Introduces a new ProgressBarManager class to manage progress bars for both batch and non-batch execution. This includes methods for creating single and nested progress bars, as well as updating batch progress bars, improving user experience during long-running tasks.

- Refactored `run` function from repeated async, executor, and engine logic.
- Changed `as_completed` from async to a regular function for better compatibility.
- Added `process_futures` to handle futures with optional progress tracking.

- Refactored Executor to utilize new async_utils and ProgressBarManager for improved composition
- Refactored run_async_tasks to utilize ProgressBarManager for improved progress tracking.
- Modified tests to validate the new behavior functions

- Introduced a locking mechanism to ensure thread-safe job processing.
- Added `_jobs_processed` attribute to maintain consistent job indexing across multiple runs.
- Implemented `clear_jobs` method to reset job indices.
- Updated tests to verify exception handling and job indexing after clearing jobs.
- Adjusted Jupyter notebook tests for consistency in results retrieval.

…sted Transformation or Parallel procedures

- The apply_transforms() function has been updated to handle different types of transformations recursively:
  If transforms is a list, it recursively applies each transform in the list.
  If transforms is a Parallel instance, it recursively applies the transformations contained within the Parallel object.
  If transforms is a BaseGraphTransformation, it generates an execution plan (a list of coroutines), gets a description, and then runs the coroutines asynchronously using run_async_tasks().
  If transforms is none of the above, it raises a ValueError indicating an invalid type.
- Move apply_nest_asyncio to async_utils for better organization
- Updated the Parallel class to support transformations with improved type hints.
- Added unit tests

…ug logging

…e Executor

- nest_asyncio has internal checks for whether it is applied, rely on those
- Ensured apply_nest_asyncio is called in the Executor class to handle nested event loops.

- Removed optional progress bar parameter from process_futures.
- Updated calls to process_futures to handle progress bar updates directly.
- Cleaned up error handling logic for results in async processing.

- Replaced event loop checks with a unified async wrapper for scoring.
- Simplified error handling and callback management.
- Ensured compatibility with Jupyter environments by applying nest_asyncio directly.

…ctly.