⚡️ Speed up function task by 0%

[codeflash-ai]

📄 0% (0.00x) speedup for task in src/async_examples/concurrency.py

⏱️ Runtime : 3.01 seconds → 3.00 seconds (best of 5 runs)

📝 Explanation and details

The optimization replaces the blocking time.sleep(1) with the non-blocking await asyncio.sleep(1). This is a critical fix for async code correctness rather than a speed improvement for single task execution.

Key changes:

• Replaced blocking call: time.sleep(1) blocks the entire event loop, preventing any concurrency
• Added proper async sleep: await asyncio.sleep(1) yields control back to the event loop, enabling true asynchronous behavior
• Import change: Switched from time to asyncio module

Why this matters:
The line profiler shows the optimized version completes its function logic in 0.000169s vs 3.01s because asyncio.sleep() immediately yields control and the profiler only measures the function's active execution time, not the sleep duration. The blocking time.sleep() keeps the function actively running for the full second.

Concurrency benefits:
While single task execution shows no speedup (both still wait 1 second), the optimized version enables proper async concurrency. When running multiple tasks with asyncio.gather(), the optimized version allows all tasks to sleep simultaneously rather than sequentially, providing dramatic speedups (100 concurrent tasks complete in ~1 second instead of ~100 seconds).

This optimization is essential for any async code that needs to work with multiple concurrent operations or integrate properly with async frameworks.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 19 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

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_expected_value():
    """Test that task returns the correct result when awaited."""
    result = await task()

@pytest.mark.asyncio




async def test_task_concurrent_execution():
    """Test that multiple tasks can be run concurrently and all return correct results."""
    results = await asyncio.gather(
        task(delay=0.05, result="a"),
        task(delay=0.02, result="b"),
        task(delay=0.01, result="c"),
        return_exceptions=False
    )

@pytest.mark.asyncio
async def test_task_concurrent_with_exception():
    """Test that exceptions propagate correctly in concurrent execution."""
    tasks = [
        task(delay=0.01, result="ok"),
        task(delay=0.01, raise_exc=True),
        task(delay=0.01, result="ok2"),
    ]
    results = await asyncio.gather(*tasks, return_exceptions=True)

@pytest.mark.asyncio
async def test_task_cancellation():
    """Test that task can be cancelled and raises asyncio.CancelledError."""
    codeflash_output = task(delay=0.2); coro = codeflash_output
    task_obj = asyncio.create_task(coro)
    await asyncio.sleep(0.05)  # Let it start
    task_obj.cancel()
    with pytest.raises(asyncio.CancelledError):
        await task_obj

@pytest.mark.asyncio

async def test_task_many_concurrent():
    """Test that many concurrent tasks all complete and return correct values."""
    n = 100
    delays = [0.01 * (i % 3) for i in range(n)]
    expected = [f"result-{i}" for i in range(n)]
    coros = [task(delay=delays[i], result=expected[i]) for i in range(n)]
    results = await asyncio.gather(*coros)

@pytest.mark.asyncio
async def test_task_performance_under_load():
    """Test that the function completes under moderate concurrent load."""
    n = 200
    coros = [task(delay=0.01) for _ in range(n)]
    # Should not take more than 1 second in total
    start = asyncio.get_event_loop().time()
    results = await asyncio.gather(*coros)
    end = asyncio.get_event_loop().time()

@pytest.mark.asyncio
async def test_task_gather_with_mixed_exceptions():
    """Test that asyncio.gather returns exceptions for failed tasks and results for successful ones."""
    n = 10
    coros = [task(delay=0.01, raise_exc=(i % 2 == 0), result=f"r{i}") for i in range(n)]
    results = await asyncio.gather(*coros, return_exceptions=True)
    for i, res in enumerate(results):
        if i % 2 == 0:
            pass
        else:
            pass
# 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

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_expected_value():
    # Test that task returns the expected string 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
    result = await coro

# 2. EDGE TEST CASES

@pytest.mark.asyncio

async def test_task_concurrent_execution():
    # Test that multiple tasks can be awaited concurrently and all return results
    results = await asyncio.gather(
        task(delay=0.1, result="a"),
        task(delay=0.2, result="b"),
        task(delay=0.05, result="c")
    )

@pytest.mark.asyncio
async def test_task_cancellation():
    # Test that task can be cancelled and raises asyncio.CancelledError
    t = asyncio.create_task(task(delay=1))
    await asyncio.sleep(0.1)  # Let the task start
    t.cancel()
    with pytest.raises(asyncio.CancelledError):
        await t

@pytest.mark.asyncio



async def test_task_many_concurrent_calls():
    # Test task with a large number of concurrent executions
    N = 100
    results = await asyncio.gather(*[task(delay=0.01, result=str(i)) for i in range(N)])

@pytest.mark.asyncio
async def test_task_performance_under_load():
    # Test that all tasks complete within a reasonable time under load
    N = 100
    start = asyncio.get_event_loop().time()
    results = await asyncio.gather(*[task(delay=0.02) for _ in range(N)])
    end = asyncio.get_event_loop().time()

@pytest.mark.asyncio
async def test_task_concurrent_exceptions():
    # Test that exceptions in some concurrent tasks do not prevent others from finishing
    coros = [
        task(delay=0.01, result="ok"),
        task(delay=0.01, raise_exc=True),
        task(delay=0.01, result="ok2"),
    ]
    results = await asyncio.gather(*coros, return_exceptions=True)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
from src.async_examples.concurrency import task

To edit these changes git checkout codeflash/optimize-task-mfd39l1h and push.