openalgo-backtrader 0.1.8

Backtrader integration for OpenAlgo (India) - stores, feeds, and brokers

openalgo-backtrader

Backtrader integration for OpenAlgo (India) - stores, feeds, and brokers.

Installation

uv pip install openalgo-backtrader

Usage

Import the package in your code as follows:

from openalgo_bt.stores.oa import OAStore
from openalgo_bt.feeds.oa import OAData

Project Structure

• openalgo_bt/ - Main package
  • stores/oa.py - OAStore for OpenAlgo API
  • feeds/oa.py - OAData for Backtrader feeds
  • brokers/oabroker.py - OABroker for Backtrader brokers

Sample Store/Broker Creation

Here is how to setup a Store/Broker (example tested with Zerodha backend at OpenAlgo). Both blocks are for "LIVE" setup

from openalgo_bt.stores.oa import OAStore
store = OAStore()
broker = store.getbroker(
    product="MIS", 
    strategy="Live Consistent Trend Bracket", 
    debug=True,
    simulate_fills=False,  # Use real broker for live trading
    use_funds=False        # Use local cash management
)
cerebro.setbroker(broker)

And to setup a Data (or multiple for that matter)

data = OAData(
  symbol=symbol,
  interval="1m",                   # Explicit OpenAlgo interval to bypass timeframe/compression mapping
  compression=1,                   # 1-minute bars
  fromdate=datetime.now() - timedelta(days=1),  # Some historical data for warmup
  live=True,                       # Enable live streaming
  ws_url=ws_url,
  ws_mode=2,                       # Quote mode
)
cerebro.adddata(data, name=symbol)

Using higher compression values (intraday aggregation)

When your backend only provides 1-minute data, OAData can now deliver higher intraday compressions by resampling locally:

• Historical:
  • If you request Minutes/Hours with compression>1 and the OpenAlgo backend does not support that interval, OAData fetches 1m candles and aggregates them into N-minute buckets.
• Live:
  • Websocket ticks are aggregated into the requested bucket size on the fly.

Notes:

• Bucket alignment is done in Asia/Kolkata time by flooring to the nearest multiple of the bucket size.
• Volume comes from per-tick last_quantity when available, or from deltas of cumulative session volume otherwise.
• If OpenAlgo supports the requested interval natively (e.g. 5m), OAData will use it. If not, it will fallback to 1m + local aggregation transparently.

Examples:

# Historical 5-minute bars (local 1m->5m if backend interval unsupported)
import backtrader as bt
from datetime import datetime, timedelta
from openalgo_bt.feeds.oa import OAData

TF_MINUTES = getattr(getattr(bt, "TimeFrame", object), "Minutes", 1)

data = OAData(
    symbol="NSE:RELIANCE",
    timeframe=TF_MINUTES,
    compression=5,
    fromdate=datetime.now() - timedelta(days=5),
    todate=datetime.now(),
)

# Live 15-minute bars (aggregated locally from 1m ticks)
import os
import backtrader as bt
from datetime import datetime
from openalgo_bt.feeds.oa import OAData

TF_MINUTES = getattr(getattr(bt, "TimeFrame", object), "Minutes", 1)

data = OAData(
    symbol="NSE:RELIANCE",
    timeframe=TF_MINUTES,
    compression=15,
    fromdate=datetime(2025, 8, 8),   # optional historical warmup
    live=True,
    ws_url=os.getenv("WEBSOCKET_URL"),
    ws_mode=2,  # Quote mode
)

Tip: Some editors’ type stubs don’t expose bt.TimeFrame.Minutes; use: TF_MINUTES = getattr(getattr(bt, "TimeFrame", object), "Minutes", 1)

Requirements

• Python 3.8+
• python-dotenv
• backtrader (user must install)
• openalgo (user must install)

License

See LICENSE.