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https://github.com/ap4y/leaf

Flashcard app that uses spaced repetition algorithms for interval calculations
https://github.com/ap4y/leaf

flashcards spaced-repetition supermemo

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Flashcard app that uses spaced repetition algorithms for interval calculations

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README 

        
* 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.