Connectors are essential for the development of an application with Simplifier. They are used to persist data and can connect to different, external IT landscapes in order to access the required data.
Once a connector is configured, various calls can be added and tested directly. In Simplifier, there are already several preconfigured connector types such as SOAP, REST, SQL or SAP RFC and so on, which can be linked to the APIs with just a few clicks. In this example, we create a REST connector that can access the data of a to-do list API.
STEP 1: General Connectivity
Selecting “Add new connector” in the connector tile will display an input mask with the necessary information.
At this point, the name, the connector type and the service URL is relevant.
In this example, the next screenshot defines some input parameters that allow us to query data – I will explain these briefly.
In this case, the parameter “pathParams” sets the constant value “todos” after the target URL and can be extended by further parameters, including dynamic parameters, such as “pathParams”.
All parameters specified with pathParams are separated by “/” and added to the target URL. The format for the transmission is specified with “postFormat” and sends the data, in this example in JSON format.
Using “verb” decides whether the call should read (GET), write (POST) or delete (DELETE) data.
Parameters without a constant value should be given an alias, as this could lead to complications.
STEP 3: Test Connector Call
As all relevant parameters are entered, let’s test the call by entering an ID via the button “Save & Test”. In the screenshot, you can see by the green-bordered box with the output values that the call with the ID 252 was successful.
If you enter an ID that does not exist, no values can be returned. The red-bordered box indicates that the call is incorrect in this case.
With the help of connectors, the access to different APIs is easy to manage and thus the application can be connected to different IT systems. They can also be used multiple times and have reduced maintenance requirements. This saves time and reduces errors when changes are made to the data structure.
Kindly provided by mindsquare