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Task scopes for AnyIO

Project description

This library implements scoped taskgroups / nurseries.

Rationale

Composability

Large programs often consist of building blocks which depend on each other. Those dependencies may be non-trivial, aren’t always linear, and generally form some sort of directed acyclic graph instead of a nice linear or hierarchical set of relationships.

Let’s invent an example.

Your server contains some admin module, which requires a support library, which connects to a database. Halfway through it encounters an error, thus loads an error handler, which also uses the database.

Next, a client of your server does some shady stuff so you want to log that, and since loading the error handler and connecting to the database is expensive you want to re-use the handler you already have.

Later the admin code terminates. However, it shouldn’t unload the error handler, because that other code still needs it.

This is a problem because you like to use Structured Programming principles, which state that if you started it you need to stop it. Thus, you need to jump through some hoops getting all of this connected up, keeping track of each module’s users, and shutting things down in the correct order.

Worse: let’s say that your code dies with a fatal exception. That exception typically propagates through all of your code and thus tends to cancel the database connection before the error handler has a chance to log the problem. Worse, if the error from the logger occurs in a finally: block it basically replaces the original exception, so you’ll have a lot of fun trying to debug all of this.

AsyncScope can help you.

AsyncScope keeps track of your program’s building blocks. It remembers which parts depend on which other parts, prevents cyclic dependencies, and terminates a scope as soon as nobody uses it any more.

Now your error handler stays around exactly as long as you need it, your database connection won’t die while the error handler (or any other code) requires it, your error gets logged correctly, and you find the problem.

Multiple services

Some programs need any number of async contexts, e.g. a client that talks to any number of servers within the same method. Creating server contexts is often awkward under these circumstances; you need a subtask or an contextlib.AsyncExitStack to act as the contexts’ “keeper”. However, setting up a subtask is a lot of boilerplate; an exit stack doesn’t help when you need to dynamically remove servers.

AsyncScope helps by decoupling code structure from service usage, while ensuring that external connections and other subtasks are not duplicated and ended cleanly when their last user terminates.

Usage

Main code

Wrap your main code in an async with asyncscope.main_scope('NAME'): ... block. (The name defaults to _main if omitted.)

This call initializes the global AsyncScope.scope object. It always refers to the current service (i.e. initially, your main code).

Wrapping services

A “service” is defined as any nontrivial object that might be used from multiple contexts within your program. That can be a HTTP session, or a database connection, any object that’s non-trivial to create, …

AsyncScope requires wrapping your service in a function with common calling conventions because it doesn’t know (indeed doesn’t want to know) the details of how to set up and tear down your service objects.

Here are some examples.

If the service uses a run method, you’d do this:

from asyncscope import scope

async def some_service(*p, **kw):
   srv = your_service(*p, **kw)
   async with anyio.create_task_group() as tg:
      await tg.start(srv.run)

      scope.register(srv)
      await scope.no_more_dependents()

      await srv.stop_running()
      tg.cancel_scope.cancel()

Alternately, if the service runs as an async context manager:

from asyncscope import scope

async def some_service(*p, **kw):
   async with your_service(*p, **kw) as srv:
      # NB: some services use "async with await …"
      scope.register(srv)
      await scope.no_more_dependents()

Alternately², it might run as a context-free background service:

from asyncscope import scope

async def some_service(*p, **kw):
   srv = your_service(*p, **kw)
   srv = await srv.start()

   scope.register(srv)
   await scope.no_more_dependents()

   await srv.aclose()

Alternately³, if the service is an annoying-to-set-up object:

from asyncscope import scope

async def some_service(*p, **kw):
   srv = SomeObject(*p, **kw)
   await SomeObject.costly_setup()

   scope.register(srv)
   try:
      await scope.no_more_dependents()
   finally:
      srv.teardown()
   # use this to e.g. clean up circular references within your object

Next, we’ll see how to use these objects.

Using services

Using AsyncScope, a service is used in one of two ways.

  • within a context:

    from asyncscope import scope
    
    async with scope.using_service(name, some_service, *p, **kw) as srv:
       ...
  • until the caller’s scope ends or you explicitly release it:

    from asyncscope import scope
    
    srv = await scope.service(name, some_service, *p, **kw)
    ...
    del srv  # don't hog the memory!
    scope.release(name)
  • check whether a named service exists:

    from asyncscope import scope
    
    try:
        srv = scope.lookup(name)
    except KeyError:
       pass  # no it does not
    else:
       ...
       del srv
       scope.release(name)

In all three cases srv is the object that your some_service code has passed to AsyncScope.Scope.register.

Service naming

AsyncScope uses name to discover whether the service is already up and running. If so, it records that the current scope is also using this named service and simply returns it.

Names must be globally unique. To avoid collisions, add your object class, an idenifier like id(YourServiceClass), or id(container_object) to it, depending on usage.

AsyncScope does not try to derive uniqueness from its parameters, because arbitrary naming conventions are unlikely to work for everybody. One easy way to disambiguate potential collisions is to include id(some_service) in the name.

Implications

Calling Scope.service or Scope.using_service does not guarantee that the service in question will start when you do: it might have been running already. Likewise, leaving the async with block or exiting the caller’s scope may not stop the service: there might be other users, or some caching mechanism that delays closing it.

Calling these functions twice / nesting Scope.using_service calls is OK. Usage cycles (service A starts service B which later requires A) are forbidden and will be detected.

Every scope contains a taskgroup which you can access using the usual start and start_soon methods. You can also call scope.spawn(). This function returns a CancelScope that wraps the new tasks, so you can cancel it if you need to. All tasks started this way are also auto-cancelled when the scope exits.

Your some_service code must call scope.register() exactly once, otherwise the scopes waiting for it to start will wait forever. (They’ll get cancelled if your scope’s main task exits before doing so.)

The current scope is available as the scope context variable.

The examples directory contains some sample code.

Loggging

scope.logger is a standard logging.Logger object, named scope.NAME.

Multithreading

AsyncScope is not compatible with multithreading. Using a single main scope from multiple threads will cause inconsistent data, deadlocks, and/or other hard-to-find bugs.

If you start a separate async mainloop in a new thread, you must call scope.thread_reset() before entering the thread’s main scope. You also should pass a thread-specific name to main_scope.

Do not share services between threads. They are typically not multithreading-aware and AsyncScope might terminate them at any time.

Exception handling

This section describes the effects of an exception that escapes from a service’s main task, causing it to terminate.

Errors that are subclasses of BaseException but not Exception are never caught. If the service did not yet call Scope.register they may receive either a concurrent.Futures.CancelledError, or a cancellation exception from the async framework.

Exceptions raised after the service called Scope.register are not handled. They will ultimately propagate out of the AsyncScope.main_scope block.

Otherwise the error are propagated to the caller(s) that are waiting for its Scope.register call.

Otherwise the exception is left unhandled; the effects are described in the nest section.

Cancellation semantics

When a scope exits (either cleanly or when it raises an error that escapes its taskgroup), the scopes depending on it are cancelled immediately, in parallel. Then, those it itself depends on are terminated cleanly and in-order, assuming they’re not used by some other scope.

This also happens when a scope’s main task ends.

“Clean termination” means that the scope’s call to no_more_dependents() returns. If there is no such call open, the scope’s tasks are cancelled.

TODO: write a service which your code can use to keep another service alive for a bit.

Code structure

A scope’s main code typically looks like this:

  • do whatever you need to start the service. This code may start other scopes it depends on. Note that if the scope is already running, service simply returns its existing service object.

  • call scope.register(serice_object)

  • call await scope.no_more_dependents() (subordinate task) or wait for SIGTERM (daemon main task) or terminate (main task’s job is done)

  • cleanly stop your service.

If no_more_dependents is not used, your code will be cancelled instead.

Scopes typically don’t need to access their own scope object. It’s stored in a contextvar and can be retrieved via scope.get() if you need it. For most uses, however, asyncscope’s global scope object accesses the current scope transparently.

Temporary services

Some services don’t need to be running all the time. To release a service early, use async with scope.subscope():. This creates an embeeded scope. Services started within this subscope are auto-released when it exits, assuming as usual that no other code uses them.

When a (sub)scope’s main task ends, any still-running tasks running within its task group are cancelled instead of waiting for them to end (as a “normal” task group would).

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