Recommendations

CSCI-GA.2820-003 DevOps and Agile Methodologies Fall 2021

Recommendations Service

This repo contains details of our Recommendations Service. It could also recommend based on what other customers have purchased like "customers who bought item A usually buy item B". Recommendations should have a recommendation type like cross-sell, up-sell, accessory, etc. This way a product page could request all of the up-sells for a product.

Prerequisite Installation using Vagrant

Clone the project to your development folder and create your Vagrant VM

$ git clone https://github.com/NYUDevOps2021-recommendation/recommendations.git
$ cd recommendations
$ vagrant up

Once the VM is up you can use it with:

$ vagrant ssh
$ cd /vagrant
$ FLASK_APP=service:app flask run -h 0.0.0.0

When you are done, you can use Ctrl+C to stop the server and then exit and shut down the vm with:

$ exit
$ vagrant halt

Manually running the Tests

Test Driven Development (TDD)

This repo also has unit tests that you can run nose

nosetests

Nose is configured to automatically include the flags --with-spec --spec-color so that red-green-refactor is meaningful. If you are in a command shell that supports colors, passing tests will be green while failing tests will be red.

Behavior Driven Development (BDD)

These tests require the service to be running becasue unlike the the TDD unit tests that test the code locally, these BDD intagration tests are using Selenium to manipulate a web page on a running server.

Run the tests using behave

honcho start &
behave

API Calls with specified inputs available within this service

GET  /recommendations?product-id={id}&relation={relation} - Read a Recommendation based on product_origin and relation
GET  /recommendations/{id} - Retrieves a recommendation with a specific id
POST /recommendations - Creates a recommendation in the datbase from the posted database
PUT  /recommendations/{id} - Updates a recommendation in the database from the posted database
DELETE /recommendations{id} - Removes a recommendation from the database that matches the id

Valid content description of JSON file

{
  "id": <int> # the id of a recommendation 
  "product_origin": <int> # the id of the product in the recommendation 
  "product_target": <int> # the id of the product that's being recommended with a given product
  "relation": <int> # describes the type of recommendation(1 for cross-sell, 2 for up-sell, 3 for accessory)
  "is_deleted" : <int> # 0 is not deleted, 1 is deleted
}