feat: add Parallel Execution

[patelheet30]

• Add comprehensive tests for all three backends with graceful fallback
• Add ParallelExecutor class with multiprocessing, threading, and joblib backends
• Modify report() method to support parallel, n_jobs, and backend parameters
• Implement automatic parallelisation detection based on check count and DataFrame size
• Add joblib as optional dependency for data science optimised parallelisation
• Update documentation with backend comparison and examples

BREAKING CHANGE: None (backward compatible, joblib is optional)