Using python -m bokeh: python -m bokeh serve -show app.py. The following are equivalent: Running the bokeh command line script: bokeh serve -show app.py. Pinch, display_event ( div, attributes = pinch_attributes )) output_file ( "js_events. Bokeh is a newly introduced Python library, like D3.js, which is used for interactive data visualization targeting web browsers. Provide a main function to run bokeh commands. Therefore it is very important to master different python tools and frameworks. P ython is one of the most crucial tools for data scientists, as it provides a wide array of libraries and frameworks that can be used for data analysis, manipulation, modeling, and more. Pan, display_event ( div, attributes = pan_attributes )) p. Master Python for Data Science Through This Roadmap. MouseWheel, display_event ( div, attributes = wheel_attributes )) p. Bokeh works by generating plots in web browsers, combining a high-level Python programming interface that generates javascript (js) code to display HTML. Bokeh’s CustomJS callbacks allow you to define JavaScript-based custom interactivity for various widgets and events in Bokeh documents. Web server gateway interface, sometimes known as WSGI, is a standard for creating web applications in Python. It is built using the Jinja2 template engine and the WSGI tools. js_on_event ( event, display_event ( div, attributes = point_attributes )) p. Bokeh comes with a rich set of widgets that can be used with either client-side JavaScript callbacks, or with real Python code in a Bokeh server application. Flask is a web framework that offers libraries for creating simple web applications in Python. LODEnd, display_event ( div )) # End of LOD display # Events with attributes point_attributes = # Point events wheel_attributes = point_attributes + # Mouse wheel event pan_attributes = point_attributes + # Pan event pinch_attributes = point_attributes + # Pinch event point_events = for event in point_events : p. LODStart, display_event ( div )) # Start of LOD display p. ButtonClick, display_event ( div )) # Button click p. random ( size = 4000 ) * 1.5, fill_color = colors, fill_alpha = 0.6, line_color = None ) div = Div ( width = 1000 ) button = Button ( label = "Button", button_type = "success" ) layout = column ( button, row ( p, div )) # Events with no attributes button. random ( size = 4000 ) * 1.5 colors = p = figure ( tools = "pan,wheel_zoom,zoom_in,zoom_out,reset" ) p. Import numpy as np from bokeh.io import show, output_file from otting import figure from bokeh import events from bokeh.models import CustomJS, Div, Button from bokeh.layouts import column, row def display_event ( div, attributes =, style = 'float:left clear:left font_size=0.5pt' ): "Build a suitable CustomJS to display the current event in the div model." return CustomJS ( args = dict ( div = div ), code = """ var attrs = %s var args = for (var i=0 i" + cb_obj.event_name + "(" + args.join(", ") + ") \\ n" var text = (line) var lines = text.split(" \\ n") if ( lines.length > 35 ) div.text = lines.join(" \\ n") """ % ( attributes, style )) x = np.
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