Files
deer-flow/backend/tests/bench_actor.py
T
greatmengqi 3e17417122 feat: asyncio-native Actor framework with supervision, middleware, and pluggable mailbox
Lightweight actor library built on asyncio primitives (~800 lines):

- Actor base class with lifecycle hooks (on_started/on_stopped/on_restart)
- ActorRef with tell (fire-and-forget) and ask (request-response)
- Supervision: OneForOne/AllForOne strategies with restart limits
- Middleware pipeline for cross-cutting concerns
- Pluggable Mailbox interface (MemoryMailbox default, RedisMailbox optional)
- ReplyRegistry + ReplyChannel: ask() works across any mailbox backend
- System-level thread pool for blocking I/O (run_in_executor)
- Dead letter handling, poison message quarantine, parallel shutdown
- 22 tests + benchmark suite
2026-03-30 23:50:54 +08:00

264 lines
7.3 KiB
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"""Actor framework benchmarks — throughput, latency, concurrency."""
import asyncio
import time
import statistics
from deerflow.actor import Actor, ActorSystem, Middleware
class NoopActor(Actor):
async def on_receive(self, message):
return message
class CounterActor(Actor):
async def on_started(self):
self.count = 0
async def on_receive(self, message):
self.count += 1
return self.count
class ChainActor(Actor):
"""Forwards message to next actor in chain."""
next_ref = None
async def on_receive(self, message):
if self.next_ref is not None:
return await self.next_ref.ask(message)
return message
class ComputeActor(Actor):
"""Simulates CPU work via thread pool."""
async def on_receive(self, message):
def fib(n):
a, b = 0, 1
for _ in range(n):
a, b = b, a + b
return a
return await self.context.run_in_executor(fib, message)
class CountMiddleware(Middleware):
def __init__(self):
self.count = 0
async def on_receive(self, ctx, message, next_fn):
self.count += 1
return await next_fn(ctx, message)
def fmt(n):
if n >= 1_000_000:
return f"{n/1_000_000:.1f}M"
if n >= 1_000:
return f"{n/1_000:.0f}K"
return str(n)
async def bench_tell_throughput(n=100_000):
"""Measure tell (fire-and-forget) throughput."""
system = ActorSystem("bench")
ref = await system.spawn(CounterActor, "counter", mailbox_size=n + 10)
start = time.perf_counter()
for _ in range(n):
await ref.tell("inc")
# Wait for all messages to be processed
count = await ref.ask("get", timeout=30.0)
elapsed = time.perf_counter() - start
await system.shutdown()
rate = n / elapsed
print(f" tell throughput: {fmt(n)} msgs in {elapsed:.2f}s = {fmt(int(rate))}/s")
async def bench_ask_throughput(n=50_000):
"""Measure ask (request-response) throughput."""
system = ActorSystem("bench")
ref = await system.spawn(NoopActor, "echo")
start = time.perf_counter()
for _ in range(n):
await ref.ask("ping")
elapsed = time.perf_counter() - start
await system.shutdown()
rate = n / elapsed
print(f" ask throughput: {fmt(n)} msgs in {elapsed:.2f}s = {fmt(int(rate))}/s")
async def bench_ask_latency(n=10_000):
"""Measure ask round-trip latency percentiles."""
system = ActorSystem("bench")
ref = await system.spawn(NoopActor, "echo")
# Warmup
for _ in range(100):
await ref.ask("warmup")
latencies = []
for _ in range(n):
t0 = time.perf_counter()
await ref.ask("ping")
latencies.append((time.perf_counter() - t0) * 1_000_000) # microseconds
await system.shutdown()
latencies.sort()
p50 = latencies[len(latencies) // 2]
p99 = latencies[int(len(latencies) * 0.99)]
p999 = latencies[int(len(latencies) * 0.999)]
print(f" ask latency: p50={p50:.0f}µs p99={p99:.0f}µs p99.9={p999:.0f}µs")
async def bench_concurrent_actors(num_actors=1000, msgs_per_actor=100):
"""Measure throughput with many concurrent actors."""
system = ActorSystem("bench")
refs = []
for i in range(num_actors):
refs.append(await system.spawn(CounterActor, f"a{i}", mailbox_size=msgs_per_actor + 10))
start = time.perf_counter()
async def send_batch(ref, n):
for i in range(n):
await ref.tell("inc")
# Yield control every 50 msgs so actor loops can drain
if i % 50 == 49:
await asyncio.sleep(0)
return await ref.ask("get", timeout=30.0)
results = await asyncio.gather(*[send_batch(r, msgs_per_actor) for r in refs])
elapsed = time.perf_counter() - start
total = num_actors * msgs_per_actor
delivered = sum(results)
rate = total / elapsed
loss = total - delivered
print(f" {num_actors} actors × {msgs_per_actor} msgs: {fmt(total)} in {elapsed:.2f}s = {fmt(int(rate))}/s (loss: {loss})")
await system.shutdown()
async def bench_actor_chain(depth=100):
"""Measure ask latency through a chain of actors (hop overhead)."""
system = ActorSystem("bench")
refs = []
for i in range(depth):
refs.append(await system.spawn(ChainActor, f"c{i}"))
# Link chain: c0 → c1 → ... → c99
for i in range(depth - 1):
refs[i]._cell.actor.next_ref = refs[i + 1]
start = time.perf_counter()
result = await refs[0].ask("ping", timeout=30.0)
elapsed = time.perf_counter() - start
assert result == "ping"
per_hop = elapsed / depth * 1_000_000 # µs
print(f" chain {depth} hops: {elapsed*1000:.1f}ms total, {per_hop:.0f}µs/hop")
await system.shutdown()
async def bench_middleware_overhead(n=50_000):
"""Measure overhead of middleware pipeline."""
mw = CountMiddleware()
system_plain = ActorSystem("plain")
ref_plain = await system_plain.spawn(NoopActor, "echo")
system_mw = ActorSystem("mw")
ref_mw = await system_mw.spawn(NoopActor, "echo", middlewares=[mw])
# Plain
t0 = time.perf_counter()
for _ in range(n):
await ref_plain.ask("p")
plain_elapsed = time.perf_counter() - t0
# With middleware
t0 = time.perf_counter()
for _ in range(n):
await ref_mw.ask("p")
mw_elapsed = time.perf_counter() - t0
overhead = ((mw_elapsed - plain_elapsed) / plain_elapsed) * 100
print(f" middleware overhead: {overhead:+.1f}% ({fmt(n)} ask calls, 1 middleware)")
await system_plain.shutdown()
await system_mw.shutdown()
async def bench_executor_parallel(num_tasks=16):
"""Measure thread pool parallelism with CPU work."""
system = ActorSystem("bench", executor_workers=8)
refs = [await system.spawn(ComputeActor, f"cpu{i}") for i in range(num_tasks)]
start = time.perf_counter()
results = await asyncio.gather(*[r.ask(10_000, timeout=30.0) for r in refs])
elapsed = time.perf_counter() - start
print(f" executor parallel: {num_tasks} fib(10K) in {elapsed*1000:.0f}ms ({num_tasks/elapsed:.0f} tasks/s)")
await system.shutdown()
async def bench_spawn_teardown(n=5000):
"""Measure actor spawn + shutdown speed."""
system = ActorSystem("bench")
start = time.perf_counter()
refs = []
for i in range(n):
refs.append(await system.spawn(NoopActor, f"a{i}"))
spawn_elapsed = time.perf_counter() - start
start = time.perf_counter()
await system.shutdown()
shutdown_elapsed = time.perf_counter() - start
print(f" spawn {n}: {spawn_elapsed*1000:.0f}ms ({n/spawn_elapsed:.0f}/s)")
print(f" shutdown {n}: {shutdown_elapsed*1000:.0f}ms")
async def main():
print("=" * 60)
print(" Actor Framework Benchmarks")
print("=" * 60)
print()
print("[Throughput]")
await bench_tell_throughput()
await bench_ask_throughput()
print()
print("[Latency]")
await bench_ask_latency()
await bench_actor_chain()
print()
print("[Concurrency]")
await bench_concurrent_actors()
await bench_executor_parallel()
print()
print("[Overhead]")
await bench_middleware_overhead()
print()
print("[Lifecycle]")
await bench_spawn_teardown()
print()
print("=" * 60)
print(" Done")
print("=" * 60)
if __name__ == "__main__":
asyncio.run(main())