Greenado is a utility library that provides greenlet-based coroutines for tornado. In tornado, coroutines allow you to perform asynchronous operations without using callbacks, providing a pseudo-synchronous flow in your functions.
When using Tornado’s
@gen.coroutine in a
large codebase, you will notice that they tend to be ‘infectious’ from
the bottom up. In other words, for them to be truly useful, callers of
the coroutine should ‘yield’ to them, which requires them to be a
coroutine. In turn, their callers need to ‘yield’, and so on.
Instead, greenado coroutines infect from the top down, and only requires
somewhere in the call hierarchy, but it doesn’t really matter where.
Once the decorator is used, you can use
to pseudo-synchronously wait for asynchronous events to occur. This reduces
complexity in large codebases, as you only need to use the decorator at
the very top of your call trees, and nowhere else.
Installation & Requirements¶
Installation is easiest using pip:
$ pip install greenado
greenado should work using tornado 3.2, but I only actively use it in tornado 4+
I have only tested greenado on Linux & OSX, but I imagine that it would work correctly on platforms that tornado and greenlet support.
In the below examples, ‘main_function’ is your toplevel function in the call hierarchy that needs to call things that eventually call some asynchronous operation in tornado.
Normal tornado coroutine usage might look something like this:
from tornado import gen @gen.coroutine def do_long_operation(): retval = yield long_operation() raise gen.Return(retval) @gen.coroutine def call_long_operation(): retval = yield do_long_operation() raise gen.Return(retval) @gen.coroutine def main_function(): retval = yield call_long_operation()
With greenado, it looks something like this instead:
import greenado def do_long_operation(): retval = greenado.gyield(long_operation()) return retval def call_long_operation(): retval = do_long_operation() return retval @greenado.groutine def main_function(): retval = call_long_operation()
Functions wrapped by
@greenado.groutine return a
tornado.concurrent.Future object which you must either yield, call
result(), or use
IOLoop.add_future on, otherwise you may risk
Why can’t I use the yield keyword?¶
Well, actually, if you use yet another decorator, you still can! Check out this example:
import greenado @greenado.generator def do_long_operation(): retval = yield long_operation() return retval def call_long_operation(): retval = do_long_operation() return retval @greenado.groutine def main_function(): retval = call_long_operation()
You’ll note that this is very similar to the coroutines available from
tornado (and in fact, the implementation is mostly the same), but the
difference is that (once again) you don’t need to do anything special
to call the do_long_operation function, other than make sure that
@greenado.groutine is in the call stack somewhere.
greenado.testing contains a function called gen_test which can be used
import greenado from greenado.testing import gen_test from tornado.testing import AsyncTestCase def something_that_yields(): greenado.gyield(something()) class MyTest(AsyncTestCase): @gen_test def test_something(self): something_that_yields()
Contributing new changes¶
- Fork this repository
- Create your feature branch (git checkout -b my-new-feature)
- Test your changes (tests/run_tests.sh)
- Commit your changes (git commit -am ‘Add some feature’)
- Push to the branch (git push origin my-new-feature)
- Create new Pull Request