Introduction to Deferreds¶
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
sTranslate 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.
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:
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:
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:
from __future__ import print_function
total = 0
for account in accounts:
total += account.get_balance()
print("Total balance ${}".format(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”?
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
, except
, 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:
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:
pod_bay_doors.open()
pod.launch()
We write:
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 “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 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:
pprint(sorted(x.get_names()))
Also written as:
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:
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:
x.get_names().addCallback(sorted).addCallback(pprint)
Since d.addCallback
returns d
.
Simple failure handling¶
We often want to write code equivalent to this:
try:
x.get_names()
except Exception as e:
report_error(e)
How would we write this with Deferred
s?
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:
try:
y = f()
except Exception as e:
g(e)
else:
h(y)
Well, we’d write it like this with Deferred
s:
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:
try:
y = f()
except Exception as e:
y = g(e)
h(y)
And with Deferred
s:
d = f()
d.addErrback(g)
d.addCallback(h)
Because addErrback
returns d
, we can chain the calls like so:
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?
try:
y = f()
z = h(y)
except Exception as e:
g(e)
With Deferred
s, it would look like this:
d = f()
d.addCallback(h)
d.addErrback(g)
Or, more succinctly:
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:
try:
y = f()
finally:
g()
Well, roughly we do this:
d = f()
d.addBoth(g)
This adds g
as both the callback and the errback.
It is equivalent to:
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
).
Coroutines with async/await¶
Python 3.5 introduced PEP 492 (“Coroutines with async and await syntax”) and native coroutines.
Deferred.fromCoroutine
allows you to write coroutines with the async def
syntax and await
on Deferreds, similar to inlineCallbacks
.
Rather than decorating every function that may await
a Deferred (as you would with functions that yield
Deferreds with inlineCallbacks
), you only need to call fromCoroutine
with the outer-most coroutine object to schedule it for execution.
Coroutines can await
other coroutines once running without needing to use this function themselves.
Note
New in version Twisted: NEXT
Coroutines can be passed to yield
in code based on inlineCallbacks
.
Note
The ensureDeferred
function also provides a way to convert a coroutine to a Deferred, but it’s interface is more type-ambiguous; Deferred.fromCoroutine
is meant to replace it.
Awaiting on a Deferred which fires with a Failure will raise the exception inside your coroutine as if it were regular Python.
If your coroutine raises an exception, it will be translated into a Failure fired on the Deferred that Deferred.fromCoroutine
returns for you.
Calling return
will cause the Deferred that Deferred.fromCoroutine
returned for you to fire with a result.
import json
from twisted.internet.defer import Deferred
from twisted.logger import Logger
log = Logger()
async def getUsers():
try:
return json.loads(await makeRequest("GET", "/users"))
except ConnectionError:
log.failure("makeRequest failed due to connection error")
return []
def do():
d = Deferred.fromCoroutine(getUsers())
d.addCallback(print)
return d
When writing coroutines, you do not need to use Deferred.fromCoroutine
when you are writing a coroutine which calls other coroutines which await on Deferreds; you can just await
on it directly.
For example:
async def foo():
res = await someFunctionThatReturnsADeferred()
return res
async def bar():
baz = await someOtherDeferredFunction()
fooResult = await foo()
return baz + fooResult
def myDeferredReturningFunction():
coro = bar()
return Deferred.fromCoroutine(coro)
Even though Deferreds were used in both coroutines, only bar
had to be wrapped in Deferred.fromCoroutine
to return a Deferred.
Inline callbacks - using ‘yield’¶
Note
Unless your code supports Python 2 (and therefore needs compatibility with older versions of Twisted), writing coroutines with the functionality described in “Coroutines with async/await” is preferred over inlineCallbacks
.
Coroutines are supported by dedicated Python syntax, are compatible with asyncio
, and provide higher performance.
New in version Twisted: NEXT
Existing inlineCallbacks
-based code can be converted to coroutines function-by-function.
Simply replace inlineCallbacks
by async def
and yield
with await
.
Existing inlineCallbacks
functions can yield
coroutines, therefore the only place requiring attention is where the returned value is used as Deferred
by calling its member functions such as addCallback
.
Use Deferred.fromCoroutine
in such places for compatibility.
Twisted features a decorator named inlineCallbacks
which allows you to work with Deferreds without writing callback functions.
This is done by writing your code as generators, which yield Deferred
s instead of attaching callbacks.
Consider the following function written in the traditional Deferred
style:
def getUsers():
d = makeRequest("GET", "/users")
d.addCallback(json.loads)
return d
using inlineCallbacks
, we can write this as:
from twisted.internet.defer import inlineCallbacks, returnValue
@inlineCallbacks
def getUsers(self):
responseBody = yield makeRequest("GET", "/users")
returnValue(json.loads(responseBody))
a couple of things are happening here:
instead of calling
addCallback
on theDeferred
returned bymakeRequest
, we yield it. This causes Twisted to return theDeferred
‘s result to us.the final result of the function is propagated using
return
as usual.
Both versions of getUsers
present exactly the same API to their callers: both return a Deferred
that fires with the parsed JSON body of the request.
Though the inlineCallbacks
version looks like synchronous code, which blocks while waiting for the request to finish, each yield
statement allows other code to run while waiting for the Deferred
being yielded to fire.
inlineCallbacks
become even more powerful when dealing with complex control flow and error handling.
For example, what if makeRequest
fails due to a connection error?
For the sake of this example, let’s say we want to log the exception and return an empty list.
def getUsers():
d = makeRequest("GET", "/users")
def connectionError(failure):
failure.trap(ConnectionError)
log.failure("makeRequest failed due to connection error",
failure)
return []
d.addCallbacks(json.loads, connectionError)
return d
With inlineCallbacks
, we can rewrite this as:
@inlineCallbacks
def getUsers(self):
try:
responseBody = yield makeRequest("GET", "/users")
except ConnectionError:
log.failure("makeRequest failed due to connection error")
returnValue([])
returnValue(json.loads(responseBody))
Our exception handling is simplified because we can use Python’s familiar try
/ except
syntax for handling ConnectionError
s.
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
Write code without callbacks using
inlineCallbacks
Write coroutines that interact with Deferreds using
Deferred.fromCoroutine
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.