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This CodenameOne library enables apps to easily cache data downloaded from the app server (or any other source) in the device's file system. Cached data is saved in JSON format, one file per object type. Caching data can potentially improve the app's performance and responsivity, cut down on cell data usage, extend battery life, and enable 'offline mode'.


Installing the library is the same as any another cn1 library, as explained in the docs. You can either install this library using the cn1lib wizard, or clone the repository, build the project in your IDE, and copy the .cn1lib file from the /dist folder.


The data caching cycle usually looks like this:

Initialize cache (first time only) -> Sync local cache to server -> Retrieve/modify data from cache -> Update server

Depending on the needs of the application, the cache may need to be resynced from the server periodically (if it's an app in which users exchange data). All the various stages of this cycle are exposed by the library's API.


Each CacheFile instance is responsible for a single class of objects that are to be cached. For instance, an app that allows users to trade used cars, there might be a Car object and a User object that you want to cache on the device.

public class Car {
	private long carId;
	private String model;
	private String condition;
	private int year;
	private long ownerId;
	(getters and setters)

public class User {
	private long userId;
	private String name;
	private String email;
	(getters and setters)

Implementing CacheSerializer

Each one of these classes needs its own CacheFile to manage its cached data, and a CacheSerializer to serialize and deserialize the objects. In this case, implementing the serializer is quite straightforward:

public class CarSerializer implements CacheSerializer<Car>{
	public Car deserialize(JSONObject rawData){
		Car car = new Car();
		return car;
    public JSONObject serialize(Car car){
		return new JSONObject()
		.put("id", car.getId())
		.put("model", car.getModel())
		.put("condition", car.getCondition())
		.put("year", car.getYear())
		.put("owner", car.getOwnerId());
    default public Object getObjectId(Car car){
        return object.getId();

Note: The getObjectId method must return a unique value for each object in the given cache.

ParseObject Serialization
An example of a serializer for ParseObject (from the parse4cn1 library) can be found in this gist. It is important to note that the implementation in the gist assumes that all ParseObject references are fetched at the time of serialization.

A similar serializer can be easily implemented for the User class. Once we've done that, we can instantiate a CacheFile object and specify which class's cache it will manage by setting the typed parameter.

For instance, in our car trading app, we need two different instances:

CacheFile<Car> carCache = new CacheFile(FileSystemStorage.getInstance().getAppHomePath() + "cache/car.json", new CarSerializer(), true);
CacheFile<User> userCache = new CacheFile(FileSystemStorage.getInstance().getAppHomePath() + "cache/user.json", new UserSerializer(), true);

CacheFile Constructor

The constructor for CacheFile takes three arguments, as seen above.

The first argument is the absolute path to the file on the device that will contain the cached data. The file will be created if it doesn't exist, and will be overwritten if it does. The containing directory must be created ahead of time. For instance, if you want to store my cache at /myappdir/cache/car.json, you will need to create the directory /myappdir/cache before calling the constructor.

The second argument is a CacheSerializer implementation with the same typed parameter as the CacheFile.

The third argument is boolean, which determines whether or not the cache will be held in memory as well, or only in the filesystem (true for memory caching). Memory caching provides for much quicker retrieval and manipulation of data, and can cut down on battery usage, but can be a strain on the device's resources if very large datasets are being cached. If memory caching is used, the data needs to be persisted to the file via the CacheFile.syncFromMemCacheAsync() method before exiting the app, or all changes will be lost.

It is best practice to use only a single instance of CacheFile per type of object being stored. One simple way to achieve this is by instantiating all CacheFiles in the cn1 application class's start() method, and hold a static reference to the CacheFile:

public class MyApplication{
	public static CacheFile carCache<Car>;
	public void start(){
		carCache = new CacheFile(FileSystemStorage.getInstance().getAppHomePath() + "cache/car.json", new CarSerializer(), true);

And then, in the form that displays the car data:

CacheFile<Car> carCache = MyApplication.carCache;
Car[] cars = carCache.getAll(); // retrieve all cars in the cache

Syncing From External Data Source

The method CacheFile.syncAll() is used to populate the cache with data, either initially, or at any point when the cached data needs to be refreshed from the server or any other source. All existing data in the cache is replaced completely by the data array received in the method argument.

Retrieving Objects

CacheFile exposes a few different methods for retrieving objects:

  • CacheFile.getAll() retrieves all the objects in the cache
  • CacheFile.getRange(int first, int last) retrieves all the objects in the given range, by 0-based index (including the last index). The list is ordered according to the comparator that was passed in the constructor (see below), or is unordered, if no comparator was set. This method can be used in conjunction with cn1's InfiniteContainer to easily create infinitely scrolling cache-based lists of objects.
  • CacheFile.get(Object id) retrieves a single object, using the id as calculated by the serializer.

List Sorting

By passing a Comparator implementation as a fourth argument of the CacheFile, you can affect how the objects will be sorted (applies to the getAll() and getRange() methods). You can sort a single cache of objects more than one way by creating multiple instances of CacheFile all based on the same physical file, using different comparators. For instance, if the car swapping app wanted to allow fast sorting by price, year, or model, it would look something like this:

String carCacheFilepath = FileSystemStorage.getInstance().getAppHomePath() + "cache/car.json";
CacheSerializer carSerializer = new CarSerializer();
CacheFile carByPrice = new CacheFile(carCacheFilepath, carSerializer, true, new CarByPriceComparator());
CacheFile carByYear = new CacheFile(carCacheFilepath, carSerializer, true, new CarByYearComparator());
CacheFile carByModel = new CacheFile(carCacheFilepath, carSerializer, true, new CarByModelComparator());

This way, the cars are all presorted simultaneously by price, year, and model (in a case like this it might be wiser not to use memory caching - depending on how large the dataset is, it could cause a strain on system memory).

Updating Objects

Updating the cache can be done one object at a time, using the following methods:

  • CacheFile.addToCache(Object o, CacheErrorNotifier notifier)
  • CacheFile.update(Object o, CacheErrorNotifier notifier)
  • CacheFile.remove(Object o, CacheErrorNotifier notifier)

Typically, the app will want to save the object to the external source as well:

	public class Car{
		private CacheFile carCache;
		public boolean save(){
				} else{
				return true;
			}catch(Exception ex){
				return false;

Cache Validation

While at some point the cache will need to be refreshed with current data from the external data source, it's not a trivial task to keep track of data freshness. Therefore the app can set a data freshness policy for each CacheFile instance that will then allow it to query the cache about the state of the data. After instatiating an instance of CacheFile, the setPolicy() method can be used to enforce a policy of data freshness, which is determined via the isCacheValid() method. Currently only three policies are available, but other policies can be added by extending the CacheFile class and overriding the isCacheValid() method. The various policies are cumulative, i.e. if the cache in invalid according to any one of the criteria, the method will return false. For instance, if the app needs to ensure the data will be refreshed when the app is opened, and at least once an hour while the app is open, the following code would be expected:

// in application class
public void start(){
	carCache = new CacheFile("cars.json", new CarSerializer, true);
	carCache.setPolicy(new HashSet(new CachingPolicy[]{CachingPolicy.SYNC_ON_APP_OPEN, SYNC_HOURLY}));

// in DAL class
public List<Car> getAllCars(){
		return carCache.getAll();
	// if cache is invalid	
	List<Car> cars = getCarsFromServer();
	return cars;

Likewise, if the app only needs the data to be refreshed once a day, then only the SYNC_DAILY restraint would be applied.

The CacheErrorNotifier Interface

Since the cache is held in the file as a JSON array, the entire file is actually rewritten every time the cache is persisted to the filesystem. This can be a rather lengthy operation, therefore it is executed on a worker thread, not on the EDT (see here for more details). By passing an implementation of CacheErrorNotifier when performing an operation that writes to the file, the exception can be retrieved from the worker thread, and can be reacted to appropriately.

The CacheErrorNotifier will only report an error if 1. the operation writes to the filesystem and 2. the operation threw an error. The operations that write to the filesystem vary, depending on whether or not memory caching is being used:

  • syncAll() always writes to the filesystem
  • addToCache(), update(), and remove() write to the filesystem if memory caching is not being used
  • retrieval operations never write to file, therefore they do not accept a notifier object in the method arguments

Similarly, passing null for the notifier argument is the way to indicate that the app is not interested in being notified of potential exceptions.


A minimalistic caching framework for CodenameOne apps to cache server data








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