365 lines
13 KiB
Markdown
365 lines
13 KiB
Markdown
# Log Contexts
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To help track the processing of individual requests, synapse uses a
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'`log context`' to track which request it is handling at any given
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moment. This is done via a thread-local variable; a `logging.Filter` is
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then used to fish the information back out of the thread-local variable
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and add it to each log record.
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Logcontexts are also used for CPU and database accounting, so that we
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can track which requests were responsible for high CPU use or database
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activity.
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The `synapse.logging.context` module provides facilities for managing
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the current log context (as well as providing the `LoggingContextFilter`
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class).
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Asynchronous functions make the whole thing complicated, so this document describes
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how it all works, and how to write code which follows the rules.
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In this document, "awaitable" refers to any object which can be `await`ed. In the context of
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Synapse, that normally means either a coroutine or a Twisted
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[`Deferred`](https://twistedmatrix.com/documents/current/api/twisted.internet.defer.Deferred.html).
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## Logcontexts without asynchronous code
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In the absence of any asynchronous voodoo, things are simple enough. As with
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any code of this nature, the rule is that our function should leave
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things as it found them:
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```python
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from synapse.logging import context # omitted from future snippets
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def handle_request(request_id):
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request_context = context.LoggingContext()
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calling_context = context.set_current_context(request_context)
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try:
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request_context.request = request_id
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do_request_handling()
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logger.debug("finished")
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finally:
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context.set_current_context(calling_context)
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def do_request_handling():
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logger.debug("phew") # this will be logged against request_id
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```
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LoggingContext implements the context management methods, so the above
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can be written much more succinctly as:
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```python
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def handle_request(request_id):
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with context.LoggingContext() as request_context:
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request_context.request = request_id
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do_request_handling()
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logger.debug("finished")
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def do_request_handling():
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logger.debug("phew")
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```
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## Using logcontexts with awaitables
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Awaitables break the linear flow of code so that there is no longer a single entry point
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where we should set the logcontext and a single exit point where we should remove it.
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Consider the example above, where `do_request_handling` needs to do some
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blocking operation, and returns an awaitable:
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```python
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async def handle_request(request_id):
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with context.LoggingContext() as request_context:
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request_context.request = request_id
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await do_request_handling()
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logger.debug("finished")
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```
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In the above flow:
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- The logcontext is set
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- `do_request_handling` is called, and returns an awaitable
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- `handle_request` awaits the awaitable
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- Execution of `handle_request` is suspended
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So we have stopped processing the request (and will probably go on to
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start processing the next), without clearing the logcontext.
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To circumvent this problem, synapse code assumes that, wherever you have
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an awaitable, you will want to `await` it. To that end, wherever
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functions return awaitables, we adopt the following conventions:
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**Rules for functions returning awaitables:**
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> - If the awaitable is already complete, the function returns with the
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> same logcontext it started with.
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> - If the awaitable is incomplete, the function clears the logcontext
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> before returning; when the awaitable completes, it restores the
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> logcontext before running any callbacks.
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That sounds complicated, but actually it means a lot of code (including
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the example above) "just works". There are two cases:
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- If `do_request_handling` returns a completed awaitable, then the
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logcontext will still be in place. In this case, execution will
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continue immediately after the `await`; the "finished" line will
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be logged against the right context, and the `with` block restores
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the original context before we return to the caller.
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- If the returned awaitable is incomplete, `do_request_handling` clears
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the logcontext before returning. The logcontext is therefore clear
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when `handle_request` `await`s the awaitable.
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Once `do_request_handling`'s awaitable completes, it will reinstate
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the logcontext, before running the second half of `handle_request`,
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so again the "finished" line will be logged against the right context,
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and the `with` block restores the original context.
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As an aside, it's worth noting that `handle_request` follows our rules
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- though that only matters if the caller has its own logcontext which it
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cares about.
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The following sections describe pitfalls and helpful patterns when
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implementing these rules.
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Always await your awaitables
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----------------------------
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Whenever you get an awaitable back from a function, you should `await` on
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it as soon as possible. Do not pass go; do not do any logging; do not
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call any other functions.
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```python
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async def fun():
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logger.debug("starting")
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await do_some_stuff() # just like this
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coro = more_stuff()
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result = await coro # also fine, of course
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return result
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```
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Provided this pattern is followed all the way back up to the callchain
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to where the logcontext was set, this will make things work out ok:
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provided `do_some_stuff` and `more_stuff` follow the rules above, then
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so will `fun`.
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It's all too easy to forget to `await`: for instance if we forgot that
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`do_some_stuff` returned an awaitable, we might plough on regardless. This
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leads to a mess; it will probably work itself out eventually, but not
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before a load of stuff has been logged against the wrong context.
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(Normally, other things will break, more obviously, if you forget to
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`await`, so this tends not to be a major problem in practice.)
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Of course sometimes you need to do something a bit fancier with your
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awaitable - not all code follows the linear A-then-B-then-C pattern.
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Notes on implementing more complex patterns are in later sections.
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## Where you create a new awaitable, make it follow the rules
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Most of the time, an awaitable comes from another synapse function.
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Sometimes, though, we need to make up a new awaitable, or we get an awaitable
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back from external code. We need to make it follow our rules.
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The easy way to do it is by using `context.make_deferred_yieldable`. Suppose we want to implement
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`sleep`, which returns a deferred which will run its callbacks after a
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given number of seconds. That might look like:
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```python
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# not a logcontext-rules-compliant function
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def get_sleep_deferred(seconds):
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d = defer.Deferred()
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reactor.callLater(seconds, d.callback, None)
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return d
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```
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That doesn't follow the rules, but we can fix it by calling it through
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`context.make_deferred_yieldable`:
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```python
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async def sleep(seconds):
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return await context.make_deferred_yieldable(get_sleep_deferred(seconds))
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```
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## Fire-and-forget
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Sometimes you want to fire off a chain of execution, but not wait for
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its result. That might look a bit like this:
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```python
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async def do_request_handling():
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await foreground_operation()
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# *don't* do this
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background_operation()
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logger.debug("Request handling complete")
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async def background_operation():
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await first_background_step()
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logger.debug("Completed first step")
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await second_background_step()
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logger.debug("Completed second step")
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```
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The above code does a couple of steps in the background after
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`do_request_handling` has finished. The log lines are still logged
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against the `request_context` logcontext, which may or may not be
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desirable. There are two big problems with the above, however. The first
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problem is that, if `background_operation` returns an incomplete
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awaitable, it will expect its caller to `await` immediately, so will have
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cleared the logcontext. In this example, that means that 'Request
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handling complete' will be logged without any context.
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The second problem, which is potentially even worse, is that when the
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awaitable returned by `background_operation` completes, it will restore
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the original logcontext. There is nothing waiting on that awaitable, so
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the logcontext will leak into the reactor and possibly get attached to
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some arbitrary future operation.
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There are two potential solutions to this.
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One option is to surround the call to `background_operation` with a
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`PreserveLoggingContext` call. That will reset the logcontext before
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starting `background_operation` (so the context restored when the
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deferred completes will be the empty logcontext), and will restore the
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current logcontext before continuing the foreground process:
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```python
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async def do_request_handling():
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await foreground_operation()
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# start background_operation off in the empty logcontext, to
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# avoid leaking the current context into the reactor.
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with PreserveLoggingContext():
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background_operation()
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# this will now be logged against the request context
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logger.debug("Request handling complete")
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```
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Obviously that option means that the operations done in
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`background_operation` would be not be logged against a logcontext
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(though that might be fixed by setting a different logcontext via a
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`with LoggingContext(...)` in `background_operation`).
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The second option is to use `context.run_in_background`, which wraps a
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function so that it doesn't reset the logcontext even when it returns
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an incomplete awaitable, and adds a callback to the returned awaitable to
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reset the logcontext. In other words, it turns a function that follows
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the Synapse rules about logcontexts and awaitables into one which behaves
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more like an external function --- the opposite operation to that
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described in the previous section. It can be used like this:
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```python
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async def do_request_handling():
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await foreground_operation()
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context.run_in_background(background_operation)
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# this will now be logged against the request context
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logger.debug("Request handling complete")
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```
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## Passing synapse deferreds into third-party functions
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A typical example of this is where we want to collect together two or
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more awaitables via `defer.gatherResults`:
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```python
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a1 = operation1()
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a2 = operation2()
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a3 = defer.gatherResults([a1, a2])
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```
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This is really a variation of the fire-and-forget problem above, in that
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we are firing off `a1` and `a2` without awaiting on them. The difference
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is that we now have third-party code attached to their callbacks. Anyway
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either technique given in the [Fire-and-forget](#fire-and-forget)
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section will work.
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Of course, the new awaitable returned by `gather` needs to be
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wrapped in order to make it follow the logcontext rules before we can
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yield it, as described in [Where you create a new awaitable, make it
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follow the
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rules](#where-you-create-a-new-awaitable-make-it-follow-the-rules).
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So, option one: reset the logcontext before starting the operations to
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be gathered:
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```python
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async def do_request_handling():
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with PreserveLoggingContext():
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a1 = operation1()
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a2 = operation2()
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result = await defer.gatherResults([a1, a2])
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```
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In this case particularly, though, option two, of using
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`context.run_in_background` almost certainly makes more sense, so that
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`operation1` and `operation2` are both logged against the original
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logcontext. This looks like:
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```python
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async def do_request_handling():
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a1 = context.run_in_background(operation1)
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a2 = context.run_in_background(operation2)
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result = await make_deferred_yieldable(defer.gatherResults([a1, a2]))
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```
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## A note on garbage-collection of awaitable chains
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It turns out that our logcontext rules do not play nicely with awaitable
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chains which get orphaned and garbage-collected.
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Imagine we have some code that looks like this:
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```python
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listener_queue = []
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def on_something_interesting():
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for d in listener_queue:
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d.callback("foo")
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async def await_something_interesting():
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new_awaitable = defer.Deferred()
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listener_queue.append(new_awaitable)
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with PreserveLoggingContext():
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await new_awaitable
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```
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Obviously, the idea here is that we have a bunch of things which are
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waiting for an event. (It's just an example of the problem here, but a
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relatively common one.)
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Now let's imagine two further things happen. First of all, whatever was
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waiting for the interesting thing goes away. (Perhaps the request times
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out, or something *even more* interesting happens.)
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Secondly, let's suppose that we decide that the interesting thing is
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never going to happen, and we reset the listener queue:
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```python
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def reset_listener_queue():
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listener_queue.clear()
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```
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So, both ends of the awaitable chain have now dropped their references,
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and the awaitable chain is now orphaned, and will be garbage-collected at
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some point. Note that `await_something_interesting` is a coroutine,
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which Python implements as a generator function. When Python
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garbage-collects generator functions, it gives them a chance to
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clean up by making the `await` (or `yield`) raise a `GeneratorExit`
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exception. In our case, that means that the `__exit__` handler of
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`PreserveLoggingContext` will carefully restore the request context, but
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there is now nothing waiting for its return, so the request context is
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never cleared.
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To reiterate, this problem only arises when *both* ends of a awaitable
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chain are dropped. Dropping the the reference to an awaitable you're
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supposed to be awaiting is bad practice, so this doesn't
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actually happen too much. Unfortunately, when it does happen, it will
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lead to leaked logcontexts which are incredibly hard to track down.
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