Metadata-Version: 2.1
Name: backtrader-plotting
Version: 1.1.0
Summary: Plotting package for Backtrader (Bokeh)
Home-page: https://github.com/verybadsoldier/backtrader_plotting
Author: verybadsolider
Author-email: vbs@springrts.de
License: GPLv3+
Project-URL: Bug Tracker, https://github.com/verybadsoldier/backtrader_plotting/issues
Project-URL: Documentation, https://github.com/verybadsoldier/backtrader_plotting/wiki
Project-URL: Source Code, https://github.com/verybadsoldier/backtrader_plotting
Project-URL: Demos, https://github.com/verybadsoldier/backtrader_plotting/tree/gh-pages
Description: # backtrader_plotting
        Library to add extended plotting capabilities to `backtrader` (https://www.backtrader.com/). Currently the only available backend is `Bokeh` (https://bokeh.org/).
        
        ## Features
        * Interactive plots
        * Interactive `backtrader` optimization result browser (only supported for single-strategy runs)
        * Highly configurable 
        * Different skinnable themes
        * Easy to use
        
        Feel free to test it and play with it. I am happy about feedback, critics and ideas on backtrader forum (and also in GitHub issues):
        https://community.backtrader.com/topic/813/bokeh-integration-interactive-webbrowser-plotting
        
        Needs Python >= 3.6.
        ## Demos
        https://verybadsoldier.github.io/backtrader_plotting/
        
        ## Installation
        `pip install backtrader_plotting`
        
        ## Quickstart
        
        ```python
        from backtrader_plotting import Bokeh
        from backtrader_plotting.schemes import Tradimo
        
        <your backtrader code>
        
        b = Bokeh(style='bar', plot_mode='single', scheme=Tradimo())
        cerebro.plot(b)
        ```
        
        ## Minimal Example
        ```python
        import datetime
        
        import backtrader as bt
        
        from backtrader_plotting import Bokeh
        
        
        class TestStrategy(bt.Strategy):
            params = (
                ('buydate', 21),
                ('holdtime', 6),
            )
        
            def next(self):
                if len(self.data) == self.p.buydate:
                    self.buy(self.datas[0], size=None)
        
                if len(self.data) == self.p.buydate + self.p.holdtime:
                    self.sell(self.datas[0], size=None)
        
        
        if __name__ == '__main__':
            cerebro = bt.Cerebro()
        
            cerebro.addstrategy(TestStrategy, buydate=3)
        
            data = bt.feeds.YahooFinanceCSVData(
                dataname="datas/orcl-1995-2014.txt",
                # Do not pass values before this date
                fromdate=datetime.datetime(2000, 1, 1),
                # Do not pass values after this date
                todate=datetime.datetime(2001, 2, 28),
                reverse=False,
                )
            cerebro.adddata(data)
        
            cerebro.run()
        
            b = Bokeh(style='bar', plot_mode='single')
            cerebro.plot(b)
        ```
        
        ## Plotting Optimization Results
        Another way to use this package is to use the `OptBrowser` to browse a `backtrader` optimization result:
        
        ```python
        ...
        cerebro.optstrategy(TestStrategy, buydate=range(1, 10, 1))
        cerebro.addanalyzer(bt.analyzers.SharpeRatio)
        ...
        res = cerebro.run()
        bo = Bokeh()
        browser = OptBrowser(bo, result)
        browser.start()
        ```
        
        This will start a Bokeh application (standalone webserver) displaying all optimization results. Different results can be selected and viewed.
        
        It is possible possible to add further user-provided columns.
        When dealing with huge amounts of optimization results the number of results can be limited and the remaining results can be sorted by a user-provided function to allow for simple selection of the best results.
        
        ## Documentation
        Please refert to the Wiki for further documentation: https://github.com/verybadsoldier/backtrader_plotting/wiki
        
Keywords: trading,development,plotting,backtrader
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
