Demo Notebooks

Feast can generate tailored Jupyter notebooks for any Feast project. The notebooks adapt to your feature_store.yaml configuration and provide a hands-on walkthrough of core Feast functionality.

What you get

For each project discovered, Feast creates a directory with notebooks covering:

Notebook
Description

01 — Feature Store Overview

Explore registered entities, feature views, feature services, and data sources.

02 — Historical Feature Retrieval

Build a training dataset with point-in-time correct joins using get_historical_features.

03 — Online Feature Serving

Materialize features to the online store and retrieve them at low latency with get_online_features.

The content adapts automatically based on:

  • Online / offline store types — descriptions reflect the actual backends configured.

  • Registry type — local registries include feast apply; remote registries use refresh_registry().

  • Authentication — auth details from feature_store.yaml are surfaced when configured.

  • Vector search — a vector/RAG retrieval section is included when embeddings are detected.

Prerequisites

  • Python 3.9+

  • Feast installed (pip install feast)

  • A feature repository with a valid feature_store.yaml

Using the CLI

Run the command from (or pointing to) a directory containing feature_store.yaml:

This searches for feature_store.yaml in the current directory and every file inside the feast-config/ directory. Each file in feast-config/ is treated as a separate project config. For each project found, notebooks are written to ./feast-demo-notebooks/<project>/.

Options

Option
Default
Description

-o, --output-dir

./feast-demo-notebooks

Root directory for generated notebooks

--overwrite

false

Overwrite if the output directory already exists

Using the Python SDK

Parameters

Parameter
Type
Default
Description

output_dir

str

"./feast-demo-notebooks"

Root directory for generated notebooks

repo_path

str

"."

Directory to search for feature_store.yaml files

overwrite

bool

False

Overwrite existing output directories

Examples

Multi-project repositories

If your feast-config/ directory contains multiple files, each is treated as a separate project and a dedicated notebook directory is created:

Running the notebooks

Open any generated notebook in Jupyter, JupyterLab, or VS Code and run cells from top to bottom. Each notebook:

  1. Configures the path to your feature_store.yaml automatically (no manual editing needed).

  2. Connects to the feature store using the Feast Python SDK.

  3. Walks through relevant operations with real data from your project.

The first notebook (01 — Overview) includes a prerequisites check and feast apply / registry sync step. Subsequent notebooks assume these have already been completed.

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