main.py

#!/usr/bin/env python3
"""
CL Option Zone - Main Calculator
支持互動式參數詢問與命令行參數兩種模式
"""

import sys
import os
import argparse
from rich.console import Console
from rich.table import Table
from rich.panel import Panel
from rich.layout import Layout

# Add project root to path
sys.path.insert(0, os.path.dirname(__file__))

from core.data_loader import DataLoader
from core.volume_profile import VolumeProfileAnalyzer
from core.support_strength import SupportStrengthAnalyzer
from core.interactive_input import InteractiveInput

console = Console()


def main():
    parser = argparse.ArgumentParser(description="CL Volume Profile & Option Zone Calculator")
    parser.add_argument("--interactive", "-i", action="store_true", help="啟用互動式參數詢問 / Enable interactive parameter input")
    parser.add_argument("--symbol", type=str, default="CL=F", help="Ticker Symbol (default: CL=F)")
    parser.add_argument("--period", type=str, default="5d", help="Lookback period (e.g. 5d, 1mo)")
    parser.add_argument("--bins", type=int, default=150, help="Number of price bins")
    parser.add_argument("--lang", type=str, default="zh-TW", choices=["zh-TW", "en"], help="Language / 語言")
    args = parser.parse_args()

    # 互動式模式
    if args.interactive:
        run_interactive_mode()
    else:
        run_command_mode(args)


def run_interactive_mode():
    """執行互動式參數詢問模式"""
    interactor = InteractiveInput()
    settings = interactor.run_interactive()
    
    if settings is None:
        console.print("[yellow]操作已取消 / Operation cancelled[/]")
        return
    
    # 使用取得的設定執行分析
    args = argparse.Namespace(
        symbol=settings["symbol"],
        period=settings["period"],
        bins=settings["bins"]
    )
    
    # 根據語言設定顯示歡迎訊息
    if settings["language"] == "zh-TW":
        console.print(Panel.fit(f"[bold gold1]📊 CL 選擇權區域分析器[/]\n[dim]標的: {args.symbol} | 週期: {args.period}[/]", border_style="gold1"))
    else:
        console.print(Panel.fit(f"[bold gold1]📊 CL Option Zone Analyzer[/]\n[dim]Target: {args.symbol} | Period: {args.period}[/]", border_style="gold1"))

    execute_analysis(args, settings["language"])


def run_command_mode(args):
    """執行命令行參數模式"""
    lang = args.lang
    
    if lang == "zh-TW":
        console.print(Panel.fit(f"[bold gold1]📊 CL 選擇權區域分析器[/]\n[dim]標的: {args.symbol} | 週期: {args.period}[/]", border_style="gold1"))
    else:
        console.print(Panel.fit(f"[bold gold1]📊 CL Option Zone Analyzer[/]\n[dim]Target: {args.symbol} | Period: {args.period}[/]", border_style="gold1"))
    
    execute_analysis(args, lang)

    execute_analysis(args, lang)

def display_report(price, res, strength_res, lang="zh-TW"):
    # 根據語言設定
    if lang == "zh-TW":
        titles = {
            "key_levels": "🛡️ 關鍵價位與區域",
            "metric": "指標",
            "price_level": "價格",
            "relation": "與現價關係",
            "current_price": "現價",
            "vah": "價值區高點 (VAH)",
            "poc": "控制點 (POC)",
            "val": "價值區低點 (VAL)",
            "strength_ranking": "💪 支撐強度排名 (前15)",
            "rank": "排名",
            "strength_score": "強度分數",
            "z_score": "Z分數",
            "distance": "距離",
            "inside_value": "【區間內】",
            "above_value": "【區間上】(多頭/超買)",
            "below_value": "【區間下】(空頭/折扣)",
            "market_context": "市場環境",
            "strategic_bias": "🎯 策略傾向",
            "poc_target": "POC 回歸目標",
            "vah_resistance": "VAH 阻力/突破點",
            "val_support": "VAL 支撐/跌破點",
            "high_volume_nodes": "⚠️ 高成交量節點 (結構性價位)",
            "low_volume_nodes": "🚀 低成交量節點 (流動性真空)",
            "analysis_title": "📊 量化分析"
        }
    else:
        titles = {
            "key_levels": "🛡️ Key Levels & Zones",
            "metric": "Metric",
            "price_level": "Price Level",
            "relation": "Relation to Spot",
            "current_price": "Current Price",
            "vah": "VAH (Value Area High)",
            "poc": "POC (Point of Control)",
            "val": "VAL (Value Area Low)",
            "strength_ranking": "💪 Support Strength Ranking (Top 15)",
            "rank": "Rank",
            "strength_score": "Strength Score",
            "z_score": "Z-Score",
            "distance": "Distance",
            "inside_value": "[bold green]INSIDE VALUE[/]",
            "above_value": "[bold red]ABOVE VALUE (Bullish/Overextended)[/]",
            "below_value": "[bold blue]BELOW VALUE (Bearish/Discount)[/]",
            "market_context": "Market Context",
            "strategic_bias": "🎯 Strategic Bias",
            "poc_target": "POC - Mean Reversion Target",
            "vah_resistance": "VAH - Resistance / Breakout Level",
            "val_support": "VAL - Support / Breakdown Level",
            "high_volume_nodes": "⚠️ High Volume Nodes (Structural Levels)",
            "low_volume_nodes": "🚀 Low Volume Nodes (Liquidity Voids)",
            "analysis_title": "📊 Quantitative Analysis"
        }
    
    # Determine Trend/Zone
    if lang == "zh-TW":
        if price > res['VAH']:
            zone_status = titles["above_value"]
        elif price < res['VAL']:
            zone_status = titles["below_value"]
        else:
            zone_status = titles["inside_value"]
    else:
        if price > res['VAH']:
            zone_status = titles["above_value"]
        elif price < res['VAL']:
            zone_status = titles["below_value"]
        else:
            zone_status = titles["inside_value"]

    # Main Table
    table = Table(title=titles["key_levels"], show_header=True, header_style="bold magenta")
    table.add_column(titles["metric"], style="cyan")
    table.add_column(titles["price_level"], style="yellow", justify="right")
    table.add_column(titles["relation"], style="white")

    def get_diff(level):
        diff = price - level
        color = "red" if diff < 0 else "green"
        return f"[{color}]{diff:+.2f}[/]"

    table.add_row(titles["current_price"], f"{price:.2f}", "-")
    table.add_row(titles["vah"], f"{res['VAH']}", get_diff(res['VAH']))
    table.add_row(titles["poc"], f"[bold]{res['POC']}[/]", get_diff(res['POC']))
    table.add_row(titles["val"], f"{res['VAL']}", get_diff(res['VAL']))

    console.print(table)
    
    # 支撐強度排名表
    strength_table = Table(title=titles["strength_ranking"], show_header=True, header_style="bold gold1")
    strength_table.add_column(titles["rank"], style="cyan", width=6)
    strength_table.add_column(titles["price_level"], style="yellow", justify="right", width=10)
    strength_table.add_column(titles["strength_score"], style="white", justify="right", width=14)
    strength_table.add_column(titles["z_score"], style="magenta", justify="right", width=10)
    strength_table.add_column(titles["distance"], style="dim", justify="right", width=10)
    
    # 取前15名
    top_n = 15
    for i in range(min(top_n, len(strength_res['ranks']))):
        rank = strength_res['ranks'][i]
        level = strength_res['levels'][i]
        score = strength_res['normalized'][i]
        z_score = strength_res['z_scores'][i]
        
        # 計算距離當前價格
        distance = ((level - price) / price) * 100
        distance_str = f"{distance:+.2f}%"
        
        # 高亮POC/VAH/VAL
        level_str = f"{level:.2f}"
        if lang == "zh-TW":
            if abs(level - res['POC']) < 0.5:
                level_str = f"[bold yellow]{level:.2f} (POC)[/]"
            elif abs(level - res['VAH']) < 0.5:
                level_str = f"[bold red]{level:.2f} (VAH)[/]"
            elif abs(level - res['VAL']) < 0.5:
                level_str = f"[bold green]{level:.2f} (VAL)[/]"
        else:
            if abs(level - res['POC']) < 0.5:
                level_str = f"[bold yellow]{level:.2f} (POC)[/]"
            elif abs(level - res['VAH']) < 0.5:
                level_str = f"[bold red]{level:.2f} (VAH)[/]"
            elif abs(level - res['VAL']) < 0.5:
                level_str = f"[bold green]{level:.2f} (VAL)[/]"
        
        # 分數條形圖
        bar_length = int(score / 5)
        score_bar = "█" * bar_length
        score_str = f"{score:6.2f} {score_bar}"
        
        strength_table.add_row(
            f"#{rank}",
            level_str,
            score_str,
            f"{z_score:.2f}",
            distance_str
        )
    
    console.print(strength_table)
    
    # Strategy Signal
    if lang == "zh-TW":
        strat_panel = f"""
    [bold underline]{titles['market_context']}[/]: {zone_status}
    
    [bold]{titles['strategic_bias']}:[/bold]
    • [bold yellow]{titles['poc_target']}: {res['POC']}
    • [bold red]{titles['vah_resistance']}: {res['VAH']}
    • [bold green]{titles['val_support']}: {res['VAL']}
    
    [bold]{titles['high_volume_nodes']}:[/]
    {', '.join([str(x) for x in res['HVNs']])}
    
    [bold]{titles['low_volume_nodes']}:[/]
    {', '.join([str(x) for x in res['LVNs']])}
    """
    else:
        strat_panel = f"""
    [bold underline]{titles['market_context']}[/]: {zone_status}
    
    [bold]{titles['strategic_bias']}:[/bold]
    • [bold yellow]{titles['poc_target']}: {res['POC']}
    • [bold red]{titles['vah_resistance']}: {res['VAH']}
    • [bold green]{titles['val_support']}: {res['VAL']}
    
    [bold]{titles['high_volume_nodes']}:[/]
    {', '.join([str(x) for x in res['HVNs']])}
    
    [bold]{titles['low_volume_nodes']}:[/]
    {', '.join([str(x) for x in res['LVNs']])}
    """
    
    console.print(Panel(strat_panel, title=titles["analysis_title"], border_style="cyan"))


def execute_analysis(args, lang="zh-TW"):
    """執行分析的核心邏輯"""
    # 1. Load Data
    loader = DataLoader(args.symbol)
    
    # 根據語言設定訊息
    if lang == "zh-TW":
        status_messages = {
            "fetching": "[bold green]正在獲取數據...[/]",
            "loaded": f"✅ 數據已載入: [cyan]{{}}[/] 根K線。現價: [bold white]{{:.2f}}[/]",
            "volume_profile": "[bold blue]計算成交量分布...[/]",
            "support_strength": "[bold magenta]計算支撐強度...[/]",
            "error_load": "[red]載入數據錯誤: {}[/]",
            "error_analysis": "[red]分析錯誤: {}[/]"
        }
    else:
        status_messages = {
            "fetching": "[bold green]Fetching Data...[/]",
            "loaded": f"✅ Data loaded: [cyan]{{}}[/] candles. Last Price: [bold white]{{:.2f}}[/]",
            "volume_profile": "[bold blue]Calculating Volume Profile...[/]",
            "support_strength": "[bold magenta]Calculating Support Strength...[/]",
            "error_load": "[red]Error loading data: {}[/]",
            "error_analysis": "[red]Analysis Error: {}[/]"
        }
    
    try:
        with console.status(status_messages["fetching"]):
            df = loader.fetch_data(period=args.period, interval="5m")
            current_price = loader.get_latest_price()
            
        console.print(status_messages["loaded"].format(len(df), current_price))
        
    except Exception as e:
        console.print(status_messages["error_load"].format(e))
        return

    # 2. Analyze
    try:
        with console.status(status_messages["volume_profile"]):
            analyzer = VolumeProfileAnalyzer(df, n_bins=args.bins)
            results = analyzer.calculate()
            
        # 3. 支撐強度分析
        with console.status(status_messages["support_strength"]):
            strength_analyzer = SupportStrengthAnalyzer(
                df, 
                analyzer.profile, 
                analyzer.bin_prices
            )
            strength_results = strength_analyzer.calculate(current_price)
            
    except Exception as e:
        console.print(status_messages["error_analysis"].format(e))
        import traceback
        console.print(traceback.format_exc())
        return

    # 4. Report
    display_report(current_price, results, strength_results, lang)

if __name__ == "__main__":
    main()