divfusion 0.3.4

Super-simple self-contained interactive HTML-Reports combining elements from various sources. Manages styling and layout via customisable css.

divfusion

divfusion takes multiple HTML elements and generates a stand-alone HTML-Report while managing styling and layout. In practise, these elements ('divs') would originate from other Python modules, especially those that generate plots and provide a html export (e.g. plotly).

If used with plotly, this closes between a single-figure plotly export and a full-fledged plotly-dash server, which needs to be hosted somewhere. Using this Library, all interactivity of plotly is preserved (hovering, zooming, buttons, dropdowns, etc.). In addition to that, you can add html-exports of your pd.DataFrames, images or any other HTML content. divfusion brings all of this together and manges the layout and style of the report for you (bring your own css is possible in a future version).

The resulting html file is completely self-contained and can be opened in any browser on any device.

Installation

You can install divfusion via pip:

pip install divfusion

Usage

To use divfusion.Report, you must first import the class:

from divfusion import Report

Next, create a new instance of Report by passing the following parameters:

• title - The title of the report (string)
• div_like - A list of div_like elements. Can be
  • strings
  • plotly figures
  • pandas dataframes
  • pandas series
  • All nested combinations of the above (first dimension is columns, second dimension is rows)
• css_files (optional) - The CSS files to include (list)
• js_files (optional) - The JS files to include (list)
• js_libs (optional) - A list of JS libraries to include (list)

report = Report(title="My Report",
                div_like=[[px.scatter(x=[1, 2, 3], y=[1, 2, 3]), "<div>some text</div>"],
                          ["<div>Some Info Text</div>", "<div>HTML Table</div>"],
                          [pd.DataFrame([[1, 2, 3], [4, 5, 6]]), pd.Series([1, 2, 3])]
                          ])

The Elements will be placed as the nested list of divs suggests: Columns horizontally, Rows vertically. Optionally you can add custom css files, js files or js script tags.

To generate the HTML report, call the write method and pass the file path where you want to save the report:

report.write("path/to/report.html")

Dependencies

Currently divfusion requires pandas>=1.4.0 and plotly>=5.0.0. Python >= 3.10 is required.

Future Work

• Add support for custom css
• Provide easy-to-use wrapper functions for adding plotly-figures, pandas-dataframes, etc.

Contribution

I welcome any and all contributions, no matter what size. Please feel free to open an issue or pull request against dev.

License

Apache License 2.0