stash

Description:

stash

stash #







Overview #
The stash library is a key-value store abstraction with a pluggable backend architecture that provides support for vault and cache objects. The vault is a simple key value storage for primitives and objects but the cache goes one step further and adds caching semantics. The design of the cache was heavily influenced by the JCache spec from the Java world, albeit it draws inspiration from other libraries as well. It supports the most traditional capabilities found on well know caching libraries like expiration or eviction and all it's core concepts were designed from ground up with extensibility in mind.
3rd party library support was a major concern since the inception, as such, a library stash_test is provided with a complete set of tests that allow the developers of novel storage backends to test their implementations against the same baseline tests that were used by the main library.
History #
The stash library started it's life as a pure cache library, however with the multiple versions, it become clear that the pluggable storage backend architecture could be reused to provide a key value abstraction that can be leveraged in other scenarios like the storage of preferences or assets or as a general purpose key value database. With version 4.0.0, comes the first major revision and most of the breaking changes since it's inception.
Features #

🚀 Binary serialization - Provides out-of-box highly performant binary serialization using an implementation of msgpack inspired on the msgpack_dart package and adapted to the specific needs of this library .
🔀 Type Agnostic Reuse the same store for multiple types. Each store is partitioned and it's possible to configure a type and the respective fromEncodable function per partition.
✨ Events - Subscribable events for vault and cache instances, providing notifications on creation, update or removal of an entry and also expiry and eviction notifications for caches.
📊 Statistics - Supports the capture of vault and cache statistics
⏰ Cache Expiry policies - out-of-box support for Eternal,Created, Accessed, Modified and Touched policies.
📤 Cache Eviction policies - out-of-box support for FIFO(first-in, first-out), FILO (first-in, last-out), LRU (least-recently used), MRU (most-recently used), LFU (least-frequently used, the default), MFU (most frequently used) and Hyperbolic
🎲 Cache entry sampling - Sampling of eviction candidates randomly or via reservoir sampling
🍔 Tiered cache - Allows the configuration of a primary highly performing cache (in-memory for example) and a secondary second-level cache
➿ Extensible - Pluggable implementations of custom encoding/decoding, storage, stats, expiry, eviction and sampling strategies.
🔧 Testable - Storage, vault and cache harness for 3d party support of novel storage backend strategies

Storage Implementations #
There's a vast array of storage implementations available which you can use.



Package
Version
SDK
Platform
Description




stash_memory

DART FLUTTER
ANDROID IOS LINUX MACOS WEB WINDOWS
A memory storage implementation


stash_file

DART FLUTTER
ANDROID IOS LINUX MACOS WEB WINDOWS
A storage implementation using the file package


stash_sqlite

DART FLUTTER
ANDROID IOS LINUX MACOS WINDOWS
A storage implementation using the drift package


stash_hive

DART FLUTTER
ANDROID IOS LINUX MACOS WEB WINDOWS
A storage implementation using the hive package


stash_sembast

DART FLUTTER
ANDROID IOS LINUX MACOS WINDOWS
A storage implementation using the sembast package


stash_sembast_web

DART FLUTTER
WEB
A storage implementation using the sembast_web package


stash_objectbox

DART FLUTTER
ANDROID IOS LINUX MACOS WINDOWS
A storage implementation using the objectbox package


stash_cbl

DART FLUTTER
ANDROID IOS LINUX MACOS WINDOWS
A storage implementation using the cbl package


stash_isar

DART FLUTTER
ANDROID IOS LINUX MACOS WINDOWS
A storage implementation using the isar package


stash_shared_preferences

FLUTTER
ANDROID IOS LINUX MACOS WEB WINDOWS
A storage implementation using the shared_preferences package


stash_secure_storage

FLUTTER
ANDROID IOS LINUX MACOS WEB WINDOWS
A storage implementation using the flutter_secure_storage package



Library Integrations #
There's also some integrations with well know dart libraries



Package
Pub
Description




stash_dio

Integrates with the Dio HTTP client



Test Support #
Finally a testing library is provided to aid in the development of third party storage backend extensions



Package
Pub
Description




stash_test

Testing support for stash extensions



Getting Started #
Select one of the storage libraries and add the api and storage packages to your pubspec.yaml replacing x.x.x and y.y.y with the latest version of both. The example below uses the stash_memory package which provides an in-memory storage:
dependencies:
stash_api: ^x.x.x
stash_memory: ^y.y.y
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Run the following command to install dependencies:
dart pub get
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Finally, to start developing import the api and the selected storage implementation. In the example bellow the selected storage implementation is stash_memory thus we import the stash_apiand the stash_memory libraries:
import 'package:stash/stash_api.dart';
import 'package:stash/stash_memory.dart';
// In a more general sense 'package:stash/stash_xxx.dart' where xxx is the name of the
// storage provider, memory, hive and so on
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Usage #
Start by creating an instance of the storage backend and to decide if the stash needs caching or plain key-value semantics. For the former we need a cache while for the latter we need a vault. For example, to use an in-memory vault you we need to call the newMemoryVaultStore function which is exported by the stash_memory package. This function allows the user to bootstrap a in-memory store for vaults. Note that there is a similar one for caches dubbed newMemoryCacheStore
// Create a in-memory store
final store = await newMemoryVaultStore();
// In a more general sense 'newXXXVaultStore' or 'newXXXCacheStore' where xxx is the name of the storage provider,
// memory, file, sqlite, hive and so on
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Then you can create as many vault's as you wish from this store (for caches you need a different storage). Let's create one to store string's and add an element to it
// Creates a vault from the previously created store
final stringVault = await store.vault<String>();

// Adds a new value to the vault
await stringVault.put('key1', 'value1');
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Let's create a untyped vault and add two values to it with different types
// Creates a second vault from the previously created store
final anyVault = await store.vault();

// Adds a string value to the vault
await anyVault.put('key1', 'value1');

// Adds an int value to the vault
await anyVault.put('key1', 1);
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On both cases if the name of the vault is not provided a uuid is automatically assigned as the name. By using different names you can reuse the same storage and partition your data accordingly
Now let's create a cache. In this case a new type of store is needed as the cache needs additional fields to support expiry and eviction. In the example bellow a store is created followed by a cache with a max capacity of 10. Note: that the eviction policy is only applied if maxEntries is specified
// Creates a in-memory store
final store = await newMemoryCacheStore();

// Creates a cache with a max capacity of 10 from the previously created store
final cache = await store.cache<String>(maxEntries: 10);
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Then add a element to the cache:
// Adds a 'value1' under 'key1' to the cache
await cache.put('key1', 'value1');
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Finally, retrieve that element:
// Retrieves the value from the cache
final value = await cache.get('key1');
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The in-memory example is the simplest one, on that case there is no persistence so encoding/decoding of elements is not needed. Conversely when the storage mechanism uses persistence and we need to add custom objects they need to be json serializable and the appropriate configuration provided to allow the serialization/deserialization of those objects. This means that on those cases additional configuration is needed to allow the serilization/deserialization to happen.
Find bellow and example that uses stash_file as the storage implementation. In this case an object is stored, so in order to deserialize it the user needs to provide a way to decode it, like so: fromEncodable: (json) => Task.fromJson(json). The lambda should make a call to a user provided function that deserializes the object. Conversly, the serialization happens by convention i.e. by calling the toJson method on the object. Note that this example is sufficiently simple to warrant the usage of manual coded functions to serialize/deserialize the objects but it could be paired with the json_serializable package or similar for the automatic generation of the Json serialization / deserialization code.
import 'dart:io';

import 'package:stash/stash_api.dart';
import 'package:stash_file/stash_file.dart';

class Task {
final int id;
final String title;
final bool completed;

Task({required this.id, required this.title, this.completed = false});

/// Creates a [Task] from json map
factory Task.fromJson(Map<String, dynamic> json) => Task(
id: json['id'] as int,
title: json['title'] as String,
completed: json['completed'] as bool);

/// Creates a json map from a [Task]
Map<String, dynamic> toJson() =>
<String, dynamic>{'id': id, 'title': title, 'completed': completed};

@override
String toString() {
return 'Task $id, "$title" is ${completed ? "completed" : "not completed"}';
}
}

void main() async {
// Temporary directory
final path = Directory.systemTemp.path;

// Creates a store
final store = await newFileLocalCacheStore(path: path);

// Creates a cache with a capacity of 10 from the previously created store
final cache = await store.cache<Task>(
name: 'cache1',
fromEncodable: (json) => Task.fromJson(json),
maxEntries: 10,
eventListenerMode: EventListenerMode.synchronous)
..on<CacheEntryCreatedEvent<Task>>().listen(
(event) => print('Key "${event.entry.key}" added to the cache'));

// Adds a task with key 'task1' to the cache
await cache.put(
'task1', Task(id: 1, title: 'Run cache store example', completed: true));
// Retrieves the value from the cache
print(await cache.get('task1'));
}
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Notice that fromEncodable function is configured per cache which means you can configure a cache with a different type using the same store. This was not previously possible as before version 4.3.0 the fromEncodable function was configured per store. That has changed with version 4.3.0 which introduced this feature. Find bellow a complete example that stores two different objects in the same store and creates two vaults using two different fromEncodable functions.
import 'dart:io';

import 'package:stash/stash_api.dart';
import 'package:stash_file/stash_file.dart';

class Task {
final int id;
final String title;
final bool completed;

Task({required this.id, required this.title, this.completed = false});

/// Creates a [Task] from json map
factory Task.fromJson(Map<String, dynamic> json) => Task(
id: json['id'] as int,
title: json['title'] as String,
completed: json['completed'] as bool);

/// Creates a json map from a [Task]
Map<String, dynamic> toJson() =>
<String, dynamic>{'id': id, 'title': title, 'completed': completed};

@override
String toString() {
return 'Task $id, "$title" is ${completed ? "completed" : "not completed"}';
}
}

class Contact {
final int id;
final String name;

Contact({required this.id, required this.name});

/// Creates a [Contact] from json map
factory Contact.fromJson(Map<String, dynamic> json) =>
Contact(id: json['id'] as int, name: json['name'] as String);

/// Creates a json map from a [Contact]
Map<String, dynamic> toJson() => <String, dynamic>{'id': id, 'name': name};

@override
String toString() {
return 'Contact $id, "$name"';
}
}

void main() async {
// Temporary directory
final path = Directory.systemTemp.path;

// Creates a store
final store = await newFileLocalVaultStore(path: path);

// Creates a vault that stores Tasks from the previously created store
final taskVault = await store.vault<Task>(
name: 'taskVault',
fromEncodable: (json) => Task.fromJson(json),
eventListenerMode: EventListenerMode.synchronous)
..on<VaultEntryCreatedEvent<Task>>().listen(
(event) => print('Key "${event.entry.key}" added to the task vault'));

// Creates a vault that stores Contacts from the previously created store
final contactVault = await store.vault<Contact>(
name: 'contactVault',
fromEncodable: (json) => Contact.fromJson(json),
eventListenerMode: EventListenerMode.synchronous)
..on<VaultEntryCreatedEvent<Contact>>().listen((event) =>
print('Key "${event.entry.key}" added to the contact vault'));

// Adds a task with key 'task1' to the vault
await taskVault.put('task1',
Task(id: 1, title: 'Run task vault store example', completed: true));

// Adds a contact with key 'contact1' to the vault
await contactVault.put(
'contact1', Contact(id: 1, name: 'Run contact vault store example'));

// Retrieves the value from the task vault
print(await taskVault.get('task1'));

// Retrieves the value from the contact vault
print(await contactVault.get('contact1'));
}
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It's possible to automate the fetching of value whenever a vault or cache entry is not present or when the entry expired. You just need to provide a vaultLoader or a cacheLoader and when some entry is absent or expired stash can retrieve a new value for the specified key. The loader is configured when creating a vault or a cache e.g. store.cache(cacheLoader: (key) => ...). Note that this function must return a Future.
Vault #
Operations #
The Vault frontend provides a number of operations which are presented in the table bellow:



Operation
Description




name
Returns the name of the vault


size
Returns the number of entries on the vault


keys
Returns all the vault keys


containsKey
Checks if the vault contains an entry for the specified key


get
Gets the vault value for the specified key


getAll
Gets the vault values of the specified set of keys


put
Adds / Replace the vault value of the specified key


putAll
Adds / Replaces the vault values with the specified map of key / values


putIfAbsent
Replaces the specified key with the provided value if not already set


clear
Clears the contents of the vault


remove
Removes the specified key value


removeAll
Removes the specified keys values


getAndPut
Returns the specified key vault value and replaces it with value


getAndRemove
Gets the specified key vault value and removes it


manager
Returns the vault manager


statsEnabled
If the stats are enabled


stats
Returns the vault stats


on
Allows the subscription of vault events



Events #
The user of a Vault can subscribe to entry events if they are enabled as, by default, no events are propagated. The three possible configurations are setted via the eventListenerMode parameter. When creating a Vault the default value is Disabled as in, no events are published, but can be configured with Sync providing synchronous events or with Async in which case it provides assynchronous events. A user can subscribe all events or only to a specific set of events. On the example bellow a memory vault is created subscribing all the events synchronously.
// Creates a vault from a previously created store subscribing to the created, updated, removed events
final vault = await store.vault<String>(
eventListenerMode: EventListenerMode.synchronous)
..on<VaultEntryCreatedEvent<String>>().listen(
(event) => print('Key "${event.entry.key}" added'))
..on<VaultEntryUpdatedEvent<String>>().listen(
(event) => print('Key "${event.newEntry.key}" updated'))
..on<VaultEntryRemovedEvent<String>>().listen(
(event) => print('Key "${event.entry.key}" removed'));
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Event
Description




VaultEntryCreatedEvent
Triggered when a vault entry is created.


VaultEntryUpdatedEvent
Triggered when a vault entry is updated.


VaultEntryRemovedEvent
Triggered when a Vault entry is removed.



Statistics #
The user of a Vault can collect a number of statistics about it's usage by enabling stats through the statsEnabled flag. He can also provide a custom implementation of the VaultStats interface allowing custom statistics backends. The VaultStats interface defines a number of statistics that the user can collect through the following operations:



Operation
Description




gets
Returns the number of get requests satisfied by the vault


puts
Returns the number of puts satisfied by the vault


removals
Returns the number of removals satisfied by the vault


averageGetTime
Returns the mean time to execute gets in milliseconds


averagePutTime
Returns the mean time to execute puts in milliseconds


averageRemoveTime
Returns the mean time to execute a remove in milliseconds


clear
Clears the statistics counters to 0 for the associated vault.



Cache #
Operations #
The Cache frontend provides a number of operations which are presented in the table bellow.



Operation
Description




size
Returns the number of entries on the cache


keys
Returns all the cache keys


containsKey
Checks if the cache contains an entry for the specified key


get
Gets the cache value for the specified key


getAll
Gets the cache values of the specified set of keys


put
Adds / Replace the cache value of the specified key


putAll
Adds / Replaces the cache values with the specified map of key / values


putIfAbsent
Replaces the specified key with the provided value if not already set


clear
Clears the contents of the cache


remove
Removes the specified key value


removeAll
Removes the specified keys values


getAndPut
Returns the specified key cache value and replaces it with value


getAndRemove
Gets the specified key cache value and removes it


manager
Returns the cache manager


statsEnabled
If the stats are enabled


stats
Returns the cache stats


on
Allows the subscription of cache events



Types #
To create a Cache we can use the function exported by a specific storage library, newMemoryCacheStore in case of the stash_memory library (generically newXXXCacheStore where xxx is the name of the storage provider).
Note that this is not the only type of cache provided, stash also provies a tiered cache which can be created with a call to newTieredCache function which is exported by the base stash library. It allows the creation of a cache that uses primary and secondary cache surrogates. The idea is to have a fast in-memory cache as the primary and a persistent cache as the secondary altough other combinations are definitely supported. In this cases it's normal to have a bigger capacity for the secondary and a lower capacity for the primary cache. In the example bellow a new tiered cache is created using two in-memory caches the first with a maximum capacity of 10 and the second with unlimited capacity.
// Creates a in-memory store
final store = await newMemoryCacheStore();

/// Creates a tiered cache with both the primary and the secondary caches using
/// a memory based storage. The first cache with a maximum capacity of 10 and
/// the second with unlimited capacity
final cache = newTieredCache(
await store.cache<String>(maxEntries: 10),
await store.cache<String>());
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A more common use case is to have the primary cache using a memory storage and the secondary a cache backed by a persistent storage like the one provided by stash_file or stash_sqlite packages. The example bellow illustrates one of those use cases with the stash_file package as the provider of the storage backend of the secondary cache.
// Creates a in-memory store
final memoryStore = await newMemoryCacheStore();

// Creates a file store
final fileStore = await newFileLocalCacheStore(path: Directory.systemTemp.path);

final cache = newTieredCache(
await memoryStore.cache<String>(name: 'memoryCache', maxEntries: 10),
await fileStore.cache(name: 'diskCache', maxEntries: 1000));
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Expiry Policies #
It's possible to define how the expiration of cache entries works based on creation, access and modification operations. A number of pre-defined expiry polices are provided out-of-box that define multiple combinations of those interactions. Note that, most of the expiry policies can be configured with a specific duration which is used to increase the expiry time when some type of operation is executed on the cache. This mechanism was heavily inspired on the JCache expiry semantics. By default the configuration does not enforce any kind of expiration, thus it uses the Eternal expiry policy. It is of course possible to configure an alternative expiry policy setting the expiryPolicy parameter e.g. store.cache(expiryPolicy: const AccessedExpiryPolicy(Duration(days: 1))). Another alternative is to configure a custom expiry policy through the implementation of the ExpiryPolicy interface.



Policy
Description




EternalExpiryPolicy
The cache does not expire regardless of the operations executed by the user


CreatedExpiryPolicy
Whenever the cache is created the configured duration is appended to the current time. No other operations reset the expiry time


AccessedExpiryPolicy
Whenever the cache is created or accessed the configured duration is appended to the current time.


ModifiedExpiryPolicy
Whenever the cache is created or updated the configured duration is appended to the current time.


TouchedExpiryPolicy
Whenever the cache is created, accessed or updated the configured duration is appended to the current time.



Eviction Policies #
As discussed Cache supports eviction and provides a number of pre-defined eviction policies that are described in the table bellow. Note that it's mandatory to configure the cache with a number for maxEntries e.g. store.cache(maxEntries: 10). Without this configuration the eviction algorithm is not triggered since there is no limit defined for the number of items on the cache. The default algorithm is LRU (least-recently used) but other algorithms can be configured through the use of the evictionPolicy parameter e.g. store.cache(evictionPolicy: const HyperbolicEvictionPolicy()). Another alternative is to configure a custom eviction policy through the implementation of the EvictionPolicy interface.



Policy
Description




FifoEvictionPolicy
FIFO (first-in, first-out) policy behaves in the same way as a FIFO queue, i.e. it evicts the entries in the order they were added, without any regard to how often or how many times they were accessed before.


FiloEvictionPolicy
FILO (first-in, last-out) policy behaves in the same way as a stack and is the exact opposite of the FIFO queue. The cache evicts the entries added most recently first without any regard to how often or how many times it was accessed before.


LruEvictionPolicy
LRU (least-recently used) policy discards the least recently used entries first.


MruEvictionPolicy
MRU (most-recently used) policy discards, in contrast to LRU, the most recently used entries first.


LfuEvictionPolicy
LFU (least-frequently used) policy counts how often an entry is used. Those that are least often used are discarded first. In that sense it works very similarly to LRU except that instead of storing the value of how recently a block was accessed, it stores the value of how many times it was accessed.


MfuEvictionPolicy
MFU (most-frequently used) policy is the exact opposite of LFU. It counts how often a entry is used but it discards those that are most used first.


HyperbolicEvictionPolicy
Hyperbolic policy, combines the LRU and LFU semantics through the use of a priority function defined as pr(i) = number of accsses / time since i entered the cache. With this strategy it's possible to address some of the problems of the LFU policy by measuring relative popularity



When the maximum capacity of a cache is exceeded eviction of one or more entries is inevitable. At that point the eviction algorithm works with a set of entries that are defined by the sampling strategy used. In the default configuration the whole set of entries is used which means that the cache statistics will be retrieved from each and every one of the entries. This works fine for modest sized caches but can became a performance burden for bigger caches. On that cases a more efficient sampling strategy should be selected to avoid sampling the whole set of entities from storage. On those cases it's possible to configure the sampling strategy with the sampler parameter e.g. newMemoryCache(sampler: ReservoirSampler(0.5)) uses a ReservoirSampler sampler to select only half of the entries as candidates for eviction. The configuration of a custom sampler is also possible through the implementation of the KeySampler interface.



Sampler
Description




FullSampler
Returns the whole set, no sampling is performed


ShuffleSampler
A sampler that shuffles the elements from a list of keys and takes a sample


ReservoirSampler
An implementation of the reservoir sampling algorithm



Events #
The user of a Cache can subscribe to entry events if they are enabled as, by default, no events are propagated. The three possible configurations are setted via the eventListenerMode parameter. When creating a Cache the default value is Disabled as in, no events are published, but can be configured with Sync providing synchronous events or with Async in which case it provides assynchronous events. A user can subscribe all events or only to a specific set of events. On the example bellow a memory cache is created with a maximum of 10 entries subscribing all the events synchronously.
// Creates a cache with a capacity of 10 from a previously created store subscribing to the created, updated, removed, expired and evicted events
final cache = await store.cache<String>(
maxEntries: 10,
eventListenerMode: EventListenerMode.synchronous)
..on<CacheEntryCreatedEvent<String>>().listen(
(event) => print('Key "${event.entry.key}" added'))
..on<CacheEntryUpdatedEvent<String>>().listen(
(event) => print('Key "${event.newEntry.key}" updated'))
..on<CacheEntryRemovedEvent<String>>().listen(
(event) => print('Key "${event.entry.key}" removed'))
..on<CacheEntryExpiredEvent<String>>().listen(
(event) => print('Key "${event.entry.key}" expired'))
..on<CacheEntryEvictedEvent<String>>().listen(
(event) => print('Key "${event.entry.key}" evicted'));
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Event
Description




CacheEntryCreatedEvent
Triggered when a cache entry is created.


CacheEntryUpdatedEvent
Triggered when a cache entry is updated.


CacheEntryRemovedEvent
Triggered when a cache entry is removed.


CacheEntryExpiredEvent
Triggered when a cache entry expires.


CacheEntryEvictedEvent
Triggered when a cache entry is evicted.



Statistics #
The user of a Cache can collect a number of statistics about it's usage by enabling stats through the statsEnabled. He can also provide a custom implementation of the CacheStats interface allowing custom statistics backends.
The CacheStats interface defines a number of statistics that the user can collect through the following operations:



Operation
Description




gets
Returns the number of get requests satisfied by the cache


getPercentage
Returns the percentage of successful gets, as a decimal e.g 75


misses
Returns the number of cache misses


missPercentage
Returns the percentage of accesses that failed to find anything


requests
Returns the number of requests to the cache


puts
Returns the number of puts satisfied by the cache


removals
Returns the number of removals satisfied by the cache


averageGetTime
Returns the mean time to execute gets in milliseconds


averagePutTime
Returns the mean time to execute puts in milliseconds


averageRemoveTime
Returns the mean time to execute a remove in milliseconds


expiries
Returns the number of cache expiries


evictions
Returns the number of cache evictions


clear
Clears the statistics counters to 0 for the associated cache.



Contributing #
Contributions are always welcome!
If you would like to contribute with other parts of the API, feel free to make a Github pull request as I'm always looking for contributions for:

Tests
Documentation
New APIs

See CONTRIBUTING.md for ways to get started.
Thanks goes to these wonderful people (emoji key), that have already contributed to the project:






Gabriel Terwesten📖 💻 ⚠️ 💡
Mike Hoolehan⚠️
Thomas Järvstrand🐛
Romain Franceschini💻
Simon Stevens💻 🐛






This project follows the all-contributors specification. Contributions of any kind welcome!
Features and Bugs #
Please file feature requests and bugs at the issue tracker.
License #
This project is licensed under the MIT License - see the LICENSE file for details