Adding and importing inputs in a configuration

Most Captain Data workflows require inputs to run. Here's how you can add or import inputs for your workflows effectively:

Add Inputs

You can add inputs in two ways:

1. One-by-One:

   • Copy and paste the URL for each input.

   • Add as many inputs as you want by clicking on "+ New".

   • A helpful how-to guide is available in the right panel if you need assistance 🙌.
     

2. Import from a File:

   • Upload inputs from a CSV or XLS file with any set of columns.

   • Drag and drop your file into the upload zone.

   • Ensure the file is correctly formatted for smooth processing.

Important File Formatting

To ensure your file is processed correctly:

• Include the required input column name (e.g., linkedin_profile_url).

• Find the required column name in the Workflow Configuration:

  • Click on the three dots next to the first step.

  • Select Input to view the expected key.
    
    
    
    

    You can drag & drop a file in the zone.

    

    The column is perfectly mapped and you visualize all the imported data!

    If you have an error, you probably don't have the appropriate headers on your CSV file.

    You can also filter columns you want to see:

    

     

Once uploaded, the column will be mapped perfectly, and you can visualize all the imported data.

If you encounter an error, such as:

"An error occurred while validating your inputs, please check your file or contact us."

Make sure your file includes the appropriate headers.

Recommended Input Limits

For optimal performance:

• Single-column files (e.g., linkedin_profile_url): Limit to 4,000 rows.

• Files with metadata (additional columns): Limit to 1,000 rows or less if it doesn't work.

Handling Large CSV Files

If your file exceeds these limits, split it into smaller files:

• Single-column files: Up to 4,000 rows.

• Files with metadata: Up to 1,000 rows.

This ensures the platform processes your data efficiently and avoids delays or errors.

Why Input Size Matters

Actions like Extract LinkedIn Profile generate large volumes of output data. Managing input size prevents performance issues and ensures smooth workflow execution.

If in doubt, provide a sample CSV for review to verify its compatibility.

Adding Metadata

Additionally, to the primary column, you can add as many columns as you want as "meta".

They will be mapped as extra column:

Columns are mapped as-is, e.g. we do not change them.

⚠️  We do recommend though that you use first_name instead of First Name.
(No capital letters and no spaces)

You will find this data in the meta column, all in JSON at the first step, and last step:


You can now unstructured your metadata! To do so, you just need to activate the Metadata Iterator option in your job’s launch settings > Configure output data > Inputs Meta Mapping, which will split each metadata into single columns:

Data Validation

Some workflows require additional data validation.

For example here it absolutely needs a linkedin_profile_url to be working so it gives you an error:

If you need, you can filter only invalid inputs by click "Show X input(s) with error(s)".

And if you hit the "Clear" button while selecting only inputs in errors, it will remove only the wrong inputs:

Google Sheets

If you're working with Google Sheets, you can download the spreadsheet as a CSV.