Python Enhancement Proposals

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• PEP 687

PEP 687 Isolating modules in the standard library

Author:

Erlend Egeberg Aasland <erlend at python.org>, Petr Viktorin <encukou at gmail.com>

Discussions-To:

Discourse thread

Status:

Final

Type:

Standards Track

Requires:

489, 573, 630

Created:

04-Apr-2022

Python-Version:

3.12

Post-History:

04-Apr-2022, 11-Apr-2022

Resolution:

Discourse message

• Abstract
• Note on Backdating
• Motivation & Rationale
• Specification
  • Conversion to heap types
  • Process
    • Part 1: Preparation
    • Part 2: Implementation
• Backwards Compatibility
• Security Implications
• How to Teach This
• Reference Implementation
• Copyright

Abstract

Extensions in the standard library will be converted to multi-phase initialization (PEP 489) and where possible, all state will be stored on module objects rather than in process-global variables.

Note on Backdating

Much of this proposal has already been implemented. We submit this PEP to explain the changes, seek consensus on whether they are good, propose the remaining changes, and set best practices for new modules.

Motivation & Rationale

The informational PEP 630 describes the background, motivation, rationale, implications and implementation notes of the proposed changes as they apply generally to any extension module (not just the standard library).

It is an integral part of this proposal. Read it first.

This PEP discusses specifics of the standard library.

Specification

The body of PEP 630 will be converted to a HOWTO in the Python documentation, and that PEP will be retired (marked Final).

All extension modules in the standard library will be converted to multi-phase initialization introduced in PEP 489.

All stdlib extension modules will be isolated. That is:

• Types, functions and other objects defined by the module will either be immutable, or not shared with other module instances.
• State specific to the module will not be shared with other module instances, unless it represents global state.

  For example, _csv.field_size_limit will get/set a module-specific number. On the other hand, functions like readline.get_history_item or os.getpid will continue to work with state that is process-global (external to the module, and possibly shared across other libraries, including non-Python ones).

Conversion to heap types

Static types that do not need module state access, and have no other reason to be converted, should stay static.

Types whose methods need access to their module instance will be converted to heap types following PEP 630, with the following considerations:

• All standard library types that used to be static types should remain immutable. Heap types must be defined with the Py_TPFLAGS_IMMUTABLE_TYPE flag to retain immutability. See bpo-43908.

  Tests should ensure TypeError is raised when trying to create a new attribute of an immutable type.

• A static type with tp_new = NULL does not have a public constructor, but heap types inherit the constructor from the base class. Make sure types that previously were impossible to instantiate retain that feature; use Py_TPFLAGS_DISALLOW_INSTANTIATION. Add tests using test.support.check_disallow_instantiation(). See bpo-43916.
• Converted heap types may unintentionally become serializable (pickle-able). Test that calling pickle.dumps has the same result before and after conversion, and if the test fails, add a __reduce__ method that raises TypeError. See PR-21002 for an example.

These issues will be added to the Devguide to help any future conversions.

If another kind of issue is found, the module in question should be unchanged until a solution is found and added to the Devguide, and already converted modules are checked and fixed.

Process

The following process should be added to the Devguide, and remain until all modules are converted. Any new findings should be documented there or in the general HOWTO.

Part 1: Preparation

1. Open a discussion, either on the bug tracker or on Discourse. Involve the module maintainer and/or code owner. Explain the reason and rationale for the changes.
2. Identify global state performance bottlenecks. Create a proof-of-concept implementation, and measure the performance impact. pyperf is a good tool for benchmarking.
3. Create an implementation plan. For small modules with few types, a single PR may do the job. For larger modules with lots of types, and possibly also external library callbacks, multiple PRs will be needed.

Part 2: Implementation

Note: this is a suggested implementation plan for a complex module, based on lessons learned with other modules. Feel free to simplify it for smaller modules.

1. Add Argument Clinic where possible; it enables you to easily use the defining class to fetch module state from type methods.
2. Prepare for module state; establish a module state struct, add an instance as a static global variable, and create helper stubs for fetching the module state.
3. Add relevant global variables to the module state struct, and modify code that accesses the global state to use the module state helpers instead. This step may be broken into several PRs.
4. Where necessary, convert static types to heap types.
5. Convert the global module state struct to true module state.
6. Implement multi-phase initialisation.

Steps 4 through 6 should preferably land in a single alpha development phase.

Backwards Compatibility

Extension modules in the standard library will now be loadable more than once. For example, deleting such a module from sys.modules and re-importing it will result in a fresh module instance, isolated from any previously loaded instances.

This may affect code that expected the previous behavior: globals of extension modules were shallowly copied from the first loaded module.

Security Implications

None known.

How to Teach This

A large part of this proposal is a HOWTO aimed at experienced users, which will be moved to the documentation.

Beginners should not be affected.

Reference Implementation

Most of the changes are now in the main branch, as commits for these issues:

• bpo-40077, Convert static types to heap types: use PyType_FromSpec()
• bpo-46417, Clear static types in Py_Finalize() for embedded Python
• bpo-1635741, Py_Finalize() doesnt clear all Python objects at exit

As an example, changes and fix-ups done in the _csv module are:

• GH-23224, Remove static state from the _csv module
• GH-26008, Allow subclassing of csv.Error
• GH-26074, Add GC support to _csv heap types
• GH-26351, Make heap types converted during 3.10 alpha immutable

Copyright

This document is placed in the public domain or under the CC0-1.0-Universal license, whichever is more permissive.

Contents

• Abstract
• Note on Backdating
• Motivation & Rationale
• Specification
  • Conversion to heap types
  • Process
    • Part 1: Preparation
    • Part 2: Implementation
• Backwards Compatibility
• Security Implications
• How to Teach This
• Reference Implementation
• Copyright

Source: https://github.com/python/peps/blob/main/peps/pep-0687.rst

Last modified: 2026-06-15 17:28:27 UTC