ai-hats-wt

ai-hats-wt

A hook-agnostic git-worktree engine: create, merge, and discard linked git worktrees with a layered file-locking concurrency model — from a bare git repository, with no configuration.

ai-hats-wt is the worktree core extracted from the ai-hats framework. It has no dependency on ai-hats: everything below runs against a plain git init with no ai-hats.yaml, no composition, and no tracker. Its only runtime dependencies are ai-hats-core (dependency-free filesystem primitives) and filelock.

Install

pip install ai-hats-wt

Requires Python 3.13+.

Quickstart

Drive the full create → merge (or → discard) lifecycle on any git repo:

from pathlib import Path
from ai_hats_wt import WorktreeManager

project = Path("/path/to/a/git/repo")

# A manager for one linked worktree on its own branch.
mgr = WorktreeManager(project, branch_name="feature/x")

wt_path = mgr.create()  # linked worktree checked out on feature/x
mgr.save_state()  # persist state under <project>/.wt

# ... make commits inside wt_path ...

mgr.merge()  # land the branch on the base, remove the worktree
# or:
# mgr.discard()          # throw the worktree + branch away, land nothing

That is the entire happy path. WorktreeManager defaults to the no-op lifecycle and a project-local state directory (<project>/.wt), so a bare consumer needs nothing else. The same flow is exercised end-to-end by the package's test_wt_standalone.py.

Public API

The supported surface is ai_hats_wt.__all__:

The full exception set (WorktreePartialCleanupError, WorktreeRemoveError, OriginalBranchMissingError, WorktreeStateLostError, WorktreeStateIncompleteError, WorktreeBaseBranchError, WorktreeBaseBranchMismatchError, WorktreeMainRepoMidMergeError, WorktreeTeardownAborted, WorktreeLockError) lets a host catch precise failures instead of parsing git stderr. Per-method behaviour is documented on the code — import a symbol and read its docstring; this README is the entry point, not the reference.

Lifecycle hooks (extension-point)

WorktreeManager runs no hooks by default (NOOP_LIFECYCLE). A host can inject behaviour at the create/merge/discard boundaries by passing its own WorktreeLifecycle bundle:

from ai_hats_wt import WorktreeManager, WorktreeLifecycle, LifecycleContext


class MyLifecycle(WorktreeLifecycle):
    def on_created(
        self, ctx: LifecycleContext
    ) -> None: ...  # e.g. seed files into ctx.worktree_path

    def before_teardown(
        self, event: str, ctx: LifecycleContext
    ) -> None: ...  # event is "merge" / "discard" / "cleanup"


mgr = WorktreeManager(project, branch_name="feature/x", lifecycle=MyLifecycle())

This is the seam ai-hats uses to run its own carry/hook layer; a standalone consumer typically leaves the default no-op in place.

Concurrency

Worktree operations are serialized by a layered file-locking model (state locks, git-index-lock retry, ref-lock waits) so that concurrent create / merge calls on the same repo do not corrupt each other. It is on by default; there is nothing to configure.

Dependencies

• ai-hats-core — atomic filesystem I/O.
• filelock — the cross-process lock backend.

Everything else is the Python standard library.

Versioning

SemVer. The public API is ai_hats_wt.__all__; breaking changes to it bump the major version. Submodule internals (anything not in __all__) are not part of the contract.

License

MIT. See the ai-hats repository for the full license and contribution guide.