Setup and Solvers

This page collects the commands and solver notes needed to build the site or run the notebooks.

Colab¶

Use these links to open the published notebooks directly in Google Colab:

• Python Basics

• Pyomo Fundamentals

• Pyomo Nonlinear Problems

• Blocks and Model Transformations

• Dynamic Systems

• Generalized Disjunctive Programming

• Pyomo contrib and Debugging Tools

The nonlinear notebook installs the IDAES extension bundle in Colab when IPOPT is missing. The fundamentals notebook uses GLPK for mixed-integer examples; install GLPK before running those cells in a fresh runtime. The dynamic-system notebook uses IPOPT for discretized optimization examples and SciPy for the simulation exercise; Colab includes SciPy by default.

Local Environment¶

The documentation environment is managed with uv:

uv sync --locked --group docs
uv run --group docs python -m unittest discover -s tests
env BASE_URL=/pyomo-summer-ws uv run --group docs jupyter book build --html --ci
uv run --group docs python tools/write_legacy_redirects.py
uv run --group docs python tools/check_static_site.py
uv run --group docs python -m http.server --directory _build/html 8000

The documentation build renders notebooks without executing them. Running the notebooks locally also requires solver executables on PATH.

Solver Notes¶

Pyomo calls external solvers through SolverFactory. The examples use:

• GLPK through glpsol for linear and mixed-integer examples.

• IPOPT through ipopt for nonlinear examples.

On Ubuntu, GLPK is available from the system package manager:

sudo apt-get install glpk-utils

For local IPOPT or cross-platform GLPK installs, a Conda environment from conda-forge is usually the most direct route:

conda install -c conda-forge glpk ipopt

Confirm solver discovery before running solver-dependent examples:

uv run --group docs python - <<'PY'
import shutil

for solver in ("glpsol", "ipopt"):
    print(f"{solver}: {shutil.which(solver) or 'not found'}")
PY

Solutions Policy¶

The public site is a self-study build. It includes solution cells or solution-file links close to each exercise so learners can check their work. Instructors using these materials for a live workshop can remove the solution cells or distribute only the _incomplete.py exercise files.