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future based ndb sharded functions, for traversing ndb objects at any scale, for Google App Engine, Python standard environment

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# appenginetaskutils
This is the repo for the appengine task utils library. It generates the appenginetaskutils package

## Install

Use the python package for this library. You can find the package online [here](https://pypi.python.org/pypi/appenginetaskutils).

Change to your Python App Engine project's root folder and do the following:

> pip install appenginetaskutils --target lib

Or add it to your requirements.txt. You'll also need to set up vendoring, see [app engine vendoring instructions here](https://cloud.google.com/appengine/docs/python/tools/using-libraries-python-27).

## @task

The most basic element of the taskutils library is task(). This decorator function is designed to be used as a replacement for [deferred](https://cloud.google.com/appengine/articles/deferred).

### Configuring @task

When using deferred you have a builtin to configure in app.yaml to make it work. For taskutils.task, you need to add the following to your app.yaml and/or \<servicename\>.yaml file:

handlers:
- url: /_ah/task/.*
script: taskutils.app
login: admin

This rule creates a generic handler for task to defer work to background push tasks.

Add it at the top of the list (to make sure other rules don't override it).

### Importing task

You can import task into your modules like this:

from taskutils import task

### Using task as a decorator

You can take any function and make it run in a separate task, like this:

@task
def myfunction():
... do stuff ...

Just call the function normally, eg:

myfunction()

You can use @task on any function, including nested functions, recursive functions, recursive nested functions, the sky is the limit. This is possible because of use of [yccloudpickle](https://medium.com/the-infinite-machine/python-function-serialisation-with-yccloudpickle-b2ff6b2ad5da#.zei3n0ibu) as the underlying serialisation library.

Your function can also have arguments, including other functions:

def myouterfunction(mapf):

@task
def myinnerfunction(objects):
for object in objects:
mapf(object)

...get some list of lists of objects...
for objects in objectslist:
myinnerfunction(objects)

def dosomethingwithobject(object):
... do something with an object ...

myouterfunction(dosomethingwithobject)

The functions and arguments are being serialised and deserialised for you behind the scenes.

When enqueuing a background task, the App Engine Task and TaskQueue libraries can take a set of parameters. You can pass these to the decorator:

@task(queue="myqueue", countdown=5)
def anotherfunction():
... do stuff ...

Details of the arguments allowed to Tasks are available [here](https://cloud.google.com/appengine/docs/python/refdocs/google.appengine.api.taskqueue), under **class google.appengine.api.taskqueue.Task(payload=None, \*\*kwargs)**. The task decorator supports a couple of extra ones, detailed below.

### Using task as a factory

You can also use task to decorate a function on the fly, like this:

def somefunction(a, b):
... does something ...

somefunctionintask = task(somefunction, queue="myqueue")

Then you can call the function returned by task when you are ready:

somefunctionintask(1, 2)

You could do both of these steps at once, too:


task(somefunction, queue="myqueue")(1, 2)

### transactional

Pass transactional=True to have your [task launch transactionally](https://cloud.google.com/appengine/docs/python/datastore/transactions#transactional_task_enqueuing). eg:

@task(transactional=True)
def myserioustransactionaltask():
...

### includeheaders

If you'd like access to headers in your function (a dictionary of headers passed to your task, it's a web request after all), set includeheaders=True in your call to @task. You'll also need to accept the headers argument in your function.

@task(includeheaders=True)
def myfunctionwithheaders(amount, headers):
... stuff ...

myfunctionwithheaders(10)

App Engine passes useful information to your task in headers, for example X-Appengine-TaskRetryCount.

### other bits

When using deferred, all your calls are logged as /_ah/queue/deferred. But @task uses a url of the form /_ah/task/\<module\>/\<function\>, eg:

/_ah/task/mymodule/somefunction

which makes debugging a lot easier.







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