Automated Departmental Report Generator
A Flask app that scrapes external data sources and composes structured reports with AI-assisted insight generation.
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Automated Departmental Report Generator
A Python Flask application that automates the tedious process of pulling together departmental reports from multiple data sources.
Problem
Report compilation was manual: someone would spend hours pulling data from various web dashboards, copy-pasting into a template, then writing a summary. This project cuts that to minutes.
How It Works
- Scraping — BeautifulSoup spiders pull structured data from internal and external web sources
- Assembly — Collected data is normalised and inserted into a report template
- AI insights — The AI API analyses the data and suggests key takeaways for the reader
- Output — A structured PDF or HTML report is generated and available for download
Tech Stack
- Python + Flask for the web app
- BeautifulSoup for scraping
- Jinja2 for report templating
- AI API (GPT family) for insight generation
- WeasyPrint for PDF export
Edge Cases That Bit Me
Web scraping breaks whenever the source site updates its layout. I ended up building a monitoring system that alerts when a scraper returns an unexpected result count, which catches layout changes before they silently corrupt reports.
Source: GitHub