Skip to content

Conversation

@codeflash-ai
Copy link

@codeflash-ai codeflash-ai bot commented Oct 21, 2025

📄 254% (2.54x) speedup for DummyClient.get_properties in framework/py/flwr/simulation/ray_transport/ray_client_proxy_test.py

⏱️ Runtime : 3.84 milliseconds 1.08 milliseconds (best of 383 runs)

📝 Explanation and details

The optimized code achieves a 254% speedup by eliminating expensive object creation overhead in the hot path.

Key optimizations:

  1. Avoided ConfigRecord constructor overhead: Instead of calling ConfigRecord({"result": str(result)}) which creates a temporary dictionary and goes through the full constructor, the code uses ConfigRecord.__new__() and directly assigns to ._data, bypassing intermediate allocations.

  2. Cached string conversion: The str(result) call is performed once and stored in str_result to avoid redundant string conversions.

  3. Cached dictionary reference: config_rec = self.client_state.config_records avoids repeated attribute lookups.

Performance impact: The line profiler shows the original bottleneck was the ConfigRecord creation (89.2% of runtime, 12.38ms). The optimization reduces this to just 19.4% of total runtime (528μs) - a ~23x improvement on the critical path.

Best use cases: This optimization excels when get_properties() is called frequently (as shown in the large-scale tests with 1000+ clients), since it eliminates per-call allocation overhead. The optimization maintains identical functionality while dramatically reducing memory churn in high-frequency scenarios.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 3180 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 2 Passed
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests and Runtime
from math import pi

# imports
import pytest  # used for our unit tests
from simulation.ray_transport.ray_client_proxy_test import DummyClient


# function to test
class ConfigRecord(dict):
    """Mock ConfigRecord for testing."""
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)

class RecordDict(dict):
    """Mock RecordDict for testing."""
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.config_records = {}
from simulation.ray_transport.ray_client_proxy_test import DummyClient

# unit tests

# --- BASIC TEST CASES ---

def test_basic_positive_node_id():
    """Test with a typical positive node_id."""
    state = RecordDict()
    client = DummyClient(node_id=3, state=state)
    config = {}
    codeflash_output = client.get_properties(config); props = codeflash_output

def test_basic_zero_node_id():
    """Test with node_id = 0."""
    state = RecordDict()
    client = DummyClient(node_id=0, state=state)
    config = {}
    codeflash_output = client.get_properties(config); props = codeflash_output

def test_basic_negative_node_id():
    """Test with node_id < 0."""
    state = RecordDict()
    client = DummyClient(node_id=-2, state=state)
    config = {}
    codeflash_output = client.get_properties(config); props = codeflash_output

# --- EDGE TEST CASES ---

def test_edge_large_positive_node_id():
    """Test with a large positive node_id."""
    large_id = 10**6
    state = RecordDict()
    client = DummyClient(node_id=large_id, state=state)
    config = {}
    codeflash_output = client.get_properties(config); props = codeflash_output

def test_edge_large_negative_node_id():
    """Test with a large negative node_id."""
    large_id = -10**6
    state = RecordDict()
    client = DummyClient(node_id=large_id, state=state)
    config = {}
    codeflash_output = client.get_properties(config); props = codeflash_output

def test_edge_non_integer_node_id():
    """Test with a float node_id."""
    state = RecordDict()
    client = DummyClient(node_id=2.5, state=state)
    config = {}
    codeflash_output = client.get_properties(config); props = codeflash_output

def test_edge_config_is_none():
    """Test with config = None."""
    state = RecordDict()
    client = DummyClient(node_id=5, state=state)
    codeflash_output = client.get_properties(None); props = codeflash_output

def test_edge_config_is_empty_dict():
    """Test with config = {}."""
    state = RecordDict()
    client = DummyClient(node_id=7, state=state)
    codeflash_output = client.get_properties({}); props = codeflash_output

def test_edge_config_with_extra_keys():
    """Test with config containing extra keys."""
    state = RecordDict()
    client = DummyClient(node_id=4, state=state)
    config = {"foo": "bar", "baz": 123}
    codeflash_output = client.get_properties(config); props = codeflash_output

def test_edge_state_with_existing_config_records():
    """Test when state already has config_records."""
    state = RecordDict()
    state.config_records["existing"] = ConfigRecord({"old": "value"})
    client = DummyClient(node_id=6, state=state)
    config = {}
    codeflash_output = client.get_properties(config); props = codeflash_output

def test_edge_node_id_is_bool():
    """Test with node_id as boolean (should treat True as 1, False as 0)."""
    state_true = RecordDict()
    client_true = DummyClient(node_id=True, state=state_true)
    codeflash_output = client_true.get_properties({}); props_true = codeflash_output

    state_false = RecordDict()
    client_false = DummyClient(node_id=False, state=state_false)
    codeflash_output = client_false.get_properties({}); props_false = codeflash_output

def test_edge_node_id_is_string_number():
    """Test with node_id as a string representing a number (should fail)."""
    state = RecordDict()
    with pytest.raises(TypeError):
        DummyClient(node_id="5", state=state).get_properties({})

def test_edge_state_missing_config_records():
    """Test with state missing config_records attribute (should fail)."""
    class BadState(dict): pass
    bad_state = BadState()
    client = DummyClient(node_id=7, state=bad_state)
    with pytest.raises(AttributeError):
        client.get_properties({})

# --- LARGE SCALE TEST CASES ---

def test_large_scale_many_clients():
    """Test with many clients to ensure scalability."""
    num_clients = 1000
    states = [RecordDict() for _ in range(num_clients)]
    clients = [DummyClient(node_id=i, state=states[i]) for i in range(num_clients)]
    config = {}
    # Check a few random clients to avoid excessive computation
    for idx in [0, 1, 10, 100, 500, 999]:
        codeflash_output = clients[idx].get_properties(config); props = codeflash_output

def test_large_scale_state_config_records_growth():
    """Test that config_records grows correctly for many calls."""
    state = RecordDict()
    client = DummyClient(node_id=42, state=state)
    config = {}
    # Simulate multiple calls, each should overwrite 'result'
    for i in range(100):
        codeflash_output = client.get_properties(config); props = codeflash_output

def test_large_scale_state_with_many_config_records():
    """Test state with many config_records entries."""
    state = RecordDict()
    # Prepopulate with many unrelated config_records
    for i in range(999):
        state.config_records[f"key_{i}"] = ConfigRecord({"value": str(i)})
    client = DummyClient(node_id=77, state=state)
    config = {}
    codeflash_output = client.get_properties(config); props = codeflash_output
    # All previous keys should still exist
    for i in range(999):
        pass
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from math import pi

# imports
import pytest  # used for our unit tests
from simulation.ray_transport.ray_client_proxy_test import DummyClient


# function to test
class ConfigRecord:
    """A simple config record for storing results."""
    def __init__(self, data):
        self.data = data

class RecordDict(dict):
    """A dictionary for config records."""
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.config_records = {}
from simulation.ray_transport.ray_client_proxy_test import DummyClient

# unit tests

# 1. Basic Test Cases

def test_get_properties_basic_positive_integer():
    # Test with a basic positive integer node_id
    state = RecordDict()
    client = DummyClient(node_id=1, state=state)
    codeflash_output = client.get_properties(config={}); result = codeflash_output

def test_get_properties_basic_zero():
    # Test with node_id = 0
    state = RecordDict()
    client = DummyClient(node_id=0, state=state)
    codeflash_output = client.get_properties(config={}); result = codeflash_output

def test_get_properties_basic_negative_integer():
    # Test with a basic negative integer node_id
    state = RecordDict()
    client = DummyClient(node_id=-3, state=state)
    codeflash_output = client.get_properties(config={}); result = codeflash_output

def test_get_properties_basic_large_integer():
    # Test with a large positive integer node_id
    state = RecordDict()
    client = DummyClient(node_id=123456, state=state)
    codeflash_output = client.get_properties(config={}); result = codeflash_output

# 2. Edge Test Cases

def test_get_properties_edge_minimum_integer():
    # Test with minimum possible integer node_id (simulate -999)
    state = RecordDict()
    client = DummyClient(node_id=-999, state=state)
    codeflash_output = client.get_properties(config={}); result = codeflash_output

def test_get_properties_edge_maximum_integer():
    # Test with maximum reasonable integer node_id (simulate 999)
    state = RecordDict()
    client = DummyClient(node_id=999, state=state)
    codeflash_output = client.get_properties(config={}); result = codeflash_output

def test_get_properties_edge_float_node_id():
    # Test with node_id as a float (should work, but not intended)
    state = RecordDict()
    client = DummyClient(node_id=3.5, state=state)
    codeflash_output = client.get_properties(config={}); result = codeflash_output

def test_get_properties_edge_non_numeric_node_id():
    # Test with node_id as a string (should fail)
    state = RecordDict()
    with pytest.raises(TypeError):
        client = DummyClient(node_id="abc", state=state)
        client.get_properties(config={})

def test_get_properties_edge_config_content():
    # Test with config containing keys (should be ignored)
    state = RecordDict()
    client = DummyClient(node_id=5, state=state)
    config = {"unused_key": "unused_value"}
    codeflash_output = client.get_properties(config=config); result = codeflash_output

def test_get_properties_edge_state_mutation():
    # Test that state is mutated (config_records updated)
    state = RecordDict()
    client = DummyClient(node_id=2, state=state)
    client.get_properties(config={})

# 3. Large Scale Test Cases

def test_get_properties_large_scale_many_clients():
    # Test with many clients (up to 1000)
    clients = []
    states = []
    for i in range(1000):
        state = RecordDict()
        client = DummyClient(node_id=i, state=state)
        clients.append(client)
        states.append(state)
    # Call get_properties for each client and check result
    for i, client in enumerate(clients):
        codeflash_output = client.get_properties(config={}); result = codeflash_output

def test_get_properties_large_scale_state_storage():
    # Test that config_records does not overwrite previous results for different clients
    states = [RecordDict() for _ in range(10)]
    clients = [DummyClient(node_id=i, state=states[i]) for i in range(10)]
    for i, client in enumerate(clients):
        client.get_properties(config={})
        # Other states should not be affected
        for j, other_state in enumerate(states):
            if j != i:
                # If not called yet, should not have 'result'
                if j > i:
                    pass

def test_get_properties_large_scale_performance():
    # Test performance for large node_id values (not actual timing, but correctness)
    state = RecordDict()
    large_node_id = 999_999
    client = DummyClient(node_id=large_node_id, state=state)
    codeflash_output = client.get_properties(config={}); result = codeflash_output
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from flwr.common.record.recorddict import RecordDict
from simulation.ray_transport.ray_client_proxy_test import DummyClient

def test_DummyClient_get_properties():
    DummyClient.get_properties(DummyClient(0, RecordDict(records={}, parameters_records={}, metrics_records={}, configs_records={})), {})
🔎 Concolic Coverage Tests and Runtime

To edit these changes git checkout codeflash/optimize-DummyClient.get_properties-mh16n8b9 and push.

Codeflash

The optimized code achieves a **254% speedup** by eliminating expensive object creation overhead in the hot path. 

**Key optimizations:**

1. **Avoided ConfigRecord constructor overhead**: Instead of calling `ConfigRecord({"result": str(result)})` which creates a temporary dictionary and goes through the full constructor, the code uses `ConfigRecord.__new__()` and directly assigns to `._data`, bypassing intermediate allocations.

2. **Cached string conversion**: The `str(result)` call is performed once and stored in `str_result` to avoid redundant string conversions.

3. **Cached dictionary reference**: `config_rec = self.client_state.config_records` avoids repeated attribute lookups.

**Performance impact**: The line profiler shows the original bottleneck was the ConfigRecord creation (89.2% of runtime, 12.38ms). The optimization reduces this to just 19.4% of total runtime (528μs) - a ~23x improvement on the critical path.

**Best use cases**: This optimization excels when `get_properties()` is called frequently (as shown in the large-scale tests with 1000+ clients), since it eliminates per-call allocation overhead. The optimization maintains identical functionality while dramatically reducing memory churn in high-frequency scenarios.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 October 21, 2025 23:15
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Oct 21, 2025
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

⚡️ codeflash Optimization PR opened by Codeflash AI

Projects

None yet

Development

Successfully merging this pull request may close these issues.

1 participant