remote_caching 1.0.2
remote_caching: ^1.0.2 copied to clipboard
A Flutter package for caching remote API calls with configurable duration.
Remote Caching
A lightweight, flexible, and persistent cache layer for remote API calls in Flutter.
Avoid redundant network calls. Boost performance. Cache smartly.
A lightweight yet powerful Flutter package for caching asynchronous remote calls locally using SQLite β with full support for expiration, serialization, and custom deserializers.
π§ Save your API responses. π Avoid unnecessary calls. β‘ Go fast. π‘ Stay clean.
β¨ Features #
- β Automatic caching of remote data
- β³ Configurable expiration duration per call
- π Manual cache invalidation (by key or all)
- πΎ SQLite-powered persistent cache
- π§© Generic support for any type (
Map
,List
, custom models...) - π§° Custom
fromJson()
support for deserializing complex types - π Cache statistics API
- π§ͺ Test-friendly and easy to debug (
verboseMode
)
β Why RemoteCaching? #
- π You need structured, persistent caching for remote API calls
- π‘ You want control over serialization and expiration
- π§Ό You donβt want to reinvent the wheel each time you need simple cache logic
π Getting Started #
Add to your pubspec.yaml
:
flutter pub add remote_caching
Then run:
flutter pub get
π οΈ Usage #
1. Initialize the cache system #
await RemoteCaching.instance.init(
defaultCacheDuration: Duration(hours: 1), // Optional
verboseMode: true, // Optional: see logs in your console
);
2. Cache a remote API call #
final user = await RemoteCaching.instance.call<UserProfile>(
'user_profile',
cacheDuration: Duration(minutes: 30), // Optional
remote: () async => await fetchUserProfile(),
fromJson: (json) => UserProfile.fromJson(json as Map<String, dynamic>), // Optional
);
Or if you want to cache a remote call with a dynamic key:
final pizza = await RemoteCaching.instance.call<Pizza>(
'pizza_${pizzaName}',
cacheDuration: Duration(minutes: 30), // Optional
remote: () async => await fetchPizza(pizzaName),
fromJson: (json) => Pizza.fromJson(json as Map<String, dynamic>), // Optional
);
- The first call fetches from remote and caches the result.
- Subsequent calls within 30 minutes return the cached value.
- After expiration, the remote is called again and cache is updated.
3. Force refresh #
await RemoteCaching.instance.call(
'user_profile',
forceRefresh: true,
remote: () async => await fetchUserProfile()
);
4. Clear cache #
await RemoteCaching.instance.clearCache(); // All
await RemoteCaching.instance.clearCacheForKey('user_profile'); // By key
5. Get cache statistics #
final stats = await RemoteCaching.instance.getCacheStats();
print(stats); // CachingStats(totalEntries: 3, totalSizeBytes: 1234, expiredEntries: 1)
π¦ Example #
A full example is available in the example/
directory. It demonstrates how to cache results from the Agify.io API and display them in a Flutter app.
π API Reference #
RemoteCaching #
Method | Description |
---|---|
init({Duration? defaultCacheDuration, bool verboseMode = false}) |
Initialize the cache system |
call<T>(String key, {required Future<T> Function() remote, Duration? cacheDuration, bool forceRefresh = false, T Function(Object? json)? fromJson}) |
Cache a remote call |
clearCache() |
Clear all cache |
clearCacheForKey(String key) |
Clear cache for a specific key |
getCacheStats() |
Get cache statistics |
dispose() |
Dispose the cache system |
β FAQ #
Q: What happens if serialization or deserialization fails?
A: The error is logged, the cache is ignored, and the remote call is used. Your app will never crash due to cache errors.
Q: Can I use my own model classes?
A: Yes! Just provide a fromJson
function and ensure your model supports toJson
.
Q: Does it work offline?
A: Cached data is available offline until it expires or is cleared.
Q: Does it work on all platforms?
A: We use sqlite3 with sqflite_common_ffi to support all platforms. Refer to the packages docs for more information.
π€ Contributing #
Contributions, issues and feature requests are welcome! Feel free to check issues page or submit a pull request.
- Fork the repo
- Create your feature branch (
git checkout -b feature/my-feature
) - Commit your changes (
git commit -am 'Add new feature'
) - Push to the branch (
git push origin feature/my-feature
) - Create a new Pull Request
Made with β€οΈ by Eliatolin