GitHub - pflow-xyz/go-pflow: Go library for Petri net modeling, ODE simulation, and code generation

A Go library for Petri net modeling, ODE simulation, process mining, and zero-knowledge proofs.

go-pflow is not an AI/ML library. It implements structural, dynamical computation based on Petri nets and differential equations. See Why Petri Nets? for the motivation.

For comprehensive documentation, see the book.

Installation

go get github.com/pflow-xyz/go-pflow

Quick Start

// Build a Petri net and simulate with ODE solver
net, rates := petri.Build().
    Place("S", 999).Place("I", 1).Place("R", 0).
    Transition("infect").Transition("recover").
    Arc("S", "infect", 1).Arc("I", "infect", 1).Arc("infect", "I", 2).
    Arc("I", "recover", 1).Arc("recover", "R", 1).
    WithCustomRates(map[string]float64{"infect": 0.3, "recover": 0.1})

prob := solver.NewProblem(net, net.SetState(nil), [2]float64{0, 100}, rates)
sol := solver.Solve(prob, solver.Tsit5(), solver.DefaultOptions())
fmt.Println("Final state:", sol.GetFinalState())

See The go-pflow Library for the full API guide.

Packages

Package	Purpose	Book Chapter
`petri`	Core types, fluent Builder API	Ch 1: Why Petri Nets?
`solver`	ODE solvers (Tsit5, RK45, implicit)	Ch 3: Discrete to Continuous
`stateutil`	State map utilities	Ch 18: go-pflow Library
`hypothesis`	Move evaluation for game AI	Ch 6: Game Mechanics
`sensitivity`	Parameter sensitivity analysis	Ch 18: go-pflow Library
`cache`	Simulation memoization	Ch 18: go-pflow Library
`reachability`	Deadlock/liveness analysis	Ch 2: Mathematics of Flow
`workflow`	Task dependencies, SLA tracking	Ch 10: Complex State Machines
`statemachine`	Hierarchical state machines	Ch 18: go-pflow Library
`actor`	Message-passing actor model	Ch 18: go-pflow Library
`eventlog`	Event log parsing	Ch 11: Process Mining
`mining`	Process discovery, rate learning	Ch 11: Process Mining
`monitoring`	Real-time prediction, SLA alerts	Ch 11: Process Mining
`learn`	Neural ODE-ish parameter fitting	Ch 18: go-pflow Library
`tokenmodel`	Token model schemas, DSL	Ch 4: Token Language
`codegen/solidity`	Solidity smart contract generation	Ch 17: Code Generation
`prover`	Groth16 ZK proofs with gnark	Ch 12: Zero-Knowledge Proofs
`visualization`	SVG rendering	Ch 18: go-pflow Library
`plotter`	Time series SVG plots	Ch 18: go-pflow Library

Examples

Each example maps to a book chapter demonstrating the modeling pattern:

Example	Domain	Book Chapter	Run
basic	Token flow fundamentals	Ch 1	`cd examples/basic && go run main.go`
coffeeshop	Resource modeling	Ch 5	`cd examples/coffeeshop/cmd && go run main.go`
tictactoe	Game AI, move evaluation	Ch 6	`cd examples/tictactoe && go run ./cmd`
sudoku	Constraint satisfaction	Ch 7	`cd examples/sudoku/cmd && go run *.go`
knapsack	Combinatorial optimization	Ch 8	`cd examples/knapsack/cmd && go run *.go`
poker	Complex state machines	Ch 10	`cd examples/poker && go run ./cmd`
monitoring_demo	Process mining, SLA prediction	Ch 11	`cd examples/monitoring_demo && go run main.go`
erc	Token standards, Solidity codegen	Ch 4	`go run ./examples/erc`
connect4	Pattern recognition	Ch 6	`cd examples/connect4 && go run ./cmd`
nim	Optimal strategy	Ch 6	`cd examples/nim && go run ./cmd`
chess	N-Queens, Knight's Tour	Ch 7	`cd examples/chess/cmd && go run *.go`
neural	Parameter learning	Ch 3	`cd examples/neural && go run main.go`
visualization_demo	SVG generation	Ch 16	`make run-visualization`