Easy way to measure the amount of stress and happiness within a team/project/random context.
Data is stored in an sqlite db. It looks like this:
{
"id": 1,
"message": "happy",
"timestamp": 1428273876
}You can simply fire it up using:
docker build -t mood-meter --no-cache .
docker run -p 8080:80 -it mood-meterThe server will be available on 127.0.0.1:5000.
Use the provided requirements.txt to install the deps and then you can either run
the Flask development server using python app.py or start the app via gunicorn,
using gunicorn -k eventlet app:app.
Don't forget to build the JS as well - you can read everything about it in
static/README.md.
GET / - home for frontend.
GET /api/statuses/ - list endpoint for status objects (supports filtering via message, since and until).
Example:
{
"data": [
{
"id": 3,
"message": "happy",
"timestamp": 1428276198
},
{
"id": 2,
"message": "happy",
"timestamp": 1428273877
},
{
"id": 1,
"message": "happy",
"timestamp": 1428273876
}
]
}POST /api/statuses/ - adds a new status; needs content-type json and {"message": $msg}, with $msg one of
"stressed" and "happy".
GET /api/timeseries/ - data endpoint for building timeseries graphs on top of the data (supports same filters
as statuses/ and, in addition, a resolution - day, hour, minute or second - defaulting to day).
Example:
{
"1428192000": 3,
"1428278400": 0
}The possible statuses are defined in constants.py. Feel free to change them
and everything will keep working!