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docs: record resume concurrency guard

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# Resume Run Concurrency Guard Implementation Plan
> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
**Goal:** Prevent two concurrent `resume_run` calls in the same server process from both advancing the same interrupted run from the same checkpoint.
**Architecture:** Add a small process-local keyed async lock helper in `wf_api`, then wrap `WorkflowRunApi.resume_run()` with a critical section keyed by `run_id`. This intentionally protects one long-lived API process; it does not pretend the JSON filesystem store is safe for multi-process/cloud concurrency, which remains a transactional-store follow-up.
**Tech Stack:** Python 3.14, `asyncio.Lock`, pytest, pytest-asyncio, `wf_api`, `wf_artifacts.FileRunStore`.
---
## File Structure
- Create `src/wf_api/run_locks.py`
- Owns one focused helper, `AsyncKeyedLock`, for process-local async critical sections keyed by string ids.
- No dependency on run models or stores.
- Modify `src/wf_api/runs.py`
- Instantiate a resume lock registry on `WorkflowRunApi`.
- Wrap the existing resume implementation in `async with self._resume_locks.lock(run_id)`.
- Add a short comment explaining why the lock lives above `RunStore`.
- Create `tests/wf_api/test_run_locks.py`
- Tests lock serialization for the same key and concurrency for different keys.
- Create `tests/wf_api/test_resume_concurrency.py`
- Seeds an interrupted run directly in `FileRunStore`.
- Uses a fake runtime that blocks inside `resume_workflow_from_plan`.
- Starts two concurrent resumes for the same `run_id`.
- Asserts only the first reaches runtime and the second rejects after the first persists completion.
- Modify `docs/superpowers/specs/2026-06-03-persisted-run-resume-contract.md`
- Mark the process-local guard as the next concrete slice.
- Keep the transactional-store limitation explicit.
- Modify `docs/current_roadmap.md`
- Link this active implementation plan under Priority 2.
---
### Task 1: Add Keyed Async Lock Tests
**Files:**
- Create: `tests/wf_api/test_run_locks.py`
- [ ] **Step 1: Write failing tests for the lock helper**
Create `tests/wf_api/test_run_locks.py`:
```python
from __future__ import annotations
import asyncio
from wf_api.run_locks import AsyncKeyedLock
async def test_async_keyed_lock_serializes_same_key() -> None:
locks = AsyncKeyedLock()
entered: list[str] = []
release_first = asyncio.Event()
async def first() -> None:
async with locks.lock("run_123"):
entered.append("first")
await release_first.wait()
async def second() -> None:
async with locks.lock("run_123"):
entered.append("second")
first_task = asyncio.create_task(first())
await asyncio.sleep(0)
second_task = asyncio.create_task(second())
await asyncio.sleep(0)
assert entered == ["first"]
release_first.set()
await asyncio.gather(first_task, second_task)
assert entered == ["first", "second"]
async def test_async_keyed_lock_allows_different_keys_concurrently() -> None:
locks = AsyncKeyedLock()
entered: list[str] = []
release = asyncio.Event()
async def hold(key: str) -> None:
async with locks.lock(key):
entered.append(key)
await release.wait()
first_task = asyncio.create_task(hold("run_a"))
second_task = asyncio.create_task(hold("run_b"))
await asyncio.sleep(0)
assert entered == ["run_a", "run_b"]
release.set()
await asyncio.gather(first_task, second_task)
```
- [ ] **Step 2: Run tests to verify they fail**
Run:
```bash
uv run pytest tests/wf_api/test_run_locks.py -q
```
Expected: FAIL with `ModuleNotFoundError: No module named 'wf_api.run_locks'`.
---
### Task 2: Implement `AsyncKeyedLock`
**Files:**
- Create: `src/wf_api/run_locks.py`
- [ ] **Step 1: Add the keyed lock helper**
Create `src/wf_api/run_locks.py`:
```python
from __future__ import annotations
import asyncio
from collections.abc import AsyncIterator
from contextlib import asynccontextmanager
from dataclasses import dataclass
@dataclass(slots=True)
class _LockEntry:
lock: asyncio.Lock
users: int = 0
class AsyncKeyedLock:
"""Process-local async critical sections keyed by a stable string id.
This helper intentionally does not provide cross-process locking. Use it for
one API/server process; use a transactional store for multi-worker safety.
"""
def __init__(self) -> None:
self._guard = asyncio.Lock()
self._entries: dict[str, _LockEntry] = {}
@asynccontextmanager
async def lock(self, key: str) -> AsyncIterator[None]:
"""Hold the critical section for `key` until the context exits."""
entry = await self._retain(key)
await entry.lock.acquire()
try:
yield
finally:
entry.lock.release()
await self._release(key, entry)
async def _retain(self, key: str) -> _LockEntry:
async with self._guard:
entry = self._entries.get(key)
if entry is None:
entry = _LockEntry(lock=asyncio.Lock())
self._entries[key] = entry
entry.users += 1
return entry
async def _release(self, key: str, entry: _LockEntry) -> None:
async with self._guard:
entry.users -= 1
if entry.users == 0 and not entry.lock.locked():
self._entries.pop(key, None)
```
- [ ] **Step 2: Run keyed lock tests**
Run:
```bash
uv run pytest tests/wf_api/test_run_locks.py -q
```
Expected: PASS, `2 passed`.
- [ ] **Step 3: Run lint/typecheck on the new helper**
Run:
```bash
uv run ruff check src/wf_api/run_locks.py tests/wf_api/test_run_locks.py
uv run basedpyright --level error src/wf_api/run_locks.py tests/wf_api/test_run_locks.py
```
Expected:
```text
All checks passed!
0 errors, 0 warnings, 0 notes
```
- [ ] **Step 4: Commit the helper**
Run:
```bash
git add src/wf_api/run_locks.py tests/wf_api/test_run_locks.py
git commit -m "feat: add async keyed lock helper"
```
---
### Task 3: Add Same-Run Resume Race Regression Test
**Files:**
- Create: `tests/wf_api/test_resume_concurrency.py`
- [ ] **Step 1: Write the failing resume race test**
Create `tests/wf_api/test_resume_concurrency.py`:
```python
from __future__ import annotations
import asyncio
from pathlib import Path
from typing import Any
import pytest
from wf_api.models import RawWorkflowPlan
from wf_api.operation_context import WorkflowOperationContext
from wf_api.run_lifecycle import create_pinned_environment, persist_stopped_run
from wf_api.runs import WorkflowRunApi
from wf_api.saved_subgraphs import SavedSubgraphTree
from wf_artifacts import (
FileRunStore,
WorkflowArtifact,
WorkflowDeployment,
)
from wf_authoring import NodeSpec
from wf_core import InterruptRequest, RunState, RunStatus
from wf_platform import CapabilityBuckets, CapabilitySource
class DummyEvents:
def record_event(self, event: object) -> None:
pass
def record_workflow_event(
self,
event_type: str,
*,
capability_id: str,
payload: dict[str, Any],
) -> None:
pass
class EmptySpecProvider:
@property
def capability_sources(self) -> dict[str, CapabilitySource]:
return {}
def get_qualified_spec(self, qualified_name: str) -> NodeSpec[Any, Any]:
raise KeyError(f"unknown capability {qualified_name!r}")
class BlockingResumeRuntime:
def __init__(self) -> None:
self.entered = 0
self.first_entered = asyncio.Event()
self.release_first = asyncio.Event()
async def run_workflow_from_plan(
self,
plan: RawWorkflowPlan,
workflow_input: dict[str, Any],
deployment: WorkflowDeployment | None = None,
artifact: WorkflowArtifact | None = None,
saved_subgraph_tree: SavedSubgraphTree | None = None,
) -> RunState:
raise AssertionError("test should not start new workflow runs")
async def resume_workflow_from_plan(
self,
plan: RawWorkflowPlan,
run: RunState,
*,
resume_payload: dict[str, Any],
resume_outcome: str,
deployment: WorkflowDeployment | None = None,
artifact: WorkflowArtifact | None = None,
saved_subgraph_tree: SavedSubgraphTree | None = None,
) -> RunState:
self.entered += 1
self.first_entered.set()
await self.release_first.wait()
return RunState(
workflow_name=plan.name,
status=RunStatus.COMPLETED,
workflow_input=run.workflow_input,
state={"answer": resume_payload["answer"]},
outcome=resume_outcome,
output={"answer": resume_payload["answer"]},
)
def test_resume_run_serializes_same_run_attempts(tmp_path: Path) -> None:
async def scenario() -> None:
store = FileRunStore(tmp_path / "runs")
runtime = BlockingResumeRuntime()
run_id = _seed_interrupted_run(store)
api = WorkflowRunApi(
WorkflowOperationContext(
artifact_store=None,
draft_workspace_store=None,
run_store=store,
events=DummyEvents(),
specs=EmptySpecProvider(),
runtime=runtime,
live_sources=None,
)
)
first = asyncio.create_task(
api.resume_run(run_id=run_id, resume_payload={"answer": "first"})
)
await runtime.first_entered.wait()
second = asyncio.create_task(
api.resume_run(run_id=run_id, resume_payload={"answer": "second"})
)
await asyncio.sleep(0)
assert runtime.entered == 1
runtime.release_first.set()
first_payload = await first
assert first_payload["status"] == "completed"
assert first_payload["output"] == {"answer": "first"}
with pytest.raises(ValueError, match="is not interrupted"):
await second
assert runtime.entered == 1
assert store.get_latest_checkpoint(run_id).sequence == 2
assert len(store.list_checkpoints(run_id)) == 2
asyncio.run(scenario())
def _seed_interrupted_run(store: FileRunStore) -> str:
artifact = _artifact()
deployment = WorkflowDeployment(
id="pause.default",
artifact_id=artifact.id,
artifact_version=artifact.version,
bindings=[],
)
interrupted = RunState(
workflow_name="pause",
status=RunStatus.INTERRUPTED,
workflow_input={"question": "continue?"},
state={},
interrupt=InterruptRequest(
id="interrupt:approval",
frame_id="root",
node_id="approval",
kind="approval",
payload={"question": "continue?"},
),
)
record = persist_stopped_run(
store=store,
environment=create_pinned_environment(
deployment=deployment,
artifact=artifact,
tree=SavedSubgraphTree(artifacts_by_ref={}),
),
run=interrupted,
)
return record.id
def _artifact() -> WorkflowArtifact:
return WorkflowArtifact(
id="pause",
version=1,
title="Pause",
input_schema={"type": "object", "properties": {}},
output_schema={"type": "object", "properties": {}},
outcomes=("ok", "submitted"),
plan={
"name": "pause",
"input_schema": {"type": "object", "properties": {}},
"state_schema": {"type": "object", "properties": {}},
"output_schema": {"type": "object", "properties": {}},
"outcomes": ["ok", "submitted"],
"start": "end_submitted",
"nodes": [
{"id": "end_submitted", "type": "end", "outcome": "submitted"}
],
"edges": [],
},
)
```
- [ ] **Step 2: Run the test to verify the race exists**
Run:
```bash
uv run pytest tests/wf_api/test_resume_concurrency.py -q
```
Expected before wiring the lock: FAIL. The likely failure is:
```text
assert runtime.entered == 1
E assert 2 == 1
```
If the failure appears later as duplicate checkpoint sequence or final output from `"second"`, that is also acceptable. The test must fail because the second concurrent resume reaches runtime or writes from the same starting checkpoint.
---
### Task 4: Wrap `WorkflowRunApi.resume_run` With the Keyed Lock
**Files:**
- Modify: `src/wf_api/runs.py`
- [ ] **Step 1: Import and instantiate the lock helper**
In `src/wf_api/runs.py`, add the import:
```python
from .run_locks import AsyncKeyedLock
```
Change the constructor from:
```python
def __init__(self, context: WorkflowOperationContext) -> None:
self.context = context
self.deployments = WorkflowDeploymentApi(context)
```
to:
```python
def __init__(
self,
context: WorkflowOperationContext,
*,
resume_locks: AsyncKeyedLock | None = None,
) -> None:
self.context = context
self.deployments = WorkflowDeploymentApi(context)
self._resume_locks = resume_locks or AsyncKeyedLock()
```
- [ ] **Step 2: Split the unlocked resume body into a private helper**
Replace the current `resume_run` method with this wrapper plus private method:
```python
async def resume_run(
self,
*,
run_id: str,
resume_payload: dict[str, Any],
resume_outcome: str = "submitted",
trace_range: TraceRangeLike | None = None,
) -> dict[str, Any]:
"""Resume one durable interrupted deployment run."""
# FileRunStore locks individual file writes only. The API layer owns the
# process-local read/execute/write critical section for one run id.
async with self._resume_locks.lock(run_id):
return await self._resume_run_unlocked(
run_id=run_id,
resume_payload=resume_payload,
resume_outcome=resume_outcome,
trace_range=trace_range,
)
async def _resume_run_unlocked(
self,
*,
run_id: str,
resume_payload: dict[str, Any],
resume_outcome: str,
trace_range: TraceRangeLike | None,
) -> dict[str, Any]:
trace_values = _trace_range_values(trace_range)
record, stopped_run = restore_interrupted_run(self._run_store(), run_id)
environment = record.environment
diagnostics = validate_pinned_resume_environment(
record=record,
sources=_available_sources(self.context.specs.capability_sources),
)
if has_blocking_diagnostics(diagnostics):
blocked = mark_resume_blocked(
store=self._run_store(),
record=record,
diagnostics=diagnostics,
)
return _run_payload(
deployment=environment.deployment,
artifact=environment.root_artifact,
status=stopped_run.status.value,
run_id=blocked.id,
resume_readiness=blocked.resume_readiness.value,
interrupt=_interrupt_payload(stopped_run),
outcome=stopped_run.outcome,
error=stopped_run.error,
output=stopped_run.output,
diagnostics=diagnostics,
trace_count=len(stopped_run.trace),
)
plan = raw_plan_from_artifact(environment.root_artifact)
tree = saved_subgraph_tree_from_snapshots(environment.child_artifacts)
run = await self.context.runtime.resume_workflow_from_plan(
plan,
stopped_run,
resume_payload=resume_payload,
resume_outcome=resume_outcome,
deployment=environment.deployment,
artifact=environment.root_artifact,
saved_subgraph_tree=tree,
)
next_record = persist_stopped_run(
store=self._run_store(),
environment=environment,
run=run,
run_id=run_id,
)
return _run_payload(
deployment=environment.deployment,
artifact=environment.root_artifact,
status=run.status.value,
run_id=next_record.id,
resume_readiness=next_record.resume_readiness.value,
interrupt=_interrupt_payload(run),
outcome=run.outcome,
error=run.error,
output=run.output,
trace_count=len(run.trace),
**_trace_slice_fields(run, trace_values),
)
```
The body is the existing implementation moved under `_resume_run_unlocked`; do not change blocked-resume or persistence semantics.
- [ ] **Step 3: Run the resume race test**
Run:
```bash
uv run pytest tests/wf_api/test_resume_concurrency.py -q
```
Expected: PASS, `1 passed`.
- [ ] **Step 4: Run existing run API tests**
Run:
```bash
uv run pytest tests/wf_api/test_run_api.py tests/wf_api/test_resume_concurrency.py tests/wf_api/test_run_locks.py -q
```
Expected: all tests pass.
- [ ] **Step 5: Commit the API wiring**
Run:
```bash
git add src/wf_api/runs.py tests/wf_api/test_resume_concurrency.py
git commit -m "fix: serialize same-run resume attempts"
```
---
### Task 5: Update Durable Resume Docs
**Files:**
- Modify: `docs/superpowers/specs/2026-06-03-persisted-run-resume-contract.md`
- Modify: `docs/current_roadmap.md`
- [ ] **Step 1: Update the resume contract current implementation section**
In `docs/superpowers/specs/2026-06-03-persisted-run-resume-contract.md`, under `### resume_run`, change the current implementation bullets to:
```markdown
Current implementation:
- `WorkflowRunApi.resume_run()` follows this contract for stored interrupted
runs and blocked dependency validation.
- Same-process callers are serialized per `run_id` around the restore,
dependency validation, runtime resume, and checkpoint write sequence.
- `restore_interrupted_run()` rejects non-interrupted statuses.
- `mark_resume_blocked()` updates run summary without writing a checkpoint.
```
- [ ] **Step 2: Update the store contract limitation**
In the same spec, replace the `Current limits:` list under `## Store Contract` with:
```markdown
Current limits:
- `WorkflowRunApi.resume_run()` provides a process-local per-run critical
section for one API/server process.
- `FileRunStore` locks individual file writes only; it does not provide
compare-and-swap or cross-process transactions.
- The file store is appropriate for local/dev/single-process use.
- A multi-worker or cloud deployment still needs SQLite/Postgres or another
transactional store before claiming strong concurrent resume safety.
```
- [ ] **Step 3: Update the gap list**
In the same spec, replace gap item `4. **Resume concurrency guard**` with:
```markdown
4. **Resume concurrency guard**
- Implemented for same-process API callers through a per-`run_id` async
critical section in `WorkflowRunApi.resume_run()`.
- Cross-process protection remains part of the transactional backend gap.
```
- [ ] **Step 4: Update the roadmap**
In `docs/current_roadmap.md`, under `## Priority 2: Durable Run/Resume Hardening`, replace:
```markdown
- Add same-run concurrency protection around `resume_run`.
- Clarify store-level locking/transaction expectations for filesystem stores.
```
with:
```markdown
- Completed: same-process `resume_run` calls are serialized per run id.
Implementation:
[`resume run concurrency guard`](historical/superpowers/plans/2026-06-09-resume-run-concurrency-guard.md).
- Clarify store-level locking/transaction expectations for future filesystem
and transactional stores.
```
- [ ] **Step 5: Move this plan to historical after implementation**
After all code and docs pass verification, move this plan:
```bash
git mv docs/superpowers/plans/2026-06-09-resume-run-concurrency-guard.md docs/historical/superpowers/plans/2026-06-09-resume-run-concurrency-guard.md
```
Then commit docs:
```bash
git add docs/current_roadmap.md docs/superpowers/specs/2026-06-03-persisted-run-resume-contract.md docs/historical/superpowers/plans/2026-06-09-resume-run-concurrency-guard.md
git commit -m "docs: record resume concurrency guard"
```
---
### Task 6: Final Verification
**Files:**
- No new files.
- [ ] **Step 1: Run focused tests**
Run:
```bash
uv run pytest tests/wf_api/test_run_locks.py tests/wf_api/test_resume_concurrency.py tests/wf_api/test_run_api.py tests/wf_mcp/test_saved_subgraphs.py tests/wf_transport_rpc_http/test_mcp_backed_server_rpc.py -q
```
Expected: all selected tests pass.
- [ ] **Step 2: Run broader API tests**
Run:
```bash
uv run pytest tests/wf_api -q
```
Expected: all `wf_api` tests pass.
- [ ] **Step 3: Run lint and typecheck**
Run:
```bash
uv run ruff check src/wf_api tests/wf_api
uv run ruff format --check src/wf_api tests/wf_api
uv run basedpyright --level error src/wf_api tests/wf_api/test_run_locks.py tests/wf_api/test_resume_concurrency.py tests/wf_api/test_run_api.py
```
Expected:
```text
All checks passed!
0 errors, 0 warnings, 0 notes
```
- [ ] **Step 4: Inspect git status**
Run:
```bash
git status --short
```
Expected: clean working tree after the commits above.
---
## Self-Review
- Spec coverage: The plan implements the roadmap gap "same-run concurrency protection around `resume_run`" and explicitly preserves the store-level transactional limitation.
- Placeholder scan: No `TBD`, vague "handle errors", or unspecified test work remains.
- Type consistency: `AsyncKeyedLock`, `WorkflowRunApi.resume_run`, `RawWorkflowPlan`, `WorkflowOperationContext`, `FileRunStore`, and `SavedSubgraphTree` names match current code.
- Scope control: This plan does not add run listing, checkpoint listing, retries, cloud transactions, or public API shape changes.