Proposal: Contribute a new feature and raise a PR for Qlib
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 48.7k
- Forks
- 7.7k
- PR merge metrics
- No merged PRs in 30d
Description
🌟 Feature Description
This issue proposes to contribute a new feature to the Qlib project and subsequently open a pull request for the contribution. The detailed nature of the contribution can be discussed and scoped with the maintainers.
Motivation
- Application scenario: Enhance Qlib's capabilities and encourage open-source contributions.
- Related works (Papers, Github repos etc.): Will reference relevant works based on the feature discussed.
- Any other relevant and important information: Aims to follow project guidelines and best practices for open-source contributions.
Alternatives
Alternatives may include suggesting improvements to existing features or modules, or contributing documentation or bug fixes instead of a new feature.
Additional Notes
Looking forward to feedback from the maintainers on where contributions are most needed, and the process for raising a pull request after receiving initial feedback.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No specific feature, file, test, or entry point is identified in the issue. Start by reviewing Qlib's contribution guidelines and asking maintainers to define a concrete scope and relevant module. Done means an agreed feature is implemented and a pull request is opened.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- fintech-quant, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100