package daypack-lib
Install
Dune Dependency
Authors
Maintainers
Sources
sha256=8e846eef4fcba032d2a3efede550d22bf4fd7923c1ddfcfbef5dc09b7d0d0fec
README.md.html
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 5pmsleep_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
LICENSE
MIT