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Variables are a cornerstone of creating dynamic, reusable, and scalable automations in Jsonify. They allow you to run the same workflow logic with different inputs, personalize actions, and manage data flow effectively.

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What are Variables in Jsonify?

In Jsonify, a variable is essentially a named placeholder for a piece of data that can change. When the workflow runs, the placeholder is replaced with its actual value for that specific run or iteration. Variable names are case-sensitive.

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Why Use Variables?

  • Reusability: Build a generic workflow and use variables to adapt it to different specific inputs without duplicating the entire workflow.
  • Dynamic Operations:
    • Open different URLs based on a list.
    • Perform searches with varying keywords.
    • Instruct data extraction based on changing criteria.
    • Personalize interactions (e.g., typing a specific username).
  • Data Input: Easily feed lists of data (e.g., from a CSV, or typed in) into your workflow using the Open datasets block.
  • Data Chaining: Use data extracted by one Extract Data block as a variable input for subsequent blocks within the same processing loop (e.g., for each item in a list).

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Defining Variables: The Open datasets Block

The primary way to introduce a list of varying inputs into your workflow is through the Open datasets block.
  • Columns as Variable Names: Each column header you define in the Open datasets table becomes a variable name (e.g., company_name, product_url, search_keyword). Remember, these names are case-sensitive.
  • Rows as Value Sets: Each row in the table represents a distinct set of values for these variables. The workflow (or the part of it following Open datasets) will run once for each row.
  • Special Column Name URL: If you name a column exactly URL (case-sensitive) in the Open datasets block and provide valid, complete URLs (starting with http:// or https://) in its rows, the AI Agent will automatically open each of these URLs. In this specific case, a subsequent Open Websites block is not required to open these particular URLs. For any other column name intended to hold URLs that you want to open via the Open Websites block, ensure the values are complete URLs.
Refer to the detailed guide on the Open datasets block for configuration specifics.

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Using Variables in Other Blocks

Once defined (e.g., in Open datasets), you can use these variables in most other blocks that accept text input for their configuration.
  • Syntax: Variables are referenced using double curly braces: {{variable_name}}.
    • Make sure the variable_name inside the braces exactly matches the column header from Open datasets (including case).
  • Common Use Cases:
    • Open Websites:
      • URL: https://{{website_domain}}/products (assuming website_domain provides just the domain like example.com)
    • Search on Google:
      • Query: reviews for {{product_name}}
    • Interact with Page:
      • Action: type {{user_comment}} into 'comment_field'
      • Action: click button 'Download {{report_filename}}'
    • Extract Data (in Descriptions or Additional Instructions):
      • Description for a field: Extract the price for the item named {{item_name}}.
      • Additional Instruction: Only extract reviews that mention the brand {{brand_to_filter_by}}.
    • Find Links:
      • Description: Find the link to the contact page for {{company_name}}

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Variables from Extract Data Output

When you use an Extract Data block, the NAME you give to each attribute (e.g., product_title, reviewer_name) can act as a variable for subsequent blocks within that same iteration or loop. These are also case-sensitive.
  • Example:
    1. Open Websites (opens a category page)
    2. Find Links (finds links to all product pages, e.g., outputs product_page_url)
    3. Follow Links (configured to “Follow each link” product_page_url)
      • Now, for each product page visited:
    4. Extract Data (extracts product_name and price from the current product page)
    5. Search on Google (can use {{product_name}} from the previous step: Search for 'competitors of {{product_name}}')
This allows you to chain operations based on data extracted in real-time.

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Tips for Naming Variables

  • Descriptive: Choose names that clearly indicate what the variable represents (e.g., customer_email instead of eml).
  • Consistent: Use a consistent naming convention (e.g., snake_case like product_id, or camelCase like productId). Remember case sensitivity.
  • Avoid Spaces and Special Characters (other than underscore): Stick to letters, numbers, and underscores for maximum compatibility and clarity.

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Scope of Variables

  • Open datasets Scope: Variables defined in Open datasets are available to all subsequent blocks for each iteration (row) defined in the Open datasets block.
  • Extract Data Scope: Variables created from Extract Data field names are scoped to the current item being processed in a list or the current page for that specific iteration.
Understanding and effectively utilizing variables will dramatically increase the flexibility and power of your Jsonify workflows, allowing you to automate more complex and varied tasks with less effort.