Equalify UIC PDF Analysis

This project includes two key tools for analyzing PDF accessibility linked in a CSV input file:

Components

1. Equalify UIC PDF Analysis

This script (equalify-uic-pdf-analysis.py) performs automated checks on PDF files. It:

• Analyzes each PDF's size, page count, text content, and tag structure.
• Supports PDFs hosted on direct links or Box.com.
• Submits eligible PDFs for advanced accessibility analysis via Equalify’s scan service.
• Outputs results to output.csv.

2. Equalify UIC PDF Dashboard

This Streamlit dashboard (equalify-uic-pdf-dashboard.py) provides a visual summary of the analysis results. It:

• Displays key metrics like total checks passed/failed and number of files.
• Includes a pie chart and table of failure reasons by description.
• Reads Equalify result JSONs from the results/ folder.

Getting Started

• Place your input data in a file called input.csv in the root directory. The file should include a column named Link with PDF or Box file URLs.
• Run the analysis script:

python equalify-uic-pdf-analysis.py

• After the analysis completes, start the dashboard:

streamlit run equalify-uic-pdf-dashboard.py

Make sure to install required dependencies (see requirements.txt) and set your Box API credentials in a .env file.

Maintainers

This project is maintained by the Accessibility Engineering team at University of Illinois Chicago (UIC) Technology Solutions.