Introduce

Why is Backtrader_Bokeh

Backtrader_Bokeh

You can visit our wiki homepage for more information: EN | 中文

Backtrader_Bokeh to add extended plotting capabilities to Backtrader using Bokeh based on the awesome backtrader_plotting and btplotting. Besides this, a lot of issues are fixed and new functionality is added. See the list below for differences.

What is different:

Basic:

  • No need for custom backtrader
  • Different naming / structure
  • Different data generation which allows to generate data for different data sources. This is useful when replaying or resampling data, for example to remove gaps.
  • Different filtering of plot objects
  • Support for replay data
  • Every figure has its own ColumnDataSource, so the live client can patch without having issues with nan values, every figure is updated individually
  • Display of plots looks more like backtrader plotting (order, heights, etc.)
  • Allows to generate custom columns, which don't have to be hardcoded. This is being used to generate color for candles, varea values, etc.
  • Possibility to fill gaps of higher timeframes with data

Plotting:

  • Datas, Indicators, Observer and Volume have own aspect ratios, which can be configured in live client or scheme
  • Different datafeed's plot sytle can be customize separately
  • Only one axis for volume will be added when using multiple data sources on one figure
  • Volume axis position is configureable in scheme, by default it is being plotted on the right side
  • Linked Crosshair across all figures
  • fill_gt, fill_lt, fill support
  • Plot objects can be filtered by one or more datanames or by plot group
  • Custom plot group, which can be configured in app or in live client by providing all plotids in a comma-seperated list or by selecting the parts of the plot to display

Tabs:

  • Default tabs can be completely removed
  • New log panel to also include logging information
  • Can be extended with custom tabs (for example order execution with live client, custom analysis, etc.)

Live plotting:

  • Navigation in live client (Pause, Backward, Forward)
  • Live plotting is done using an analyzer, so there is no need to use custom backtrader
  • Live plotting data update works in a single thread and is done by a DataHandler
  • Data update is being done every n seconds, which is configureable

Features

  • Interactive plots
  • Interactive backtrader optimization result browser (only supported for single-strategy runs)
  • Highly configurable
  • Different skinnable themes
  • Easy to use

Bug fixed

Some examples, more detail in CHANGELOG.md

  • Many bugs in Backtrader that have not been still fixed, Backtrader_Bokeh fixed those through Monkey Patch
  • Because of optbrowser address and port assignment problem, if port 80 is occupied, the web page will not be opened in the optimization mode. * live mode is the same way
  • Very imortant, fixed the legend can't be displayed in the observer or indicators's figuer
  • And more...

Python >= 3.6 is required.

How to use

Just give Live Mode example, about Normal Mode and Optstrategy Mode pls refer to wiki-en | wiki-中文 * Add to cerebro as an analyzer (Live Mode):

from backtrader_bokeh import bt
  ...
  ...

cerebro = bt.Cerebro()
cerebro.addstrategy(MyStrategy)
cerebro.adddata(LiveDataStream()) # Note! Data is must Live Data
cerebro.addanalyzer(bt.analyzers.Live, force_plot_legend=True, autostart=True)
cerebro.run()
# cerebro.plot() # do not run this line unless your data is not real-time
  • If you need to change the default port or share the plotting to public:
cerebro.addanalyzer(bt.analyzers.Live, address="localhost", port=8889)

Jupyter

In Jupyter you can plut to a single browser tab with iplot=False:

from backtrader_bokeh import bt
plot = bt.Bokeh()
cerebro.plot(plot, iplot=False)

You may encounters TypeError: <class '__main__.YourStrategyClass'> is a built-in class error.

To remove the source code tab use:

from backtrader_bokeh import bt
plot = bt.Bokeh()
plot.tabs.remove(bt.tabs.SourceTab)
cerebro.plot(plot, iplot=False)

Demos

https://iniself.github.io/backtrader_bokeh

Installation

pip install backtrader_bokeh

or

pip install git+https://github.com/iniself/backtrader_bokeh

Sponsoring

If you want to support the development of backtrader_bokeh, consider to support this project.

  • ETH: 0x0275779f70179748C6fCe1Fe5D7638DfA7e3F986