Why is 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:
- 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
- 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
- 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.)
- 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
- Interactive plots
backtraderoptimization result browser (only supported for single-strategy runs)
- Highly configurable
- Different skinnable themes
- Easy to use
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)
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)
pip install backtrader_bokeh
pip install git+https://github.com/iniself/backtrader_bokeh
If you want to support the development of backtrader_bokeh, consider to support this project.
- ETH: 0x0275779f70179748C6fCe1Fe5D7638DfA7e3F986