⚡️ Speed up function funcA by 23%

[codeflash-ai]

📄 23% (0.23x) speedup for funcA in code_to_optimize/code_directories/simple_tracer_e2e/workload.py

⏱️ Runtime : 577 microseconds → 469 microseconds (best of 340 runs)

📝 Explanation and details

Here is an optimized version of your program.
Key improvements.

• Avoids unnecessary list creation in the join operation by using a generator expression instead of a list comprehension.

• Caches the string representations for each integer 0..1000, so that str(i) is reused instead of reconstructed each time.

• Avoids recalculating the string representations for every call.

• Retains all behavior, matching the function outputs exactly.

• This avoids repeated str conversions entirely for numbers up to 1000, which is your range.

• Uses a tuple (_STRINGS) because it's immutable and fast for indexing.

• The functional and comment structure is preserved.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 73 Passed
⏪ Replay Tests	✅ 3 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

from functools import lru_cache

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

# unit tests

# 1. Basic Test Cases

def test_funcA_zero():
    # Test with input 0 (should return empty string)
    codeflash_output = funcA(0) # 2.40μs -> 2.88μs (16.7% slower)

def test_funcA_one():
    # Test with input 1 (should return "0")
    codeflash_output = funcA(1) # 2.69μs -> 2.94μs (8.21% slower)

def test_funcA_two():
    # Test with input 2 (should return "0 1")
    codeflash_output = funcA(2) # 3.08μs -> 3.24μs (4.67% slower)

def test_funcA_five():
    # Test with input 5 (should return "0 1 2 3 4")
    codeflash_output = funcA(5) # 3.04μs -> 3.13μs (2.88% slower)

def test_funcA_typical_small():
    # Test with a typical small number
    codeflash_output = funcA(10) # 982ns -> 1.03μs (4.84% slower)

# 2. Edge Test Cases

def test_funcA_negative():
    # Test with a negative number (should return empty string, as range(negative) is empty)
    codeflash_output = funcA(-5) # 2.24μs -> 2.73μs (17.7% slower)

def test_funcA_large_exact_limit():
    # Test with exactly the upper limit (1000)
    codeflash_output = funcA(1000); result = codeflash_output # 75.7μs -> 56.2μs (34.7% faster)
    # Should be "0 1 2 ... 999"
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_above_limit():
    # Test with a number above the limit (should be capped at 1000)
    codeflash_output = funcA(1500); result = codeflash_output # 1.19μs -> 1.15μs (3.47% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_limit_plus_one():
    # Test with just above the limit (1001)
    codeflash_output = funcA(1001); result = codeflash_output # 1.10μs -> 1.14μs (3.50% slower)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_limit_minus_one():
    # Test with just below the limit (999)
    codeflash_output = funcA(999); result = codeflash_output # 72.5μs -> 55.3μs (31.3% faster)
    expected = " ".join(str(i) for i in range(999))

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

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

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

def test_funcA_boolean_input():
    # Test with boolean input (should treat True as 1 and False as 0)
    codeflash_output = funcA(True) # 3.48μs -> 3.72μs (6.46% slower)
    codeflash_output = funcA(False) # 1.33μs -> 1.56μs (14.8% slower)

def test_funcA_large_negative():
    # Test with a large negative number
    codeflash_output = funcA(-10000) # 2.21μs -> 2.73μs (19.0% slower)

def test_funcA_edge_case_one_less_than_zero():
    # Test with -1 (should return empty string)
    codeflash_output = funcA(-1) # 2.20μs -> 2.56μs (13.7% slower)

# 3. Large Scale Test Cases

def test_funcA_large_scale_500():
    # Test with 500 (should return "0 1 ... 499")
    codeflash_output = funcA(500); result = codeflash_output # 37.9μs -> 29.8μs (27.0% faster)
    expected = " ".join(str(i) for i in range(500))

def test_funcA_large_scale_999():
    # Test with 999 (should return "0 1 ... 998")
    codeflash_output = funcA(999); result = codeflash_output # 1.19μs -> 1.16μs (2.58% faster)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_performance_cache():
    # Test repeated calls to ensure caching works and does not error
    for i in range(0, 1001, 100):
        expected = " ".join(str(j) for j in range(i))
        codeflash_output = funcA(i)
    # Call again to check cache
    for i in range(0, 1001, 100):
        expected = " ".join(str(j) for j in range(i))
        codeflash_output = funcA(i)

def test_funcA_large_scale_upper_bound():
    # Test with the maximum allowed value (1000)
    codeflash_output = funcA(1000); result = codeflash_output # 1.19μs -> 1.15μs (3.47% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_large_scale_upper_bound_plus():
    # Test with a value just over the maximum allowed (should cap at 1000)
    codeflash_output = funcA(1005); result = codeflash_output # 1.12μs -> 1.17μs (4.27% slower)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_large_scale_all_digits():
    # Test that all digits are present in the output for large N
    codeflash_output = funcA(1000); result = codeflash_output # 1.15μs -> 1.10μs (4.44% faster)
    for digit in "0123456789":
        pass

def test_funcA_large_scale_output_length():
    # Test the output length for a large N
    # For N=1000, length should be sum of len(str(i)) for i in range(1000) plus 999 spaces
    expected_length = sum(len(str(i)) for i in range(1000)) + 999
    codeflash_output = funcA(1000); result = codeflash_output # 1.05μs -> 1.08μs (2.77% slower)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

from functools import lru_cache

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

# unit tests

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

def test_zero():
    # Test when number is 0; should return empty string
    codeflash_output = funcA(0) # 1.12μs -> 1.14μs (1.75% slower)

def test_one():
    # Test when number is 1; should return "0"
    codeflash_output = funcA(1) # 1.09μs -> 1.08μs (0.832% faster)

def test_two():
    # Test when number is 2; should return "0 1"
    codeflash_output = funcA(2) # 1.00μs -> 1.00μs (0.000% faster)

def test_small_number():
    # Test a small number, e.g., 5; should return "0 1 2 3 4"
    codeflash_output = funcA(5) # 991ns -> 982ns (0.916% faster)

def test_typical_number():
    # Test a typical number, e.g., 10
    expected = " ".join(str(i) for i in range(10))
    codeflash_output = funcA(10) # 962ns -> 982ns (2.04% slower)

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

def test_negative_number():
    # Negative input should be treated as range(negative), which is empty
    codeflash_output = funcA(-1) # 1.04μs -> 972ns (7.20% faster)
    codeflash_output = funcA(-100) # 1.92μs -> 2.41μs (20.3% slower)

def test_non_integer_input():
    # Non-integer input should raise TypeError, as range() requires int
    with pytest.raises(TypeError):
        funcA(3.5)
    with pytest.raises(TypeError):
        funcA("10")

def test_large_exact_limit():
    # Test exactly at the upper bound (1000)
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1000) # 1.23μs -> 1.34μs (8.12% slower)

def test_above_limit():
    # Test above the upper bound; should be capped at 1000
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1001) # 1.07μs -> 1.16μs (7.66% slower)
    codeflash_output = funcA(2000) # 541ns -> 541ns (0.000% faster)

def test_edge_near_limit():
    # Test just below and just above the cap
    expected_999 = " ".join(str(i) for i in range(999))
    expected_1000 = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(999) # 1.25μs -> 1.23μs (1.54% faster)
    codeflash_output = funcA(1000) # 591ns -> 581ns (1.72% faster)
    codeflash_output = funcA(1001) # 420ns -> 421ns (0.238% slower)

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

def test_input_is_bool():
    # True is treated as 1, False as 0
    codeflash_output = funcA(True) # 1.43μs -> 1.46μs (2.05% slower)
    codeflash_output = funcA(False) # 621ns -> 611ns (1.64% faster)

def test_input_is_large_negative():
    # Large negative number should return empty string
    codeflash_output = funcA(-999999) # 2.58μs -> 3.16μs (18.1% slower)

def test_input_is_zero_string():
    # String "0" should raise TypeError
    with pytest.raises(TypeError):
        funcA("0")

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

def test_large_scale_500():
    # Test with 500 elements
    expected = " ".join(str(i) for i in range(500))
    codeflash_output = funcA(500) # 1.26μs -> 1.26μs (0.000% faster)

def test_large_scale_999():
    # Test with 999 elements (just below the cap)
    expected = " ".join(str(i) for i in range(999))
    codeflash_output = funcA(999) # 1.31μs -> 1.26μs (3.96% faster)

def test_large_scale_1000():
    # Test with 1000 elements (at the cap)
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1000) # 1.16μs -> 1.16μs (0.000% faster)

def test_large_scale_above_cap():
    # Test with a number much larger than the cap
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(5000) # 1.18μs -> 1.11μs (6.29% faster)

def test_performance_large():
    # Test that large input does not take too long (not a strict performance test, but ensures no crash)
    codeflash_output = funcA(1000); result = codeflash_output # 1.22μs -> 1.12μs (8.82% faster)

# -------------
# Determinism
# -------------

def test_deterministic_output():
    # Multiple calls with same input should yield same output (tests caching/determinism)
    codeflash_output = funcA(123); out1 = codeflash_output # 11.9μs -> 10.4μs (14.2% faster)
    codeflash_output = funcA(123); out2 = codeflash_output # 641ns -> 641ns (0.000% faster)

# -------------
# Mutation Sensitivity
# -------------

def test_mutation_sensitivity():
    # If the function output is off by one, the test should fail
    codeflash_output = funcA(10); correct = codeflash_output # 1.02μs -> 1.02μs (0.000% faster)
    # Simulate a wrong output (off by one)
    wrong = " ".join(str(i) for i in range(9))
    # Simulate a wrong output (reversed)
    wrong_rev = " ".join(str(i) for i in reversed(range(10)))
    # Simulate a wrong output (comma-separated)
    wrong_comma = ",".join(str(i) for i in range(10))
# 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-mccvrobh and push.