# Pyomo/pyomo

An object-oriented algebraic modeling language in Python for structured optimization problems.

Repository: https://github.com/Pyomo/pyomo
Canonical: https://ross.abutalabs.com/products/pyomo
Homepage: https://www.pyomo.org
Language: Python
License: NOASSERTION
License Family: other
Topics: python, optimization, linear-programming, mathematical-programming, modeling-language, nonlinear-programming
Last push: 2026-08-26T17:22:22+00:00

## Health v2 (maintenance only)
Score: 91/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 75, longevity 100
- inputs: {"age_days": 3750, "days_push": 7, "days_rel": 90, "gap_med": 50, "n_releases_24m": 10}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2511, forks 590 (observed 2026-08-28T04:06:57.424198+00:00)

## What it is
Pyomo is a Python-based open-source algebraic modeling language for formulating, solving, and analyzing structured optimization problems. It supports a wide range of problem types (LP, MILP, NLP, stochastic, disjunctive, DAE) and interfaces with external commercial and open-source solvers.

## Use cases
- formulate and solve linear programming models in Python
- build mixed-integer optimization models
- model nonlinear optimization problems symbolically
- solve stochastic optimization problems with parallel subproblems
- model differential algebraic equations for optimization
- interface Python models with solvers like Gurobi, CPLEX, or CBC
- develop high-level optimization and analysis tools

## When to choose
- you need to express optimization models in a full-featured programming language rather than a DSL like AMPL or GAMS
- you want solver-agnostic modeling that works with many commercial and open-source solvers
- you need advanced problem types such as stochastic programming, generalized disjunctive programming, or equilibrium constraints
- you are building research or production optimization applications in Python

## When to avoid
- you need a built-in solver - Pyomo requires installing third-party solvers separately
- you only need simple curve fitting or least-squares, where SciPy is lighter weight
- you need a graphical modeling environment like AIMMS
- your use case is machine learning model training rather than mathematical optimization

## Facets
- artifact type: library
- maturity: stable
- function: math, sdk, developer-tools
- domain: mathematics, data-science, performance
- platform: python, cross-platform
- tags: optimization, algebraic-modeling-language, linear-programming, mixed-integer-programming, operations-research, solver-interface, nonlinear-programming, algorithms

## Member repositories
- Pyomo/pyomo (main) score 91

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:57.424198+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:26:21.460360+00:00, confidence not recorded.
  - readme: https://github.com/Pyomo/pyomo (fetched 2026-08-28T04:06:57.424198+00:00, sha e50e1a25d719)
  - homepage: https://www.pyomo.org (fetched 2026-08-29T10:08:52.124386+00:00, sha 4f645a0d9a58)
  - site_page: https://www.pyomo.org/about (fetched 2026-08-29T10:08:52.126899+00:00, sha d18554ffb4e7)
  - site_page: https://www.pyomo.org/installation (fetched 2026-08-29T10:08:52.128862+00:00, sha f135f932cf28)
  - site_page: https://www.pyomo.org/documentation (fetched 2026-08-29T10:08:52.130615+00:00, sha 637a93676a47)
- Data as of 2026-08-30T08:39:29.467469+00:00.