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raven-python

Reconstruction, Analysis and Visualisation of Metabolic Networks — in Python.

raven-python is the Python counterpart of the RAVEN Toolbox 2 (MATLAB). It builds on cobrapy for everything cobrapy already does well (simulation, standard analyses, SBML I/O, model manipulation) and adds the functionality that is unique to RAVEN:

  • De novo reconstruction from KEGG and protein homology (BLAST / DIAMOND).
  • Context-specific models from omics data via tINIT / ftINIT, with task-aware gap-filling and the linear-merge MILP reduction.
  • Metabolic-task validation (check_tasks, find_task_essential_reactions).
  • Connectivity gap-filling against template models.
  • Omics integration — Human Protein Atlas (proteomics + RNA-seq) ingestion.
  • Sub-cellular localisation prediction by MILP, with partial-update mode and pluggable predictors (WoLF PSORT, DeepLoc, …).
  • N-model comparison; reporter metabolites; FSEOF; flux sampling.
  • YAML I/O following the cobra standard, plus geckopy's ec-* enzyme-constrained fields; SIF export; RAVEN-style Excel export.

:::{admonition} Design principle :class: tip

The canonical in-memory object is always a {class}cobra.Model. There is no parallel RAVEN struct and no ravenCobraWrapper-style adapter — RAVEN-specific fields that cobra doesn't model natively live in cobra's annotation / notes dictionaries. This keeps raven-python interoperable with the wider COBRA ecosystem. :::

Where to start

::::{grid} 1 1 2 2 :gutter: 3

:::{grid-item-card} 🚀 Quickstart :link: guide/quickstart :link-type: doc

Install, load a model, and run your first reconstruction / ftINIT extraction. :::

:::{grid-item-card} 🧭 Coming from MATLAB RAVEN? :link: reference/migration :link-type: doc

The function-by-function map from RAVEN to raven-python (and cobrapy). :::

:::{grid-item-card} 📚 User guide :link: guide/index :link-type: doc

Task-oriented how-tos for each capability — reconstruction, tINIT, tasks, omics, … :::

:::{grid-item-card} 🔍 API reference :link: reference/api/index :link-type: doc

Every public function and class, generated from the docstrings. ::: ::::

Status

raven-python has been validated against MATLAB RAVEN on Human-GEM (5 Hart2015 cell-line models, Jaccard 0.975–0.980 — see the Human-GEM validation study). The functional scope of the original toolbox is covered, with two principled omissions: MetaCyc-based reconstruction (flagged for removal from MATLAB RAVEN too) and dynamic FBA (well covered by other maintained Python packages). What's still open is catalogued in the to-do list.

:hidden:
:caption: Getting started

guide/quickstart
installation

:hidden:
:caption: User guide

guide/index

:hidden:
:caption: Reference

reference/index

:hidden:
:caption: Studies & validation

studies/index

:hidden:
:caption: Maintenance

maintenance/index

:hidden:
:caption: Project

reference/changelog
reference/todo
reference/known_issues

:hidden:
:caption: Design archive

archive/ftinit_review_and_plan
archive/localization_design
archive/plan_get_model_from_homology