oura-analytics

Automate daily health briefings by fetching and normalizing Oura Cloud data across sleep, readiness, activity, and HRV metrics. This process generates hybrid morning briefings that summarize key health drivers for quick decision-making.

Yes, you can generate multi-week trend reports for HRV and sleep efficiency. The analytics workflow aggregates normalized Oura Cloud data to support long-term trend detection and configurable alerts for low readiness or poor sleep.

Yes, you need Python 3 along with the pytz and PyYAML libraries to execute the scripts. These dependencies are required to fetch, normalize, analyze, and report Oura health data from the scripts directory.

Set up automated alerts for low readiness scores by configuring the alerting feature within the reporting scripts. You can optionally enable notifications to Telegram by setting the TELEGRAM_BOT_TOKEN and TELEGRAM_CHAT_ID environment variables.

The best way to consolidate Oura sleep and activity data is using a unified analytics workflow that fetches and normalizes data from Oura Cloud. It automates report generation, aggregating multiple metrics into a single weekly or monthly summary.

The Oura analytics script requires the OURA_API_TOKEN environment variable to authenticate and securely fetch your personal health data from Oura Cloud. Without this token, the scripts cannot access your sleep, readiness, or HRV information.