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Data

SweatStack stores athletes' training data from wearables, devices, and other apps, and exposes it through a REST API and a Python SDK. Your app can read every activity an athlete has recorded, their dailies, their structured test results, and the metabolic profile derived from all of that.

Start with the Data model for the entities, the terms we use for them, and how they relate. Every other page in this section assumes you've read it.

The pages here cover concepts, common patterns, and curated response examples. For the full request and response schema of every endpoint, see the API reference. To call an endpoint live against your account, use the API playground.

Data types

  • Activities: recorded sessions. Per-activity timeseries (power, heart rate, speed, and the other metrics) and longitudinal queries across a user's full history.
  • Dailies: once-per-day values. Body mass, resting heart rate, HRV, sleep, and a few others.
  • Tests: structured performance evaluations like lactate, VO2max, and FTP tests. Each produces a defined results schema.
  • Metabolic profile: thresholds, training zones, and intensity-duration models, computed from the athlete's activities.