# API Components
source: https://docs.chalk.ai/docs/api-components

## The building blocks of Chalk.

Chalk's feature pipeline helps you define the features you need and compute their values.
The following concepts are the foundation of our implementation:

- Features - Chalk lets you spell out your feature
values using Python classes. Feature classes are namespaced, and can have
relationships to other feature namespaces.
- Resolvers - Resolvers compute the values
of your features from other feature values. Feature resolvers are defined
online and offline for inference and training,
and support ETL between online and offline.
- Online Inference - In production, you can query
your features through one of Chalk's API clients. At query time, you can choose
to override any feature caching.
- Training - Chalk supports querying your
offline features directly from a Python notebook.