PEP: 387 Title: Backwards Compatibility Policy Author: Benjamin Peterson <benjamin@python.org> PEP-Delegate: Brett Cannon <brett@python.org> Status: Active Type: Process Created: 18-Jun-2009 Post-History: 19-Jun-2009,

12-Jun-2020, 19-Dec-2022, 16-Jun-2023

Replaces: 291

Abstract

This PEP outlines Python's backwards compatibility policy.

Rationale

As one of the most used programming languages today [1], the Python core language and its standard library play a critical role in millions of applications and libraries. This is fantastic. However, it means the development team must be very careful not to break this existing 3rd party code with new releases.

This PEP takes the perspective that "backwards incompatibility" means preexisting code ceases to comparatively function after a change. It is acknowledged that this is not a concrete definition, but the expectation is people in general understand what is meant by "backwards incompatibility", and if they are unsure they may ask the Python development team and/or steering council for guidance.

Backwards Compatibility Rules

This policy applies to all public APIs. These include:

Syntax and behavior of these constructs as defined by the reference manual.
The C-API.
Function, class, module, attribute, and method names and types.
Given a set of arguments, the return value, side effects, and raised exceptions of a function. This does not preclude changes from reasonable bug fixes.
The position and expected types of arguments and returned values.
Behavior of classes with regards to subclasses: the conditions under which overridden methods are called.
Documented exceptions and the semantics which lead to their raising.
Exceptions commonly raised in EAFP scenarios.

Others are explicitly not part of the public API. They can change or be removed at any time in any way. These include:

Function, class, module, attribute, method, and C-API names and types that are prefixed by "_" (except special names).
Anything documented publicly as being private. Note that if something is not documented at all, it is not automatically considered private.
Imported modules (unless explicitly documented as part of the public API; e.g. importing the bacon module in the spam does not automatically mean spam.bacon is part of the public API unless it is documented as such).
Inheritance patterns of internal classes.
Test suites. (Anything in the Lib/test directory or test subdirectories of packages.)
Backward compatibility rules do not apply to any module or API that is explicitly documented as Provisional per PEP 411.

Basic policy for backwards compatibility

In general, incompatibilities should have a large benefit to breakage ratio, and the incompatibility should be easy to resolve in affected code. For example, adding an stdlib module with the same name as a third party package is generally not acceptable. Adding a method or attribute that conflicts with 3rd party code through inheritance, however, is likely reasonable.
Unless it is going through the deprecation process below, the behavior of an API must not change in an incompatible fashion between any two consecutive releases. Python's yearly release process (PEP 602) means that the deprecation period must last at least two years.
Similarly a feature cannot be removed without notice between any two consecutive releases.
For changes that are unable to raise a deprecation warning, consult with the steering council.
The steering council may grant exceptions to this policy. In particular, they may shorten the required deprecation period for a feature. Exceptions are only granted for extreme situations such as dangerously broken or insecure features or features no one could reasonably be depending on (e.g., support for completely obsolete platforms).

Soft Deprecation

A soft deprecation can be used when using an API which should no longer be used to write new code, but it remains safe to continue using it in existing code. The API remains documented and tested, but will not be developed further (no enhancement).

The main difference between a "soft" and a (regular) "hard" deprecation is that the soft deprecation does not imply scheduling the removal of the deprecated API.

Another difference is that a soft deprecation does not issue a warning: it's only mentioned in the documentation, whereas usually a "hard" deprecation issues a DeprecationWarning warning at runtime. The documentation of a soft deprecation should explain why the API should be avoided, and if possible propose a replacement.

If the decision is made to deprecate (in the regular sense) a feature that is currently soft deprecated, the deprecation must follow the Backwards Compatibility Rules (i.e., there is no exception because the feature is already soft deprecated).

Making Incompatible Changes

Making an incompatible change is a gradual process performed over several releases:

Discuss the change. Depending on the degree of incompatibility, this could be on the bug tracker, python-dev, python-list, or the appropriate SIG. A PEP or similar document may be written. Hopefully users of the affected API will pipe up to comment.
Add a warning to the current main branch. If behavior is changing, the API may gain a new function or method to perform the new behavior; old usage should raise the warning. If an API is being removed, simply warn whenever it is entered. DeprecationWarning is the usual warning category to use, but PendingDeprecationWarning may be used in special cases where the old and new versions of the API will coexist for many releases [2]. The warning message should include the release the incompatibility is expected to become the default and a link to an issue that users can post feedback to. When feasible, also change typeshed to add the @deprecated decorator (see PEP 702) to the deprecated API, so that users of static type checkers have another way to learn about the deprecation.

For C API, a compiler warning generated by the Py_DEPRECATED macro is also acceptable.
Wait for the warning to appear in at least two minor Python versions of the same major version, or one minor version in an older major version (e.g., for a warning in Python 3.10.0, you either wait until at least Python 3.12 or Python 4.0 to make the change). It is preferred, though, to wait 5 years before removal (e.g., warn starting in Python 3.10, removal in 3.15; this happens to coincide with the current lifetime of a minor release of Python).
- If the expected maintenance overhead and security risk of the deprecated behavior is small (e.g. an old function is reimplemented in terms of a new, more general one), it can stay indefinitely (or until the situation changes).
- If the deprecated feature is replaced by a new one, it should generally be removed only after the last Python version without the new feature reaches end of support.
See if there's any feedback. Users not involved in the original discussions may comment now after seeing the warning. Perhaps reconsider.
The behavior change or feature removal may now be made default or permanent having reached the declared version. Remove the old version and warning.
If a warning cannot be provided to users, consult with the steering council.

Changelog

2025-Jan-27: Updated to prefer a 5-year deprecation period before removal.
2023-Nov-14: Added @deprecated decorator per PEP 702.
2023-Jul-03: Added the Soft Deprecation section, as discussed in https://discuss.python.org/t/27957.
2023-Jun-26: Multiple smaller updates and clarifications, discussed in https://discuss.python.org/t/22042.
2022-Apr-04: Added explicit notes to ask the Steering Council in several exceptional cases.
2021-Apr-16: Clarified how long a warning must be emitted before a change can be made.
2020-Jul-20: Initial accepted version.

References

[1]	TIOBE Programming Community Index https://www.tiobe.com/tiobe-index/

[2]	The warnings module http://docs.python.org/library/warnings.html

Copyright

This document has been placed in the public domain.

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