Feature set review API
The feature set review process involves the reviewer's acceptance. Depending on the system configuration, all feature sets or only sensitive ones may be subject to review.
Manage review requests from other users
Reviewer is a user who can approve or reject feature sets.
List of all pending feature set reviews requests from users
- Python
- Scala
reviews = client.feature_set_reviews.manageable_requests(filters)
val reviews = client.featureSetReviews.manageableRequests(filters)
The filters argument is optional and specifies which review
status(es) you are interested in. By default, it is empty.
To provide filter to your requests, please create it as:
- Python
- Scala
from featurestore.core.review_statuses IN_PROGRESS, APPROVED, REJECTED
filters = [IN_PROGRESS, REJECTED]
import ai.h2o.featurestore.core.ReviewStatuses.{IN_PROGRESS, APPROVED, REJECTED}
val filters = Seq(IN_PROGRESS, REJECTED)
List of pending feature set reviews requests related to project
Similarly, you can list the pending feature set reviews on a project basis.
- Python
- Scala
project = client.projects.get("project_name")
reviews = project.feature_set_reviews.manageable_requests(filters)
val project = client.projects.get("project_name")
val reviews = project.featureSetReviews.manageableRequests(filters)
Approve a feature set review request from the user
- Python
- Scala
review_request.approve("it will be fun")
review.approve("it will be fun")
Reject a feature set review request from the user
- Python
- Scala
review_request.reject("it's not ready yet")
review.reject("it's not ready yet")
Get a feature set to review
To get feature set in review, please call:
- Python
- Scala
review_request.get_feature_set()
review.getFeatureSet()
Preview the data of feature set to review
To preview data ingested to feature set related to review, simply call method:
- Python
- Scala
review_request.get_preview()
review.getPreview()
Manage own feature sets in review
User can see own review requests.
List all feature sets review requests in review
- Python
- Scala
reviews = client.feature_set_reviews.my_requests(filters)
val reviews = client.featureSetReviews.myRequests(filters)
The filters argument is optional and specifies which review
status(es) you are interested in. By default, it is empty.
To verify the status of your request, specify using the corresponding filters. For example:
- Python
- Scala
from featurestore.core.review_statuses IN_PROGRESS, APPROVED, REJECTED
filters = [IN_PROGRESS, REJECTED]
import ai.h2o.featurestore.core.ReviewStatuses.{IN_PROGRESS, APPROVED, REJECTED}
val filters = Seq(IN_PROGRESS, REJECTED)
List feature sets review requests in review related to project
Similarly, you can list your own review requests that are related to a project.
- Python
- Scala
project = client.projects.get("project_name")
reviews = project.feature_set_reviews.my_requests(filters)
val project = client.projects.get("project_name")
val reviews = project.featureSetReviews.myRequests(filters)
Get a feature set in review
To get feature set with features related to the review, simply call method:
- Python
- Scala
review.get_feature_set()
review.getFeatureSet()
Preview the data of feature set in review
To preview data on feature set in review, please call:
- Python
- Scala
review.get_preview()
review.getPreview()
Delete feature set version in in review
To delete feature set major version which is in review and is in status IN_PROGRESS or REJECTED, please call:
- Python
- Scala
review.delete()
review.delete()
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