AutoHolidays is an intelligent, algorithm-driven Python package designed to optimize leave planning by identifying the
most strategic days to take time off from professional commitments. By analyzing entitled leave balances, weekly offs, public
holidays, and fully customizable constraints, it computes optimal combinations that maximize continuous break periods
while minimizing leave usage. Built for both individuals and teams, the module supports coordinated planning without
disrupting operational continuity. Its flexible architecture adapts seamlessly to diverse organizational policies and regional
calendars, making it suitable for personal productivity enthusiasts as well as enterprise environments.
This project is licensed under the MIT License. Permission is granted to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the software. The software is provided “as is”, without warranty of any kind, express or implied. See the LICENSE file for full details.
This application is developed with the intention of providing useful functionality and a safe user experience. It is not designed to cause harm, misuse data, or negatively impact users, devices, or systems. However, all software carries inherent risks depending on how it is installed, configured, and used. Users are solely responsible for ensuring that the application is used appropriately and in accordance with applicable laws, regulations, and best practices. It is strongly recommended that users take necessary precautions, including maintaining updated security software, safeguarding sensitive information, and regularly backing up data. The developers assume no liability for any direct, indirect, incidental, or consequential damages arising from the use or misuse of this application and shall not be held responsible or subject to claims beyond these stated terms. If you do not agree to follow these guidelines and take the necessary precautions, you should not use this application.
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. A detailed overview on how to contribute can be found in the contributing guidelines.
As contributors and maintainers to this project, you are expected to abide by PyUtility's code of conduct. More information can be found at: Contributor Code of Conduct.