suade_analytics

Suade Labs Analytics Challenge (Connor Adams)

This is a Flask API that parses .csv data for a demo shop, for a given date in the format YYYY-MM-DD

Info

Due to the time constraints of this challenge (24 hrs) I had some challenges with the structure of the application. This app is loading the .csv files into memory and directly querying the files using python and some SQL queries brought in from the pandasql python package.

This IS NOT an optimal solution by any means. If I had more time, I would read these .csv files into a MySQL database (preferably through Amazon RDS using an EC2 instance) then parse the data with actual SQL queries. An actual RDMS would help with parsing this data immensely.

Build

To build, Create a VM using Python 3.9 import requirements from

suade_analytics/requirements.txt

And point the configuration class to

suade_analytics/app.py

If using terminal, just run

python app.py

Running

API will be running on http://127.0.0.1:5000/ with the swagger docs on http://127.0.0.1:5000/apidocs

Example Output

curl -s http://127.0.0.1:5000/get_analytics_report/2019-08-02 | jq

{
  "commissions": {
    "order_average": 10514893.66,
    "promotions": {
      "1": 22633010.44,
      "2": 19293679.09,
      "3": 22016151.23,
      "4": 15290844.79,
      "5": 13743272.78
    },
    "total": 92976958.32
  },
  "customers": 10,
  "discount_rate_avg": 0.13,
  "items": 3082,
  "order_total_avg": 164998295.76,
  "total_discount_amount": 150457385.36
}