Next Steps¶
Installed and verified? Here is a curated route through MineProductivity for a first-time user.
Recommended: start with the Learning Suite¶
The guided path
Fundamentals is the recommended starting point for everyone — mining engineers, data scientists, software engineers, and researchers alike.
Ten lessons, in the order the architecture is layered, each a runnable script plus a full tutorial. Start at Lesson 01 — Hello, MineProductivity and work forward; by Lesson 10 you can model a mine, measure it, characterise it, decide on it, and present it.
Prefer to dive at a specific topic? The table below is the à-la-carte route.
Or jump straight to a topic¶
| I want to… | Start here |
|---|---|
| Learn the framework properly, from first principles | Learning Suite — Fundamentals - ten lessons, start to finish. |
| See the whole platform in one script | examples/quickstart/01_five_minute_tour.py - one truck, one shift, one KPI, ~50 lines. |
| Follow a guided, cell-by-cell walkthrough | notebooks/beginner/01_first_kpi_lookup.ipynb. |
| Compute my first KPI | KPIs tutorial. |
| Model equipment, fleets, and shifts | Ontology tutorial. |
| Ingest data from a real source | Connectors tutorial. |
| Record my first event | Events tutorial. |
| Understand plugin discovery | Registry tutorial. |
| Turn analytics into decisions | Decision tutorial. |
| Search for the best plan | Optimization tutorial. |
| Orchestrate autonomous work | AI Agents tutorial. |
| Present it to a human | Visualization tutorial. |
| Read the full API of a package | Packages or the API Reference. |
| Understand the system's shape | Architecture Handbook. |
Every example is a plain, runnable .py file - no test framework involved. The Tutorials section indexes them all.