anext()

anext() is the asynchronous counterpart to next() — it retrieves the next item from an async iterator by returning an awaitable coroutine that resolves to the value (or raises StopAsyncIteration when exhausted). Introduced in Python 3.10, anext() enables clean, non-blocking iteration over async sources (generators, queues, streams, custom async iterables) using await anext(it) — perfect for real-time data feeds, WebSockets, async file reading, network streams, or earthquake event queues. In 2026, anext() is a core tool in modern async Python — used with asyncio, trio, anyio, and integrated with Dask’s async support for parallel stream processing.

Here’s a complete, practical guide to using anext() in Python: basic async iteration, manual stepping with await, sentinel/end handling, real-world patterns (event streams, queue consumption, earthquake real-time feed), and modern best practices with type hints, error handling, cancellation, timeouts, performance, and alternatives in Polars/Dask/xarray.

Basic anext() usage — await next value from async iterator, handle exhaustion.


import asyncio

async def countdown(n: int):
    while n > 0:
        yield n
        n -= 1
        await asyncio.sleep(0.3)

async def main():
    agen = countdown(5)
    
    print(await anext(agen))  # 5
    print(await anext(agen))  # 4
    print(await anext(agen))  # 3
    
    # Manual loop with try/except for end
    while True:
        try:
            value = await anext(agen)
            print(value)
        except StopAsyncIteration:
            print("Done!")
            break

asyncio.run(main())
# Output: 5 4 3 2 1 Done!

Using anext() with asyncio.Queue — classic producer-consumer with sentinel.


async def producer(queue: asyncio.Queue):
    for i in range(5):
        await queue.put(i)
        await asyncio.sleep(0.5)
    await queue.put(None)  # sentinel to stop

async def consumer(queue: asyncio.Queue):
    while True:
        item = await anext(queue.get, None)  # stops at sentinel
        if item is None:
            print("Consumer done")
            break
        print(f"Consumed: {item}")
        queue.task_done()

async def main():
    queue = asyncio.Queue()
    await asyncio.gather(
        producer(queue),
        consumer(queue)
    )

asyncio.run(main())

Real-world pattern: processing real-time earthquake event stream — filter significant quakes.


import asyncio
import json
from typing import AsyncIterator

async def quake_stream() -> AsyncIterator[dict]:
    # Simulate real-time feed (in practice: WebSocket/USGS stream)
    events = [
        {"mag": 4.2, "place": "California"},
        {"mag": 7.1, "place": "Japan"},
        {"mag": 5.8, "place": "Indonesia"},
        {"mag": 6.5, "place": "Chile"}
    ]
    for e in events:
        await asyncio.sleep(1)
        yield e

async def monitor():
    it = aiter(quake_stream())
    
    while True:
        try:
            event = await anext(it)
            if event["mag"] >= 6.0:
                print(f"ALERT: Mag {event['mag']} in {event['place']}")
        except StopAsyncIteration:
            print("Stream ended")
            break
        except asyncio.TimeoutError:
            print("Timeout waiting for event")
            break

async def main():
    await asyncio.wait_for(monitor(), timeout=10.0)  # safety timeout

asyncio.run(main())

Best practices for anext() in async Python. Prefer async for — idiomatic when iterating entire stream. Modern tip: use Polars/Dask for batch/stream hybrids — pl.scan_ndjson(...) or da.from_array(...); use anext() for truly streaming/event-driven. Use sentinels — None or custom object — to signal end. Use asyncio.timeout() — prevent infinite waits. Add type hints — async def stream() -> AsyncIterator[dict]. Handle cancellation — try/finally for cleanup. Use asyncio.as_completed() — concurrent futures with anext. Use anyio — higher-level async primitives. Use websockets — for real-time feeds. Use httpx.AsyncClient — for async HTTP streams. Profile with asyncio.run() + uvloop — faster event loop. Test with pytest-asyncio — async fixtures. Use aiter() with asyncio.Queue.get_nowait() — non-blocking checks. Use db.read_text(...).map(json.loads) — Dask Bag for large JSONL files. Use anext(it, default) — provide default instead of raising StopAsyncIteration (Python 3.10+).

anext() retrieves the next value from an async iterator via awaitable coroutine — use with async for, queues, generators, streams, or custom async iterables. In 2026, use sentinels for termination, type hints for clarity, anyio/uvloop for speed, and integrate with Dask/Polars/xarray for batch/stream hybrids. Master anext(), and you’ll handle real-time or async data flows elegantly, efficiently, and scalably.

Next time you need the next item from an async source — await anext(). It’s Python’s cleanest way to say: “Give me the next value asynchronously — without blocking the event loop.”

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