CRN-craft

Reproducible simulation and analysis of well-mixed chemical reaction networks, with a native Rust core. Models, requests and results are versioned JSON documents with strict input checks, explicit budgets and replayable seeds.

pip install crn-craft

Wheels for CPython 3.10 and newer (stable ABI) on Linux x86_64, Windows x64 and macOS (x86_64 and arm64); other platforms build from the source distribution with a Rust toolchain.

Example

Immigration–death (birth rate 4, death rate 0.2, starting from zero) has a Poisson law with mean 20 (1 - exp(-0.2 t)): 12.64 at t = 5 and 17.29 at t = 10.

import crn_craft as crn

model = crn.load_example("immigration-death")
request = crn.ssa_spec(
    model, end=10.0, save_times=[0.0, 5.0, 10.0], replicates=1000, seed=1
)
result = crn.simulate_ssa(model, request)
print(result["sampler"])
print(result["statistics"]["mean"], result["statistics"]["mean_standard_error"])

xoshiro256pp-u53/direct_cr/inverse/fast-1
[[0.0], [12.618], [17.22500000000001]] [[0.0], [0.10959967193421745], [0.13107843665743252]]

Both means lie within one standard error of the exact values. The same seed gives the same result on every run and for every thread count.

What is included

• Exact stochastic simulation: direct, cached_direct, direct_cr, sorting_direct and rssa_cr, with inverse or Ziggurat waiting times. fast (the default) emulates JumpProcesses.jl; fast=False selects the checked policy, which rejects lost increments and channels below the 53-bit selection resolution.
• Prepared simulations and reusable parameter templates for optimization loops (crn.prepare_ssa, crn.prepare_parameters).
• Sparse finite state projection (crn.fsp), explicitly approximate Poisson leaping (crn.tau), network analysis and conservation checks.
• Strict SBML and BioNetGen import subsets (crn-craft-import) and the crn-craft command for archives, verification and export.
• pip install "crn-craft[fit]" adds the pinned SciPy, fcmaes-rust and SQP-craft versions used by the fitting examples.

The rules engine for dynamic, attributed species is in the wheel as crn_craft.rules: prepared parallel ensembles, trackers, event logs and callbacks, and the mtDNA methods; see the mtDNA user manual. Its command-line tools (rules-check, rules) are in the native CLI (cargo install crn-craft-cli --locked, crates crn-craft and crn-craft-rules), which installs a crn-craft command of the same name as the wheel's. The optional diffsol BDF integrator with forward sensitivities and the job worker for optimization-jobs build from the repository and are not part of the wheel.

Documentation

• Repository and README
• Tutorial
• Alternative exact SSA methods and the fast switch
• Optimization tutorials C1–C4
• Agent context
• Changelog

A successful numerical run is not biological validation. MIT licensed; see THIRD_PARTY_NOTICES.md for the Ziggurat tables adapted from Julia.