Start with a complete local example that matches your workflow. Every bundled fixture is synthetic. None demonstrates real forecasting accuracy or independently witnessed publication time.
Download the example bundle
comuvia-offline-examples.zip contains the quickstart, three supplied SDK tutorials, their synthetic fixtures, source license and a contents manifest. No package wheels, keys, private store or portfolio data are included.
| Example | What you learn | Expected behavior |
|---|---|---|
Quickstart · example.py |
Record → evaluate → append → reproduce | 5 records; displayed loss 0.09; reproduction match |
A: source evidence · tutorial_a_narrative.py |
Link source, assertion and interpretation | Narrative evidence is preserved without invented probabilities |
B: corrected forecast · tutorial_b_forecast.py |
Keep original and corrected outcomes | Original 0.09 and corrected 0.49 remain reproducible |
C: provider replay · tutorial_c_foreglass.py |
Retain source semantics through normalization | 7 questions, 8 forecasts, 0 eligible in the supplied fixture |
A simulation publishing example
An application can retain model inputs, declared assumptions and result artifacts, then use the SDK to identify the records. A conditional estimate stays a conditional estimate: it is not silently scored as an unconditional real-world forecast.
The downloadable SDK examples above are the portable starting point. They demonstrate evidence handling, not the accuracy of a forecasting model.