Porting tips¶
This section highlights some of the known incompatible changes made in Python that could break Python scripts and modules that used to work in prior versions. The sections are split into retroactive changes made to all Python releases, and information specific to every Python branch (compared to the previous one).
This guide is by no means considered complete. If you can think of other problems you’ve hit while porting your packages, please let me know and I will update it.
Retroactive changes¶
bpo43882: urlsplit now strips LF, CR and HT characters¶
Changed in: 2.7.18_p9, 3.6.13_p3, 3.7.10_p3, 3.8.9_p2, 3.9.4_p1
Historically, various urllib.parse methods have passed special characters such as LF, CR and HT through into the split URL components. This could have resulted in various exploits if Python programs did not validate the resulting components and used them verbatim.
bpo43882 attempted to address the issue by making urllib.parse strip the three aforementioned characters from the output of its functions. This fixed one class of potential issues but at the same time opened another can of worms. For example, URL validators that used to check for dangerous special characters in the split URL components stopped working correctly. In the best case, the URL were now sanitized instead of being rejected. In the worst, the original unparsed URL with dangerous characters started being passed through. See e.g. django PR#14349 for an example of impact and a fix.
Behavior before:
>>> urllib.parse.urlparse('https://example.com/bad\nurl')
ParseResult(scheme='https', netloc='example.com', path='/bad\nurl', params='', query='', fragment='')
Behavior after:
>>> urllib.parse.urlparse('https://example.com/bad\nurl')
ParseResult(scheme='https', netloc='example.com', path='/badurl', params='', query='', fragment='')
Experimental Python implementations¶
PyPy¶
PyPy is using JIT to run Python code which can result in significant performance improvements in some workflows, but it could also penalize other programs.
In particular, calls to compiled extensions can penalize PyPy severely.
For this reason, it is generally recommended to skip building “speedup”
extensions for PyPy — in fact, upstream build systems frequently do that
automatically. A common approach is to combine checks for PyPy with
native-extensions
USE flag:
python_compile() {
if ! use native-extensions || [[ ${EPYTHON} == pypy3 ]]; then
local -x MULTIDICT_NO_EXTENSIONS=1
fi
distutils-r1_python_compile
}
However, this does not imply that Python packages largely based on C extensions should not be marked for PyPy3 compatibility. For example, while packages such as Pandas can be less performant under PyPy, they could be used as a part of larger program that overall benefits from running under PyPy.
Freethreading CPython versions¶
CPython is used the so-called “global interpreter lock” to prevent multiple threads from executing Python code simultaneously. It was designed like this to simplify implementation, but at the cost of limiting the possible performance gain from use of multiple threads. Historically, only compiled extensions could temporarily disable it to take advantage of threading.
Starting with CPython 3.13, a support for an experimental “freethreading” mode has been added. If CPython is built in this variant, it uses more fine-grained locking mechanisms to make it possible to run multiple Python threads simultaneously. Note that this mode can only improve performance of multithreaded applications, and (at least at this point) penalizes single-threaded applications.
The freethreaded versions of CPython are not ABI-compatible with
the regular builds. Therefore, they are slotted as separate versions
with a t
suffix, e.g. Python 3.13 freethreading can be found
as dev-lang/python:3.13t
. They also need to be tested and added
to PYTHON_COMPAT
separately, e.g. as python3_13t
.
Note that compiled extensions need to declare support for freethreading
explicitly (see: C API Extension Support for Free Threading). While
extensions without explicit support can be compiled for freethreading
Python versions, importing them will cause GIL to be reenabled
and therefore defeat the purpose of freethreading build. To determine
whether a C extension supports freethreading mode, grep the code
for Py_MOD_GIL_NOT_USED
. CPython will also verbosely warn upon
importing extensions without this support.
In general, do not add python3_13t
to PYTHON_COMPAT
in leaf
packages, unless they make use of multithreading and have real gain
from freethreaded versions — otherwise, it may actually be slower than
the regular variant.
For dependency packages, add python3_13t
only after explicitly
testing that the package in question works. Do not add it
if the package in question installs extensions that do not support
freethreading. This would penalize the setup, prevent proper testing
and therefore defeat the purpose of separately specifying this target.
Preferably, wait until they do. For some common dependencies, adding it
may be acceptable, provided that the extensions are optional and that
they are not built for freethreading targets.
Python 3.13¶
See also: what’s new in Python 3.13
cgi module removal¶
Python 3.13 removed the deprecated cgi module that provided a number of utilities for CGI scripts. The standard library documentation (as of Python 3.12) provides detailed information on replacing the deprecated functions.
The said documentation recommends the multipart package as a replacement for some of the functions. In its context, the multipart vs. python-multipart packages section of Migration guides should be consulted as well.
Docstring dedenting¶
Prior to Python 3.13, all whitespace in docstrings would be preserved
and exposed in the __doc__
attribute. Starting with 3.13,
docstrings are instead stripped and dedented. For example, consider
the following docstring:
def frobnicate(thing):
"""Frobnicate the thing
Do some magic frobnication on the thing.
Example::
frobnicated_thing = frobnicate(thing)
"""
In Python 3.12, all whitespace is preserved in __doc__
, yielding:
Frobnicate the thing
Do some magic frobnication on the thing.
Example::
frobnicated_thing = frobnicate(thing)
Python 3.13 instead strips leading whitespace from the first line, and the common amount of whitespace from the subsequent lines, yielding:
Frobnicate the thing
Do some magic frobnication on the thing.
Example::
frobnicated_thing = frobnicate(thing)
This can break some tests that rely on specific __doc__
values.
To ensure consistent results, inspect.cleandoc() can be used
to perform the same operation in older Python versions, i.e.:
assert inspect.cleandoc(frobnicate.__doc__) == expected_doc
Python 3.12¶
See also: what’s new in Python 3.12
.called_with (and other invalid assertions) now trigger an error¶
It is not uncommon for test suites to write invalid assertions such as:
with unittest.mock.patch("...") as foo_mock:
...
assert foo_mock.called_with(...)
Prior to Python 3.12, such assertions would silently pass. Since
the .called_with()
method does not exist, a MagicMock
object
is returned and it evaluates to True
in boolean context.
Starting with Python 3.12, an exception is raised instead:
AttributeError: 'called_with' is not a valid assertion. Use a spec for the mock if 'called_with' is meant to be an attribute.
The fix is to use the correct .assert_called_with()
method
or similar:
with unittest.mock.patch("...") as foo_mock:
...
foo_mock.assert_called_with(...)
See the unittest.mock documentation for the complete list of available assertions.
Please note that since the original code did not actually test anything, fixing the test case may reveal failed expectations.
Deprecated test method alias removal¶
Python 3.12 removes multiple deprecated test method aliases, such
as assertEquals()
and assertRegexpMatches()
. The documentation
provides a list of removed aliases and their modern replacements.
It should be noted that all of the new methods are available since Python 3.2 (and most even earlier), so the calls can be replaced without worrying about backwards compatibility.
Most of the time, it should be possible to trivially sed
the methods
in ebuild without having to carry a patch, e.g.:
src_prepare() {
# https://github.com/byroot/pysrt/commit/93f52f6d4f70f4e18dc71deeaae0ec1e9100a50f
sed -i -e 's:assertEquals:assertEqual:' tests/*.py || die
distutils-r1_src_prepare
}
Python 3.11¶
See also: what’s new in Python 3.11
Generator-based coroutine removal (asyncio.coroutine)¶
Support for generator-based coroutines has been deprecated since Python 3.8, and is finally removed in 3.11. This usually results in the following error:
AttributeError: module 'asyncio' has no attribute 'coroutine'
The recommended solution is to use PEP 492 coroutines. They are
available since Python 3.5. This means replacing
the @asyncio.coroutine
decorator with async def
keyword,
and yield from
with await
.
For example, the following snippet:
@asyncio.coroutine
def foo():
yield from asyncio.sleep(5)
would become:
async def foo():
await asyncio.sleep(5)
inspect.getargspec() and inspect.formatargspec() removal¶
The inspect.getargspec() (deprecated since Python 3.0) and inspect.formatargspec() (deprecated since Python 3.5) functions are both removed in Python 3.11.
The inspect.getargspec() function provides a legacy interface to inspect the signature of callables. It is replaced by the object-oriented inspect.signature() API (available since Python 3.3), or a mostly compatible inspect.getfullargspec() function (available since Python 3.0).
For example, a trivial function would yield the following results:
>>> def foo(p1, p2, /, kp3, kp4 = 10, kp5 = None, *args, **kwargs):
... pass
...
>>> inspect.getargspec(foo)
ArgSpec(args=['p1', 'p2', 'kp3', 'kp4', 'kp5'],
varargs='args',
keywords='kwargs',
defaults=(10, None))
>>> inspect.getfullargspec(foo)
FullArgSpec(args=['p1', 'p2', 'kp3', 'kp4', 'kp5'],
varargs='args',
varkw='kwargs',
defaults=(10, None),
kwonlyargs=[],
kwonlydefaults=None,
annotations={})
>>> inspect.signature(foo)
<Signature (p1, p2, /, kp3, kp4=10, kp5=None, *args, **kwargs)>
The named tuple returned by inspect.getfullargspec() starts with
the same information, except that the key used to hold the name
of **
parameter is varkw
rather than keywords
.
inspect.signature() returns a Signature
object.
Both of the newer functions support keyword-only arguments and type annotations:
>>> def foo(p1: int, p2: str, /, kp3: str, kp4: int = 10,
... kp5: float = None, *args, k6: str, k7: int = 12,
... k8: float, **kwargs) -> float:
... pass
...
>>> inspect.getfullargspec(foo)
FullArgSpec(args=['p1', 'p2', 'kp3', 'kp4', 'kp5'],
varargs='args',
varkw='kwargs',
defaults=(10, None),
kwonlyargs=['k6', 'k7', 'k8'],
kwonlydefaults={'k7': 12},
annotations={'return': <class 'float'>,
'p1': <class 'int'>,
'p2': <class 'str'>,
'kp3': <class 'str'>,
'kp4': <class 'int'>,
'kp5': <class 'float'>,
'k6': <class 'str'>,
'k7': <class 'int'>,
'k8': <class 'float'>})
>>> inspect.signature(foo)
<Signature (p1: int, p2: str, /, kp3: str, kp4: int = 10,
kp5: float = None, *args, k6: str, k7: int = 12,
k8: float, **kwargs) -> float>
One notable difference between inspect.signature() and the two other functions is that the latter always include the ‘self’ argument of method prototypes, while the former skips it if the method is bound to an object. That is:
>>> class foo:
... def x(self, bar):
... pass
...
>>> inspect.getargspec(foo.x)
ArgSpec(args=['self', 'bar'], varargs=None, keywords=None, defaults=None)
>>> inspect.getargspec(foo().x)
ArgSpec(args=['self', 'bar'], varargs=None, keywords=None, defaults=None)
>>> inspect.signature(foo.x)
<Signature (self, bar)>
>>> inspect.signature(foo().x)
<Signature (bar)>
The inspect.formatargspec() function provides a pretty-formatted
argument spec from the tuple returned by inspect.getfullargspec()
(or inspect.getargspec()). It is replaced by stringification
of Signature
objects:
>>> def foo(p1: int, p2: str, /, kp3: str, kp4: int = 10,
... kp5: float = None, *args, k6: str, k7: int = 12,
... k8: float, **kwargs) -> float:
... pass
...
>>> inspect.formatargspec(*inspect.getfullargspec(foo))
'(p1: int, p2: str, kp3: str, kp4: int=10, kp5: float=None, '
'*args, k6: str, k7: int=12, k8: float, **kwargs) -> float'
>>> str(inspect.signature(foo))
'(p1: int, p2: str, /, kp3: str, kp4: int = 10, kp5: float = None, '
'*args, k6: str, k7: int = 12, k8: float, **kwargs) -> float'
Python 3.10¶
See also: what’s new in Python 3.10
configure: No package ‘python-3.1’ found¶
automake prior to 1.16.3 wrongly recognized Python 3.10 as 3.1. As a result, build with Python 3.10 fails:
checking for python version... 3.1
checking for python platform... linux
checking for python script directory... ${prefix}/lib/python3.10/site-packages
checking for python extension module directory... ${exec_prefix}/lib/python3.10/site-packages
checking for PYTHON... no
configure: error: Package requirements (python-3.1) were not met:
No package 'python-3.1' found
Consider adjusting the PKG_CONFIG_PATH environment variable if you
installed software in a non-standard prefix.
Alternatively, you may set the environment variables PYTHON_CFLAGS
and PYTHON_LIBS to avoid the need to call pkg-config.
See the pkg-config man page for more details.
Error: Process completed with exit code 1.
To resolve this in ebuild, you need to autoreconf with the Gentoo distribution of automake:
inherit autotools
# ...
src_prepare() {
default
eautoreconf
}
The upstream fix is to create new distfiles using automake-1.16.3+.
distutils.sysconfig deprecation¶
Upstream intends to remove distutils by Python 3.12. Python 3.10 starts throwing deprecation warnings for various distutils modules. The distutils.sysconfig is usually easy to port.
The following table summarizes replacements for common path getters.
distutils.sysconfig call
sysconfig replacement
get_python_inc(False)
get_path("include")
get_python_inc(True)
get_path("platinclude")
get_python_lib(False, False)
get_path("purelib")
get_python_lib(True, False)
get_path("platlib")
get_python_lib(False, True)
get_path("stdlib")
get_python_lib(True, True)
get_path("platstdlib")
For both functions, omitted parameters default to False
. There is
no trivial replacement for the variants with prefix
argument.
Python 3.9¶
See also: what’s new in Python 3.9
base64.encodestring / base64.decodestring removal¶
Python 3.9 removes the deprecated base64.encodestring()
and base64.decodestring()
functions. While they were deprecated
since Python 3.1, many packages still use them today.
The drop-in Python 3.1+ replacements are base64.encodebytes()
and base64.decodebytes()
. Note that contrary to the names, the old
functions were simply aliases to the byte variants in Python 3
and required the arguments to be bytes
anyway.
If compatibility with Python 2 is still desired, then the byte variants ought to be called on 3.1+ and string variants before that. The old variants accept both byte and unicode strings on Python 2.
Example compatibility import:
import sys
if sys.version_info >= (3, 1):
from base64 import encodebytes as b64_encodebytes
else:
from base64 import encodestring as b64_encodebytes
Note that the base64
module also provides b64encode()
and b64decode()
functions that were not renamed. b64decode()
can be used as a drop-in replacement for decodebytes()
. However,
b64encode()
does not insert newlines to split the output
like encodebytes()
does, and instead returns a single line
of base64-encoded data for any length of output.
Python 3.8¶
See also: what’s new in Python 3.8
python-config and pkg-config no longer list Python library by default¶
Until Python 3.7, the python-X.Y
pkg-config file and python-config
tool listed the Python library. Starting with 3.8, this is no longer
the case. If you are building Python extensions, this is fine (they
are not supposed to link directly to libpython).
If you are building programs that need to embed the Python interpreter,
new python-X.Y-embed
pkg-config file and --embed
parameter
are provided for the purpose.
$ pkg-config --libs python-3.7
-lpython3.7m
$ pkg-config --libs python-3.8
$ pkg-config --libs python-3.8-embed
-lpython3.8
To achieve backwards compatibility, you should query
python-X.Y-embed
first and fall back to python-X.Y
.
Replacing the toml package¶
The old toml package is no longer maintained. It was last released in November 2020 and it was never updated to implement TOML 1.0. The recommended alternatives are:
the built-in tomllib module (since Python 3.11) with fallback to tomli package for reading TOML files
the tomli-w package for writing TOML files
the tomlkit package for editing already existing TOML files while preserving style
Porting to tomllib/tomli without toml fallback¶
Using a combination of tomllib and tomli is the recommended approach for packages that only read TOML files, or both read and write them but do not need to preserve style. The tomllib module is available since Python 3.11, while tomli versions providing a compatible API are compatible with Python 3.6 and newer.
The key differences between toml and tomllib/tomli are:
the
load()
function accepts only a file object open for reading in binary mode whereas toml expects a path or a file object open for reading in text modethe exception raised for invalid input is named
TOMLDecodeError
where it is namedTomlDecodeError
in toml
For example, the following code:
import toml
try:
d1 = toml.load("in1.toml")
except toml.TomlDecodeError:
d1 = None
with open("in2.toml", "r") as f:
d2 = toml.load(f)
d3 = toml.loads('test = "foo"\n')
would normally be written as:
import sys
if sys.version_info >= (3, 11):
import tomllib
else:
import tomli as tomllib
try:
# tomllib does not accept paths
with open("in1.toml", "rb") as f:
d1 = tomllib.load(f)
# the exception uses uppercase "TOML"
except tomllib.TOMLDecodeError:
d1 = None
# the file must be open in binary mode
with open("in2.toml", "rb") as f:
d2 = tomllib.load(f)
d3 = tomllib.loads('test = "foo"\n')
The following dependency string:
dependencies = [
"toml",
]
would be replaced by:
dependencies = [
"tomli >= 1.2.3; python_version < '3.11'",
]
Porting to tomllib/tomli with toml fallback¶
If upstream insists on preserving compatibility with EOL versions of Python, it is possible to use a combination of tomllib, tomli and toml. Unfortunately, the incompatibilites in API need to be taken into consideration.
For example, a backwards compatible code for loading a TOML file could look like the following:
import sys
try:
if sys.version_info >= (3, 11):
import tomllib
else:
import tomli as tomllib
try:
with open("in1.toml", "rb") as f:
d1 = tomllib.load(f)
except tomllib.TOMLDecodeError:
d1 = None
except ImportError:
import toml
try:
with open("in1.toml", "r") as f:
d1 = toml.load(f)
except toml.TomlDecodeError:
d1 = None
In this case, the dependency string becomes more complex:
dependencies = [
"tomli >= 1.2.3; python_version >= '3.6' and python_version < '3.11'",
"toml; python_version < '3.6'",
]
Porting to tomli-w¶
tomli-w provides a minimal module for dumping TOML files.
The key differences between toml and tomli-w are:
the
dump()
function takes a file object open for writing in binary mode whereas toml expected a file object open for writing in text modeproviding a custom encoder instance is not supported
For example, the following code:
import toml
with open("out.toml", "w") as f:
toml.dump({"test": "data"}, f)
would be replaced by:
import tomli_w
with open("out.toml", "wb") as f:
tomli_w.dump({"test": "data"}, f)
Note that when both reading and writing TOML files is necessary, two modules need to be imported and used separately rather than one.