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Nanoservices

Midst of the nanoservices talk
Midst of the nanoservices talk

Python has an Iterator Protocol that generators implement. Generators also offer lesser known methods send and throw. Reuven’s talk describes how these two facts together enable generators to create a stateful “nanoservice”.

Some might think yield from is just syntactic sugar for yielding within a for loop. The talk is tied together with a meaningful use case for yield from to connect subroutines within the nanoservice.

To see how a nanoservice could look:

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import contextlib
import itertools
from collections import deque
from collections.abc import Generator, Iterable
from typing import Any


class DumpData(Exception):
    """Exception used to indicate the window's contents should be dumped."""


class ClearWindow(Exception):
    """Exception used to indicate the window should be cleared."""


def moving_window_average_gen(
    data: Iterable[float] = (),
    window_size: int = 3,
) -> Generator[float | int | None, float, None]:
    """Run a nanoservice for a simple moving window average.

    Starter: https://docs.python.org/3/library/collections.html#deque-recipes

    Args:
        data: Data to pre-fill into the deque, to avoid bias from little data.
        window_size: Window size for the moving window average.

    Returns:
        Generator that intakes a new value and returns an average.
    """
    window = deque(data, maxlen=window_size)
    current_sum = sum(window)

    def on_new_value(value: Any) -> float:
        if not isinstance(value, int | float):
            raise TypeError(f"Please send in numbers, not {type(value)}.")
        nonlocal current_sum
        current_sum += value if len(window) < window_size else value - window.popleft()
        window.append(value)
        return current_sum / len(window)

    out_value: float | None = None
    while True:
        try:
            print("MWA nanoservice: waiting after yield.")
            in_value = yield out_value
        except DumpData:
            print("MWA nanoservice: providing length.")
            yield len(window)
            print("MWA nanoservice: dumping data.")
            # NOTE: use islice since deque doesn't support slicing
            yield from itertools.islice(window, len(window) - 1)
            out_value = window[-1]  # Trick to avoid extra next call
            continue
        except ClearWindow:
            print("MWA nanoservice: clearing window.")
            window.clear()
            current_sum = 0
            out_value = None
            continue
        except GeneratorExit:
            print("MWA nanoservice: exiting.")
            raise

        try:
            out_value = on_new_value(in_value)
        except TypeError:
            print(f"MWA nanoservice: rejected input {in_value!r}.")
            out_value = None


def demo() -> None:
    mwa_nanoservice = moving_window_average_gen()
    next(mwa_nanoservice)  # Initialize to first yield

    # 1. General usage
    assert mwa_nanoservice.send(5) == 5
    assert mwa_nanoservice.send(7) == 6
    # Check we handle someone forgetting a value or sending wrong type
    assert next(mwa_nanoservice) is None
    assert mwa_nanoservice.send("unexpected") is None  # type: ignore[arg-type]
    assert mwa_nanoservice.send(9) == 7
    assert mwa_nanoservice.send(11) == 9

    # 2. Dumping all data from moving window
    num_datapoints = mwa_nanoservice.throw(DumpData)
    assert tuple(
        next(mwa_nanoservice) for _ in range(num_datapoints)  # type: ignore[arg-type]
    ) == (7, 9, 11)
    assert mwa_nanoservice.send(13) == 11

    # 3. Clearing the window's contents
    assert mwa_nanoservice.throw(ClearWindow) is None
    assert mwa_nanoservice.send(15) == 15

    # 4. Shut down the nanoservice
    mwa_nanoservice.close()
    with contextlib.suppress(StopIteration):
        assert mwa_nanoservice.send(17) is None