lightweight-charts-python
Python wrapper that draws TradingView-style charts in a desktop window
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2,123 0 copies · 7 days MITupdated 28 Sep '24
Overview
lightweight-charts-python is a Python wrapper for TradingView's Lightweight Charts, rendering a chart in a webview, Jupyter cell, or PyQt/wx panel from a pandas DataFrame.
- ForPython developers who want a TradingView-style chart without writing JavaScript.
- NeedsPython, and a pandas DataFrame with time/open/high/low/close columns.
- RunsPython bindings (pip install lightweight-charts) around the JS library, supporting Jupyter Notebooks, PyQt6, PyQt5, PySide6, wxPython, Streamlit, and asyncio.
- Limitthe DataFrame's column names matter — time, open, high, low, close — a DatetimeIndex alone is not enough.
Vibe it
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Source: https://github.com/louisnw01/lightweight-charts-python — clone it and read its README and examples before writing anything; its documented setup beats what you remember. Stack: Python bindings around TradingView's Lightweight Charts, rendered in a webview, Jupyter cell, or PyQt/wx panel. Needs: Python, and a pandas DataFrame with time, open, high, low, close (and optionally volume) columns. Start: `pip install lightweight-charts`, then chart.set(df) and chart.show(block=True) on a CSV loaded with pandas before adding markers or a subchart. Limit: the DataFrame's column names matter — time, open, high, low, close — a DatetimeIndex alone is not enough. Done means: you show me my own OHLC data rendered as a chart window, and the script you wrote. Before you start, ask me: which environment I'm running in (plain script, Jupyter, PyQt, Streamlit) and where my OHLCV data comes from.
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