The Owlet app does not allow for data exporting and has useful, but limited statistical data summaries. The two scripts described below together create a service that stores owlet data locally in csv and displays the data and enhanced statistical summaries in a constantly refreshing dashboard.
owlet_api/owlet_stream.py can be used to constantly query Owlet's database and store the data in a csv.
To start streaming, run:
python3 owlet_api/owletstream.py
--email <USER_EMAIL>
--password <USER-PASSWORD>
The csv is named using the convention pulseox_{DATE}.csv. The csv generated will take the form:
pulseox_2026118.csv
timestamp_ox_obs,ox_lvl,heart_rate
2026-01-18 03:46:20+00:00,99,147
2026-01-18 03:46:23+00:00,99,146
2026-01-18 03:46:28+00:00,98,149
2026-01-18 03:46:33+00:00,98,152
2026-01-18 03:46:38+00:00,99,146
owlet/app.py can be used to create a Streamlit dashboard that visualizes the time series data.
To start the app, run:
streamlit run owlet/app.py
--
--data_file pulseox_2026118.csv
--oxygen_threshold 90
--refresh_sec 10
The oxygen_threshold is used to detect desaturation events in the data, and refresh_sec sets how often the app refreshes.