anext()

The built-in anext() function allows you to retrieve the next item from an asynchronous iterator in a controlled manner. It is particularly useful when you need to skip items or handle iteration manually, rather than using an async for loop:

Python asyn_gen.py 
import asyncio

async def async_generator():
    for i in range(3):
        yield i
        await asyncio.sleep(0.1)

# Usage
async def main():
    agen = async_generator()
    print(await anext(agen))  # Output: 0
    print(await anext(agen))  # Output: 1

asyncio.run(main())

anext() Signatures

Python Syntax 
anext(async_iterator)
anext(async_iterator, default)

Arguments

Argument Description Default Value
async_iterator The asynchronous iterator from which to retrieve the next item. Required argument
default The value to return if the iterator is exhausted, instead of raising an exception. Optional argument

Return Value

  • When awaited, anext() returns the next item from the provided asynchronous iterator.
  • If a default value is provided and the iterator is exhausted, anext() returns the default value.
  • If no default value is provided and the iterator is exhausted, StopAsyncIteration is raised.

anext() Examples

With an asynchronous iterator as an argument:

Python 
async def async_numbers():
    for number in range(3):
        yield number
        await asyncio.sleep(0.1)

# Usage
async def main():
    async_iter = async_numbers()
    print(await anext(async_iter))  # Output: 0
    print(await anext(async_iter))  # Output: 1
    print(await anext(async_iter))  # Output: 2

asyncio.run(main())

With a default value:

Python 
async def main():
    async_iter = async_numbers()
    print(await anext(async_iter, "No more items"))  # Output: 0
    print(await anext(async_iter, "No more items"))  # Output: 1
    print(await anext(async_iter, "No more items"))  # Output: 2
    print(await anext(async_iter, "No more items"))  # Output: No more items

asyncio.run(main())

anext() Common Use Cases

The most common use cases for the anext() function include:

  • Skipping initial items in an asynchronous iterator
  • Implementing custom iteration logic with asynchronous iterators
  • Handling potentially infinite asynchronous iterators where manual control over iteration is required

anext() Real-World Example

In this example, we’ll use anext() to process rows from an asynchronously read CSV file, skipping the header row:

Python async_csv.py 
import asyncio
import csv
import aiofiles

class AsyncCSVIterator:
    def __init__(self, path):
        self.path = path
        self.reader = None

    def __aiter__(self):
        return self

    async def __anext__(self):
        if self.reader is None:
            async with aiofiles.open(self.path, mode="r") as file:
                lines = await file.readlines()
                self.reader = csv.reader(lines)
        try:
            return next(self.reader)
        except StopIteration:
            raise StopAsyncIteration

async def main():
    csv_iter = AsyncCSVIterator("data.csv")
    await anext(csv_iter)  # Skip the headers
    async for row in csv_iter:
        print(row)

asyncio.run(main())

In this example, anext() lets you skip the header row of a CSV file before processing the data rows. This approach is helpful when working with files that have a known structure where certain rows need to be excluded from processing.

Asynchronous Iterators and Iterables in Python

Tutorial

Asynchronous Iterators and Iterables in Python

In this tutorial, you'll learn how to create and use asynchronous iterators and iterables in Python. You'll explore their syntax and structure and discover how they can be leveraged to handle asynchronous operations more efficiently.

advanced python

For additional information on related topics, take a look at the following resources:

By Leodanis Pozo Ramos • Updated Nov. 22, 2024 • Reviewed by Dan Bader
Python’s Built-in Functions Share Feedback