The throttle library provides a robust and versatile throttling mechanism for Python.
It can be used in multiple environments, from a single thread to a distributed server cluster.
It supports Python versions 2.6 to 3.3.
In order to perform throttling tasks, simply use the :meth:~throttle.throttle
function:
.. code-block:: python
import throttle
def some_fun(uid):
if not throttle.check(key=uid, rate=30, size=10):
raise ThrottleError()
# Do the job
# Or with a custom Redis client,
throttle(key=key, rate=1, capacity=5, storage=BaseStorage(client=Redis(host='localhost', port=6379, db=220, password=None)), amount=3)
throttle uses the "token bucket" algorithm: for each key, a virtual bucket exists.
Whenever a new request gets in, the algorithm performs the following actions:
- Test if adding the request's cost to the bucket would exceed its capacity; in that case, return False
- Otherwise, add the request's cost to the bucket, and return True
Simultaneously, the bucket's current value is decremented at the chosen rate.
This allows for temporary bursts and average computations.
From pip (https://pypi.python.org/pypi/lotus_eaters):
.. code-block:: sh
$ pip install lotus_eaters
From Github:
.. code-block:: sh
$ git clone git://github.com/mpetyx/lotus_eaters.git