Catalytic fields always have a field type. For example, a field with the type “Text” accepts all alphanumeric characters, and the type “Integer” only accepts whole numbers. There are 11 commonly used field types.
You can specify the field type when you add a field to a Workflow or data table. If an action in a process adds the wrong type of data to a field, like adding a date to an integer field type, a fix task is created; in this way, field types help standardize and validate field data.
By choosing the right field type for your process, you can configure fields and data tables to fit the data they will store.
💡Tip: Field types are set manually from a Workflow or Data table. In some cases, like importing a CSV or Excel file to a data table, field types are inferred automatically. See importing data tables for how Catalytic infers field types.
Fields formatted as long text accept all alphanumeric characters and values, and treat all values as text, including numbers. Many tasks output text type fields.
Even though the text type is the most common, some actions do not accept text type data. Date and Date and Time field types require a specific format as an input, and in some cases, a date stored in a text type field cannot be an input to Date or Date and Time actions.
To use a text type field in this way, use actions like Dates: Format a date time to transform fields into a date or date-time format. See the How to convert data from one field type into a new type for more on converting values between field types.
Text fields support entry validation, which prevents or restricts a user from submitting a form or task when a field has incorrect data. To learn more, check Apply entry validation to fields.
Short text is identical to long text field, but does not accept new lines.
Integer fields accept integers, or whole numbers. Decimal numbers are rounded up or down to the nearest whole number. Text, dates, or other non-numbers are not accepted.
If a user enters a non-integer into an integer field, the field will highlight red and prevent submission.
Integer fields support entry validation, which prevents or restricts a user from submitting a form or task when a field has incorrect data. To learn more, check Apply entry validation to fields.
Decimal fields accept all whole and decimal numbers. Decimal fields are not rounded. Text, dates, or other non-numbers are not accepted.
If a user enters a non-decimal or integer into a decimal field, the field will highlight red and prevent submission.
Decimal fields support entry validation, which prevents or restricts a user from submitting a form or task when a field has incorrect data. To learn more, check Apply entry validation to fields.
You can choose the number of decimal places to show using the Decimal places configuration. Values will be rounded if necessary.
Date fields are in
YYYY-MM-DD format. If a date-time is input into a date field, the time is stripped from the value. All other values are not accepted. Date type fields include a date picker dialog.
You can choose the format for the date during configuration, such as
December 10th, 2020. The format affects how the date appears, but all dates are still stored in the ISO format,
The date’s appearance is localized depending on where the viewer is in the world.
Date-time fields are formatted in ISO format,
YYYY-MM-DDThh:mm:ss.sZ. For example, March 23rd, 2018, 3:40PM CST is equivalent to
2018-03-23T03:40:00.0-06:00. If a date-time is added to a field with no time zone, it defaults to UTC.
Catalytic will always display date-times in the time zone of the viewer. For example, a field with the date-time,
2018-03-23T03:40:00.0-06:00, is displayed based on the viewer’s time zone. The actual value is unchanged.
You can choose the format for the date-time during configuration, such as
12/10/2020 18:00, or
December 10th, 2020 12:00 PM. The format affects how the date appears, but all dates are still stored in the ISO format,
The date’s appearance is localized depending on where the viewer is in the world.
True or false fields only accept true or false values. Dates, or other non-numbers are not accepted.
Single Choice fields are text fields with preset values to choose from. Users can choose one of the available options, and cannot select multiple options.
Multiple Choice fields are text fields with preset values to choose from. Users can choose one or more options.
File fields contain files. File fields support drag and drop uploading, and downloading. There are no restrictions on file type or file extension.
To upload a file, select the file type field. This will bring up the default file upload dialog for the user’s web browser. File type fields accept one file upload at a time. To upload multiple files, use the Files field type.
After a file is uploaded, click the file in the field to download it. This will download the file to your default directory.
💡Tip: File fields are easy to reference and reuse in your Workflow, so it is recommended to use them over Files fields whenever possible.
You can set the allowed file types by setting a file type entry validation restriction. Enter the allowed file types as a comma separated list.
Multiple file fields can contain multiple files, and support drag and drop uploading, and downloading. There are no restrictions on file type or file extension.
To upload one or more files, select the file type field. This will bring up the default file upload dialog for the user’s web browser.
For more information on Multiple File fields, see the Multiple File field type article.
You can set the allowed file types by setting a file type entry validation restriction. See the steps above for more details.
Instruction fields are special fields commonly used in web forms and actions like Assign task to a person.
Instruction fields do not require or accept an input, and are instead helpful for adding detail to a task or web form. Instruction fields support field references and Markdown. See the Markdown article for tools to help work in Markdown.
You can conditionally display text in an instruction field, for example, you can show specific instructions depending on different conditions or field values. To conditionally display instruction fields, see:
- The Set rules to show or hide fields in a form or task article.
- The Use a field reference to conditionally display text in a field section.
Data table fields enable you to present an interactive data table within a task. Users can update any of the rows or columns, just like they would a spreadsheet.
Data table fields appear as buttons. You can click on any data table field to open it up and make edits. Users can make changes to fields, add new data to empty fields, or delete field data: and all changes are made to the actual data table, instantly.
Data table fields are great if you have lengthy lists of form fields in tasks, because they consolidate the work of multiple fields into one field. See the Data Table Field Type article for details on how the field works, how to add them, and how they differ from a full data table.
Store a Workflow ID in a Workflow field and reference it in other places. This is most commonly used as an Instance Field, for example if you know you will be referencing the regularly reference the same Workflow. A referenced Workflow field shows as text when included on a form or in instructions.
It is functionally similar to a short text field, and can be used interchangeably.
To find a Workflow’s ID, see How to reference a Workflow or Table by its name, field, or ID.
User type fields accept user names. Clicking on an entry stored in a user field links directly to that user profile page.
Check box fields are an easy way to add sections like “Click here to agree” or “Yes, please sign me up for the mailing list” to a web form. The text that appears next to the checkbox is set in the Checkbox Text field.
A checkbox field still requires a display name, and can optionally have a description. You can set the default state for checkboxes to checked or unchecked.
Email fields have built in validation and only accept properly formatted emails. This field verifies whether the syntax is correct, not whether it’s a valid email.
The password field obscures the entry by default. Password fields have a toggleable icon, which toggles visibility of the entry.
⚠️ Heads-up: By default, field data is public. Be sure to set the field permissions to confidential or highly confidential if you intend to use this field with passwords or other confidential data. See Set the permissions and visibility of fields.
Catalytic has numerous actions to help convert data between field types:
- Field: Set value of a decimal field
- Field: Set value of an integer field
- Field: Set value of a text field
- Dates: Set value of a date field
- Field: Set the value of a multiple choice field
Date and date-time fields have additional actions that help convert between field types:
If incorrectly formatted data is added to a field, a fix task is created. For example, if an action attempts to add the text
Apple to an Integer type field, this will create a fix task.
Field types like the date and integer type have built in validation and only accept formatted data. For other custom validation, like for currency, PO numbers, phone numbers, or more, see the Apply entry validation to fields or Conditionally display text in instructions or emails article.
You can change a field’s type if necessary, like if you create a new field, or cases where an inferred field type is incorrect. The following instructions show how to change an Instance Field type. To change other fields, such as in an Assign task to a person action, navigate to the fields section of that action.
- From the Workflow Builder page, click to expand the Triggers and Fields section.
Select a field you wish to change the field type for.
- Navigate to the Type section. Set the type.
- Select at the top of the page.
See the Edit or remove fields in a row section of the Updating data tables article for instructions how to change field types from a data table view.
Changing a field’s type may result in unexpected changes to any past data the field collected and stored. For example, if a integer field is changed to true or false, all historical values will change to false.
With how field types are designed, it is recommended to test these changes outside of a production environment to verify all changes are acceptable.