Dataflow and Reactive Programming Systems
A Practical Handbook on Developing Dataflow Programming Systems
Dataflow concepts are the heart of Reactive Programming, Flow-Based Programming (e.g. NoFlo), Unix pipes, Actors and message passing in general.

Dataflow-based systems are easy to design once you understand the large number of implementation details that could drastically change how the system operates. Understanding these vectors of change is important so you don’t waste your time developing the wrong system.

By the end of the book you will understand…

  • All possible design choices with dataflow-like systems
  • How their effects interplay
  • How to develop your own dataflow system

NoFlo - An implementer's guide to dataflow and reactive programming systems, a Kickstarter worth our support!

NoFlo is a Flow-Based Programming environment for JavaScript

Jonas Boner, CTO of Typesafe - Dataflow and Reactive Programming Systems - upcoming book

Jonas Boner, CTO of Typesafe

Some Quotes from Readers...
"When I saw your book I was like "FINALLY" the world has woken up to dataflow." - Stewart Mackenzie
"I like to pay some attention to new developments... but don't always have the time..., "straight to the chase" books like the one you are proposing to write are very valuable." - Samuel Rødal
  • 1.1 Overview of the Book
  • 1.2 Reactive Programming is Dataflow
  • 1.3 Von Neumann Architecture
  • 1.4 Benefits of Dataflow
  • 1.5 History
  • 1.6 The Purpose of this Book
2 Dataflow Explained
  • 2.1 Pipeline Dataflow
  • 2.2 Nodes
  • 2.3 Data
  • 2.4 Arcs
  • 2.5 Dataflow Graphs
  • 2.6 Executing a Graph
  • 2.7 Features of Dataflow Systems
  • 2.7.1 Push or Pull Data
  • 2.7.2 Mutable or Immutable Data
  • 2.7.3 Static or Dynamic
  • 2.7.3.1 Dynamic
  • 2.7.3.2 Static
  • 2.7.4 Functional or Stateful Nodes
  • 2.7.5 Synchronous or Asynchronous Activation
  • 2.7.5.1 Asynchronous
  • 2.7.5.2 Synchronous
  • 2.7.5.3 Hybrid
  • 2.7.6 Multiple Inputs and/or Outputs
  • 2.7.7 Fire Patterns
  • 2.7.8 Cycles and Feedback
  • 2.7.9 Recursion
  • 2.7.9.1 Implementation of Recursive Nodes
  • 2.7.10 Compound Nodes
  • 2.7.10.1 Execution of Compound Nodes
  • 2.7.10.2 Design of Compound Nodes
  • 2.7.11 Arc Capacity > 1
  • 2.7.12 Arc Joins and/or Splits
  • 2.7.13 Multi-Rate Token Production and Consumption
  • 2.8 Common Dataflow Nodes
  • 2.8.1 Switch Node/ Choice Node
  • 2.8.2 Merge Node/ Correlate Node/ Join Node
  • 2.8.3 Distribute Node/ Splitter Node
  • 2.8.4 Gate Node
  • 2.8.5 Terminal Node
  • 2.8.6 Source Node
  • 2.8.7 Sink Node
  • 2.9 Miscellaneous Topics
  • 2.9.1 Granularity
  • 2.9.2 When is it Done?
3 Actor Model
  • 3.1 Summary of the Actor Model
  • 3.2 Comparison to Object Oriented Programming
  • 3.3 Relation to Dataflow
  • 3.4 Dataflow Features
  • 3.5 Where is the Actor Model Used?
  • 3.6 Where is it Not Used?
4 Flow-Based Programming
  • 4.1 Summary of Flow-Based Programming
  • 4.2 Dataflow Features
  • 4.3 Benefits of Flow-Based Programming
5 Communicating Sequential Processes
  • 5.1 Summary of CSP
  • 5.2 Message Passing Channels
  • 5.3 Channels as a Concurrency Primitive
  • 5.4 Channel Implementations
6 Implicit Dataflow
  • 6.1 Unix Pipes
  • 6.2 Sockets
  • 6.3 Function
  • 6.4 Manager Controlled Communication
  • 6.5 Message Passing Channels
  • 6.6 Feature Creep
7 Asynchronous Dataflow Implementation
  • 7.1 Architecture Overview
  • 7.2 Implementation Walk-Through
  • 7.3 Main Data Types
  • 7.3.1 Port Address
  • 7.3.2 Data Token
  • 7.3.3 Execute Token
  • 7.3.4 Node
  • 7.3.5 Node Definition
  • 7.3.6 Arc
  • 7.3.7 Fire Pattern
  • 7.3.8 Token Store
  • 7.3.9 Node Store
  • 7.3.10 Arc Store
  • 7.3.11 Dataflow Program
  • 7.4 Implementation Components
  • 7.4.1 IO Unit
  • 7.4.2 Transmit Unit
  • 7.4.3 Enable Unit
  • 7.4.4 Execute Unit
  • 7.5 Program Execution Example
  • 7.6 Preparing a Program for Execution
  • 7.7 Multiple Dataflow Engines
8 Synchronous Dataflow Implementation
  • 8.1 Compilation
  • 8.2 How to Build a Schedule
  • 8.2.1 Label Nodes/Arcs and Token Rates
  • 8.2.2 Create a Topology Matrix
  • 8.2.3 Does a Schedule Exist?
  • 8.2.4 Determine Initial Arc Capacities
  • 8.2.5 Execution Simulation
  • 8.2.6 Simulation Process Overview
  • 8.2.7 Simulation Process in Detail
  • 8.2.7.1 Step 1: Create a new activation matrix:
  • 8.2.7.2 Step 2: Create an activation vector
  • 8.2.7.3 Step 3: Create new Token and Fire Count Vectors
  • 8.2.7.4 Step 4: Stop or Repeat
  • 8.2.8 Analyze for Errors
  • 8.2.9 Search for a Schedule
  • 8.2.10 Test Schedule
  • 8.3 Parallel Schedules
9 Dynamic Dataflow Implementation
  • 9.1 Introduction
  • 9.2 Overall Design
  • 9.3 Features of this Design
  • 9.4 Notation Convention
  • 9.5 General Types
  • 9.6 Nodes
  • 9.6.1 Pipeline Node
  • 9.6.2 PipelineNodeObject Methods
  • 9.6.3 Developer Accessible Nodes
  • 9.6.4 Primitive Node
  • 9.6.5 PrimitiveNodeObject Methods
  • 9.6.6 Operation of a PimitiveNodeObject
  • 9.6.7 Compound Nodes
  • 9.6.8 CompoundNodeObject Methods
  • 9.6.9 NodeClass and NodeObject
  • 9.6.10 NodeObject Methods
  • 9.7 Limitations
  • 9.8 Implementation Language Requirements
Glossary Bibliography
  • Important Books and Papers
  • General
  • Hardware
  • Synchronous Dataflow
  • Communicating Sequential Processes
  • Actor Model
  • Programming Languages