An efficient implementation of a rate limiter for asyncio.

This project implements the Leaky bucket algorithm, giving you precise control over the rate a code section can be entered.

It was first developed as an answer on Stack Overflow.


$ pip install aiolimiter

The library requires Python 3.6 or newer.


  • Python >= 3.6


Typical use

Create an instance of the aiolimiter.AsyncLimiter class, specifying the maximum capacity that can be acquired in one minute:

from aiolimiter import AsyncLimiter

limiter = AsyncLimiter(100)

then use this object as an asynchronous context manager, so with async with, to enclose a section you want to control the rate of execution of:

with limiter:
    # this section will, at most, be entered 100 times / minute

You can also call the AsyncLimiter.acquire() async method directly:

await limit.acquire()  # blocks until there is capacity

or you can simply test if there is space first by calling AsyncLimiter.has_capacity():

if limit.has_capacity():
    # reject a request due to rate limiting

Varying capacity requests

Note that you can count some requests as ‘heavier’ or ‘lighter’ by increasing or decreasing the amount of capacity you work with:

await limit.acquire(10)
if limit.has_capacity(0.5):

Do be careful with this though; when mixing capacity amounts, small capacity requests tend to get run before large blocks of capacity when at or close to the maximum rate, because there is a greater likelihood that there is enough free capacity for a smaller request before there is space for a larger one.


The rate limit only kicks in once capacity has been reached:

>>> import asyncio, time
>>> from aiolimiter import AsyncLimiter
>>> limiter = AsyncLimiter(4, 8)
>>> async def task(id):
...     await asyncio.sleep(id * 0.01)
...     async with limiter:
...         print(f'{id:>2d}: Drip! {time.time() - ref:>5.2f}')
>>> tasks = [task(i) for i in range(10)]
>>> tasks = [task(i) for i in range(10)]
>>> ref = time.time(); result =
 0: Drip!  0.00
 1: Drip!  0.01
 2: Drip!  0.02
 3: Drip!  0.03
 4: Drip!  2.05
 5: Drip!  4.05
 6: Drip!  6.05
 7: Drip!  8.06
 8: Drip! 10.06
 9: Drip! 12.07

For the first 4 tasks, plenty of capacity was available so they were allowed the limited section in quick succession. Once capacity has been reached, however tasks have to wait until enough time has passed to free up capacity.

The maximum burst size is equal to the AsyncLimiter.max_rate value, if you don’t want to permit bursts, set the maximum rate to 1 and set time_period to the minimum time between acquisitions:

>>> limiter = AsyncLimiter(1, 1.5)  # no bursts, allow entry every 1.5 seconds
>>> tasks = [task(i) for i in range(5)]
>>> ref = time.time(); result =
 0: Drip!  0.00
 1: Drip!  1.52
 2: Drip!  3.03
 3: Drip!  4.54
 4: Drip!  6.05


class aiolimiter.AsyncLimiter(max_rate, time_period=60)

A leaky bucket rate limiter.

This is an asynchronous context manager; when used with async with, entering the context acquires capacity:

limiter = AsyncLimiter(10)
for foo in bar:
    async with limiter:
        # process foo elements at 10 items per minute
  • max_rate (float) – Allow up to max_rate / time_period acquisitions before blocking.

  • time_period (float) – duration, in seconds, of the time period in which to limit the rate. Note that up to max_rate acquisitions are allowed within this time period in a burst.

async acquire(amount=1)

Acquire capacity in the limiter.

If the limit has been reached, blocks until enough capacity has been freed before returning.


amount (float) – How much capacity you need to be available.


Raises ValueError if amount is greater than max_rate.

Return type



Check if there is enough capacity remaining in the limiter


amount (float) – How much capacity you need to be available.

Return type


max_rate = None

The configured max_rate value for this limiter.

time_period = None

The configured time_period value for this limiter.


aiolimiter is offered under the MIT license.

Source code

The project is hosted on GitHub

Please file an issue in the bug tracker if you have found a bug or have some suggestions to improve the library.

Indices and tables