An Overview

The only real problem the professional software developers are facing these days is complexity. There are only two meaningful choices here: to reduce complexity or to fight it. We know many patterns, algorithms, languages, and tools that help you to make the task less complicated. However, there are only two approaches we can embrace it instead.

The first one, called Object-Oriented Programming (OOP). It provides developers with a way to design extremely complex solutions while focusing on developing only a small portion of it at the time. The OOP enables the developer to implement the program logic as a set of relationships between several objects that interact with each other using public interfaces. Objects have the following features:

  • Encapsulation. The ability to hide data and operational logic behind the public interface. That keeps both safe from outside interference and misuse.
  • Inheritance. The ability to reuse and extend even hidden logic and operations by creating descendant classes.
  • Polymorphism. The ability to treat objects of sibling classes as identical instances of the parent class. It works in the assumption that each subclass implements the standard public methods the way it can be used in a generalized manner.

The Railway-Oriented Programming allows the developer to design the program logic as one or several processes. Each process is a sequence of tasks sharing a common context.

  • Process. A sequence of tasks that can read and modify the process context. Tasks are scheduled to be executed sequentially, but they may have internal flow logic.
  • Context. It can be any data object that can be in one of two states: Success or Failure. Context exists during execution time and may also contain other data.

Scott Wlaschin introduced the concept of Railway-Oriented Programming in his presentation on the “F# for fun and profit” website. He promotes it as the advantage of a functional programming language. I have discovered that we can use this approach in almost any programming language. Developers shall apply this pattern at the design stage, not the coding. In that case, one can avoid the obvious risk to make the code more complex instead of simplifying it.

The advantages of using the Rails pattern are the following:

  • Simplicity. It can be implemented using any object-oriented or functional language. It does not require special syntax or compiler features.
  • No interfaces. All tasks of the process are “compatible” with each other. That provides developers with the flexibility they need to make changes to the application.
  • Reliability. The most significant advantage of this approach is that it generates the most reliable code. The railway process does not fall off-the-tracks. No matter what has happened on the road, it guarantees that the result (either success or failure) will be delivered to the final destination.

When deciding to use this pattern, developers need to consider the following shortcomings:

  • Shared context. All tasks of the process are sharing the same context. Every task has only one output, and it is responsible for validating the state of the context.
  • Joins are not simple. Each process requires its own context. After performing cycles or parallel operations, you have to write code that combines multiple contexts to one.
  • Verbose. On average, it requires more lines of code than a traditional or object-oriented approach. However, the code is usually much more readable.

How it works

The idea of the Rails pattern is straightforward. The following diagram shows the process that consists of three tasks (A, B, and C). Each task in the process must wait for the data produced by the previous operation.


There are many possible scenarios for executing this process. This diagram illustrates only three of them:

  • The happy path is the scenario when all tasks completed successfully.
  • The first task executes successfully, but the next one fails.
  • The first task fails.

The Rails pattern makes sure that both success and failure are treated universally across all tasks in the process. To accomplish that, every step in the sequence is responsible for validating data and handling exceptions. In case of an error, the task poisons the context by adding an error message. All steps will be executed in the same sequence, no matter which one has failed. The poisoned context shall fall through the rest of the route.

Showcase using Java Script

Let me illustrate using the Rails pattern using JavaScript and NodeJS. Let’s assume you have the following data encoded in JSON format and stored in a file:

  "name": "John Doe",
  "age": 35

Our goal is to read this file and output the name to the screen. We design a simple process that consists of five steps:

  • Get the file name from the command line parameter
  • Read text from the file
  • Parse the JSON text to an object
  • Print the value of the object property ’name’
  • Validate data and handle errors

Some developers like a purely functional style of coding. They may compress all five steps to a single Excel-like function. In that case, the application code may look like this:

var fs = require('fs');
console.log("User name is ",
    JSON.parse(fs.readFileSync(String(process.argv.slice(2), 'utf8')).name));

To test the app, enter the following command:

$ node test.js example.json
User name is Jon Doe

Even though the application is working, it is not very reliable. If anything goes wrong, it will just throw an exception. More, the code written in this style is unreadable, difficult to test, and dangerous to modify.

Classic approach

We can rewrite this code using the classic procedural programming style:

var fs = require('fs');
var fname = process.argv.slice(2);
fname = String(fname);
var data = fs.readFileSync(fname, 'utf8');
var obj = JSON.parse(data);
console.log("User name is ",;

The code is more readable. Splitting the program to independent tasks makes it much easier to read and test.

The code is still short. However, as soon as you begin to add data validation and error handling to this code, it will start to grow. Moreover, the error handling will break the original workflow, make the code unreadable, difficult to test, and dangerous to modify.

Using Railway pattern

Let’s write the code exactly as we designed the process. It consists of five steps:

// **** Main code *************************
var context = initContenxt();
context = validateParams(context);
context = readFromFile(context);
context = validateData(context);

The approach requires implementing every task as an independent function with a unified interface. This way, we have better control over the application flow. The code is much larger, but it is also much cleaner.

We can use business domain terminology to describe the flow. We can add error handling without losing readability. The code is already optimized for unit testing. You may change the order in which the tasks are executed. It is much easier to design, develop, and debug. Let’s review every step individually.

Task 1: Create Context

First, we need to create the process context. It is an object that collects the data and reflects the current state of the workflow shared by all tasks. Implementation of the context object may vary depending on the language. In our example, our context looks like this:

function initContext() {
  var context = {
    status: "OK",
    fname: null,
    error: null,
    data: null,
    hasError: function () {
      return this.status != "OK";
    setError: function (msg) {
      this.status = "ERROR";
      this.error = msg;
      return this;
    setException: function (ex) {
      this.status = "EXCEPTION";
      this.error = ex.message;
      return this;
  return context;

A context is an object that can be in one of two states: Success or Failure. When an error happens, the task switches the state of the context object from Success to Failure. All process functions can use the context to store and pass data.

Task 2: Validate Parameters

In the Railway pattern, every task is responsible for validating data context and input parameters. Even the initial state of the process may contain errors, so the first statement of every function is to checks the state of the context. If the context has failed already, the operation shall not proceed (fall through).

The task can interrupt the execution at any time, but it must return the process context in any case:

function validateParams(context) {
  if (context.hasError()) return context;
  if (process.argv.length < 3) return context.setError("Provide file name");
  context.fname = String(process.argv.slice(2));

  if (fs.existsSync(context.fname)) {
    return context;
  } else {
    return context.setError("File '" + context.fname + "' was not found");

As you can see, the code is readable and easy to test.

Task 3: Read Data From File

The Railway pattern provides a “smooth ride” experience. It means that task functions shall never throw exceptions. The only way to return an error is by “poisoning” the context. That means that any exceptions that happened inside the function shall be converted to a failed state of the process context.

function readFromFile(context) {
  if (context.hasError()) return context;
  try {
    var obj = JSON.parse(fs.readFileSync(context.fname, 'utf8')); = obj;
  catch (e) {
    return context.setException(e);
  return context;

In case of successful execution, the task function performs the IO operations and returns the data by adding them to the context.

Task 4: Validate Data

In this example, we combine all data validation into a single function. In a real scenario, you may want to implement every validation task separately so that you can reuse it.

function validateData(context) {
  if (context.hasError()) return context;
  try {
    var name =;
    if (!name || 0 === name.length) return context.setError("Invalid name");
    if ( == null) return context.setError("Age is missing");
    var age =;
    if (age != parseInt(age, 10)) return context.setError("Invalid age");
  catch (e) {
    return context.setException(e);
  return context;

Note that you can add many more validations to the code without losing readability. Here are some suggestions on how to use validation tasks:

  • Each railway task perform a single function (specialization)
  • Do not mix data validation with other operations
  • In more complicated cases, create multiple data validation functions. You may split it down to one method per data element.
  • There is no such thing as a partial failure. The process either can proceed, or it has failed.

Task 5: Display The Result

The final task does not have to return the context:

function displayResult(context) {
  if (context.hasError()) {
    console.error(context.status, ":", context.error);
  } else {
    console.log("User name is ",;

As you can see, you may postpone the error-based decision making until the end of the process. Use this opportunity to log the results of the process execution and communicate it to users. You may even store the entire context in the log for debugging purposes.


The Railway pattern is not a universal solution, but it has distinct advantages:

  • It can be used in almost any language, both functional and object-oriented.
  • It is compatible with Domain-Driven Design and Test-Driven development approaches.
  • It allows the developer to design highly reliable processes.
  • It supports asynchronous execution and does not compromise the performance.
  • It is not a library, so you are free to decide how to implement it in your code.

Watch the original lecture of Scott Wlaschin. Railway Oriented Programming — error handling in functional languages: