A proactive rate-limiting tool utilizing Redis.

Users can actively limit the call frequency of functions or methods, and calls that would cause exceeding the limit will be delayed until they can be executed.

$ pip install client_throttler

1. [Optional] Configure a default config for all Throttler rate limiters.

   from redis.client import Redis
   from client_throttler import setup, ThrottlerConfig
   
   setup(ThrottlerConfig(redis_client=Redis(host="localhost", port=1234, db=1), rate="100/s"))

2. Simply add a decorator to the function or method that needs to have its calls limited.

   from redis.client import Redis
   from client_throttler import throttler, ThrottlerConfig, Throttler
   
   redis_client = Redis(host="localhost", port=1234, db=2)
   
   # use default config
   @throttler()
   def func_a(*args, **kwargs):
       return args, kwargs
   
   # use default config, and change custom config
   @throttler(ThrottlerConfig(rate="1/2s"))
   def func_b(*args, **kwargs):
       return args, kwargs
   
   # use default config, and change redis client and some custom config
   @throttler(ThrottlerConfig(rate="1/2s", redis_client=redis_client))
   def func_c(*args, **kwargs):
       return args, kwargs
   
   # change a callable into throttled callable
   def func_d(*args, **kwargs):
       return args, kwargs
   func = Throttler(ThrottlerConfig(func=func_d))
   func(*args, **kwargs)

3. [Optinal] get metric data

   from redis.client import Redis
   from client_throttler import MetricManager, ThrottlerConfig, Throttler
   
   redis_client = Redis(host="localhost", port=1234, db=2)
   
   def func_a(*args, **kwargs):
       return args, kwargs
   
   # enable_metric_record=True should be set when collect metric
   config = ThrottlerConfig(func=func_a, redis_client=redis_client, rate="100/s", enable_metric_record=True)
   func = Throttler(config)
   
   """
   call your func
   """
   
   metrics = MetricManager(config).load_metrics()

Based on the MIT protocol. Please refer to LICENSE