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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