Portfolio

Access and manage your portfolio including positions, holdings, order book, and trade book through the PyArrow SDK.

Positions

Get your current trading positions across all segments.

from pyarrow_client import ArrowClient

client = ArrowClient(app_id="your_app_id")
# ... authenticate ...

# Get all positions
positions = client.get_positions()

for position in positions:
    print(f"Symbol: {position['symbol']}")
    print(f"Exchange: {position['exchange']}")
    print(f"Quantity: {position['quantity']}")
    print(f"Average Price: ₹{position['averagePrice']}")
    print(f"P&L: ₹{position['pnl']}")
    print("-" * 40)

Position Fields

Field	Type	Description
symbol	string	Trading symbol
exchange	string	Exchange code (NSE/BSE/NFO/BFO)
quantity	string	Net position quantity
averagePrice	string	Average entry price
ltp	string	Last traded price
pnl	string	Profit/Loss
product	string	Product type (I/C/M)
buyQuantity	string	Buy quantity
sellQuantity	string	Sell quantity
buyValue	string	Buy value
sellValue	string	Sell value

Example: Position Analysis

def analyze_positions(client):
    """Analyze current positions and calculate total P&L."""

    positions = client.get_positions()

    if not positions:
        print("No open positions")
        return

    total_pnl = 0

    print("=" * 60)
    print(f"{'Symbol':<20} {'Qty':>10} {'P&L':>15}")
    print("=" * 60)

    for pos in positions:
        symbol = pos.get('symbol', 'N/A')
        qty = pos.get('quantity', '0')
        pnl = float(pos.get('pnl', 0))
        total_pnl += pnl

        pnl_str = f"₹{pnl:,.2f}"
        print(f"{symbol:<20} {qty:>10} {pnl_str:>15}")

    print("=" * 60)
    print(f"{'Total P&L':<31} ₹{total_pnl:>14,.2f}")

    return total_pnl

# Usage
total = analyze_positions(client)

Holdings

Get your delivery holdings (stocks held in demat account).

# Get all holdings
holdings = client.get_holdings()

print(f"Holdings: {holdings}")

Holdings Structure

# Iterate through holdings
for holding in holdings.get('data', []):
    print(f"Symbol: {holding['symbol']}")
    print(f"Quantity: {holding['quantity']}")
    print(f"Average Price: ₹{holding['averagePrice']}")
    print(f"Current Value: ₹{holding['currentValue']}")
    print(f"P&L: ₹{holding['pnl']}")
    print("-" * 40)

Holdings Fields

Field	Type	Description
symbol	string	Stock symbol
isin	string	ISIN code
quantity	string	Number of shares held
averagePrice	string	Average purchase price
ltp	string	Last traded price
currentValue	string	Current market value
pnl	string	Unrealized profit/loss
pnlPercent	string	P&L percentage

Example: Holdings Summary

def holdings_summary(client):
    """Generate holdings portfolio summary."""

    holdings = client.get_holdings()

    total_invested = 0
    total_current = 0

    print("\n📊 PORTFOLIO HOLDINGS")
    print("=" * 70)
    print(f"{'Symbol':<15} {'Qty':>8} {'Avg':>10} {'LTP':>10} {'P&L':>12} {'%':>8}")
    print("-" * 70)

    for holding in holdings.get('data', []):
        symbol = holding.get('symbol', 'N/A')
        qty = int(holding.get('quantity', 0))
        avg = float(holding.get('averagePrice', 0))
        ltp = float(holding.get('ltp', 0))
        pnl = float(holding.get('pnl', 0))
        pnl_pct = float(holding.get('pnlPercent', 0))

        invested = qty * avg
        current = qty * ltp
        total_invested += invested
        total_current += current

        print(f"{symbol:<15} {qty:>8} {avg:>10.2f} {ltp:>10.2f} {pnl:>12.2f} {pnl_pct:>7.2f}%")

    print("=" * 70)
    total_pnl = total_current - total_invested
    total_pnl_pct = (total_pnl / total_invested * 100) if total_invested > 0 else 0

    print(f"{'Invested:':<35} ₹{total_invested:>12,.2f}")
    print(f"{'Current Value:':<35} ₹{total_current:>12,.2f}")
    print(f"{'Total P&L:':<35} ₹{total_pnl:>12,.2f} ({total_pnl_pct:.2f}%)")

    return {
        'invested': total_invested,
        'current': total_current,
        'pnl': total_pnl,
        'pnl_percent': total_pnl_pct
    }

# Usage
summary = holdings_summary(client)

Order Book

Access your complete order book for the trading day.

# Get all orders
orders = client.get_order_book()

for order in orders:
    print(f"Order ID: {order['id']}")
    print(f"Symbol: {order['symbol']} ({order['exchange']})")
    print(f"Type: {order['transactionType']} {order['order']}")
    print(f"Qty: {order['quantity']} @ ₹{order['price']}")
    print(f"Status: {order['orderStatus']}")
    print(f"Filled: {order['cumulativeFillQty']}")
    print("-" * 40)

Order Book Fields

Field	Type	Description
id	string	Order ID
exchange	string	Exchange code
symbol	string	Trading symbol
price	string	Order price
quantity	string	Order quantity
product	string	Product type
orderStatus	string	PENDING/OPEN/COMPLETE/CANCELLED/REJECTED
transactionType	string	B (Buy) / S (Sell)
order	string	Order type (LMT/MKT/SL-LMT/SL-MKT)
cumulativeFillQty	string	Quantity filled so far
averagePrice	string	Average execution price
exchangeOrderID	string	Exchange order number
orderTime	string	Order timestamp
rejectReason	string	Rejection reason (if rejected)

Example: Order Analysis

def order_analysis(client):
    """Analyze today's orders by status."""

    orders = client.get_order_book()

    status_count = {
        'PENDING': 0,
        'OPEN': 0,
        'COMPLETE': 0,
        'CANCELLED': 0,
        'REJECTED': 0
    }

    for order in orders:
        status = order.get('orderStatus', 'UNKNOWN')
        if status in status_count:
            status_count[status] += 1

    print("\n📋 ORDER SUMMARY")
    print("=" * 30)
    for status, count in status_count.items():
        emoji = {
            'PENDING': '⏳',
            'OPEN': '📖',
            'COMPLETE': '✅',
            'CANCELLED': '❌',
            'REJECTED': '🚫'
        }.get(status, '•')
        print(f"{emoji} {status}: {count}")
    print("=" * 30)
    print(f"Total Orders: {len(orders)}")

    return status_count

# Usage
order_stats = order_analysis(client)

Trade Book

Review all executed trades for the day.

# Get all trades
trades = client.get_trade_book()

for trade in trades:
    print(f"Order ID: {trade['id']}")
    print(f"Symbol: {trade['symbol']} ({trade['exchange']})")
    print(f"Type: {trade['transactionType']}")
    print(f"Fill Price: ₹{trade['fillPrice']}")
    print(f"Fill Qty: {trade['fillQuantity']}")
    print(f"Time: {trade['exchangeUpdateTime']}")
    print("-" * 40)

Trade Book Fields

Field	Type	Description
id	string	Order ID
exchange	string	Exchange code
symbol	string	Trading symbol
quantity	string	Order quantity
product	string	Product type
transactionType	string	B (Buy) / S (Sell)
order	string	Order type
fillPrice	string	Execution price
fillQuantity	string	Executed quantity
fillTime	string	Execution timestamp
fillID	string	Trade/Fill ID
exchangeOrderID	string	Exchange order number
averagePrice	string	Average price

Example: Trade Summary

def trade_summary(client):
    """Generate trade summary with buy/sell breakdown."""

    trades = client.get_trade_book()

    buy_value = 0
    sell_value = 0
    buy_count = 0
    sell_count = 0

    print("\n📈 TRADE BOOK")
    print("=" * 80)
    print(f"{'Time':<20} {'Symbol':<15} {'Type':<6} {'Qty':>8} {'Price':>12} {'Value':>15}")
    print("-" * 80)

    for trade in trades:
        time = trade.get('exchangeUpdateTime', '')[:19]
        symbol = trade.get('symbol', 'N/A')
        txn_type = 'BUY' if trade.get('transactionType') == 'B' else 'SELL'
        qty = int(trade.get('fillQuantity', 0))
        price = float(trade.get('fillPrice', 0))
        value = qty * price

        if trade.get('transactionType') == 'B':
            buy_value += value
            buy_count += 1
        else:
            sell_value += value
            sell_count += 1

        print(f"{time:<20} {symbol:<15} {txn_type:<6} {qty:>8} ₹{price:>11.2f} ₹{value:>14,.2f}")

    print("=" * 80)
    print(f"\n💰 Buy Trades: {buy_count} | Value: ₹{buy_value:,.2f}")
    print(f"💰 Sell Trades: {sell_count} | Value: ₹{sell_value:,.2f}")
    print(f"📊 Net Turnover: ₹{buy_value + sell_value:,.2f}")

    return {
        'buy_value': buy_value,
        'sell_value': sell_value,
        'total_trades': len(trades)
    }

# Usage
summary = trade_summary(client)

User Limits & Funds

Get available margins and trading limits.

# Get user limits
limits = client.get_user_limits()

for limit in limits:
    print(f"Segment: {limit.get('segment')}")
    print(f"Available Margin: ₹{limit.get('availableMargin')}")
    print(f"Used Margin: ₹{limit.get('usedMargin')}")
    print(f"Total Margin: ₹{limit.get('totalMargin')}")
    print("-" * 40)

User Limits Fields

Field	Type	Description
segment	string	Trading segment
availableMargin	string	Available funds for trading
usedMargin	string	Margin currently in use
totalMargin	string	Total margin value
openingBalance	string	Opening balance
payIn	string	Funds added today
payOut	string	Funds withdrawn today

User Details

Get authenticated user's profile information.

# Get user details
user = client.get_user_details()

print(f"User ID: {user.get('userID')}")
print(f"Name: {user.get('name')}")
print(f"Email: {user.get('email')}")
print(f"Phone: {user.get('phone')}")
print(f"PAN: {user.get('pan')}")

Complete Example

from pyarrow_client import ArrowClient

def portfolio_dashboard(client):
    """Complete portfolio dashboard."""

    print("\n" + "=" * 60)
    print("📊 PORTFOLIO DASHBOARD")
    print("=" * 60)

    # User Info
    user = client.get_user_details()
    print(f"\n👤 Welcome, {user.get('name', 'Trader')}!")

    # Funds Summary
    limits = client.get_user_limits()
    if limits:
        total_available = sum(float(l.get('availableMargin', 0)) for l in limits)
        print(f"\n💰 Available Margin: ₹{total_available:,.2f}")

    # Holdings
    holdings = client.get_holdings()
    if holdings.get('data'):
        print(f"\n📦 Holdings: {len(holdings['data'])} stocks")

    # Positions
    positions = client.get_positions()
    if positions:
        total_pnl = sum(float(p.get('pnl', 0)) for p in positions)
        print(f"\n📈 Open Positions: {len(positions)}")
        print(f"   Day P&L: ₹{total_pnl:,.2f}")
    else:
        print("\n📈 No open positions")

    # Orders
    orders = client.get_order_book()
    open_orders = [o for o in orders if o.get('orderStatus') in ['PENDING', 'OPEN']]
    print(f"\n📋 Today's Orders: {len(orders)}")
    print(f"   Open Orders: {len(open_orders)}")

    # Trades
    trades = client.get_trade_book()
    print(f"\n✅ Trades Executed: {len(trades)}")

    print("\n" + "=" * 60)

# Usage
client = ArrowClient(app_id="your_app_id")
# ... authenticate ...
portfolio_dashboard(client)