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Flashcard app that uses spaced repetition algorithms for interval calculations
- Leaf
Leaf is a flashcard app that uses [[https://en.wikipedia.org/wiki/Spaced_repetition][spaced repetition]] algorithm. Leaf focuses on simplifying database management, ease of access and support for various spaced repetition curves (including custom).
[[https://gitlab.com/ap4y/leaf/raw/master/screenshot.png]]
** Getting started
Leaf is a [[https://golang.org/][golang]] application and you are going to need golang toolchain to compile the app.
To install or update run:
#+BEGIN_SRC shell go get -u github.com/ap4y/leaf/cmd/leaf #+END_SRC
or
#+BEGIN_SRC shell go get -u github.com/ap4y/leaf/cmd/leaf-server #+END_SRC
Leaf provides 2 different versions:
- ~leaf~ is a command line utility that provides review UI in the terminal
- ~leaf-server~ is a web app that implements review UI along with additional features like stats viewer.
Both utilities have following configuration options:
- ~-decks .~ is a path to a folder with deck files.
- ~-db leaf.db~ is a location of a stats DB that contains spaced repetition variables for your decks.
For ~leaf-server~ you can also adjust address to start server on via ~-addr :8000~.
Terminal CLI (~leaf~) has following commands:
- ~review~ will initiate review session for a deck
- ~stats~ will return stats snapshots for a deck
Both commands expect deck name after the command name. Full example:
#+BEGIN_SRC shell ./leaf -decks ./fixtures review Hiragana #+END_SRC
** Database management
Leaf uses plain text files structured usin [[https://orgmode.org/manual/Headlines.html#Headlines][org-mode headlines]]. Consider following file:
#+BEGIN_SRC org
- Sample :PROPERTIES: :RATER: auto :ALGORITHM: sm2+c :PER_REVIEW: 20 :SIDES: answer :END: ** Question 1 Answer 1 ** Question 2 Answer 2 #+END_SRC
Such file will be parsed as a deck named Sample and it will have 2 cards. For a full deck example check [[https://gitlab.com/ap4y/leaf/raw/master/fixtures/hiragana.org][hiragana]] deck.
You can use text formatting, images, links and code blocks in your deck files. Check [[https://gitlab.com/ap4y/leaf/raw/master/fixtures/org-mode.org][org-mode]] deck for an overview of supported options.
Top header level property drawer is used to adjust review parameters. Following parameters are supported:
- ~ALGORITHM~ is a spaced repetition algorithm to use. Default is ~sm2+c~. All possible values can be found [[https://gitlab.com/ap4y/leaf/blob/master/stats.go#L35-44][here]].
- ~RATER~ defines which rating system will be used for reviews. Defaults to ~auto~, supported values: ~auto~ and ~self~.
- ~PER_REVIEW~ is a maximum amount of cards per review session.
- ~SIDES~ is an optional field that defines names of the card sides, used in the UI for placeholders.
Spaced repetition variables are stored in a separate file in a binary database. You can edit deck files at any time and changes will be automatically reflected in the web app.
** Spaced repetition algorithms
Leaf implements multiple spaced repetition algorithms and allows you to define new ones. Following algorithms are supported as of now:
- [[https://www.supermemo.com/en/archives1990-2015/english/ol/sm2][supermemo2]]
- [[http://www.blueraja.com/blog/477/a-better-spaced-repetition-learning-algorithm-sm2][supermemo2+]]
- Custom curve for supermemo2+. I found it works better for me.
- [[https://fasiha.github.io/ebisu.js/][ebisu]]
You can find calculated intervals in corresponding test files. Check [[https://gitlab.com/ap4y/leaf/blob/master/stats.go#L9-19][SRSAlgorithm]] interface to define a new algorithm or curve.
Please keep in mind that algorithm variables may not be compatible with each other and algorithm switching is not supported.
** Review rating
All reviews are rated using ~[0..1]~ scale. Rating higher than ~0.6~ will mark review as successful. You can use 2 different types of rating systems:
-
~auto~ (default) is based on amount of mistakes made during review. For ~auto~ rating is assigned using [[https://gitlab.com/ap4y/leaf/blob/master/rating.go#L45-47][HarshRater]] which implements steep curve and a single mistake will have score less than ~0.6~. Check [[https://gitlab.com/ap4y/leaf/blob/master/rating.go#L34-36][Rater]] interface to get understanding how to define a different rater curve.
-
~self~ is a self assessment system. You have to assign score for each review and score will be converted to a rating as such: ~hard = 0.2~, ~good = 0.6~, ~easy = 1.0~, ~again~ will push card back into the review queue.
To change rating system for a deck define org-mode property ~RATER~ in your deck file.