process_batch_data

Process multiple data batches concurrently using keyword argument dictionaries. Enables efficient parallelization for operations like text transformations, with integrated exception handling and logging for SEO data analysis.

Instructions

Parallelized version of process_batch_data.

This function accepts a list of keyword argument dictionaries and executes process_batch_data concurrently for each set of arguments.

Original function signature: process_batch_data(items: List, operation: str)

Args: kwargs_list (List[Dict[str, Any]]): A list of dictionaries, where each dictionary provides the keyword arguments for a single call to process_batch_data.

Returns: List[Any]: A list containing the results of each call to process_batch_data, in the same order as the input kwargs_list.

Original docstring: Process a batch of data items.

This is an example of a tool that benefits from parallelization.
It will be automatically decorated with the parallelize decorator
in addition to exception handling and logging.

Args:
    items: List of strings to process
    operation: Operation to perform ('upper', 'lower', 'reverse')
    
Returns:
    Processed items with metadata

Input Schema

Name	Required	Description	Default
`kwargs_list`	Yes

Input Schema (JSON Schema)

{
  "properties": {
    "kwargs_list": {
      "items": {
        "additionalProperties": true,
        "type": "object"
      },
      "title": "Kwargs List",
      "type": "array"
    }
  },
  "required": [
    "kwargs_list"
  ],
  "title": "process_batch_dataArguments",
  "type": "object"
}

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