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Flash cards that are active! Inspired by the concept of active learning / active recall (shoutout to Javier!)

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ActiveCards

ActiveCards is a flashcards based app that allows you to practice learning concepts through active recalling and also the ability to share your cards with others. It is a fullstack React App made with a Redux state manager and a backend using Python, Flask, SQL-Alchemy, and PostgresSQL.

  • Reference to the ActiveCards Wiki Wiki Docs
Table of Contents
1. Features
2. Future Features
3. Contact
4. Getting Started

Technologies

Features

Workspace for Directories / Decks

Workspace

Deck / Cards View

Deck View

Adding Custom Answers

Answers CRUD

Edit, Create, Delete Deck / Cards

Edit, Create, Delete

Future Features

  1. Search - ability to search

  2. Feed Page - area to preview decks and view other decks

  3. Extensions - ability to add other extensions to your active cards(i.e. multiple choice)

Contact

Wes Trinh

westrinh00@gmail.com

Getting started

  1. Clone this repository

  2. Install dependencies

    pipenv install --dev -r dev-requirements.txt && pipenv install -r requirements.txt
  3. Create a .env file based on the example with proper settings for your development environment

  4. Setup your PostgreSQL user, password and database and make sure it matches your .env file

  5. Get into your pipenv, migrate your database, seed your database, and run your flask app

    pipenv shell
    flask db upgrade
    flask seed all
    flask run
  6. To run the React App in development, checkout the README inside the react-app directory.


IMPORTANT! If you add any python dependencies to your pipfiles, you'll need to regenerate your requirements.txt before deployment. You can do this by running:

pipenv lock -r > requirements.txt

ALSO IMPORTANT! psycopg2-binary MUST remain a dev dependency because you can't install it on apline-linux. There is a layer in the Dockerfile that will install psycopg2 (not binary) for us.


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Flash cards that are active! Inspired by the concept of active learning / active recall (shoutout to Javier!)

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