Chainlink external adapter for Quandl API

Getting started

REQUIRED: First step is creating an account at Quandl and creating an API key.

Once you have it, simply run the image:

$ docker container run --rm --detach --name cl-ea-quandl --publish 5000:5000 --env QUANDL_API_KEY=[INSERT HERE YOUR KEY] willianpaixao/cl-ea-quandl:latest

NOTE: don't forget to replace with your API key

To quickly test, make a request using curl:

$ curl --request POST --header "Content-Type: application/json" --data '{"id": 1, "data": {"dataset": "FRED/GDP"}}' localhost:5000
{
  "data": {
    "dataset": "FRED/GDP",
    "result": 21157.122
  },
  "jobRunID": 1,
  "statusCode": 200
}

Quandl API

Now that you have a running adapter, look at the Quandl API documentation for all possible parameters that can be passed and at the Quandl feed explorer to pick the data you need.

Examples

You can explore the free (as in "free of charge") data feeds here. Most common usages are for macroeconomic data and financial indexes, some examples are:

Dataset	Description
FRED/GDP	USA's Gross Domestic Product
FRED/UNRATE	USA's Civilian Unemployment Rate
FRED/GFDEBTN	USA's Federal Public Debt
NASDAQOMX/OMXS30	OMX Stockholm 30 Index
BCB/11	Brazilian interest rate

NOTE: You can purchase a premium feed but this is out of the scope of this service.

Development

You can easily build with Docker, by running:

$ docker image build --tag cl-ea-quandl:latest .

$ gcloud functions deploy cl-ea-quandl --set-env-vars QUANDL_API_KEY=[INSERT HERE YOUR KEY] --entry-point index --runtime python38 --memory 128MB --trigger-http --allow-unauthenticated

Alternatively you can run locally without Docker with:

$ QUANDL_API_KEY=[INSERT HERE YOUR KEY] FLASK_ENV=development flask run

Testing

Make sure you have installed all dependencies using Pipfile, then run:

$ FLASK_ENV=testing pytest --setup-show

Contributing

Did you run into a bug? Please create an issue. Do you want to contribute? All PRs are welcome.