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  • Introduction
  • Community
  • Roadmap
  • Changelog
  • Getting started
    • Quickstart
    • Concepts
      • Overview
      • Data source
      • Dataset
      • Entity
      • Feature view
      • Stream feature view
      • Feature retrieval
      • Point-in-time joins
      • Registry
    • Architecture
      • Overview
      • Feature repository
      • Registry
      • Offline store
      • Online store
      • Provider
    • Learning by example
    • Third party integrations
    • FAQ
  • Tutorials
    • Overview
    • Driver ranking
    • Fraud detection on GCP
    • Real-time credit scoring on AWS
    • Driver stats on Snowflake
    • Validating historical features with Great Expectations
    • Using Scalable Registry
    • Building streaming features
  • How-to Guides
    • Running Feast with Snowflake/GCP/AWS
      • Install Feast
      • Create a feature repository
      • Deploy a feature store
      • Build a training dataset
      • Load data into the online store
      • Read features from the online store
    • Running Feast in production
    • Deploying a Java feature server on Kubernetes
    • Upgrading from Feast 0.9
    • Adding a custom provider
    • Adding a new online store
    • Adding a new offline store
    • Adding or reusing tests
  • Reference
    • Codebase Structure
    • Data sources
      • File
      • Snowflake
      • BigQuery
      • Redshift
      • Push
      • Kafka
      • Kinesis
      • Spark (contrib)
      • PostgreSQL (contrib)
    • Offline stores
      • File
      • Snowflake
      • BigQuery
      • Redshift
      • Spark (contrib)
      • PostgreSQL (contrib)
    • Online stores
      • SQLite
      • Redis
      • Datastore
      • DynamoDB
      • PostgreSQL (contrib)
    • Providers
      • Local
      • Google Cloud Platform
      • Amazon Web Services
    • Feature repository
      • feature_store.yaml
      • .feastignore
    • Feature servers
      • Python feature server
      • Go-based feature retrieval
    • [Alpha] Web UI
    • [Alpha] Data quality monitoring
    • [Alpha] On demand feature view
    • [Alpha] AWS Lambda feature server
    • Feast CLI reference
    • Python API reference
    • Usage
  • Project
    • Contribution process
    • Development guide
    • Versioning policy
    • Release process
    • Feast 0.9 vs Feast 0.10+
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  1. Project

Contribution process

PreviousUsageNextDevelopment guide

Last updated 2 years ago

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We use and to communicate development ideas. The simplest way to contribute to Feast is to leave comments in our in the or our GitHub issues. You will need to join our in order to get access.

We follow a process of . If you believe you know what the project needs then just start development. If you are unsure about which direction to take with development then please communicate your ideas through a GitHub issue or through our before starting development.

Please to the master branch of the Feast repository once you are ready to submit your contribution. Code submission to Feast (including submission from project maintainers) require review and approval from maintainers or code owners.

PRs that are submitted by the general public need to be identified as ok-to-test. Once enabled, will run a range of tests to verify the submission, after which community members will help to review the pull request.

See also for other ways to get involved with the community (e.g. joining community calls)

RFCs
GitHub issues
RFCs
Feast Google Drive
Google Group
lazy consensus
Slack Channel
submit a PR
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Community