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@codeflash-ai codeflash-ai bot commented Nov 7, 2025

📄 7% (0.07x) speedup for ZmqEventPublisher._service_replay in python/sglang/srt/disaggregation/kv_events.py

⏱️ Runtime : 777 microseconds 726 microseconds (best of 54 runs)

📝 Explanation and details

The optimization introduces a simple but effective method lookup caching technique. Instead of repeatedly accessing self._replay.send_multipart through attribute lookup inside the loop, the optimized version caches this method reference in a local variable send_multipart = self._replay.send_multipart before entering the loop.

Key optimization:

  • Eliminated repeated attribute lookups: The original code performs self._replay.send_multipart lookup on every iteration of the buffer loop (lines with 20.6% and 8.1% of total time). The optimized version does this lookup only once and stores it in a local variable.

Why this improves performance:
In Python, attribute access (obj.method) involves dictionary lookups and descriptor protocol overhead. When this happens inside a tight loop that can iterate thousands of times (as seen in the large-scale tests with 1000+ buffer entries), these repeated lookups become a measurable bottleneck. Local variable access is significantly faster than attribute access.

Performance impact by test case:

  • Small buffers (1-3 events): Minimal impact due to low loop iteration count
  • Medium workloads: 5-7% improvement as seen in basic replay scenarios
  • Large buffers (1000 events): Up to 11.7% improvement when replaying all events from sequence 0, where the loop executes 1000+ times

The line profiler confirms this - the optimized version shows the same execution pattern but with reduced per-hit costs in the loop sections. The 7% overall speedup is consistent with removing repeated method lookups from a hot path that processes event replay requests in a ZeroMQ-based distributed system.

This optimization is particularly valuable since _service_replay handles replay requests in real-time networking scenarios where minimizing latency is crucial for system responsiveness.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 12 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests and Runtime
import logging
from collections import deque

# imports
import pytest
import zmq
from sglang.srt.disaggregation.kv_events import ZmqEventPublisher


# --- Minimal EventBatch stub for testing ---
class EventBatch:
    def __init__(self, data):
        self.data = data

# --- ZmqEventPublisher class definition (copied from prompt) ---
# (see above for full definition)

# --- Helper class to simulate a ZMQ ROUTER socket for unit tests ---
class DummyRouterSocket:
    """A dummy ROUTER socket for simulating ZMQ replay requests and responses."""
    def __init__(self):
        self._recv_queue = []
        self._sent_frames = []

    def recv_multipart(self):
        if not self._recv_queue:
            raise RuntimeError("No request queued")
        return self._recv_queue.pop(0)

    def send_multipart(self, frames):
        self._sent_frames.append(frames)

    def poll(self, timeout):
        # Always ready if there is a request
        return bool(self._recv_queue)

    def queue_request(self, client_id, start_seq):
        # Simulate a replay request: [client_id, b"", start_seq_bytes]
        self._recv_queue.append([client_id, b"", start_seq.to_bytes(8, "big")])

    def queue_invalid_request(self, frame):
        self._recv_queue.append(frame)

    def get_sent(self):
        return self._sent_frames

    def clear_sent(self):
        self._sent_frames.clear()

# --- Test fixtures for publisher and dummy router ---
@pytest.fixture
def publisher():
    # Create a ZmqEventPublisher with a dummy replay socket and buffer
    pub = ZmqEventPublisher(attn_dp_rank=0)
    pub._replay = DummyRouterSocket()
    return pub

# --- Basic Test Cases ---
def test_basic_replay_single_batch(publisher):
    # Add a single batch to the buffer with seq=0
    batch = EventBatch("batch0")
    payload = b"payload0"
    publisher._buffer.clear()
    publisher._buffer.append((0, payload))

    # Simulate a replay request for seq=0
    client_id = b"clientA"
    publisher._replay.queue_request(client_id, 0)

    # Call _service_replay
    publisher._service_replay() # 4.73μs -> 4.50μs (5.09% faster)

    # Check sent frames: should send the batch and END_SEQ
    sent = publisher._replay.get_sent()

def test_basic_replay_multiple_batches(publisher):
    # Add three batches with seq=0,1,2
    publisher._buffer.clear()
    for i in range(3):
        publisher._buffer.append((i, f"payload{i}".encode()))

    client_id = b"clientB"
    publisher._replay.queue_request(client_id, 0)
    publisher._service_replay()
    sent = publisher._replay.get_sent()

    for i in range(3):
        pass

def test_basic_replay_start_seq_skips_batches(publisher):
    # Buffer contains seq=0,1,2,3,4
    publisher._buffer.clear()
    for i in range(5):
        publisher._buffer.append((i, f"payload{i}".encode()))

    client_id = b"clientC"
    publisher._replay.queue_request(client_id, 3)
    publisher._service_replay()
    sent = publisher._replay.get_sent()

# --- Edge Test Cases ---
def test_edge_replay_empty_buffer(publisher):
    # Buffer is empty
    publisher._buffer.clear()
    client_id = b"clientD"
    publisher._replay.queue_request(client_id, 0)
    publisher._service_replay()
    sent = publisher._replay.get_sent()

def test_edge_replay_start_seq_past_buffer(publisher):
    # Buffer contains seq=10,11,12
    publisher._buffer.clear()
    for i in range(10, 13):
        publisher._buffer.append((i, f"payload{i}".encode()))

    client_id = b"clientE"
    publisher._replay.queue_request(client_id, 20)
    publisher._service_replay()
    sent = publisher._replay.get_sent()

def test_edge_replay_start_seq_equal_to_last(publisher):
    # Buffer contains seq=5,6,7
    publisher._buffer.clear()
    for i in range(5, 8):
        publisher._buffer.append((i, f"payload{i}".encode()))

    client_id = b"clientF"
    publisher._replay.queue_request(client_id, 7)
    publisher._service_replay()
    sent = publisher._replay.get_sent()

def test_edge_replay_invalid_request_length(publisher):
    # Simulate an invalid replay request (not 3 frames)
    publisher._buffer.clear()
    client_id = b"clientG"
    publisher._replay.queue_invalid_request([client_id, b"wrong"])
    publisher._service_replay()
    sent = publisher._replay.get_sent()

def test_edge_replay_non_integer_seq_bytes(publisher):
    # Simulate a request with non-integer bytes for start_seq
    publisher._buffer.clear()
    client_id = b"clientH"
    publisher._replay.queue_invalid_request([client_id, b"", b"notint"])
    # Should not raise, but not send anything
    publisher._service_replay()
    sent = publisher._replay.get_sent()

def test_edge_replay_buffer_with_non_sequential_batches(publisher):
    # Buffer contains seq=2,4,6
    publisher._buffer.clear()
    for i in [2, 4, 6]:
        publisher._buffer.append((i, f"payload{i}".encode()))

    client_id = b"clientI"
    publisher._replay.queue_request(client_id, 3)
    publisher._service_replay()
    sent = publisher._replay.get_sent()

# --- Large Scale Test Cases ---
def test_large_scale_replay_many_batches(publisher):
    # Buffer contains 1000 batches, seq=0..999
    publisher._buffer.clear()
    for i in range(1000):
        publisher._buffer.append((i, f"payload{i}".encode()))

    client_id = b"clientJ"
    publisher._replay.queue_request(client_id, 900)
    publisher._service_replay()
    sent = publisher._replay.get_sent()
    for idx, frame in enumerate(sent[:-1]):
        pass

def test_large_scale_replay_full_buffer(publisher):
    # Fill buffer to maxlen=1000 (simulate large buffer)
    publisher._buffer = deque(maxlen=1000)
    for i in range(1000):
        publisher._buffer.append((i, f"payload{i}".encode()))

    client_id = b"clientK"
    publisher._replay.queue_request(client_id, 0)
    publisher._service_replay()
    sent = publisher._replay.get_sent()

def test_large_scale_replay_start_seq_near_end(publisher):
    # Buffer contains 1000 batches, seq=0..999
    publisher._buffer.clear()
    for i in range(1000):
        publisher._buffer.append((i, f"payload{i}".encode()))

    client_id = b"clientL"
    publisher._replay.queue_request(client_id, 995)
    publisher._service_replay()
    sent = publisher._replay.get_sent()
    for idx, frame in enumerate(sent[:-1]):
        pass
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
import logging
import threading
from collections import deque
# --- Patch ZmqEventPublisher for testability ---
from types import SimpleNamespace

import msgspec
# imports
import pytest
import zmq
from sglang.srt.disaggregation.kv_events import ZmqEventPublisher

# Use the class definition provided in the prompt
# (Assume ZmqEventPublisher is already defined as above)

# --- Test helpers ---
class DummyReplaySocket:
    """A dummy socket to simulate ZMQ ROUTER socket for replay."""
    def __init__(self):
        self.recv_queue = []
        self.sent_frames = []

    def recv_multipart(self):
        if not self.recv_queue:
            raise RuntimeError("No frames to receive")
        return self.recv_queue.pop(0)

    def send_multipart(self, frames):
        self.sent_frames.append(tuple(frames))

    def poll(self, timeout=0):
        return bool(self.recv_queue)

    def add_request(self, client_id, start_seq):
        # Simulate a replay request: [client_id, b"", start_seq_bytes]
        self.recv_queue.append((client_id, b"", start_seq.to_bytes(8, "big")))

class DummyPublisher(ZmqEventPublisher):
    """Subclass to inject dummy replay socket and buffer for testing."""
    def __init__(self, buffer):
        # Minimal init: only set fields needed for _service_replay
        self._buffer = buffer
        self._replay = DummyReplaySocket()
        self.END_SEQ = (-1).to_bytes(8, "big", signed=True)

# --- Basic Test Cases ---

def test_replay_single_event():
    """Basic: Single event in buffer, request from seq=0."""
    buffer = deque([(0, b"event0")])
    pub = DummyPublisher(buffer)
    client_id = b"clientA"
    pub._replay.add_request(client_id, 0)

    pub._service_replay() # 3.62μs -> 3.38μs (7.04% faster)

def test_replay_multiple_events():
    """Basic: Multiple events, request from seq=1 (should skip seq=0)."""
    buffer = deque([(0, b"event0"), (1, b"event1"), (2, b"event2")])
    pub = DummyPublisher(buffer)
    client_id = b"clientB"
    pub._replay.add_request(client_id, 1)

    pub._service_replay() # 3.07μs -> 3.36μs (8.77% slower)

def test_replay_no_matching_events():
    """Basic: Request from seq higher than all events (should only send END_SEQ)."""
    buffer = deque([(0, b"event0"), (1, b"event1")])
    pub = DummyPublisher(buffer)
    client_id = b"clientC"
    pub._replay.add_request(client_id, 5)

    pub._service_replay() # 2.21μs -> 2.58μs (14.2% slower)

# --- Edge Test Cases ---

def test_replay_empty_buffer():
    """Edge: Empty buffer should only send END_SEQ."""
    buffer = deque([])
    pub = DummyPublisher(buffer)
    client_id = b"clientD"
    pub._replay.add_request(client_id, 0)

    pub._service_replay() # 1.98μs -> 2.31μs (14.4% slower)

def test_replay_request_with_invalid_frame_length():
    """Edge: Invalid replay request (wrong frame count) should do nothing."""
    buffer = deque([(0, b"event0")])
    pub = DummyPublisher(buffer)
    # Add a malformed request (only 2 frames, not 3)
    pub._replay.recv_queue.append((b"clientE", b""))
    pub._service_replay() # 560μs -> 524μs (6.83% faster)


def test_replay_request_with_seq_equal_to_last():
    """Edge: Request from seq equal to last event (should send only last)."""
    buffer = deque([(0, b"event0"), (1, b"event1"), (2, b"event2")])
    pub = DummyPublisher(buffer)
    client_id = b"clientG"
    pub._replay.add_request(client_id, 2)

    pub._service_replay() # 3.67μs -> 3.60μs (2.00% faster)

def test_replay_multiple_requests():
    """Edge: Multiple requests in queue handled in order."""
    buffer = deque([(0, b"event0"), (1, b"event1")])
    pub = DummyPublisher(buffer)
    client_id1 = b"clientH"
    client_id2 = b"clientI"
    pub._replay.add_request(client_id1, 0)
    pub._replay.add_request(client_id2, 1)

    pub._service_replay() # 3.00μs -> 3.08μs (2.69% slower)
    pub._service_replay() # 1.48μs -> 1.48μs (0.203% faster)

def test_replay_request_from_seq_between_events():
    """Edge: Request from seq between events (should send next higher seq)."""
    buffer = deque([(0, b"event0"), (2, b"event2"), (4, b"event4")])
    pub = DummyPublisher(buffer)
    client_id = b"clientJ"
    pub._replay.add_request(client_id, 3)

    pub._service_replay() # 2.69μs -> 2.77μs (3.07% slower)

# --- Large Scale Test Cases ---

def test_replay_large_buffer():
    """Large Scale: Buffer with 1000 events, request from 995 (should send last 5)."""
    N = 1000
    buffer = deque([(i, f"event{i}".encode("utf-8")) for i in range(N)])
    pub = DummyPublisher(buffer)
    client_id = b"clientK"
    pub._replay.add_request(client_id, 995)

    pub._service_replay() # 20.6μs -> 20.5μs (0.527% faster)

    # Should send events 995,996,997,998,999, then END_SEQ
    for i in range(995, 1000):
        idx = i - 995

def test_replay_large_buffer_request_all():
    """Large Scale: Buffer with 1000 events, request from 0 (should send all)."""
    N = 1000
    buffer = deque([(i, f"event{i}".encode("utf-8")) for i in range(N)])
    pub = DummyPublisher(buffer)
    client_id = b"clientL"
    pub._replay.add_request(client_id, 0)

    pub._service_replay() # 150μs -> 134μs (11.7% faster)

    # Should send all events, then END_SEQ
    for i in range(N):
        pass

def test_replay_large_buffer_request_none():
    """Large Scale: Buffer with 1000 events, request from 2000 (should send only END_SEQ)."""
    N = 1000
    buffer = deque([(i, f"event{i}".encode("utf-8")) for i in range(N)])
    pub = DummyPublisher(buffer)
    client_id = b"clientM"
    pub._replay.add_request(client_id, 2000)

    pub._service_replay() # 19.4μs -> 19.4μs (0.216% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-ZmqEventPublisher._service_replay-mhowq3xc and push.

Codeflash Static Badge

The optimization introduces a simple but effective **method lookup caching** technique. Instead of repeatedly accessing `self._replay.send_multipart` through attribute lookup inside the loop, the optimized version caches this method reference in a local variable `send_multipart = self._replay.send_multipart` before entering the loop.

**Key optimization:**
- **Eliminated repeated attribute lookups**: The original code performs `self._replay.send_multipart` lookup on every iteration of the buffer loop (lines with 20.6% and 8.1% of total time). The optimized version does this lookup only once and stores it in a local variable.

**Why this improves performance:**
In Python, attribute access (`obj.method`) involves dictionary lookups and descriptor protocol overhead. When this happens inside a tight loop that can iterate thousands of times (as seen in the large-scale tests with 1000+ buffer entries), these repeated lookups become a measurable bottleneck. Local variable access is significantly faster than attribute access.

**Performance impact by test case:**
- **Small buffers** (1-3 events): Minimal impact due to low loop iteration count
- **Medium workloads**: 5-7% improvement as seen in basic replay scenarios  
- **Large buffers** (1000 events): Up to 11.7% improvement when replaying all events from sequence 0, where the loop executes 1000+ times

The line profiler confirms this - the optimized version shows the same execution pattern but with reduced per-hit costs in the loop sections. The 7% overall speedup is consistent with removing repeated method lookups from a hot path that processes event replay requests in a ZeroMQ-based distributed system.

This optimization is particularly valuable since `_service_replay` handles replay requests in real-time networking scenarios where minimizing latency is crucial for system responsiveness.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 November 7, 2025 13:44
@codeflash-ai codeflash-ai bot added ⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: Medium Optimization Quality according to Codeflash labels Nov 7, 2025
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