quantumbotx/core/brokers/indonesian_brokers.py

# core/brokers/indonesian_brokers.py
"""
Indonesian Market Brokers Integration for QuantumBotX
Supporting local Indonesian brokers and international brokers popular in Indonesia
"""

import pandas as pd
import time
import requests
import json
import numpy as np
from datetime import datetime, timedelta
from typing import Dict, List, Optional
import logging

from .base_broker import (
    BaseBroker, OrderType, OrderStatus, Timeframe, 
    Position, Order, AccountInfo
)

logger = logging.getLogger(__name__)

class IndopremierBroker(BaseBroker):
    """
    Indopremier Securities (IPOT) - Popular Indonesian broker
    Known for good demo accounts and local market access
    """
    
    def __init__(self, demo: bool = True):
        super().__init__("Indopremier")
        self.demo = demo
        self.base_url = "https://demo-api.indopremier.com" if demo else "https://api.indopremier.com"
        self.session = requests.Session()
        
        # Indonesian market symbols
        self.supported_symbols = [
            # IDX (Indonesian Stock Exchange) - Blue chips
            'BBCA.JK',    # Bank Central Asia
            'BBRI.JK',    # Bank Rakyat Indonesia  
            'BMRI.JK',    # Bank Mandiri
            'TLKM.JK',    # Telkom Indonesia
            'ASII.JK',    # Astra International
            'UNVR.JK',    # Unilever Indonesia
            'ICBP.JK',    # Indofood CBP
            'INDF.JK',    # Indofood Sukses Makmur
            'GGRM.JK',    # Gudang Garam
            'HMSP.JK',    # HM Sampoerna
            
            # IDX ETFs and Indices
            'LQ45.JK',    # LQ45 Index
            'IHSG.JK',    # Jakarta Composite Index
            
            # International through Indopremier
            'USDID',      # USD/IDR
            'USDIDR',     # USD/IDR alternative
            'XAUIDR',     # Gold in IDR
        ]
    
    def connect(self, credentials: Dict) -> bool:
        """Connect to Indopremier"""
        try:
            username = credentials.get("username")
            password = credentials.get("password")
            
            if not all([username, password]):
                logger.error("Indopremier username and password required")
                return False
            
            # Simulate authentication for demo
            if self.demo:
                self.is_connected = True
                logger.info("Connected to Indopremier Demo")
                return True
            
            # Real implementation would use actual API
            auth_data = {
                'username': username,
                'password': password
            }
            
            # This would be actual API call
            self.is_connected = True
            logger.info("Connected to Indopremier Live")
            return True
            
        except Exception as e:
            logger.error(f"Failed to connect to Indopremier: {e}")
            return False
    
    def get_market_data(self, symbol: str, timeframe: Timeframe, count: int = 500) -> pd.DataFrame:
        """Get Indonesian market data"""
        try:
            # For demo, generate realistic Indonesian stock data
            dates = pd.date_range(end=datetime.now(), periods=count, freq='1h')
            
            # Realistic prices for Indonesian stocks
            base_prices = {
                'BBCA.JK': 9000,   # BCA around 9,000 IDR
                'BBRI.JK': 4500,   # BRI around 4,500 IDR
                'BMRI.JK': 8500,   # Mandiri around 8,500 IDR
                'TLKM.JK': 3200,   # Telkom around 3,200 IDR
                'ASII.JK': 6800,   # Astra around 6,800 IDR
                'UNVR.JK': 7200,   # Unilever around 7,200 IDR
                'USDID': 15400,    # USD/IDR around 15,400
                'XAUIDR': 1000000, # Gold around 1M IDR per oz
            }
            
            base_price = base_prices.get(symbol, 5000)
            
            # Indonesian market volatility (generally lower than crypto)
            volatility = 0.015 if '.JK' in symbol else 0.008  # 1.5% for stocks, 0.8% for forex
            
            # Generate price movements
            returns = np.random.randn(count) * volatility
            prices = base_price * (1 + returns).cumprod()
            
            df = pd.DataFrame({
                'time': dates,
                'open': prices,
                'high': prices * (1 + np.random.uniform(0, 0.01, count)),
                'low': prices * (1 - np.random.uniform(0, 0.01, count)),
                'close': prices,
                'volume': np.random.randint(100000, 1000000, count)  # Indonesian market volumes
            })
            
            # Ensure OHLC integrity
            df['high'] = df[['high', 'close', 'open']].max(axis=1)
            df['low'] = df[['low', 'close', 'open']].min(axis=1)
            
            # Adjust for Indonesian market hours (09:00-16:00 WIB, Mon-Fri)
            # Filter out weekend data for stock symbols
            if '.JK' in symbol:
                df = df[df['time'].dt.weekday < 5]  # Monday=0, Sunday=6
            
            return df
            
        except Exception as e:
            logger.error(f"Failed to get Indopremier market data for {symbol}: {e}")
            return pd.DataFrame()
    def disconnect(self) -> bool:
        """Disconnect from Indopremier"""
        self.is_connected = False
        logger.info("Disconnected from Indopremier")
        return True
    
    def get_symbols(self) -> List[str]:
        """Get list of available trading symbols"""
        return self.supported_symbols
    
    def get_current_price(self, symbol: str) -> Dict[str, float]:
        """Get current bid/ask prices"""
        try:
            # For demo, use last price from market data
            df = self.get_market_data(symbol, Timeframe.M1, 1)
            if not df.empty:
                last_price = df.iloc[-1]['close']
                spread = last_price * 0.001  # 0.1% spread for Indonesian stocks
                return {
                    "bid": last_price - spread/2,
                    "ask": last_price + spread/2
                }
            return {"bid": 0.0, "ask": 0.0}
        except Exception as e:
            logger.error(f"Failed to get Indopremier current price for {symbol}: {e}")
            return {"bid": 0.0, "ask": 0.0}
    
    def place_order(self, symbol: str, order_type: OrderType, side: str,
                   size: float, price: Optional[float] = None,
                   stop_loss: Optional[float] = None,
                   take_profit: Optional[float] = None) -> Order:
        """Place order (simulated for demo)"""
        try:
            order_id = str(int(time.time()))
            
            # For Indonesian stocks, size is in lots (100 shares)
            if '.JK' in symbol:
                size = max(1, int(size))  # Minimum 1 lot
            
            order = Order(
                order_id=order_id,
                symbol=symbol,
                order_type=order_type,
                side=side.lower(),
                size=size,
                price=price
            )
            
            # Simulate immediate execution for demo
            order.status = OrderStatus.FILLED
            order.filled_size = size
            
            current_price = self.get_current_price(symbol)
            order.avg_fill_price = current_price['ask'] if side.lower() == 'buy' else current_price['bid']
            
            logger.info(f"Indopremier demo order: {side} {size} {symbol} at {order.avg_fill_price}")
            return order
            
        except Exception as e:
            logger.error(f"Failed to place Indopremier order: {e}")
            order = Order(
                order_id="failed",
                symbol=symbol,
                order_type=order_type,
                side=side.lower(),
                size=size,
                price=price
            )
            order.status = OrderStatus.REJECTED
            return order
    
    def cancel_order(self, order_id: str) -> bool:
        """Cancel an existing order"""
        logger.info(f"Indopremier demo: Order {order_id} cancelled")
        return True
    
    def get_positions(self) -> List[Position]:
        """Get all open positions"""
        # For demo, return empty list
        return []
    
    def get_orders(self) -> List[Order]:
        """Get all pending orders"""
        # For demo, return empty list
        return []
    
    def get_account_info(self) -> AccountInfo:
        """Get account information"""
        try:
            return AccountInfo(
                balance=1000000000,  # 1 billion IDR demo balance
                equity=1000000000,
                margin=0.0,
                free_margin=1000000000,
                margin_level=100.0,
                currency="IDR"
            )
        except Exception as e:
            logger.error(f"Failed to get Indopremier account info: {e}")
            return AccountInfo(0, 0, 0, 0, 0, "IDR")
    
    def get_trade_history(self, days: int = 30) -> List[Dict]:
        """Get trade history"""
        # For demo, return empty list
        return []

class XMIndonesiaBroker(BaseBroker):
    """
    XM Indonesia - Popular international broker in Indonesia
    Offers forex, commodities, and indices with good demo accounts
    """
    
    def __init__(self, demo: bool = True):
        super().__init__("XM Indonesia")
        self.demo = demo
        
        # XM Indonesia popular symbols
        self.supported_symbols = [
            # Major Forex pairs
            'EURUSD', 'GBPUSD', 'USDJPY', 'USDCHF', 'AUDUSD', 'USDCAD',
            'NZDUSD', 'EURGBP', 'EURJPY', 'GBPJPY',
            
            # IDR pairs (if available)
            'USDIDR', 'EURIDR', 'GBPIDR', 'JPYIDR',
            
            # Commodities popular in Indonesia
            'XAUUSD', 'XAGUSD', 'USOIL', 'UKOIL', 'NGAS',
            
            # Indices
            'US30', 'SPX500', 'NAS100', 'UK100', 'GER30', 'FRA40',
            'AUS200', 'JPN225', 'HK50',
            
            # Cryptocurrency CFDs
            'BTCUSD', 'ETHUSD', 'LTCUSD', 'XRPUSD'
        ]
    
    def connect(self, credentials: Dict) -> bool:
        """Connect to XM Indonesia"""
        try:
            login = credentials.get("login")
            password = credentials.get("password")
            server = credentials.get("server", "XM-Demo" if self.demo else "XM-Real")
            
            if not all([login, password]):
                logger.error("XM Indonesia login and password required")
                return False
            
            # XM uses MT4/MT5 platform, so similar to existing MT5 integration
            self.is_connected = True
            
            logger.info(f"Connected to XM Indonesia {'Demo' if self.demo else 'Live'}")
            return True
            
        except Exception as e:
            logger.error(f"Failed to connect to XM Indonesia: {e}")
            return False
    
    def disconnect(self) -> bool:
        self.is_connected = False
        return True
    
    def get_symbols(self) -> List[str]:
        return self.supported_symbols
    
    def get_market_data(self, symbol: str, timeframe: Timeframe, count: int = 500) -> pd.DataFrame:
        # Generate simulated forex data
        dates = pd.date_range(end=datetime.now(), periods=count, freq='1h')
        base_prices = {'EURUSD': 1.0850, 'USDIDR': 15400, 'XAUUSD': 2020}
        base_price = base_prices.get(symbol, 1.0)
        
        returns = np.random.randn(count) * 0.01
        prices = base_price * (1 + returns).cumprod()
        
        return pd.DataFrame({
            'time': dates, 'open': prices, 'high': prices * 1.002, 
            'low': prices * 0.998, 'close': prices, 'volume': np.random.randint(1000, 10000, count)
        })
    
    def get_current_price(self, symbol: str) -> Dict[str, float]:
        df = self.get_market_data(symbol, Timeframe.M1, 1)
        if not df.empty:
            price = df.iloc[-1]['close']
            return {"bid": price - 0.0001, "ask": price + 0.0001}
        return {"bid": 0.0, "ask": 0.0}
    
    def place_order(self, symbol: str, order_type: OrderType, side: str, size: float, 
                   price: Optional[float] = None, stop_loss: Optional[float] = None, 
                   take_profit: Optional[float] = None) -> Order:
        order = Order(str(int(time.time())), symbol, order_type, side.lower(), size, price)
        order.status = OrderStatus.FILLED
        return order
    
    def cancel_order(self, order_id: str) -> bool:
        return True
    
    def get_positions(self) -> List[Position]:
        return []
    
    def get_orders(self) -> List[Order]:
        return []
    
    def get_account_info(self) -> AccountInfo:
        return AccountInfo(10000, 10000, 0, 10000, 100, "USD")
    
    def get_trade_history(self, days: int = 30) -> List[Dict]:
        return []

class OctaFXIndonesiaBroker(BaseBroker):
    """
    OctaFX Indonesia - Another popular international broker
    Known for good spreads and demo accounts
    """
    
    def __init__(self, demo: bool = True):
        super().__init__("OctaFX Indonesia")
        self.demo = demo
        
        self.supported_symbols = [
            # Forex majors and minors
            'EURUSD', 'GBPUSD', 'USDJPY', 'USDCHF', 'AUDUSD', 'USDCAD',
            'NZDUSD', 'EURGBP', 'EURJPY', 'GBPJPY', 'AUDJPY', 'NZDJPY',
            'EURCHF', 'GBPCHF', 'AUDCHF', 'NZDCHF', 'CADCHF', 'CHFJPY',
            
            # Exotic pairs including IDR
            'USDIDR', 'USDSGD', 'USDTHB', 'USDMYR',
            
            # Metals
            'XAUUSD', 'XAGUSD', 'XPDUSD', 'XPTUSD',
            
            # Energies
            'USOIL', 'UKOIL', 'NGAS',
            
            # Indices
            'SPX500', 'NAS100', 'US30', 'UK100', 'GER30', 'FRA40', 'ESP35',
            'ITA40', 'AUS200', 'JPN225', 'HK50'
        ]
    
    def connect(self, credentials: Dict) -> bool:
        self.is_connected = True
        return True
    
    def disconnect(self) -> bool:
        self.is_connected = False
        return True
    
    def get_symbols(self) -> List[str]:
        return self.supported_symbols
    
    def get_market_data(self, symbol: str, timeframe: Timeframe, count: int = 500) -> pd.DataFrame:
        dates = pd.date_range(end=datetime.now(), periods=count, freq='1h')
        base_price = 1.0850 if 'EUR' in symbol else 15400 if 'IDR' in symbol else 100
        returns = np.random.randn(count) * 0.01
        prices = base_price * (1 + returns).cumprod()
        return pd.DataFrame({
            'time': dates, 'open': prices, 'high': prices * 1.001, 
            'low': prices * 0.999, 'close': prices, 'volume': np.random.randint(1000, 5000, count)
        })
    
    def get_current_price(self, symbol: str) -> Dict[str, float]:
        df = self.get_market_data(symbol, Timeframe.M1, 1)
        if not df.empty:
            price = df.iloc[-1]['close']
            return {"bid": price - 0.0001, "ask": price + 0.0001}
        return {"bid": 0.0, "ask": 0.0}
    
    def place_order(self, symbol: str, order_type: OrderType, side: str, size: float, 
                   price: Optional[float] = None, stop_loss: Optional[float] = None, 
                   take_profit: Optional[float] = None) -> Order:
        order = Order(str(int(time.time())), symbol, order_type, side.lower(), size, price)
        order.status = OrderStatus.FILLED
        return order
    
    def cancel_order(self, order_id: str) -> bool:
        return True
    
    def get_positions(self) -> List[Position]:
        return []
    
    def get_orders(self) -> List[Order]:
        return []
    
    def get_account_info(self) -> AccountInfo:
        return AccountInfo(10000, 10000, 0, 10000, 100, "USD")
    
    def get_trade_history(self, days: int = 30) -> List[Dict]:
        return []

class HSBCIndonesiaBroker(BaseBroker):
    """
    HSBC Indonesia - International bank with trading platform
    Good for forex and international markets
    """
    
    def __init__(self, demo: bool = True):
        super().__init__("HSBC Indonesia")
        self.demo = demo
        
        self.supported_symbols = [
            # Major currencies
            'EURUSD', 'GBPUSD', 'USDJPY', 'USDCHF', 'AUDUSD', 'USDCAD',
            
            # Asian currencies (HSBC specialty)
            'USDIDR', 'USDSGD', 'USDHKD', 'USDKRW', 'USDCNY', 'USDTHB',
            'USDMYR', 'USDPHP', 'USDVND',
            
            # Cross currencies
            'EURIDR', 'GBPIDR', 'AUDIDR', 'JPYIDR', 'SGDIDR',
            
            # Precious metals
            'XAUUSD', 'XAGUSD'
        ]
    
    def connect(self, credentials: Dict) -> bool:
        self.is_connected = True
        return True
    
    def disconnect(self) -> bool:
        self.is_connected = False
        return True
    
    def get_symbols(self) -> List[str]:
        return self.supported_symbols
    
    def get_market_data(self, symbol: str, timeframe: Timeframe, count: int = 500) -> pd.DataFrame:
        dates = pd.date_range(end=datetime.now(), periods=count, freq='1h')
        base_price = 15400 if 'IDR' in symbol else 1.0850 if 'EUR' in symbol else 100
        returns = np.random.randn(count) * 0.008
        prices = base_price * (1 + returns).cumprod()
        return pd.DataFrame({
            'time': dates, 'open': prices, 'high': prices * 1.001, 
            'low': prices * 0.999, 'close': prices, 'volume': np.random.randint(500, 2000, count)
        })
    
    def get_current_price(self, symbol: str) -> Dict[str, float]:
        df = self.get_market_data(symbol, Timeframe.M1, 1)
        if not df.empty:
            price = df.iloc[-1]['close']
            return {"bid": price - 0.0002, "ask": price + 0.0002}
        return {"bid": 0.0, "ask": 0.0}
    
    def place_order(self, symbol: str, order_type: OrderType, side: str, size: float, 
                   price: Optional[float] = None, stop_loss: Optional[float] = None, 
                   take_profit: Optional[float] = None) -> Order:
        order = Order(str(int(time.time())), symbol, order_type, side.lower(), size, price)
        order.status = OrderStatus.FILLED
        return order
    
    def cancel_order(self, order_id: str) -> bool:
        return True
    
    def get_positions(self) -> List[Position]:
        return []
    
    def get_orders(self) -> List[Order]:
        return []
    
    def get_account_info(self) -> AccountInfo:
        return AccountInfo(10000, 10000, 0, 10000, 100, "USD")
    
    def get_trade_history(self, days: int = 30) -> List[Dict]:
        return []

# Factory function for Indonesian brokers
def create_indonesian_broker(broker_name: str, demo: bool = True) -> BaseBroker:
    """Create Indonesian broker instance"""
    brokers = {
        'indopremier': IndopremierBroker,
        'xm_indonesia': XMIndonesiaBroker,
        'octafx_indonesia': OctaFXIndonesiaBroker,
        'hsbc_indonesia': HSBCIndonesiaBroker
    }
    
    broker_class = brokers.get(broker_name.lower())
    if broker_class:
        return broker_class(demo=demo)
    else:
        raise ValueError(f"Unknown Indonesian broker: {broker_name}")

# Indonesian market information
INDONESIAN_MARKET_INFO = {
    'market_hours': {
        'idx_stocks': 'Monday-Friday 09:00-16:00 WIB (GMT+7)',
        'forex_local': '24/5 (follows global forex)',
        'commodities': '24/5 (follows global commodities)'
    },
    'popular_stocks': {
        'BBCA.JK': 'Bank Central Asia - Largest private bank',
        'BBRI.JK': 'Bank Rakyat Indonesia - State-owned bank',
        'BMRI.JK': 'Bank Mandiri - Largest bank by assets',
        'TLKM.JK': 'Telkom Indonesia - Telecom giant',
        'ASII.JK': 'Astra International - Automotive conglomerate',
        'UNVR.JK': 'Unilever Indonesia - Consumer goods',
        'ICBP.JK': 'Indofood CBP - Food and beverages',
        'GGRM.JK': 'Gudang Garam - Cigarette manufacturer',
        'HMSP.JK': 'HM Sampoerna - Tobacco company'
    },
    'currency_info': {
        'base_currency': 'IDR (Indonesian Rupiah)',
        'typical_usd_idr': '15,000-16,000 IDR per USD',
        'volatility': 'Moderate, influenced by commodity prices'
    },
    'regulatory_info': {
        'regulator': 'OJK (Otoritas Jasa Keuangan)',
        'stock_exchange': 'IDX (Indonesia Stock Exchange)',
        'trading_lot': '100 shares minimum for most stocks'
    }
}