forecose 0.1.0

A time-series forecasting extension for pydexcom using Google's TimesFM

A time-series forecasting extension for pydexcom using Google's TimesFM. Used to predict immediate, short term blood glucose readings.

All modelling and forecasting is performed locally on your device. The only external connections made are with:

• Dexcom Share API: fetching CGM readings following the pydexcom approach.
• HuggingFace: one-time download of the forecasting model weights on the first run.

Quick Start

1. Ensure that you have installed the pydexcom package and enabled the Share service within your Dexcom G7 / G6 / G5 / G4.

pip install pydexcom

2. Initialise pydexcom with your Dexcom credentials (below shows the simplist route, refere to pydexcom for further instruction).

>>> from pydexcom import Dexcom
>>> dexcom = Dexcom(username="username", password="password")

3. Generate a prediction.

>>> from forecose import DexcomForecast
>>> forecaster = DexcomForecast.from_dexcom( 
        dexcom=dexcom,      # pull recent readings from your active 'Dexcom' session
        context_len=288,    # uses prior day's readings as context
        horizon=12          # predicts the next hour
    )
>>> predictions = forecaster.forecast()
>>> print(predictions.head())
                         timestamp  predicted_glucose       q10       q25       q50       q75       q90
0 2026-06-25 11:01:19.199000+01:00           8.243370  8.244899  8.125346  8.214749  8.266071  8.309934
1 2026-06-25 11:06:19.199000+01:00           8.050682  8.073329  7.738788  8.018662  8.208736  8.303193
2 2026-06-25 11:11:19.199000+01:00           7.897943  7.879324  7.332723  7.783697  8.082028  8.256586
3 2026-06-25 11:16:19.199000+01:00           7.767045  7.738261  6.965607  7.621467  8.026337  8.236394
4 2026-06-25 11:21:19.199000+01:00           7.615633  7.667328  6.668064  7.442780  7.972524  8.216294