⚡️ Speed up function funcA by 3,983%

[codeflash-ai]

📄 3,983% (39.83x) speedup for funcA in code_to_optimize/code_directories/simple_tracer_e2e/workload.py

⏱️ Runtime : 52.4 milliseconds → 1.28 milliseconds (best of 325 runs)

📝 Explanation and details

Here's an optimized version of your program.
Optimization notes:

• The for i in range(number * 100): k += i loop can be replaced using the arithmetic series sum formula for integers: sum = n*(n-1)//2 (from 0 to n-1), which is much faster.
• j = sum(range(number)) is similarly just number*(number-1)//2.
• " ".join(str(i) for i in range(number)) can be sped up with a map object instead of a generator expression.
• The number = number if number < 1000 else 1000 line is already optimal for a single expression.

Here is the optimized version, with all comments preserved as per your instructions.
Function signature and all outputs remain unchanged.

Key speedups:

• k and j computation now take constant time.
• join is as fast as possible without using C extensions.

Let me know if further improvements are required or if the join result needs to be in a different format for very large number!

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 46 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

# 1. Basic Test Cases

def test_funcA_zero():
    # Test with number = 0 (should return empty string)
    codeflash_output = funcA(0) # 2.60μs -> 1.99μs (30.1% faster)

def test_funcA_one():
    # Test with number = 1 (should return "0")
    codeflash_output = funcA(1) # 5.89μs -> 2.38μs (147% faster)

def test_funcA_small_positive():
    # Test with small positive number
    codeflash_output = funcA(3) # 11.9μs -> 2.61μs (356% faster)
    codeflash_output = funcA(5) # 16.3μs -> 1.35μs (1103% faster)

def test_funcA_typical():
    # Test with a typical number within the limit
    codeflash_output = funcA(10) # 34.3μs -> 3.17μs (979% faster)

# 2. Edge Test Cases

def test_funcA_negative():
    # Test with negative number (should return empty string, as range(-3) is empty)
    codeflash_output = funcA(-3) # 2.43μs -> 1.89μs (28.6% faster)

def test_funcA_limit_boundary():
    # Test with number right at the limit (999)
    expected = " ".join(str(i) for i in range(999))
    codeflash_output = funcA(999) # 3.38ms -> 76.0μs (4349% faster)

def test_funcA_limit_exact():
    # Test with number at the limit (1000)
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1000) # 3.38ms -> 75.7μs (4369% faster)

def test_funcA_above_limit():
    # Test with number above the limit (should cap at 1000)
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1001) # 3.35ms -> 75.7μs (4323% faster)
    codeflash_output = funcA(5000) # 3.37ms -> 74.5μs (4418% faster)

def test_funcA_large_negative():
    # Test with a large negative number
    codeflash_output = funcA(-1000) # 2.46μs -> 2.14μs (15.0% faster)

def test_funcA_non_integer_input():
    # Test with a float input (should raise TypeError, as range expects int)
    with pytest.raises(TypeError):
        funcA(3.5)

    with pytest.raises(TypeError):
        funcA("10")  # string input

def test_funcA_bool_input():
    # Test with boolean input (True is 1, False is 0)
    codeflash_output = funcA(True) # 6.43μs -> 2.85μs (125% faster)
    codeflash_output = funcA(False) # 1.62μs -> 1.37μs (18.2% faster)

# 3. Large Scale Test Cases

def test_funcA_large_scale_just_below_limit():
    # Test with a large input just below the cap
    n = 999
    codeflash_output = funcA(n); result = codeflash_output # 3.38ms -> 78.7μs (4194% faster)
    parts = result.split()

def test_funcA_large_scale_at_limit():
    # Test with the maximum allowed input
    n = 1000
    codeflash_output = funcA(n); result = codeflash_output # 3.34ms -> 77.8μs (4194% faster)
    parts = result.split()

def test_funcA_large_scale_above_limit():
    # Test with input well above the cap
    n = 9999
    codeflash_output = funcA(n); result = codeflash_output # 3.36ms -> 77.5μs (4229% faster)
    parts = result.split()

def test_funcA_performance_reasonable():
    # Test that the function completes quickly for large allowed input
    n = 1000
    import time
    start = time.time()
    codeflash_output = funcA(n); result = codeflash_output # 3.38ms -> 77.4μs (4272% faster)
    elapsed = time.time() - start

# 4. Additional Edge Cases

def test_funcA_input_is_none():
    # None input should raise TypeError
    with pytest.raises(TypeError):
        funcA(None)

def test_funcA_input_is_list():
    # List input should raise TypeError
    with pytest.raises(TypeError):
        funcA([1,2,3])

def test_funcA_input_is_dict():
    # Dict input should raise TypeError
    with pytest.raises(TypeError):
        funcA({'a': 1})


def test_funcA_input_is_complex():
    # Complex input should raise TypeError
    with pytest.raises(TypeError):
        funcA(3+4j)
# 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 an empty string)
    codeflash_output = funcA(0) # 2.65μs -> 2.10μs (25.7% faster)

def test_funcA_one():
    # Test with number = 1 (should return "0")
    codeflash_output = funcA(1) # 5.97μs -> 2.41μs (147% faster)

def test_funcA_small_number():
    # Test with number = 5 (should return "0 1 2 3 4")
    codeflash_output = funcA(5) # 18.3μs -> 2.89μs (535% faster)

def test_funcA_typical_number():
    # Test with number = 10 (should return "0 1 2 3 4 5 6 7 8 9")
    codeflash_output = funcA(10) # 34.6μs -> 3.19μs (986% faster)

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

def test_funcA_negative_number():
    # Test with a negative number (should behave like range(negative) == empty)
    codeflash_output = funcA(-5) # 2.52μs -> 1.97μs (27.4% faster)

def test_funcA_large_number_exactly_1000():
    # Test with number = 1000 (should return numbers 0 to 999)
    codeflash_output = funcA(1000); result = codeflash_output # 3.34ms -> 78.6μs (4146% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_large_number_above_1000():
    # Test with number > 1000 (should be capped at 1000)
    codeflash_output = funcA(1500); result = codeflash_output # 3.36ms -> 78.4μs (4180% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_number_is_999():
    # Test with number just below the cap
    codeflash_output = funcA(999); result = codeflash_output # 3.34ms -> 77.8μs (4195% faster)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_number_is_1001():
    # Test with number just above the cap
    codeflash_output = funcA(1001); result = codeflash_output # 3.39ms -> 77.6μs (4273% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_float_input():
    # Test with float input (should raise TypeError)
    with pytest.raises(TypeError):
        funcA(5.5)

def test_funcA_string_input():
    # Test with string input (should raise TypeError)
    with pytest.raises(TypeError):
        funcA("10")

def test_funcA_none_input():
    # Test with None input (should raise TypeError)
    with pytest.raises(TypeError):
        funcA(None)

def test_funcA_boolean_input():
    # Test with boolean input (should treat True as 1, False as 0)
    codeflash_output = funcA(True) # 6.32μs -> 2.83μs (124% faster)
    codeflash_output = funcA(False) # 1.70μs -> 1.41μs (20.5% faster)

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

def test_funcA_large_scale_500():
    # Test with a large but manageable number (500)
    codeflash_output = funcA(500); result = codeflash_output # 1.61ms -> 40.4μs (3891% faster)
    expected = " ".join(str(i) for i in range(500))

def test_funcA_large_scale_999():
    # Test with number = 999 (just below the cap)
    codeflash_output = funcA(999); result = codeflash_output # 3.35ms -> 77.5μs (4216% faster)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_large_scale_1000():
    # Test with number = 1000 (at the cap)
    codeflash_output = funcA(1000); result = codeflash_output # 3.36ms -> 77.2μs (4244% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_performance():
    # Test that the function does not take too long with large input
    import time
    start = time.time()
    funcA(1000)
    end = time.time()

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

def test_funcA_input_mutation():
    # Test that input is not mutated (not relevant for int, but for completeness)
    n = 5
    funcA(n)

def test_funcA_output_content():
    # Spot check that numbers are separated by single spaces, no trailing space
    codeflash_output = funcA(4); result = codeflash_output # 14.9μs -> 2.69μs (452% faster)

def test_funcA_unicode_handling():
    # Ensure that the function does not break with unicode input (should TypeError)
    with pytest.raises(TypeError):
        funcA("五")

def test_funcA_input_is_list():
    # Passing a list should raise TypeError
    with pytest.raises(TypeError):
        funcA([1, 2, 3])

def test_funcA_input_is_dict():
    # Passing a dict should raise TypeError
    with pytest.raises(TypeError):
        funcA({'a': 1})
# 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-mcdq6gkh and push.