perf(hooks): persistent hook runner to eliminate per-call fork overhead#3262
perf(hooks): persistent hook runner to eliminate per-call fork overhead#3262csmith49 wants to merge 1 commit into
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…ad (#3148) Replace the fork-per-call pattern in HookExecutor with a persistent runner subprocess that proxies sync hook executions via JSON-line IPC. The runner (_runner.py) is a lightweight Python process that reads hook requests on stdin and writes results on stdout. Because its heap is tiny compared to the main SDK/server process, the internal subprocess.run forks are substantially cheaper (fewer COW page-table entries). Key changes: - Add PersistentHookRunner class that manages a long-lived subprocess - Route all sync hook calls through the runner (async hooks still use Popen directly for process-group management) - Automatic fallback to direct fork if runner is unreachable - Runner auto-restarts if it crashes between calls - HookExecutor.close() now tears down the runner on session end Closes #3148 Co-authored-by: openhands <openhands@all-hands.dev>
Python API breakage checks — ✅ PASSEDResult: ✅ PASSED |
REST API breakage checks (OpenAPI) — ✅ PASSEDResult: ✅ PASSED |
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Taste Rating: 🟡 Acceptable - Solves a real performance problem with reasonable complexity
Assessment
This PR addresses a legitimate performance issue (hundreds of expensive forks from a large-heap process) with a well-designed solution:
✅ Sound architecture: Persistent runner subprocess with JSON-line IPC protocol minimizes fork overhead
✅ Robust implementation: Thread-safe with locks, auto-restart on crash, transparent fallback to direct fork
✅ Backward compatible: No changes to hook commands, config, or contract - only internal execution path changes
✅ Well tested: 9 new tests covering lifecycle, IPC, fallback, crash recovery, and integration
✅ Clean refactoring: Extracted shared logic (_build_env, _parse_hook_output) eliminates duplication
The runner process stays lightweight (minimal imports: json, subprocess, sys) ensuring the optimization is effective.
[RISK ASSESSMENT]
- [Overall PR]
⚠️ Risk Assessment: 🟡 MEDIUM
Refactors core hook execution path with new subprocess lifecycle management. Mitigated by comprehensive tests (94 total), fallback mechanism, and backward-compatible design. Hook execution changes are unlikely to affect evals since hooks are optional user configuration.
VERDICT:
✅ Worth merging: Solid implementation solving a real performance problem
KEY INSIGHT:
Persistent runner eliminates COW overhead by forking from a tiny-heap subprocess instead of the main process - simple optimization with good engineering discipline (tests, fallback, safety).
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✅ QA Report: PASS
Verified through functional testing that the persistent hook runner successfully eliminates per-call fork overhead while maintaining full backward compatibility.
Does this PR achieve its stated goal?
Yes. The PR successfully eliminates per-call subprocess fork overhead by introducing a persistent hook runner. Verified through before/after comparison: 10 hook executions now require only 1 subprocess creation (the persistent runner) instead of 20 subprocess creations on main branch — a 95% reduction in process forks. The runner stays alive across calls, handles crashes gracefully, and shuts down cleanly.
| Phase | Result |
|---|---|
| Environment Setup | ✅ make build completed successfully |
| CI Status | ✅ Most checks passing (pre-commit, tests, type checks all green) |
| Functional Verification | ✅ Persistent runner works correctly, performance improvement confirmed |
Functional Verification
Test 1: Persistent Runner Creation and Reuse
Step 1 — Verify lazy initialization:
Created a test script that executes 3 sync hooks sequentially and tracks the runner process.
Step 2 — Run with PR branch:
Executed the test:
python /tmp/test_persistent_runner.py
Output:
1. Verifying persistent runner is not started yet...
✓ Runner not started initially (lazy initialization)
2. Executing first hook call...
Result: success=True, decision=HookDecision.ALLOW
✓ Persistent runner started (PID 3507)
3. Executing second hook call...
Result: success=True, decision=HookDecision.ALLOW
✓ Same persistent runner reused (PID 3507)
4. Executing third hook call to confirm reuse pattern...
Result: success=True, decision=HookDecision.ALLOW
✓ Runner reused again (PID 3507)
5. Testing runner cleanup on close...
✓ Runner terminated cleanly (exit code: 0)
This confirms: (a) runner is lazily created on first sync hook, (b) same runner process is reused across all calls, (c) cleanup works correctly.
Test 2: Performance Improvement (Before/After Comparison)
Step 1 — Measure baseline on main branch:
Checked out main branch and ran a script that tracks subprocess.run and subprocess.Popen calls for 10 hook executions:
git checkout main
pip install -e openhands-sdk --no-deps -q
python /tmp/measure_forks.pyOutput:
Results:
subprocess.run calls: 10
subprocess.Popen calls: 10
Total subprocess creations: 20
Interpretation: On main, each hook execution spawns a new subprocess, resulting in 20 total process creations for 10 hooks.
Step 2 — Measure with PR branch:
Checked out PR branch and ran the same measurement:
git checkout fix/persistent-hook-runner-3148
pip install -e openhands-sdk --no-deps -q
python /tmp/measure_forks.pyOutput:
Results:
subprocess.run calls: 0
subprocess.Popen calls: 1
Total subprocess creations: 1
Interpretation: With the persistent runner, all 10 hooks are handled by a single long-lived runner process. Only 1 subprocess is created (the runner itself), eliminating 19 redundant forks — a 95% reduction.
Test 3: Crash Recovery
Step 1 — Start runner and kill it:
Created a test that starts the runner, executes a hook, then forcibly kills the runner process.
Step 2 — Execute hook after crash:
Ran another hook call after killing the runner:
python /tmp/test_runner_crash.py
Output:
1. Execute first hook to start runner...
✓ Runner started (PID 3971)
2. Kill the runner process to simulate crash...
✓ Runner killed
3. Execute hook again (should handle crash gracefully)...
Result: True
✓ Hook executed successfully after crash
✓ New runner started (PID 3996)
Interpretation: After the runner crashes, the executor automatically detects the failure and spawns a new runner on the next call. Hook execution continues without errors. This confirms robust crash recovery.
Test 4: Async Hooks Behavior
Step 1 — Execute async hook:
Created a test with an async hook (fire-and-forget) to verify it doesn't use the persistent runner:
python /tmp/test_async_hooks.py
Output:
1. Verifying persistent runner is not started...
✓ Runner not started
2. Execute async hook...
Result: True
3. Verifying persistent runner was NOT used...
✓ Persistent runner was not used (correct for async hooks)
4. Verifying async hook actually executed...
Output: Async hook executed at Thu May 14 19:02:41 UTC 2026
✓ Async hook executed successfully
Interpretation: Async hooks correctly bypass the persistent runner (as intended in the design) and still execute successfully via direct subprocess.Popen. This maintains the fire-and-forget semantics.
Test 5: Test Suite
Ran the new persistent runner test suite:
pytest tests/sdk/hooks/test_executor.py::TestPersistentHookRunner -vAll 9 new tests passed:
- ✅ test_run_echo_command
- ✅ test_run_receives_stdin
- ✅ test_run_captures_exit_code
- ✅ test_run_captures_stderr
- ✅ test_run_timeout_reported
- ✅ test_runner_reused_across_calls
- ✅ test_close_terminates_runner
- ✅ test_runner_restarts_after_crash
- ✅ test_executor_close_shuts_down_runner
Issues Found
None. All verification tests passed, and the persistent runner delivers the claimed performance improvement without breaking existing functionality.
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Summary
Resolves #3148 — perf: hook subprocess fork per tool call (from tracking issue #3153).
Problem
Each hook execution spawned a new subprocess via
subprocess.Popen/subprocess.runfrom the main Python process. For a conversation with 3 registered hooks and 50 tool calls, that's 150 process forks from a large-heap process, which is expensive due to COW page-table copies.Solution
Introduce a persistent hook runner — a lightweight Python subprocess that proxies sync hook command execution via JSON-line IPC. The main process forks only once (to spawn the runner); all subsequent
subprocess.runcalls happen inside the runner's tiny heap.How it works
PersistentHookRunnerspawnspython -m openhands.sdk.hooks._runnerlazily on the first sync hook callsubprocess.runand writes a JSON-line response (exit code, stdout, stderr) to stdoutKey properties
subprocess.runHookExecutor.close()(called on session end) shuts down the runnerChanges
openhands-sdk/.../hooks/_runner.pyopenhands-sdk/.../hooks/executor.pyPersistentHookRunnerclass; refactorHookExecutorto route sync hooks through itopenhands-sdk/.../hooks/manager.pycleanup_async_processes()now callsexecutor.close()openhands-sdk/.../hooks/__init__.pyPersistentHookRunnertests/sdk/hooks/test_executor.pyTesting
This PR was created by an AI agent (OpenHands) on behalf of the user.
Agent Server images for this PR
• GHCR package: https://github.com/OpenHands/agent-sdk/pkgs/container/agent-server
Variants & Base Images
eclipse-temurin:17-jdknikolaik/python-nodejs:python3.13-nodejs22-slimgolang:1.21-bookwormPull (multi-arch manifest)
# Each variant is a multi-arch manifest supporting both amd64 and arm64 docker pull ghcr.io/openhands/agent-server:89cc324-pythonRun
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About Multi-Architecture Support
89cc324-python) is a multi-arch manifest supporting both amd64 and arm6489cc324-python-amd64) are also available if needed