tinyio 0.1.2

A tiny event loop for Python.

tinyio

A tiny (~200 lines) event loop for Python

Ever used asyncio and wished you hadn't?

tinyio is a dead-simple event loop for Python, born out of my frustration with trying to get robust error handling with asyncio. (I'm not the only one running into its sharp corners: link1, link2.)

This is an alternative for the simple use-cases, where you just need an event loop, and want to crash the whole thing if anything goes wrong. (Raising an exception in every coroutine so it can clean up its resources.)

import tinyio

def slow_add_one(x: int):
    yield tinyio.sleep(1)
    return x + 1

def foo():
    four, five = yield [slow_add_one(3), slow_add_one(4)]
    return four, five

loop = tinyio.Loop()
out = loop.run(foo())
assert out == (4, 5)

• Somewhat unusually, our syntax uses yield rather than await, but the behaviour is the same. Await another coroutine with yield coro. Await on multiple with yield [coro1, coro2, ...] (a 'gather' in asyncio terminology; a 'nursery' in trio terminology).
• An error in one coroutine will cancel all coroutines across the entire event loop.
  • If the erroring coroutine is sequentially depended on by a chain of other coroutines, then we chain their tracebacks for easier debugging.
  • Errors even propagate to and from synchronous operations ran in threads.
• Can nest tinyio loops inside each other, none of this one-per-thread business.
• Ludicrously simple. No need for futures, tasks, etc. Here's the full API:

  tinyio.Loop
  tinyio.run_in_thread
  tinyio.sleep
  tinyio.CancelledError
  

Installation

pip install tinyio

Documentation

Loops

Create a loop with tinyio.Loop(). It has a single method, .run(coro), which consumes a coroutine, and which returns the output of that coroutine.

Coroutines can yield four possible things:

• yield: yield nothing, this just pauses and gives other coroutines a chance to run.
• yield coro: wait on a single coroutine, in which case we'll resume with the output of that coroutine once it is available.
• yield [coro1, coro2, coro3]: wait on multiple coroutines by putting them in a list, and resume with a list of outputs once all have completed. This is what asyncio calls a 'gather' or 'TaskGroup', and what trio calls a 'nursery'.
• yield {coro1, coro2, coro3}: schedule one or more coroutines but do not wait on their result - they will run independently in the background.

You can safely yield the same coroutine multiple times, e.g. perhaps four coroutines have a diamond dependency pattern, with two coroutines each depending on a single shared one.

Threading

Synchronous functions can be ran in threads using tinyio.run_in_thread(fn, *args, **kwargs), which returns a coroutine you can yield on:

import time, tinyio

def slow_blocking_add_one(x: int) -> int:
    time.sleep(1)
    return x + 1

def foo(x: int):
    out = yield [tinyio.run_in_thread(slow_blocking_add_one, x) for _ in range(3)]
    return out

loop = tinyio.Loop()
out = loop.run(foo(x=1))  # runs in one second, not three
assert out == [2, 2, 2]

The thread will call fn(*args, **kwargs).

Sleeping

This is tinyio.sleep(delay_in_seconds), which is a coroutine you can yield on.

Error propagation

If any coroutine raises an error, then:

1. All coroutines across the entire loop will have tinyio.CancelledError raised in them (from whatever yield point they are currently waiting at).
2. Any functions ran in threads via tinyio.run_in_thread will also have tinyio.CancelledError raised in the thread.
3. The original error is raised out of loop.run(...). This behaviour can be configured (e.g. to collect errors into a BaseExceptionGroup) by setting loop.run(..., exception_group=None/False/True).

This gives every coroutine a chance to shut down gracefully. Debuggers like patdb offer the ability to navigate across exceptions in an exception group, allowing you to inspect the state of all coroutines that were related to the error.

FAQ

Why yield - why not await like is normally seen for coroutines?

The reason is that await does not offer a suspension point to an event loop (it just calls __await__ and maybe that offers a suspension point), so if we wanted to use that syntax then we'd need to replace yield coro with something like await tinyio.Task(coro). The traditional syntax is not worth the extra class.

I have a function I want to be a coroutine, but it has zero yield statements, so it is just a normal function?

You can distinguish it from a normal Python function by putting if False: yield somewhere inside its body. Another common trick is to put a yield statement after the final return statement. Bit ugly but oh well.

Any funny business to know around loops?

The output of each coroutine is stored on the Loop() class. If you attempt to run a previously-ran coroutine in a new Loop() then they will be treated as just returning None, which is probably not what you want.

vs asyncio or trio?.

I wasted a lot of time trying to get correct error propagation with asyncio, trying to reason whether my tasks would be cleaned up correctly or not (edge-triggered vs level-triggered etc etc). trio is excellent but still has a one-loop-per-thread rule, and doesn't propagate cancellations to/from threads. These points inspired me to try writing my own.

Nonetheless you'll definitely still want one of the above if you need anything fancy. If you don't, and you really really want simple error semantics, then maybe tinyio is for you instead. (In particular trio will be a better choice if you still need the event loop when cleaning up from errors; in contrast tinyio does not allow scheduling work back on the event loop at that time.)