vivid-2024 0.1.1

A comprehensive platform for HR professionals.

VIVID

What is Vivid?

Vivid is an open-source platform offering a suite of intelligent tools designed to support HR professionals in HR transformation, talent management, and total rewards. It's completely free and open-source, ensuring accessibility for everyone!

CAUTION

Vivid is in the early development stages. Some features may be incomplete or evolving. Our documentation is a work in progress. New versions, which may include breaking changes, are released periodically. We provide migration guides, but transitions might require some effort. Proceed if you are comfortable with this environment.

Design Goals

• Comprehensive: Provide a complete toolset for HR transformation, talent management, and total rewards.
• User-Friendly: Accessible for HR professionals, yet flexible for advanced users.
• Data-Driven: Utilize data to offer insightful analytics and recommendations.
• Modular: Use only the components you need and customize them to suit your needs.
• Efficient: Optimize processes to save time and resources.
• Collaborative: Encourage community contributions and shared improvements.

About

Vivid aims to empower the HR community with a reliable and intelligent platform for HR transformation, talent management, and total rewards. Stay tuned for more updates and features as we grow.

Docs

We are actively developing our documentation. Currently, you can find:

• Quick Start Guide: The official guide to getting started with Vivid.
• API Docs: Automatically generated documentation for Vivid's API.

More documentation, examples, and tutorials will be added as the project evolves.

Community

We are building a community of HR professionals and developers interested in contributing to Vivid. Join us and stay connected:

• GitHub Discussions: Ask questions and find answers about Vivid.

Future plans include:

• Discord: An official server for real-time discussions and support.
• Reddit: An official subreddit for broader discussions.
• Vivid Assets: A collection of related projects, tools, plugins, and educational materials.

Contributing

Interested in contributing to Vivid? Check out our Contributor's Guide. For simpler issues, feel free to open an issue or PR and address it yourself!

For more complex architectural decisions or experimental features, please open an RFC (Request For Comments) so we can brainstorm together.

License

Vivid is free, open-source, and permissively licensed! Except where noted (below and/or in individual files), all code in this repository is dual-licensed under either:

• MIT License (http://opensource.org/licenses/MIT)
• Apache License, Version 2.0 (http://www.apache.org/licenses/LICENSE-2.0)

at your discretion. This dual-licensing model is standard and beneficial.

Some parts of the platform's code come with additional copyright notices and license terms due to their external origins. These are generally BSD-like, but details vary by package. Contributions to those packages must adhere to those terms. The license field of each package will also reflect this.

Assets included in this repository (for examples) typically have different open licenses. These are not included in your projects unless copied by you, and are not distributed in the published Vivid packages. See CREDITS.md for license details of those files.

Your Contributions

Unless stated otherwise, any contribution intentionally submitted for inclusion in the project by you, as defined in the Apache-2.0 license, shall be dual-licensed as above, without additional terms or conditions.

Vivid Examples

We are diligently working on developing comprehensive examples to demonstrate the capabilities of the Vivid platform. These examples will provide detailed insights into performing various analyses, showcasing the platform's extensive functionality and offering a stable starting point for users.

Example in Progress

Given the complexity and scope of the Vivid platform, creating meaningful examples requires careful planning and thorough development. We are currently preparing foundational examples, which will include a Python script that initializes Vivid and runs a default analysis.

We appreciate your patience and understanding as we strive to deliver high-quality resources. Stay tuned for updates and new examples as we continue to build and enhance the platform.

Prerequisites

Ensure you have the vivid package installed. You can install it using pip:

pip install vivid