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  • Language
    Python
  • License
    MIT License
  • Created about 9 years ago
  • Updated over 2 years ago

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Repository Details

API Rate Limit Decorator

ratelimit build Maintainability

APIs are a very common way to interact with web services. As the need to consume data grows, so does the number of API calls necessary to remain up to date with data sources. However many API providers constrain developers from making too many API calls. This is know as rate limiting and in a worst case scenario your application can be banned from making further API calls if it abuses these limits.

This packages introduces a function decorator preventing a function from being called more often than that allowed by the API provider. This should prevent API providers from banning your applications by conforming to their rate limits.

Installation

PyPi

Add this line to your application's requirements.txt:

ratelimit

And then execute:

$ pip install -r requirements.txt

Or install it yourself:

$ pip install ratelimit

GitHub

Installing the latest version from Github:

$ git clone https://github.com/tomasbasham/ratelimit
$ cd ratelimit
$ python setup.py install

Usage

To use this package simply decorate any function that makes an API call:

from ratelimit import limits

import requests

FIFTEEN_MINUTES = 900

@limits(calls=15, period=FIFTEEN_MINUTES)
def call_api(url):
    response = requests.get(url)

    if response.status_code != 200:
        raise Exception('API response: {}'.format(response.status_code))
    return response

This function will not be able to make more then 15 API call within a 15 minute time period.

The arguments passed into the decorator describe the number of function invocation allowed over a specified time period (in seconds). If no time period is specified then it defaults to 15 minutes (the time window imposed by Twitter).

If a decorated function is called more times than that allowed within the specified time period then a ratelimit.RateLimitException is raised. This may be used to implement a retry strategy such as an expoential backoff

from ratelimit import limits, RateLimitException
from backoff import on_exception, expo

import requests

FIFTEEN_MINUTES = 900

@on_exception(expo, RateLimitException, max_tries=8)
@limits(calls=15, period=FIFTEEN_MINUTES)
def call_api(url):
    response = requests.get(url)

    if response.status_code != 200:
        raise Exception('API response: {}'.format(response.status_code))
    return response

Alternatively to cause the current thread to sleep until the specified time period has ellapsed and then retry the function use the sleep_and_retry decorator. This ensures that every function invocation is successful at the cost of halting the thread.

from ratelimit import limits, sleep_and_retry

import requests

FIFTEEN_MINUTES = 900

@sleep_and_retry
@limits(calls=15, period=FIFTEEN_MINUTES)
def call_api(url):
    response = requests.get(url)

    if response.status_code != 200:
        raise Exception('API response: {}'.format(response.status_code))
    return response

License

This project is licensed under the MIT License.