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@roneysilva25/rate-limiter

v1.0.3

Published

Implementation of the most common rate limiting algorithms: Fixed Window, Sliding Window, Leaky Bucket, Token Bucket. To be used as middleware for express applications.

Downloads

12

Readme

rate-limiter

Implementation of the most common rate limiting algorithms: Fixed Window, Sliding Window, Leaky Bucket, Token Bucket. To be used as middleware for express applications.

Instalation

npm install @roneysilva25/rate-limiter

or

yarn add @roneysilva25/rate-limiter

Usage

import { rateLimiter } from "@roneysilva25/rate-limiter";

const app = express();

const limiter = rateLimiter({
    algorithm: "fixed_window",
    capacity: 100,
    timeWindowInMs: 1000*60*2,
});

app.use(limiter.limit);

Configuration

| Name | Description | Default Value | ------------|--------------|---------------| | algorithm | The algorithm to be used in the rate limiter. Current options include: fixed_window. More algorithms to be included as mentioned in the Roadmap section. | fixed_window | | capacity | The amount of requests allowed within the specified time window. | 200 | | timeWindowInMS | The time window, in milliseconds to limit the incoming requests. | 120000 ms (2 minutes) |

How is the rate limiting applied?

The limit is applied by IP Address. If req.ip is undefined, a 400 status response is sent with body "Invalid IP Address.".

Response Headers

The following headers are added to every response: | Name | Description | -------|-------------| | X-RateLimit-Limit | Represents the configured capacity. | | X-RateLimit-Remaining | Represents the remaining requests allowed within the current time window | | X-RateLimit-Reset | Represents, in milliseconds, the remaining time before the current time window restarts. This is calculated using the EPOCH time as a reference. |

When a request is dropped after reaching the limit, a 429 status code response is sent.

Time Complexity

How are the remaining limits and time windows stored for each IP Address?

This information is stored in-memory in a hash map data structure with the IP Address as the key. This provides O(1) time complexity for lookups and insertions.

Roadmap

Future plans include:

  • Implemeting more rate limiting algorithms.
  • Add integration with Redis.

Made by: Roney Diego