⚡️ Speed up method CollectionQueryEvent.batch by 21%

[codeflash-ai]

📄 21% (0.21x) speedup for CollectionQueryEvent.batch in chromadb/telemetry/product/events.py

⏱️ Runtime : 3.96 milliseconds → 3.27 milliseconds (best of 123 runs)

📝 Explanation and details

The optimized code achieves a 21% speedup through two key optimizations:

1. slots Declaration
Added __slots__ to define a fixed set of attributes, which:

• Reduces memory overhead per instance by eliminating the __dict__
• Speeds up attribute access operations throughout the method
• Particularly benefits the heavy attribute access in the batch() method

2. Optimized Constructor Call Pattern
Restructured the batch() method to:

• Use a shorter variable name o instead of other to reduce lookup overhead
• Pre-compute all constructor arguments in a tuple, then unpack with *args
• This reduces the constructor call from multiple keyword arguments to a single tuple unpacking operation

Performance Impact by Test Case:

• Basic cases: 8-19% faster for simple batching operations
• Large-scale scenarios: 20-35% faster, especially beneficial for:
  • Chain batching of many events (21.7% faster for 1000 events)
  • Operations with large integer values (29.1% faster)
  • High-frequency batching scenarios (22.4% faster for 500 iterations)

The optimizations are most effective for workloads involving frequent object creation and attribute access, which is typical in telemetry event batching where many events are processed and combined rapidly.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 7072 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	✅ 6 Passed
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

from typing import ClassVar, cast

# imports
import pytest
from chromadb.telemetry.product.events import CollectionQueryEvent

# function to test


class ProductTelemetryEvent:
    max_batch_size: ClassVar[int] = 1
    batch_size: int

    def __init__(self, batch_size: int = 1):
        self.batch_size = batch_size

    @property
    def batch_key(self):
        # Assume batch_key is a tuple of class name and any distinguishing attributes.
        # For CollectionQueryEvent, we'll use collection_uuid.
        if hasattr(self, "collection_uuid"):
            return (self.__class__.__name__, getattr(self, "collection_uuid"))
        return (self.__class__.__name__,)
from chromadb.telemetry.product.events import CollectionQueryEvent

# unit tests

# --------------- Basic Test Cases ---------------

def test_batch_basic_addition():
    # Test that batch correctly adds fields for two events with same collection_uuid
    e1 = CollectionQueryEvent(
        collection_uuid="abc",
        query_amount=1,
        filtered_ids_amount=2,
        with_metadata_filter=3,
        with_document_filter=4,
        n_results=5,
        include_metadatas=6,
        include_documents=7,
        include_uris=8,
        include_distances=9,
        batch_size=10,
    )
    e2 = CollectionQueryEvent(
        collection_uuid="abc",
        query_amount=10,
        filtered_ids_amount=20,
        with_metadata_filter=30,
        with_document_filter=40,
        n_results=50,
        include_metadatas=60,
        include_documents=70,
        include_uris=80,
        include_distances=90,
        batch_size=100,
    )
    codeflash_output = e1.batch(e2); batched = codeflash_output # 2.79μs -> 2.59μs (8.00% faster)

def test_batch_basic_single_batch_size_default():
    # Test batching with default batch_size (should be 1)
    e1 = CollectionQueryEvent("id", 1,1,1,1,1,1,1,1,1)
    e2 = CollectionQueryEvent("id", 2,2,2,2,2,2,2,2,2)
    codeflash_output = e1.batch(e2); batched = codeflash_output # 3.10μs -> 2.60μs (19.5% faster)

def test_batch_basic_zero_values():
    # Test batching with zero values
    e1 = CollectionQueryEvent("id", 0,0,0,0,0,0,0,0,0)
    e2 = CollectionQueryEvent("id", 0,0,0,0,0,0,0,0,0)
    codeflash_output = e1.batch(e2); batched = codeflash_output # 3.10μs -> 2.73μs (13.7% faster)

# --------------- Edge Test Cases ---------------

def test_batch_different_collection_uuid():
    # Test that batching with different collection_uuid raises ValueError
    e1 = CollectionQueryEvent("id1", 1,1,1,1,1,1,1,1,1)
    e2 = CollectionQueryEvent("id2", 2,2,2,2,2,2,2,2,2)
    with pytest.raises(ValueError):
        e1.batch(e2) # 1.77μs -> 1.81μs (2.10% slower)

def test_batch_with_non_collection_event():
    # Test that batching with a non-CollectionQueryEvent raises ValueError
    class DummyEvent(ProductTelemetryEvent):
        pass
    e1 = CollectionQueryEvent("id", 1,1,1,1,1,1,1,1,1)
    e2 = DummyEvent()
    with pytest.raises(ValueError):
        e1.batch(e2) # 2.73μs -> 2.59μs (5.49% faster)

def test_batch_negative_values():
    # Test batching with negative values
    e1 = CollectionQueryEvent("id", -1,-2,-3,-4,-5,-6,-7,-8,-9,-10)
    e2 = CollectionQueryEvent("id", -10,-20,-30,-40,-50,-60,-70,-80,-90,-100)
    codeflash_output = e1.batch(e2); batched = codeflash_output # 3.88μs -> 2.86μs (35.6% faster)

def test_batch_max_batch_size_not_enforced():
    # Test that batch does not enforce max_batch_size (should not raise)
    e1 = CollectionQueryEvent("id", 1,1,1,1,1,1,1,1,1, batch_size=2999)
    e2 = CollectionQueryEvent("id", 1,1,1,1,1,1,1,1,1, batch_size=100)
    codeflash_output = e1.batch(e2); batched = codeflash_output # 3.57μs -> 2.82μs (26.4% faster)

def test_batch_with_large_int_values():
    # Test batching with large integer values
    big = 2**60
    e1 = CollectionQueryEvent("id", big,big,big,big,big,big,big,big,big,big)
    e2 = CollectionQueryEvent("id", big,big,big,big,big,big,big,big,big,big)
    codeflash_output = e1.batch(e2); batched = codeflash_output # 3.88μs -> 3.01μs (29.1% faster)

# --------------- Large Scale Test Cases ---------------

def test_batch_many_times_scalability():
    # Test batching a chain of events (up to 1000)
    N = 1000
    events = [
        CollectionQueryEvent(
            "large",
            query_amount=1,
            filtered_ids_amount=2,
            with_metadata_filter=3,
            with_document_filter=4,
            n_results=5,
            include_metadatas=6,
            include_documents=7,
            include_uris=8,
            include_distances=9,
            batch_size=1,
        )
        for _ in range(N)
    ]
    # Batch all events together
    batched = events[0]
    for e in events[1:]:
        codeflash_output = batched.batch(e); batched = codeflash_output # 1.55ms -> 1.28ms (21.7% faster)

def test_batch_large_batch_size_and_fields():
    # Test batching with large batch_size and large field values
    N = 999
    e1 = CollectionQueryEvent("big", N,N,N,N,N,N,N,N,N,N)
    e2 = CollectionQueryEvent("big", N,N,N,N,N,N,N,N,N,N)
    codeflash_output = e1.batch(e2); batched = codeflash_output # 3.63μs -> 2.99μs (21.5% faster)

def test_batch_performance_with_many_events():
    # Test performance and correctness with many events (no assertion on time, but correctness)
    N = 500
    base = CollectionQueryEvent("perf", 1,2,3,4,5,6,7,8,9,10)
    batched = base
    for _ in range(N-1):
        codeflash_output = batched.batch(base); batched = codeflash_output # 779μs -> 636μs (22.4% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from typing import ClassVar, cast

# imports
import pytest
from chromadb.telemetry.product.events import CollectionQueryEvent


class ProductTelemetryEvent:
    max_batch_size: ClassVar[int] = 1
    batch_size: int

    def __init__(self, batch_size: int = 1):
        self.batch_size = batch_size

    @property
    def batch_key(self):
        # For testing, batch_key is a tuple of class and collection_uuid if present
        # This ensures that only events from the same collection can be batched
        # If no collection_uuid, just use class name
        return (self.__class__, getattr(self, "collection_uuid", None))
from chromadb.telemetry.product.events import CollectionQueryEvent

# unit tests

# ---------------- Basic Test Cases ----------------

def make_event(
    collection_uuid="uuid1",
    query_amount=1,
    filtered_ids_amount=0,
    with_metadata_filter=0,
    with_document_filter=0,
    n_results=1,
    include_metadatas=0,
    include_documents=0,
    include_uris=0,
    include_distances=0,
    batch_size=1,
):
    # Helper to create events with defaults
    return CollectionQueryEvent(
        collection_uuid=collection_uuid,
        query_amount=query_amount,
        filtered_ids_amount=filtered_ids_amount,
        with_metadata_filter=with_metadata_filter,
        with_document_filter=with_document_filter,
        n_results=n_results,
        include_metadatas=include_metadatas,
        include_documents=include_documents,
        include_uris=include_uris,
        include_distances=include_distances,
        batch_size=batch_size,
    )

def test_batch_basic_addition():
    # Test that batching two events adds all integer fields
    e1 = make_event(query_amount=2, filtered_ids_amount=3, with_metadata_filter=1, n_results=5, batch_size=1)
    e2 = make_event(query_amount=4, filtered_ids_amount=7, with_metadata_filter=2, n_results=6, batch_size=2)
    codeflash_output = e1.batch(e2); res = codeflash_output # 3.97μs -> 3.56μs (11.5% faster)

def test_batch_basic_preserves_collection_uuid():
    # Test that collection_uuid is preserved and must match
    e1 = make_event(collection_uuid="abc")
    e2 = make_event(collection_uuid="abc")
    codeflash_output = e1.batch(e2); res = codeflash_output # 3.13μs -> 2.99μs (4.92% faster)

def test_batch_basic_all_fields():
    # Test batching with all fields nonzero and different
    e1 = make_event(
        collection_uuid="col1",
        query_amount=5,
        filtered_ids_amount=2,
        with_metadata_filter=1,
        with_document_filter=0,
        n_results=7,
        include_metadatas=3,
        include_documents=4,
        include_uris=1,
        include_distances=2,
        batch_size=1,
    )
    e2 = make_event(
        collection_uuid="col1",
        query_amount=6,
        filtered_ids_amount=8,
        with_metadata_filter=2,
        with_document_filter=3,
        n_results=5,
        include_metadatas=1,
        include_documents=2,
        include_uris=0,
        include_distances=3,
        batch_size=2,
    )
    codeflash_output = e1.batch(e2); res = codeflash_output # 3.01μs -> 2.98μs (1.07% faster)

# ---------------- Edge Test Cases ----------------

def test_batch_different_collection_uuid_raises():
    # Events with different collection_uuid cannot be batched
    e1 = make_event(collection_uuid="uuid1")
    e2 = make_event(collection_uuid="uuid2")
    with pytest.raises(ValueError):
        e1.batch(e2) # 1.85μs -> 1.84μs (0.707% faster)

def test_batch_zero_fields():
    # Test batching events where all fields are zero
    e1 = make_event(
        collection_uuid="zero",
        query_amount=0,
        filtered_ids_amount=0,
        with_metadata_filter=0,
        with_document_filter=0,
        n_results=0,
        include_metadatas=0,
        include_documents=0,
        include_uris=0,
        include_distances=0,
        batch_size=0,
    )
    e2 = make_event(
        collection_uuid="zero",
        query_amount=0,
        filtered_ids_amount=0,
        with_metadata_filter=0,
        with_document_filter=0,
        n_results=0,
        include_metadatas=0,
        include_documents=0,
        include_uris=0,
        include_distances=0,
        batch_size=0,
    )
    codeflash_output = e1.batch(e2); res = codeflash_output # 3.00μs -> 2.90μs (3.27% faster)

def test_batch_negative_values():
    # Test batching with negative values (should sum as usual)
    e1 = make_event(
        collection_uuid="neg",
        query_amount=-5,
        filtered_ids_amount=-2,
        with_metadata_filter=-1,
        with_document_filter=-3,
        n_results=-4,
        include_metadatas=-2,
        include_documents=-1,
        include_uris=-6,
        include_distances=-7,
        batch_size=-2,
    )
    e2 = make_event(
        collection_uuid="neg",
        query_amount=-3,
        filtered_ids_amount=-1,
        with_metadata_filter=-2,
        with_document_filter=-1,
        n_results=-5,
        include_metadatas=-3,
        include_documents=-2,
        include_uris=-4,
        include_distances=-5,
        batch_size=-1,
    )
    codeflash_output = e1.batch(e2); res = codeflash_output # 2.93μs -> 2.93μs (0.034% slower)

def test_batch_different_types_raises():
    # Test that batching with a different event type raises ValueError
    class DummyEvent(ProductTelemetryEvent):
        def __init__(self):
            super().__init__()
        @property
        def batch_key(self):
            return (self.__class__, None)
    e1 = make_event(collection_uuid="uuid")
    e2 = DummyEvent()
    with pytest.raises(ValueError):
        e1.batch(e2) # 2.06μs -> 2.16μs (4.49% slower)

def test_batch_self():
    # Test batching an event with itself doubles all fields
    e = make_event(
        collection_uuid="self",
        query_amount=2,
        filtered_ids_amount=3,
        with_metadata_filter=1,
        with_document_filter=4,
        n_results=5,
        include_metadatas=6,
        include_documents=7,
        include_uris=8,
        include_distances=9,
        batch_size=1,
    )
    codeflash_output = e.batch(e); res = codeflash_output # 3.29μs -> 2.99μs (10.1% faster)

def test_batch_size_limit_not_enforced():
    # Test that max_batch_size is not enforced by batch method itself
    e1 = make_event(collection_uuid="big", batch_size=2000)
    e2 = make_event(collection_uuid="big", batch_size=1500)
    codeflash_output = e1.batch(e2); res = codeflash_output # 3.00μs -> 2.86μs (5.04% faster)

# ---------------- Large Scale Test Cases ----------------

def test_batch_many_fields_large_values():
    # Test batching with large numbers in all fields
    big = 10**6
    e1 = make_event(
        collection_uuid="large",
        query_amount=big,
        filtered_ids_amount=big,
        with_metadata_filter=big,
        with_document_filter=big,
        n_results=big,
        include_metadatas=big,
        include_documents=big,
        include_uris=big,
        include_distances=big,
        batch_size=big,
    )
    e2 = make_event(
        collection_uuid="large",
        query_amount=big,
        filtered_ids_amount=big,
        with_metadata_filter=big,
        with_document_filter=big,
        n_results=big,
        include_metadatas=big,
        include_documents=big,
        include_uris=big,
        include_distances=big,
        batch_size=big,
    )
    codeflash_output = e1.batch(e2); res = codeflash_output # 2.95μs -> 2.83μs (4.42% faster)

def test_batch_chain_large_scale():
    # Test batching a chain of events (simulate batching 1000 events)
    base = make_event(collection_uuid="chain", query_amount=1)
    result = base
    for i in range(1, 1000):
        next_event = make_event(collection_uuid="chain", query_amount=1)
        codeflash_output = result.batch(next_event); result = codeflash_output # 1.55ms -> 1.29ms (20.4% faster)

def test_batch_performance_large_batch():
    # Test batching two events with batch_size near the max_batch_size
    e1 = make_event(collection_uuid="perf", batch_size=1500, query_amount=1500)
    e2 = make_event(collection_uuid="perf", batch_size=1499, query_amount=1499)
    codeflash_output = e1.batch(e2); res = codeflash_output # 3.10μs -> 2.85μs (8.67% faster)

def test_batch_fields_independent_large_scale():
    # Test that batching does not mix up fields even with large, distinct values
    e1 = make_event(
        collection_uuid="indep",
        query_amount=100,
        filtered_ids_amount=200,
        with_metadata_filter=300,
        with_document_filter=400,
        n_results=500,
        include_metadatas=600,
        include_documents=700,
        include_uris=800,
        include_distances=900,
        batch_size=1000,
    )
    e2 = make_event(
        collection_uuid="indep",
        query_amount=1,
        filtered_ids_amount=2,
        with_metadata_filter=3,
        with_document_filter=4,
        n_results=5,
        include_metadatas=6,
        include_documents=7,
        include_uris=8,
        include_distances=9,
        batch_size=10,
    )
    codeflash_output = e1.batch(e2); res = codeflash_output # 2.84μs -> 2.66μs (6.73% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from chromadb.telemetry.product.events import ClientStartEvent
from chromadb.telemetry.product.events import CollectionQueryEvent
import pytest

def test_CollectionQueryEvent_batch():
    CollectionQueryEvent.batch(CollectionQueryEvent('', 0, 0, 0, 0, 0, 0, 0, 0, 0, batch_size=0), CollectionQueryEvent('', 0, 0, 0, 0, 0, 0, 0, 0, 0, batch_size=0))

def test_CollectionQueryEvent_batch_2():
    with pytest.raises(ValueError, match='Cannot\\ batch\\ events'):
        CollectionQueryEvent.batch(CollectionQueryEvent('', 0, 0, 0, 0, 0, 0, 0, 0, 0, batch_size=0), ClientStartEvent())

🔎 Concolic Coverage Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
codeflash_concolic_aqrniplu/tmpxt_q0up6/test_concolic_coverage.py::test_CollectionQueryEvent_batch	3.53μs	2.87μs	22.9%✅
codeflash_concolic_aqrniplu/tmpxt_q0up6/test_concolic_coverage.py::test_CollectionQueryEvent_batch_2	2.17μs	2.00μs	8.62%✅

To edit these changes git checkout codeflash/optimize-CollectionQueryEvent.batch-mh1zdunq and push.