Log Contexts

To help track the processing of individual requests, synapse uses a 'log context' to track which request it is handling at any given moment. This is done via a thread-local variable; a logging.Filter is then used to fish the information back out of the thread-local variable and add it to each log record.

Logcontexts are also used for CPU and database accounting, so that we can track which requests were responsible for high CPU use or database activity.

The synapse.logging.context module provides a facilities for managing the current log context (as well as providing the LoggingContextFilter class).

Asynchronous functions make the whole thing complicated, so this document describes how it all works, and how to write code which follows the rules.

In this document, "awaitable" refers to any object which can be awaited. In the context of Synapse, that normally means either a coroutine or a Twisted Deferred.

Logcontexts without asynchronous code

In the absence of any asynchronous voodoo, things are simple enough. As with any code of this nature, the rule is that our function should leave things as it found them:

from synapse.logging import context         # omitted from future snippets

def handle_request(request_id):
    request_context = context.LoggingContext()

    calling_context = context.set_current_context(request_context)
    try:
        request_context.request = request_id
        do_request_handling()
        logger.debug("finished")
    finally:
        context.set_current_context(calling_context)

def do_request_handling():
    logger.debug("phew")  # this will be logged against request_id

LoggingContext implements the context management methods, so the above can be written much more succinctly as:

def handle_request(request_id):
    with context.LoggingContext() as request_context:
        request_context.request = request_id
        do_request_handling()
        logger.debug("finished")

def do_request_handling():
    logger.debug("phew")

Using logcontexts with awaitables

Awaitables break the linear flow of code so that there is no longer a single entry point where we should set the logcontext and a single exit point where we should remove it.

Consider the example above, where do_request_handling needs to do some blocking operation, and returns an awaitable:

async def handle_request(request_id):
    with context.LoggingContext() as request_context:
        request_context.request = request_id
        await do_request_handling()
        logger.debug("finished")

In the above flow:

The logcontext is set
do_request_handling is called, and returns an awaitable
handle_request awaits the awaitable
Execution of handle_request is suspended

So we have stopped processing the request (and will probably go on to start processing the next), without clearing the logcontext.

To circumvent this problem, synapse code assumes that, wherever you have an awaitable, you will want to await it. To that end, whereever functions return awaitables, we adopt the following conventions:

Rules for functions returning awaitables:

If the awaitable is already complete, the function returns with the same logcontext it started with.

If the awaitable is incomplete, the function clears the logcontext before returning; when the awaitable completes, it restores the logcontext before running any callbacks.

That sounds complicated, but actually it means a lot of code (including the example above) "just works". There are two cases:

If do_request_handling returns a completed awaitable, then the logcontext will still be in place. In this case, execution will continue immediately after the await; the "finished" line will be logged against the right context, and the with block restores the original context before we return to the caller.
If the returned awaitable is incomplete, do_request_handling clears the logcontext before returning. The logcontext is therefore clear when handle_request awaits the awaitable.

Once do_request_handling's awaitable completes, it will reinstate the logcontext, before running the second half of handle_request, so again the "finished" line will be logged against the right context, and the with block restores the original context.

As an aside, it's worth noting that handle_request follows our rules

though that only matters if the caller has its own logcontext which it cares about.

The following sections describe pitfalls and helpful patterns when implementing these rules.

Always await your awaitables

Whenever you get an awaitable back from a function, you should await on it as soon as possible. Do not pass go; do not do any logging; do not call any other functions.

async def fun():
    logger.debug("starting")
    await do_some_stuff()       # just like this

    coro = more_stuff()
    result = await coro         # also fine, of course

    return result

Provided this pattern is followed all the way back up to the callchain to where the logcontext was set, this will make things work out ok: provided do_some_stuff and more_stuff follow the rules above, then so will fun.

It's all too easy to forget to await: for instance if we forgot that do_some_stuff returned an awaitable, we might plough on regardless. This leads to a mess; it will probably work itself out eventually, but not before a load of stuff has been logged against the wrong context. (Normally, other things will break, more obviously, if you forget to await, so this tends not to be a major problem in practice.)

Of course sometimes you need to do something a bit fancier with your awaitable - not all code follows the linear A-then-B-then-C pattern. Notes on implementing more complex patterns are in later sections.

Where you create a new awaitable, make it follow the rules

Most of the time, an awaitable comes from another synapse function. Sometimes, though, we need to make up a new awaitable, or we get an awaitable back from external code. We need to make it follow our rules.

The easy way to do it is by using context.make_deferred_yieldable. Suppose we want to implement sleep, which returns a deferred which will run its callbacks after a given number of seconds. That might look like:

# not a logcontext-rules-compliant function
def get_sleep_deferred(seconds):
    d = defer.Deferred()
    reactor.callLater(seconds, d.callback, None)
    return d

That doesn't follow the rules, but we can fix it by calling it through context.make_deferred_yieldable:

async def sleep(seconds):
    return await context.make_deferred_yieldable(get_sleep_deferred(seconds))

Fire-and-forget

Sometimes you want to fire off a chain of execution, but not wait for its result. That might look a bit like this:

async def do_request_handling():
    await foreground_operation()

    # *don't* do this
    background_operation()

    logger.debug("Request handling complete")

async def background_operation():
    await first_background_step()
    logger.debug("Completed first step")
    await second_background_step()
    logger.debug("Completed second step")

The above code does a couple of steps in the background after do_request_handling has finished. The log lines are still logged against the request_context logcontext, which may or may not be desirable. There are two big problems with the above, however. The first problem is that, if background_operation returns an incomplete awaitable, it will expect its caller to await immediately, so will have cleared the logcontext. In this example, that means that 'Request handling complete' will be logged without any context.

The second problem, which is potentially even worse, is that when the awaitable returned by background_operation completes, it will restore the original logcontext. There is nothing waiting on that awaitable, so the logcontext will leak into the reactor and possibly get attached to some arbitrary future operation.

There are two potential solutions to this.

One option is to surround the call to background_operation with a PreserveLoggingContext call. That will reset the logcontext before starting background_operation (so the context restored when the deferred completes will be the empty logcontext), and will restore the current logcontext before continuing the foreground process:

async def do_request_handling():
    await foreground_operation()

    # start background_operation off in the empty logcontext, to
    # avoid leaking the current context into the reactor.
    with PreserveLoggingContext():
        background_operation()

    # this will now be logged against the request context
    logger.debug("Request handling complete")

Obviously that option means that the operations done in background_operation would be not be logged against a logcontext (though that might be fixed by setting a different logcontext via a with LoggingContext(...) in background_operation).

The second option is to use context.run_in_background, which wraps a function so that it doesn't reset the logcontext even when it returns an incomplete awaitable, and adds a callback to the returned awaitable to reset the logcontext. In other words, it turns a function that follows the Synapse rules about logcontexts and awaitables into one which behaves more like an external function --- the opposite operation to that described in the previous section. It can be used like this:

async def do_request_handling():
    await foreground_operation()

    context.run_in_background(background_operation)

    # this will now be logged against the request context
    logger.debug("Request handling complete")

Passing synapse deferreds into third-party functions

A typical example of this is where we want to collect together two or more awaitables via defer.gatherResults:

a1 = operation1()
a2 = operation2()
a3 = defer.gatherResults([a1, a2])

This is really a variation of the fire-and-forget problem above, in that we are firing off a1 and a2 without awaiting on them. The difference is that we now have third-party code attached to their callbacks. Anyway either technique given in the Fire-and-forget section will work.

Of course, the new awaitable returned by gather needs to be wrapped in order to make it follow the logcontext rules before we can yield it, as described in Where you create a new awaitable, make it follow the rules.

So, option one: reset the logcontext before starting the operations to be gathered:

async def do_request_handling():
    with PreserveLoggingContext():
        a1 = operation1()
        a2 = operation2()
        result = await defer.gatherResults([a1, a2])

In this case particularly, though, option two, of using context.run_in_background almost certainly makes more sense, so that operation1 and operation2 are both logged against the original logcontext. This looks like:

async def do_request_handling():
    a1 = context.run_in_background(operation1)
    a2 = context.run_in_background(operation2)

    result = await make_deferred_yieldable(defer.gatherResults([a1, a2]))

A note on garbage-collection of awaitable chains

It turns out that our logcontext rules do not play nicely with awaitable chains which get orphaned and garbage-collected.

Imagine we have some code that looks like this:

listener_queue = []

def on_something_interesting():
    for d in listener_queue:
        d.callback("foo")

async def await_something_interesting():
    new_awaitable = defer.Deferred()
    listener_queue.append(new_awaitable)

    with PreserveLoggingContext():
        await new_awaitable

Obviously, the idea here is that we have a bunch of things which are waiting for an event. (It's just an example of the problem here, but a relatively common one.)

Now let's imagine two further things happen. First of all, whatever was waiting for the interesting thing goes away. (Perhaps the request times out, or something even more interesting happens.)

Secondly, let's suppose that we decide that the interesting thing is never going to happen, and we reset the listener queue:

def reset_listener_queue():
    listener_queue.clear()

So, both ends of the awaitable chain have now dropped their references, and the awaitable chain is now orphaned, and will be garbage-collected at some point. Note that await_something_interesting is a coroutine, which Python implements as a generator function. When Python garbage-collects generator functions, it gives them a chance to clean up by making the async (or yield) raise a GeneratorExit exception. In our case, that means that the __exit__ handler of PreserveLoggingContext will carefully restore the request context, but there is now nothing waiting for its return, so the request context is never cleared.

To reiterate, this problem only arises when both ends of a awaitable chain are dropped. Dropping the the reference to an awaitable you're supposed to be awaiting is bad practice, so this doesn't actually happen too much. Unfortunately, when it does happen, it will lead to leaked logcontexts which are incredibly hard to track down.

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