Main.py

import customtkinter as ctk
import sqlite3
import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier, IsolationForest
from sklearn.cluster import KMeans, DBSCAN
from sklearn.decomposition import PCA
from sklearn.feature_selection import SelectKBest, f_regression, mutual_info_classif
from sklearn.pipeline import make_pipeline
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import (StandardScaler, OneHotEncoder, MinMaxScaler, 
                                  LabelEncoder, PowerTransformer, OrdinalEncoder)
from sklearn.compose import ColumnTransformer
from sklearn.metrics import (mean_squared_error, silhouette_score, 
                           accuracy_score, classification_report, confusion_matrix,
                           roc_auc_score, precision_recall_curve, explained_variance_score)
from sklearn.model_selection import (train_test_split, cross_val_score, 
                                   GridSearchCV, RandomizedSearchCV, StratifiedKFold)
from sklearn.svm import SVC, SVR, OneClassSVM
from sklearn.linear_model import LinearRegression, LogisticRegression, Ridge, Lasso
from sklearn.neural_network import MLPClassifier, MLPRegressor
from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
from sklearn.ensemble import (GradientBoostingRegressor, GradientBoostingClassifier,
                            AdaBoostRegressor, AdaBoostClassifier, VotingClassifier)
from xgboost import XGBClassifier, XGBRegressor
from lightgbm import LGBMClassifier, LGBMRegressor
from catboost import CatBoostClassifier, CatBoostRegressor
from sklearn.naive_bayes import GaussianNB
from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor
from sklearn.calibration import CalibratedClassifierCV
from sklearn.inspection import permutation_importance, PartialDependenceDisplay
import tensorflow as tf
from tensorflow.keras import layers, models, callbacks
from tensorflow.keras.utils import plot_model
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader, TensorDataset
import matplotlib.pyplot as plt
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import seaborn as sns
import pickle
import json
import os
import re
import threading
import queue
import time
import psutil
import warnings
from datetime import datetime, timedelta
from tkinter import filedialog, ttk, messagebox, simpledialog
import hashlib
import uuid
import joblib
import dill
import shap
import eli5
import lime
import lime.lime_tabular
from scipy import stats
from statsmodels.tsa.seasonal import seasonal_decompose
from statsmodels.tsa.arima.model import ARIMA
from statsmodels.tsa.stattools import adfuller
import pyodbc
import mysql.connector
import psycopg2
import cx_Oracle
from cryptography.fernet import Fernet
from PIL import Image, ImageTk
import requests
import yaml
import zipfile
import tempfile
import webbrowser
import inspect
import traceback
import logging
import sys
import gc
warnings.filterwarnings('ignore')

# Configure logging
logging.basicConfig(
    filename='enterprise_visualsql.log',
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger('EnterpriseVisualSQL')

# ==================== ENHANCED APPLICATION ====================
class EnterpriseVisualSQL(ctk.CTk):
    def __init__(self):
        super().__init__()
        self.title("Enterprise VisualSQL AI 4.0 Pro Ultimate")
        self.geometry("1920x1080")
        self.minsize(1400, 900)
        self.iconbitmap(self.resource_path("app_icon.ico")) if os.path.exists("app_icon.ico") else None
        
        # Initialize application state with enhanced features
        self.initialize_application_state()
        
        # UI Setup
        self.setup_ui()
        
        # Start background services
        self.start_background_services()
        
        # Load user preferences and restore session
        self.load_application_state()
        
        # Apply UI theme
        self.apply_ui_theme()
    
    def initialize_application_state(self):
        """Initialize all application state variables"""
        # Core state
        self.connection = None
        self.current_data = None
        self.current_model = None
        self.model_history = []
        self.data_pipeline = self.AdvancedDataPipeline()
        self.model_warehouse = self.ModelWarehouse()
        self.performance_optimizer = self.PerformanceOptimizer()
        self.security_manager = self.SecurityManager()
        self.collaboration = self.CollaborationTools()
        self.user_preferences = self.load_preferences()
        self.undo_stack = []
        self.redo_stack = []
        self.data_snapshots = {}
        self.auto_save_enabled = True
        self.auto_save_interval = 300  # 5 minutes
        self.last_save_time = time.time()
        self.job_queue = queue.Queue()
        self.system_monitor = self.SystemMonitor(self)
        self.error_tracker = self.ErrorTracker()
        self.feature_store = self.FeatureStore()
        self.experiment_tracker = self.ExperimentTracker()
        self.mlflow_integration = self.MLflowIntegration()
        self.api_integration = self.APIIntegration()
        
        # UI state
        self.ui_state = {
            "current_tab": "sql",
            "window_size": (1920, 1080),
            "sidebar_width": 300,
            "theme": "dark"
        }
        
        # Runtime state
        self.active_threads = []
        self.resource_usage = {
            "cpu": 0.0,
            "memory": 0.0,
            "gpu": 0.0
        }
        self.last_activity = datetime.now()
        self.session_id = str(uuid.uuid4())
        self.feature_flags = self.load_feature_flags()
    
    # ==================== 100+ NEW FEATURES & DETAILS ====================
    
    # 1. Enhanced Database Connectivity (10 features)
    def setup_database_explorer(self):
        """Professional database explorer with multiple connection support"""
        explorer_frame = ctk.CTkFrame(self.sidebar)
        explorer_frame.pack(fill="x", padx=5, pady=5, expand=False)
        
        # Connection manager with tabs
        self.db_notebook = ctk.CTkTabview(explorer_frame, height=250)
        self.db_notebook.pack(fill="x", pady=(0,10))
        
        # Main connection tab
        conn_tab = self.db_notebook.add("Connection")
        
        # Database type selection with icons
        db_types = [
            ("SQLite", "database-sqlite"),
            ("MySQL", "database-mysql"),
            ("PostgreSQL", "database-postgres"),
            ("SQL Server", "database-sqlserver"),
            ("Oracle", "database-oracle"),
            ("BigQuery", "database-bigquery"),
            ("Snowflake", "database-snowflake"),
            ("Redshift", "database-redshift"),
            ("MongoDB", "database-mongodb"),
            ("Cassandra", "database-cassandra")
        ]
        
        # Create database type selector with icons
        self.db_type = ctk.CTkComboBox(
            conn_tab,
            values=[db[0] for db in db_types],
            state="readonly",
            command=self.update_connection_fields
        )
        self.db_type.pack(fill="x", padx=5, pady=2)
        
        # Connection fields container
        self.connection_fields_frame = ctk.CTkFrame(conn_tab)
        self.connection_fields_frame.pack(fill="x", pady=2)
        
        # SQLite specific fields
        self.sqlite_frame = ctk.CTkFrame(self.connection_fields_frame)
        ctk.CTkLabel(self.sqlite_frame, text="Database File:").pack(anchor="w")
        self.sqlite_path = ctk.CTkEntry(self.sqlite_frame, placeholder_text="Path to SQLite database")
        self.sqlite_path.pack(fill="x", padx=5, pady=2, side="left", expand=True)
        self.sqlite_browse_btn = ctk.CTkButton(
            self.sqlite_frame, 
            text="📁", 
            width=40,
            command=self.browse_sqlite_file
        )
        self.sqlite_browse_btn.pack(side="right", padx=5)
        
        # MySQL specific fields
        self.mysql_frame = ctk.CTkFrame(self.connection_fields_frame)
        self.mysql_frame.pack_forget()
        ctk.CTkLabel(self.mysql_frame, text="Host:").pack(anchor="w")
        self.mysql_host = ctk.CTkEntry(self.mysql_frame, placeholder_text="localhost")
        self.mysql_host.pack(fill="x", padx=5, pady=2)
        ctk.CTkLabel(self.mysql_frame, text="Database:").pack(anchor="w")
        self.mysql_database = ctk.CTkEntry(self.mysql_frame, placeholder_text="Database name")
        self.mysql_database.pack(fill="x", padx=5, pady=2)
        ctk.CTkLabel(self.mysql_frame, text="User:").pack(anchor="w")
        self.mysql_user = ctk.CTkEntry(self.mysql_frame, placeholder_text="Username")
        self.mysql_user.pack(fill="x", padx=5, pady=2)
        ctk.CTkLabel(self.mysql_frame, text="Password:").pack(anchor="w")
        self.mysql_password = ctk.CTkEntry(self.mysql_frame, placeholder_text="Password", show="*")
        self.mysql_password.pack(fill="x", padx=5, pady=2)
        
        # ... (similar frames for other database types)
        
        # Default to SQLite
        self.sqlite_frame.pack(fill="x", pady=2)
        
        # Advanced connection options
        self.advanced_conn_btn = ctk.CTkButton(
            conn_tab,
            text="Advanced Options ▼",
            command=self.toggle_advanced_connection_options,
            width=150,
            fg_color="transparent",
            border_width=1
        )
        self.advanced_conn_btn.pack(pady=5)
        
        self.advanced_conn_frame = ctk.CTkFrame(conn_tab)
        self.advanced_conn_frame.pack_forget()
        
        # SSL options
        ssl_frame = ctk.CTkFrame(self.advanced_conn_frame)
        ssl_frame.pack(fill="x", padx=5, pady=2)
        self.ssl_check = ctk.CTkCheckBox(ssl_frame, text="Use SSL/TLS")
        self.ssl_check.pack(side="left", padx=5)
        self.ssl_cert = ctk.CTkEntry(ssl_frame, placeholder_text="SSL Certificate", width=200)
        self.ssl_cert.pack(side="left", padx=5)
        self.ssl_cert_browse = ctk.CTkButton(ssl_frame, text="📁", width=30, command=self.browse_ssl_cert)
        self.ssl_cert_browse.pack(side="left", padx=2)
        
        # SSH tunneling
        ssh_frame = ctk.CTkFrame(self.advanced_conn_frame)
        ssh_frame.pack(fill="x", padx=5, pady=2)
        self.ssh_tunnel_check = ctk.CTkCheckBox(ssh_frame, text="SSH Tunnel")
        self.ssh_tunnel_check.pack(side="left", padx=5)
        self.ssh_host = ctk.CTkEntry(ssh_frame, placeholder_text="SSH Host", width=120)
        self.ssh_host.pack(side="left", padx=5)
        self.ssh_user = ctk.CTkEntry(ssh_frame, placeholder_text="SSH User", width=100)
        self.ssh_user.pack(side="left", padx=5)
        self.ssh_port = ctk.CTkEntry(ssh_frame, placeholder_text="Port", width=60)
        self.ssh_port.pack(side="left", padx=5)
        
        # Connection controls
        conn_btn_frame = ctk.CTkFrame(conn_tab)
        conn_btn_frame.pack(fill="x", pady=(0,5))
        
        self.connect_btn = ctk.CTkButton(
            conn_btn_frame,
            text="Connect",
            command=self.connect_db,
            width=100,
            image=self.load_icon("connect")
        )
        self.connect_btn.pack(side="left", padx=2)
        
        self.test_btn = ctk.CTkButton(
            conn_btn_frame,
            text="Test",
            command=self.test_connection,
            width=80,
            image=self.load_icon("test")
        )
        self.test_btn.pack(side="left", padx=2)
        
        self.disconnect_btn = ctk.CTkButton(
            conn_btn_frame,
            text="Disconnect",
            command=self.disconnect_db,
            width=100,
            state="disabled",
            image=self.load_icon("disconnect")
        )
        self.disconnect_btn.pack(side="right", padx=2)
        
        # Recent connections tab
        recent_tab = self.db_notebook.add("Recent")
        self.recent_connections = ttk.Treeview(recent_tab, columns=("type", "date"), show="tree headings")
        self.recent_connections.heading("#0", text="Connection")
        self.recent_connections.heading("type", text="Type")
        self.recent_connections.heading("date", text="Last Used")
        vsb = ttk.Scrollbar(recent_tab, orient="vertical", command=self.recent_connections.yview)
        hsb = ttk.Scrollbar(recent_tab, orient="horizontal", command=self.recent_connections.xview)
        self.recent_connections.configure(yscrollcommand=vsb.set, xscrollcommand=hsb.set)
        self.recent_connections.pack(fill="both", expand=True, side="left")
        vsb.pack(fill="y", side="right")
        hsb.pack(fill="x", side="bottom")
        
        # Table explorer with enhanced features
        self.setup_table_explorer(explorer_frame)
    
    # 2. Advanced AI Workbench (10 features)
    def setup_ai_workbench(self):
        """Professional AI development environment with MLOps integration"""
        ai_frame = ctk.CTkFrame(self.sidebar)
        ai_frame.pack(fill="x", padx=5, pady=5, expand=False)
        
        ctk.CTkLabel(ai_frame, text="AI Workbench Pro", font=ctk.CTkFont(weight="bold", size=14)).pack(pady=(0,10))
        
        # Model category selection with icons
        model_categories = [
            ("Regression", "chart-line"),
            ("Classification", "category"),
            ("Clustering", "cluster"),
            ("Anomaly Detection", "alert-circle"),
            ("Time Series", "timeline"),
            ("Recommender", "recommend"),
            ("Computer Vision", "image"),
            ("NLP", "text"),
            ("Survival Analysis", "heart-pulse"),
            ("Causal Inference", "cause-effect")
        ]
        
        self.model_category = ctk.CTkComboBox(
            ai_frame,
            values=[cat[0] for cat in model_categories],
            state="readonly",
            command=self.update_model_types
        )
        self.model_category.pack(fill="x", padx=5, pady=2)
        
        # Model type selection with search
        model_type_frame = ctk.CTkFrame(ai_frame)
        model_type_frame.pack(fill="x", padx=5, pady=2)
        ctk.CTkLabel(model_type_frame, text="Model Type:").pack(anchor="w")
        self.model_type_search = ctk.CTkEntry(model_type_frame, placeholder_text="Search models...")
        self.model_type_search.pack(side="left", fill="x", expand=True, padx=(0,5))
        self.model_type_search.bind("<KeyRelease>", self.filter_model_types)
        self.model_type = ctk.CTkComboBox(
            model_type_frame,
            values=[],
            state="readonly",
            command=self.update_model_details
        )
        self.model_type.pack(side="right", fill="x", expand=True)
        
        # Model details panel
        self.model_details_frame = ctk.CTkFrame(ai_frame)
        self.model_details_frame.pack(fill="x", padx=5, pady=5)
        self.model_details = ctk.CTkTextbox(self.model_details_frame, height=100, wrap="word")
        self.model_details.pack(fill="both", expand=True)
        self.model_details.configure(state="disabled")
        
        # Target variable selection with type detection
        target_frame = ctk.CTkFrame(ai_frame)
        target_frame.pack(fill="x", padx=5, pady=2)
        ctk.CTkLabel(target_frame, text="Target Variable:").pack(anchor="w")
        self.target_var = ctk.CTkComboBox(
            target_frame,
            values=[],
            state="readonly"
        )
        self.target_var.pack(fill="x", padx=5, pady=2)
        
        # Hyperparameter tuning with presets
        hyper_frame = ctk.CTkFrame(ai_frame)
        hyper_frame.pack(fill="x", padx=5, pady=5)
        ctk.CTkLabel(hyper_frame, text="Hyperparameters:").pack(anchor="w")
        self.hyper_preset = ctk.CTkComboBox(
            hyper_frame,
            values=["Default", "Simple", "Balanced", "Complex", "Custom"],
            state="readonly"
        )
        self.hyper_preset.pack(fill="x", padx=5, pady=2)
        self.hyper_preset.set("Default")
        self.hyper_preset.bind("<<ComboboxSelected>>", self.load_hyper_preset)
        
        # Feature selection with importance preview
        feature_frame = ctk.CTkFrame(ai_frame)
        feature_frame.pack(fill="x", padx=5, pady=5)
        ctk.CTkLabel(feature_frame, text="Features:").pack(anchor="w")
        self.feature_selector = ctk.CTkScrollableFrame(feature_frame, height=100)
        self.feature_selector.pack(fill="both", expand=True)
        
        # Training controls with experiment tracking
        train_frame = ctk.CTkFrame(ai_frame)
        train_frame.pack(fill="x", padx=5, pady=5)
        self.start_train_btn = ctk.CTkButton(
            train_frame,
            text="Start Training",
            command=self.start_training,
            width=120,
            image=self.load_icon("train")
        )
        self.start_train_btn.pack(side="left", padx=2)
        self.track_experiment = ctk.CTkCheckBox(train_frame, text="Track in MLflow")
        self.track_experiment.pack(side="left", padx=10)
        self.auto_deploy = ctk.CTkCheckBox(train_frame, text="Auto-deploy")
        self.auto_deploy.pack(side="left", padx=10)
        
        # Model evaluation with advanced metrics
        self.setup_model_evaluation(ai_frame)
    
    # 3. Enhanced Visualization Studio (10 features)
    def setup_visualization_studio(self):
        """Professional visualization studio with dashboard creation"""
        vis_tab = self.notebook.add("Visualization Studio")
        
        # Dashboard management
        dashboard_frame = ctk.CTkFrame(vis_tab)
        dashboard_frame.pack(fill="x", padx=5, pady=5)
        self.dashboard_name = ctk.CTkEntry(dashboard_frame, placeholder_text="Dashboard Name", width=200)
        self.dashboard_name.pack(side="left", padx=5)
        self.save_dashboard_btn = ctk.CTkButton(
            dashboard_frame,
            text="Save Dashboard",
            command=self.save_dashboard,
            width=120
        )
        self.save_dashboard_btn.pack(side="left", padx=5)
        self.load_dashboard_btn = ctk.CTkButton(
            dashboard_frame,
            text="Load Dashboard",
            command=self.load_dashboard,
            width=120
        )
        self.load_dashboard_btn.pack(side="left", padx=5)
        self.add_chart_btn = ctk.CTkButton(
            dashboard_frame,
            text="+ Add Chart",
            command=self.add_chart_to_dashboard,
            width=100,
            fg_color="#2e7d32",
            hover_color="#1b5e20"
        )
        self.add_chart_btn.pack(side="right", padx=5)
        
        # Visualization canvas with grid layout
        self.dashboard_canvas = ctk.CTkFrame(vis_tab)
        self.dashboard_canvas.pack(fill="both", expand=True, padx=5, pady=(0,5))
        self.dashboard_canvas.grid_columnconfigure(0, weight=1)
        self.dashboard_canvas.grid_columnconfigure(1, weight=1)
        self.dashboard_canvas.grid_rowconfigure(0, weight=1)
        self.dashboard_canvas.grid_rowconfigure(1, weight=1)
        
        # Initialize with 2x2 grid
        self.chart_frames = []
        for i in range(2):
            for j in range(2):
                frame = ctk.CTkFrame(self.dashboard_canvas)
                frame.grid(row=i, column=j, padx=5, pady=5, sticky="nsew")
                self.chart_frames.append(frame)
        
        # Chart configuration panel
        self.chart_config_panel = ctk.CTkFrame(vis_tab)
        self.chart_config_panel.pack_forget()
    
    # 4. Model Training Center (10 features)
    def setup_model_training_center(self):
        """Professional model training environment with distributed training"""
        model_tab = self.notebook.add