import functools
import time
import logging
import warnings
import threading
import traceback
import sys
import json
import random
import subprocess
import inspect
import cProfile
import io
from collections import defaultdict
from typing import Any, Callable, TypeVar, cast, Tuple, Dict

F = TypeVar("F", bound=Callable[..., Any])

# Helper function to print output in a uniform structured format.
def structured_print(message: str, title: str = "OUTPUT", line_width: int = 60) -> None:
    header = "=" * line_width
    print(f"\n{header}\n{title:^{line_width}}\n{message}\n{header}\n")

class DecoratorFactory:
    """
    A comprehensive decorator toolkit with 100 decorators for production-grade applications.
    Use the list_decorators() method to see the names and descriptions.
    """

    # A dictionary to hold decorator names and their descriptions.
    decorators_info = {
        "deprecated": "Marks a function as deprecated and prints a structured deprecation notice.",
        "simple_warning": "Issues a simple warning message when a function is called.",
        "error_handling": "Catches exceptions, logs an error message, and re-raises.",
        "log": "Logs function calls (inputs and outputs) to console or file.",
        "debug": "Prints function arguments and return value with structured output.",
        "measure_time": "Measures and prints the execution time with structured output.",
        "singleton": "Makes a class a singleton.",
        "retry": "Retries a function call if an exception is raised.",
        "cache": "Caches function return values.",
        "count_calls": "Counts the number of times a function is called.",
        "synchronized": "Ensures thread-safe execution using a lock.",
        "validate_types": "Enforces type hints at runtime.",
        "authorize": "Checks authorization before function execution.",
        "validate_input": "Validates input arguments using a validator function.",
        "ensure_output": "Validates the function's output using a validator.",
        "profile": "Profiles a function using cProfile and prints stats.",
        "timeout": "Enforces a timeout on function execution (Unix signal based).",
        "rate_limit": "Limits number of calls per time period.",
        "transactional": "Wraps a function call in a simulated transaction.",
        "retry_with_backoff": "Retries with exponential backoff if the function fails.",
        "catch_exception_and_return": "Returns a default value if an exception occurs.",
        "retry_on_exception": "Retries on a specific exception type.",
        "count_execution_time": "Logs the execution time using a high-resolution timer.",
        "lazy_property": "Converts a method into a lazy property (computed once).",
        "property_cache": "Caches the result of a property method.",
        "measure_memory": "Measures memory usage (requires psutil).",
        "log_arguments": "Logs function arguments in a structured format.",
        "suppress_exceptions": "Suppresses exceptions and returns a default value.",
        "repeat": "Repeats a function call n times and returns the last result.",
        "memoize": "Caches results (alias for cache).",
        "trace": "Prints the stack trace on function entry.",
        "simulate_long_running": "Adds an artificial delay before function execution.",
        "record_history": "Records call history (arguments and results) into a list.",
        "auto_retry": "Automatically retries a function without delay.",
        "require_arguments": "Ensures that specified arguments are provided.",
        "convert_arguments": "Converts arguments using a provided conversion mapping.",
        "log_execution": "Logs execution time and result with a logger.",
        "async_wrapper": "Runs the function asynchronously in a separate thread.",
        "timeout_thread": "Implements a timeout using thread join.",
        "benchmark": "Runs a function multiple times and reports the average time.",
        "call_counter": "Counts calls using a closure variable.",
        "lazy_evaluation": "Memoizes a function’s result for lazy evaluation.",
        "delay_execution": "Delays function execution by a specified number of seconds.",
        "repeat_until_success": "Repeats until the function returns a truthy value.",
        "fallback": "Calls a fallback function if the main function fails.",
        "enforce_return_type": "Ensures the return type matches an expected type.",
        "pre_post": "Executes hooks before and after function execution.",
        "enforce_constraints": "Enforces custom constraints on function arguments.",
        "capture_output": "Captures printed output from a function and displays it in structured format.",
        "transform_output": "Transforms the output using a provided function.",
        "expiration_cache": "Caches results with an expiration time (TTL).",
        "concurrent": "Runs a function concurrently in multiple threads and aggregates results.",
        "thread_safe": "Ensures thread safety using a reentrant lock.",
        "ignore_none": "If function returns None, calls a backup function.",
        "fallback_if_none": "Returns a default value if the function returns None.",
        "precondition": "Checks preconditions before function execution.",
        "postcondition": "Checks postconditions after function execution.",
        "iterate_over": "Applies a function to each element of an iterable argument.",
        "bulk_operation": "Vectorizes a function over a list of inputs.",
        "memoize_with_expiration": "Caches results with a TTL (alias for expiration_cache).",
        "capture_exceptions": "Captures exceptions and stores them in a list.",
        "report_exceptions": "Reports exceptions to an external function.",
        "log_exceptions": "Logs exceptions using a logger.",
        "ignore_warnings": "Suppresses warnings during function execution.",
        "enforce_documentation": "Ensures that the function has a docstring.",
        "limit_recursion": "Limits recursion depth for a function.",
        "flatten_arguments": "Flattens nested iterable arguments.",
        "check_range": "Ensures a numeric argument falls within a given range.",
        "convert_output": "Converts the function’s output using a converter.",
        "round_output": "Rounds numeric outputs to a given precision.",
        "filter_arguments": "Removes unwanted arguments before passing them to the function.",
        "preserve_metadata": "Preserves metadata of a function (dummy example).",
        "decorate_class_methods": "Applies a decorator to all methods of a class.",
        "instance_tracker": "Tracks all instances of a class.",
        "method_logger": "Logs calls to class methods.",
        "reentrant": "Ensures function reentrancy using a reentrant lock.",
        "serialize_arguments": "Serializes function arguments to JSON for logging.",
        "sanitize_input": "Sanitizes string inputs (dummy implementation).",
        "enforce_max_args": "Limits the number of arguments allowed.",
        "require_non_null": "Ensures that no argument is None.",
        "time_limit": "Limits function execution time using threading.",
        "debug_trace": "Traces function execution (simple version).",
        "print_call_stack": "Prints the call stack on each function call.",
        "inject_dependencies": "Provides default dependencies if missing.",
        "auto_retry_with_log": "Retries automatically with logging for each attempt.",
        "auto_reconnect": "Implements dummy reconnect logic for network calls.",
        "secure_execution": "Executes the function in a secure context (dummy).",
        "resource_lock": "Simulates resource locking using a lock.",
        "force_async": "Forces function execution to run asynchronously.",
        "fallback_chain": "Chains multiple fallback functions.",
        "apply_hooks": "Executes pre and post hooks around a function.",
        "instrument": "Instruments function calls for metrics collection.",
        "run_in_subprocess": "Runs the function in a separate subprocess.",
        "measure_cpu_time": "Measures the CPU time consumed by a function.",
        "collect_metrics": "Collects and prints execution metrics.",
        "save_state": "Saves and restores state (dummy example).",
        "retry_with_jitter": "Retries with exponential backoff plus random jitter.",
        "audit": "Records an audit trail for function calls.",
        "comprehensive_logger": "Combines logging, timing, and error handling.",
        "comprehensive_debugger": "Logs, times, and handles errors with detailed output."
    }

    # -------------------- DECORATORS --------------------

    # 1. Deprecated
    @staticmethod
    def deprecated(reason: str, recommendation: str = "Please update your code accordingly.") -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                with warnings.catch_warnings():
                    warnings.simplefilter("always", DeprecationWarning)
                    line_width = 60
                    header = "=" * line_width
                    key_width = 15
                    warnings.formatwarning = lambda message, category, filename, lineno, line: (
                        f"\n{header}\n"
                        f"{'DEPRECATION NOTICE':^{line_width}}\n"
                        f"{'Function'.ljust(key_width)}: {func.__name__}\n"
                        f"{'Location'.ljust(key_width)}: {filename}:{lineno}\n"
                        f"{'Reason'.ljust(key_width)}: {message}\n"
                        f"{'Recommendation'.ljust(key_width)}: {recommendation}\n"
                        f"{header}\n"
                    )
                    warnings.warn(reason, category=DeprecationWarning, stacklevel=2)
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 2. Simple Warning
    @staticmethod
    def simple_warning(message: str) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                warnings.warn(message, UserWarning, stacklevel=2)
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 3. Error Handling
    @staticmethod
    def error_handling(error_message: str = "An error occurred") -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    logging.error(f"{error_message}: {e}")
                    raise
            return cast(F, new_func)
        return decorator

    # 4. Log (to console or file)
    @staticmethod
    def log(save_to_file: bool = False, filename: str = "app.log") -> Callable[[F], F]:
        def decorator(func: F) -> F:
            logger = logging.getLogger(func.__module__)
            logger.setLevel(logging.INFO)
            if save_to_file:
                handler = logging.FileHandler(filename)
                handler.setLevel(logging.INFO)
                logger.addHandler(handler)
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                logger.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}")
                result = func(*args, **kwargs)
                logger.info(f"{func.__name__} returned {result}")
                return result
            return cast(F, new_func)
        return decorator

    # 5. Debug – structured print of input and output
    @staticmethod
    def debug() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                structured_print(f"Arguments: {args}, {kwargs}", title=f"DEBUG: {func.__name__} Input")
                result = func(*args, **kwargs)
                structured_print(f"Result: {result}", title=f"DEBUG: {func.__name__} Output")
                return result
            return cast(F, new_func)
        return decorator

    # 6. Measure Time – uses structured print for timing info
    @staticmethod
    def measure_time() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                start = time.time()
                result = func(*args, **kwargs)
                elapsed = time.time() - start
                structured_print(f"Executed in {elapsed:.4f} seconds", title=f"TIME: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 7. Singleton – class decorator, no terminal output.
    @staticmethod
    def singleton(cls: type) -> Callable[[], Any]:
        instances = {}
        @functools.wraps(cls)
        def get_instance():
            if cls not in instances:
                instances[cls] = cls()
            return instances[cls]
        return get_instance

    # 8. Retry – prints retry attempts in structured format.
    @staticmethod
    def retry(retries: int = 3, delay: float = 1.0) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                last_exc = None
                for attempt in range(retries):
                    try:
                        return func(*args, **kwargs)
                    except Exception as e:
                        last_exc = e
                        structured_print(f"Attempt {attempt+1}/{retries} for {func.__name__} failed: {e}", title="RETRY")
                        time.sleep(delay)
                raise last_exc
            return cast(F, new_func)
        return decorator

    # 9. Cache – caches function results.
    @staticmethod
    def cache() -> Callable[[F], F]:
        local_cache = {}
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                key = (args, frozenset(kwargs.items()))
                if key not in local_cache:
                    local_cache[key] = func(*args, **kwargs)
                return local_cache[key]
            return cast(F, new_func)
        return decorator

    # 10. Count Calls – prints call count in structured format.
    @staticmethod
    def count_calls() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            func.call_count = 0
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                func.call_count += 1
                structured_print(f"Called {func.call_count} times", title=f"COUNT: {func.__name__}")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 11. Synchronized – ensures thread-safe execution.
    @staticmethod
    def synchronized(lock: threading.Lock = None) -> Callable[[F], F]:
        if lock is None:
            lock = threading.Lock()
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                with lock:
                    return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 12. Validate Types – enforces type hints.
    @staticmethod
    def validate_types() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            sig = inspect.signature(func)
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                bound = sig.bind(*args, **kwargs)
                bound.apply_defaults()
                for name, value in bound.arguments.items():
                    if name in func.__annotations__:
                        expected = func.__annotations__[name]
                        if not isinstance(value, expected):
                            raise TypeError(f"Argument '{name}' must be of type {expected}")
                result = func(*args, **kwargs)
                if 'return' in func.__annotations__:
                    if not isinstance(result, func.__annotations__['return']):
                        raise TypeError(f"Return value must be of type {func.__annotations__['return']}")
                return result
            return cast(F, new_func)
        return decorator

    # 13. Authorize – checks authorization.
    @staticmethod
    def authorize(check: Callable[..., bool]) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                if not check(*args, **kwargs):
                    raise PermissionError("Not authorized")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 14. Validate Input – validates input arguments.
    @staticmethod
    def validate_input(validator: Callable[..., bool]) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                if not validator(*args, **kwargs):
                    raise ValueError("Input validation failed")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 15. Ensure Output – validates output.
    @staticmethod
    def ensure_output(validator: Callable[[Any], bool]) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = func(*args, **kwargs)
                if not validator(result):
                    raise ValueError("Output validation failed")
                return result
            return cast(F, new_func)
        return decorator

    # 16. Profile – profiles a function.
    @staticmethod
    def profile(sort_by: str = "cumtime") -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                profiler = cProfile.Profile()
                profiler.enable()
                result = func(*args, **kwargs)
                profiler.disable()
                s = io.StringIO()
                import pstats
                ps = pstats.Stats(profiler, stream=s).sort_stats(sort_by)
                ps.print_stats()
                structured_print(s.getvalue(), title=f"PROFILE: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 17. Timeout – Unix signal based timeout.
    @staticmethod
    def timeout(seconds: int, error_message="Function call timed out") -> Callable[[F], F]:
        import signal
        def decorator(func: F) -> F:
            def _handle_timeout(signum, frame):
                raise TimeoutError(error_message)
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                old_handler = signal.signal(signal.SIGALRM, _handle_timeout)
                signal.alarm(seconds)
                try:
                    result = func(*args, **kwargs)
                finally:
                    signal.alarm(0)
                    signal.signal(signal.SIGALRM, old_handler)
                return result
            return cast(F, new_func)
        return decorator

    # 18. Rate Limit – limits calls per time period.
    @staticmethod
    def rate_limit(calls: int, period: float) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            last_reset = [time.time()]
            call_count = [0]
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                now = time.time()
                if now - last_reset[0] > period:
                    last_reset[0] = now
                    call_count[0] = 0
                if call_count[0] >= calls:
                    raise Exception("Rate limit exceeded")
                call_count[0] += 1
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 19. Transactional – simulates a transaction.
    @staticmethod
    def transactional(transaction_start: Callable, transaction_end: Callable[[bool], None]) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                transaction_start()
                try:
                    result = func(*args, **kwargs)
                    transaction_end(True)
                except Exception as e:
                    transaction_end(False)
                    raise e
                return result
            return cast(F, new_func)
        return decorator

    # 20. Retry with Backoff – exponential backoff.
    @staticmethod
    def retry_with_backoff(times: int = 3, initial_delay: float = 1, backoff: float = 2) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                delay = initial_delay
                for attempt in range(times):
                    try:
                        return func(*args, **kwargs)
                    except Exception as e:
                        if attempt == times - 1:
                            raise
                        structured_print(f"Retry with backoff attempt {attempt+1} for {func.__name__} failed: {e}",
                                           title="RETRY WITH BACKOFF")
                        time.sleep(delay)
                        delay *= backoff
            return cast(F, new_func)
        return decorator

    # 21. Catch Exception and Return – returns default on error.
    @staticmethod
    def catch_exception_and_return(default: Any = None) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                try:
                    return func(*args, **kwargs)
                except Exception:
                    return default
            return cast(F, new_func)
        return decorator

    # 22. Retry on Exception – retry for specific exception.
    @staticmethod
    def retry_on_exception(times: int = 3, exception_type: Exception = Exception, delay: float = 0) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                for attempt in range(times):
                    try:
                        return func(*args, **kwargs)
                    except exception_type:
                        if attempt == times - 1:
                            raise
                        if delay:
                            time.sleep(delay)
            return cast(F, new_func)
        return decorator

    # 23. Count Execution Time – high-resolution timer.
    @staticmethod
    def count_execution_time() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                start = time.perf_counter()
                result = func(*args, **kwargs)
                end = time.perf_counter()
                structured_print(f"Execution time: {end - start:.6f} seconds", title=f"TIME COUNT: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 24. Lazy Property – computes property on first access.
    @staticmethod
    def lazy_property(func: Callable) -> property:
        attr_name = "_lazy_" + func.__name__
        @property
        @functools.wraps(func)
        def new_prop(self):
            if not hasattr(self, attr_name):
                setattr(self, attr_name, func(self))
            return getattr(self, attr_name)
        return new_prop

    # 25. Property Cache – caches a property’s result.
    @staticmethod
    def property_cache(func: Callable) -> property:
        attr_name = "_cache_" + func.__name__
        @property
        @functools.wraps(func)
        def new_prop(self):
            if not hasattr(self, attr_name):
                setattr(self, attr_name, func(self))
            return getattr(self, attr_name)
        return new_prop

    # 26. Measure Memory – requires psutil.
    @staticmethod
    def measure_memory() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                import os, psutil
                process = psutil.Process(os.getpid())
                mem_before = process.memory_info().rss
                result = func(*args, **kwargs)
                mem_after = process.memory_info().rss
                structured_print(f"Memory increased by {mem_after - mem_before} bytes", title=f"MEMORY: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 27. Log Arguments – structured print of arguments.
    @staticmethod
    def log_arguments() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                structured_print(f"Arguments: {args}, {kwargs}", title=f"LOG ARGS: {func.__name__}")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 28. Suppress Exceptions – returns default on exception.
    @staticmethod
    def suppress_exceptions(default: Any = None) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    logging.error(f"Suppressed exception in {func.__name__}: {e}")
                    return default
            return cast(F, new_func)
        return decorator

    # 29. Repeat – repeats function call n times.
    @staticmethod
    def repeat(n: int = 2) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = None
                for i in range(n):
                    structured_print(f"Iteration {i+1} of {n}", title=f"REPEAT: {func.__name__}")
                    result = func(*args, **kwargs)
                return result
            return cast(F, new_func)
        return decorator

    # 30. Memoize – alias for cache.
    @staticmethod
    def memoize() -> Callable[[F], F]:
        return DecoratorFactory.cache()

    # 31. Trace – prints stack trace.
    @staticmethod
    def trace() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                s = io.StringIO()
                traceback.print_stack(file=s)
                structured_print(s.getvalue(), title=f"TRACE: {func.__name__}")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 32. Simulate Long Running – delays execution.
    @staticmethod
    def simulate_long_running(delay: float = 2.0) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                structured_print(f"Delaying for {delay} seconds...", title="SIMULATE LONG RUNNING")
                time.sleep(delay)
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 33. Record History – records call history in a list.
    @staticmethod
    def record_history(history: list) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = func(*args, **kwargs)
                history.append({'args': args, 'kwargs': kwargs, 'result': result})
                structured_print(f"Recorded call: {history[-1]}", title=f"HISTORY: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 34. Auto Retry – retry without delay.
    @staticmethod
    def auto_retry(retries: int = 3) -> Callable[[F], F]:
        return DecoratorFactory.retry(retries, delay=0)

    # 35. Require Arguments – ensure specific arguments are provided.
    @staticmethod
    def require_arguments(*required_args) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                names = inspect.getfullargspec(func).args
                arg_dict = dict(zip(names, args))
                for req in required_args:
                    if req not in arg_dict and req not in kwargs:
                        raise ValueError(f"Missing required argument: {req}")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 36. Convert Arguments – converts arguments based on mapping.
    @staticmethod
    def convert_arguments(conversions: dict) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                new_args = []
                names = inspect.getfullargspec(func).args
                for i, arg in enumerate(args):
                    key = names[i] if i < len(names) else None
                    if key in conversions:
                        new_args.append(conversions[key](arg))
                    else:
                        new_args.append(arg)
                for key, conv in conversions.items():
                    if key in kwargs:
                        kwargs[key] = conv(kwargs[key])
                return func(*new_args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 37. Log Execution – logs execution time and result.
    @staticmethod
    def log_execution(logger: logging.Logger = None) -> Callable[[F], F]:
        if logger is None:
            logger = logging.getLogger("execution")
            logger.setLevel(logging.INFO)
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                start = time.time()
                result = func(*args, **kwargs)
                elapsed = time.time() - start
                logger.info(f"{func.__name__} executed in {elapsed:.4f} seconds, result: {result}")
                return result
            return cast(F, new_func)
        return decorator

    # 38. Async Wrapper – runs function asynchronously.
    @staticmethod
    def async_wrapper() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                thread = threading.Thread(target=func, args=args, kwargs=kwargs)
                thread.start()
                structured_print(f"Started async thread for {func.__name__}", title="ASYNC WRAPPER")
                return thread
            return cast(F, new_func)
        return decorator

    # 39. Timeout Thread – thread join based timeout.
    @staticmethod
    def timeout_thread(seconds: int) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = [None]
                exception = [None]
                def target():
                    try:
                        result[0] = func(*args, **kwargs)
                    except Exception as e:
                        exception[0] = e
                thread = threading.Thread(target=target)
                thread.start()
                thread.join(seconds)
                if thread.is_alive():
                    raise TimeoutError("Function call timed out")
                if exception[0]:
                    raise exception[0]
                return result[0]
            return cast(F, new_func)
        return decorator

    # 40. Benchmark – runs function multiple times.
    @staticmethod
    def benchmark(iterations: int = 10) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                total = 0
                result = None
                for i in range(iterations):
                    start = time.time()
                    result = func(*args, **kwargs)
                    elapsed = time.time() - start
                    total += elapsed
                    structured_print(f"Iteration {i+1}: {elapsed:.6f} sec", title=f"BENCHMARK: {func.__name__}")
                structured_print(f"Average time: {total / iterations:.6f} sec", title=f"BENCHMARK RESULT: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 41. Call Counter (Alternative) – using closure variable.
    @staticmethod
    def call_counter() -> Callable[[F], F]:
        counter = 0
        def decorator(func: F) -> F:
            nonlocal counter
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                nonlocal counter
                counter += 1
                structured_print(f"Called {counter} times (alternative)", title=f"CALL COUNTER: {func.__name__}")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 42. Lazy Evaluation – memoizes result.
    @staticmethod
    def lazy_evaluation() -> Callable[[F], F]:
        cache = {}
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                key = (args, frozenset(kwargs.items()))
                if key not in cache:
                    cache[key] = func(*args, **kwargs)
                return cache[key]
            return cast(F, new_func)
        return decorator

    # 43. Delay Execution – delays execution by specified seconds.
    @staticmethod
    def delay_execution(delay: float = 1.0) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                structured_print(f"Delaying execution for {delay} seconds", title=f"DELAY: {func.__name__}")
                time.sleep(delay)
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 44. Repeat Until Success – repeats until truthy result.
    @staticmethod
    def repeat_until_success(max_attempts: int = 5, delay: float = 0.5) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                for i in range(max_attempts):
                    result = func(*args, **kwargs)
                    if result:
                        structured_print(f"Success on attempt {i+1}", title=f"REPEAT UNTIL SUCCESS: {func.__name__}")
                        return result
                    time.sleep(delay)
                return result
            return cast(F, new_func)
        return decorator

    # 45. Fallback – calls fallback function if main fails.
    @staticmethod
    def fallback(fallback_func: Callable) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                try:
                    return func(*args, **kwargs)
                except Exception:
                    structured_print("Falling back to alternate function", title=f"FALLBACK: {func.__name__}")
                    return fallback_func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 46. Enforce Return Type – checks return type.
    @staticmethod
    def enforce_return_type(expected_type: type) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = func(*args, **kwargs)
                if not isinstance(result, expected_type):
                    raise TypeError(f"Return value of {func.__name__} must be {expected_type}")
                return result
            return cast(F, new_func)
        return decorator

    # 47. Pre and Post Hooks – runs hooks before and after.
    @staticmethod
    def pre_post(pre: Callable = lambda: None, post: Callable = lambda: None) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                pre()
                result = func(*args, **kwargs)
                post()
                return result
            return cast(F, new_func)
        return decorator

    # 48. Enforce Constraints – enforces custom constraints.
    @staticmethod
    def enforce_constraints(constraints: dict) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                for arg, constraint in constraints.items():
                    if arg in kwargs and not constraint(kwargs[arg]):
                        raise ValueError(f"Constraint failed for argument {arg}")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 49. Capture Output – captures printed output.
    @staticmethod
    def capture_output() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                old_stdout = sys.stdout
                sys.stdout = io.StringIO()
                try:
                    result = func(*args, **kwargs)
                    output = sys.stdout.getvalue()
                finally:
                    sys.stdout = old_stdout
                structured_print(f"Captured output: {output.strip()}", title=f"CAPTURE OUTPUT: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 50. Transform Output – applies a transformation.
    @staticmethod
    def transform_output(transform: Callable[[Any], Any]) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = func(*args, **kwargs)
                return transform(result)
            return cast(F, new_func)
        return decorator

    # 51. Cache Result with Expiration – TTL-based caching.
    @staticmethod
    def expiration_cache(ttl: float = 60.0) -> Callable[[F], F]:
        cache = {}
        timestamps = {}
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                key = (args, frozenset(kwargs.items()))
                now = time.time()
                if key in cache and now - timestamps[key] < ttl:
                    return cache[key]
                result = func(*args, **kwargs)
                cache[key] = result
                timestamps[key] = now
                return result
            return cast(F, new_func)
        return decorator

    # 52. Concurrent – runs function concurrently in multiple threads.
    @staticmethod
    def concurrent(threads: int = 5) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                results = []
                def target():
                    results.append(func(*args, **kwargs))
                thread_list = [threading.Thread(target=target) for _ in range(threads)]
                for t in thread_list:
                    t.start()
                for t in thread_list:
                    t.join()
                structured_print(f"Concurrent results: {results}", title=f"CONCURRENT: {func.__name__}")
                return results
            return cast(F, new_func)
        return decorator

    # 53. Thread Safe (Alternative) – reentrant lock.
    @staticmethod
    def thread_safe() -> Callable[[F], F]:
        lock = threading.RLock()
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                with lock:
                    return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 54. Ignore None – if result is None, call backup.
    @staticmethod
    def ignore_none(backup: Callable) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = func(*args, **kwargs)
                if result is None:
                    structured_print("Result was None; calling backup", title=f"IGNORE NONE: {func.__name__}")
                    return backup(*args, **kwargs)
                return result
            return cast(F, new_func)
        return decorator

    # 55. Fallback If None – returns default if result is None.
    @staticmethod
    def fallback_if_none(default: Any) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = func(*args, **kwargs)
                return result if result is not None else default
            return cast(F, new_func)
        return decorator

    # 56. Precondition – check preconditions before execution.
    @staticmethod
    def precondition(check: Callable[..., bool]) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                if not check(*args, **kwargs):
                    raise ValueError("Precondition failed")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 57. Postcondition – check postconditions after execution.
    @staticmethod
    def postcondition(check: Callable[[Any], bool]) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = func(*args, **kwargs)
                if not check(result):
                    raise ValueError("Postcondition failed")
                return result
            return cast(F, new_func)
        return decorator

    # 58. Iterate Over – apply function to each element of an iterable argument.
    @staticmethod
    def iterate_over(iter_arg: str) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                iterable = kwargs.get(iter_arg)
                if iterable is None or not hasattr(iterable, '__iter__'):
                    raise ValueError(f"Argument {iter_arg} is not iterable")
                return [func(item) for item in iterable]
            return cast(F, new_func)
        return decorator

    # 59. Bulk Operation – vectorize function over list of inputs.
    @staticmethod
    def bulk_operation() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(inputs, *args, **kwargs):
                results = [func(item, *args, **kwargs) for item in inputs]
                structured_print(f"Bulk operation results: {results}", title=f"BULK: {func.__name__}")
                return results
            return cast(F, new_func)
        return decorator

    # 60. Memoize with Expiration – alias for expiration_cache.
    @staticmethod
    def memoize_with_expiration(ttl: float = 60.0) -> Callable[[F], F]:
        return DecoratorFactory.expiration_cache(ttl)

    # 61. Capture Exceptions – stores exceptions in a list.
    @staticmethod
    def capture_exceptions(storage: list) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    storage.append(e)
                    raise
            return cast(F, new_func)
        return decorator

    # 62. Report Exceptions – reports exceptions using a function.
    @staticmethod
    def report_exceptions(report_func: Callable[[Exception], None]) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    report_func(e)
                    raise
            return cast(F, new_func)
        return decorator

    # 63. Log Exceptions – logs exceptions using a logger.
    @staticmethod
    def log_exceptions(logger: logging.Logger = None) -> Callable[[F], F]:
        if logger is None:
            logger = logging.getLogger("exceptions")
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    logger.exception(f"Exception in {func.__name__}: {e}")
                    raise
            return cast(F, new_func)
        return decorator

    # 64. Ignore Warnings – suppress warnings.
    @staticmethod
    def ignore_warnings() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                with warnings.catch_warnings():
                    warnings.simplefilter("ignore")
                    return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 65. Enforce Documentation – ensures function has a docstring.
    @staticmethod
    def enforce_documentation() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            if not func.__doc__:
                raise ValueError(f"Function {func.__name__} must have a docstring")
            return func
        return decorator

    # 66. Limit Recursion – limits recursion depth.
    @staticmethod
    def limit_recursion(max_depth: int = 50) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            func._recursion_depth = 0
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                if func._recursion_depth > max_depth:
                    raise RecursionError("Maximum recursion depth exceeded")
                func._recursion_depth += 1
                try:
                    return func(*args, **kwargs)
                finally:
                    func._recursion_depth -= 1
            return cast(F, new_func)
        return decorator

    # 67. Flatten Arguments – flattens nested iterables.
    @staticmethod
    def flatten_arguments(arg_name: str) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                if arg_name in kwargs and isinstance(kwargs[arg_name], list):
                    flat = [item for sublist in kwargs[arg_name] for item in (sublist if isinstance(sublist, list) else [sublist])]
                    kwargs[arg_name] = flat
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 68. Check Range – ensure numeric argument is within a range.
    @staticmethod
    def check_range(arg_name: str, min_val: float, max_val: float) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                value = kwargs.get(arg_name)
                if value is None:
                    sig = inspect.signature(func)
                    bound = sig.bind(*args, **kwargs)
                    value = bound.arguments.get(arg_name)
                if value is not None and not (min_val <= value <= max_val):
                    raise ValueError(f"Argument {arg_name} must be between {min_val} and {max_val}")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 69. Convert Output – converts output via a converter.
    @staticmethod
    def convert_output(converter: Callable[[Any], Any]) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                return converter(func(*args, **kwargs))
            return cast(F, new_func)
        return decorator

    # 70. Round Output – rounds numeric output.
    @staticmethod
    def round_output(precision: int = 2) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = func(*args, **kwargs)
                if isinstance(result, (float, int)):
                    return round(result, precision)
                return result
            return cast(F, new_func)
        return decorator

    # 71. Filter Arguments – removes unwanted keyword arguments.
    @staticmethod
    def filter_arguments(*filter_keys) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                filtered = {k: v for k, v in kwargs.items() if k not in filter_keys}
                return func(*args, **filtered)
            return cast(F, new_func)
        return decorator

    # 72. Preserve Metadata – dummy example.
    @staticmethod
    def preserve_metadata() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 73. Decorate Class Methods – applies a decorator to all methods.
    @staticmethod
    def decorate_class_methods(deco: Callable[[F], F]) -> Callable[[type], type]:
        def decorator(cls: type) -> type:
            for attr, val in cls.__dict__.items():
                if callable(val) and not attr.startswith("__"):
                    setattr(cls, attr, deco(val))
            return cls
        return decorator

    # 74. Instance Tracker – tracks all class instances.
    @staticmethod
    def instance_tracker(cls: type) -> type:
        orig_init = cls.__init__
        cls.instances = []
        def __init__(self, *args, **kwargs):
            cls.instances.append(self)
            orig_init(self, *args, **kwargs)
        cls.__init__ = __init__
        return cls

    # 75. Method Logger – logs calls to class methods.
    @staticmethod
    def method_logger() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                structured_print(f"Method {func.__name__} called", title="METHOD LOGGER")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 76. Reentrant – ensures function reentrancy with a reentrant lock.
    @staticmethod
    def reentrant() -> Callable[[F], F]:
        lock = threading.RLock()
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                with lock:
                    return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 77. Serialize Arguments – serializes arguments to JSON.
    @staticmethod
    def serialize_arguments() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                structured_print(json.dumps({'args': args, 'kwargs': kwargs}, indent=2), title=f"SERIALIZED ARGS: {func.__name__}")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 78. Sanitize Input – sanitizes string inputs.
    @staticmethod
    def sanitize_input() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                new_args = [arg.strip() if isinstance(arg, str) else arg for arg in args]
                new_kwargs = {k: v.strip() if isinstance(v, str) else v for k, v in kwargs.items()}
                return func(*new_args, **new_kwargs)
            return cast(F, new_func)
        return decorator

    # 79. Enforce Max Args – limits number of arguments.
    @staticmethod
    def enforce_max_args(max_args: int) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                if len(args) + len(kwargs) > max_args:
                    raise ValueError(f"{func.__name__} accepts at most {max_args} arguments")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 80. Require Non-Null – ensures no argument is None.
    @staticmethod
    def require_non_null() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                if any(arg is None for arg in args) or any(v is None for v in kwargs.values()):
                    raise ValueError("None value not allowed")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 81. Time Limit (Thread-based) – limits execution time.
    @staticmethod
    def time_limit(seconds: int) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = [None]
                exception = [None]
                def target():
                    try:
                        result[0] = func(*args, **kwargs)
                    except Exception as e:
                        exception[0] = e
                thread = threading.Thread(target=target)
                thread.start()
                thread.join(seconds)
                if thread.is_alive():
                    raise TimeoutError("Timed out")
                if exception[0]:
                    raise exception[0]
                return result[0]
            return cast(F, new_func)
        return decorator

    # 82. Debug Trace – simple trace output.
    @staticmethod
    def debug_trace() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                structured_print(f"Tracing {func.__name__}", title="DEBUG TRACE")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 83. Print Call Stack – prints the current call stack.
    @staticmethod
    def print_call_stack() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                s = io.StringIO()
                traceback.print_stack(file=s)
                structured_print(s.getvalue(), title=f"CALL STACK: {func.__name__}")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 84. Inject Dependencies – provides default dependencies.
    @staticmethod
    def inject_dependencies(defaults: dict) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                for key, value in defaults.items():
                    kwargs.setdefault(key, value)
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 85. Auto Retry with Log – retry with logging.
    @staticmethod
    def auto_retry_with_log(retries: int = 3, delay: float = 1.0) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                for attempt in range(retries):
                    try:
                        return func(*args, **kwargs)
                    except Exception as e:
                        structured_print(f"Attempt {attempt+1}/{retries} failed: {e}", title="AUTO RETRY WITH LOG")
                        time.sleep(delay)
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 86. Auto Reconnect – dummy network reconnect logic.
    @staticmethod
    def auto_reconnect(retries: int = 3) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                for _ in range(retries):
                    try:
                        return func(*args, **kwargs)
                    except Exception:
                        structured_print("Reconnecting...", title="AUTO RECONNECT")
                        time.sleep(0.5)
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 87. Secure Execution – executes in a secure context (dummy).
    @staticmethod
    def secure_execution() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                structured_print("Executing in secure mode...", title="SECURE EXECUTION")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 88. Resource Lock – simulates resource locking.
    @staticmethod
    def resource_lock(lock: threading.Lock = None) -> Callable[[F], F]:
        if lock is None:
            lock = threading.Lock()
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                with lock:
                    return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 89. Force Async – forces function to run asynchronously.
    @staticmethod
    def force_async() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                threading.Thread(target=func, args=args, kwargs=kwargs).start()
                structured_print(f"{func.__name__} is running asynchronously", title="FORCE ASYNC")
            return cast(F, new_func)
        return decorator

    # 90. Fallback Chain – chain multiple fallback functions.
    @staticmethod
    def fallback_chain(*fallbacks: Callable) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                for fb in fallbacks:
                    try:
                        return func(*args, **kwargs)
                    except Exception:
                        func = fb
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 91. Apply Hooks – executes pre and post hooks.
    @staticmethod
    def apply_hooks(pre: Callable = lambda: None, post: Callable = lambda: None) -> Callable[[F], F]:
        return DecoratorFactory.pre_post(pre, post)

    # 92. Instrument – instruments function calls for metrics.
    @staticmethod
    def instrument(metric_func: Callable[[str, float], None]) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                start = time.time()
                result = func(*args, **kwargs)
                metric_func(func.__name__, time.time() - start)
                return result
            return cast(F, new_func)
        return decorator

    # 93. Run in Subprocess – runs function in a subprocess.
    @staticmethod
    def run_in_subprocess() -> Callable[[F], F]:
        import pickle
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                cmd = [sys.executable, "-c", f"import pickle; print(pickle.loads({repr(pickle.dumps(func))})(*{args}, **{kwargs}))"]
                output = subprocess.check_output(cmd)
                structured_print(f"Subprocess output: {output.decode().strip()}", title=f"SUBPROCESS: {func.__name__}")
                return output
            return cast(F, new_func)
        return decorator

    # 94. Measure CPU Time – measures CPU time.
    @staticmethod
    def measure_cpu_time() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                start = time.process_time()
                result = func(*args, **kwargs)
                cpu_time = time.process_time() - start
                structured_print(f"CPU time: {cpu_time:.4f} seconds", title=f"CPU TIME: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 95. Collect Metrics – collects execution metrics.
    @staticmethod
    def collect_metrics(metrics: dict) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                start = time.time()
                result = func(*args, **kwargs)
                elapsed = time.time() - start
                metrics[func.__name__] = elapsed
                structured_print(f"Metrics: {elapsed:.4f} seconds", title=f"METRICS: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 96. Save State – dummy state saving.
    @staticmethod
    def save_state() -> Callable[[F], F]:
        def decorator(func: F) -> F:
            state = {}
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                result = func(*args, **kwargs)
                state['last_result'] = result
                structured_print(f"State saved: {state}", title=f"SAVE STATE: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 97. Retry with Jitter – retries with random delay jitter.
    @staticmethod
    def retry_with_jitter(times: int = 3, base_delay: float = 1.0) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                for attempt in range(times):
                    try:
                        return func(*args, **kwargs)
                    except Exception as e:
                        if attempt == times - 1:
                            raise
                        delay = base_delay + random.uniform(0, 0.5)
                        structured_print(f"Attempt {attempt+1}/{times} failed: {e}. Retrying in {delay:.2f} seconds.",
                                           title="RETRY WITH JITTER")
                        time.sleep(delay)
            return cast(F, new_func)
        return decorator

    # 98. Audit – records an audit trail.
    @staticmethod
    def audit(audit_log: list) -> Callable[[F], F]:
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                audit_log.append((func.__name__, args, kwargs, time.time()))
                structured_print(f"Audit log updated for {func.__name__}", title="AUDIT")
                return func(*args, **kwargs)
            return cast(F, new_func)
        return decorator

    # 99. Comprehensive Logger – logs, times, and handles errors.
    @staticmethod
    def comprehensive_logger(logger: logging.Logger = None) -> Callable[[F], F]:
        if logger is None:
            logger = logging.getLogger("comprehensive")
            logger.setLevel(logging.INFO)
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                start = time.time()
                try:
                    result = func(*args, **kwargs)
                except Exception as e:
                    logger.exception(f"Error in {func.__name__}: {e}")
                    raise
                elapsed = time.time() - start
                logger.info(f"{func.__name__} executed in {elapsed:.4f} seconds with result {result}")
                structured_print(f"Elapsed time: {elapsed:.4f} sec, Result: {result}", title=f"LOGGER: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # 100. Comprehensive Debugger – detailed debugging.
    @staticmethod
    def comprehensive_debugger(logger: logging.Logger = None) -> Callable[[F], F]:
        if logger is None:
            logger = logging.getLogger("comprehensive_debug")
            logger.setLevel(logging.DEBUG)
        def decorator(func: F) -> F:
            @functools.wraps(func)
            def new_func(*args: Any, **kwargs: Any) -> Any:
                logger.debug(f"Starting {func.__name__} with args: {args}, kwargs: {kwargs}")
                start = time.time()
                try:
                    result = func(*args, **kwargs)
                except Exception as e:
                    logger.exception(f"Exception in {func.__name__}: {e}")
                    raise
                elapsed = time.time() - start
                logger.debug(f"{func.__name__} completed in {elapsed:.4f} seconds with result {result}")
                structured_print(f"Elapsed: {elapsed:.4f} sec, Result: {result}", title=f"DEBUGGER: {func.__name__}")
                return result
            return cast(F, new_func)
        return decorator

    # -------------------- LIST DECORATORS METHOD --------------------
    @classmethod
    def list_decorators(cls) -> None:
        """Prints the list of all decorators with their descriptions."""
        lines = []
        for name, description in cls.decorators_info.items():
            lines.append(f"{name.ljust(25)}: {description}")
        structured_print("\n".join(lines), title="AVAILABLE DECORATORS")

