PaulMest / reporting

A simple python library for generating interactive reports and visualizations from common data-sources in a variety of formats

PyReporting

This is a Python reporting library

Getting Started

Prerequisites

Environment

1. Python 3.6+ -- This project uses type hints
2. Node.js version 8+ -- Needed to build the JS used for some of the interactive UI controls

Clone repo

$ git clone <repo URI>

Libraries

# Install all Python dependencies
$ pip install -r requirements.txt

$ cd pyreportingJs

# Install and build JS packages (option 1)    
$ yarn install
$ yarn build

# If you don't have yarn, use npm (option 2)
$ npm install
$ npm run build

Running the samples

Before running samples for the first time, you should download bokeh's sample dataset.

$ python
>>> import bokeh
>>> bokeh.sampledata.download()

Run sample_report.py

sample_report.py contains one example of every type of report component.

# NOTE: Make sure you're in the root of the pyreporting project (where requirements.txt lives) 

# Launch with module command
$ python -m examples.sample_report

# Launch with file path command
$ PYTHONPATH=. python ./examples/sample_report.py

After running this command, a directory should be created in ./examples/report/Sample Report/[timestamp] and a browser should open with your report.