Fitbit Fetch Script and InfluxDB Grafana Integration

A Python-based data collection service that retrieves personal health and activity metrics from the Fitbit Web API, writes them into a local InfluxDB time-series database, and visualizes the results in Grafana. It is designed for ongoing automatic syncing as well as historical backfilling to build long-term health trends.

Key Features

• Automatic data collection from the Fitbit API with OAuth 2.0 token refresh
• Stores metrics in InfluxDB for time-series analysis (best supported on InfluxDB 1.11)
• Grafana dashboard support, including heatmaps and long-term trend panels
• Collects a broad set of metrics such as heart rate (including intraday), steps, sleep, SpO2, HRV, breathing rate, activity minutes, and device battery
• Historical backfilling mode designed to respect Fitbit rate limits and handle 429 responses
• Docker Compose stack for running the fetcher, InfluxDB, and Grafana together

Use Cases

• Personal health and fitness dashboard with long-term trends and daily summaries
• Homelab time-series tracking of wearable metrics in InfluxDB with Grafana
• Historical analysis by backfilling months/years of Fitbit data for reporting

Limitations and Considerations

• Requires creating a Fitbit developer application and configuring OAuth tokens
• InfluxDB 2.x support is described as limited and may produce a less detailed dashboard; InfluxDB 1.11 is strongly recommended
• InfluxDB 3 OSS has query-time limitations that can make long-term visualization harder

It works well for users who want ownership of their Fitbit-derived metrics in their own database and prefer Grafana for visualization. The included schema and dashboards make it practical to deploy as a repeatable, automated pipeline.