Python interpreters

Versions of Python

By a version of Python we usually mean the variant of Python language and standard library interface as used by a specific version of CPython, the reference implementation of Python.

Python versions are determined from the two first version components. The major version is incremented when major incompatible changes are introduced in the language, as was the case in Python 3. Along with minor version changes, the new releases introduce new features and remove deprecated APIs. The Python documentation generally indicates when a particular API was added or deprecated, and when it is planned to be removed.

Practically speaking, this means that a program written purely for Python 2 is unlikely to work on Python 3, and requires major changes to achieve compatibility. On the other hand, a program written for Python 3.7 is very likely to work with Python 3.8, and reasonably likely to support Python 3.6 as well. If that is not the case, minor changes are usually sufficient to fix that.

For example, Python 3.7 introduced a new importlib.resources module. If your program uses it, it will not work on Python 3.6 without a backwards compatibility code.

Python 3.8 removed the deprecated platform.linux_distribution() function. If your program used it, it will not work on Python 3.8 without changes. However, it was deprecated since Python 3.5, so if you were targetting 3.7, you should not have been using it in the first place.

Gentoo supports building packages against Python 2.7 and a shifting window of 3-4 versions of Python 3. They are provided as slots of dev-lang/python.

Alternative Python implementations

CPython is the reference and most commonly used Python implementation. However, there are other interpreters that aim to maintain reasonable compatibility with it.

PyPy is an implementation of Python built using in-house RPython language, using a Just-in-Time compiler to achieve better performance (generally in long-running programs running a lot of Python code). It maintains quite good compatibility with CPython, except when programs rely on its implementation details or GC behavior.

PyPy upstream provides PyPy variants compatible with Python 2.7 and one version of Python 3. Gentoo supports building packages against PyPy3. PyPy2.7 is provided as dev-python/pypy, while PyPy3 is provided as dev-python/pypy3.

Jython is an implementation of Python written in Java. Besides being a stand-alone Python interpreter, it supports bidirectional interaction between Python and Java libraries.

Jython development is very slow paced, and it is currently bound to Python 2.7. Gentoo does not support building packages for Jython anymore. The interpreter is still provided as dev-java/jython.

IronPython is an implementation of Python for the .NET framework. Alike Jython, it supports bidirectional interaction between Python and .NET Framework. It is currently bound to Python 2.7. It is not packaged in Gentoo.

Brython is an implementation of Python 3 for client-side web programming (in JavaScript). It provides a subset of Python 3 standard library combined with access to DOM objects. It is packaged in Gentoo as dev-python/brython.

MicroPython is an implementation of Python 3 aimed for microcontrollers and embedded environments. It aims to maintain some compatibility with CPython while providing stripped down standard library and additional modules to interface with hardware. It is packaged as dev-lang/micropython.

Tauthon is a fork of Python 2.7 that aims to backport new language features and standard library modules while preserving backwards compatibility with existing code. It is not packaged in Gentoo.

Support for multiple implementations

The support for simultaneously using multiple Python implementations is implemented primarily through USE flags. The packages installing or using Python files define either PYTHON_TARGETS or PYTHON_SINGLE_TARGET flags that permit user to choose which implementations are used.

Modules and extensions are installed separately for each interpreter, in its specific site-packages directory. This means that a package can run using a specific target correctly only if all its dependencies were also installed for the same implementation. This is enforced via USE dependencies.

Additionally, dev-lang/python-exec provides a mechanism for installing multiple variants of each Python script simultaneously. This is necessary to support scripts that differ between Python versions (particularly between Python 2 and Python 3) but it is also used to prevent scripts from being called via unsupported interpreter (i.e. one that does not have its accompanying modules or dependencies installed).

This also implies that all installed Python scripts must have their shebangs adjusted to use a specific Python interpreter (not python nor python3 but e.g. python3.7), and all other executables must also be modified to call specific version of Python directly.


A common method of improving compatibility with older versions of Python is to backport new standard library modules or features. Packages doing that are generally called backports.

Ideally, backports copy the code from the standard library with minimal changes, and provide a matching API. In some cases, new versions of backports are released as the standard library changes, and their usability extends from providing a missing module to extending older version of the module. For example, the dev-python/funcsigs package originally backported function signatures from Python 3.3 to older versions, and afterwards was updated to backport new features from Python 3.6, becoming useful to versions 3.3 through 3.5.

Sometimes, the opposite happens. dev-python/mock started as a stand-alone package, and was integrated into the standard library as unittest.mock later on. Afterwards, the external package became a backport of the standard library module.

In some cases backports effectively replace external packages. Once lzma module has been added to the standard library, its backport dev-python/backports-lzma has effectively replaced the competing LZMA packages.

Individual backports differ by the level of compatibility with the standard library provided, and therefore on the amount of additional code needed in your program. The exact kind of dependencies used depends on that.

dev-python/ipaddress is a drop-in backport of the ipaddress module from Python 3.3. It is using the same module name, so a code written to use this module will work out-of-the-box on Python 2.7 if the package is installed. As a side note, since Python always prefers built-in modules over external packages, there is no point in enabling Python 3 in this package as the installed module would never be used. Appropriately, you should depend on this package only for the Python versions needing it.

dev-python/mock is a compatible backport of the unittest.mock module. It can’t use the same name as the standard library module, therefore the packages need to use it conditionally, e.g.:

    from unittest.mock import Mock
except ImportError:  # py<3.3
    from mock import Mock


import sys
if sys.hexversion >= 0x03030000:
    from unittest.mock import Mock
    from mock import Mock

However, the actual API remains compatible, so the programs do not need more compatibility code than that. In some cases, upstreams fail (or even refuse) to use the external mock package conditionally — in that case, you either need to depend on this package unconditionally, or patch it.

dev-python/trollius aimed to provide a backport of asyncio for Python 2. Since the asyncio framework relies on new Python syntax, the backport cannot be API compatible and requires using a different syntax than native asyncio code.