Generator-based operators for asynchronous iteration

aiostream provides a collection of stream operators that can be combined to create asynchronous pipelines of operations.

It can be seen as an asynchronous version of itertools, although some aspects are slightly different. Essentially, all the provided operators return a unified interface called a stream. A stream is an enhanced asynchronous iterable providing the following features:

• Operator pipe-lining - using pipe symbol |
• Repeatability - every iteration creates a different iterator
• Safe iteration context - using async with and the stream method
• Simplified execution - get the last element from a stream using await
• Slicing and indexing - using square brackets []
• Concatenation - using addition symbol +

The stream operators rely heavily on asynchronous generators (PEP 525):

• python >= 3.6

The stream operators are separated in 7 categories:

The following example demonstrates most of the streams capabilities:

import asyncio
from aiostream import stream, pipe


async def main():

    # Create a counting stream with a 0.2 seconds interval
    xs = stream.count(interval=0.2)

    # Operators can be piped using '|'
    ys = xs | pipe.map(lambda x: x**2)

    # Streams can be sliced
    zs = ys[1:10:2]

    # Use a stream context for proper resource management
    async with zs.stream() as streamer:

        # Asynchronous iteration
        async for z in streamer:

            # Print 1, 9, 25, 49 and 81
            print('->', z)

    # Streams can be awaited and return the last value
    print('9² = ', await zs)

    # Streams can run several times
    print('9² = ', await zs)

    # Streams can be concatenated
    one_two_three = stream.just(1) + stream.range(2, 4)

    # Print [1, 2, 3]
    print(await stream.list(one_two_three))


# Run main coroutine
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
loop.close()

More examples are available in the example section of the documentation.

Vincent Michel: [email protected]