DateTime Columns
How to add a datetime column to your importer through code.
You can add a column to your importer directly through the UI of your Fuse account, or you can do so in code using the documentation below.
The DateTime column type validates that values are a specific DateTime format.
addColumn Function
The addColumn
function accepts an object as an argument.
internal_key
(String) - required: The internal key used to access a column’s value.label
(String) - required: The user-facing column label that is shown in the interface.column_type
(String) - required: Should be “datetime”.required
(String) - required: Whether or not the column is required.pattern
(String) - required: must be one of these patterns.position
(Optional): The position or order of the column.unique
(Optional): Whether values should be unique.validations
(Optional): An array of built-in data validations. See Built-in DateTime Validations.transformations
(Optional): An array of built-in data transformations. See Built-in DateTime Transformations.
Example Code
Patterns
MM/dd/yyyy HH:mm
Example: 08/31/2023 12:30; 09/31/2005 12:30
MM/dd/yyyy HH:mm:ss
Example: 08/31/2023 12:30:45; 08/31/2005 12:30:45
MM/dd/yyyy HH:mm:ss.SSS
Example: 08/31/2023 12:30:45.500; 08/31/2005 12:30:45.500
MM/dd/yyyy h:mm a
Example: 08/31/2023 1:30 PM; 08/31/2023 1:30 PM
MM/dd/yyyy h:mm:ss a
Example: 08/31/2023 1:30:45 PM; 08/31/2005 1:30:45 PM
MMM dd HH:mm:ss yyyy
Example: Jan 15 00:34:59 1990; Feb 15 00:34:59 1990
dd MMM HH:mm:ss yyyy
Example: 15 Jan 00:34:59 1990; 15 Feb 00:34:59 1990
MM/dd/yyyy h:mm:ss.SSS a
Example: 08/31/2023 1:30:45.500 PM; 06/11/2030 1:30:45.500 PM
MMMM dd, yyyy HH:mm
Example: August 31, 2023 12:30; January 15, 2023 12:30
MMMM dd, yyyy HH:mm:ss
Example: August 31, 2023 12:30:45; January 15, 2023 12:30:45
MMMM dd, yyyy h:mm a
Example: August 31, 2023 1:30 PM; January 15, 2023 1:30 PM
MMMM dd, yyyy h:mm:ss a
Example: August 31, 2023 1:30:45 PM; January 15, 2023 1:30:45 PM
MMMM dd, yyyy h:mm:ss.SSS a
Example: August 31, 2023 1:30:45.500 PM; January 15, 2023 1:30:45.500 PM
MM-dd-yy HH:mm
Example: 01-15-90 10:10; 05-15-90 10:10
dd-MM-yyyy HH:mm
Example: 15-01-1990 10:10; 15-01-1990 10:10
dd/MM/yyyy HH:mm
Example: 15/01/1990 10:10; 12/11/1990 10:10
dd-MM-yyyy h:mm a
Example: 15-01-1990 10:10 AM; 15-01-1990 10:10 AM
dd/MM/yyyy h:mm a
Example: 12/11/1990 10:10 AM; 15/01/1990 10:10 AM
MM/dd/yy HH:mm
Example: 01/15/90 10:10; 05/15/90 10:10
MM/dd/yy HH:mm:ss
Example: 01/15/90 10:10:14; 05/15/90 10:10:14
MM/dd/yy h:mm:ss a
Example: 01/15/90 5:10:14 AM; 05/15/90 5:10:14 AM
yyyy/MM/dd HH:mm
Example: 1990/01/15 10:10; 2007/11/16 10:10
MM-dd-yyyy HH:mm
Example: 01-15-1990 10:10; 05-15-1990 10:10
yyyy-MM-dd HH:mm
Example: 1990-01-15 10:10; 2007-11-16 10:10
yyyy-MM-dd’T’HH:mm:ss.SSSZ
Example: 1990-01-15T00:34:55.020+09:30; 2007-11-16T00:34:55.020+09:30
yyyy-MM-dd’T’HH:mm:ss.SSS
Example: 1990-01-15T00:34:55.020; 2007-11-16T00:34:55.020
yyyy-MM-dd’T’HH:mmZ
Example: 1990-01-15T10:10+09:30; 2007-11-16T10:10+09:30
yyyy-MM-dd’T’HH:mm
Example: 1990-01-15T10:10; 2007-11-16T10:10
dd/MM/yyyy
Example: 25/04/2023; 15/11/2023
Built-in DateTime Validations
The options property of addColumn
accepts an array of validations. Each validation has three properties:
validation_type:
the name of the validationmessage:
the message showed to the end user if the validation failsoptions:
options for the specific validation type
The validations property accepts an array of objects that contains these possible values: validation_type
, message
and options
. As the example below:
before_date
Specifies that the value must be before a certain date.
after_date
Specifies that the value must be after a certain date.
unique_case_sensitive
Specifies that the value must be unique using case-sensitive comparison.
unique_case_insensitive
Specifies that the value must be unique using case-insensitive comparison.
Built-in DateTime Transformations
The options property of addColumn
accepts an array of transformations. For the datetime transformations, you can specify one property:
transformation_type:
the name of the transformation
The transformations property accepts an array of objects that contains these possible values: transformation_type
. As the example below:
autoformat
The autoformat transformation automatically transforms the date in the column to a standardized format specified by the pattern
on the column.