aiothrottler 
Throttler for asyncio Python
Installation
pip install aiothrottlerUsage
Create a shared Throttler, passing a minimum interval, e.g. 0.5 seconds
from aiothrottler import Throttler
throttler = Throttler(min_interval=0.5)and then just before the piece(s) of code to be throttled, call this and await its result.
await throttler()
# There will be a gap of at least 0.5 seconds
# between executions reaching this lineExample: multiple tasks throttled
import asyncio
import time
from aiothrottler import Throttler
async def main():
throttler = Throttler(min_interval=0.5)
await asyncio.gather(*[
worker(throttler) for _ in range(10)
])
async def worker(throttler):
await throttler()
# Interval of at least 0.5 seconds between prints
# even though all workers started together
print(time.time())
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
loop.close()Example: single task throttled/smoothed
import asyncio
import random
import time
from aiothrottler import Throttler
async def main():
throttler = Throttler(min_interval=0.5)
for _ in range(10):
await throttler()
# Interval of at least 0.5 seconds between prints
# even though each sleep is random
print(time.time())
await asyncio.sleep(random.random())
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
loop.close()Differences to alternatives
-
The API features a function to call to
awaitits result [some use a context manager] -
The API is imperative [some use a functional approach/higher-order function]
-
No polling is used [some use polling internally]
-
A minimum interval between resolutions is used to throttle [rather that a max resolutions per time interval, which can cause an irregular pattern of resolutions]
-
The tests cover edge cases, such as asserting on throttling after tasks being throttled have been cancelled [some alternatives do not]
