I would like to rewrite some of my tasks as pipelines. Mainly because of the fact that I need a way of detecting when a task finished or start a tasks in specific order. My problem is that I'm not sure how to rewrite the recursive tasks to pipelines. By recursive I mean tasks that call themselves like this:
class MyTask(webapp.RequestHandler):
def post(self):
cursor = self.request.get('cursor', None)
[set cursor if not null]
[fetch 100 entities form datastore]
if len(result) >= 100:
[ create the same task in the queue and pass the cursor ]
[do actual work the task was created for]
Now I would really like to write it as a pipeline and do something similar to:
class DoSomeJob(pipeline.Pipeline):
def run(self):
with pipeline.InOrder():
yield MyTask()
yield MyOtherTask()
yield DoSomeMoreWork(message2)
Any help with this one will be greatly appreciated. Thank you!
A basic pipeline just returns a value:
class MyFirstPipeline(pipeline.Pipeline):
def run(self):
return "Hello World"
The value has to be JSON serializable.
If you need to coordinate several pipelines you will need to use a generator pipeline and the yield
statement.
class MyGeneratorPipeline(pipeline.Pipeline):
def run(self):
yield MyFirstPipeline()
You can treat the yielding of a pipeline as if it returns a 'future'.
You can pass this future as the input arg to another pipeline:
class MyGeneratorPipeline(pipeline.Pipeline):
def run(self):
result = yield MyFirstPipeline()
yield MyOtherPipeline(result)
The Pipeline API will ensure that the run
method of MyOtherPipeline
is only called once the result
future from MyFirstPipeline
has been resolved to a real value.
You can't mix yield
and return
in the same method. If you are using yield
the value has to be a Pipeline instance. This can lead to a problem if you want to do this:
class MyRootPipeline(pipeline.Pipeline):
def run(self, *input_args):
results = []
for input_arg in input_args:
intermediate = yield MyFirstPipeline(input_arg)
result = yield MyOtherPipeline(intermediate)
results.append(result)
yield results
In this case the Pipeline API just sees a list in your final yield results
line, so it doesn't know to resolve the futures inside it before returning and you will get an error.
They're not documented but there is a library of utility pipelines included which can help here:
https://code.google.com/p/appengine-pipeline/source/browse/trunk/src/pipeline/common.py
So a version of the above which actually works would look like:
import pipeline
from pipeline import common
class MyRootPipeline(pipeline.Pipeline):
def run(self, *input_args):
results = []
for input_arg in input_args:
intermediate = yield MyFirstPipeline(input_arg)
result = yield MyOtherPipeline(intermediate)
results.append(result)
yield common.List(*results)
Now we're ok, we're yielding a pipeline instance and Pipeline API knows to resolve its future value properly. The source of the common.List
pipeline is very simple:
class List(pipeline.Pipeline):
"""Returns a list with the supplied positional arguments."""
def run(self, *args):
return list(args)
...at the point that this pipeline's run
method is called the Pipeline API has resolved all of the items in the list to actual values, which can be passed in as *args
.
Anyway, back to your original example, you could do something like this:
class FetchEntitites(pipeline.Pipeline):
def run(self, cursor=None)
if cursor is not None:
cursor = Cursor(urlsafe=cursor)
# I think it's ok to pass None as the cursor here, haven't confirmed
results, next_curs, more = MyModel.query().fetch_page(100,
start_cursor=cursor)
# queue up a task for the next page of results immediately
future_results = []
if more:
future_results = yield FetchEntitites(next_curs.urlsafe())
current_results = [ do some work on `results` ]
# (assumes current_results and future_results are both lists)
# this will have to wait for all of the recursive calls in
# future_results to resolve before it can resolve itself:
yield common.Extend(current_results, future_results)
At the start I said we can treat result = yield MyPipeline()
as if it returns a 'future'. This is not strictly true, obviously we are actually just yielding the instantiated pipeline. (Needless to say our run
method is now a generator function.)
The weird part of how Python's yield expressions work is that, despite what it looks like, the value that you yield
goes somewhere outside the function (to the Pipeline API apparatus) rather than into your result
var. The value of the result
var on the left side of the expression is also pushed in from outside the function, by calling send
on the generator (the generator being the run
method you defined).
So by yielding an instantiated Pipeline, you are letting the Pipeline API take that instance and call its run
method somewhere else at some other time (in fact it will be passed into a task queue as a class name and a set of args and kwargs and re-instantiated there... this is why your args and kwargs need to be JSON serializable too).
Meanwhile the Pipeline API send
s a PipelineFuture
object into your run
generator and this is what appears in your result
var. It seems a bit magical and counter-intuitive but this is how generators with yield expressions work.
It's taken quite a bit of head-scratching for me to work it out to this level and I welcome any clarifications or corrections on anything I got wrong.
When you create a pipeline, it hands back an object that represents a "stage". You can ask the stage for its id, then save it away. Later, you can reconstitute the stage from the saved id, then ask the stage if it's done.
See http://code.google.com/p/appengine-pipeline/wiki/GettingStarted and look for has_finalized
. There's an example that does most of what you need.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With