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Design and manage feature stores for ML systems. Use when building reusable feature pipelines, managing feature versioning, or serving features for inference.
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Template for creating new skills. Copy this directory and customize for your specific use case.
| name | feature-store |
| description | Design and manage feature stores for ML systems. Use when building reusable feature pipelines, managing feature versioning, or serving features for inference. |
Activate this skill when working with feature engineering at scale.
from feast import FeatureStore, Entity, FeatureView
store = FeatureStore(repo_path="feature_repo/")
# Define features
user_features = FeatureView(
name="user_features",
entities=[user_entity],
schema=[
Field(name="total_purchases", dtype=Int64),
Field(name="avg_order_value", dtype=Float64),
],
source=user_source,
)
# Retrieve for training
training_df = store.get_historical_features(
entity_df=entity_df,
features=["user_features:total_purchases"],
).to_df()