PyCon Korea 2018 컨퍼런스 중 '파이썬으로 학생 들여다보기' 세션의 샘플 코드입니다.
(Sample code for 'Looking into Student Experience with Python' of PyCon Korea 2018.)
(Reference: https://www.pycon.kr/2018/program/32 - In Korean)
- Actor, Verb, Object - Elements of Statement(Statement의 요소): https://gist.github.com/rubysoho07/062df1cf32a72a0bbc3ebd77c5111312
- Statement - Describing Learning Activities(학습 활동 표현): https://gist.github.com/rubysoho07/33729dec4dcfbb0ef37d05dbe31f9df4
- Actor, Action, Object - Elements of Event(Event의 요소): https://gist.github.com/rubysoho07/393057852a1457fb7d826ae3d21cf2c5
- Event - Describing Learning Activities(학습 활동 표현): https://gist.github.com/rubysoho07/810d7b0e4c2b94fb1a8fb1af625a6c6c
- Python 3.6.5
- Ubuntu 18.04 LTS
- MongoDB 3.6
- 소스를 먼저 받으세요. (Git이 설치되어 있지 않다면, 우측의
Clone or download
->Download ZIP
을 눌러서 압축 파일을 받습니다. 파일을 받으면 적당한 곳에 압축을 풀어줍니다.)
Clone this repository. (If Git is not installed, clickClone or download
->Download ZIP
to download zip archive. Unzip the file where you want to)
$ git clone https://github.com/rubysoho07/learning-analytics-example.git
- 데이터 저장을 위해 MongoDB를 설치해 주세요. 사용하는 플랫폼에 맞추어 설치하면 됩니다.
Install MongoDB to store learning data. Check your operating system before installation.
(Reference: https://docs.mongodb.com/manual/administration/install-community/) - pip으로 필요한 패키지를 설치합니다. (기왕이면
virtualenv
를 이용하여 별도의 환경을 구성하는 것이 좋습니다.)
Install prerequisites with pip. (If possible, I want to recommend to make a virtual environment withvirtualenv
.)
$ cd learning-analytics-example
$ pip install -r requirements.txt
- MongoDB 서버를 실행합니다. / Run MongoDB Server.
- 테스트용 데이터를 MongoDB에 import 합니다. (Localhost에 설치함을 가정)
Import test data to MongoDB. (Supposed that MongoDB was installed in localhost.)
$ mongoimport --host='localhost:27017' -d 'LRS' -c 'CaliperEvents' --file='caliper_gradeevent_sample.json'
- Flask 어플리케이션을 실행합니다. / Run a Flask application.
$ python main.py
In folder /home/yungon/workspace/learning-analytics-example
/home/yungon/.pyenv/versions/la-example/bin/python -m flask run
* Serving Flask app "main.py"
* Environment: development
* Debug mode: off
* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
- 웹 브라우저에서
http://localhost:5000
으로 접속합니다.
Connect tohttp://localhost:5000
on your web browser.
- Flask
- PyMongo
- Caliper Python 1.1
- Billboard.js
- xAPI Specification (ADL): https://github.com/adlnet/xAPI-Spec
- Caliper v1.1 Specification (IMS Global): https://www.imsglobal.org/sites/default/files/caliper/v1p1/caliper-spec-v1p1/caliper-spec-v1p1.html
- TinCan Python(xAPI): https://github.com/RusticiSoftware/TinCanPython
- Caliper Sensor API(Python): https://github.com/IMSGlobal/caliper-python