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Example Gallery

Examples are grouped into two tiers:

  • Essentials: onboarding notebooks/scripts using the recommended path (run, trace, scenario)
  • Advanced: larger workflows and integration templates that still use the same execution patterns, but add scale and system complexity

Essentials

Example Quick Links Key Learning Outcomes
00 Quickstart
A 5-minute introduction to the core API.		 📖 View on GitHub
Open In Colab		 • Create a tracked run
• Observe cache hits on repeated runs
• Query run history
01 Monte Carlo Sweeps
Recommended path scenario + run + trace usage at moderate scale.		 📖 View on GitHub
Open In Colab		 • Parameter sweeps with provenance
• Mixed run and trace step styles
• Hybrid query workflow

Advanced

Example Quick Links Key Learning Outcomes
02 Iterative Workflows
Scenario workflows with feedback loops.		 📖 View on GitHub
Open In Colab		 • Iterative scenario loops
• Cache hydration choices across iterations
• Provenance queries for extension runs
03 Demand Modeling
End-to-end transportation simulation.		 📖 View on GitHub
Open In Colab		 • Multi-step model pipelines
• Scenario comparison and lineage tracing
• Matrix-style downstream analysis

For non-recommended lifecycle/decorator APIs, see Advanced Usage, especially Manual Lifecycle and Decorators.

Installation

pip install consist

If you are running notebooks and need notebook tooling:

pip install "consist[examples]"

For notebook/module layout details, see examples/README.md.