Overview

What FitTrack is

FitTrack is a workout tracker. A user signs in, logs a workout as a series of sets — each set is an exercise plus reps and weight — and watches their progress build up over time: personal records, total volume per week, and how each exercise trends. It’s deliberately focused: an exercise catalog, workout logging, and progress. No social feed, no training programs, no nutrition — those live in where to go next.

The point of the project isn’t the fitness domain — it’s building one product for two clients on one shared backend. You write a single FastAPI service, back it with Supabase (managed Postgres and Auth), and consume it from both a Flutter mobile app (the primary, mobile-first experience) and a Svelte web companion (a lighter dashboard). The same API, two very different front ends.

The feature set

• Auth — sign up and sign in via Supabase Auth; every API call is authenticated with the Supabase-issued JWT.
• Exercise catalog — a shared library of exercises, plus user-created ones.
• Workout logging — start a session, add sets (exercise, reps, weight), finish it.
• History — browse past workouts.
• Progress & stats — personal records, weekly volume, per-exercise trends, computed server-side.
• Two clients — a Flutter mobile app and a Svelte web companion, both on the same FastAPI backend.

The course map

Each build module adapts a Learn Hub course to one slice of FitTrack.

Module	What you build	Learn Hub course it adapts
1 · Setup & Tooling	The Python toolchain (uv), the FastAPI project, and a Supabase project	Python
2 · Supabase Foundation	The Postgres schema, migrations, and Auth, on managed Supabase	Supabase
3 · FastAPI Foundation	The async FastAPI app, config, structure, and DB access	Python / Python for TS Devs
4 · Auth (Supabase JWT)	Verifying the Supabase JWT and a get_current_user dependency	Supabase / Python
5 · Domain Model	Exercises, workouts, and sets as Pydantic + SQLAlchemy + repositories	Python
6 · Exercises API	The exercise-catalog CRUD, shared and user-created	Python / REST
7 · Workouts API	Logging workout sessions and their sets, and reading history	Python
8 · Progress & Stats	Personal records, volume, and per-exercise aggregations	Python / SQL
9 · Flutter — Foundation	The Flutter app: Riverpod, Supabase auth, an API client	Flutter
10 · Flutter — Tracking	The mobile tracking UI: log sets, view history	Flutter
11 · Svelte Web Companion	A SvelteKit dashboard reading the same API	Svelte
12 · Testing	pytest for the backend, widget tests for Flutter	Python
13 · Deployment	Containerize the API, hosted Supabase, ship both clients	Docker

Verify

You’re ready to move on when you can answer these in your own words:

• Why does FitTrack put a FastAPI backend in front of Supabase instead of having the clients talk to Supabase directly?
• What does each of the two clients — Flutter and Svelte — do, and what do they share?
• Which three features make up FitTrack’s core, and which ideas were deliberately left out?

Next, the architecture shows how the pieces fit together.