This documentation provides a comprehensive explanation of the string functions available in our system.

DATA_SELECT Function: #data_select_function
REGEX_REPLACE Function: #regex_replace_function
EXTRACT_REMOVE Function (and Related Functions): #extract_remove_function

DATA_SELECT Function

The DATA_SELECT function allows you to extract specific information from data formatted in JSON, XML, or HTML. It takes two arguments:

Data Type: This specifies the format of your data, either "JSON", "XML", or "HTML".
Selector: This defines the path to the desired information within the data. It uses a dot notation similar to navigating directories on a computer.

Key Points:

DATA_SELECT(JSON)[data.array~2.name]

This example extracts the value of the "name" property within the second element of the "array" property from JSON data.

The ~ symbol indicates an array position (e.g., array~2 refers to the second element).
You can use nested selectors to navigate deeper within the data structure.

JSON Example:

Syntax:

DATA_SELECT(JSON)[data.array~2.name]

JSON:

{
  "data": {
    "array": [
      { "name": "Item 1" },
      { "name": "Item 2" },
      { "name": "Item 3" }
    ]
  }
}

Explanation:

We want to extract the value of the "name" property within the second element (~2) of the "array" property.
The selector navigates through the JSON structure using dot notation.

Result: Using the DATA_SELECT(JSON)[data.array~2.name] function would return the string: "Item 3".

HTML Example:

Syntax:

DATA_SELECT(HTML)[html.body.table.tr~2.td~1.text.innerText]

HTML:

<!DOCTYPE html>
<html>
<body>
  <table>
    <tr>
      <th>Name</th>
      <th>Description</th>
    </tr>
    <tr>
      <td>Item 1</td>
      <td>A great product</td>
    </tr>
    <tr>
      <td>Item 2</td>
      <td>This is the content we want to extract</td>
    </tr>
    <tr>
      <td>Item 3</td>
      <td>Another product</td>
    </tr>
  </table>
</body>
</html>

Explanation:

We want to extract the text content from the second table row (table) in the HTML.
Inside that row, we target the first table cell (tr~2.td~1).
Finally, we use .text.innerText to specify that we want the inner text content of that cell.

Result:

Using the provided DATA_SELECT function would extract the value: "This is the content we want to extract".

XML Example:

Syntax:

DATA_SELECT(XML)[data.array.item[2].name]

XML:

<data>
  <array>
    <item>
      <name>Item 1</name>
    </item>
    <item>
      <name>Item 2</name>
    </item>
    <item>
      <name>Item 3</name>
    </item>
  </array>
</data>

Explanation:

We want to extract the text content of the "name" element within the second ([2]) child element (item) of the parent element (array) named "data".
The selector uses square brackets to specify the position of the child element within its parent.

Result: Using the DATA_SELECT(XML)[data.array.item[2].name] function would return the string: "Item 3".

REGEX_REPLACE Function

The REGEX_REPLACE function helps you modify text by searching for a specific pattern (using regular expressions) and replacing it with another value. It takes two arguments:

Regex Pattern: This defines the pattern you want to find in the text. Regular expressions are a powerful tool for complex text matching, but there are resources available online for learning the basics.
Replacement Value: This specifies what you want to replace the matched pattern with. It can be empty (to remove the pattern) or any other text.

Key Points:

REGEX_REPLACE([^a-z])[""] {{ [F].[description] }}

This example removes all characters except lowercase letters ([a-z]) from the content stored in the field named "description" associated with variable [F].

Regular expressions can be complex, so refer to online resources for detailed explanations.
The [^] syntax within the pattern matches any character except those listed inside the brackets.

Example:

Syntax:

REGEX_REPLACE([pattern])[replacement]{{content}}

Text:

We are having a sale on products this weekend!  SALE! SALE!

Explanation:

We want to remove all instances of the word "SALE!" (including the exclamation mark) from the text.

REGEX_REPLACE Function:

Pattern: SALE! (case-sensitive)
- This pattern matches the literal text "SALE!" exactly.
Replacement: "" (empty string)
- This replaces all matched patterns with nothing, effectively removing them.

Final Code:

REGEX_REPLACE(SALE!)[""]{{We are having a sale on products this weekend!  SALE! SALE!}}

Result with Function:

Using the REGEX_REPLACE(SALE!)[""]{{We are having a sale on products this weekend! SALE! SALE!}} function would modify the text to: "We are having a sale on products this weekend! " (Note the space after the weekend).

EXTRACT Functions:

The EXTRACT_REMOVE function, along with the related functions EXTRACT_ALL, EXTRACT_FIRST, and EXTRACT_LAST, allow you to manipulate text based on a predefined list of values. These functions require you to create a list (named using the List_ prefix) containing the values you want to target.

EXTRACT_REMOVE: This function removes all occurrences of the values in your list from the text.
EXTRACT_ALL: This function joins all occurrences of the values in your list, separated by the delimiter defined for the list (usually a comma ,).
EXTRACT_FIRST: This function extracts the first occurrence of a value from your list within the text.
EXTRACT_LAST: This function extracts the last occurrence of a value from your list within the text.

Key Points:

List_Colors = Red, Green, Blue
EXTRACT_REMOVE(List_Colors) {{ [F].[description] }}

This example removes the words "Red", "Green", and "Blue" from the content stored in the field named "description" associated with variable [F].

You need to define your lists separately using the List_ prefix followed by the list name and the values separated by commas.
The chosen EXTRACT function determines how the list values are handled within the text.

Example:

Syntax:

EXTRACT_REMOVE(List_Name){{content}}

Text:

This product is free for a limited time, don't miss this chance! Get yours today or while supplies last.

Explanation:

We want to remove promotional phrases like "free for a limited time", "don't miss this chance", "get yours today", and "while supplies last".

List Creation:

Before using EXTRACT_REMOVE, you need to define a list containing the words or phrases you want to remove. You can create one by navigating to app.godatafeed.com/product#/product/lists.

Here, we'll name it List_Promotions.

List_Promotions = free for a limited time, don't miss this chance, get yours today, while supplies last

EXTRACT_REMOVE Function:

The function uses the list you created (separated by commas in this case).

Final Code:

List_Promotions = free for a limited time, don't miss this chance, get yours today, while supplies last
EXTRACT_REMOVE(List_Promotions){{This product is free for a limited time, don't miss this chance! Get yours today or while supplies last.}}

Result with Function:

Using the List_Promotions and EXTRACT_REMOVE function together would modify the text to: "This product is ." (Note the period at the end). It removes all promotional phrases defined in the list.

Additional Notes:

This documentation provides a basic overview of the functions. For more advanced usage scenarios, refer to the code comments within the system.
If you encounter any issues or have further questions, feel free to consult the system documentation or contact support.

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String Function Documentation 2024

Table of Contents

DATA_SELECT Function

Key Points:

JSON Example:

HTML Example:

XML Example:

REGEX_REPLACE Function

Key Points:

Example:

EXTRACT Functions:

Key Points:

Example:

Additional Notes:

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Table of Contents

DATA_SELECT Function

Key Points:

JSON Example:

HTML Example:

XML Example:

REGEX_REPLACE Function

Key Points:

Example:

EXTRACT Functions:

Key Points:

Example:

Additional Notes:

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