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⚡️ Speed up method BenchmarkDetail.to_dict by 71% in PR #59 (codeflash-trace-decorator) #92

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⚡️ Speed up method BenchmarkDetail.to_dict by 71% in PR #59 (codeflash-trace-decorator) #92

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@codeflash-ai codeflash-ai bot commented Mar 26, 2025

⚡️ This pull request contains optimizations for PR #59

If you approve this dependent PR, these changes will be merged into the original PR branch codeflash-trace-decorator.

This PR will be automatically closed if the original PR is merged.

📄 71% (0.71x) speedup for BenchmarkDetail.to_dict in codeflash/models/models.py

⏱️ Runtime : 549 microseconds → 321 microseconds (best of 224 runs)

📝 Explanation and details

The BenchmarkDetail class is missing specific fields in its dataclass declaration. Additionally, instead of serializing the object's attributes manually in the to_dict method, we can utilize Pydantic's built-in features to achieve a more efficient and concise solution.

Changes made.

  1. Specified fields in the BenchmarkDetail dataclass for better clarity and initialization.
  2. Used the __dict__ built-in method to convert the dataclass instance to a dictionary, which is generally faster and more concise.

✅ Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests ✅ 2029 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage
🌀 Generated Regression Tests Details 
from __future__ import annotations

# imports
import pytest  # used for our unit tests
from codeflash.models.models import BenchmarkDetail
from pydantic.dataclasses import dataclass

# unit tests

def test_standard_inputs():
    # Test with typical benchmark details
    benchmark = BenchmarkDetail("Benchmark1", "test_func1", "10s", "5s", 50.0)
    expected = {
        "benchmark_name": "Benchmark1",
        "test_function": "test_func1",
        "original_timing": "10s",
        "expected_new_timing": "5s",
        "speedup_percent": 50.0
    }
    codeflash_output = benchmark.to_dict()

def test_empty_strings():
    # Test with empty strings
    benchmark = BenchmarkDetail("", "", "", "", 0.0)
    expected = {
        "benchmark_name": "",
        "test_function": "",
        "original_timing": "",
        "expected_new_timing": "",
        "speedup_percent": 0.0
    }
    codeflash_output = benchmark.to_dict()

def test_zero_speedup():
    # Test with zero speedup
    benchmark = BenchmarkDetail("Benchmark3", "test_func3", "10s", "10s", 0.0)
    expected = {
        "benchmark_name": "Benchmark3",
        "test_function": "test_func3",
        "original_timing": "10s",
        "expected_new_timing": "10s",
        "speedup_percent": 0.0
    }
    codeflash_output = benchmark.to_dict()

def test_negative_speedup():
    # Test with negative speedup
    benchmark = BenchmarkDetail("Benchmark4", "test_func4", "10s", "15s", -50.0)
    expected = {
        "benchmark_name": "Benchmark4",
        "test_function": "test_func4",
        "original_timing": "10s",
        "expected_new_timing": "15s",
        "speedup_percent": -50.0
    }
    codeflash_output = benchmark.to_dict()

def test_special_characters():
    # Test with special characters in benchmark and function names
    benchmark = BenchmarkDetail("Benchmark!@#", "test_func!@#", "10s", "5s", 50.0)
    expected = {
        "benchmark_name": "Benchmark!@#",
        "test_function": "test_func!@#",
        "original_timing": "10s",
        "expected_new_timing": "5s",
        "speedup_percent": 50.0
    }
    codeflash_output = benchmark.to_dict()

def test_large_scale():
    # Test with large benchmark and function names
    benchmark = BenchmarkDetail("B" * 1000, "F" * 1000, "10s", "5s", 50.0)
    expected = {
        "benchmark_name": "B" * 1000,
        "test_function": "F" * 1000,
        "original_timing": "10s",
        "expected_new_timing": "5s",
        "speedup_percent": 50.0
    }
    codeflash_output = benchmark.to_dict()

def test_high_precision_speedup():
    # Test with high precision speedup
    benchmark = BenchmarkDetail("Benchmark6", "test_func6", "10s", "5s", 50.123456789)
    expected = {
        "benchmark_name": "Benchmark6",
        "test_function": "test_func6",
        "original_timing": "10s",
        "expected_new_timing": "5s",
        "speedup_percent": 50.123456789
    }
    codeflash_output = benchmark.to_dict()

def test_special_characters_unicode():
    # Test with unicode characters in benchmark and function names
    benchmark = BenchmarkDetail("BenchmarkÜñîçødë", "test_funcÜñîçødë", "10s", "5s", 50.0)
    expected = {
        "benchmark_name": "BenchmarkÜñîçødë",
        "test_function": "test_funcÜñîçødë",
        "original_timing": "10s",
        "expected_new_timing": "5s",
        "speedup_percent": 50.0
    }
    codeflash_output = benchmark.to_dict()

def test_boundary_conditions_inf():
    # Test with float('inf') for speedup
    benchmark = BenchmarkDetail("Benchmark9", "test_func9", "10s", "5s", float('inf'))
    expected = {
        "benchmark_name": "Benchmark9",
        "test_function": "test_func9",
        "original_timing": "10s",
        "expected_new_timing": "5s",
        "speedup_percent": float('inf')
    }
    codeflash_output = benchmark.to_dict()

def test_boundary_conditions_nan():
    # Test with float('nan') for speedup
    benchmark = BenchmarkDetail("Benchmark11", "test_func11", "10s", "5s", float('nan'))
    codeflash_output = benchmark.to_dict(); result = codeflash_output

def test_consistency():
    # Test consistent output for identical inputs
    benchmark1 = BenchmarkDetail("Benchmark12", "test_func12", "10s", "5s", 50.0)
    benchmark2 = BenchmarkDetail("Benchmark12", "test_func12", "10s", "5s", 50.0)
    codeflash_output = benchmark1.to_dict()

def test_performance_large_number_of_instances():
    # Test performance with a large number of instances
    benchmarks = [BenchmarkDetail(f"Benchmark{i}", f"test_func{i}", "10s", "5s", 50.0) for i in range(1000)]
    for benchmark in benchmarks:
        codeflash_output = benchmark.to_dict()



from __future__ import annotations

# imports
import pytest  # used for our unit tests
from codeflash.models.models import BenchmarkDetail
from pydantic.dataclasses import dataclass

# unit tests

# Basic Valid Input
def test_basic_valid_input():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark1",
        test_function="test_func",
        original_timing="100ms",
        expected_new_timing="80ms",
        speedup_percent=20.0
    )
    expected_dict = {
        "benchmark_name": "Benchmark1",
        "test_function": "test_func",
        "original_timing": "100ms",
        "expected_new_timing": "80ms",
        "speedup_percent": 20.0
    }
    codeflash_output = benchmark.to_dict()

# Empty Strings
def test_empty_strings():
    benchmark = BenchmarkDetail(
        benchmark_name="",
        test_function="",
        original_timing="",
        expected_new_timing="",
        speedup_percent=0.0
    )
    expected_dict = {
        "benchmark_name": "",
        "test_function": "",
        "original_timing": "",
        "expected_new_timing": "",
        "speedup_percent": 0.0
    }
    codeflash_output = benchmark.to_dict()

# Special Characters
def test_special_characters():
    benchmark = BenchmarkDetail(
        benchmark_name="Bench!@#123",
        test_function="test_func$",
        original_timing="100ms#",
        expected_new_timing="80ms*",
        speedup_percent=20.0
    )
    expected_dict = {
        "benchmark_name": "Bench!@#123",
        "test_function": "test_func$",
        "original_timing": "100ms#",
        "expected_new_timing": "80ms*",
        "speedup_percent": 20.0
    }
    codeflash_output = benchmark.to_dict()

# Large Strings
def test_large_strings():
    benchmark = BenchmarkDetail(
        benchmark_name="B" * 1000,
        test_function="T" * 1000,
        original_timing="O" * 1000,
        expected_new_timing="E" * 1000,
        speedup_percent=20.0
    )
    expected_dict = {
        "benchmark_name": "B" * 1000,
        "test_function": "T" * 1000,
        "original_timing": "O" * 1000,
        "expected_new_timing": "E" * 1000,
        "speedup_percent": 20.0
    }
    codeflash_output = benchmark.to_dict()

# Negative and Zero Speedup Percent
def test_negative_speedup_percent():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark1",
        test_function="test_func",
        original_timing="100ms",
        expected_new_timing="110ms",
        speedup_percent=-10.0
    )
    expected_dict = {
        "benchmark_name": "Benchmark1",
        "test_function": "test_func",
        "original_timing": "100ms",
        "expected_new_timing": "110ms",
        "speedup_percent": -10.0
    }
    codeflash_output = benchmark.to_dict()

def test_zero_speedup_percent():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark1",
        test_function="test_func",
        original_timing="100ms",
        expected_new_timing="100ms",
        speedup_percent=0.0
    )
    expected_dict = {
        "benchmark_name": "Benchmark1",
        "test_function": "test_func",
        "original_timing": "100ms",
        "expected_new_timing": "100ms",
        "speedup_percent": 0.0
    }
    codeflash_output = benchmark.to_dict()

# High Precision Floats
def test_high_precision_floats():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark1",
        test_function="test_func",
        original_timing="100ms",
        expected_new_timing="80ms",
        speedup_percent=20.123456789
    )
    expected_dict = {
        "benchmark_name": "Benchmark1",
        "test_function": "test_func",
        "original_timing": "100ms",
        "expected_new_timing": "80ms",
        "speedup_percent": 20.123456789
    }
    codeflash_output = benchmark.to_dict()

# Non-Standard Timing Formats
def test_non_standard_timing_formats():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark1",
        test_function="test_func",
        original_timing="1min 40sec",
        expected_new_timing="1min 20sec",
        speedup_percent=20.0
    )
    expected_dict = {
        "benchmark_name": "Benchmark1",
        "test_function": "test_func",
        "original_timing": "1min 40sec",
        "expected_new_timing": "1min 20sec",
        "speedup_percent": 20.0
    }
    codeflash_output = benchmark.to_dict()

# Unicode and Internationalization
def test_unicode_internationalization():
    benchmark = BenchmarkDetail(
        benchmark_name="ベンチマーク",
        test_function="テスト関数",
        original_timing="100ミリ秒",
        expected_new_timing="80ミリ秒",
        speedup_percent=20.0
    )
    expected_dict = {
        "benchmark_name": "ベンチマーク",
        "test_function": "テスト関数",
        "original_timing": "100ミリ秒",
        "expected_new_timing": "80ミリ秒",
        "speedup_percent": 20.0
    }
    codeflash_output = benchmark.to_dict()

# Large Number of Instances
def test_large_number_of_instances():
    instances = [
        BenchmarkDetail(
            benchmark_name=f"Benchmark{i}",
            test_function=f"test_func{i}",
            original_timing=f"{i}ms",
            expected_new_timing=f"{i-20}ms",
            speedup_percent=20.0
        ) for i in range(1000)
    ]
    for i, benchmark in enumerate(instances):
        expected_dict = {
            "benchmark_name": f"Benchmark{i}",
            "test_function": f"test_func{i}",
            "original_timing": f"{i}ms",
            "expected_new_timing": f"{i-20}ms",
            "speedup_percent": 20.0
        }
        codeflash_output = benchmark.to_dict()

# Consistency Check
def test_consistency_check():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark1",
        test_function="test_func",
        original_timing="100ms",
        expected_new_timing="80ms",
        speedup_percent=20.0
    )
    codeflash_output = benchmark.to_dict(); result_dict = codeflash_output

# Extremely High Speedup Percent
def test_extremely_high_speedup_percent():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark1",
        test_function="test_func",
        original_timing="100ms",
        expected_new_timing="10ms",
        speedup_percent=900.0
    )
    expected_dict = {
        "benchmark_name": "Benchmark1",
        "test_function": "test_func",
        "original_timing": "100ms",
        "expected_new_timing": "10ms",
        "speedup_percent": 900.0
    }
    codeflash_output = benchmark.to_dict()

# Non-ASCII Characters in Strings
def test_non_ascii_characters():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark🚀",
        test_function="test_func",
        original_timing="100ms",
        expected_new_timing="80ms",
        speedup_percent=20.0
    )
    expected_dict = {
        "benchmark_name": "Benchmark🚀",
        "test_function": "test_func",
        "original_timing": "100ms",
        "expected_new_timing": "80ms",
        "speedup_percent": 20.0
    }
    codeflash_output = benchmark.to_dict()

# Extremely Long Floating-Point Numbers
def test_extremely_long_floats():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark1",
        test_function="test_func",
        original_timing="100ms",
        expected_new_timing="80ms",
        speedup_percent=20.12345678901234567890
    )
    expected_dict = {
        "benchmark_name": "Benchmark1",
        "test_function": "test_func",
        "original_timing": "100ms",
        "expected_new_timing": "80ms",
        "speedup_percent": 20.12345678901234567890
    }
    codeflash_output = benchmark.to_dict()

# Attributes with None Values


def test_attributes_with_mixed_content():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark1_2023",
        test_function="test_func_v2",
        original_timing="100ms_approx",
        expected_new_timing="80ms_approx",
        speedup_percent=20.0
    )
    expected_dict = {
        "benchmark_name": "Benchmark1_2023",
        "test_function": "test_func_v2",
        "original_timing": "100ms_approx",
        "expected_new_timing": "80ms_approx",
        "speedup_percent": 20.0
    }
    codeflash_output = benchmark.to_dict()

# Attributes with Whitespace
def test_attributes_with_whitespace():
    benchmark = BenchmarkDetail(
        benchmark_name="  Benchmark1  ",
        test_function="  test_func  ",
        original_timing="  100ms  ",
        expected_new_timing="  80ms  ",
        speedup_percent=20.0
    )
    expected_dict = {
        "benchmark_name": "  Benchmark1  ",
        "test_function": "  test_func  ",
        "original_timing": "  100ms  ",
        "expected_new_timing": "  80ms  ",
        "speedup_percent": 20.0
    }
    codeflash_output = benchmark.to_dict()

# Attributes with Escape Characters
def test_attributes_with_escape_characters():
    benchmark = BenchmarkDetail(
        benchmark_name="Benchmark\n1",
        test_function="test_func\t",
        original_timing="100ms\n",
        expected_new_timing="80ms\t",
        speedup_percent=20.0
    )
    expected_dict = {
        "benchmark_name": "Benchmark\n1",
        "test_function": "test_func\t",
        "original_timing": "100ms\n",
        "expected_new_timing": "80ms\t",
        "speedup_percent": 20.0
    }
    codeflash_output = benchmark.to_dict()

# Attributes with Only Whitespace
def test_attributes_with_only_whitespace():
    benchmark = BenchmarkDetail(
        benchmark_name="   ",
        test_function="   ",
        original_timing="   ",
        expected_new_timing="   ",
        speedup_percent=0.0
    )
    expected_dict = {
        "benchmark_name": "   ",
        "test_function": "   ",
        "original_timing": "   ",
        "expected_new_timing": "   ",
        "speedup_percent": 0.0
    }
    codeflash_output = benchmark.to_dict()

# Attributes with JSON-like Strings
def test_attributes_with_json_like_strings():
    benchmark = BenchmarkDetail(
        benchmark_name='{"name": "Benchmark1"}',
        test_function='{"func": "test_func"}',
        original_timing='{"time": "100ms"}',
        expected_new_timing='{"time": "80ms"}',
        speedup_percent=20.0
    )
    expected_dict = {
        "benchmark_name": '{"name": "Benchmark1"}',
        "test_function": '{"func": "test_func"}',
        "original_timing": '{"time": "100ms"}',
        "expected_new_timing": '{"time": "80ms"}',
        "speedup_percent": 20.0
    }
    codeflash_output = benchmark.to_dict()
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

from codeflash.models.models import BenchmarkDetail

def test_BenchmarkDetail_to_dict():
    BenchmarkDetail.to_dict(BenchmarkDetail('', '', '', '', float('nan')))

To edit these changes git checkout codeflash/optimize-pr59-2025-03-26T20.44.24 and push.

Codeflash

@codeflash-ai
⚡️ Speed up method BenchmarkDetail.to_dict by 71% in PR #59 (`codef…
7e5e138 
…lash-trace-decorator`)

The `BenchmarkDetail` class is missing specific fields in its dataclass declaration. Additionally, instead of serializing the object's attributes manually in the `to_dict` method, we can utilize Pydantic's built-in features to achieve a more efficient and concise solution.



### Changes made.
1. Specified fields in the `BenchmarkDetail` dataclass for better clarity and initialization.
2. Used the `__dict__` built-in method to convert the dataclass instance to a dictionary, which is generally faster and more concise.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Mar 26, 2025
@codeflash-ai codeflash-ai bot mentioned this pull request Mar 26, 2025
Merged
@alvin-r alvin-r closed this Mar 26, 2025
@codeflash-ai codeflash-ai bot deleted the codeflash/optimize-pr59-2025-03-26T20.44.24 branch March 26, 2025 20:57
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