# Feast

> Feast — open-source feature store. Online and offline serving, point-in-time joins, feature validation, and streaming ingestion. Standardizes feature management across training and production.

- Skill: `mkurman/feast` (Agent Skill)
- Install (CLI): `npx skillmds@latest add mkurman/feast`
- Raw SKILL.md: https://api.skillmd.com/api/skills/mkurman/feast/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: mkurman (https://skillmd.com/u/mkurman)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/mkurman/feast

---

## Overview

Feast is an open-source feature store for production ML, providing offline (batch training data via SQL queries) and online (low-latency serving via Redis, Firestore, or DynamoDB) feature retrieval with point-in-time correctness. Features are versioned, validated, and governed through a registry.

## Installation

```bash
uv pip install feast
```

## Feature Definition

```python
from feast import Entity, FeatureView, FileSource, ValueType
from datetime import timedelta

driver = Entity(name="driver_id", value_type=ValueType.INT64, description="Driver identifier")
source = FileSource(path="data/driver_stats.parquet", timestamp_field="event_timestamp")
feature_view = FeatureView(
    name="driver_hourly_stats",
    entities=[driver],
    ttl=timedelta(hours=2),
    source=source,
)
```

## Serve

```bash
feast apply   # register in registry
feast serve   # online serving at localhost:6566
```

## References
- [Feast docs](https://docs.feast.dev/)
- [Feast GitHub](https://github.com/feast-dev/feast)