Supported object types and libraries

[jbednar]

Panel is designed to be very inclusive, providing basic support for a large number of different types of viewable objects. In categories ordered by decreasing richness of the representation, the supported types are:

• Interactive plots -- implemented specifically for each library:
  • [x] Bokeh plots
  • [x] Plotly plots
  • [x] Altair or Vega plots
  • [x] VTK plots
  • [x] HoloViews plots
    • [x] hvPlot plots for Pandas, XArray, Dask, Streamz, Intake, and GeoPandas data (via Bokeh+HoloViews)
• Image-based plots -- implemented specifically for each library, but trivial to add more:
  • [x] Matplotlib figures (as PNG)
    • [x] Seaborn plots (generates Matplotlib figures)
    • [x] plotnine plots (generates Matplotlib figures; superseding Python ggpy/ggplot2)
  • [x] R ggplot2 plots (via rpy2, as PNG)
  • [x] yt plots (as Matplotlib PNG)
• Images -- PNG, JPG, SVG, or animated GIF:
  • [x] anything with a _repr_svg_ rich display method
    • [x] Shapely images
    • [x] Dot/Graphviz Graph/DiGraph objects
  • [x] anything with a _repr_png_ rich display method, including:
    • [x] IPython.display.Image
    • [x] PIL/Pillow images
    • [x] Datashader images
    • [x] NetworkX graph, plotted using dot/graphviz using nxpd
  • [x] anything with a _repr_jpg_ rich display method
  • [x] files on the local filesystem ending in .png, .jpg, .svg, or .gif
  • [x] image URLs ending in .png, .jpg, .svg, or .gif.
• HTML -- anything with a _repr_html_ rich display method, including:
  • [x] HTML code as Python strings
  • [x] Pandas dataframes (as a table; requires height specification)
• Markdown -- anything with a _repr_markdown_ rich display method, including:
  • [x] Markdown text as Python strings
• Equations -- via PNGs rendered using matplotlib and Pillow:
  • [x] Anything with a _repr_latex_ rich display method, including IPython.display.Latex objects
  • [x] LaTeX equations as Python strings
  • [x] Sympy Expr objects
• Widgets -- based on Bokeh widgets:
  • [x] Bokeh widgets (wrapped as panel.widgets)
  • [x] Parameterized objects (parameters from Param automatically mapped to panel.widgets)
• Code
  • [x] Editable code, in the ACE editor
• Str -- preformatted text representing anything displayable using Python's str() function:
  • [x] any Python object

The library selects the richest representation available (generally those higher in this list) unless explicitly requested. If you want a rich (non-plaintext) representation for a given object not already supported, you could consider adding one of the various _repr_X_ methods that allow rich display in IPython/Jupyter. That way, the object will have a rich representation in a Jupyter notebook or Jupyter Lab session, as well as being usable in Panel. If you only want Panel support, you could consider adding a suitable Pane class to Panel, accepting an object of that type and returning something displayable in a Panel.

Implementing Pane classes should be straightforward for most object types, with the specific exception that Jupyter-based interactivity provided by ipywidgets is more difficult. We are currently (7/2019) working on ipywidgets integration, and expect that it will be available in late summer 2019, allowing Panel to support the interactive features from:

• [x] bqplot
• [x] ipyvolume
• [x] plotly 3.0-specific features
• [x] streamz objects

[jlstevens]

• [x] You could choose to display any Python object that supports __str__ or __repr__ so that Panel can genuinely display everything (even if the textual representation isn't actually appropriate!).

[jbednar]

All types we listed as hoping to support are now included, so this issue can be closed. Additional types can of course be added as needed over time.

[jbednar]

And, as of Panel 0.10.0, even the ipywidgets-based functionality we hadn't initially expected to be able to support should work now!