⚡️ Speed up function funcA by 4,438%

[codeflash-ai]

📄 4,438% (44.38x) speedup for funcA in code_to_optimize/code_directories/simple_tracer_e2e/workload.py

⏱️ Runtime : 57.8 milliseconds → 1.27 milliseconds (best of 367 runs)

📝 Explanation and details

Here’s an optimized version of your code. Improvements.

• number = min(number, 1000) is slightly faster and clearer than the original assignment.
• Remove the unnecessary computation of k (since it is not used anywhere in the function).
• Preallocate a list of string representations for " ".join() rather than using a generator, which is marginally faster when the range is not huge.
• If number is often small (<10000), the list allocation is very fast and not a memory/bottleneck concern for these sizes.

If k or j was needed for side effects, let me know—otherwise, as in your original code, they are unused and should be omitted entirely for maximum performance.

Here’s the rewritten program.

If you do want the values of k and j to be computed and returned/used, let me know, and I’ll preserve their computation in the most efficient way. This current version exactly matches the function's original behavior (returns the joined string).

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 48 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
    codeflash_output = funcA(0) # 2.56μs -> 1.47μs (74.1% faster)

def test_funcA_one():
    # Test with input 1: should return "0"
    codeflash_output = funcA(1) # 5.89μs -> 2.01μs (193% faster)

def test_funcA_small_number():
    # Test with a small number
    codeflash_output = funcA(3) # 11.9μs -> 2.24μs (429% faster)
    codeflash_output = funcA(5) # 16.4μs -> 1.27μs (1188% faster)

def test_funcA_typical_number():
    # Test with a typical number in the middle of the allowed range
    codeflash_output = funcA(10) # 34.6μs -> 2.59μs (1234% faster)

# ---------------------------
# EDGE TEST CASES
# ---------------------------

def test_funcA_negative_number():
    # Negative numbers: range(n) is empty for n <= 0, so should return empty string
    codeflash_output = funcA(-1) # 2.48μs -> 1.42μs (73.9% faster)
    codeflash_output = funcA(-100) # 1.21μs -> 661ns (83.4% faster)

def test_funcA_just_below_limit():
    # Test with number just below the limit
    n = 999
    expected = " ".join(str(i) for i in range(n))
    codeflash_output = funcA(n) # 3.37ms -> 69.8μs (4730% faster)

def test_funcA_at_limit():
    # Test with number at the limit (1000)
    n = 1000
    expected = " ".join(str(i) for i in range(n))
    codeflash_output = funcA(n) # 3.40ms -> 69.7μs (4778% faster)

def test_funcA_above_limit():
    # Test with number above the limit (should be capped at 1000)
    n = 1500
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(n) # 3.35ms -> 69.5μs (4716% faster)

def test_funcA_large_negative():
    # Large negative input should also return empty string
    codeflash_output = funcA(-999999) # 2.55μs -> 1.42μs (79.6% faster)

def test_funcA_non_integer_input():
    # Non-integer input: should raise TypeError since range() requires integer
    with pytest.raises(TypeError):
        funcA(3.5)
    with pytest.raises(TypeError):
        funcA("10")
    with pytest.raises(TypeError):
        funcA(None)

def test_funcA_boolean_input():
    # Boolean input: True is 1, False is 0
    codeflash_output = funcA(True) # 6.40μs -> 2.20μs (190% faster)
    codeflash_output = funcA(False) # 1.71μs -> 862ns (98.7% faster)

# ---------------------------
# LARGE SCALE TEST CASES
# ---------------------------

def test_funcA_large_but_within_limit():
    # Test with a large number (close to the limit)
    n = 999
    codeflash_output = funcA(n); result = codeflash_output # 3.39ms -> 71.7μs (4631% faster)

def test_funcA_at_maximum():
    # Test at the absolute maximum allowed (1000)
    n = 1000
    codeflash_output = funcA(n); result = codeflash_output # 3.38ms -> 71.0μs (4657% faster)

def test_funcA_above_maximum():
    # Test with a number above the maximum allowed (should be capped at 1000)
    n = 2000
    codeflash_output = funcA(n); result = codeflash_output # 3.35ms -> 70.8μs (4638% faster)

def test_funcA_performance():
    # Test performance for large n, should not be too slow
    n = 1000
    codeflash_output = funcA(n); result = codeflash_output # 3.30ms -> 70.5μs (4576% faster)

# ---------------------------
# ADDITIONAL EDGE CASES
# ---------------------------

def test_funcA_input_is_limit_boundary():
    # Test with input exactly at the boundary (1000)
    codeflash_output = funcA(1000) # 3.40ms -> 70.5μs (4732% faster)

def test_funcA_input_is_one_below_limit():
    # Test with input one below the boundary
    codeflash_output = funcA(999) # 3.43ms -> 70.4μs (4771% faster)

def test_funcA_input_is_one_above_limit():
    # Test with input one above the boundary (should cap at 1000)
    codeflash_output = funcA(1001) # 3.34ms -> 70.5μs (4641% faster)

def test_funcA_input_is_large_negative():
    # Test with a very large negative input
    codeflash_output = funcA(-1000000) # 2.60μs -> 1.44μs (80.5% faster)
# 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) # 2.60μs -> 1.62μs (59.9% faster)

def test_funcA_one():
    # Test with number = 1 (should return '0')
    codeflash_output = funcA(1) # 5.94μs -> 1.98μs (199% faster)

def test_funcA_small_number():
    # Test with number = 5 (should return '0 1 2 3 4')
    codeflash_output = funcA(5) # 18.3μs -> 2.42μs (654% faster)

def test_funcA_typical_number():
    # Test with a typical small number
    codeflash_output = funcA(10) # 34.4μs -> 2.71μs (1171% faster)

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

def test_funcA_negative_number():
    # Negative number: range(negative) is empty, should return empty string
    codeflash_output = funcA(-5) # 2.48μs -> 1.37μs (80.9% faster)

def test_funcA_just_below_threshold():
    # Test with number = 999 (should not be capped)
    expected = " ".join(str(i) for i in range(999))
    codeflash_output = funcA(999) # 3.37ms -> 69.7μs (4743% faster)

def test_funcA_at_threshold():
    # Test with number = 1000 (should be capped at 1000)
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1000) # 3.35ms -> 69.6μs (4717% faster)

def test_funcA_above_threshold():
    # Test with number = 1001 (should be capped at 1000)
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1001) # 3.36ms -> 69.5μs (4730% faster)

def test_funcA_large_negative():
    # Large negative input should return empty string
    codeflash_output = funcA(-10000) # 2.59μs -> 1.42μs (82.3% faster)

def test_funcA_float_input():
    # Float input: should raise TypeError since range expects int
    with pytest.raises(TypeError):
        funcA(5.5)

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

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

def test_funcA_bool_input():
    # Boolean input: True is 1, False is 0
    codeflash_output = funcA(True) # 6.24μs -> 2.23μs (180% faster)
    codeflash_output = funcA(False) # 1.63μs -> 911ns (79.3% faster)

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

def test_funcA_large_number_just_below_cap():
    # Test with number = 999 (should not be capped)
    codeflash_output = funcA(999); result = codeflash_output # 3.34ms -> 74.1μs (4414% faster)

def test_funcA_large_number_at_cap():
    # Test with number = 1000 (should be capped at 1000)
    codeflash_output = funcA(1000); result = codeflash_output # 3.36ms -> 71.2μs (4619% faster)

def test_funcA_large_number_above_cap():
    # Test with number = 1500 (should be capped at 1000)
    codeflash_output = funcA(1500); result = codeflash_output # 3.36ms -> 70.9μs (4646% faster)

def test_funcA_performance_large_input():
    # This test checks that the function can handle the largest allowed input efficiently
    import time
    start = time.time()
    codeflash_output = funcA(1000); result = codeflash_output # 3.34ms -> 71.0μs (4606% faster)
    duration = time.time() - start

# -------------------------
# Additional Edge Cases
# -------------------------

@pytest.mark.parametrize("input_val,expected", [
    (2, "0 1"),
    (3, "0 1 2"),
    (4, "0 1 2 3"),
    (50, " ".join(str(i) for i in range(50))),
    (-1, ""),
    (-100, ""),
])
def test_funcA_various_small_inputs(input_val, expected):
    # Parametrized test for various small and negative inputs
    codeflash_output = funcA(input_val) # 2.42μs -> 1.44μs (67.4% faster)
# 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-mcl3iut8 and push.