Extract data using regular expressions

Generates new tags with the data extracted from one or more regular expressions.

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In detail

What it does and what it's for

Automating tasks with Botize's Text Parser allows you to extract specific data from texts using regular expressions. This integration enables the creation of tags containing lists of elements extracted according to defined patterns, streamlining processes such as extracting email addresses, numbers, or URLs from any textual content.

With this tool, you can set up automations that efficiently process texts, applying multiple regular expressions to obtain the relevant information you need. This is particularly useful for tasks like cleaning affiliate URLs in Telegram messages or extracting specific content from incoming emails.

Each new tag is a list of 1 or more items according to the regular expression used. To access the values of each tag, use the name followed by a period and the index of the element. For example {{new_tag.1}} to access the second value containing the tag.
This operation is equivalent to the command match in Javascript.

How it works

How it fits in an automated task

A Botize task pairs a trigger with one or more actions. This piece is one of them.

Pick a trigger

The event that starts the task, from this app or any other.

This action runs

Botize performs it automatically using the data the trigger delivers.

Turn it on and forget it

The task runs on its own from then on. If something's off, tweak it or we'll help you.

Setup

Customization options

Fields you can adjust when using it in your automation.

Regular Expression Examples

The following table contains a list of regular expression examples for different cases.

Extract first sentence

Text	Text 1. Text 2. Text 3.
Pattern	/(.[^\.]*)\./
Results	{{match.0}} → Text 1. {{match.1}} → Text 1

Extract the first sentence and the remaining text

Text	Text 1. Text 2. Text 3.
Pattern	/(.[^\.])\.(.)/
Results	{{match.0}} → Text 1. Text 2. Text 3. {{match.1}} → Text 1 {{match.2}} → Text 2. Text 3.

Extract the email

Text	My email address is contact@gmail.com
Pattern	/([a-zA-Z0-9._-]+@[a-zA-Z0-9._-]+\.[a-zA-Z0-9_-]+)/gi
Results	{{match.0}} → contact@gmail.com

Extract the first number

Text	The ABC 123 Song
Pattern	/^[^\d]*(\d+)/
Results	{{match.0}} → The ABC 123 {{match.1}} → 123

Extract the first word ending in '-tion'

Text	Automation is key for optimization
Pattern	/\b\w*tion\b/
Results	{{match.0}} → automation

Extract the first URL

Text	Visit my website https://abc.com/section?param=1
Pattern	/(http\|ftp\|https)://([\w_-]+(?:(?:\.[\w_-]+)+))([\w.,@?^=%&:/~+#-]*[\w@?^=%&/~+#-])/
Results	{{match.0}} → https://abc.com/section?param=1 {{match.1}} → https {{match.2}} → abc.com {{match.3}} → /section?param=1

Extract the first URL from a specified domain

Text	Visit my website https://abc.com/section?param=1 and https://xyz.com
Pattern	/https://ad\.admitad\.com/[^"\s]+/
Results	{{match.0}} → https://xyz.com