Text channel

Use the built-in Text channel to examine bulk text with Regex and extract results.

Steps

The steps you can use with Text fall into a single category: Text

Use case examples

The following are some examples of using the Text channel.

Email validation

This checks to see if a given string is a valid email:

^[^@ ]+@[^@ ]+\.[^@ \.]{2,}$

Date validation

This checks for a valid date format:

\d{4}-\d{2}-\d{2}

In this example, the code validates if given date string matches this pattern: YYYY–MM–DD, for example, 2019–12–18.

Credit card number validation

These chec for the correct format of different credit cards:

Visa: ^4[0–9]{12}(?:[0–9]{3})?$

American Express: ^3[47][0–9]{13}$

MasterCard: ^(?:5[1–5][0–9]{2}|222[1–9]|22[3–9][0–9]|2[3–6][0–9]{2}|27[01][0–9]|2720)[0–9]{12}$

Check document for emails

In this use case, whenever a record is created in Quickbase we can perform a check if it’s an email in the correct format and based on that we can do whatever we want, for example, we can send an email to an admin that we created a record with an incorrect format:

[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}

This checks for strings in the type of: xxxxxx@xxx.xx or .xxx

Looping through field values in a pipeline

You can use the Text channel to Find All Matches to a Regex using the following Regex:

([^;]+) 

You can use the multi-select option to separates values using a semi-colon. Otherwise, you can change the semi-colon to a comma in the middle of the regular expression, since the comma is the delimiter in your use case:

([^,]+)

For each match/Regex filtered group (because it's split by a semi-colon or a comma in your case), you can then use each group to create a new record.

So in the subsequent create record step, map the regex step's Group 1 to the new table:

{{b.group_1}}

See screenshots below for reference.