SuperMemo2
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📦 Published package for spaced repetition algorithm SM-2
SuperMemo2
A package that implemented the spaced repetition algorithm SM-2 for you to quickly calculate your next review date for whatever you are learning.
📌 Note: The algorithm SM-2 doesn't equal to the computer implementation SuperMemo2. In fact, the 3 earliest implementations (SuperMemo1, SuperMemo2 and SuperMemo3) all used algorithm SM-2. I didn't notice that when I first published the package on PyPI, and I can't change the package name.
Table of Contents
- Motivation
- Installing and Supported Versions
- A Simple Example
- Features
- What is SM-2?
- Code Reference
- Testing
- Changelog
- Credits
Motivation
The goal was to have an efficient way to calculate the next review date for studying/learning. Removes the burden of remembering the algorithm, equations, and math from the users.
Installation and Supported Versions
Package Install
Install and upate the package using pip:
pip3 install -U supermemo2
To Play Around with the Code
Download the code:
git clone https://github.com/alankan886/SuperMemo2.git
Install dependencies to run the code:
pip3 install -r requirements.txt
supermemo2 supports Python 3+
A Simple Example
from supermemo2 import SMTwo
# first review
# using quality=4 as an example, read below for what each value from 0 to 5 represents
# review date would default to date.today() if not provided
review = SMTwo.first_review(4, "2021-3-14")
# review prints SMTwo(easiness=2.36, interval=1, repetitions=1, review_date=datetime.date(2021, 3, 15))
# second review
review = SMTwo(review.easiness, review.interval, review.repetitions).review(4, "2021-3-14")
# review prints similar to example above.
Features
📣 Calculates the review date of the task following the SM-2 algorithm.
📣 The first_review method to calculate the review date at ease without having to know the initial values.
What is SM-2?
🎥 If you are curious of what spaced repetition is, check this short video out.
📌 A longer but interactive article on spaced repetition learning.
What are the "values"?
The values are the:
- Quality: The quality of recalling the answer from a scale of 0 to 5.
- 5: perfect response.
- 4: correct response after a hesitation.
- 3: correct response recalled with serious difficulty.
- 2: incorrect response; where the correct one seemed easy to recall.
- 1: incorrect response; the correct one remembered.
- 0: complete blackout.
- Easiness: The easiness factor, a multipler that affects the size of the interval, determine by the quality of the recall.
- Interval: The gap/space between your next review.
- Repetitions: The count of correct response (quality >= 3) you have in a row.
Code Reference
class supermemo2.SMTwo(easiness, interval, repetitions)
Parameters:
- easiness (float) - the easiness determines the interval.
- interval (int) - the interval between the latest review date and the next review date.
- repetitions (int) - the count of consecutive reviews with quality larger than 2.
first_review( quality, review_date=None, date_fmt=None )
Static method that calcualtes the next review date for the first review without having to know the initial values, and returns a dictionary containing the new values.
Parameters:
- quality (int) - the recall quality of the review.
- review_date (str or datetime.date) - optional parameter, the date of the review.
- date_fmt (string) - optional parameter, the format of the review_date. Formats like
year_mon_day
,mon_day_year
andday_mon_year
.
Returns: dictionary containing values like quality, easiness, interval, repetitions and review_date.
Return Type: Dict
Usage:
from supermemo2 import SMTwo, mon_day_year
# using default date date.today()
SMTwo.first_review(3)
# providing string date in Year-Month-Day format
SMTwo.first_review(3, "2021-12-01")
# providing string date in Month-Day-Year format
SMTwo.first_review(3, "12-01-2021", mon_day_year)
# providing date object date
from datetime import date
d = date(2021, 12, 1)
SMTwo.first_review(3, d)
review( quality, review_date=None, date_fmt=None )
Calcualtes the next review date based on previous values, and returns a dictionary containing the new values.
Parameters:
- quality (int) - the recall quality of the review.
- review_date (str or datetime.date) - optional parameter, the date of the review.
- date_fmt (string) - optional parameter, the format of the review_date. Formats like
year_mon_day
,mon_day_year
andday_mon_year
.
Returns: dictionary containing values like quality, easiness, interval, repetitions and review_date.
Return Type: Dict
Usage:
from supermemo2 import SMTwo, mon_day_year
# using previous values from first_review call
r = SMTwo.first_review(3)
# using default date date.today()
SMTwo(r.easiness, r.interval, r.repetitions).review(3)
# providing string date in Year-Month-Day format
SMTwo(r.easiness, r.interval, r.repetitions).review(3, "2021-12-01")
# providing string date in Month-Day-Year format
SMTwo(r.easiness, r.interval, r.repetitions).review(3, "12-01-2021", mon_day_year)
# providing date object date
from datetime import date
d = date(2021, 12, 1)
SMTwo(r.easiness, r.interval, r.repetitions).review(3, d)
Testing
Assuming you dowloaded the code and installed requirements.
Run the tests
pytest tests/
Check test coverages
pytest --cov
Check coverage on Codecov.
Changelog
2.0.0 (2021-03-28): Major changes/rebuild, Update recommended
- Rebuilt and simplfied the package.
1.0.3 (2021-01-30): Minor bug fix, Update recommended
- Re-evaluate the default date argument to first_review() on each call.
1.0.2 (2021-01-18): Major and Minor bug fix, Update recommended
- Add required attrs package version to setup.py.
- Allow users to access SMTwo model.
- Fix E-Factor calculation when q < 3.
1.0.1 (2021-01-02): Fix tests, update README and add Github actions, Update not required
- Add missing assertions to test_api.py.
- Update README badges and fix format.
- Add Github actions to run tests against Python versions 3.6 to 3.9 in different OS, and upload coverage to Codecov.
1.0.0 (2021-01-01): Complete rebuild, Update recommended
- Build a new SMTwo class using the attrs package.
- Provide API methods to quickly access the SMTwo class.
- Develop 100% coverage integration and unit tests in a TDD manner.
- Write new documentation.
0.1.0 (2020-07-14): Add tests, Update not required
- Add passing unit tests with a coverage of 100%.
0.0.4 (2020-07-10): Minor bug fix, Update recommended
- Fix interval calculation error when q < 3.
0.0.3 (2020-07-06): Documentation Update, Update not required
- Add new section about SM-2 in documentation, and fix some formats in README.
0.0.2 (2020-07-05): Refactor feature, Update recommended
- Refactor the supermemo2 algorithm code into a simpler structure, and remove unnecessary methods in the class.
0.0.1 (2020-07-02): Feature release
- Initial Release