AnkiStatsServer

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• AnkiStatsServer
  • Assumptions
  • Prerequisites
  • Obtaining and configuring the application
    • Clone the github repo
    • Setup a configuration file
  • Database setup
    • Initialize Alembic
    • Begin first migration
    • Database upgrade
  • Usage

This is a Flask application that provides an API for storing a subset of Anki statistics in a MySQL database. Out-of-the box Anki provides a rich set of metrics for tracking your learning efficiency; but does not provide a solution for saving this data over time. This application is one part of a solution to save this data for further use.

As of April 2016, this application simply provides a one-way conduit for getting data into a MySQL database. And it only accepts a certain subset of metrics - those that are provided by the companion project AnkiStats. If you have idea that build on this basic project, please dive in.

Assumptions

You should have a server on which to install this application, some basic knowledge around the terminal, and a working install of MySQL server.

Prerequisites

You'll need to get some prerequisites out of the way first. To make it easy, you can just run the included setup.py script to grab all of the prerequisites.

$ sudo python ./setup.py

For the record, you're installing:

• Flask - a microframework for Python web applications
• SQLAlchemy - a Python SQL toolkit and ORM that this application leverages to work closes with Flask.
• Flask-SQLAlchemy - a Flask extension that provides SQLAlchemy support for the application.
• SQLAlchemy-Migrate - allows us to deal with changes in the database schema.

Obtaining and configuring the application

Clone the github repo

cd to the parent directory of choice and clone.

git clone https://github.com/NSBum/AnkiStatsServer.git

Setup a configuration file

You'll need to create a configuration file config.py at the root level of your project. Probably I should handle this differently with environment variables or something. But I'm lazy. The configuration should look like:

SQLALCHEMY_DATABASE_URI = 'mysql://user_name:[email protected]/dbname'
SQLALCHEMY_TRACK_MODIFICATIONS = False
SECRET_KEY = 'some_top_secret_FBI_bait'
DEBUG = True

Database setup

The application uses Alembic, part of Flask-Migrate that you installed above to managed schema changes. It can also be used to generate the database de novo. You'll need to have a database named anki on MySQL.

Initialize Alembic

$ python manage.py db init
  Creating directory /anki/migrations ... done
  Creating directory /anki/migrations/versions ... done
  Generating /anki/migrations/alembic.ini ... done
  Generating /anki/migrations/env.py ... done
  Generating /anki/migrations/README ... done
  Generating /anki/migrations/script.py.mako ... done
  Please edit configuration/connection/logging settings in
  '/anki/migrations/alembic.ini' before proceeding.

After running the database initialization you should have a folder migrations in the project. This is all of the data needed to run migrations for the project. Next you'll need to begin the first migration.

Begin first migration

$ python manage.py db migrate
  INFO  [alembic.runtime.migration] Context impl MySQLImpl.
  INFO  [alembic.runtime.migration] Will assume non-transactional DDL.
  INFO  [alembic.autogenerate.compare] Detected added table 'stats'
  Generating /home/ec2-user/AnkiStatsServer/migrations/versions/65ed34d8a8ee_.py ... done

Finally we have to perform the actual upgrade.

Database upgrade

$ python manage.py db upgrade
  INFO  [alembic.runtime.migration] Context impl MySQLImpl.
  INFO  [alembic.runtime.migration] Will assume non-transactional DDL.
  INFO  [alembic.runtime.migration] Running upgrade  -> 65ed34d8a8ee, empty message

Now you are ready to run the application.

$ python app.py

Usage

This is a dead-simple API, desperately looking for more features. For now, there's one API end-point: /data. To save Anki stats, you'll need to make a POST request to that end-point with the following JSON as the payload:

{"vocab": 665, "tcount": 1165, "review": 125, "time": 1460016000, "filter": 0, "msum": 7, "relearn": 15, "mcnt": 8, "learn": 61, "duration": 979, "total": 201, "tomorrow": 132}

If the request is successful, you should receive the following response:

{
  "id": 8,
  "result": {
    "status": 200
  }
}

where id is the row s_id value.