Back

7 Jul, 2022 | Community

Your guide to contributing to the Quix library

When, why, and how to contribute code samples to the Quix library.

Steve Rosam
Words by
Steve Rosam, Full-stack developer
Blog 173 feature

Making your life easier, one code sample at a time

The Quix library is all about creating integrations and shortcuts for those building with streaming data. The library contains code samples, which we call connectors, which cut down on development time while remaining customizable.

The library includes three types of connectors:

  • Source connectors enable you to bring data to your pipeline.
  • Transformation connectors let you adapt data. Extract and load, merge, synchronize, enrich, predict or anything else you might want to do with your data — the options are endless.
  • Destination connectors deliver transformed data to analytics dashboards, alerts, data warehouses or any other data application.

You can access the library within the Quix platform or GitHub to use prepared connectors, but you’ll build them in GitHub. Detailed instructions are included below and on GitHub. Contributors are very welcome at Quix!

How to add a new source, transformation or destination connector

  1. Create a fork of the quix-library
  2. Add a folder to the directory that best suits your project (e.g., Python>Sources>New Folder)
  3. Add your source code to the folder
  4. Complete a library.json with the relevant details for your project. When you do, ensure that you:
    1. follow the guidelines in the Empty folder for each directory
    2. include a thorough README.md that follows the template
    3. include a library.json that follows the template
  5. Submit a PR for approval, and we’ll get in touch!

That’s it — as simple as five steps. If you get stuck along the way, we’re happy to help. Visit The Stream Slack channel #quix-library and leave your questions. Someone will be there as soon as possible to offer a hand.

How to add a new application

Applications store all the code to run an end-to-end app. They are made up of multiple projects.

  1. Create a fork of the quix-library
  2. Add a folder to the Applications directory and name it something short and obvious like “chat app with real-time sentiment scoring”
  3. Add your source code to the folder:
    1. Create a sub-folder for each component project of your application, i.e., one for the chat app frontend and one for the real-time machine learning model on the backend
    2. Ensure you follow the guidelines in the Empty folder for each directory, include a library.json with the relevant details and include a thorough README.md that follows the template
  4. Submit a PR for approval, and we’ll be in touch!

How to modify a project

Follow the same pattern used when adding a new application to modify a project.

  1. Create a fork of the quix-library
  2. Modify your files
  3. Check the readme.md and library.json files
  4. Submit a PR for approval, and we’ll be in touch!

Configuring library.json

Library.json contains the metadata for the search and set-up features in the Library, which provides a smooth developer experience in the Quix portal.Both features increase the reusability of your code and helps other people use it more easily.

  • Create a GUID using an online generator like Free Online GUID Generator
  • “libraryItemId”: A unique identifier for your project.
  • “name”: The display name for your project. Keep it short (<30 chars) and try to make it unique.
  • “language”: The projects language (Python, C#, NodeJs, Shell Script, Javascript etc)
  • “tags”: Additional search filters that show-up in the library. Pick two or three of the most important tags like “Complexity,” “SDK Usage” and “Pipeline State.” See Quix Library for a current list of tags. Add new tags with discretion — they may not be accepted.
  • “shortDescription”: A unique description of your project. Keep it less than 80 characters.
  • “DefaultFile”: Defines the default file to show when loading the project in a Code Explorer and is the default file displayed in the code preview in the Quix Library.
  • “EntryPoint”: The build and deploy entry point (commonly a Dockerfile).
  • “RunEntryPoint”: The Run entry point (main code file to run).
  • “Variables”: Defines the external variables of the project. Variables are used to configure the project during setup in the Quix Library or programmatically from your application. Each variable will create a unique setup field in the Quix Library.
  • “Name”: The display name for your variable
  • “Type”: The type of variable. Use Environ
  • “InputType”:
    • “HiddenText” for tokens and credentials
    • “FreeText” for anything else
    • “InputTopic” for consuming data from topics. Multiple topics permitted.
    • “OutputTopic” for producing data to topics. Multiple topics permitted.
  • “Description”: The public description of the variable
  • “Required”: Boolean value
  • “DefaultValue”: A default value for the variable
  • “SampleTemplate”: Defines whether the project is a Sample Template without ability to Save as Project or Explore the files (used for HTTP samples or similar templates using Placeholders)
  • “IconFile”: Defines an icon file to show in the project card. Optional. Only required for recognised logos and technologies.
    • Required shape: square
    • Recommended format: .png
    • Recommended size: 48×48 pixels
  • “DeploySettings”: Defines the Instant Deploy settings for the project. Optional. If you configure these properties, the project will have the “Setup & Deploy” button enabled in the Quix library. This provides users with the option to deploy the project without cloning it to their own repo. It’s particularly useful for connectors (source and destinations) and applications that don’t require customization. If the settings are null, a Docker Image for this project will not be generated and the Deploy actions will not be available in the UI.
    • “DeploymentType”: Type of deployment. Can be a Service or a Job.
    • “CpuMillicores”: Maximum CPU millicores reserved for this deployment instance. 1 millicore = 1/1000th core
    • “MemoryInMb”: Maximum memory reserved for this deployment instance. 1mb = 1/1000th GB
    • “Replicas”: Number of duplicate instances of the deployment. Used for horizontal scale. Each instance will reserve the max CPU & Memory allocations.
    • “PublicAccess”: Whether the service has a publicly accessible url.
    • “UrlPrefix”: Prefix of the public url.
    • “ValidateConnection”: Whether the Deployment process should validate the connection of the project. Specific logic is needed in the code of the project to allow the UI to validate the connection.

We’re here to help

The Quix team can’t wait to answer your questions and help you figure out how to create helpful connectors.

share

Join The Stream community, where you’ll find developers, engineers and scientists supporting each other while working on streaming projects.

Join us
Steve Rosam
words by
Steve Rosam, Full-stack developer

Steve Rosam is a Full-stack developer at Quix, where he creates and maintains solutions both in-house and for customers. Steve has worked as a software developer for two decades, previously in a variety of industries including automotive, finance, media and security.

Previous Post Next Post

Related content

View all
Quix streams blog feature image
Community | 2 Mar, 2023
Introducing Quix Streams, an open source library for telemetry data streaming
Lightweight, powerful, no JVM and no need for separate clusters of orchestrators. Here’s a look at our next-gen streaming library for C# and Python developers including feature summaries, code samples, and a sneak peek into our roadmap.
Tomas Neubauer
words by
Tomáš Neubauer, CTO & Co-Founder
The Stream February 2023
Community | 28 Feb, 2023
The Stream — February 2023 edition
Build a simple event-driven system to get ML predictions with Python and Apache Kafka
1611064394032
words by
Mike Rosam, CEO & Co-Founder
The Stream January 2023
Community | 25 Jan, 2023
The Stream — January 2023 edition
How can you send time-series data to Apache Kafka using Python and Pandas? Plus Apache Flink news, memes, and meetups
1611064394032
words by
Mike Rosam, CEO & Co-Founder

The Stream

Updates to your inbox

Get the data stream processing community's newsletter. It's for sharing insights, events and community-driven projects.

Background image