README.rst

Taytay Quick Start

Below you will find basic setup and deployment instructions for the taytay project. To begin you should have the following applications installed on your local development system:

• Python >= 3.4
• pip >= 1.5
• virtualenv >= 1.10
• virtualenvwrapper >= 3.0
• Postgres >= 9.3
• git >= 1.7

Getting Started

First clone the repository from Github and switch to the new directory:

$ git clone git@github.com:[ORGANIZATION]/taytay.git
$ cd taytay

To setup your local environment you should create a virtualenv and install the necessary requirements:

# Check that you have python3.4 installed
$ which python3.4
$ mkvirtualenv taytay -p `which python3.4`
(taytay)$ make dev

Configurable settings are managed with django-dotenv. It reads environment variables located in a file name .env in the top level directory of the project. The previous command make dev creates new .env file with a new SECRET_KEY value set.

Create the Postgres database and run the initial migrate:

(taytay)$ createdb -E UTF-8 taytay
(taytay)$ python manage.py migrate

You should now be able to run the development server:

(taytay)$ python manage.py runserver

Connecting to the API

To connect to the API at baelor.io, you'll need to create a user using the following curl command

$ curl -H "Content-Type: application/json" -X POST -d
'{"username": "yourusername","email_address": "youremail",
"password": "yourpassword","password_confirm": "yourpassword"}'
http://baelor.io/api/v0/users

You should receive an API key in the response. To make use of this key, you should include it in your .env file:

$ echo 'BAELOR_API_KEY="<api key>"' >> .env

Where <api key> would be replaced with your actual API key value.

Get song data

To get song data run the fetch_song_data command

$ python manage.py fetch_song_data

Testing

The Makefile for this project has a number of helpful commands for testing and checking code quality. Below is a brief description of the commands

• make test - Runs the full test suite and reports test coverage
• make lint - Runs a set of subcommands to check code quality

• make lint-py - Runs the code through flake8 for static analysis
• make lint-migrations - Runs Django's checks for model changes without migrations
• make lint-django - Runs Django's system checks with the base settings
• make lint-deploy - Runs Django's system checks for deployment