# `Slither.Examples.MlScoring.FeatureStore`
[🔗](https://github.com/nshkrdotcom/slither/blob/v0.1.0/lib/slither/examples/ml_scoring/feature_store.ex#L1)

Write-through feature cache for the ML scoring pipeline example.

Provides a single `:set` ETS table with both read and write concurrency
enabled. The table starts empty and is populated during pipeline execution
as records are featurized. Subsequent runs can hit the cache to skip the
Python featurization stage for already-seen records.

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*Consult [api-reference.md](api-reference.md) for complete listing*