Programming with Python

Acts as a Senior Backend Developer expert in the Python language and structural design patterns. Your goal is to design and implement a highly efficient and configurable decorator-based auditing system for the [NOMBRE_DEL_MODULO] module, ensuring that every call to critical functions is logged with surgical precision without significantly degrading the performance of the base system. The system must follow 'Core Syntax Optimization' best practices, using advanced metaprogramming techniques and the functools module to preserve the identity and metadata of decorated functions (docstrings, names, signatures).


The implementation must necessarily capture the following metadata in each execution: the exact timestamp in ISO format, the name of the invoked function, the positional (*args) and nominal (**kwargs) arguments—applying a strict security mask to [CAMPOS_ESPECIFICOS] to avoid leaks of sensitive information—, the return value obtained, and the total execution time calculated with the time or perf_counter module. Furthermore, the decorator must be flexible enough to integrate with a persistence system of type [DESTINO_DE_DATOS], allowing complete traceability of actions in production environments under a criticality level defined as [NIVEL_DE_LOGGING].


Considers complex execution scenarios, including native support for asynchronous functions (async/await) through dynamic function type detection or the use of coroutine-specific decorators. You should implement a robust exception handling block based on [MANEJO_DE_ERRORES], so that any internal failure in the audit logging process does not interrupt the main flow of the application (fail-safe philosophy). The architecture of the decorator must allow its application both in stand-alone functions and in class methods (instance methods), correctly handling access to the 'self' or 'cls' context without including these pointers in the data logs unless otherwise specified.


Finally, generate code that is compatible with Python 3.10+ and that strictly follows PEP 8 style conventions. The result must be modularized, easy to maintain, and must include a brief technical explanation of how the implementation optimizes memory and CPU usage, avoiding unnecessary creation of objects in the heap during each invocation. Provide clear usage examples where the decorator is applied to a data processing function and an asynchronous API method.

If any key information needed to fill the bracketed fields is missing, ask me the necessary questions before answering.

Act as a Senior Software Architect and Python Developer expert in creating robust and scalable command line interfaces (CLI). Your goal is to design a hyper-optimized argument management system using exclusively the `argparse` standard library for the project called [Nombre_del_Proyecto]. The solution should focus on 'Core Syntax Optimization', ensuring that the code is modular, easy to maintain, and complies with Python community best practices (PEP 8).



The design must be structured to handle advanced complexity, integrating multiple levels of subcommands for [Funcionalidades_Clave] functionalities. Each argument should be meticulously defined with respective data types, sensible default values, descriptive help messages, and clear metavariables. It is imperative that you use `ArgumentParser`, `add_subparsers`, and implement argument groups to improve the readability of the help generated by the script when the user executes `--help`.



You must include the use of `add_mutually_exclusive_group` for the [Parametros_Excluyentes] parameters, ensuring that the user cannot make logical configuration errors at runtime. Additionally, it integrates custom validations using 'type' functions to ensure that [Variables_Criticas] entries follow a specific format (such as regular expressions or strict numeric ranges). The resulting script must be able to parse the arguments and return a configuration object that will be injected into the main logic of the program.



Finally, it documents the structure of the commands within the script itself, providing command-line usage examples for each defined subcommand. Make sure you properly handle `argparse` exceptions to avoid unnecessary stack traces, instead providing clean error messages directed to the end user. The code must be ready to be integrated into a high-performance production environment.

If any key information needed to fill the bracketed fields is missing, ask me the necessary questions before answering.