cobrapy

COBRApy - Constraint-Based Reconstruction and Analysis

Overview

COBRApy is a Python library for constraint-based reconstruction and analysis (COBRA) of metabolic models, essential for systems biology research. Work with genome-scale metabolic models, perform computational simulations of cellular metabolism, conduct metabolic engineering analyses, and predict phenotypic behaviors.

Version note: Examples target cobra 0.31.1 on PyPI (import cobra). Docs: cobrapy.readthedocs.io. Repo: opencobra/cobrapy.

When to Use This Skill

Use this skill when:

• Loading, building, or exporting genome-scale metabolic models (SBML, JSON, YAML)
• Running FBA, pFBA, FVA, or flux sampling on COBRA models
• Performing gene or reaction knockout screens and production envelope analysis
• Designing or optimizing growth media and exchange constraints
• Gap-filling infeasible models or validating model consistency

Installation

uv pip install "cobra==0.31.1"

MATLAB model I/O (optional):

uv pip install "cobra[array]==0.31.1"

COBRApy uses optlang for solvers. GLPK installs automatically via swiglpk. For large MILPs/QPs, cobra 0.29+ adds a hybrid solver (HIGHS/OSQP); model.solver = "osqp" now routes through hybrid and may error on plain LPs in a future release—prefer model.solver = "hybrid" when available.

Core Capabilities

COBRApy provides comprehensive tools organized into several key areas:

1. Model Management

Load existing models from repositories or files:

from cobra.io import load_model

# Bundled locally (no network): textbook, iJO1366, salmonella
model = load_model("textbook")      # alias for e_coli_core (95 reactions)
model = load_model("e_coli_core")   # same core E. coli model
model = load_model("iJO1366")       # genome-scale E. coli (bundled)
model = load_model("salmonella")    # Salmonella iYS1720 (bundled)

# Remote (BiGG / BioModels; requires network, cached after first fetch)
model = load_model("iML1515")       # E. coli genome-scale on BiGG

# Load from files
from cobra.io import read_sbml_model, load_json_model, load_yaml_model
model = read_sbml_model("path/to/model.xml")
model = load_json_model("path/to/model.json")
model = load_yaml_model("path/to/model.yml")