Connections

Connections allow you to take data from different data sources (databases, REST APIs, Excel files etc.) and read that data in real time during contract execution. Building connections typically involves:

• Defining Connections in a template which describe some data you want to be injected into the contract at runtime.
• Defining clauses in a template which read data from a Connection and do something useful with it.
• Building connections in the UI which can read and validate data from various sources & make it available to a contract. Connections can have placeholders to enable them to be customised when using them (for example, a stock price connection may have a placeholder for ticker).

When you create a contract in the UI, if the chosen template has Connections defined, then you will need to map connections set up in the UI to supply data for each one. Alternatively, instead of using a live connection the user can enter a value to return whenever the Connection is read.

Example template

Imagine we are creating a template for contracts which make needs two things: a live stock price, and the credit score of a client. We could write a template like this:

from decimal import Decimal

from luna import Connection, Parameter, Template, clause

class MyTemplate(Template):
    stock_price = Connection(type_=Decimal)
    credit_score = Connection(type_=int)
    
    stock_price_threshold = Parameter(type_=Decimal)

    @clause
    def do_something(self):
        stock_price = self.stock_price.read()
        if stock_price > self.stock_price_threshold:
            if self.credit_score.read() > 700:
                # Do something useful

The template does not contain any knowledge of where the data is actually sourced from; it simply declares its requirements, and the data sources are then mapped when creating the contract - which could be something like

• We map stock_price to a connection to an HTTP API - and this connection has a placeholder called ticker which we set to MSFT. The underlying connection works by calling a REST API, injecting the ticker into the URL to get the stock price we want, locating the price in the response data, turning it into a Decimal which gets returned when calling self.stock_price.read().
• We map credit_score to a connection to an Excel file of the customers data, which can read the latest credit score from within the file.