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Issue #22914: Update the Python 2/3 porting HOWTO to describe a more 

automated process.
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@ -19,600 +19,359 @@ Porting Python 2 Code 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 <https://pypi.python.org/pypi/caniusepython3>`__,
`web app <https://caniusepython3.com/>`__)
With that done, your options are:
* If you are dropping Python 2 support, use :ref:`2to3 <2to3-reference>` 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
:func:`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 :term:`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 :func:`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
'''''''''''''''''''''''''''''''''''''
The Short Explanation
=====================
To make your project be single-source Python 2/3 compatible, the basic steps
are:
#. Update your code to drop support for Python 2.5 or older (supporting only
Python 2.7 is ideal)
#. Make sure you have good test coverage (coverage.py_ can help)
#. Learn the differences between Python 2 & 3
#. Use Modernize_ or Futurize_ to update your code
#. Use Pylint_ to help make sure you don't regress on your Python 3 support
(if only supporting Python 2.7/3.4 or newer)
#. Use caniusepython3_ to find out which of your dependencies are blocking your
use of Python 3
#. Once your dependencies are no longer blocking you, use continuous integration
to make sure you stay compatible with Python 2 & 3 (tox_ can help test
against multiple versions of Python)
If you are dropping support for Python 2 entirely, then after you learn the
differences between Python 2 & 3 you can run 2to3_ over your code and skip the
rest of the steps outlined above.
Details
=======
A key point about supporting Python 2 & 3 simultaneously is that you can start
**today**! Even if your dependencies are not supporting Python 3 yet that does
not mean you can't modernize your code **now** to support Python 3. Most changes
required to support Python 3 lead to cleaner code using newer practices even in
Python 2.
Another key point is that modernizing your Python 2 code to also support
Python 3 is largely automated for you. While you might have to make some API
decisions thanks to Python 3 clarifying text data versus binary data, the
lower-level work is now mostly done for you and thus can at least benefit from
the automated changes immediately.
Keep those key points in mind while you read on about the details of porting
your code to support Python 2 & 3 simultaneously.
Drop support for Python 2.5 and older (at least)
------------------------------------------------
While you can make Python 2.5 work with Python 3, it is **much** easier if you
only have to work with Python 2.6 or newer (and easier still if you only have
to work with Python 2.7). If dropping Python 2.5 is not an option then the six_
project can help you support Python 2.5 & 3 simultaneously. Do realize, though,
that nearly all the projects listed in this HOWTO will not be available to you.
If you are able to only support Python 2.6 or newer, then the required changes
to your code should continue to look and feel like idiomatic Python code. At
worst you will have to use a function instead of a method in some instances or
have to import a function instead of using a built-in one, but otherwise the
overall transformation should not feel foreign to you.
But please aim for Python 2.7. Bugfixes for that version of Python will continue
until 2020 while Python 2.6 is no longer supported. There are also some tools
mentioned in this HOWTO which do not support Python 2.6 (e.g., Pylint_), and
this will become more commonplace as time goes on.
Make sure you specify the proper version support in your ``setup.py`` file
--------------------------------------------------------------------------
In your ``setup.py`` file you should have the proper `trove classifier`_
specifying what versions of Python you support. As your project does not support
Python 3 yet you should at least have
``Programming Language :: Python :: 2 :: Only`` specified. Ideally you should
also specify each major/minor version of Python that you do support, e.g.
``Programming Language :: Python :: 2.7``.
Have good test coverage
-----------------------
Once you have your code supporting the oldest version of Python 2 you want it
to, you will want to make sure your test suite has good coverage. A good rule of
thumb is that if you want to be confident enough in your test suite that any
failures that appear after having tools rewrite your code are actual bugs in the
tools and not in your code. If you want a number to aim for, try to get over 80%
coverage (and don't feel bad if you can't easily get past 90%). If you
don't already have a tool to measure test coverage then coverage.py_ is
recommended.
Learn the differences between Python 2 & 3
-------------------------------------------
Once you have your code well-tested you are ready to begin porting your code to
Python 3! But to fully understand how your code is going to change and what
you want to look out for while you code, you will want to learn what changes
Python 3 makes in terms of Python 2. Typically the two best ways of doing that
is reading the `"What's New"`_ doc for each release of Python 3 and the
`Porting to Python 3`_ book (which is free online).
Update your code
----------------
Once you feel like you know what is different in Python 3 compared to Python 2,
it's time to update your code! You have a choice between two tools in porting
your code automatically: Modernize_ and Futurize_. Which tool you choose will
depend on how much like Python 3 you want your code to be. Futurize_ does its
best to make Python 3 idioms and practices exist in Python 2, e.g. backporting
the ``bytes`` type from Python 3 so that you have semantic parity between the
major versions of Python. Modernize_,
on the other hand, is more conservative and targets a Python 2/3 subset of
Python, relying on six_ to help provide compatibility.
Regardless of which tool you choose, they will update your code to run under
Python 3 while staying compatible with the version of Python 2 you started with.
Depending on how conservative you want to be, you may want to run the tool over
your test suite first and visually inspect the diff to make sure the
transformation is accurate. After you have transformed your test suite and
verified that all the tests still pass as expected, then you can transform your
application code knowing that any tests which fail is a translation failure.
Unfortunately the tools can't automate everything to make your code work under
Python 3 and so there are a handful of things you will need to update manually
to get full Python 3 support (which of these steps are necessary vary between
the tools). Read the documentation for the tool you choose to use to see what it
fixes by default and what it can do optionally to know what will (not) be fixed
for you and what you may have to fix on your own (e.g. using ``io.open()`` over
the built-in ``open()`` function is off by default in Modernize). Luckily,
though, there are only a couple of things to watch out for which can be
considered large issues that may be hard to debug if not watched for.
Division
++++++++
In Python 3, ``5 / 2 == 2.5`` and not ``2``; all division between ``int`` values
result in a ``float``. This change has actually been planned since Python 2.2
which was released in 2002. Since then users have been encouraged to add
``from __future__ import division`` to any and all files which use the ``/`` and
``//`` operators or to be running the interpreter with the ``-Q`` flag. If you
have not been doing this then you will need to go through your code and do two
things:
#. Add ``from __future__ import division`` to your files
#. Update any division operator as necessary to either use ``//`` to use floor
division or continue using ``/`` and expect a float
The reason that ``/`` isn't simply translated to ``//`` automatically is that if
an object defines its own ``__div__`` method but not ``__floordiv__`` then your
code would begin to fail.
Text versus binary data
+++++++++++++++++++++++
In Python 2 you could use the ``str`` type for both text and binary data.
Unfortunately this confluence of two different concepts could lead to brittle
code which sometimes worked for either kind of data, sometimes not. It also
could lead to confusing APIs if people didn't explicitly state that something
that accepted ``str`` accepted either text or binary data instead of one
specific type. This complicated the situation especially for anyone supporting
multiple languages as APIs wouldn't bother explicitly supporting ``unicode``
when they claimed text data support.
To make the distinction between text and binary data clearer and more
pronounced, Python 3 did what most languages created in the age of the internet
have done and made text and binary data distinct types that cannot blindly be
mixed together (Python predates widespread access to the internet). For any code
that only deals with text or only binary data, this separation doesn't pose an
issue. But for code that has to deal with both, it does mean you might have to
now care about when you are using text compared to binary data, which is why
this cannot be entirely automated.
To start, you will need to decide which APIs take text and which take binary
(it is **highly** recommended you don't design APIs that can take both due to
the difficulty of keeping the code working; as stated earlier it is difficult to
do well). In Python 2 this means making sure the APIs that take text can work
with ``unicode`` in Python 2 and those that work with binary data work with the
``bytes`` type from Python 3 and thus a subset of ``str`` in Python 2 (which the
``bytes`` type in Python 2 is an alias for). Usually the biggest issue is
realizing which methods exist for which types in Python 2 & 3 simultaneously
(for text that's ``unicode`` in Python 2 and ``str`` in Python 3, for binary
that's ``str``/``bytes`` in Python 2 and ``bytes`` in Python 3). The following
table lists the **unique** methods of each data type across Python 2 & 3
(e.g., the ``decode()`` method is usable on the equivalent binary data type in
either Python 2 or 3, but it can't be used by the text data type consistently
between Python 2 and 3 because ``str`` in Python 3 doesn't have the method).
======================== =====================
**Text data** **Binary data**
------------------------ ---------------------
__mod__ (``%`` operator)
------------------------ ---------------------
\ decode
------------------------ ---------------------
encode
------------------------ ---------------------
format
------------------------ ---------------------
isdecimal
------------------------ ---------------------
isnumeric
======================== =====================
Making the distinction easier to handle can be accomplished by encoding and
decoding between binary data and text at the edge of your code. This means that
when you receive text in binary data, you should immediately decode it. And if
your code needs to send text as binary data then encode it as late as possible.
This allows your code to work with only text internally and thus eliminates
having to keep track of what type of data you are working with.
The next issue is making sure you know whether the string literals in your code
represent text or binary data. At minimum you should add a ``b`` prefix to any
literal that presents binary data. For text you should either use the
``from __future__ import unicode_literals`` statement or add a ``u`` prefix to
the text literal.
As part of this dichotomy you also need to be careful about opening files.
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 :mod:`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 :func:`io.open`. Since :func:`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 :func:`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 :class:`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 :class:`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 :attr:`BaseException.args` attribute which is a
sequence containing all arguments passed to the :meth:`__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 :meth:`__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 :mod:`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
:func:`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 :ref:`2to3 <2to3-reference>` 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.
.. _3to2: https://pypi.python.org/pypi/3to2
.. _Cheeseshop: PyPI_
.. _coverage: https://pypi.python.org/pypi/coverage
.. _future: http://python-future.org/
.. _modernize: https://github.com/mitsuhiko/python-modernize
binary access (allowing to read and/or write binary data) or text access
(allowing to read and/or write text data). You should also use :func:`io.open`
for opening files instead of the built-in :func:`open` function as the :mod:`io`
module is consistent from Python 2 to 3 while the built-in :func:`open` function
is not (in Python 3 it's actually :func:`io.open`).
Finally, the indexing of binary data requires careful handling (slicing does
**not** require any special handling). In Python 2,
``b'123'[1] == b'2'`` while in Python 3 ``b'123'[1] == 50``. Because binary data
is simply a collection of binary numbers, Python 3 returns the integer value for
the byte you index on. But in Python 2 because ``bytes == str``, indexing
returns a one-item slice of bytes. The six_ project has a function
named ``six.indexbytes()`` which will return an integer like in Python 3:
``six.indexbytes(b'123', 1)``.
To summarize:
#. Decide which of your APIs take text and which take binary data
#. Make sure that your code that works with text also works with ``unicode`` and
code for binary data works with ``bytes`` in Python 2 (see the table above
for what methods you cannot use for each type)
#. Mark all binary literals with a ``b`` prefix, use a ``u`` prefix or
:mod:`__future__` import statement for text literals
#. Decode binary data to text as soon as possible, encode text as binary data as
late as possible
#. Open files using :func:`io.open` and make sure to specify the ``b`` mode when
appropriate
#. Be careful when indexing binary data
Prevent compatibility regressions
---------------------------------
Once you have fully translated your code to be compatible with Python 3, you
will want to make sure your code doesn't regress and stop working under
Python 3. This is especially true if you have a dependency which is blocking you
from actually running under Python 3 at the moment.
To help with staying compatible, any new modules you create should have
at least the following block of code at the top of it::
from __future__ import absolute_import
from __future__ import division
from __future__ import print_statement
from __future__ import unicode_literals
You can also run Python 2 with the ``-3`` flag to be warned about various
compatibility issues your code triggers during execution. If you turn warnings
into errors with ``-Werror`` then you can make sure that you don't accidentally
miss a warning.
You can also use the Pylint_ project and its ``--py3k`` flag to lint your code
to receive warnings when your code begins to deviate from Python 3
compatibility. This also prevents you from having to run Modernize_ or Futurize_
over your code regularly to catch compatibility regressions. This does require
you only support Python 2.7 and Python 3.4 or newer as that is Pylint's
minimum Python version support.
Check which dependencies block your transition
----------------------------------------------
**After** you have made your code compatible with Python 3 you should begin to
care about whether your dependencies have also been ported. The caniusepython3_
project was created to help you determine which projects
-- directly or indirectly -- are blocking you from supporting Python 3. There
is both a command-line tool as well as a web interface at
https://caniusepython3.com .
The project also provides code which you can integrate into your test suite so
that you will have a failing test when you no longer have dependencies blocking
you from using Python 3. This allows you to avoid having to manually check your
dependencies and to be notified quickly when you can start running on Python 3.
Update your ``setup.py`` file to denote Python 3 compatibility
--------------------------------------------------------------
Once your code works under Python 3, you should update the classifiers in
your ``setup.py`` to contain ``Programming Language :: Python :: 3`` and to not
specify sole Python 2 support. This will tell
anyone using your code that you support Python 2 **and** 3. Ideally you will
also want to add classifiers for each major/minor version of Python you now
support.
Use continuous integration to stay compatible
---------------------------------------------
Once you are able to fully run under Python 3 you will want to make sure your
code always works under both Python 2 & 3. Probably the best tool for running
your tests under multiple Python interpreters is tox_. You can then integrate
tox with your continuous integration system so that you never accidentally break
Python 2 or 3 support.
You may also want to use use the ``-bb`` flag with the Python 3 interpreter to
trigger an exception when you are comparing bytes to strings. Usually it's
simply ``False``, but if you made a mistake in your separation of text/binary
data handling you may be accidentally comparing text and binary data. This flag
will raise an exception when that occurs to help track down such cases.
And that's mostly it! At this point your code base is compatible with both
Python 2 and 3 simultaneously. Your testing will also be set up so that you
don't accidentally break Python 2 or 3 compatibility regardless of which version
you typically run your tests under while developing.
Dropping Python 2 support completely
====================================
If you are able to fully drop support for Python 2, then the steps required
to transition to Python 3 simplify greatly.
#. Update your code to only support Python 2.7
#. Make sure you have good test coverage (coverage.py_ can help)
#. Learn the differences between Python 2 & 3
#. Use 2to3_ to rewrite your code to run only under Python 3
After this your code will be fully Python 3 compliant but in a way that is not
supported by Python 2. You should also update the classifiers in your
``setup.py`` to contain ``Programming Language :: Python :: 3 :: Only``.
.. _2to3: https://docs.python.org/3/library/2to3.html
.. _caniusepython3:
.. _coverage.py: https://pypi.python.org/pypi/coverage
.. _Futurize: http://python-future.org/automatic_conversion.html
.. _Modernize:
.. _Porting to Python 3: http://python3porting.com/
.. _PyPI: https://pypi.python.org/pypi
.. _Python 3 Packages: https://pypi.python.org/pypi?:action=browse&c=533&show=all
.. _Pylint: https://pypi.python.org/pypi/pylint
.. _Python 3 Q & A: http://ncoghlan-devs-python-notes.readthedocs.org/en/latest/python3/questions_and_answers.html
.. _python-future: http://python-future.org/
.. _python-porting: https://mail.python.org/mailman/listinfo/python-porting
.. _six: https://pypi.python.org/pypi/six
.. _tox: https://pypi.python.org/pypi/tox
.. _trove classifiers: https://pypi.python.org/pypi?%3Aaction=list_classifiers
.. _trove classifier: https://pypi.python.org/pypi?%3Aaction=list_classifiers
.. _"What's New": https://docs.python.org/3/whatsnew/index.html

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Misc/NEWS
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@ -219,6 +219,9 @@ Build
Documentation
-------------
- Issue #22914: Update the Python 2/3 porting HOWTO to describe a more automated
approach.
- Issue #21514: The documentation of the json module now refers to new JSON RFC
7159 instead of obsoleted RFC 4627.