Python anext Function
Complete guide to Python's anext function covering async iterators, error handling, and practical asynchronous examples.
Python anext Function
Last modified April 11, 2025
This comprehensive guide explores Python’s anext function, which retrieves the next item from an asynchronous iterator. We’ll cover async iterators, error handling, and practical examples of asynchronous iteration.
Basic Definitions
The anext function is the async equivalent of next. It retrieves the next item from an asynchronous iterator or returns a default value if provided and iterator is exhausted.
Key characteristics: works with async iterators, must be awaited, raises StopAsyncIteration when exhausted (unless default is provided), and was introduced in Python 3.10.
Basic Async Iterator Usage
Here’s simple usage with an async iterator showing how anext retrieves values from an asynchronous source.
basic_anext.py
import asyncio
class AsyncCounter: def init(self, stop): self.current = 0 self.stop = stop
def __aiter__(self):
return self
async def __anext__(self):
if self.current >= self.stop:
raise StopAsyncIteration
await asyncio.sleep(0.1)
self.current += 1
return self.current
async def main(): counter = AsyncCounter(3) print(await anext(counter)) # 1 print(await anext(counter)) # 2 print(await anext(counter)) # 3
asyncio.run(main())
This example shows anext with a custom async iterator. Each call to anext must be awaited and returns the next value from the iterator.
The AsyncCounter class implements the async iterator protocol with aiter and anext methods. Note the StopAsyncIteration exception for signaling completion.
Using Default Value
anext can accept a default value to return instead of raising StopAsyncIteration when the iterator is exhausted.
default_value.py
import asyncio
async def async_gen(): yield “first” yield “second”
async def main(): ag = async_gen() print(await anext(ag)) # ‘first’ print(await anext(ag)) # ‘second’ print(await anext(ag, “default”)) # ‘default’
asyncio.run(main())
This example demonstrates the default value behavior. After yielding two values, the async generator is exhausted. The third anext call returns the default instead of raising an exception.
This pattern is useful when you want to handle the end of iteration without try/except blocks. The default can be any value, including None.
Error Handling
This example shows proper error handling when using anext with async iterators.
error_handling.py
import asyncio
async def failing_async_gen(): yield 1 raise ValueError(“Something went wrong”)
async def main(): ag = failing_async_gen() try: print(await anext(ag)) # 1 print(await anext(ag)) # Raises ValueError except ValueError as e: print(f"Caught error: {e}")
# Exhausted iterator case
ag = failing_async_gen()
try:
await anext(ag)
await anext(ag)
await anext(ag) # Would raise StopAsyncIteration
except StopAsyncIteration:
print("Iterator exhausted")
asyncio.run(main())
These examples demonstrate error handling with anext. The first case shows handling a custom exception from the iterator. The second shows catching StopAsyncIteration.
Proper error handling is crucial when working with async iterators as they can raise both iteration-related and domain-specific exceptions.
With Async Generators
anext works seamlessly with async generators, which are the most common way to create async iterators.
async_generators.py
import asyncio
async def async_data_fetcher(): for i in range(3): await asyncio.sleep(0.1) yield f"data-{i}"
async def main(): fetcher = async_data_fetcher() while True: try: data = await anext(fetcher) print(f"Received: {data}") except StopAsyncIteration: print(“No more data”) break
asyncio.run(main())
This example shows anext with an async generator function. The generator yields values asynchronously, and anext retrieves them one by one.
The while-try-except pattern is common when consuming async iterators where you don’t know the exact number of items in advance.
Real-world API Pagination
This example demonstrates a practical use case: paginating through an async API using anext.
api_pagination.py
import asyncio from typing import AsyncIterator, Dict, Any
class AsyncAPIClient: def init(self): self.page = 0
async def fetch_page(self) -> Dict[str, Any]:
self.page += 1
if self.page > 3:
return {"items": [], "has_more": False}
await asyncio.sleep(0.2)
return {
"items": [f"item-{self.page}-{i}" for i in range(2)],
"has_more": self.page < 3
}
def __aiter__(self) -> AsyncIterator[str]:
return self
async def __anext__(self) -> str:
if not hasattr(self, "_current_page"):
self._current_page = await self.fetch_page()
self._items_iter = iter(self._current_page["items"])
try:
return next(self._items_iter)
except StopIteration:
if not self._current_page["has_more"]:
raise StopAsyncIteration
self._current_page = await self.fetch_page()
self._items_iter = iter(self._current_page["items"])
return await self.__anext__()
async def main(): client = AsyncAPIClient() try: while True: item = await anext(client) print(f"Processing: {item}") except StopAsyncIteration: print(“All items processed”)
asyncio.run(main())
This example implements pagination through an async API. The AsyncAPIClient fetches pages of data and yields individual items. anext handles the iteration through both page items and page transitions.
The implementation shows how to manage complex async iteration state while providing a simple interface to consumers via anext.
Best Practices
-
Always await: Remember anext is a coroutine and must be awaited
-
Handle StopAsyncIteration: Either catch it or use a default value
-
Prefer async for: Use async for loops when possible instead of manual anext calls
-
Document behavior: Clearly document your async iterators’ behavior
-
Consider timeouts: For network operations, consider adding timeout handling
Source References
Author
My name is Jan Bodnar, and I am a passionate programmer with extensive programming experience. I have been writing programming articles since 2007. To date, I have authored over 1,400 articles and 8 e-books. I possess more than ten years of experience in teaching programming.
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