AlgoGTT SDK (v1.1.0)

Official Python SDK and CLI for the AlgoGTT Algorithmic Trading Platform.

Provides direct programmatic access to:

• Trading Engine Lifecycle: Start / stop live or paper trading sessions, configure session duration (market_close, 1_hour, 1_trade), and stream live engine logs.
• Real-Time Chart Overlays: Access the exact same live signals, markers, SL/TSL, targets, and Smart Money Concept (SMC) Fair Value Gaps displayed on the web terminal.
• Position & Order Management: Query open broker positions, live orders, dynamic order shifting, and emergency square-offs.
• Option Strips & Greeks: Retrieve option chains, PCR, and implied volatilities.
• Daily EOD Reports: Generate and export end-of-day trading summaries in JSON or HTML.

Installation

pip install --upgrade algogtt

Authentication

Set your API Key from the AlgoGTT Profile page as an environment variable:

export ALGOGTT_API_KEY="your_api_key_here"

CLI Usage

The algogtt command-line utility provides instant control over the engine directly from your terminal:

# Unpack complete example scripts into an ./algogtt-examples/ folder:
algogtt init

# 1. Start an automated trading session
algogtt session start --symbol CRUDEOIL --strategy swing_breakout --scope market_close
# Add --live to route real orders to your connected broker:
algogtt session start --symbol CRUDEOIL --strategy swing_breakout --live

# 2. Check engine status & running PID
algogtt session status

# 3. Stream real-time execution logs
algogtt session logs

# 4. Stop the active session
algogtt session stop

# 5. Fetch real-time chart overlays & trade markers
algogtt overlays --symbol CRUDEOIL --strategy swing_breakout --timeframe 1m

# 6. List active broker positions & P&L
algogtt positions

# 7. List live orders
algogtt orders

# 8. Fetch daily EOD summary
algogtt eod --date 2026-09-11

Python SDK Reference

from algogtt import AlgoGTTClient

# Automatically reads ALGOGTT_API_KEY from environment, or pass api_key="..."
client = AlgoGTTClient()

# ----------------------------------------------------
# 1. Trading Engine Lifecycle
# ----------------------------------------------------
# Start session (Paper Mode)
client.engine.start(
    symbol="CRUDEOIL",
    strategy="swing_breakout",
    session_duration="market_close",  # 'market_close' | '1_hour' | '1_trade'
    dry_run=True,                     # Set False for real live broker orders
)

# Inspect status & PID
status = client.engine.status(symbol="CRUDEOIL")
print("Engine Status:", status.get("is_running"), "PID:", status.get("pid"))

# Stream latest logs
for line in client.engine.logs():
    print(line)

# Stop session
client.engine.stop()

# ----------------------------------------------------
# 2. Real-Time Chart Overlays & SMC Signals
# ----------------------------------------------------
overlays = client.live.get_overlays(
    symbol="CRUDEOIL",
    strategy="swing_breakout",
    timeframe="1m"
)
print("Total Net P&L:", overlays.get("total_pnl"))

# Parsed trades
trades = client.live.get_trades(symbol="CRUDEOIL")
for t in trades:
    print(t["option_symbol"], "Entry:", t.get("entry_price"), "SL:", t.get("current_sl"))

# ----------------------------------------------------
# 3. Positions & Orders
# ----------------------------------------------------
positions = client.trading.get_positions()
orders = client.trading.get_orders()

# Dynamic Trailing Stop Loss / Order Shift
# client.trading.shift_order(order_id="12345", symbol="CRUDEOIL", stop_loss=315.0)

# Square Off
# client.trading.square_off()

Examples & Client Integrations

See the examples/ directory for sample scripts:

• live_engine_control.py: Start, monitor, and stop live engine sessions programmatically.
• fetch_live_overlays.py: Fetch real-time chart overlays, risk levels, and audit logs.
• parse_signals.py: Load candlestick data with strategy indicators into Pandas DataFrames.
• parse_trades.js: Native Node.js & React Native / Mobile fetch integration.
• Excel & Google Sheets: Pull live JSON directly using Power Query.

Mobile & Multi-Platform Support

AlgoGTT uses an API-First Architecture. The Web Terminal (/terminal), Android App, iOS React Native App, CLI, and external bots all consume the same authenticated REST & SSE endpoints. Any backend enhancements immediately reflect across all interfaces.