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Common Methods
These methods can be used within the Chart, QtChart, and WxChart objects.
set
data: pd.DataFrame
Sets the initial data for the chart.
The data must be given as a DataFrame, with the columns:
time | open | high | low | close | volume
The time column can also be named date, and the volume column can be omitted if volume is not enabled.
update
series: pd.Series
Updates the chart data from a given bar.
The bar should contain values with labels of the same name as the columns required for using chart.set().
update_from_tick
series: pd.Series
Updates the chart from a tick.
The series should use the labels:
time | price | volume
As before, the time can also be named date, and the volume can be omitted if volume is not enabled.
The provided ticks do not need to be rounded to an interval (1 min, 5 min etc.), as the library handles this automatically.```````
create_line
color: str | width: int
Creates and returns a Line object.
marker
time: datetime | position: 'above'/'below'/'inside' | shape: 'arrow_up'/'arrow_down'/'circle'/'square' | color: str | text: str | -> UUID
Adds a marker to the chart, and returns its UUID.
If the time parameter is not given, the marker will be placed at the latest bar.
remove_marker
m_id: UUID
Removes the marker with the given UUID.
Usage:
marker = chart.marker(text='hello_world')
chart.remove_marker(marker)
horizontal_line
price: float/int | color: str | width: int | style: 'solid'/'dotted'/'dashed'/'large_dashed'/'sparse_dotted' | text: str | axis_label_visible: bool
Places a horizontal line at the given price.
remove_horizontal_line
price: float/int
Removes a horizontal line at the given price.
config
mode: 'normal'/'logarithmic'/'percentage'/'index100' | title: str | right_padding: int
Config options for the chart.
time_scale
time_visible: bool | seconds_visible: bool
Options for the time scale of the chart.
layout
background_color: str | text_color: str | font_size: int | font_family: str
Global layout options for the chart.
candle_style
up_color: str | down_color: str | wick_enabled: bool | border_enabled: bool | border_up_color: str | border_down_color: str | wick_up_color: str | wick_down_color: str
Candle styling for each of the candle's parts (border, wick).
:class: note
Throughout the library, colors should be given as either:
* rgb: `rgb(100, 100, 100)`
* rgba: `rgba(100, 100, 100, 0.7)`
* hex: `#32a852`
volume_config
scale_margin_top: float | scale_margin_bottom: float | up_color: str | down_color: str
Volume config options.
The float values given to scale the margins must be greater than 0 and less than 1.
crosshair
mode | vert_width: int | vert_color: str | vert_style: str | vert_label_background_color: str | horz_width: int | horz_color: str | horz_style: str | horz_label_background_color: str
Crosshair formatting for its vertical and horizontal axes.
vert_style and horz_style should be given as one of: 'solid'/'dotted'/'dashed'/'large_dashed'/'sparse_dotted'
watermark
text: str | font_size: int | color: str
Overlays a watermark on top of the chart.
legend
visible: bool | ohlc: bool | percent: bool | color: str | font_size: int | font_family: str
Configures the legend of the chart.
subscribe_click
function: object
Subscribes the given function to a chart 'click' event.
The event emits a dictionary containing the bar at the time clicked, with the keys:
time | open | high | low | close
Chart
volume_enabled: bool | width: int | height: int | x: int | y: int | on_top: bool | debug: bool
The main object used for the normal functionality of lightweight-charts-python, built on the pywebview library.
show
block: bool
Shows the chart window. If block is enabled, the method will block code execution until the window is closed.
hide
Hides the chart window, and can be later shown by calling chart.show().
exit
Exits and destroys the chart and window.
Line
The Line object represents a LineSeries object in Lightweight Charts and can be used to create indicators.
The `line` object should only be accessed from the [create_line](#create-line) method of `Chart`.
set
data: pd.DataFrame
Sets the data for the line.
This should be given as a DataFrame, with the columns: time | price
update
series: pd.Series
Updates the data for the line.
This should be given as a Series object, with labels akin to the line.set() function.
QtChart
widget: QWidget | volume_enabled: bool
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.
get_webview
-> QWebEngineView
Returns the QWebEngineView object. For 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_()
WxChart
parent: wx.Panel | volume_enabled: bool
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.
get_webview
-> wx.html2.WebView
Returns a wx.html2.WebView object which can be used to for positioning and styling within wxPython. For 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()