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AlgoGTT SDK

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

Provides direct programmatic access to:

  • Broker Connection & Management: Check live connection status, available cash margin, and connect AngelOne (SmartAPI TOTP), Dhan (Personal Access Token), or OpenAlgo bridges headlessly.
  • 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

1. Get Your API Key

  1. Log in to your AlgoGTT account at https://www.algogtt.in.
  2. Go to Profile / Settings (https://www.algogtt.in/profile).
  3. Under AlgoGTT / STS API Key, click Copy (starts with STS_...).

2. Configure CLI (Run Once)

Use the built-in login command to save your credentials persistently:

algogtt login --api-key STS_YOUR_API_KEY_HERE

Stores credentials securely in ~/.algogtt/credentials. Once logged in, you can run any algogtt CLI command directly without typing --api-key.

Alternatively, set an environment variable:

export ALGOGTT_API_KEY="STS_YOUR_API_KEY_HERE"

Don't Know Python? Use Excel or AmiBroker (No Code Required)

If you don't use Python and want to integrate with your existing charting and spreadsheet tools:


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()

# ----------------------------------------------------
# 4. Broker Connection & Management
# ----------------------------------------------------
# Check broker status & cash balance
broker_st = client.broker.status()
print(f"Connected: {broker_st.get('connected')} | Broker: {broker_st.get('broker')} | Funds: ₹{broker_st.get('funds')}")

# Programmatic connect (AngelOne TOTP / Dhan / OpenAlgo)
# client.broker.connect_angelone(api_key="...", client_id="...", password="...", totp_secret="...")
# client.broker.connect_dhan(client_id="...", access_token="...")
# client.broker.connect_openalgo(host="http://127.0.0.1:5000", api_key="...")

Examples & Client Integrations

See the examples/ directory (or run algogtt init to unpack locally):

  • login_and_auth.py: Authentication test, credential verification, and connectivity troubleshooting.
  • broker_connection.py: Check broker status, margin funds, connect AngelOne (TOTP), Dhan (PAT), OpenAlgo, or disconnect sessions.
  • live_engine_control.py: Start, monitor, and stop live engine sessions programmatically.
  • fetch_live_overlays.py: Fetch real-time chart overlays, dynamic SL/TSL, profit targets, 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.
  • algogtt_trades.vba: Microsoft Excel 1-click VBA macro for importing trades and logs.
  • algogtt_signals.afl: AmiBroker AFL formula for chart plotting and automated broker order execution.

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.

Release files for algogtt 1.1.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for algogtt 1.1.3
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Table of built distributions (wheels) for algogtt 1.1.3
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Total release size: 48.3 kB

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