Developer Guide

Some explanations for those who would like to contribute to Motor development.


Motor is single-source compatible with all supported Python versions, although there are some tricks for Python 3. There is some code for the async and await features of Python 3.5+ that is conditionally compiled with eval in

In there are tricks to conditionally import tests depending on Python version. also avoids installing the frameworks/asyncio directory in a Python 2 environment.

Motor supports a range of Tornado versions, and all the Python versions those Tornado versions work with. Motor still supports Tornado 3 because New Relic has only begun to support Tornado 4, and therefore Motor continues to support Python 2.6.


Motor abstracts the differences between Tornado and asyncio by wrapping each in a “framework” interface. A Motor framework is a module implementing these properties and functions:

  • add_future
  • call_soon
  • check_event_loop
  • coroutine
  • future_or_callback
  • get_event_loop
  • get_future
  • is_event_loop
  • is_future
  • pymongo_class_wrapper
  • run_on_executor
  • yieldable

See the frameworks/tornado and frameworks/asyncio modules.

A framework-specific class, like MotorClient for Tornado or AsyncIOMotorClient for asyncio, is created by the create_class_with_framework function, which combines a framework with a framework-agnostic class, in this case AgnosticClient.

Wrapping PyMongo

For each PyMongo class, Motor declares an equivalent framework-agnostic class. For example, the AgnosticClient class is a framework-agnostic equivalent to PyMongo’s MongoClient. This agnostic class declares each method and property of the PyMongo class that it intends to wrap. These methods and properties begin life as type MotorAttributeFactory.

When create_class_with_framework creates a framework-specific class from an agnostic class, it creates methods and properties for that class which wrap the equivalent PyMongo methods and properties.

For example, the AgnosticClient class declares that drop_database is an AsyncCommand, which is a subclass of MotorAttributeFactory. At import time, create_class_with_framework calls the create_attribute method of each MotorAttributeFactory on the AgnosticClient, which results in framework-specific implementations of each method and property. So at import time, create_class_with_framework generates framework-specific wrappers of drop_database for MotorClient and AsyncIOMotorClient. These wrappers use framework-specific features to run the drop_database method asynchronously.


This is the heart of Motor’s implementation. The create_attribute method for asynchronous methods like drop_database wraps the equivalent PyMongo method in a Motor method. This wrapper method uses either the Tornado or asyncio framework to:

  • get a reference to the framework’s event loop
  • start the PyMongo method on a thread in the global ThreadPoolExecutor
  • create a Future that will be resolved by the event loop when the thread finishes
  • returns the Future to the caller

This is what allows Tornado or asyncio coroutines to call Motor methods with yield, yield from, or await to await I/O without blocking the event loop.


A common kind of bug in Motor arises when PyMongo adds a feature, like a new method or new optional behavior, which we forget to wrap with Motor.

Since PyMongo adds a test to its suite for each new feature, we could catch these omissions by applying PyMongo’s latest tests to Motor. Then a missing method or feature would cause an obvious test failure. But PyMongo is synchronous and Motor is async; how can Motor pass PyMongo’s tests?

Synchro is a hacky little module that re-synchronizes all Motor methods using the Tornado IOLoop’s run_sync method. overrides the Python interpreter’s import machinery to allow Synchro to masquerade as PyMongo, and runs PyMongo’s test suite against it. Use tox -e synchro to check out PyMongo test suite and run it with Synchro.