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(WIP) OCaml library for schedule, time, and time slots handling

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Daypack-lib

Daypack-lib is a schedule, time and time slots handling library

Note: Daypack is still WIP

The core scheduling and progress tracking functionalities are largely finished, but facilities for usage of library in frontend, and the frontend itself are still underway

Demos

Daypc (cli frontend)

TODO

Daypack_lib (core library)

See here TODO

Features

Overview

Details

  • Automatic scheduling

    • See below for strategies supported in scheduling requests
  • Manual scheduling

  • Recurrence

    • All automatic scheduling strategies are available for recurring tasks as well
  • Time pattern (more for devs)

    • Functionally very similar to cron time expression, but strictly less general than cron expression

    • This is mainly used as a query for the time slot searching functions in Time_pattern

  • Time expression

    • A natural to use language with formal grammar for specifying time point and time slots

    • Can be seen as a more expressive layer over Time_pattern

  • Duration expression

    • A natural to use language with formal grammar for specifying duration of time
  • Time profiles

    • Specification of scheduling requests is supplemented by time profiles, which are aliases for time periods (a pair of time patterns indicating start and end time of time slots)

    • Some downloadable prebuilt profiles are

      • work_hours: Monday to Friday 9am to 5pm

      • sleep_hours: Everyday 11pm to 12am, 12am to 6am

    • Time profiles are JSON files designed to be easily created/customised/extended by users, and Daypack processes all profiles provided in the profile directory (see user manual)

    • Time profile builder sites are being planned right now (similar to keyboard or mouse macro/profile building sites)

    • See user manual for details

  • Backup plan

    • You can specify multiple scheduling strategies for a given scheduling request, and Daypack will try them sequentially until one works
  • Progress tracking

    • You can mark task items as "completed" (or "uncompleted")

    • You can record time periods spent for task items

  • Schedule versioning and rollback

    • "Snapshots" are made before certain major operations such as scheduling, user can also initiate a snapshot manually

    • This allows rollbacks/undos should the user find the schedule resulted from an operation unsatisfactory

  • (WIP) Multiple users (supported by library, but frontend adoption is WIP)

  • (WIP) Taking transit time into account during scheduling

    • This feature is unlikely to land any time soon
  • Daypack_lib is offline (more for devs)

    • Daypack_lib contains implementation of all functionalities, and has zero dependency on any online service

    • This is not novel/unexpected or necessarily desirable, and is listed more for clarity's sake, as some similar software make use of online services

Constraints (or scheduling strategies) supported

Details

Note: The following lists all the constraints supported by the core library, but frontends may not expose them completely

  • Fixed

    • Manual scheduling, specifies a task segment starts at a fixed time point

    • E.g. "Meeting starts at 2pm and last for 1.5 hours"

  • Shift

    • Daypack shifts the task segment(s) around and tries to find a spot

    • E.g. "Homework takes 2 hours, schedule it for me between 9am-5pm of next 3 days"

  • Split_and_shift

    • Daypack splits task segment into smaller segments then shifts them around and tries to find a spot, takes following parameters

      • minimum size

      • maximum size (optional)

      • increment

      • split count (either maximum or exact)

    • E.g. "This work takes 5 hours, I need it done by the end of this week, split and shift for me across 5pm-10pm of said days, but all split segments must be at least 1 hour long"

  • Split_even

    • Daypack splits a task segment into evenly sized smaller segments across some specified buckets/boundaries with shifting

      • If some buckets are not usable, then Daypack tries to split across remaining buckets with larger even splits
    • E.g. "I want to exercise 5 hours, split it evenly across next 7 days, boundaries being 1pm-5pm of each day"

      • If one day ends up being too full to be used, then Daypack splits across 6 days instead, and so on
  • Time_share

    • Interleave multiple task segments with some specified interval size

    • E.g. "Interleave task A, B, C across 1pm-4:30pm with interval size of 30 mins" produces the following agenda

      • Time slots Task
        1:00pm-1:30pm Task A
        1:30pm-2:00pm Task B
        2:00pm-2:30pm Task C
        2:30pm-3:00pm Task A
        3:00pm-3:30pm Task B
        3:30pm-4:00pm Task C
        4:00pm-4:30pm Task A
  • Push_toward

    • Similar to shifting, but tries positions closest to a specified time first

    • E.g. "I need this done, which takes 15mins, it needs to be done between 4pm-10pm, but I want it as close to 6pm as possible"

Architecture and limitations

Details

Daypack does not aim to be a general solver, and only supports a limited set of constraints (which are listed above)

Furthermore, Daypack only uses a backtracking search procedure with pruning (implemented using lazy sequences) for solving the constraints, and does not use any advanced or potentially more efficient constraint solving techniques

It is subsequently inferior to a lot of other automatic task scheduling software, and cannot accomodate very complex scheduling scenarios

Nevertheless, we hope that the supported constraints are powerful enough for a simple and standalone personal task scheduler

More detailed docs on the way

Some of the features that Daypack does NOT support

  • Resource allocation

    • Doesn't seem to be a useful item for personal TODO list

Getting started

Installation

TODO

User guide

See here TODO for daypc user guide

See here TODO for daypack_lib library documentation

Contributions

Ideas

Got a feature request? Feel free to open an issue to start a discussion.

Please note that since Daypack was never designed to be a general solver, there are things prohibitively expensive to properly implement as a result (short of adding a general solver into Daypack), which we may cite as a reason should we reject your feature request

We ask for your understanding should that be the case

Code

Code contributions are welcome. Please note that by submitting your original work, you agree to license your work under the MIT license.

Acknowledgements

  • Cli frontend is heavily inspired by Taskwarrior, which one of the authors heavily used

  • We became aware of Eva later on as well, and took inspiration from its UI/UX design choices and feature set

    • The underlying architecture was independently designed and developed however
  • Many thanks to Gabriel 'Drup' Radanne for his review and suggestions on the design and implementation of time expression, and also other parts of the library

LICENSE

MIT