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CSV

Last update: Thu Nov 21 2024 00:00:00 GMT+0000 (Coordinated Universal Time)

CREATED FOR:

  • User

The ÃÛ¶¹ÊÓƵ Workfront Fusion CSV modules let you create CSV files and parse CSV text from a received text value or a file.

Access requirements

You must have the following access to use the functionality in this article:

ÃÛ¶¹ÊÓƵ Workfront plan*
Pro or higher
ÃÛ¶¹ÊÓƵ Workfront license*
Plan, Work
ÃÛ¶¹ÊÓƵ Workfront Fusion license**

Current license requirement: No Workfront Fusion license requirement.

Or

Legacy license requirement: Workfront Fusion for Work Automation and Integration, Workfront Fusion for Work Automation

Product

Current product requirement: If you have the Select or Prime ÃÛ¶¹ÊÓƵ Workfront plan, your organization must purchase ÃÛ¶¹ÊÓƵ Workfront Fusion as well as ÃÛ¶¹ÊÓƵ Workfront to use functionality described in this article. Workfront Fusion is included in the Ultimate Workfront plan.

Or

Legacy product requirement: Your organization must purchase ÃÛ¶¹ÊÓƵ Workfront Fusion as well as ÃÛ¶¹ÊÓƵ Workfront to use functionality described in this article.

To find out what plan, license type, or access you have, contact your Workfront administrator.

For information on ÃÛ¶¹ÊÓƵ Workfront Fusion licenses, see ÃÛ¶¹ÊÓƵ Workfront Fusion licenses.

Create CSV

The Create CSV Aggregator lets you create a csv text from received text values.

For more information on aggregators, see Aggregator module in ÃÛ¶¹ÊÓƵ Workfront Fusion.

Source Module
Select the module you are using to aggregate the fields you need.
Aggregated Fields
Select the fields you want to aggregate from the list of available fields.
Include headers in the first row
Select this option to include the headers in the result.
Group by
Enter the filter to group the results. For example, enter a date.
Stop processing after an empty aggregation
Select this option to stop the scenario when there are no results.

Create CSV (advanced)

The Create CSV (advanced) Aggregator lets you create a CSV text from received text values. It employs a data structure that defines the CSV columns in the resulting CSV file. Once defined, the columns appear as fields in the CSV module setup, and can be mapped to later module in the scenario.

For more information on aggregators, see Aggregator module in ÃÛ¶¹ÊÓƵ Workfront Fusion.

Source Module
Select the app module you are using to aggregate the fields you need.
Data Structure

Select the data structure to aggregate the fields in the way you want. After defining the data structure, you can map the items to the corresponding fields.

For more information, see Data structures in ÃÛ¶¹ÊÓƵ Workfront Fusion.

Include headers in the first row
Select this option to include the headers in the result.
Group by
Enter the filter to group the results. For example, enter a date.
Stop processing after an empty aggregation
Select this option to stop the scenario when there are no results.

Let us assume you would like to export your Google contacts to a CSV file with two columns "Full Name" and "Email". The output bundle from the Google Contacts >Get contacts from a group module has the following structure. The email addresses are stored inside the Emails[] item, which is an array of collections, each collection containing two items: Label and Email.

If you employ the simple Create CSV module, you are offered a list of checkboxes corresponding to a bundle's top-level items. If you attempt to tick Full name and Emails items, the Create CSV module produces the following output, which is probably not what you want:

"emails","fullName"

"[object Object]","Shon Winer"

"[object Object]","Lizeth Fulmore"

"[object Object]","Hilario Gullatt"

"[object Object]","Abby Eisenbarth"

Since the item Full Name is of simple type Text, it is exported just fine. But the item Emails, which is of a complex type Array of Collections, is exported as [object Object], which is how Collections and Arrays are transformed to text by default. For more information, see Item data types in ÃÛ¶¹ÊÓƵ Workfront Fusion.

To export content of the Email item of the first collection of the Emails[] array instead, it is necessary to employ the Create CSV (advanced) module. The module enables you to define individual columns of your CSV file and map items to them, including the nested ones.

  1. Insert the module Create CSV (advanced) in a scenario and open its configuration.

  2. Click the Add button next to the Data structure field to create a new Data structure.

  3. Write in a name for the Data structure and click the Add item button to add the individual columns. If you want to export two columns: "Full Name" and "Email", the resulting Data structure would look like this:

  4. Once you have successfully defined the Data structure, fields corresponding to each individual column should appear in the configuration of the Create CSV (advanced) module so you can map the items. Take the first item from the Emails[] array and map its item Email to the field/column Email:

  5. Execute the scenario. Since the item Emails[1]: Email mapped to column "Email" is of simple type Text, it exports correctly now:

    "Full Name","Email"

    "Shon Winer","Shon@Winer.com"

    "Lizeth Fulmore","Lizeth@Fulmore.com"

    "Hilario Gullatt","Hilario@Gullatt.com"

    "Abby Eisenbarth","Abby@Eisenbarth.com"

Parse CSV

The Parse CSV transformer lets you parse CSV text from a received text value or a file.

Number of columns
Specify the number of columns in the CSV file.
CSV contains headers

Select this option if the first row of the CSV text contains headers.

Note: The module does not use these headers to label the columns in the output. Instead, this field ensures that the headers are not included in the output data.

delimiterType

Select the delimiter for the CSV file. The delimiter is the text character that indicates the boundary between separate values or fields.

  • Comma

  • Tab

  • Other

    If you select Other, enter the delimiter character that the CSV file is using to separate values. You must enter exactly one character.

Preserve quotes inside unquoted field
Enable this option to preserve quotes.
CSV

Enter or map the CSV file that you want to parse.

Note:

If your data comes in binary form (typically from a file), you must use the `toString()` function to convert the binary data to String:

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