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LoadCSV Task

Use the LoadCSV task to load data from a CSV file into your test suite.

The Csv can be loaded from a local file, or from a remote S3 server.

This lets you configure and change your test data outside of the scenario. It also allows "dynamic" CI integrations, where the data is built by another test or service before executing the task.

Creating a Load CSV Task

When inside the editor for a new scenario, select the Scenario Start button and select Load CSV.

File Location

Local File

There are a few things to understand regarding this option :

The file must be on the same filesystem as the agent (may be different from your local machine)
CSVs are loaded on execution, not before. We don't store the data ahead of the test, so the file must be present on execution.

This is particularly useful for local development, or for cases where the data is generated in the CI pipeline before the execution. For all other cases, the S3 option may be more suitable.

You can use local or absolute paths. You can also use

S3

This option lets you load a CSV from a S3-compatible source. This lets you manage your test data buckets independantly from the test suite.

S3 Credentials

The agent uses the default AWS credentials chain to authenticate to S3, as defined in AWS documentation.

This means that the credentials should be configured on the agent host, and are never passed to the server.

You can also define them when launching the agent :

in the CI action or jar, via the AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY environment variables,
or to the jar via command line arguments : java -Daws.accessKeyId=... -Daws.secretKey=... -jar ...

Producing the CSV data into Kafka

A common use case is to use the Load CSV task as the entry point for a test suite, and then use the loaded data to produce messages into Kafka.

Example: CSV Data and Kafka Producer

In this example, we will demonstrate how to load csv data from a local file, and then use the data to produce messages into Kafka.

CSV Task

Create a Load CSV task
Update the reference to my_csv to simplify the chaining
Set the file location to Local File
provide the path to a csv file on the agent filesystem, e.g. /tmp/data.csv (or C:\tmp\data.csv on Windows)
- For this example our csv file contains the following data:
```
category,item_id,label,price
electronics,1,TV,1000
electronics,2,Phone,500
books,3,Harry Potter,10
```
- we will want to use the category column as the key for our messages, and a JSON object containing the other columns as the value
In this example, the delimiter is , (comma)
We have a header row, so we check the Has header checkbox. Headers will be derived from the first row of the CSV file.

Save the task

Producer Task

Chained to the On Record port of the Load CSV task, add a Producer task to the canvas
Configure the Cluster and Topic
Go to the Data tab
For the key :
- Choose the String data format
- Change the type of input to Template (mustache)
- Click in the input, then on the + button
- The first proposition will be an example of data selection. Let's use that, and replace column_name with category
For the value, we will build a JSON object from the other columns
- Choose the JSON data format
- Change the type of input to Template (mustache)
- To send the whole CSV record as {[column_name]: column_value}, we could use the same method as for the key, but without a column name.
  - {{source.my_csv.csvRecord.data}}
- Instead for this example, we will build a custom json by using that method on individual fields, to allow customization.
  Notice the quotes around string fields. The template engine will not add them automatically, make sure to add them where needed.
Here is the resulting template :
```
{
  "item_id": "{{source.my_csv.csvRecord.data.item_id}}",
  "item_label": "{{source.my_csv.csvRecord.data.label}}",
  "price": {{source.my_csv.csvRecord.data.price}}
}
```
Save the task. We're ready to run our scenario !