# ==================================================================================================
# DEEPFAKE AUDIO - utils/argutils.py (Interface Logic Utilities)
# ==================================================================================================
# 
# 📝 DESCRIPTION
# This module provides utility functions for managing command-line arguments within the 
# Deepfake Audio framework. It ensures consistent argument parsing, priority-based 
# sorting, and clean console output for diagnostic reporting across all pipeline stages.
#
# 👤 AUTHORS
# - Amey Thakur (https://github.com/Amey-Thakur)
# - Mega Satish (https://github.com/msatmod)
#
# 🤝🏻 CREDITS
# Original Real-Time Voice Cloning methodology by CorentinJ
# Repository: https://github.com/CorentinJ/Real-Time-Voice-Cloning
#
# 🔗 PROJECT LINKS
# Repository: https://github.com/Amey-Thakur/DEEPFAKE-AUDIO
# Video Demo: https://youtu.be/i3wnBcbHDbs
# Research: https://github.com/Amey-Thakur/DEEPFAKE-AUDIO/blob/main/DEEPFAKE-AUDIO.ipynb
#
# 📜 LICENSE
# Released under the MIT License
# Release Date: 2021-02-06
# ==================================================================================================

from pathlib import Path
import numpy as np
import argparse

_type_priorities = [    # In decreasing order
    Path,
    str,
    int,
    float,
    bool,
]

def _priority(o):
    p = next((i for i, t in enumerate(_type_priorities) if type(o) is t), None) 
    if p is not None:
        return p
    p = next((i for i, t in enumerate(_type_priorities) if isinstance(o, t)), None) 
    if p is not None:
        return p
    return len(_type_priorities)

def print_args(args: argparse.Namespace, parser=None):
    args = vars(args)
    if parser is None:
        priorities = list(map(_priority, args.values()))
    else:
        all_params = [a.dest for g in parser._action_groups for a in g._group_actions ]
        priority = lambda p: all_params.index(p) if p in all_params else len(all_params)
        priorities = list(map(priority, args.keys()))
    
    pad = max(map(len, args.keys())) + 3
    indices = np.lexsort((list(args.keys()), priorities))
    items = list(args.items())
    
    print("Arguments:")
    for i in indices:
        param, value = items[i]
        print("    {0}:{1}{2}".format(param, ' ' * (pad - len(param)), value))
    print("")