StreamChart Tutorial

StreamChart is a drop-in replacement for Chart that serves the chart over HTTP/WebSocket instead of opening a desktop window. Any browser can connect — ideal for headless servers, WSL, SSH sessions, or remote development.

Installation

StreamChart is included with the base package. FastAPI and Uvicorn are hard dependencies and are installed automatically:

pip install python-lightweight-charts

Minimal Example

import pandas as pd
from lightweight_charts import StreamChart

if __name__ == '__main__':
    chart = StreamChart()

    df = pd.read_csv('ohlcv.csv')   # time | open | high | low | close | volume
    chart.set(df)

    chart.show(port=8080, block=True)

When you run this, the console prints:

Chart server running at http://127.0.0.1:8080/?token=<64-hex-chars>

Open the URL in a browser to view the chart. The token is a 64-character hex secret that prevents unauthorised access — keep it private.

Auto-opening the browser

Pass open_browser=True to show() to launch the system default browser automatically:

chart.show(port=8080, open_browser=True, block=True)

LAN access

To expose the chart on your local network, bind to all interfaces:

chart.show(host='0.0.0.0', port=8080, block=True)

A security reminder will be printed. Share only the printed URL (with its token) with trusted viewers.

Live data streaming

StreamChart supports the same update() / update_from_tick() API as Chart:

import time
import pandas as pd
from lightweight_charts import StreamChart

if __name__ == '__main__':
    chart = StreamChart()

    df = pd.read_csv('ohlcv.csv')
    chart.set(df)

    chart.show(open_browser=True)   # non-blocking

    next_df = pd.read_csv('next_ohlcv.csv')
    for _, row in next_df.iterrows():
        chart.update(row)
        time.sleep(0.1)

Using plugins with StreamChart

All plugins work identically with StreamChart:

from lightweight_charts import StreamChart
from lightweight_charts.plugins import Tooltip

chart = StreamChart()
chart.set(df)

tooltip = Tooltip(chart.candle_series)

chart.show(block=True)

Key differences from Chart

Feature	Chart	StreamChart
Window	pywebview desktop window	Any browser via HTTP
Display	Requires display server	Headless compatible
Access URL	n/a	Printed one-time token URL
show() signature	show(block)	show(port, host, open_browser, block)
Screenshot	chart.screenshot()	Not supported
JupyterChart	Yes	No