This document describes the current stable version of Celery (3.1). For development docs, go here.

Contributors Guide to the Code

Philosophy

The API>RCP Precedence Rule

• The API is more important than Readability

• Readability is more important than Convention

• Convention is more important than Performance

  • …unless the code is a proven hotspot.

More important than anything else is the end-user API. Conventions must step aside, and any suffering is always alleviated if the end result is a better API.

Conventions and Idioms Used

Classes

Naming

• Follows PEP 8.

• Class names must be CamelCase.

• but not if they are verbs, verbs shall be lower_case:

  # - test case for a class
  class TestMyClass(Case):                # BAD
      pass
  
  class test_MyClass(Case):               # GOOD
      pass
  
  # - test case for a function
  class TestMyFunction(Case):             # BAD
      pass
  
  class test_my_function(Case):           # GOOD
      pass
  
  # - "action" class (verb)
  class UpdateTwitterStatus(object):    # BAD
      pass
  
  class update_twitter_status(object):    # GOOD
      pass
  

  Note

  Sometimes it makes sense to have a class mask as a function, and there is precedence for this in the stdlib (e.g. contextmanager). Celery examples include subtask, chord, inspect, promise and more..

• Factory functions and methods must be CamelCase (excluding verbs):

  class Celery(object):
  
      def consumer_factory(self):     # BAD
          ...
  
      def Consumer(self):             # GOOD
          ...
  

Default values

Class attributes serve as default values for the instance, as this means that they can be set by either instantiation or inheritance.

Example:

class Producer(object):
    active = True
    serializer = 'json'

    def __init__(self, serializer=None):
        self.serializer = serializer or self.serializer

        # must check for None when value can be false-y
        self.active = active if active is not None else self.active

A subclass can change the default value:

TaskProducer(Producer):
    serializer = 'pickle'

and the value can be set at instantiation:

>>> producer = TaskProducer(serializer='msgpack')

Exceptions

Custom exceptions raised by an objects methods and properties should be available as an attribute and documented in the method/property that throw.

This way a user doesn’t have to find out where to import the exception from, but rather use help(obj) and access the exception class from the instance directly.

Example:

class Empty(Exception):
    pass

class Queue(object):
    Empty = Empty

    def get(self):
        """Get the next item from the queue.

        :raises Queue.Empty: if there are no more items left.

        """
        try:
            return self.queue.popleft()
        except IndexError:
            raise self.Empty()

Composites

Similarly to exceptions, composite classes should be override-able by inheritance and/or instantiation. Common sense can be used when selecting what classes to include, but often it’s better to add one too many: predicting what users need to override is hard (this has saved us from many a monkey patch).

Example:

class Worker(object):
    Consumer = Consumer

    def __init__(self, connection, consumer_cls=None):
        self.Consumer = consumer_cls or self.Consumer

    def do_work(self):
        with self.Consumer(self.connection) as consumer:
            self.connection.drain_events()

Applications vs. “single mode”

In the beginning Celery was developed for Django, simply because this enabled us get the project started quickly, while also having a large potential user base.

In Django there is a global settings object, so multiple Django projects can’t co-exist in the same process space, this later posed a problem for using Celery with frameworks that doesn’t have this limitation.

Therefore the app concept was introduced. When using apps you use ‘celery’ objects instead of importing things from celery submodules, this (unfortunately) also means that Celery essentially has two API’s.

Here’s an example using Celery in single-mode:

from celery import task
from celery.task.control import inspect

from .models import CeleryStats

@task
def write_stats_to_db():
    stats = inspect().stats(timeout=1)
    for node_name, reply in stats:
        CeleryStats.objects.update_stat(node_name, stats)

and here’s the same using Celery app objects:

from .celery import celery
from .models import CeleryStats

@app.task
def write_stats_to_db():
    stats = celery.control.inspect().stats(timeout=1)
    for node_name, reply in stats:
        CeleryStats.objects.update_stat(node_name, stats)

In the example above the actual application instance is imported from a module in the project, this module could look something like this:

from celery import Celery

app = Celery(broker='amqp://')

Module Overview

• celery.app

  This is the core of Celery: the entry-point for all functionality.

• celery.loaders

  Every app must have a loader. The loader decides how configuration is read, what happens when the worker starts, when a task starts and ends, and so on.

  The loaders included are:

  • app

    Custom celery app instances uses this loader by default.

  • default

    “single-mode” uses this loader by default.

  Extension loaders also exist, like django-celery, celery-pylons and so on.

• celery.worker

  This is the worker implementation.

• celery.backends

  Task result backends live here.

• celery.apps

  Major user applications: worker and beat. The command-line wrappers for these are in celery.bin (see below)

• celery.bin

  Command-line applications. setup.py creates setuptools entrypoints for these.

• celery.concurrency

  Execution pool implementations (prefork, eventlet, gevent, threads).

• celery.db

  Database models for the SQLAlchemy database result backend. (should be moved into celery.backends.database)

• celery.events

  Sending and consuming monitoring events, also includes curses monitor, event dumper and utilities to work with in-memory cluster state.

• celery.execute.trace

  How tasks are executed and traced by the worker, and in eager mode.

• celery.security

  Security related functionality, currently a serializer using cryptographic digests.

• celery.task

  single-mode interface to creating tasks, and controlling workers.

• celery.tests

  The unittest suite.

• celery.utils

  Utility functions used by the celery code base. Much of it is there to be compatible across Python versions.

• celery.contrib

  Additional public code that doesn’t fit into any other namespace.