Storage backend¶

Results of the computation are stored according to the storage backend defined in RECOMMENDS_STORAGE_BACKEND (default to 'recommends.storages.djangoorm.storage.DjangoOrmStorage'). A storage backend defines how de/serialize and store/retrieve objects and results.

A storage backend can be any class extending recommends.storages.base.RecommendationStorage that implements the following methods and properties:

get_identifier(self, obj, *args, **kwargs)¶: Given an object and optional parameters, returns a string identifying the object uniquely.

resolve_identifier(self, identifier)¶: This method is the opposite of get_identifier. It resolve the object’s identifier to an actual model.

get_similarities_for_object(self, obj, limit, raw_id=False)¶

if raw_id = False:

Returns a list of Similarity objects for given obj, ordered by score.

else:

Returns a list of similar model ids[pk] for given obj, ordered by score.

Example:

[
    {
        "related_object_id": XX, "content_type_id": XX
    },
    ..
]

get_recommendations_for_user(self, user, limit, raw_id=False)¶

if raw_id = False:

Returns a list of Recommendation objects for given user, order by score.

else:

Returns a list of recommended model ids[pk] for given user, ordered by score.

Example:

[
    {
        "object_id": XX, "content_type_id": XX
    },
    ..
]

get_votes(self)¶

Optional.

Retrieves the vote matrix saved by store_votes.

You won’t usually need to implement this method, because you want to use fresh data. But it might be useful if you want some kind of heavy caching, maybe for testing purposes.

store_similarities(self, itemMatch)¶

store_recommendations(self, user, recommendations)¶

Stores all the recommendations.

recommendations is an iterable with the following schema:

(
    (
        <user>,
        (
            (<object_identifier>, <score>),
            (<object_identifier>, <score>)
        ),
    )
)

store_votes(self, iterable)¶

Optional.

Saves the vote matrix.

You won’t usually need to implement this method, because you want to use fresh data. But it might be useful if you want to dump the votes on somewhere, maybe for testing purposes.

iterable is the vote matrix, expressed as a list of tuples with the following schema:

[
    ("<user_id1>", "<object_identifier1>", <score>),
    ("<user_id1>", "<object_identifier2>", <score>),
    ("<user_id2>", "<object_identifier1>", <score>),
    ("<user_id2>", "<object_identifier2>", <score>),
]

remove_recommendations(self, obj)¶: Deletes all recommendations for object obj.

remove_similarities(self, obj)¶: Deletes all similarities that have object obj as source or target.

get_lock(self)¶: Optional. Acquires an exclusive lock on the storage is acquired. Returns True if the lock is aquired, or False if the lock is already acquired by a previous process.

release_lock(self)¶: Optional. Releases the lock acquired with the get_lock method.

RedisStorage¶

This storage allows you to store results in Redis. This is the recommended storage backend, but it is not the default because it requires you to install redis-server.

Options¶

threshold_similarities Defaults to 0. Only similarities with score greater than threshold similarities will be persisted.

threshold_recommendations Defaults to 0. Only recommendations with score greater than threshold similarities will be persisted.

Settings¶

RECOMMENDS_STORAGE_REDIS_DATABASE: A dictionary representing how to connect to the redis server. Defaults to:

{
    'HOST': 'localhost',
    'PORT': 6379,
    'NAME': 0
}

DjangoOrmStorage¶

This is the default storage. It requires minimal installation, but it’s also the less performant.

This storage allows you to store results in a database specified by your DATABASES setting.

In order to use this storage, you’ll also need to add 'recommends.storages.djangoorm' to your INSTALLED_APPS.

Options¶

threshold_similarities Defaults to 0. Only similarities with score greater than threshold similarities will be persisted.

threshold_recommendations Defaults to 0. Only recommendations with score greater than threshold similarities will be persisted.

Settings¶

To minimize disk I/O from the database, Similiarities and Suggestions will be committed in batches. The RECOMMENDS_STORAGE_COMMIT_THRESHOLD setting set how many record should be committed in each batch. Defaults to 1000.

RECOMMENDS_STORAGE_DATABASE_ALIAS is used as the database where similarities and suggestions will be stored. Note that you will have to add recommends.storages.djangoorm.routers.RecommendsRouter to your settings’ DATABASE_ROUTERS if you want to use something else than the default database. Default value is set to 'recommends'.

MongoStorage¶

Options¶

threshold_similarities Defaults to 0. Only similarities with score greater than threshold similarities will be persisted.

threshold_recommendations Defaults to 0. Only recommendations with score greater than threshold similarities will be persisted.

Settings¶

RECOMMENDS_STORAGE_MONGODB_DATABASE: A dictionary representing how to connect to the mongodb server. Defaults to:

{
    'HOST': 'localhost',
    'PORT': 27017,
    'NAME': 'recommends'
}

RECOMMENDS_STORAGE_MONGODB_FSYNC: Boolean specifying if MongoDB should force writes to the disk. Default to False.