esparto 4.0.0.post1

Data driven report builder for the PyData ecosystem.

esparto

Introduction

esparto is a Python library for building data driven reports with content from popular analytics packages. The project takes a straightforward approach to document design; with a focus on usability, portability, and extensiblity.

Creating a report is as simple as instantiating a Page object and 'adding' content in the form of DataFrames, plots, and markdown text. Documents can be built interactively in a notebook environment, and the results shared as a self-contained HTML page or PDF file.

Further customisation of the output is possible by passing a CSS stylesheet, changing the Jinja template, or declaring additional element styles within the code. The responsive Bootstrap grid ensures documents adapt to any viewing device.

Basic Usage

import esparto as es

# Do some analysis
pandas_dataframe = ...
plotly_figure = ...

# Create a Page object
page = es.Page(title="My Report")

# Add content
page["Data Analysis"]["Plot"] = plotly_figure
page["Data Analysis"]["Data"] = pandas_dataframe

# Save to HTML or PDF
page.save_html("my-report.html")
page.save_pdf("my-report.pdf")

Main Features

• Interactive document design with Jupyter Notebooks
• Share as self-contained HTML or PDF
• Customise with CSS and Jinja
• Responsive Bootstrap grid layout
• Content adaptors for:
  • Markdown
  • Pandas DataFrames
  • Matplotlib
  • Bokeh
  • Plotly

Installation

esparto is available from PyPI and Conda:

pip install esparto

conda install esparto -c conda-forge

Dependencies

• python >= 3.6
• jinja2
• markdown
• BeautifulSoup
• PyYAML

Optional

• weasyprint (for PDF output)

License

MIT

Documentation

Documentation and examples are available at domvwt.github.io/esparto/.

Contributions, Issues, and Requests

Feedback and contributions are welcome - please raise an issue or pull request on GitHub.

Examples

Iris Report - Webpage | PDF | Notebook