Skip to content

Conversation

codeflash-ai[bot]
Copy link

@codeflash-ai codeflash-ai bot commented Oct 22, 2025

📄 10% (0.10x) speedup for Limit.to_dict in chromadb/execution/expression/operator.py

⏱️ Runtime : 2.90 milliseconds 2.65 milliseconds (best of 8 runs)

📝 Explanation and details

The optimization eliminates unnecessary dictionary manipulation by using conditional returns instead of building and modifying a dictionary. The original code creates a dictionary with "offset", then conditionally adds "limit" via dictionary assignment. The optimized version uses two separate return paths: when limit is None, it directly returns {"offset": self.offset}, and when limit has a value, it returns {"offset": self.offset, "limit": self.limit} in one operation.

This change reduces the number of dictionary operations from 2-3 (create dict + conditional assignment) to 1 (single dict creation), eliminating the overhead of dictionary key insertion. The speedup is most pronounced when limit=None (17.3% faster in tests) since it avoids the conditional assignment entirely. Even when limit has a value, creating the full dictionary at once is more efficient than incremental construction.

The optimization works well across all test patterns, showing consistent 8-17% improvements for individual calls and 3-15% improvements for batch operations, making it particularly effective for high-frequency serialization scenarios.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 44 Passed
🌀 Generated Regression Tests 2005 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 75.0%
⚙️ Existing Unit Tests and Runtime
Test File::Test Function Original ⏱️ Optimized ⏱️ Speedup
test_api.py::TestRoundTripConversion.test_limit_round_trip 1.01μs 860ns 17.2%✅
🌀 Generated Regression Tests and Runtime
from dataclasses import dataclass
from typing import Any, Dict, Optional

# imports
import pytest  # used for our unit tests
from chromadb.execution.expression.operator import Limit

# unit tests

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

def test_default_values():
    # Test default construction
    l = Limit()
    codeflash_output = l.to_dict(); d = codeflash_output # 715ns -> 657ns (8.83% faster)










def test_offset_none():
    # Test with offset explicitly set to None (should raise TypeError)
    with pytest.raises(TypeError):
        Limit(offset=None)
















#------------------------------------------------
from dataclasses import dataclass
from typing import Any, Dict, Optional

# imports
import pytest  # used for our unit tests
from chromadb.execution.expression.operator import Limit

# unit tests

# 1. Basic Test Cases

def test_default_values():
    """Test default initialization (no arguments)."""
    l = Limit()
    codeflash_output = l.to_dict() # 686ns -> 638ns (7.52% faster)













def test_limit_is_none_not_in_dict():
    """Test that limit is not included when None."""
    l = Limit(offset=12, limit=None)
    codeflash_output = l.to_dict(); d = codeflash_output # 670ns -> 571ns (17.3% faster)

# 3. Large Scale Test Cases

@pytest.mark.parametrize("offset,limit", [
    (i, None) for i in range(1000)
])
def test_many_offsets(offset, limit):
    """Test many different offset values with limit=None."""
    l = Limit(offset=offset, limit=limit)
    codeflash_output = l.to_dict() # 710μs -> 617μs (15.1% faster)

@pytest.mark.parametrize("offset,limit", [
    (0, i) for i in range(1000)
])
def test_many_limits(offset, limit):
    """Test many different limit values with offset=0."""
    l = Limit(offset=offset, limit=limit)
    codeflash_output = l.to_dict() # 810μs -> 710μs (14.1% faster)

def test_large_scale_randomized():
    """Test a large number of randomized offset and limit values."""
    import random
    for _ in range(500):
        offset = random.randint(-1000, 1000)
        # limit can be None or int in [-1000, 1000]
        if random.choice([True, False]):
            limit = random.randint(-1000, 1000)
        else:
            limit = None
        l = Limit(offset=offset, limit=limit)
        codeflash_output = l.to_dict(); d = codeflash_output # 126μs -> 122μs (3.34% faster)
        if limit is not None:
            pass
        else:
            pass



#------------------------------------------------
from chromadb.execution.expression.operator import Limit

def test_Limit_to_dict():
    Limit.to_dict(Limit(offset=0, limit=0))

To edit these changes git checkout codeflash/optimize-Limit.to_dict-mh1i7ony and push.

Codeflash

The optimization eliminates unnecessary dictionary manipulation by using conditional returns instead of building and modifying a dictionary. The original code creates a dictionary with "offset", then conditionally adds "limit" via dictionary assignment. The optimized version uses two separate return paths: when `limit` is None, it directly returns `{"offset": self.offset}`, and when `limit` has a value, it returns `{"offset": self.offset, "limit": self.limit}` in one operation.

This change reduces the number of dictionary operations from 2-3 (create dict + conditional assignment) to 1 (single dict creation), eliminating the overhead of dictionary key insertion. The speedup is most pronounced when `limit=None` (17.3% faster in tests) since it avoids the conditional assignment entirely. Even when `limit` has a value, creating the full dictionary at once is more efficient than incremental construction.

The optimization works well across all test patterns, showing consistent 8-17% improvements for individual calls and 3-15% improvements for batch operations, making it particularly effective for high-frequency serialization scenarios.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 October 22, 2025 04:39
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Oct 22, 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.

0 participants