Dart implementation for Sliding Window Limiter #

A lightweight, storage‑agnostic sliding‑window rate limiter for Dart. Provide your own storage (e.g., Redis, in‑memory, database) via a tiny Storage interface, and call consume(tokens) to check and record usage.

Install #

• With Dart: dart pub add sliding_window_limiter
• With Flutter: flutter pub add sliding_window_limiter

Quick start #

import 'dart:convert';
import 'package:sliding_window_limiter/sliding_window_limiter.dart';

Future<void> main() async {
  final limiter = SlidingWindowLimiter(
    id: 'client-IP-or-user-id',
    limit: 120,                       // max tokens per interval
    interval: Duration(minutes: 1),   // sliding window interval
    storage: RedisStorage(),          // your Storage implementation
  );

  // Request 1 token for this operation
  final result = await limiter.consume(1);

  if (!result.accepted) {
    // Inform caller to retry later
    print('Retry after: ${result.retryAfter}');
    print('Wait time: ${result.waitTime.inSeconds} seconds');
    return;
  }

  print('Remaining tokens: ${result.remainingTokens}');
}

// Example storage (replace with real Redis client)
class RedisStorage implements Storage {
  @override
  Future<void> save(SlidingWindow window) async {
    // Persist window.toJson() and set TTL to:
    //   window.windowEndAt.difference(DateTime.now())
  }

  @override
  Future<SlidingWindow?> fetch(String id) async {
    final data = null; // Load JSON string by id
    if (data == null) return null;
    return SlidingWindow.fromJson(jsonDecode(data));
  }
}

If you just need an in‑memory example for tests, this minimal storage works:

class MemoryStorage implements Storage {
  final Map<String, SlidingWindow> _store = {};

  @override
  Future<void> save(SlidingWindow window) async {
    _store[window.id] = window;
  }

  @override
  Future<SlidingWindow?> fetch(String id) async {
    final w = _store[id];
    if (w == null || w.isExpired()) return null;
    return w;
  }
}

API #

• SlidingWindowLimiter:

  • id: logical key (e.g., user ID, IP).
  • limit: max tokens allowed per interval.
  • interval: sliding window duration.
  • storage: implementation of Storage.
  • Future<RateLimit> consume(int tokens): attempts to consume tokens.

• RateLimit result:

  • accepted: whether tokens were accepted.
  • remainingTokens: remaining capacity in current window (double).
  • retryAfter: timestamp when enough capacity is available.
  • waitTime: convenience Duration until retryAfter (zero if available now).
  • limit: configured max tokens per interval.

• Storage interface:

  • Future<void> save(SlidingWindow window)
  • Future<SlidingWindow?> fetch(String id)

Notes:

• tokens must be > 0 and <= limit.
• Use your storage’s TTL equal to windowEndAt - now to auto‑expire windows.
• The algorithm decays usage continuously within the window for smooth limiting.

License #

Apache-2.0 — see LICENSE.