Thank you for your interest in contributing to PredictionIO. Our mission is to enable developers to build scalable machine learning applications easily. Here is how you can help with the project development. If you have questions at anytime, please free to post on the Developer Fourm or email us at [email protected].
Areas in Need of Help
We accept contributions of all kinds at any time. We are compiling this list to show features that are highly sought after by the community.
- Tests and CI
- Engine template, tutorials, and samples
- Client SDKs
- Building engines in Java (updating the Java controller API)
- Code clean up and refactoring
- Code and data pipeline optimization
- Developer experience (UX) improvement
How to Report an Issue
If you wish to report an issue you found, you can do so on GitHub Issues.
How to Help Resolve Existing Issues
In general, bug fixes should be done the same way as new features, but critical bug fixes will follow a different path.
Critical Bug Fixes Only
- File an issue against the issue tracker if there isn't one already.
- Create a new hotfix branch described by the git flow methodology, and write the fix in that branch.
- Verify the patch and issue a pull request to the main repository.
- Once merged to the main repository, critical bug fixes will be merged to the "master" branch and new binary will be built and distributed.
How to Add / Propose a New Feature
- To propose a new feature, simply post your proposal to PredictionIO Development Google Group or email us directly at [email protected].
- Discuss with the community and the core development team on what needs to be done, and lay down concrete plans on deliverables.
- Once solid plans are made, start creating tickets on GitHub Issues.
- Work side by side with other developers using PredictionIO Development Google Group as primary mode of communication. You never know if someone else has a better idea. ;)
How to Issue a Pull Request
When you have finished your code, you can create a pull request against the develop branch. You also need to complete the Contributor Agreement. We cannot accept your PR without the agreement.
- Make sure the title and description are clear and concise. For more details on writing a good commit message, check out this guide.
- If the change is visual, make sure to include a screenshot or GIF.
- If the PR closes an issue, make sure to put Closes #X at the end of the description on a new line.
- Make sure it is being opened into the right branch.
- Make sure it has been rebased on top of that branch.
Getting Started
PredictionIO relies heavily on the git flow methodology. Please make sure you read and understand it before you start your development. By default, cloning PredictionIO will put you in the develop branch, which in most cases is where all the latest development go to.
Create a Clone of PredictionIO’s Repository
- Start by creating a GitHub account if you do not already have one.
- Go to PredictionIO’s repository and fork it to your own account.
- Clone your fork to your local machine.
If you need additional help, please refer to https://help.github.com/articles/fork-a-repo/.
Building PredictionIO from Source
After the previous section, you should have a copy of PredictionIO in your local machine ready to be built.
- Make sure you are on the develop branch. You can double check by
git status
or simplygit checkout develop
. - At the root of the repository, do
./make-distribution.sh
to build PredictionIO.
Setting Up the Environment
PredictionIO relies on 3rd party software to perform its tasks. To set them up, simply follow this documentation.
Start Hacking
You should have a PredictionIO development environment by now. Happy hacking!
Anatomy of PredictionIO’s Code Tree
The following describes each directory’s purpose.
bin
Shell scripts and any relevant components to go into the binary distribution. Utility shell scripts can also be included here.
conf
Configuration files that are used by both a source tree and binary distribution.
core
Core PredictionIO code that provides the DASE controller API, core data structures, and workflow creation and management code.
data
PredictionIO Event Server, and backend-agnostic storage layer for event store and metadata store.
docs
Source code for docs.prediction.io site, and any other documentation support files.
engines
Obsolete built-in engines. To be removed.
examples
Complete code examples showing PredictionIO’s application.
sbt
Embedded SBT (Simple Build Tool) launcher.
templates
Starting point of building your custom engine.
tools
Tools for running PredictionIO. Contains primarily the CLI (command-line interface) and its supporting code, and the experimental evaluation dashboard.