api-throttler 0.2.2

A python toolkit to enforce API rate limit on the backend

API Throttler

A Python toolkit to enforce API rate limit on the backend. The toolkit enable the service backend to limit the number of API calls in a specified period, e.g., 15 API calls per 900 seconds. There are four throttler classes in the toolkit:

• FixedWindowThrottler
• SlidingWindowThrottler
• FixedWindowThrottlerRedis
• SlidingWindowThrottlerRedis

The first two throttler classes use local storage to save throttler data (e.g., API calls that have been served and their timestamps), while the last two throttler classes use a Redis server to store throttler information. The difference between the fixed window and sliding window throttlers is the fixed window throttler uses the timestamp when the first feasible request is served as the starting timestamp to determine the number of allowed API calls in the following period, while the sliding window throttler uses the current timestamp minus the specified period as the starting timestamp to calculate the number of allowed API calls. The advantage of fixed window throttler is its simplicity, but there could be many API calls allowed if they are at the end of last period and the beginning of the current period. On the other hand, the sliding window throttler could resolve this issue, but it takes more memory.

Usage

To use this API throttler toolkit, first install it using pip:

pip install api-throttler

Then, import the package in your python script and call appropriate functions:

import time

from api_throttler import Throttler, FixedWindowThrottler, SlidingWindowThrottler


# Limit 3 calls per 10 seconds
fixed_window_throttler = FixedWindowThrottler(calls=3, period=10)
sliding_window_throttler = SlidingWindowThrottler(calls=3, period=10)


def call_api(throttler: Throttler, key: str = 'some_string_key'):
    if not throttler.is_throttled(key):
        print('API call is NOT throttled')
    else:
        print('API call is throttled')


print('Using fixed window API throttler')
for i in range(20):
    print(f'This is the {i}-th second')
    # Call API in the following i-th seconds
    if i in {0, 8, 9, 10, 11, 12}:
        call_api(fixed_window_throttler)
    time.sleep(1)

print('-'*40)

print('Using sliding window API throttler')
for i in range(20):
    print(f'This is the {i}-th second')
    if i in {0, 8, 9, 10, 11, 12}:
        call_api(sliding_window_throttler)
    time.sleep(1)

In the above example, the data of the throttler is saved in local hash table (dict). If you would like to save it into a redis server, you can use the FixedWindowThrottlerRedis and SlidingWindowThrottlerRedis classes. Please try the Flask app example in app.py using Docker by running make run in your terminal if you use Linux or Mac OS. If you use Windows, please run the following command in your command line:

docker-compose -f docker-compose/docker-compose.yml -f docker-compose/docker-compose.local.yml up --build