⚡️ Speed up function funcA by 18%

[codeflash-ai]

📄 18% (0.18x) speedup for funcA in code_to_optimize/code_directories/simple_tracer_e2e/workload.py

⏱️ Runtime : 344 microseconds → 291 microseconds (best of 370 runs)

📝 Explanation and details

Here's an optimized version of your program.
Key optimizations:

• Remove the unnecessary calculation of j, since it's unused.
• Replace the list comprehension in _joined_number_str with an efficient string-based generator expression, and use map(str, ...) (faster for this case).
• Remove the use of min() in funcA: clamp manually so as not to allocate a tuple.
• Go straight to returning the cached helper in funcA for efficiency.

Here's the refactored code.

Rationale for the changes:

• List comprehensions allocate an intermediate list in memory; map + join can use an iterator directly for less memory and increased speed.
• min(1000, number) allocates a tuple and incurs extra function call overhead; checking and assigning is better for single variable.
• Removed the calculation of j, since it is unused and just wastes CPU cycles.
• No change to function signatures or internal comments as requested since code is self-explanatory.

Let me know if you need even further performance (such as rewriting without the lru_cache for a specific use case or limiting memory even further).

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 50 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():
    # Test with 0: should return empty string
    codeflash_output = funcA(0) # 1.04μs -> 572ns (82.0% faster)

def test_funcA_one():
    # Test with 1: should return "0"
    codeflash_output = funcA(1) # 982ns -> 561ns (75.0% faster)

def test_funcA_two():
    # Test with 2: should return "0 1"
    codeflash_output = funcA(2) # 962ns -> 561ns (71.5% faster)

def test_funcA_small_number():
    # Test with 5: should return "0 1 2 3 4"
    codeflash_output = funcA(5) # 962ns -> 571ns (68.5% faster)

def test_funcA_typical():
    # Test with 10: should return "0 1 2 3 4 5 6 7 8 9"
    codeflash_output = funcA(10) # 891ns -> 571ns (56.0% faster)

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

def test_funcA_negative():
    # Test with negative input: should return empty string (since range(negative) is empty)
    codeflash_output = funcA(-5) # 1.02μs -> 581ns (75.9% faster)

def test_funcA_float_input():
    # Test with float input: should raise TypeError
    with pytest.raises(TypeError):
        funcA(3.5)

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

def test_funcA_large_input_capped():
    # Test with input greater than 1000: should cap at 1000
    codeflash_output = funcA(1500); result = codeflash_output # 1.25μs -> 692ns (80.9% faster)
    # Should be numbers from 0 to 999
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_exactly_1000():
    # Test with input exactly 1000: should return numbers 0 to 999
    codeflash_output = funcA(1000); result = codeflash_output # 1.16μs -> 661ns (75.8% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_input_just_below_cap():
    # Test with input 999: should return numbers 0 to 998
    codeflash_output = funcA(999); result = codeflash_output # 1.12μs -> 611ns (83.6% faster)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_input_one_below_zero():
    # Test with -1: should return empty string
    codeflash_output = funcA(-1) # 2.71μs -> 2.19μs (23.3% faster)

def test_funcA_non_integer_types():
    # Test with boolean input: should treat True as 1, False as 0
    codeflash_output = funcA(True) # 1.28μs -> 702ns (82.6% faster)
    codeflash_output = funcA(False) # 621ns -> 381ns (63.0% faster)

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

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

def test_funcA_large_scale_500():
    # Test with 500: should return numbers 0 to 499
    codeflash_output = funcA(500); result = codeflash_output # 46.1μs -> 40.3μs (14.3% faster)
    expected = " ".join(str(i) for i in range(500))

def test_funcA_large_scale_999():
    # Test with 999: should return numbers 0 to 998
    codeflash_output = funcA(999); result = codeflash_output # 1.14μs -> 622ns (83.6% faster)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_large_scale_performance():
    # Test with 1000: should return numbers 0 to 999 efficiently
    codeflash_output = funcA(1000); result = codeflash_output # 1.16μs -> 641ns (81.3% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_cache_efficiency():
    # Test repeated calls for caching behavior (should not affect output)
    codeflash_output = funcA(100); result1 = codeflash_output # 1.06μs -> 591ns (79.7% faster)
    codeflash_output = funcA(100); result2 = codeflash_output # 501ns -> 280ns (78.9% faster)
    # Changing input should change output
    codeflash_output = funcA(101); result3 = codeflash_output # 12.0μs -> 10.7μs (12.7% faster)

def test_funcA_large_scale_edge():
    # Test with the maximum allowed input (1000)
    codeflash_output = funcA(1000); result = codeflash_output # 1.09μs -> 591ns (84.8% faster)
# 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 0: should return an empty string
    codeflash_output = funcA(0) # 2.79μs -> 2.25μs (24.0% faster)

def test_funcA_one():
    # Test with 1: should return "0"
    codeflash_output = funcA(1) # 2.96μs -> 2.54μs (17.0% faster)

def test_funcA_two():
    # Test with 2: should return "0 1"
    codeflash_output = funcA(2) # 3.37μs -> 2.71μs (24.0% faster)

def test_funcA_small_number():
    # Test with a small number, e.g., 5
    codeflash_output = funcA(5) # 3.36μs -> 2.79μs (20.5% faster)

def test_funcA_typical_number():
    # Test with a typical number, e.g., 10
    codeflash_output = funcA(10) # 901ns -> 531ns (69.7% faster)

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

def test_funcA_negative_input():
    # Negative input: should return an empty string (range(negative) is empty)
    codeflash_output = funcA(-5) # 2.63μs -> 2.10μs (25.2% faster)

def test_funcA_large_input_exact_limit():
    # Input at the exact upper limit: 1000
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1000) # 85.8μs -> 76.6μs (12.0% faster)

def test_funcA_above_limit():
    # Input above the upper limit: should still cap at 1000
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1500) # 1.16μs -> 621ns (87.1% faster)

def test_funcA_input_is_string():
    # Input as string should raise TypeError
    with pytest.raises(TypeError):
        funcA("10")

def test_funcA_input_is_float():
    # Input as float should raise TypeError
    with pytest.raises(TypeError):
        funcA(3.5)

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

def test_funcA_input_is_bool():
    # Input as boolean (True == 1, False == 0)
    codeflash_output = funcA(True) # 3.35μs -> 3.02μs (10.9% faster)
    codeflash_output = funcA(False) # 1.90μs -> 1.40μs (35.6% faster)

def test_funcA_input_is_large_negative():
    # Large negative input: should return empty string
    codeflash_output = funcA(-1000) # 2.81μs -> 2.12μs (32.1% faster)

def test_funcA_input_is_min_int():
    # Very large negative input (simulate min int)
    codeflash_output = funcA(-2**31) # 3.08μs -> 2.09μs (46.9% faster)

def test_funcA_input_is_max_int():
    # Very large positive input (simulate max int, but should cap at 1000)
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(2**31-1) # 1.30μs -> 772ns (68.8% faster)

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

def test_funcA_large_scale_100():
    # Test with 100 elements
    expected = " ".join(str(i) for i in range(100))
    codeflash_output = funcA(100) # 11.0μs -> 9.50μs (15.8% faster)

def test_funcA_large_scale_999():
    # Test with 999 elements
    expected = " ".join(str(i) for i in range(999))
    codeflash_output = funcA(999) # 85.3μs -> 76.4μs (11.7% faster)

def test_funcA_large_scale_1000():
    # Test with 1000 elements (upper bound)
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1000) # 1.18μs -> 601ns (96.7% faster)

def test_funcA_large_scale_above_1000():
    # Test with a number above 1000, e.g., 1234 (should cap at 1000)
    expected = " ".join(str(i) for i in range(1000))
    codeflash_output = funcA(1234) # 1.09μs -> 661ns (65.4% faster)

def test_funcA_performance_large_input():
    # Performance: ensure function completes quickly for upper bound
    import time
    start = time.time()
    codeflash_output = funcA(1000); result = codeflash_output # 1.12μs -> 571ns (96.5% faster)
    end = time.time()
    expected = " ".join(str(i) for i in range(1000))

# ----------------------
# Miscellaneous/Regression Test Cases
# ----------------------

def test_funcA_idempotence():
    # Idempotence: repeated calls with same argument should yield same result
    codeflash_output = funcA(42) # 7.08μs -> 5.98μs (18.4% faster)
    codeflash_output = funcA(0) # 741ns -> 310ns (139% faster)

def test_funcA_mutation_resistance():
    # Changing the return string should break the test (mutation test)
    codeflash_output = funcA(3); result = codeflash_output # 3.23μs -> 2.73μs (18.4% faster)

def test_funcA_cached_behavior():
    # Test that the cache does not affect correctness
    codeflash_output = funcA(10) # 932ns -> 561ns (66.1% faster)
    codeflash_output = funcA(10) # 501ns -> 301ns (66.4% faster)
    codeflash_output = funcA(9) # 3.06μs -> 2.83μs (8.18% faster)
    codeflash_output = funcA(8) # 1.92μs -> 1.44μs (33.3% 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-mccv18wl and push.