process_batch_data

Process large batches of SEO data concurrently by applying specified operations (e.g., 'upper', 'lower', 'reverse') to items, ensuring efficient parallel execution and ordered results.

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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