⚡️ Speed up function funcA by 4,082%

[codeflash-ai]

📄 4,082% (40.82x) speedup for funcA in code_to_optimize/code_directories/simple_tracer_e2e/workload.py

⏱️ Runtime : 71.9 milliseconds → 1.72 milliseconds (best of 317 runs)

📝 Explanation and details

Here is an optimized version of your funcA function, preserving the result and behavior, but with significantly improved runtime for all major hot spots indicated in your profile.
The slowest parts are the explicit for loop and " ".join(str(i) ...) construction. The for-loop is simply summing; we can use the arithmetic formula for summing 0..N-1. For joining, generate all the needed numbers as strings, then join (avoiding repeated generator and multiple function calls).

Key optimizations.

• Used arithmetic sum for k instead of a for loop, reducing O(N) to O(1).
• Used the same formula for j.
• Used map(str, range(number)) directly in join, which is faster than a generator with str(i).

Timing Impact: Nearly all runtime was spent in the explicit for loop and string join; both are now as fast as possible in pure Python.
Return value and side effects are untouched.
All original comments were either obsolete due to the optimization or are not included as per instructions, unless affected by the code rewrite.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 64 Passed
⏪ Replay Tests	✅ 3 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import pytest  # used for our unit tests
from workload import funcA

# unit tests

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

def test_funcA_zero():
    # Test with input 0, should return an empty string (no numbers)
    codeflash_output = funcA(0) # 2.41μs -> 1.86μs (29.6% faster)

def test_funcA_one():
    # Test with input 1, should return '0'
    codeflash_output = funcA(1) # 5.56μs -> 2.25μs (147% faster)

def test_funcA_small_number():
    # Test with a small positive number
    codeflash_output = funcA(5) # 18.2μs -> 2.77μs (557% faster)

def test_funcA_typical_number():
    # Test with a typical number in the middle of the range
    codeflash_output = funcA(10) # 34.5μs -> 3.08μs (1021% faster)

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

def test_funcA_negative_number():
    # Negative input should result in an empty string (range(negative) is empty)
    codeflash_output = funcA(-5) # 2.33μs -> 1.99μs (17.1% faster)

def test_funcA_just_below_limit():
    # Input just below the 1000 cap
    codeflash_output = funcA(999); result = codeflash_output # 3.41ms -> 77.2μs (4315% faster)
    # Should contain numbers from 0 to 998 (999 numbers)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_at_limit():
    # Input at the 1000 cap
    codeflash_output = funcA(1000); result = codeflash_output # 3.42ms -> 77.2μs (4334% faster)
    # Should contain numbers from 0 to 999 (1000 numbers)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_above_limit():
    # Input above the cap should be clamped to 1000
    codeflash_output = funcA(1500); result = codeflash_output # 3.37ms -> 76.5μs (4307% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_large_negative():
    # Large negative input should still return an empty string
    codeflash_output = funcA(-10000) # 2.46μs -> 2.20μs (11.8% faster)

def test_funcA_input_is_limit_boundary():
    # Input exactly 1000 should not exceed the cap
    codeflash_output = funcA(1000); result = codeflash_output # 3.43ms -> 77.0μs (4357% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_input_is_limit_plus_one():
    # Input just above the cap should be capped
    codeflash_output = funcA(1001); result = codeflash_output # 3.40ms -> 76.3μs (4358% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_input_is_one_less_than_cap():
    # Input just below the cap
    codeflash_output = funcA(999); result = codeflash_output # 3.40ms -> 76.8μs (4322% faster)
    expected = " ".join(str(i) for i in range(999))

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

def test_funcA_large_input():
    # Test with a large input at the cap (1000)
    codeflash_output = funcA(1000); result = codeflash_output # 3.42ms -> 76.6μs (4361% faster)

def test_funcA_large_input_above_cap():
    # Test with a large input above the cap (should be capped at 1000)
    codeflash_output = funcA(2000); result = codeflash_output # 3.41ms -> 76.5μs (4358% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_performance_under_limit():
    # Test performance and correctness for a mid-large value
    n = 500
    codeflash_output = funcA(n); result = codeflash_output # 1.66ms -> 39.7μs (4082% faster)
    expected = " ".join(str(i) for i in range(n))

def test_funcA_performance_at_limit():
    # Test performance and correctness at the cap
    n = 1000
    codeflash_output = funcA(n); result = codeflash_output # 3.44ms -> 77.3μs (4349% faster)
    expected = " ".join(str(i) for i in range(n))

# ---------------------
# Additional Robustness Cases
# ---------------------

@pytest.mark.parametrize("input_value,expected", [
    (0, ""),
    (1, "0"),
    (2, "0 1"),
    (10, "0 1 2 3 4 5 6 7 8 9"),
    (999, " ".join(str(i) for i in range(999))),
    (1000, " ".join(str(i) for i in range(1000))),
    (1001, " ".join(str(i) for i in range(1000))),
    (-1, ""),
    (-100, ""),
])
def test_funcA_various_inputs(input_value, expected):
    # Parametrized test to cover a variety of scenarios
    codeflash_output = funcA(input_value) # 2.29μs -> 1.97μs (16.2% faster)

def test_funcA_type_handling():
    # Test with a float that is an integer value
    with pytest.raises(TypeError):
        funcA(5.0)
    # Test with a string input
    with pytest.raises(TypeError):
        funcA("10")
    # Test with None
    with pytest.raises(TypeError):
        funcA(None)
    # Test with a list
    with pytest.raises(TypeError):
        funcA([1, 2, 3])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import pytest  # used for our unit tests
from workload import funcA

# unit tests

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

def test_funcA_zero():
    # Test with number = 0 (should return empty string)
    codeflash_output = funcA(0) # 2.50μs -> 2.00μs (25.1% faster)

def test_funcA_one():
    # Test with number = 1 (should return "0")
    codeflash_output = funcA(1) # 5.61μs -> 2.31μs (142% faster)

def test_funcA_small_number():
    # Test with a small number (e.g., 5)
    codeflash_output = funcA(5) # 18.2μs -> 2.81μs (549% faster)

def test_funcA_typical_number():
    # Test with a typical number (e.g., 10)
    codeflash_output = funcA(10) # 34.1μs -> 3.12μs (993% faster)

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

def test_funcA_negative_number():
    # Negative input should produce empty string (since range(negative) is empty)
    codeflash_output = funcA(-5) # 2.30μs -> 1.94μs (18.6% faster)

def test_funcA_large_number_exactly_1000():
    # Input exactly at the 1000 threshold, should return "0 1 ... 999"
    codeflash_output = funcA(1000); result = codeflash_output # 3.40ms -> 86.4μs (3840% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_large_number_above_1000():
    # Input above 1000 should be capped at 1000
    codeflash_output = funcA(1500); result = codeflash_output # 3.43ms -> 76.6μs (4380% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_large_negative():
    # Very large negative input should still produce empty string
    codeflash_output = funcA(-100000) # 2.46μs -> 2.21μs (11.3% faster)

def test_funcA_float_input():
    # Floats are not supported, should raise TypeError
    with pytest.raises(TypeError):
        funcA(5.5)

def test_funcA_string_input():
    # Strings are not supported, should raise TypeError
    with pytest.raises(TypeError):
        funcA("10")

def test_funcA_none_input():
    # None is not supported, should raise TypeError
    with pytest.raises(TypeError):
        funcA(None)

def test_funcA_boolean_input():
    # Boolean input: True is 1, False is 0
    codeflash_output = funcA(True) # 6.27μs -> 2.92μs (115% faster)
    codeflash_output = funcA(False) # 1.60μs -> 1.24μs (29.1% faster)

def test_funcA_mutation_wrong_separator():
    # Ensure separator is exactly a single space and not e.g. comma or double space
    codeflash_output = funcA(3); result = codeflash_output # 11.7μs -> 2.71μs (331% faster)

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

def test_funcA_large_scale_999():
    # Test with large input just below the cap
    n = 999
    codeflash_output = funcA(n); result = codeflash_output # 3.35ms -> 79.2μs (4133% faster)
    expected = " ".join(str(i) for i in range(n))
    # Check first, middle, last
    parts = result.split(" ")

def test_funcA_large_scale_1000():
    # Test with input at the cap
    n = 1000
    codeflash_output = funcA(n); result = codeflash_output # 3.37ms -> 76.8μs (4295% faster)
    expected = " ".join(str(i) for i in range(n))
    # Check first, middle, last
    parts = result.split(" ")

def test_funcA_large_scale_above_cap():
    # Test with input well above the cap
    n = 2000
    codeflash_output = funcA(n); result = codeflash_output # 3.42ms -> 77.2μs (4338% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_performance():
    # Not a true performance test, but ensures function returns quickly for large n
    import time
    n = 1000
    start = time.time()
    codeflash_output = funcA(n); result = codeflash_output # 3.40ms -> 77.3μs (4299% faster)
    end = time.time()

# -------------------
# Miscellaneous/Mutation Tests
# -------------------

def test_funcA_mutation_missing_zero():
    # Ensure that the sequence always starts with "0" for n > 0
    for n in [1, 10, 100]:
        codeflash_output = funcA(n); result = codeflash_output

def test_funcA_mutation_missing_last():
    # Ensure that the sequence always ends with str(n-1) for n > 0
    for n in [1, 10, 100]:
        codeflash_output = funcA(n); result = codeflash_output

def test_funcA_mutation_off_by_one():
    # Ensure that the number of items is exactly n for various values
    for n in [0, 1, 2, 5, 10, 100, 999, 1000]:
        codeflash_output = funcA(n); result = codeflash_output
        if n == 0:
            pass
        else:
            pass

def test_funcA_mutation_wrong_order():
    # Ensure the sequence is strictly increasing by 1
    for n in [2, 10, 100]:
        codeflash_output = funcA(n); result = codeflash_output
        parts = result.split(" ")
        for i in range(1, len(parts)):
            pass
# 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-funcA-mcjhcuh5 and push.