Guides¶
Worked approaches to the things developers actually build with SweatStack. Each guide is a complete pattern: starter projects, architecture for harder integrations, and analysis workflows.
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Build a Streamlit app
A Streamlit app that authenticates with SweatStack, lets the user pick an activity, and renders a heart-rate chart. Fastest path to a working integration.
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Build and deploy a FastAPI app
End-to-end: a FastAPI app authenticated against SweatStack, deployed to Fly.io with a public URL.
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Build a native mobile app
Architecture for iOS and Android: PKCE on the device, secure token storage, and webhooks-to-push notifications via a server-side gateway.
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Onboarding and backfill UX
What to render during the first session while a user's history is still being ingested. Opinionated about what works in production.
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Custom calculations on activities
How to add your own derived metrics on top of SweatStack without mirroring activity data into a database. App metadata on the activity replaces the local store for most cases.
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Analyze activity data
A standalone Python script that queries longitudinal data, computes derived metrics, and visualizes them. The pattern for ad-hoc analysis and data work.
If a guide for what you're building doesn't exist yet, the Learn section covers the underlying concepts. For specific endpoints, the API reference has every parameter and response field. To run a request live against your account, use the API playground.