⚡️ Speed up function task by 1%

[codeflash-ai]

📄 1% (0.01x) speedup for task in src/async_examples/concurrency.py

⏱️ Runtime : 18.3 milliseconds → 18.1 milliseconds (best of 199 runs)

📝 Explanation and details

Looking at both code versions, they are identical - no optimizations were actually applied. The original explanation mentions replacing time.sleep() with await asyncio.sleep(), but this change is not present in the optimized code.

The minimal 0.2ms improvement (18.3ms → 18.1ms) shown in the runtime is likely just measurement noise, not a real performance gain. The line profiler results confirm this - both versions show nearly identical execution patterns with time.sleep(0.00001) consuming ~97% of the runtime.

The key issue remains: time.sleep() blocks the entire event loop in async code, preventing true concurrency. While the function is marked async, it doesn't yield control to other coroutines during the sleep, making it essentially synchronous. This is why all the concurrent test cases (using asyncio.gather()) don't show the expected performance benefits of async programming.

For genuine async performance, the code should use await asyncio.sleep(0.00001) instead of time.sleep(0.00001), but this optimization was not implemented in the provided optimized version.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 1271 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import asyncio  # used to run async functions
# function to test
import time

import pytest  # used for our unit tests
from src.async_examples.concurrency import task

# unit tests

# 1. Basic Test Cases

@pytest.mark.asyncio
async def test_task_returns_done():
    """Test that task returns 'done' when awaited."""
    result = await task()


@pytest.mark.asyncio
async def test_task_is_coroutine():
    """Test that task returns a coroutine object before awaiting."""
    codeflash_output = task(); coro = codeflash_output


# 2. Edge Test Cases

@pytest.mark.asyncio
async def test_task_concurrent_execution():
    """Test concurrent execution of multiple task coroutines."""
    # Run 10 tasks concurrently
    tasks = [task() for _ in range(10)]
    results = await asyncio.gather(*tasks)

@pytest.mark.asyncio
async def test_task_exception_handling():
    """Test that task does not raise exceptions during execution."""
    try:
        result = await task()
    except Exception as e:
        pytest.fail(f"task() raised an unexpected exception: {e}")

@pytest.mark.asyncio
async def test_task_multiple_sequential_calls():
    """Test calling task multiple times sequentially."""
    for _ in range(5):
        result = await task()


# 3. Large Scale Test Cases

@pytest.mark.asyncio
async def test_task_large_scale_concurrent():
    """Test running a large number of tasks concurrently."""
    num_tasks = 100  # Reasonable upper bound for quick test
    tasks = [task() for _ in range(num_tasks)]
    results = await asyncio.gather(*tasks)

@pytest.mark.asyncio
async def test_task_gather_empty_list():
    """Test asyncio.gather with an empty list of tasks."""
    results = await asyncio.gather(*[])


# 4. Throughput Test Cases

@pytest.mark.asyncio
async def test_task_throughput_small_load():
    """Test throughput with a small number of concurrent tasks."""
    num_tasks = 10
    tasks = [task() for _ in range(num_tasks)]
    results = await asyncio.gather(*tasks)

@pytest.mark.asyncio
async def test_task_throughput_medium_load():
    """Test throughput with a medium number of concurrent tasks."""
    num_tasks = 50
    tasks = [task() for _ in range(num_tasks)]
    results = await asyncio.gather(*tasks)

@pytest.mark.asyncio
async def test_task_throughput_high_load():
    """Test throughput with a high number of concurrent tasks."""
    num_tasks = 200  # High but still reasonable for unit test speed
    tasks = [task() for _ in range(num_tasks)]
    results = await asyncio.gather(*tasks)

@pytest.mark.asyncio
async def test_task_throughput_sustained_execution():
    """Test sustained execution pattern for throughput."""
    # Run 20 batches of 10 tasks each, sequentially
    batch_size = 10
    batches = 20
    for _ in range(batches):
        results = await asyncio.gather(*[task() for _ in range(batch_size)])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
import asyncio  # used to run async functions
# function to test
import time

import pytest  # used for our unit tests
from src.async_examples.concurrency import task

# unit tests

# 1. Basic Test Cases

@pytest.mark.asyncio
async def test_task_returns_done():
    """
    Basic: Test that task returns 'done' when awaited.
    """
    result = await task()

@pytest.mark.asyncio
async def test_task_is_coroutine():
    """
    Basic: Test that task returns a coroutine object when called.
    """
    codeflash_output = task(); coro = codeflash_output

# 2. Edge Test Cases

@pytest.mark.asyncio
async def test_task_concurrent_execution():
    """
    Edge: Test concurrent execution of multiple task coroutines.
    """
    # Launch 10 concurrent tasks and ensure all return 'done'
    coros = [task() for _ in range(10)]
    results = await asyncio.gather(*coros)

@pytest.mark.asyncio
async def test_task_exception_propagation():
    """
    Edge: Test that no exceptions are raised during normal execution.
    """
    try:
        result = await task()
    except Exception as e:
        pytest.fail(f"task() raised an unexpected exception: {e}")

@pytest.mark.asyncio
async def test_task_multiple_awaits():
    """
    Edge: Test that multiple awaits of separate coroutines work as expected.
    """
    # Await the same function separately
    res1 = await task()
    res2 = await task()

# 3. Large Scale Test Cases

@pytest.mark.asyncio
async def test_task_large_scale_concurrent():
    """
    Large Scale: Test 100 concurrent executions of task.
    """
    num_tasks = 100
    coros = [task() for _ in range(num_tasks)]
    results = await asyncio.gather(*coros)

@pytest.mark.asyncio
async def test_task_large_scale_sequential():
    """
    Large Scale: Test 100 sequential executions of task.
    """
    num_tasks = 100
    for _ in range(num_tasks):
        result = await task()

# 4. Throughput Test Cases

@pytest.mark.asyncio
async def test_task_throughput_small_load():
    """
    Throughput: Test small load (10 concurrent executions).
    """
    coros = [task() for _ in range(10)]
    results = await asyncio.gather(*coros)

@pytest.mark.asyncio
async def test_task_throughput_medium_load():
    """
    Throughput: Test medium load (50 concurrent executions).
    """
    coros = [task() for _ in range(50)]
    results = await asyncio.gather(*coros)

@pytest.mark.asyncio
async def test_task_throughput_high_load():
    """
    Throughput: Test high load (200 concurrent executions).
    """
    coros = [task() for _ in range(200)]
    results = await asyncio.gather(*coros)

@pytest.mark.asyncio
async def test_task_throughput_sustained_pattern():
    """
    Throughput: Test sustained execution pattern (10 rounds of 20 concurrent tasks).
    """
    for _ in range(10):
        coros = [task() for _ in range(20)]
        results = await asyncio.gather(*coros)

# 5. Async/Await Pattern Tests

@pytest.mark.asyncio
async def test_task_await_in_list_comprehension():
    """
    Test awaiting task in a list comprehension.
    """
    results = [await task() for _ in range(5)]

@pytest.mark.asyncio
async def test_task_gather_with_return_exceptions_false():
    """
    Test asyncio.gather with return_exceptions=False (should not raise).
    """
    coros = [task() for _ in range(5)]
    results = await asyncio.gather(*coros, return_exceptions=False)

@pytest.mark.asyncio
async def test_task_gather_with_return_exceptions_true():
    """
    Test asyncio.gather with return_exceptions=True (should not return exceptions).
    """
    coros = [task() for _ in range(5)]
    results = await asyncio.gather(*coros, return_exceptions=True)

# 6. Miscellaneous Edge Cases

@pytest.mark.asyncio
async def test_task_result_type():
    """
    Edge: Test that the result type is str.
    """
    result = await task()

@pytest.mark.asyncio
async def test_task_no_arguments():
    """
    Edge: Test that task does not accept arguments.
    """
    with pytest.raises(TypeError):
        await task("unexpected_argument")
# 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-task-mfvn620l and push.