Estimated time: 10 min.

In this tutorial you will learn:

Prerequisites for this tutorial:

• PIPEFORCE Enterprise 7.0 or higher

• You have a valid PIPEFORCE Developer account

• You have completed tutorial: Tutorial: Create a new app

• You have completed tutorial: Tutorial: Create and execute a pipeline

• You have a basic understanding of the PEL: Pipeline Expression Language (PEL)

Introduction

Inside a pipeline you can access any data using the Pipeline Expression Language (PEL). This is handy in case you want to analyse or transform data which is in most cases stored in the body of the pipeline.

So the question to solve in this tutorial is, how you can load an external JSON file into the pipeline body in a way that you can also apply a PE on it.

1 - Create a new JSON file in Drive

1. Login to the portal https://NAMESPACE.pipeforce.net

2. Navigate to Files. The Drive app opens.

3. Add a new text document person.json in the root folder and copy and paste this content into it:
   
   

   { "firstName": "Marissa", "lastName": "Smith", "age": 33 }

2 - Load the JSON file from Drive

1. Navigate to Workbench. The ad-hoc pipeline editor opens.

2. Replace the existing content by this pipeline:

   pipeline: - drive.read: path: "person.json"

3. RUN the pipeline and you should see the content of the file person.json as output:

   { "firstName": "Marissa", "lastName": "Smith", "age": 33 }

   This is because the file is automatically converted from a content object to its the mime type format - which is JSON in this case - and then sent to the client.

4. In order to “see” the content object and not the result, change the pipeline to this:

5. RUN the pipeline and you should see as output the content object with meta information about the file:

3 - Convert the content data to JSON

In case you want to work with the JSON data of a file, the data part of the content object is the interesting thing for you. In order to load this into the body, again use the @convert.toJson() but this time point to the data property:

After you RUN the pipeline you should see again the JSON content as output:

But this time it is provided as JSON inside the pipeline so you can access it via Pipeline Expression Language (PEL):

You should see an output similar to this, which transformed the JSON:

Congrats, you have loaded and parsed your first external data into a pipeline, ready for data manipulation!

The content object

By default, any external file loaded by a pipeline will be converted into a so called content object which is a wrapper around the file which holds additional meta information about it. The structure of such a content object is like this: