recombee_api_client.api_requests.recommend_users_to_item module

class recombee_api_client.api_requests.recommend_users_to_item.RecommendUsersToItem(item_id: str, count: int, scenario: str = UUID('66571c2a-9bc4-4d91-9ed1-bef055653061'), cascade_create: bool = UUID('66571c2a-9bc4-4d91-9ed1-bef055653061'), return_properties: bool = UUID('66571c2a-9bc4-4d91-9ed1-bef055653061'), included_properties: list = UUID('66571c2a-9bc4-4d91-9ed1-bef055653061'), filter: str = UUID('66571c2a-9bc4-4d91-9ed1-bef055653061'), booster: str = UUID('66571c2a-9bc4-4d91-9ed1-bef055653061'), logic: Union[str, dict] = UUID('66571c2a-9bc4-4d91-9ed1-bef055653061'), diversity: float = UUID('66571c2a-9bc4-4d91-9ed1-bef055653061'), expert_settings: dict = UUID('66571c2a-9bc4-4d91-9ed1-bef055653061'), return_ab_group: bool = UUID('66571c2a-9bc4-4d91-9ed1-bef055653061'))

Bases: recombee_api_client.api_requests.request.Request

Recommend users that are likely to be interested in a given item.

It is also possible to use POST HTTP method (for example in case of very long ReQL filter) - query parameters then become body parameters.

The returned users are sorted by predicted interest in the item (first user being the most interested).

Required parameters:

Parameters

  • item_id – ID of the item for which the recommendations are to be generated.

  • count – Number of items to be recommended (N for the top-N recommendation).

Optional parameters:

Parameters

scenario – Scenario defines a particular application of recommendations. It can be for example “homepage”, “cart” or “emailing”.

You can set various settings to the [scenario](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com). You can also see performance of each scenario in the Admin UI separately, so you can check how well each application performs.

The AI which optimizes models in order to get the best results may optimize different scenarios separately, or even use different models in each of the scenarios.

Parameters

  • cascade_create – If item of given itemId doesn’t exist in the database, it creates the missing item.

  • return_properties – With returnProperties=true, property values of the recommended users are returned along with their IDs in a JSON dictionary. The acquired property values can be used for easy displaying the recommended users.

Example response:

```

E{lb}

“recommId”: “039b71dc-b9cc-4645-a84f-62b841eecfce”,

“recomms”:

[

E{lb}

“id”: “user-17”,

“values”: E{lb}

“country”: “US”,

“sex”: “F” E{rb} E{rb},

E{lb}

“id”: “user-2”,

“values”: E{lb}

“country”: “CAN”,

“sex”: “M” E{rb} E{rb}

],

“numberNextRecommsCalls”: 0 E{rb}

```

Parameters

included_properties – Allows to specify, which properties should be returned when returnProperties=true is set. The properties are given as a comma-separated list.

Example response for includedProperties=country:

```

E{lb}

“recommId”: “b2b355dd-972a-4728-9c6b-2dc229db0678”,

“recomms”:

[

E{lb}

“id”: “user-17”,

“values”: E{lb}

“country”: “US” E{rb} E{rb},

E{lb}

“id”: “user-2”,

“values”: E{lb}

“country”: “CAN” E{rb} E{rb}

],

“numberNextRecommsCalls”: 0 E{rb}

```

Parameters

filter – Boolean-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to filter recommended items based on the values of their attributes.

Filters can be also assigned to a [scenario](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).

Parameters

booster – Number-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to boost recommendation rate of some items based on the values of their attributes.

Boosters can be also assigned to a [scenario](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).

Parameters

logic – Logic specifies particular behavior of the recommendation models. You can pick tailored logic for your domain and use case.

See [this section](https://docs.recombee.com/recommendation_logics.html) for list of available logics and other details.

The difference between logic and scenario is that logic specifies mainly behavior, while scenario specifies the place where recommendations are shown to the users.

Logic can be also set to a [scenario](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).

Parameters

  • diversity – Expert option Real number from [0.0, 1.0] which determines how much mutually dissimilar should the recommended items be. The default value is 0.0, i.e., no diversification. Value 1.0 means maximal diversification.

  • expert_settings – Dictionary of custom options.

  • return_ab_group – If there is a custom AB-testing running, return name of group to which the request belongs.

get_body_parameters() → dict

Values of body parameters as a dictionary (name of parameter: value of the parameter).

get_query_parameters() → dict

Values of query parameters as a dictionary (name of parameter: value of the parameter).