 2.5, use this __future__ statement.


Mark all Unicode strings with a "u" prefix
""""""""""""""""""""""""""""""""""""""""""

While Python 2.6 has a "__future__" statement to automatically cause
Python 2 to treat all string literals as Unicode, Python 2.5 does not
have that shortcut. This means you should go through and mark all
string literals with a "u" prefix to turn them explicitly into text
strings where appropriate and only support Python 3.3 or newer.
Otherwise use a project like six which provides a function to pass all
text string literals through.


Capturing the Currently Raised Exception
""""""""""""""""""""""""""""""""""""""""

In Python 2.5 and earlier the syntax to access the current exception
is:

   try:
     raise Exception()
   except Exception, exc:
     # Current exception is 'exc'.
     pass

This syntax changed in Python 3 (and backported to Python 2.6 and
later) to:

   try:
     raise Exception()
   except Exception as exc:
     # Current exception is 'exc'.
     # In Python 3, 'exc' is restricted to the block; in Python 2.6/2.7 it will "leak".
     pass

Because of this syntax change you must change how you capture the
current exception in Python 2.5 and earlier to:

   try:
     raise Exception()
   except Exception:
     import sys
     exc = sys.exc_info()[1]
     # Current exception is 'exc'.
     pass

You can get more information about the raised exception from
"sys.exc_info()" than simply the current exception instance, but you
most likely don't need it.

Note: In Python 3, the traceback is attached to the exception
  instance through the "__traceback__" attribute. If the instance is
  saved in a local variable that persists outside of the "except"
  block, the traceback will create a reference cycle with the current
  frame and its dictionary of local variables.  This will delay
  reclaiming dead resources until the next cyclic *garbage collection*
  pass.In Python 2, this problem only occurs if you save the traceback
  itself (e.g. the third element of the tuple returned by
  "sys.exc_info()") in a variable.


Handle Common "Gotchas"
~~~~~~~~~~~~~~~~~~~~~~~

These are things to watch out for no matter what version of Python 2
you are supporting which are not syntactic considerations.


"from __future__ import division"
"""""""""""""""""""""""""""""""""

While the exact same outcome can be had by using the "-Qnew" argument
to Python, using this future statement lifts the requirement that your
users use the flag to get the expected behavior of division in Python
3 (e.g., "1/2 == 0.5; 1//2 == 0").


Specify when opening a file as binary
"""""""""""""""""""""""""""""""""""""

Unless you have been working on Windows, there is a chance you have
not always bothered to add the "b" mode when opening a binary file
(e.g., "rb" for binary reading).  Under Python 3, binary files and
text files are clearly distinct and mutually incompatible; see the
"io" module for details. Therefore, you **must** make a decision of
whether a file will be used for binary access (allowing to read and/or
write bytes data) or text access (allowing to read and/or write
unicode data).


Text files
""""""""""

Text files created using "open()" under Python 2 return byte strings,
while under Python 3 they return unicode strings.  Depending on your
porting strategy, this can be an issue.

If you want text files to return unicode strings in Python 2, you have
two possibilities:

* Under Python 2.6 and higher, use "io.open()".  Since "io.open()"
  is essentially the same function in both Python 2 and Python 3, it
  will help iron out any issues that might arise.

* If pre-2.6 compatibility is needed, then you should use
  "codecs.open()" instead.  This will make sure that you get back
  unicode strings in Python 2.


Subclass "object"
"""""""""""""""""

New-style classes have been around since Python 2.2. You need to make
sure you are subclassing from "object" to avoid odd edge cases
involving method resolution order, etc. This continues to be totally
valid in Python 3 (although unneeded as all classes implicitly inherit
from "object").


Deal With the Bytes/String Dichotomy
""""""""""""""""""""""""""""""""""""

One of the biggest issues people have when porting code to Python 3 is
handling the bytes/string dichotomy. Because Python 2 allowed the
"str" type to hold textual data, people have over the years been
rather loose in their delineation of what "str" instances held text
compared to bytes. In Python 3 you cannot be so care-free anymore and
need to properly handle the difference. The key to handling this issue
is to make sure that **every** string literal in your Python 2 code is
either syntactically or functionally marked as either bytes or text
data. After this is done you then need to make sure your APIs are
designed to either handle a specific type or made to be properly
polymorphic.


Mark Up Python 2 String Literals
++++++++++++++++++++++++++++++++

First thing you must do is designate every single string literal in
Python 2 as either textual or bytes data. If you are only supporting
Python 2.6 or newer, this can be accomplished by marking bytes
literals with a "b" prefix and then designating textual data with a
"u" prefix or using the "unicode_literals" future statement.

If your project supports versions of Python predating 2.6, then you
should use the six project and its "b()" function to denote bytes
literals. For text literals you can either use six's "u()" function or
use a "u" prefix.


Decide what APIs Will Accept
++++++++++++++++++++++++++++

In Python 2 it was very easy to accidentally create an API that
accepted both bytes and textual data. But in Python 3, thanks to the
more strict handling of disparate types, this loose usage of bytes and
text together tends to fail.

Take the dict "{b'a': 'bytes', u'a': 'text'}" in Python 2.6. It
creates the dict "{u'a': 'text'}" since "b'a' == u'a'". But in Python
3 the equivalent dict creates "{b'a': 'bytes', 'a': 'text'}", i.e., no
lost data. Similar issues can crop up when transitioning Python 2 code
to Python 3.

This means you need to choose what an API is going to accept and
create and consistently stick to that API in both Python 2 and 3.


Bytes / Unicode Comparison
++++++++++++++++++++++++++

In Python 3, mixing bytes and unicode is forbidden in most situations;
it will raise a "TypeError" where Python 2 would have attempted an
implicit coercion between types.  However, there is one case where it
doesn't and it can be very misleading:

   >>> b"" == ""
   False

This is because an equality comparison is required by the language to
always succeed (and return "False" for incompatible types).  However,
this also means that code incorrectly ported to Python 3 can display
buggy behaviour if such comparisons are silently executed.  To detect
such situations, Python 3 has a "-b" flag that will display a warning:

   $ python3 -b
   >>> b"" == ""
   __main__:1: BytesWarning: Comparison between bytes and string
   False

To turn the warning into an exception, use the "-bb" flag instead:

   $ python3 -bb
   >>> b"" == ""
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
   BytesWarning: Comparison between bytes and string


Indexing bytes objects
""""""""""""""""""""""

Another potentially surprising change is the indexing behaviour of
bytes objects in Python 3:

   >>> b"xyz"[0]
   120

Indeed, Python 3 bytes objects (as well as "bytearray" objects) are
sequences of integers.  But code converted from Python 2 will often
assume that indexing a bytestring produces another bytestring, not an
integer.  To reconcile both behaviours, use slicing:

   >>> b"xyz"[0:1]
   b'x'
   >>> n = 1
   >>> b"xyz"[n:n+1]
   b'y'

The only remaining gotcha is that an out-of-bounds slice returns an
empty bytes object instead of raising "IndexError":

>>> b"xyz"[3]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
IndexError: index out of range
>>> b"xyz"[3:4]
b''


"__str__()"/"__unicode__()"
"""""""""""""""""""""""""""

In Python 2, objects can specify both a string and unicode
representation of themselves. In Python 3, though, there is only a
string representation. This becomes an issue as people can
inadvertently do things in their "__str__()" methods which have
unpredictable results (e.g., infinite recursion if you happen to use
the "unicode(self).encode('utf8')" idiom as the body of your
"__str__()" method).

You can use a mixin class to work around this. This allows you to only
define a "__unicode__()" method for your class and let the mixin
derive "__str__()" for you (code from
http://lucumr.pocoo.org/2011/1/22/forwards-compatible-python/):

   import sys

   class UnicodeMixin(object):

     """Mixin class to handle defining the proper __str__/__unicode__
     methods in Python 2 or 3."""

     if sys.version_info[0] >= 3: # Python 3
         def __str__(self):
             return self.__unicode__()
     else:  # Python 2
         def __str__(self):
             return self.__unicode__().encode('utf8')


   class Spam(UnicodeMixin):

     def __unicode__(self):
         return u'spam-spam-bacon-spam'  # 2to3 will remove the 'u' prefix


Don't Index on Exceptions
"""""""""""""""""""""""""

In Python 2, the following worked:

   >>> exc = Exception(1, 2, 3)
   >>> exc.args[1]
   2
   >>> exc[1]  # Python 2 only!
   2

But in Python 3, indexing directly on an exception is an error. You
need to make sure to only index on the "BaseException.args" attribute
which is a sequence containing all arguments passed to the
"__init__()" method.

Even better is to use the documented attributes the exception
provides.


Don't use "__getslice__" & Friends
""""""""""""""""""""""""""""""""""

Been deprecated for a while, but Python 3 finally drops support for
"__getslice__()", etc. Move completely over to "__getitem__()" and
friends.


Updating doctests
"""""""""""""""""

Don't forget to make them Python 2/3 compatible as well. If you wrote
a monolithic set of doctests (e.g., a single docstring containing all
of your doctests), you should at least consider breaking the doctests
up into smaller pieces to make it more manageable to fix. Otherwise it
might very well be worth your time and effort to port your tests to
"unittest".


Update "map" for imbalanced input sequences
"""""""""""""""""""""""""""""""""""""""""""

With Python 2, when "map" was given more than one input sequence it
would pad the shorter sequences with "None" values, returning a
sequence as long as the longest input sequence.

With Python 3, if the input sequences to "map" are of unequal length,
"map" will stop at the termination of the shortest of the sequences.
For full compatibility with "map" from Python 2.x, wrap the sequence
arguments in "itertools.zip_longest()", e.g. "map(func, *sequences)"
becomes "list(map(func, itertools.zip_longest(*sequences)))".


Eliminate "-3" Warnings
-----------------------

When you run your application's test suite, run it using the "-3" flag
passed to Python. This will cause various warnings to be raised during
execution about things that are semantic changes between Python 2 and
3. Try to eliminate those warnings to make your code even more
portable to Python 3.


Alternative Approaches
======================

While supporting Python 2 & 3 simultaneously is typically the
preferred choice by people so that they can continue to improve code
and have it work for the most number of users, your life may be easier
if you only have to support one major version of Python going forward.


Supporting Only Python 3 Going Forward From Python 2 Code
---------------------------------------------------------

If you have Python 2 code but going forward only want to improve it as
Python 3 code, then you can use *2to3* to translate your Python 2 code
to Python 3 code.  This is only recommended, though, if your current
version of your project is going into maintenance mode and you want
all new features to be exclusive to Python 3.


Backporting Python 3 code to Python 2
-------------------------------------

If you have Python 3 code and have little interest in supporting
Python 2 you can use 3to2 to translate from Python 3 code to Python 2
code. This is only recommended if you don't plan to heavily support
Python 2 users. Otherwise write your code for Python 3 and then
backport as far back as you want. This is typically easier than going
from Python 2 to 3 as you will have worked out any difficulties with
e.g. bytes/strings, etc.


Other Resources
===============

The authors of the following blog posts, wiki pages, and books deserve
special thanks for making public their tips for porting Python 2 code
to Python 3 (and thus helping provide information for this document
and its various revisions over the years):

* https://wiki.python.org/moin/PortingPythonToPy3k

* http://python3porting.com/

* http://docs.pythonsprints.com/python3_porting/py-porting.html

* http://techspot.zzzeek.org/2011/01/24/zzzeek-s-guide-to-
  python-3-porting/

* http://dabeaz.blogspot.com/2011/01/porting-py65-and-my-superboard-
  to.html

* http://lucumr.pocoo.org/2011/1/22/forwards-compatible-python/

* http://lucumr.pocoo.org/2010/2/11/porting-to-python-3-a-guide/

* https://wiki.ubuntu.com/Python/3

If you feel there is something missing from this document that should
be added, please email the python-porting mailing list.
