trading-core
skillCore trading operations with OpenAlgo - place orders, smart orders, basket orders, split orders, and order management across 25+ Indian brokers
apm::install
apm install @marketcalls/trading-coreapm::skill.md
---
name: trading-core
description: Core trading operations with OpenAlgo - place orders, smart orders, basket orders, split orders, and order management across 25+ Indian brokers
---
# OpenAlgo Trading Core
Execute trading operations using OpenAlgo's unified Python SDK. Supports NSE, BSE, NFO, MCX, and currency derivatives with a single API across 25+ brokers.
## Environment Setup
The `OPENALGO_API_KEY` must be set. Get your API key from your OpenAlgo application.
```python
from openalgo import api
client = api(
api_key='your_api_key_here',
host='http://127.0.0.1:5000' # Your OpenAlgo server
)
```
## Quick Start Scripts
### Place Market Order
```bash
python scripts/place_order.py --symbol RELIANCE --exchange NSE --action BUY --quantity 1 --product MIS
```
### Place Smart Order (Position-Aware)
```bash
python scripts/smart_order.py --symbol TATAMOTORS --exchange NSE --action SELL --quantity 5 --position-size 10
```
### Basket Order (Multiple Symbols)
```bash
python scripts/basket_order.py --orders '[{"symbol":"INFY","action":"BUY","quantity":1},{"symbol":"TCS","action":"BUY","quantity":1}]'
```
### Split Order (Large Quantities)
```bash
python scripts/split_order.py --symbol YESBANK --exchange NSE --action SELL --quantity 500 --split-size 100
```
---
## Order Constants
### Exchanges
| Code | Description |
|------|-------------|
| `NSE` | NSE Equity |
| `BSE` | BSE Equity |
| `NFO` | NSE Futures & Options |
| `BFO` | BSE Futures & Options |
| `CDS` | NSE Currency Derivatives |
| `BCD` | BSE Currency Derivatives |
| `MCX` | MCX Commodity |
| `NCDEX` | NCDEX Commodity |
| `NSE_INDEX` | NSE Indices (for quotes only) |
| `BSE_INDEX` | BSE Indices (for quotes only) |
### Product Types
| Code | Description | Use Case |
|------|-------------|----------|
| `CNC` | Cash & Carry | Equity delivery (hold overnight) |
| `NRML` | Normal | F&O positions (hold overnight) |
| `MIS` | Intraday | Auto square-off at market close |
### Price Types
| Code | Description |
|------|-------------|
| `MARKET` | Market Order (immediate execution) |
| `LIMIT` | Limit Order (specify price) |
| `SL` | Stop Loss Limit Order |
| `SL-M` | Stop Loss Market Order |
### Actions
| Code | Description |
|------|-------------|
| `BUY` | Buy order |
| `SELL` | Sell order |
---
## Core API Methods
### 1. Place Order
Place a single order with full control over parameters:
```python
response = client.placeorder(
strategy="MyStrategy",
symbol="RELIANCE",
action="BUY",
exchange="NSE",
price_type="MARKET",
product="MIS",
quantity=1
)
# Response: {'orderid': '250408000989443', 'status': 'success'}
```
**Limit Order Example:**
```python
response = client.placeorder(
strategy="MyStrategy",
symbol="YESBANK",
action="BUY",
exchange="NSE",
price_type="LIMIT",
product="MIS",
quantity=1,
price=16.50,
trigger_price=0,
disclosed_quantity=0
)
```
**Stop Loss Order Example:**
```python
response = client.placeorder(
strategy="MyStrategy",
symbol="SBIN",
action="SELL",
exchange="NSE",
price_type="SL",
product="MIS",
quantity=10,
price=750, # Limit price
trigger_price=752 # Trigger price
)
```
### 2. Smart Order (Position-Aware)
Automatically adjusts order quantity based on current position:
```python
response = client.placesmartorder(
strategy="SmartBot",
symbol="TATAMOTORS",
action="SELL",
exchange="NSE",
price_type="MARKET",
product="MIS",
quantity=1,
position_size=5 # Desired final position
)
# If current position is 0, sells 5 to reach -5
# If current position is 3, sells 8 to reach -5
```
**Use Cases:**
- Rebalancing: Set `position_size` to target position
- Reversal: Set `action` opposite to current direction
- Scale-in/out: Adjust `quantity` dynamically
### 3. Basket Order
Execute multiple orders simultaneously:
```python
basket_orders = [
{
"symbol": "INFY",
"exchange": "NSE",
"action": "BUY",
"quantity": 1,
"pricetype": "MARKET",
"product": "MIS"
},
{
"symbol": "TCS",
"exchange": "NSE",
"action": "BUY",
"quantity": 1,
"pricetype": "MARKET",
"product": "MIS"
},
{
"symbol": "WIPRO",
"exchange": "NSE",
"action": "BUY",
"quantity": 1,
"pricetype": "MARKET",
"product": "MIS"
}
]
response = client.basketorder(orders=basket_orders)
# Response includes status for each order
```
### 4. Split Order
Break large orders into smaller chunks to avoid market impact:
```python
response = client.splitorder(
symbol="YESBANK",
exchange="NSE",
action="SELL",
quantity=500,
splitsize=100, # Each order will be max 100
price_type="MARKET",
product="MIS"
)
# Creates 5 orders of 100 each
```
**Response:**
```json
{
"status": "success",
"split_size": 100,
"total_quantity": 500,
"results": [
{"order_num": 1, "orderid": "123", "quantity": 100, "status": "success"},
{"order_num": 2, "orderid": "124", "quantity": 100, "status": "success"},
...
]
}
```
---
## Order Management
### Modify Order
```python
response = client.modifyorder(
order_id="250408001002736",
strategy="MyStrategy",
symbol="YESBANK",
action="BUY",
exchange="NSE",
price_type="LIMIT",
product="MIS",
quantity=1,
price=17.00 # New price
)
```
### Cancel Order
```python
response = client.cancelorder(
order_id="250408001002736",
strategy="MyStrategy"
)
```
### Cancel All Orders
```python
response = client.cancelallorder(strategy="MyStrategy")
# Cancels all open and trigger-pending orders
```
### Close All Positions
```python
response = client.closeposition(strategy="MyStrategy")
# Squares off all open positions
```
### Get Order Status
```python
response = client.orderstatus(
order_id="250408001002736",
strategy="MyStrategy"
)
# Returns: order_status, average_price, quantity, timestamp
```
### Get Open Position
```python
response = client.openposition(
strategy="MyStrategy",
symbol="RELIANCE",
exchange="NSE",
product="MIS"
)
# Returns: {'quantity': '10', 'status': 'success'}
```
---
## Symbol Format
OpenAlgo uses standardized symbol formats across all brokers:
### Equity
- `RELIANCE`, `INFY`, `TCS`, `SBIN`
### Futures
- Format: `[SYMBOL][DDMMMYY]FUT`
- Examples: `NIFTY30JAN25FUT`, `BANKNIFTY30JAN25FUT`
### Options
- Format: `[SYMBOL][DDMMMYY][STRIKE][CE/PE]`
- Examples: `NIFTY30JAN2526000CE`, `BANKNIFTY30JAN2555000PE`
---
## Common Patterns
### Intraday Scalping
```python
# Entry
entry = client.placeorder(
strategy="Scalper",
symbol="SBIN",
action="BUY",
exchange="NSE",
price_type="MARKET",
product="MIS",
quantity=100
)
# Exit with profit target (use limit order)
exit_order = client.placeorder(
strategy="Scalper",
symbol="SBIN",
action="SELL",
exchange="NSE",
price_type="LIMIT",
product="MIS",
quantity=100,
price=current_price * 1.005 # 0.5% profit
)
```
### Swing Trading Entry
```python
response = client.placeorder(
strategy="SwingTrader",
symbol="TATASTEEL",
action="BUY",
exchange="NSE",
price_type="LIMIT",
product="CNC", # Delivery
quantity=10,
price=150.00
)
```
### Risk Management - Stop Loss
```python
# Place stop loss immediately after entry
sl_order = client.placeorder(
strategy="Scalper",
symbol="SBIN",
action="SELL",
exchange="NSE",
price_type="SL-M",
product="MIS",
quantity=100,
trigger_price=entry_price * 0.995 # 0.5% stop loss
)
```
---
## Error Handling
```python
response = client.placeorder(...)
if response.get('status') == 'success':
print(f"Order placed: {response['orderid']}")
else:
print(f"Error: {response.get('message', 'Unknown error')}")
```
## Notes
- Always verify `OPENALGO_API_KEY` is set before trading
- Use `MIS` for intraday, `CNC`/`NRML` for positional trades
- Test with small quantities first
- Use Analyzer mode for paper trading: `client.analyzertoggle(mode=True)`