Contact person: Business Client

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Location: Bengaluru, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I’m building a web-based SaaS that lets school administrators press a single button and receive an optimised class timetable. The front-end is already planned in FlutterFlow and the back-end stack will live on Firebase, with a Python micro-service driving the scheduling logic.

Here’s the workflow I need you to deliver: an administrator logs in, enters or imports teachers, subjects, rooms and time constraints, then triggers “Generate”. Your Python service (FastAPI, Flask or similar) takes those inputs, runs an optimisation routine, pushes the resulting period-by-period schedule back to Firestore and returns status updates to the FlutterFlow UI in real time. The first release focuses purely on Optimized schedule generation, so conflict resolution and predictive analytics can stay out of scope for now.

Core tasks
• Model and secure all data (Firestore, Firebase Auth, rules).
• Build the Python optimisation engine, wrap it with a REST endpoint and deploy it (Cloud Run or your preferred serverless option).
• Connect the endpoint to FlutterFlow using custom actions and handle loading / error states gracefully.
• Create an administrator dashboard in FlutterFlow to manage data and view the generated timetable, with export to PDF or CSV.
• Document setup, environment variables and deployment so I can replicate the stack.

Acceptance criteria
1. For a test dataset of ~30 teachers, 20 classrooms and 40 periods, the engine returns a conflict-free timetable in under 60 seconds.
2. Data remains synced and persists across browser refreshes; unauthenticated users see nothing.
3. All source code and design files are handed over in a clean Git repository with read-me instructions.

If you’ve shipped FlutterFlow + Firebase apps and enjoy crafting optimisation algorithms in Python, I’d love to see your approach and timeframe." (client-provided description)