Python Data Scraping Webapp

I need a solid Python build that blends a clean, browser-based interface with powerful data-scraping logic. The goal is a self-contained web application that can pull information from three distinct sources—websites, APIs, and internal databases—then present or export that data on demand.

Here’s how I picture the flow: from the front end I choose the target (URL list, API endpoint, or DB table), set any parameters or credentials, and kick off the scrape. Behind the scenes your Python scripts handle the session management, parsing, rate-limiting, pagination, and error recovery. Results land in a single unified store—SQLite or Postgres is fine—and the UI lets me filter, download CSV/JSON, or trigger another run.

Deliverables
• Responsive web UI (Django, Flask, or FastAPI—your call)
• Modular scraping modules for Websites, APIs, and Databases
• Central data store with simple schema and migration script
• Setup guide plus brief code comments so I can extend the project

Acceptance criteria
• All three source types successfully scraped in a demo session
• No hard-coded secrets; config via env variables or .env file
• Clear logging for each scrape with timestamp and status
• Application launches locally with a single command (Docker or manage.py runserver is fine)

If you’ve built similar tools or have favorite libraries like BeautifulSoup, Requests, Scrapy, SQLAlchemy, or Celery for task scheduling, let me know in your message along with an estimated turnaround.