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Development guide

Table of Contents

Overview

This guide is targeted at developers looking to contribute to Feast components in the main Feast repository:

Compatibility

Community

A quick few highlights:

    • Includes biweekly community calls at 10AM PST

Making a pull request

We use the convention that the assignee of a PR is the person with the next action.

If the assignee is empty it means that no reviewer has been found yet. If a reviewer has been found, they should also be the assigned the PR. Finally, if there are comments to be addressed, the PR author should be the one assigned the PR.

Pull request checklist

A quick list of things to keep in mind as you're making changes:

  • As you make changes

  • When you make the PR

    • Make a pull request from the forked repo you made

    • Ensure the title of the PR matches semantic release conventions (e.g. start with feat: or fix: or ci: or chore: or docs:). Keep in mind that any PR with feat: or fix: will directly make it into the change log of a release, so make sure they are understandable!

    • Ensure you add a GitHub label (i.e. a kind tag to the PR (e.g. kind/bug or kind/housekeeping)) or else checks will fail.

    • Ensure you leave a release note for any user facing changes in the PR. There is a field automatically generated in the PR request. You can write NONE in that field if there are no user facing changes.

    • Try to keep PRs smaller. This makes them easier to review.

Good practices to keep in mind

  • Fill in the description based on the default template configured when you first open the PR

    • What this PR does/why we need it

    • Which issue(s) this PR fixes

    • Does this PR introduce a user-facing change

  • Add WIP: to PR name if more work needs to be done prior to review

Forking the repo

Fork the Feast Github repo and clone your fork locally. Then make changes to a local branch to the fork.

Pre-commit Hooks

  1. Ensure that you have Python (3.7 and above) with pip, installed.

  2. Install pre-commit with pip & install pre-push hooks

pip install pre-commit
pre-commit install --hook-type pre-commit --hook-type pre-push

  1. On push, the pre-commit hook will run. This runs make format and make lint.

Signing off commits

Use git signoffs to sign your commits. See https://docs.github.com/en/github/authenticating-to-github/managing-commit-signature-verification for details

Then, you can sign off commits with the -s flag:

git commit -s -m "My first commit"

GPG-signing commits with -S is optional.

Incorporating upstream changes from master

Our preference is the use of git rebase [master] instead of git merge : git pull -r.

Note that this means if you are midway through working through a PR and rebase, you'll have to force push: git push --force-with-lease origin [branch name]

Feast Python SDK / CLI

Environment Setup

Setting up your development environment for Feast Python SDK / CLI:

  1. Ensure that you have Docker installed in your environment. Docker is used to provision service dependencies during testing, and build images for feature servers and other components.

  2. Ensure that you have make, Python (3.8 and above) with pip, installed.

  3. Recommended: Create a virtual environment to isolate development dependencies to be installed

  1. Upgrade pip if outdated

  1. (Optional): Install Node & Yarn. Then run the following to build Feast UI artifacts for use in feast ui

  1. Install development dependencies for Feast Python SDK / CLI

This will allow the installed feast version to automatically reflect changes to your local development version of Feast without needing to reinstall everytime you make code changes.

Code Style & Linting

Feast Python SDK / CLI codebase:

  • Has type annotations as enforced by mypy

  • Has imports sorted by isort

  • Is lintable by flake8

To ensure your Python code conforms to Feast Python code standards:

  • Autoformat your code to conform to the code style:

  • Lint your Python code before submitting it for review:

Unit Tests

Unit tests (pytest) for the Feast Python SDK / CLI can run as follows:

  • Ensure Feast Python SDK / CLI is not configured with configuration overrides (ie ~/.feast/config should be empty).

Integration Tests

There are two sets of tests you can run:

  1. Local integration tests (for faster development, tests file offline store & key online stores)

  2. Full integration tests (requires cloud environment setups)

Local integration tests

It leverages a file based offline store to test against emulated versions of Datastore, DynamoDB, and Redis, using ephemeral containers.

These tests create new temporary tables / datasets locally only, and they are cleaned up. when the containers are torn down.

(Advanced) Full integration tests

To test across clouds, on top of setting up Redis, you also need GCP / AWS / Snowflake setup.

GCP

  2. You will need to setup a service account, enable the BigQuery API, and create a staging location for a bucket.

    • Remember to save your PROJECT_ID and your key.json. These will be your secrets that you will need to configure in Github actions. Namely, secrets.GCP_PROJECT_ID and secrets.GCP_SA_KEY. The GCP_SA_KEY value is the contents of your key.json file.

    • Make sure to add the service account email that you created in the previous step to the users that can access your bucket. Then, make sure to give the account the correct access roles, namely objectCreator, objectViewer, objectAdmin, and admin, so that your tests can use the bucket.

  2. Login to gcloud if you haven't already:

  • When you run gcloud auth application-default login, you should see some output of the form:

  • You should run export GOOGLE_APPLICATION_CREDENTIALS="$HOME/.config/gcloud/application_default_credentials.json” to add the application credentials to your .zshrc or .bashrc.

  1. Run export GCLOUD_PROJECT=[your project id from step 2] to your .zshrc or .bashrc.

  2. Running gcloud config list should give you something like this:

  1. Export GCP specific environment variables in your workflow. Namely,

NOTE: Your GCS_STAGING_LOCATION should be in the form gs://<bucket name> where the bucket name is from step 2.

  1. Once authenticated, you should be able to run the integration tests for BigQuery without any failures.

AWS

  1. Setup AWS by creating an account, database, and cluster. You will need to enable Redshift and Dynamo.

  1. To run the AWS Redshift and Dynamo integration tests you will have to export your own AWS credentials. Namely,

Snowflake

  1. See https://signup.snowflake.com/ to setup a trial.

  2. Setup your account and if you are not an ACCOUNTADMIN (if you created your own account, you should be), give yourself the SYSADMIN role.

  • Your account name can be found under

  1. Create Dashboard and add a Tile.

  2. Create a warehouse and database named FEAST with the schemas OFFLINE and ONLINE.

  2. Then to run successfully, you'll need some environment variables setup:

  1. Once everything is setup, running snowflake integration tests should pass without failures.

Note that for Snowflake / GCP / AWS, running make test-python-integration will create new temporary tables / datasets in your cloud storage tables.

(Advanced) Running specific provider tests or running your test against specific online or offline stores

  1. If you don't need to have your test run against all of the providers(gcp, aws, and snowflake) or don't need to run against all of the online stores, you can tag your test with specific providers or stores that you need(@pytest.mark.universal_online_stores or @pytest.mark.universal_online_stores with the only parameter). The only parameter selects specific offline providers and online stores that your test will test against. Example:

  1. You can also filter tests to run by using pytest's cli filtering. Instead of using the make commands to test Feast, you can filter tests by name with the -k parameter. The parametrized integration tests are all uniquely identified by their provider and online store so the -k option can select only the tests that you need to run. For example, to run only Redshift related tests, you can use the following command:

(Experimental) Run full integration tests against containerized services

Test across clouds requires existing accounts on GCP / AWS / Snowflake, and may incur costs when using these services.

It's possible to run some integration tests against emulated local versions of these services, using ephemeral containers. These tests create new temporary tables / datasets locally only, and they are cleaned up. when the containers are torn down.

The services with containerized replacements currently implemented are:

  • Datastore

  • DynamoDB

  • Redis

  • Trino

  • HBase

  • Postgres

  • Cassandra

You can run make test-python-integration-container to run tests against the containerized versions of dependencies.

Contrib integration tests

(Contrib) Running tests for Spark offline store

You can run make test-python-universal-spark to run all tests against the Spark offline store. (Note: you'll have to run pip install -e ".[dev]" first).

Not all tests are passing yet

(Contrib) Running tests for Trino offline store

You can run make test-python-universal-trino to run all tests against the Trino offline store. (Note: you'll have to run pip install -e ".[dev]" first)

(Contrib) Running tests for Postgres offline store

You can run test-python-universal-postgres-offline to run all tests against the Postgres offline store. (Note: you'll have to run pip install -e ".[dev]" first)

(Contrib) Running tests for Postgres online store

You can run test-python-universal-postgres-online to run all tests against the Postgres offline store. (Note: you'll have to run pip install -e ".[dev]" first)

(Contrib) Running tests for HBase online store

TODO

(Experimental) Feast UI

Feast Java Serving

Developing the Feast Helm charts

There are 3 helm charts:

  • Feast Java feature server

  • Feast Python / Go feature server

  • (deprecated) Feast Python feature server

Generally, you can override the images in the helm charts with locally built Docker images, and install the local helm chart.

Feast Java Feature Server Helm Chart

It will:

  • run make build-java-docker-dev to build local Java feature server binaries

  • configure the included application-override.yaml to override the image tag to use the locally built dev images.

  • install the local chart with helm install feast-release ../../../infra/charts/feast --values application-override.yaml

Feast Python / Go Feature Server Helm Chart

It will:

  • run make build-feature-server-dev to build a local python feature server binary

  • install the local chart with helm install feast-release ../../../infra/charts/feast-feature-server --set image.tag=dev --set feature_store_yaml_base64=$(base64 feature_store.yaml)

Feast Go Client

Go Environment Setup

Setting up your development environment for Feast Go SDK:

Building Go

Build the Feast Go Client with the go toolchain:

Go Code Style & Linting

Feast Go Client codebase:

  • Conforms to the code style enforced by go fmt.

  • Is lintable by go vet.

Autoformat your Go code to satisfy the Code Style standard:

Lint your Go code:

Go Unit Tests

Unit tests for the Feast Go Client can be run as follows:

Testing with Github Actions workflows

Feast Data Storage Format

Feast data storage contracts are documented in the following locations: