This document introduces Deferred
s, Twisted's preferred mechanism for controlling
the flow of asynchronous code. Don't worry if you don't know what that means
yet—that's why you are here!
It is intended for newcomers to Twisted, and was written particularly to help
people read and understand code that already uses
Deferred
s.
This document assumes you have a good working knowledge of Python. It assumes no knowledge of Twisted.
By the end of the document, you should understand
what Deferred
s are and
how they can be used to coordinate asynchronous code. In particular, you
should be able to:
- Read and understand code that uses
Deferred
s - Translate from synchronous code to asynchronous code and back again
- Implement any sort of error-handling for asynchronous code that you wish
The joy of order
When you write Python code, one prevailing, deep, unassailled assumption is that a line of code within a block is only ever executed after the preceding line is finished.
1 2
pod_bay_doors.open() pod.launch()
The pod bay doors open, and only then does the pod launch. That's wonderful. One-line-after-another is a built-in mechanism in the language for encoding the order of execution. It's clear, terse, and unambiguous.
Exceptions make things more complicated. If
pod_bay_doors.open()
raises an exception, then
we cannot know with certainty that it completed, and so it would be wrong to
proceed blithely to the next line. Thus, Python gives us
try
, except
,
finally
and else
,
which together model almost every conceivable way of handling a raised
exception, and tend to work really well.
Function application is the other way we encode order of execution:
1
pprint(sorted(x.get_names()))
First x.get_names()
gets called,
then sorted
is called with its return value, and
then pprint
with
whatever sorted
returns. It can also be written
as:
1 2 3
names = x.get_names() sorted_names = sorted(names) pprint(sorted_names)
Sometimes it leads us to encode the order when we don't need to, as in this example:
1 2 3 4
total = 0 for account in accounts: total += account.get_balance() print "Total balance $%s" % (total,)
But that's normally not such a big deal.
All in all, things are pretty good, and all of the explanation above is laboring familiar and obvious points. One line comes after another and one thing happens after another, and both facts are inextricably tied.
But what if we had to do it differently?
A hypothetical problem
What if we could no longer rely on the previous line of code being finished
(whatever that means) before we started to interpret & execute the next
line of code? What if pod_bay_doors.open()
returned immediately, triggering something somewhere else that would
eventually open the pod bay doors, recklessly sending the Python interpreter
plunging into pod.launch()
?
That is, what would we do if the order of execution did not match the order
of lines of Python? If returning
no longer meant finishing
?
In other words, how can we deal with asynchronous operations?
How would we prevent our pod from hurtling into the still-closed doors? How could we respond to a potential failure to open the doors at all? What if opening the doors gave us some crucial information that we needed in order to launch the pod? How would we get access to that information?
And, crucially, since we are writing code, how can we write our code so that we can build other code on top of it?
The components of a solution
We would still need a way of saying do this only
when that has finished
.
We would need a way of distinguishing between successful completion and
interrupted processing, normally modeled with try
,
expect
, else
, and
finally
.
We need a mechanism for getting return failures and exception information from the thing that just executed to the thing that needs to happen next.
We need somehow to be able to operate on results that we don't have yet. Instead of acting, we need to make and encode plans for how we would act if we could.
Unless we hack the interpreter somehow, we would need to build this with the Python language constructs we are given: methods, functions, objects, and the like.
Perhaps we want something that looks a little like this:
1 2
placeholder = pod_bay_doors.open() placeholder.when_done(pod.launch)
One solution: Deferred
Twisted tackles this problem with
Deferred
s,
a type of object designed to do one thing, and one thing only: encode an
order of execution separately from the order of lines in Python source code.
It doesn't deal with threads, parallelism, signals, or subprocesses. It doesn't know anything about an event loop, greenlets, or scheduling. All it knows about is what order to do things in. How does it know that? Because we explicitly tell it the order that we want.
Thus, instead of writing:
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pod_bay_doors.open() pod.launch()
We write:
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d = pod_bay_doors.open() d.addCallback(lambda ignored: pod.launch())
That introduced a dozen new concepts in a couple of lines of code, so let's break it down. If you think you've got it, you might want to skip to the next section.
Here, pod_bay_doors.open()
is returning a
Deferred
, which we
assign to d
. We can think
of d
as a placeholder, representing the value
that open()
will eventually return when it
finally gets around to finishing.
To say do this next
, we add a callback to
d
. A callback is a function that will be called
with whatever open()
eventually returns. In this
case, we don't care, so we make a function with a single, ignored parameter
that just calls pod.launch()
.
So, we've replaced the order of lines is order of execution
with a
deliberate, in-Python encoding of the order of execution,
where d
represents the particular flow and
d.addCallback
replaces new line
.
Of course, programs generally consist of more than two lines, and we still don't know how to deal with failure.
Getting it right: The failure cases
In what follows, we are going to take each way of expressing order of
operations in normal Python (using lines of code and and
try
/except
) and
translate them into an equivalent code built with Deferred
objects.
This is going to be a bit painstaking, but if you want to really understand
how to use Deferred
s
and maintain code that uses them, it is worth understanding each example
below.
One thing, then another, then another
Recall our example from earlier:
1
pprint(sorted(x.get_names()))
Also written as:
1 2 3
names = x.get_names() sorted_names = sorted(names) pprint(sorted_names)
What if neither get_names
nor sorted
can be relied on to finish before they
return? That is, if both are asynchronous operations?
Well, in Twisted-speak they would return Deferred
s and so we would write:
1 2 3
d = x.get_names() d.addCallback(sorted) d.addCallback(pprint)
Eventually, sorted
will get called with
whatever get_names
finally delivers.
When sorted
finishes, pprint
will be called with whatever it
delivers.
We could also write this as:
1
x.get_names().addCallback(sorted).addCallback(pprint)
Since d.addCallback
returns d
.
Simple failure handling
We often want to write code equivalent to this:
1 2 3 4
try: x.get_names() except Exception, e: report_error(e)
How would we write this with Deferred
s?
1 2
d = x.get_names() d.addErrback(report_error)
errback is the Twisted name for a callback that is called when an error is received.
This glosses over an important detail. Instead of getting the exception
object e
, report_error
would get a Failure
object, which has all of the useful information
that e
does, but is optimized for use
with Deferred
s.
We'll dig into that a bit later, after we've dealt with all of the other combinations of exceptions.
Handle an error, but do something else on success
What if we want to do something after our try
block if it actually worked? Abandoning our
contrived examples and reaching for generic variable names, we get:
1 2 3 4 5 6
try: y = f() except Exception, e: g(e) else: h(y)
Well, we'd write it like this with Deferred
:
1 2
d = f() d.addCallbacks(h, g)
Where addCallbacks
means add a callback and an
errback at the same time
.
h
is the callback,
g
is the errback.
Now that we have addCallbacks
along
with addErrback
and addCallback
, we can match any possible
combination
of try
, except
, else
and finally
by varying the order in which we call
them. Explaining exactly how it works is tricky (although
the Deferred reference does rather a good job), but
once we're through all of the examples it ought to be clearer.
Handle an error, then proceed anyway
What if we want to do something after
our try
/except
block,
regardless of whether or not there was an exception? That is, what if we
wanted to do the equivalent of this generic code:
1 2 3 4 5
try: y = f() except Exception, e: y = g(e) h(y)
And with Deferred
:
1 2 3
d = f() d.addErrback(g) d.addCallback(h)
Because addErrback
returns d
, we can chain the calls like so:
1
f().addErrback(g).addCallback(h)
The order of addErrback
and addCallback
matters. In the next section, we
can see what would happen when we swap them around.
Handle an error for the entire operation
What if we want to wrap up a multi-step operation in one exception handler?
1 2 3 4 5
try: y = f() z = h(y) except Exception, e: g(e)
With Deferred
, it
would look like this:
1 2 3
d = f() d.addCallback(h) d.addErrback(g)
Or, more succinctly:
1
d = f().addCallback(h).addErrback(g)
Do something regardless
What about finally
? How do we do something
regardless of whether or not there was an exception? How do we translate
this:
1 2 3 4
try: y = f() finally: g()
Well, roughly we do this:
1 2
d = f() d.addBoth(g)
This adds g
as both the callback and the errback.
It is equivalent to:
1
d.addCallbacks(g, g)
Why roughly
? Because if f
raises, g
will be passed a Failure
object representing the
exception. Otherwise, g
will be passed the
asynchronous equivalent of the return value
of f()
(i.e. y
).
Conclusion
You have been introduced to asynchronous code and have seen how to
use Deferred
s to:
- Do something after an asynchronous operation completes successfully
- Use the result of a successful asynchronous operation
- Catch errors in asynchronous operations
- Do one thing if an operation succeeds, and a different thing if it fails
- Do something after an error has been handled successfully
- Wrap multiple asynchronous operations with one error handler
- Do something after an asynchronous operation, regardless of whether it succeeded or failed
These are very basic uses of
Deferred
. For
detailed information about how they work, how to combine multiple Deferreds,
and how to write code that mixes synchronous and asynchronous APIs, see
the Deferred reference. Alternatively, read
about how to write functions that generate
Deferreds.