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PEP 598 -- Introducing incremental feature releases

PEP:598
Title:Introducing incremental feature releases
Author:Nick Coghlan <ncoghlan at gmail.com>
Discussions-To:https://discuss.python.org/t/pep-596-python-3-9-release-schedule-doubling-the-release-cadence/1828
Status:Draft
Type:Informational
Created:15-Jun-2019
Python-Version:3.9

Abstract

PEP 596 has proposed reducing the feature delivery latency for the Python standard library and CPython reference interpreter by increasing the frequency of CPython feature releases from every 18-24 months to instead occur every 9-12 months.

Adopting such an approach has several significant practical downsides, as a CPython feature release carries certain expectations (most notably, a 5 year maintenance lifecycle, support for parallel installation with the previous feature release, and the possibility of breaking changes to the CPython-specific ABI, requiring recompilation of all extension modules) that mean faster feature releases would significantly increase the burden of maintaining 3rd party Python libraries and applications across all actively supported CPython releases.

It's also arguable whether such an approach would actually noticeably reduce the typical feature delivery latency, as the adoption cycle for new feature releases is typically measured in months or years, so more frequent releases may just lead to end users updating to every 3rd or 4th feature release, rather than every 2nd or 3rd feature release (as already happens today).

This PEP presents a competing proposal to instead slow down the frequency of parallel installable feature releases that change the filesystem layout and CPython ABI to a consistent 24 month cycle, but to compensate for this by introducing the notion of build compatible incremental feature releases, and then deferring the full feature freeze of a given feature release series from the initial baseline X.Y.0 release to a subsequent X.Y.Z feature complete release that occurs ~12 months after the initial baseline feature release.

A new feature_complete attribute on the sys.version_info structure will provide a programmatic indicator as to whether or not a release series remains open to further incremental feature releases. Alternate implementations of Python would also be free to clear this flag to indicate that their support for their nominal Python version may still be a work in progress.

The existing cycle and the new cycle would be synchronised on their feature freeze release dates, so the full Python 3.9.x feature freeze would occur in October 2021, 24 months after the Python 3.8.0 feature release, with the initial Python 3.9.0 release taking place in October 2020.

Example Future Release Schedules

Under this proposal, Python 3.9.0a1 would be released in November 2019, shortly after the Python 3.8.0 feature complete release in October 2019.

The 3.9.0b1 release would then follow 6 months later in May 2020, with 3.9.0 itself being released in October 2020.

Assuming micro releases of 3.9.x were to occur quarterly, then the overall release timeline would look like:

  • 2019-11: 3.9.0a1
  • ... additional alpha releases as determined by the release manager
  • 2020-05: 3.9.0b1
  • ... additional beta releases as determined by the release manager
  • 2020-08: 3.9.0bX (final beta release that locks ABI compatibility)
  • 2020-09: 3.9.0rc1
  • ... additional release candidates as determined by the release manager
  • 2020-10: 3.9.0 (BFR - baseline feature release)
  • 2021-01: 3.9.1 (IFR - incremental feature release)
  • 2021-04: 3.9.2 (IFR)
  • 2021-07: 3.9.3 (IFR)
  • 2021-10: 3.9.4 (feature complete release)
  • 2022-01: 3.9.5
  • 2022-04: 3.9.6
  • 2022-07: 3.9.7
  • 2022-10: 3.9.8 (final regular maintenance release)
  • ... additional security fix only releases as needed
  • 2025-10: 3.9.x branch closed

Feature complete release numbers would typically be written without any qualifier (as they are today), while the baseline and incremental feature releases would be expected to have a qualifier appended indicating that they aren't a traditional CPython release (3.9.0 (BFR), 3.9.1 (IFR), etc).

The Python 3.10 release series would start being published the month after the first Python 3.9 feature complete release, in parallel with the final 12 months of routine Python 3.9 maintenance releases:

  • 2021-11: 3.10.0a1
  • ... additional alpha releases as determined by the release manager
  • 2022-05: 3.10.0b1
  • ... additional beta releases as determined by the release manager
  • 2022-08: 3.10.0bX (final beta release that locks ABI compatibility)
  • 2022-09: 3.10.0rc1
  • ... additional release candidates as determined by the release manager
  • 2022-10: 3.10.0 (BFR)
  • 2023-01: 3.10.1 (IFR)
  • 2023-04: 3.10.2 (IFR)
  • 2023-07: 3.10.3 (IFR)
  • 2023-10: 3.10.4
  • 2024-01: 3.10.5
  • 2024-04: 3.10.6
  • 2024-07: 3.10.7
  • 2024-10: 3.10.8 (final regular maintenance release)
  • ... additional security fix only releases as needed
  • 2027-10: 3.10.x branch closed

In this model, there are always two or three active branches:

  • 2019-04 -> 2019-10: 3.9.0 pre-alpha, 3.8.0 pre-release, 3.7.x maintenance
  • 2019-10 -> 2020-05: 3.9.0 pre-beta, 3.8.x maintenance
  • 2020-05 -> 2020-10: 3.10.0 pre-alpha, 3.9.0 pre-release, 3.8.x maintenance
  • 2020-10 -> 2021-10: 3.10.0 pre-alpha, 3.9.x feature releases, 3.8.x maintenance
  • 2021-10 -> 2022-05: 3.10.0 pre-beta, 3.9.x maintenance
  • 2022-05 -> 2022-10: 3.11.0 pre-alpha, 3.10.0 pre-release, 3.9.x maintenance
  • 2022-10 -> 2023-10: 3.11.0 pre-alpha, 3.10.x feature releases, 3.9.x maintenance
  • 2023-10 -> 2024-05: 3.11.0 pre-beta, 3.10.x maintenance
  • 2024-05 -> 2024-10: 3.12.0 pre-alpha, 3.11.0 pre-release, 3.10.x maintenance
  • ... etc

(Pre-alpha and pre-beta development occurs on the main git branch, all other development occurs on a release specific branch with changes typically backported from the main git branch)

TODO: this really needs a diagram to help explain it, so I'll add a picture once I have one to add.

This is quite similar to the status quo, but with a more consistent cadence, alternating between baseline feature release years (2020, 2022, etc) that focus on the alpha and beta cycle for a new baseline feature release (while continuing to publish maintenance releases for the previous feature release series), and feature complete release years (2021, 2023, etc), that focus on making smaller improvements to the current feature release series (while making plans for the next feature release series the following year).

Proposal

Excluding alpha and beta releases, CPython currently has 3 different kinds of release increment:

  • Feature release (i.e. X.Y.0 releases)
  • Maintenance release (X.Y.Z releases within ~2 years of X.Y.0)
  • Source-only security release (subsequent X.Y.Z releases)

Feature freeze takes place at the time of the X.Y.0b1 release. Build compatibility freeze now takes place at the time of the last beta release (providing time for projects to upload wheel archives to PyPI prior to the first release candidate).

This then creates the following periods in the lifecycle of a release series:

  • Pre-beta (release series is the CPython development branch)
  • Beta (release enters maintenance mode, ABI compatibility mostly locked)
  • Maintenance (ABI locked, only bug fixes & docs enhancements accepted)
  • Security fix only (no further binary releases, only security fixes accepted)
  • End of life (no further releases of any kind)

The proposal in this PEP is that the "Feature release" category be split up into three different kinds of feature release:

  • Baseline feature release (X.Y.0 releases)
  • Incremental feature release (any X.Y.Z releases published between a baseline feature release and the corresponding feature complete release)
  • Feature complete release (a specific X.Y.Z release ~1 year after X.Y.0)
  • Maintenance release (X.Y.Z releases within ~1 years of the feature complete release)
  • Source-only security release (subsequent X.Y.Z releases)

This would then introduce a new "Feature releases" phase in the release series lifecycle:

  • Pre-beta (release series is the CPython development branch)
  • Beta (release enters feature additions mode, ABI compatibility not yet locked)
  • Feature releases (ABI locked, backwards compatible API additions accepted)
  • Maintenance (ABI locked, only bug fixes & docs enhancements accepted)
  • Security fix only (no further binary releases, only security fixes accepted)
  • End of life (no further releases of any kind)

The pre-release beta period would be relaxed to use the incremental feature release policy for changes, rather than the stricter maintenance release policy.

For governance purposes, baseline feature releases are the only releases that would qualify as a "feature release" in the PEP 13 sense (incremental feature releases wouldn't count).

Baseline feature releases and feature release series

Baseline feature releases are essentially just the existing feature releases, given a new name to help distinguish them from the new incremental feature releases, and also to help indicate that unlike their predecessors, they are no longer considered feature complete at release.

Baseline feature releases would continue to define a new feature release series, locking in the following language, build, and installation compatibility constraints for the remainder of that series:

  • Python language grammar
  • ast module AST format
  • CPython interpreter opcode format
  • pyc file magic number and filename compatibility tags
  • extension module filename compatibility tags
  • wheel archive compatibility tags
  • default package and module import directories
  • default installation filename and directories

Baseline feature releases would also continue to be the only releases where:

  • new deprecations, pending deprecations, and other warnings can be introduced
  • existing pending deprecations can be converted to full deprecations
  • existing warnings can be converted to errors
  • other changes requiring "Porting to Python X.Y" entries in the What's New document can be introduced

Key characteristics of a feature release series:

  • an installation within one feature release series does not conflict with installations of other feature release series (i.e. they can be installed in parallel)
  • an installation within a feature release series can be updated to a later micro release within the same series without requiring reinstallation or any other changes to previously installed components

Key characteristics of a baseline feature release:

  • in a baseline feature release, sys.version_info.feature_complete == False
  • in a baseline feature release, sys.version_info.micro == 0
  • baseline feature releases may contain higher risk changes to the language and interpreter, such as grammar modifications, major refactoring of interpreter and standard library internals, or potentially invasive feature additions that carry a risk of unintended side effects on other existing functionality
  • features introduced in a baseline feature release are the only features permitted to rely on sys.version_info as their sole runtime indicator of the feature's availability

Key expectations around feature release series and baseline feature releases:

  • most public projects will only actively test against the most recent micro release within a release series
  • many (most?) public projects will only add a new release series to their test matrix after the initial baseline feature release has already been published, which can make it difficult to resolve issues that require providing new flags or APIs to explicitly opt-in to old behaviour after a default behaviour changed
  • private projects with known target environments will test against whichever micro release version they're actually using
  • most private projects will also only consider migrating to a new release series after the initial baseline feature release has already been published, again posing a problem if the resolution of their problems requires an API addition

The key motivation of the proposal in this PEP is that the public and private project behaviours described above aren't new expectations: they're descriptions of the way CPython release series are already handled by the wider community today. As such, the PEP represents an attempt to adjust our release policies and processes to better match the way the wider community already handles them, rather than changing our processes in a way that then means the wider community needs to adjust to us rather than the other way around.

Incremental feature releases

Incremental feature releases are the key new process addition being proposed by this PEP. They are subject to the same strict runtime compatibility requirements as the existing maintenance releases, but would have the following more relaxed policies around API additions and enhancements:

  • new public APIs can be added to any standard library module (including builtins)
  • subject to the feature detection requirement below, new optional arguments can be added to existing APIs (including builtins)
  • new public APIs can be added to the stable C ABI (with appropriate version guards)
  • new public APIs can be added to the CPython C API
  • with the approval of the release manager, backwards compatible reliability improvements can be made to existing APIs and syntactic constructs
  • with the approval of the release manager, performance improvements can be incorporated for existing APIs and syntactic constructs

The intent of this change in policy is to allow usability improvements for new (and existing!) language features to be delivered in a more timely fashion, rather than requiring users to incur the inherent delay and costs of waiting for and then upgrading to the next feature release series.

Key characteristics of an incremental feature release:

  • in an incremental feature release, sys.version_info.feature_complete == False
  • in an incremental feature release, sys.version_info.micro != 0
  • all API additions made in an incremental feature release must support efficient runtime feature detection that doesn't rely on either sys.version_info or runtime code object introspection. In most cases, a simple hasattr check on the affected module will serve this purpose, but when it doesn't, an alternative approach will need to be implemented as part of the feature addition. Prior art in this area includes the pickle.HIGHEST_PROTOCOL attribute, the hashlib.algorithms_available set, and the various os.supports_* sets that the os module already offers for platform dependent capability detection

Key expectations around incremental feature releases:

  • "don't break existing installations on upgrade" remains a key requirement for all micro releases, even with the more permissive change inclusion policy
  • more intrusive changes should still be deferred to the next baseline feature release
  • public Python projects that start relying on features added in an incremental feature release should set their Python-Requires metadata appropriately (projects already do this when necessary - e.g. aiohttp specifically requires 3.5.3 or later due to an issue with asyncio.get_event_loop() in earlier versions)

Some standard library modules may also impose their own restrictions on acceptable changes in incremental feature releases (for example, new hash algorithms should only ever be added to hashlib.algorithms_guaranteed in a baseline feature release - incremental feature releases would only be permitted to add algorithms to hashlib.algorithms_available)

Feature complete release and subsequent maintenance releases

The feature complete release for a given feature release series would be developed under the normal policy for an incremental feature release, but would have one distinguishing feature:

  • in a feature complete release, sys.version_info.feature_complete == True

Any subsequent maintenance and security fix only releases would also have that flag set, and may informally be referred to as "feature complete releases". For release series definition purposes though, the feature complete release is the first one that sets that flag to "True".

Proposed policy adjustment for provisional APIs

To help improve consistency in management of provisional APIs, this PEP proposes that provisional APIs be subject to regular backwards compatibility requirements following the feature complete release for a given release series.

Other aspects of managing provisional APIs would remain as they are today, so as long as an API remains in the provisional state, regular backwards compatibility requirements would not apply to that API in baseline and incremental feature releases.

This policy is expected to provide increased clarity to end users (as even provisional APIs will become stable for that release series in the feature complete release), with minimal practical downsides for standard library maintainers, based on the following analysis of documented API additions and changes in micro releases of CPython since 3.0.0:

  • 21 3.x.1 version added/changed notes
  • 30 3.x.2 version added/changed notes
  • 18 3.x.3 version added/changed notes
  • 11 3.x.4 version added/changed notes
  • 1 3.x.5 version added/changed notes
  • 0 3.x.6+ version added/changed notes

When post-baseline-release changes need to be made, the majority of them occur within the first two maintenance releases, which have always occurred within 12 months of the baseline release.

(Note: these counts are not solely for provisional APIs - they cover all APIs where semantic changes were made after the baseline release that were considered necessary to cover in the documentation. To avoid double counting changes, the numbers exclude any change markers from the What's New section)

Motivation

The motivation for change in this PEP is essentially the same as the motivation for change in PEP 596: the current 18-24 month gap between feature releases has a lot of undesirable consequences, especially for the standard library (see PEP 596 for further articulation of the details).

This PEP's concern with the specific proposal in PEP 596 is that it doubles the number of actively supported Python branches, increasing the complexity of compatibility testing matrices for the entire Python community, increasing the number of binary Python wheels to be uploaded to PyPI when not using the stable ABI, and just generally having a high chance of inflicting a relatively high level of additional cost across the entire Python ecosystem.

The view taken in this PEP is that there's an alternative approach that provides most of the benefits of a faster feature release without actually incurring the associated costs: we can split the current X.Y.0 "feature freeze" into two parts, such that the baseline X.Y.0 release only imposes a "runtime compatibility freeze", and the full standard library feature freeze is deferred until later in the release series lifecycle.

Caveats and Limitations

This proposal does NOT retroactively apply to Python 3.8 - it is being proposed for Python 3.9 and later releases only.

Actual release dates may be adjusted up to a month earlier or later at the discretion of the release manager, based on release team availability, and the timing of other events (e.g. PyCon US, or the annual core development sprints). However, part of the goal of this proposal is to provide a consistent annual cadence for both contributors and end users, so adjustments ideally would be rare.

This PEP does not dictate a specific cadence for micro releases within a release series - it just specifies the rough timelines for transitions between the release series lifecycle phases (pre-alpha, alpha, beta, feature releases, bug fixes, security fixes). The number of micro releases within each phase is determined by the release manager for that series based on how frequently they and the rest of the release team for that series are prepared to undertake the associated work.

However, for the sake of the example timelines, the PEP assumes quarterly micro releases (the cadence used for Python 3.6 and 3.7, splitting the difference between the twice yearly cadence used for some historical release series, and the monthly cadence planned for Python 3.8 and 3.9).

Design Discussion

Why this proposal over simply doing more frequent baseline feature releases?

The filesystem layout changes and other inherently incompatible changes involved in a baseline feature release create additional work for large sections of the wider Python community.

Decoupling those layout changes from the Python version numbering scheme is also something that would in and of itself involve making backwards incompatible changes, as well as adjusting community expectations around which versions will install over the top of each other, and which can be installed in parallel on a single system.

We also don't have a straightforward means to communicate to the community variations in support periods like "Only support Python version X.Y until X.Y+1 is out, but support X.Z until X.Z+2 is out".

So this PEP takes as its starting assumption that the vast majority of Python users simply shouldn't need to care that we're changing our release policy, and the only folks that should be affected are those that are eagerly waiting for standard library improvements, and other backwards compatible interpreter enhancements, and those that need to manage mission critical applications in complex deployment environments.

Implications for Python library development

Many Python libraries (both open source and proprietary) currently adopt the practice of testing solely against the latest micro release within each feature release series that the project still supports.

The design assumption in this PEP is that this practice will continue to be followed during the feature release phase of a release series, with the expectation being that anyone choosing to adopt a new release series before it is feature complete will closely track the incremental feature releases.

Libraries that support a previous feature release series are unlikely to adopt features added in an incremental feature release, and if they do adopt such a feature, then any associated fallback compatibility strategies should be implemented in such a way that they're also effective on the earlier releases in that release series.

Implications for the proposed Scientific Python ecosystem support period

Based on discussions at SciPy 2019, a NEP is currently being drafted [2] to define a common convention across the Scientific Python ecosystem for dropping support for older Python versions.

While the exact formulation of that policy is still being discussed, the initial proposal was very simple: support any Python feature release published within the last 42 months.

For an 18 month feature release cadence, that works out to always supporting at least the two most recent feature releases, and then dropping support for all X.Y.z releases around 6 months after X.(Y+2).0 is released. This means there is a 6 month period roughly every other year where the three most recent feature releases are supported.

For a 12 month release cadence, it would work out to always supporting at least the three most recent feature releases, and then dropping support for all X.Y.z releases around 6 months after X.(Y+3).0 is released. This means that for half of each year, the four most recent feature releases would be supported.

For a 24 month release cadence, a 42 month support cycle works out to always supporting at least the most recent feature release, and then dropping support for all X.Y.z feature releases around 18 months after X.(Y+1).0 is released. This means there is a 6 month period every other year where only one feature release is supported (and that period overlaps with the pre-release testing period for the X.(Y+2).0 baseline feature release).

Importantly for the proposal in this PEP, that support period would abide by the recommendation that library developers maintain support for the previous release series until the latest release series has attained feature complete status: dropping support 18 months after the baseline feature release will be roughly equivalent to dropping support 6 months after the feature complete release, without needing to track exactly which release marked the series as feature complete.

Implications for simple deployment environments

For the purposes of this PEP, a "simple" deployment environment is any use case where it is straightforward to ensure that all target environments are updated to a new Python micro version at the same time (or at least in advance of the rollout of new higher level application versions), such that any pre-release testing that occurs need only target a single Python micro version.

The simplest such case would be scripting for personal use, where the testing and target environments are the exact same environment.

Similarly simple environments would be containerised web services, where the same Python container is used in the CI pipeline as is used on deployment, and any application that bundles its own Python runtime, rather than relying on a pre-existing Python deployment on the target system.

For these use cases, this PEP shouldn't have any significant implications - only a single micro version needs to be tested, independently of whether that version is feature complete or not.

Implications for complex deployment environments

For the purposes of this PEP, "complex" deployment environments are use cases which don't meet the "simple deployment" criterion above: new application versions are combined with two or more distinct micro versions within the same release series as part of the deployment process, rather than always targeting exactly one micro version at a time.

If the proposal in this PEP has the desired effect of reducing feature delivery latency, then it can be expected that developers using a release series that is not yet feature complete will actually make use of the new features as they're made available. This then means that testing against a newer incremental feature release becomes an even less valid test of compatibility with the baseline feature release and older incremental feature releases than testing against a newer maintenance release is for older maintenance releases.

One option for handling such cases is to simply prohibit the use of new Python versions until the series has reached "feature complete" status. Such a policy is effectively already adopted by many organisations when it comes to new feature release series, with acceptance into operational environments occurring months or years after the original release. If this policy is adopted, then such organisations could potentially still adopt a new Python version every other year - it would just be based on the availability of the feature complete releases, rather than the baseline feature releases.

A less strict alternative to outright prohibition would be to restrict the use of any release series that is still in its feature release phase to applications where the occasional outage or failed deployment due to a lack of forwards compatibility is considered acceptable.

However, a third variant, which allows selective adoption of new language features where appropriate, while also degrading gracefully enough to be suitable for mission critical applications, would be to institute a policy that applications wishing to target a release series that is not yet feature complete must also support the previous feature release series for compatibility testing purposes.

If this last policy is adopted, then testing against the previous release series becomes the new proxy for testing against the baseline feature release and any older incremental feature releases of the newer release series, without actually needing to install and test against all of them.

Only after the newer release series is feature complete would support for the previous release series be dropped entirely.

In a sufficiently complex environment, the second and third policies could also be combined, with critical applications maintaining compatibility with the previous release series, while newer, more experimental, applications and services would be permitted to target the newer release series directly without any additional safeguards in their testing process.

Depending on demand and interest, there are also further enhancements that could be made to continuous integration pipelines to help ensure compatibility with a chosen minimum version within a release series, without needing to run tests against multiple micro releases. For example, applications could potentially be tested against the latest incremental feature release, but typechecked against the oldest still deployed incremental feature release.

Duration of the feature additions period

This PEP proposes that feature additions be limited to 12 months after the initial baseline feature release.

The primary motivation for that is specifically to sync up with the Ubuntu LTS timing, such that the feature complete release for the Python 3.9.x series gets published in October 2021, ready for inclusion in the Ubuntu 22.04 release. (other LTS Linux distributions like RHEL, SLES, and Debian don't have a fixed publishing cadence, so they can more easily tweak their LTS timing a bit to align with stable versions of their inputs. Canonical deliberately haven't given themselves that flexibility with their own release cycle).

The 12 month feature addition period then arises from splitting the time from the 2019-10 release of Python 3.8.0 and a final Python 3.9.x incremental feature release in 2021-10 evenly between pre-release development and subsequent incremental feature releases.

This is an area where this PEP could adopt part of the proposal in PEP 596, by instead making that split ~9 months of pre-release development, and ~15 months of incremental feature releases:

  • 2019-11: 3.9.0a1
  • ... additional alpha releases as determined by the release manager
  • 2020-03: 3.9.0b1
  • 2020-04: 3.9.0b2
  • 2020-05: 3.9.0b3 (final beta release that locks ABI compatibility)
  • 2020-06: 3.9.0rc1
  • ... additional release candidates as determined by the release manager
  • 2020-07: 3.9.0 (BFR)
  • 2020-10: 3.9.1 (IFR)
  • 2021-01: 3.9.2 (IFR)
  • 2021-04: 3.9.3 (IFR)
  • 2021-07: 3.9.4 (IFR)
  • 2021-10: 3.9.5
  • 2022-01: 3.9.6
  • 2022-04: 3.9.7
  • 2022-07: 3.9.8
  • 2022-10: 3.9.9 (final regular maintenance release)
  • ... additional security fix only releases as needed
  • 2025-10: 3.9.x branch closed

This approach would mean there were still always two or three active branches, it's just that proportionally more time would be spent with a branch in the "feature releases" phase, as compared to the "pre-alpha", "pre-beta", and "pre-release" phases:

  • 2019-04 -> 2019-10: 3.9.0 pre-alpha, 3.8.0 pre-release, 3.7.x maintenance
  • 2019-10 -> 2020-03: 3.9.0 pre-beta, 3.8.x maintenance
  • 2020-03 -> 2020-07: 3.10.0 pre-alpha, 3.9.0 pre-release, 3.8.x maintenance
  • 2020-07 -> 2021-10: 3.10.0 pre-alpha, 3.9.x feature releases, 3.8.x maintenance
  • 2021-10 -> 2022-03: 3.10.0 pre-beta, 3.9.x maintenance
  • 2022-03 -> 2022-07: 3.11.0 pre-alpha, 3.10.0 pre-release, 3.9.x maintenance
  • 2022-07 -> 2023-10: 3.11.0 pre-alpha, 3.10.x feature releases, 3.9.x maintenance
  • 2023-10 -> 2024-03: 3.11.0 pre-beta, 3.10.x maintenance
  • 2024-03 -> 2024-07: 3.12.0 pre-alpha, 3.11.0 pre-release, 3.10.x maintenance
  • ... etc

Duration of the unreleased pre-alpha period

In the baseline proposal in this PEP, the proposed timelines still include periods where we go for 18 months without making a release from the main git branch (e.g. 3.9.0b1 would branch off in 2020-05, and 3.10.0a1 wouldn't be published until 2021-11). They just allow for a wider variety of changes to be backported to the most recent maintenance branch for 12 of those months.

The variant of the proposal that moves the beta branch point earlier in the release series lifecycle would increase that period of no direct releases to 21 months - the only period where releases were made directly from the main branch would be during the relatively short window between the last incremental feature release of the previous release series, and the beta branch point a few months later.

While alternating the annual cadence between "big foundational enhancements" and "targeted low risk API usability improvements" is a deliberate feature of this proposal, it still seems strange to wait that long for feedback in the event that changes are made shortly after the previous release series is branched.

An alternative way of handling this would be to start publishing alpha releases for the next baseline feature release during the feature addition period (similar to the way that PEP 596 proposes to starting publishing Python 3.9.0 alpha releases during the Python 3.8.0 release candidate period).

However, rather than setting specific timelines for that at a policy level, it may make sense to leave that decision to individual release managers, based on the specific changes that are being proposed for the release they're managing.

Why not switch directly to full semantic versioning?

If this were a versioning design document for a new language, it would use semantic versioning: the policies described above for baseline feature releases would be applied to X.0.0 releases, the policies for incremental feature releases would be applied to X.Y.0 releases, and the policies for maintenance releases would be applied to X.Y.Z releases.

The problem for Python specifically is that all the policies and properties for parallel installation support and ABI compatibility definitions are currently associated with the first two fields of the version number, and it has been that way for the better part of thirty years.

As a result, it makes sense to split out the policy question of introducing incremental feature releases in the first place from the technical question of making the version numbering scheme better match the semantics of the different release types.

If the proposal in this PEP were to be accepted by the Steering Council for Python 3.9, then a better time to tackle that technical question would be for the subsequent October 2022 baseline feature release, as there are already inherent compatibility risks associated with the choice of either "Python 4.0" (erroneous checks for the major version being exactly 3 rather than 3 or greater), or "Python 3.10" (code incorrectly assuming that the minor version will always contain exactly one decimal digit) [1].

While the text of this PEP assumes that the release published in 2022 will be 3.10 (as the PEP author personally considers that the more reasonable and most likely choice), there are complex pros and cons on both sides of that decision, and this PEP does arguably add a potential pro in favour of choosing the "Python 4.0" option (with the caveat that we would also need to amend the affected installation layout and compatibility markers to only consider the major version number, rather than both the major and minor version).

If such a version numbering change were to be proposed and accepted, then the example 3.10.x timeline given above would instead become the following 4.x series timeline:

  • 2021-11: 4.0.0a1
  • ... additional alpha releases as determined by the release manager
  • 2022-05: 4.0.0b1
  • ... additional beta releases as determined by the release manager
  • 2022-08: 4.0.0bX (final beta release that locks ABI compatibility)
  • 2022-09: 4.0.0rc1
  • ... additional release candidates as determined by the release manager
  • 2022-10: 4.0.0 (BFR)
  • 2023-01: 4.1.0 (IFR)
  • 2023-04: 4.2.0 (IFR)
  • 2023-07: 4.3.0 (IFR)
  • 2023-10: 4.4.0 (IFR)
  • 2024-01: 4.4.1
  • 2024-04: 4.4.2
  • 2024-07: 4.4.3
  • 2024-10: 4.4.4 (final regular maintenance release)
  • ... additional security fix only releases as needed
  • 2027-10: 4.x branch closed

And the 5 year schedule forecast would look like:

  • 2019-04 -> 2019-10: 3.9.0 pre-alpha, 3.8.0 pre-release, 3.7.x maintenance
  • 2019-10 -> 2020-05: 3.9.0 pre-beta, 3.8.x maintenance
  • 2020-05 -> 2020-10: 4.0.0 pre-alpha, 3.9.0 pre-release, 3.8.x maintenance
  • 2020-10 -> 2021-10: 4.0.0 pre-alpha, 3.9.x feature releases, 3.8.x maintenance
  • 2021-10 -> 2022-05: 4.0.0 pre-beta, 3.9.x maintenance
  • 2022-05 -> 2022-10: 5.0.0 pre-alpha, 4.0.0 pre-release, 3.9.x maintenance
  • 2022-10 -> 2023-10: 5.0.0 pre-alpha, 4.x.0 feature releases, 3.9.x maintenance
  • 2023-10 -> 2024-05: 5.0.0 pre-beta, 4.x.y maintenance
  • 2024-05 -> 2024-10: 6.0.0 pre-alpha, 5.0.0 pre-release, 4.x.y maintenance
  • ... etc

References

[1]Anthony Sottile created a pseudo "Python 3.10" to find and fix such issues (https://github.com/asottile/python3.10)
[2]NEP proposing a standard policy for dropping support of old Python versions (https://github.com/numpy/numpy/pull/14086)
Source: https://github.com/python/peps/blob/master/pep-0598.rst