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Travis Optimiser

Deployed via google cloud functions

Endpoint: (GET) https://asia-east2-travis-mvp-v2.cloudfunctions.net/travis-recommender

To make a request: attach requested google places id in a header, accepts either 1 or 2 headers in a list: ids:["ChIJczgQh8lC1moR9r9gP44FRvY", "ChIJdedaLk5d1moRQOX0CXZWBB0"]

  • These are Chinatown and Southern Cross respectively, so search should return shops in the middle

Response format (json): {"33":"ChIJ9RT5wLRC1moRpIkhaxraJMc","37":"ChIJcxVwKrVC1moRcHnRJ0dR5vM"}

Curl test (status test): curl -X GET -k -H 'ids: ["ChIJczgQh8lC1moR9r9gP44FRvY", "ChIJdedaLk5d1moRQOX0CXZWBB0"]' -i 'https://asia-east2-travis-mvp-v2.cloudfunctions.net/travis-recommender'

DONE list

  • Flat file location: Stored on a GCP Cloud Storage bucket, see config.yml (not published to github)

  • Add google search for different types of establishments, in an area

  • Add single radius search

  • Add controller for search, that

    • check if search is single radius or between two locations
    • makes sure there are 5 results, and saves any additional searches to the csv file
  • Deploy to google cloud functions - DONE

    • Modify storage location to a GCP cloud storage filepath - DONE
  • Update IAM Authorisation - Should be Automatic when called from within gcp

To do list:

  • Update data to cloud when user requests new data
  • Content based recommender that classifies restaurants by type
  • Create a list of types of restaurants, for recommendation
  • System that links to accounts
  • convert data management system to an object

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Recommender & Route Optimiser backend for Travis

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