lightweight-charts-python/docs/source/charts.md

Charts

This page contains a reference to all chart objects that can be used within the library. They all have access to the common methods.

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Chart

width: int | height: int | x: int | y: int | on_top: bool | maximize: bool | debug: bool | toolbox: bool

The main object used for the normal functionality of lightweight-charts-python, built on the pywebview library.

The `Chart` object should be defined within an `if __name__ == '__main__'` block.

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show

block: bool

Shows the chart window, blocking until the chart has loaded. If block is enabled, the method will block code execution until the window is closed.

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hide

Hides the chart window, which can be later shown by calling chart.show().

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exit

Exits and destroys the chart window.

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show_async

block: bool

Show the chart asynchronously.

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screenshot

-> bytes

Takes a screenshot of the chart, and returns a bytes object containing the image. For example:

if __name__ == '__main__':
    chart = Chart()
    df = pd.read_csv('ohlcv.csv')
    chart.set(df)
    chart.show()
    
    img = chart.screenshot()
    with open('screenshot.png', 'wb') as f:
        f.write(img)

This method should be called after the chart window has loaded.

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QtChart

widget: QWidget

The QtChart object allows the use of charts within a QMainWindow object, and has similar functionality to the Chart object for manipulating data, configuring and styling.

Either the PyQt5 or PySide6 libraries will work with this chart.

Callbacks can be received through the Qt event loop.

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get_webview

-> QWebEngineView

Returns the QWebEngineView object.

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Example:

import pandas as pd
from PyQt5.QtWidgets import QApplication, QMainWindow, QVBoxLayout, QWidget

from lightweight_charts.widgets import QtChart

app = QApplication([])
window = QMainWindow()
layout = QVBoxLayout()
widget = QWidget()
widget.setLayout(layout)

window.resize(800, 500)
layout.setContentsMargins(0, 0, 0, 0)

chart = QtChart(widget)

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

layout.addWidget(chart.get_webview())

window.setCentralWidget(widget)
window.show()

app.exec_()

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WxChart

parent: wx.Panel

The WxChart object allows the use of charts within a wx.Frame object, and has similar functionality to the Chart object for manipulating data, configuring and styling.

Callbacks can be received through the Wx event loop.

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get_webview

-> wx.html2.WebView

Returns a wx.html2.WebView object which can be used to for positioning and styling within wxPython.

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Example:

import wx
import pandas as pd

from lightweight_charts.widgets import WxChart


class MyFrame(wx.Frame):
    def __init__(self):
        super().__init__(None)
        self.SetSize(1000, 500)

        panel = wx.Panel(self)
        sizer = wx.BoxSizer(wx.VERTICAL)
        panel.SetSizer(sizer)

        chart = WxChart(panel)

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

        sizer.Add(chart.get_webview(), 1, wx.EXPAND | wx.ALL)
        sizer.Layout()
        self.Show()


if __name__ == '__main__':
    app = wx.App()
    frame = MyFrame()
    app.MainLoop()

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StreamlitChart

The StreamlitChart object allows the use of charts within a Streamlit app, and has similar functionality to the Chart object for manipulating data, configuring and styling.

This object only supports the displaying of static data, and should not be used with the update_from_tick or update methods. Every call to the chart object must occur before calling load.

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load

Loads the chart into the Streamlit app. This should be called after setting, styling, and configuring the chart, as no further calls to the StreamlitChart will be acknowledged.

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Example:

import pandas as pd
from lightweight_charts.widgets import StreamlitChart

chart = StreamlitChart(width=900, height=600)

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

chart.load()

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JupyterChart

The JupyterChart object allows the use of charts within a notebook, and has similar functionality to the Chart object for manipulating data, configuring and styling.

This object only supports the displaying of static data, and should not be used with the update_from_tick or update methods. Every call to the chart object must occur before calling load.

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load

Renders the chart. This should be called after setting, styling, and configuring the chart, as no further calls to the JupyterChart will be acknowledged.

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Example:

import pandas as pd
from lightweight_charts import JupyterChart

chart = JupyterChart()

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

chart.load()