⚡️ Speed up function funcA by 10%

[codeflash-ai]

📄 10% (0.10x) speedup for funcA in code_to_optimize/code_directories/simple_tracer_e2e/workload.py

⏱️ Runtime : 927 microseconds → 843 microseconds (best of 369 runs)

📝 Explanation and details

Certainly! Here’s how you can make this code faster and more memory-efficient.

Optimizations:

• Avoid repeated string conversions inside " ".join(str(i) for i in range(number)). Precompute strings for common values if needed.
• Use a tuple comprehension, but " ".join(map(str, range(number))) is faster and more memory efficient than a generator expression.
• Since range(number) is always sequential, you can do even better: use " ".join(map(str, range(number))) directly, which is both faster and uses less memory.

Below is the optimized code (with all comments preserved or updated if a relevant section changed).

Explanation of the changes:

• Replaced the generator expression with map(str, ...), which is faster for long sequential ranges due to not creating intermediate generator objects.
• Kept the caching and function signatures exactly as requested.
• Kept all comments and structure the same.
• No unnecessary copies, allocations, or data structures are introduced.

This will now run a little faster, especially for larger numbers. If you need much higher performance and are often calling with the same number, consider using a static precomputed array, but for the given constraints, this is the best improvement without drastically changing the logic or memory behavior.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 82 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

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

def test_funcA_zero():
    # Basic: number = 0 should return an empty string
    codeflash_output = funcA(0) # 2.73μs -> 2.77μs (1.77% slower)

def test_funcA_one():
    # Basic: number = 1 should return "0"
    codeflash_output = funcA(1) # 2.81μs -> 2.77μs (1.45% faster)

def test_funcA_small_number():
    # Basic: number = 5 should return "0 1 2 3 4"
    codeflash_output = funcA(5) # 3.38μs -> 3.34μs (1.17% faster)

def test_funcA_typical_number():
    # Basic: number = 10 should return "0 1 2 3 4 5 6 7 8 9"
    codeflash_output = funcA(10) # 892ns -> 982ns (9.16% slower)

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

def test_funcA_negative_number():
    # Edge: negative number should return empty string (range(negative) is empty)
    codeflash_output = funcA(-1) # 2.44μs -> 2.52μs (2.78% slower)
    codeflash_output = funcA(-100) # 1.39μs -> 1.28μs (8.66% faster)

def test_funcA_large_number_exact_limit():
    # Edge: number = 1000 should return "0 1 2 ... 999"
    codeflash_output = funcA(1000); result = codeflash_output # 83.0μs -> 79.3μs (4.64% faster)
    parts = result.split()

def test_funcA_above_limit():
    # Edge: number > 1000 should be capped at 1000
    codeflash_output = funcA(1500); result = codeflash_output # 1.08μs -> 1.13μs (4.42% slower)
    parts = result.split()

def test_funcA_limit_plus_one():
    # Edge: number = 1001 should be capped at 1000
    codeflash_output = funcA(1001); result = codeflash_output # 1.10μs -> 1.07μs (2.89% faster)
    parts = result.split()

def test_funcA_limit_minus_one():
    # Edge: number = 999 should return "0 1 ... 998"
    codeflash_output = funcA(999); result = codeflash_output # 81.0μs -> 72.4μs (12.0% faster)
    parts = result.split()

def test_funcA_non_integer_input():
    # Edge: non-integer input should raise TypeError
    with pytest.raises(TypeError):
        funcA("100")
    with pytest.raises(TypeError):
        funcA(5.5)
    with pytest.raises(TypeError):
        funcA(None)

def test_funcA_boolean_input():
    # Edge: boolean input (True == 1, False == 0)
    codeflash_output = funcA(True) # 3.41μs -> 3.48μs (2.04% slower)
    codeflash_output = funcA(False) # 1.58μs -> 1.45μs (8.95% faster)

def test_funcA_mutation_check():
    # Edge: ensure correct output, not off-by-one or reversed
    codeflash_output = funcA(3) # 3.04μs -> 3.00μs (1.34% faster)
    # Should not be "1 2 3" or "2 1 0"
    codeflash_output = funcA(3) # 531ns -> 521ns (1.92% faster)
    codeflash_output = funcA(3) # 361ns -> 371ns (2.70% slower)

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

def test_funcA_large_scale_500():
    # Large: number = 500
    codeflash_output = funcA(500); result = codeflash_output # 42.3μs -> 37.8μs (12.0% faster)
    parts = result.split()

def test_funcA_large_scale_999():
    # Large: number = 999
    codeflash_output = funcA(999); result = codeflash_output # 1.04μs -> 1.09μs (4.67% slower)
    parts = result.split()

def test_funcA_large_scale_just_over_limit():
    # Large: number = 1005, should cap at 1000
    codeflash_output = funcA(1005); result = codeflash_output # 1.00μs -> 1.11μs (9.89% slower)
    parts = result.split()

def test_funcA_large_scale_performance():
    # Large: call funcA(1000) multiple times to test caching/performance
    for _ in range(10):
        codeflash_output = funcA(1000); result = codeflash_output
        parts = result.split()

def test_funcA_large_scale_multiple_sizes():
    # Large: test a range of sizes for scalability
    for n in [10, 100, 250, 500, 750, 1000]:
        codeflash_output = funcA(n); result = codeflash_output
        parts = result.split()
        if n > 0:
            pass
        else:
            pass

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

def test_funcA_input_mutation():
    # Edge: ensure input is not mutated
    n = 10
    funcA(n)

def test_funcA_string_output_format():
    # Edge: ensure output is a single string, not a list or other type
    codeflash_output = funcA(10); out = codeflash_output # 972ns -> 992ns (2.02% slower)

def test_funcA_output_is_space_separated():
    # Edge: ensure output is space-separated, not comma or other delimiter
    codeflash_output = funcA(5); out = codeflash_output # 922ns -> 961ns (4.06% slower)

def test_funcA_empty_string_for_zero_or_negative():
    # Edge: output is empty string for zero or negative input
    for n in [0, -1, -100]:
        codeflash_output = funcA(n)
# 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_funcA_zero():
    # Test with input 0: should return an empty string
    codeflash_output = funcA(0) # 1.03μs -> 992ns (4.13% faster)

def test_funcA_one():
    # Test with input 1: should return "0"
    codeflash_output = funcA(1) # 972ns -> 992ns (2.02% slower)

def test_funcA_small_number():
    # Test with input 5: should return "0 1 2 3 4"
    codeflash_output = funcA(5) # 972ns -> 932ns (4.29% faster)

def test_funcA_typical_number():
    # Test with input 10: should return "0 1 2 3 4 5 6 7 8 9"
    codeflash_output = funcA(10) # 982ns -> 981ns (0.102% faster)

def test_funcA_multiple_calls_same_input():
    # Test repeated calls with the same input (cache should not affect result)
    codeflash_output = funcA(7); result1 = codeflash_output # 3.71μs -> 3.49μs (6.34% faster)
    codeflash_output = funcA(7); result2 = codeflash_output # 521ns -> 511ns (1.96% faster)

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

def test_funcA_negative_input():
    # Negative input should return empty string (since range(negative) is empty)
    codeflash_output = funcA(-5) # 2.65μs -> 2.50μs (6.03% faster)

def test_funcA_large_input_capped():
    # Input above 1000 should be capped at 1000
    codeflash_output = funcA(1500); result = codeflash_output # 1.13μs -> 1.12μs (0.801% faster)
    # Should be string of numbers from 0 to 999
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_input_exactly_1000():
    # Input exactly 1000 (upper bound, inclusive)
    codeflash_output = funcA(1000); result = codeflash_output # 1.12μs -> 1.09μs (2.75% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_input_just_below_cap():
    # Input just below the cap (999)
    codeflash_output = funcA(999); result = codeflash_output # 1.13μs -> 1.15μs (1.65% slower)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_input_just_above_cap():
    # Input just above the cap (1001)
    codeflash_output = funcA(1001); result = codeflash_output # 1.09μs -> 1.14μs (4.38% slower)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_float_input():
    # Float input should raise TypeError, as range expects int
    with pytest.raises(TypeError):
        funcA(3.5)

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) # 1.45μs -> 1.42μs (2.04% faster)
    codeflash_output = funcA(False) # 581ns -> 561ns (3.57% faster)

def test_funcA_input_maxsize_cache():
    # Test the cache does not affect correctness at the boundary
    for i in range(1000, 995, -1):
        expected = " ".join(str(j) for j in range(i))
        codeflash_output = funcA(i)

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

def test_funcA_large_scale_500():
    # Test with a large input (500)
    codeflash_output = funcA(500); result = codeflash_output # 1.17μs -> 1.13μs (3.63% faster)
    expected = " ".join(str(i) for i in range(500))

def test_funcA_large_scale_999():
    # Test with input just below the cap (999)
    codeflash_output = funcA(999); result = codeflash_output # 1.10μs -> 1.22μs (9.82% slower)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_large_scale_1000():
    # Test with the largest allowed input (1000)
    codeflash_output = funcA(1000); result = codeflash_output # 1.12μs -> 1.16μs (3.44% slower)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_performance_many_calls():
    # Performance: call funcA with many different values to exercise the cache
    for i in range(0, 1000, 100):
        expected = " ".join(str(j) for j in range(i))
        codeflash_output = funcA(i)

def test_funcA_large_scale_various_inputs():
    # Test a selection of large inputs for correctness and cache robustness
    inputs = [250, 500, 750, 999, 1000]
    for n in inputs:
        expected = " ".join(str(i) for i in range(n))
        codeflash_output = funcA(n)
# 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-mccv5hj7 and push.

[codeflash-ai]

This PR has been automatically closed because the original PR #401 by codeflash-ai[bot] was closed.