This is a REST API built on top of fbprophet for forecasting time-series data. It is used by the Congestion Tracing API to predict future congestion.

Tested with: PostgreSQL 12.2

Create a database:

sudo -u postgres psql
create database "database_name" owner "database_owner";

Build docker container:

docker build -t prediction_api .

Run the container:

docker run --network=host prediction_api

All API requests require the use of an API key. To authenticate an API request, you should append your API key as a URL parameter.

POST /api/prediction/?key=1234567890

Note: for security reasons there is NO default api key added into the database. For testing the API, a hashed key must be manually added, after running the container, as a SHA3_256 encoded string into the company table.
The hash can be obtained easily from here.
Example adding the SHA3_256 encoded hash of 1234567890 key in the database:

insert into company values(1, 'your_company_name', '01da8843e976913aa5c15a62d45f1c9267391dcbd0a76ad411919043f374a163');

To make a prediction a POST request is needed containing the time-series data as JSON in the request body and the prediction date as a url parameter.
Latitude, longitude and radius are required and used just for caching the prediction model and uniquely identifying the saved cache to be retrieved later.

POST /api/prediction/?key=1234567890&prediction_date=2020-08-02T20:07:31Z&lat=44.4133671&lon=26.1630280&radius=10.0

• URL Params

  Required:
  key=[string] - Authorization key.
  prediction_date=[timestamp] - A future timestamp for which you want the prediction to be made. The timestamp must use the ISO 8601 standard.
  lat=[numeric] - Latitude.
  lon=[numeric] - Longitude.
  radius=[numeric] - Radius.

• Request body

  [
      {
          "timestamp": "2020-08-02T20:07:00Z",
          "value": 1
      },
      {
          "timestamp": "2020-08-02T20:07:30Z",
          "value": 4
      }
  ]

• Sample call:

  curl --request POST 'http://localhost:5000/api/prediction?key=1234567890&prediction_date=2020-08-19T17:07:33.478200Z&lat=44.4133671&lon=26.1630280&radius=10.0' \
  --header 'Content-Type: application/json' \
  --data-raw '[
      {
          "timestamp": "2020-08-02T20:07:00Z",
          "value": 1
      },
      {
          "timestamp": "2020-08-02T20:07:30Z",
          "value": 4
      }
  ]'

  Success Response:

  Code: 200 OK
  Content:

     {
         "predicted_value": "4.041208956969186",
         "predicted_date": "2020-08-19T17:07:33.478200Z"
     }

  predicted_value - is the value predicted by the machine learning algorithm trained on data from the request body.
  predicted_date - represents the future date for which the prediction has been made.

Code: 400 BAD REQUEST
Content:

{
    "timestamp": "2020-08-22T13:21:05.045562Z",
    "status": 403,
    "error": "Bad Request",
    "message": "The client sent a request that this server could not understand.",
    "path": "/api/prediction"
}

Code: 403 FORBIDDEN
Content:

{
    "timestamp": "2020-08-22T13:21:05.045562Z",
    "status": 403,
    "error": "Forbidden",
    "message": "",
    "path": "/api/prediction"
}

Code: 404 NOT FOUND
Content:

{
    "timestamp": "2020-08-23T16:32:22.854640Z",
    "status": 404,
    "error": "Not Found",
    "message": "The requested URL was not found on the server.",
    "path": "/api/a-wrong-path"
}

Code: 500 INTERNAL SERVER ERROR
Content:

{
    "timestamp": "2020-08-22T13:21:05.045562Z",
    "status": 500,
    "error": "Internal Server Error",
    "message": "Oops! Something went wrong on our side.",
    "path": "/api/prediction"
}