Important Note!

Backtrader_Bokeh has been fully upgraded to Noba which has richer feature, such as ioc container, event system, pipeline system, and a database abstraction layer

Perhaps you should not use this Backtrader_Bokeh again, but if you insist on using it, there is no problem, and we also provide support.

The following is README to the Backtrader_Bokeh.

Regards

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
Support keyboard operation
Interactive backtrader optimization result browser (only supported for single-strategy runs)
Highly configurable
Different skinnable themes
In addition to OHLC, additional datafeed line can be ploted
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/

Contact us

Telegram Channel: Aui_Say Discord Server: Aui and Friends

Installation

pip install backtrader_bokeh

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