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Welcome to algorithm development in JavaScript.

This guide will take you through the steps to getting started in algorithm development and cover the basics of managing dependencies, working with various types of inputs and outputs, calling other algorithms and managing data.

By the end of the guide you will see how to develop a couple of simple algorithms and you’ll be ready to start contributing to the algorithm marketplace.

Table of Contents

Available Libraries

Algorithmia makes a number of libraries available to make algorithm development easier.

The full Javascript Node 6.9 language and standard library is available for you to use in your algorithms.

Furthermore, algorithms can call other algorithms and manage data on the Algorithmia platform via the Algorithmia NodeJS Client.

Create an Algorithm

Let’s start by creating an algorithm. First navigate to Algorithmia and by hovering over “More” you’ll see a dropdown with a purple button that says “Add Algorithm”. Go ahead and click that button.

Add algorithm navigation

When you click the “Add Algorithm” button, you’ll see a form for creating your algorithm that we’ll fill out step by step below:

Create an algorithm in JavaScript

Algorithmia Name: The first thing you’ll notice in the form is the field “Algorithm Name” which will be the name of your algorithm. You’ll want to name your algorithm something descriptive based on what the algorithm does.

For example this guide shows how to create an algorithm that splits text up into words, which is called tokenizing in natural language processing. So, this example algorithm is called “Tokenize Text”, but go ahead and name your algorithm according to what your code does.

Algorithm ID: The unique AlgoURL path users will use to call your algorithm.

Language: Next you’ll pick the language of your choice. This is the JavaScript guide so choose JavaScript as the language.

Source Code: Because we want to make this algorithm open source and available for everyone to view the source code, we’ll choose “Open Source”.

As an incentive to promote community contributions, open source algorithms on the Algorithmia Platform will earn 1% of the usage cost (0.01cr/sec of execution time).

Special Permissions: Next is the “Special Permissions” section that allows your algorithm to have access to the internet and allows it to call other algorithms. In this example we’ll want access to the internet and since our final algorithm will call another algorithm we want to select “Can call other algorithms” as well.

Also under Special Permissions, you can select “Standard execution environment” or “Advanced GPU”. Since our algorithm isn’t processing large amounts of data needed to run on a GPU environment, we’ll select “Standard execution environment”.

You can find out more about algorithm permissions in the Algorithm Permissions Section. Also, consider whether your algorithm would benefit from using a Graphics Processing Unit to accelerate certain kinds of computation, such as image processing and deep learning. When “Advanced GPU” is selected, the algorithm will run on servers with GPU hardware, with specific drivers and frameworks to help algorithm developers take advantage of GPU computing. This includes nvidia drivers, CUDA support, and several of the most popular deep learning frameworks, including TensorFlow, Caffe, Theano, and Torch.

Now hit the “Create” button on the bottom lower right of the form and you’ll see this modal:

cli info modal

You can now clone your Algorithm (via Git) and install the CLI to edit/test locally, or you can close the modal and continue to create your algorithm in the Web IDE.

Editing your algorithm locally via GIT & CLI

The preferred way to edit and test your Algorithm’s code is to install the CLI on your local machine, clone your algorithm’s repo via Git, and use your favorite editing tools to modify the code. This gives you the benefits of using a familiar development environment, plus an easy way to test your changes locally before committing changes back to the repo and publishing a new algorithm version.

To learn more about this process, Algorithmia’s CLI and Git guides. If you’re already familiar with the CLI and Git, the basic steps you need to take are:

  1. Install the CLI: curl -sSLf | sh (Windows instructions here )
  2. Clone your algorithm: algo clone username/algoname
  3. Use your preferred editor to modify the code
  4. Test your algorithm: cd algoname; algo runlocal -D [JSON FILE]
  5. Commit your changes: git commit -m [commit message]; git push origin master
  6. Publish your changes: for now, you must do this via the web IDE:
    1. visit
    2. click on your algorithm
    3. click “Edit Source”
    4. click “Compile”, then “Publish

Editing your algorithm via the web IDE

If you prefer to continue creating your algorithm in the Web IDE, simply close the modal and you should see the algorithm console for your newly created algorithm:

Algorithm console JavaScript

Edit the source code right in the Web IDE, clicking “Compile” when you have changes you want to test. In the area below the code editor, you can enter JSON you witsh to test with. When you are ready to publish a version of your code for general use, click “Publish”.

Managing Dependencies

Now that you have created your algorithm, you can add dependencies. The algorithm we are about to create does not have any dependencies other than algorithmia (which is added by default), but it is important to know how to do this - so for now we’ll add lodash just as an example.

Algorithmia supports adding 3rd party dependencies via the NPM Javascript package manager . You don’t need to create the package.json file manually. Instead, on the algorithm editor page there is a button on the top right that says “Dependencies”. Click that button and you’ll see a modal window:

JavaScript Dependency File

Add dependencies by including the package name and version inside the dependencies section. To add lodash version 4.17.4, edit that section as follows:

"dependencies": {
	"algorithmia": "0.3.x",
 	"lodash": "4.17.4"

Now click “Save dependencies” to close the modal window.

Note: that you will still need to import your package to your algorithm file. For example, to include your package ‘lodash’ add the following to your .js file:

lodash = require("lodash")();

Write your First Algorithm

As you can see in your algorithm editor, there is a basic algorithm already written that takes a string as input and returns the string “Hello” followed by the user input.

The main thing to note about the algorithm is that it’s wrapped in the apply() function.

The apply() function defines the input point of the algorithm. We use the apply() function in order to make different algorithms standardized. This makes them easily chained and helps authors think about designing their algorithms in a way that makes them easy to leverage and predictable for end users.

To run this algorithm first hit the “Compile” button on the top right hand corner of the algorithm editor and then at the bottom of the page in the console you’ll see a confirmation that it has compiled and the version number of that commit. Until you have Published your algorithm, the version number will be a hash such as 4be0e18fba270e4aaa7cff20555268903f69a11b - only you will be able to call this version. After you’ve Published an algorithm, it will be given a major.minor.revision number as described in the Versioning Documentation.

Compiling your algorithm will also save your work, but note that the first time you compile your algorithm it might take some time while subsequent compiles will be quicker.

To test the algorithm type your name or another string in the console and hit enter on your keyboard:

Run basic algorithm in console JavaScript

I/O for your Algorithms

Now that you’ve compiled and ran a basic algorithm in the console, we’ll briefly go through some of the inputs and outputs you would expect to work with when creating an algorithm.

The first algorithm that we’ll create will take a JSON formatted object, which has been passed as input by the user. However, you don’t need to worry about deserializing the JSON; it is done automatically before the call to apply().

Your algorithm will output a JSON formatted object, returned via the callback function cb, which the user will consume via an API call to the algorithm path found at the bottom of the algorithm description page. This path is based on your Algorithmia user name and the name of your algorithm, so if you are “demo” and your algorithm is “TokenizeText”, then the path for version 0.1.1 of your algorithm will be demo/TokenizeText/0.1.1

Working with Basic Data Structures

If the input to your algorithm is a bare string (e.g. "world"), then typeof input will be ‘string’. However, we do not recommend accepting bare strings (JSON-encoded Objects are preferable), so we’ll return an error message in that case.

Following this, you can distinguish between simple Arrays vs Objects by using Array.isArray. Here’s an example that will accept either an Array, or an Object with the property “values” (which is an Array):

exports.apply = function(input, cb) {
  if (typeof input == 'string'){
    	cb("Please provide a JSON-formatted Array or Object", null);
  } else if (Array.isArray(input)) {
        var result = {
            "sum": sum(input)
    	cb(null, result);
  } else if (input["values"] && Array.isArray(input["values"])) {
        var result = {
            "sum": sum(input['values'])
    	cb(null, result);
  } else {
      cb("Please provide an Array of \"values\"", null);

var sum = function(arr) {
    return arr.reduce( function(a,b) {return a+b;} );

Go ahead and type or paste the code sample above in the Algorithmia code editor after removing the “Hello World” code.

Now compile the new code sample and when that’s done test the code in the console by passing in the input and hitting enter on your keyboard:


This should return:


Note that this returns well-formatted JSON which will be easy for the user to consume.

You’ll get a similar result by passing in just [8,6,7,5,3,0,9], but giving it a bare string or an Object without a “value” property will return an error message.

When you are creating an algorithm be mindful of the data types you require from the user and the output you return to them. Our advice is to create algorithms that allow for a few different input types such as a file, a sequence or a URL.

Working with Data Stored on Algorithmia

This next code snippet shows how to create an algorithm working with a data file that a user has stored using Algorithmia’s Hosted Data Source.

While users who consume an algorithm have access to both Dropbox and Amazon S3 connectors, algorithm developers can only use the Algorithmia Hosted Data Source to host data for algorithm development.


If you wish to follow along working through the example yourself, create a text file that contains any unstructured text such as a chapter from a public domain book or article. We used a chapter from Burning Daylight, by Jack London which you can copy and paste into a text file. Or copy and paste it from here: Chapter One Burning Daylight, by Jack London. Then you will can upload it into one of your Data Collections (create a collection, drop the file into the “Drop files here” area which appears at the bottom of the page).

This example shows how to create an algorithm that takes a user’s file stored in a data collection on the Algorithmia platform and splits up the text into sentences and words. This implementation simply splits the text on any dot, then on whitespace \s characters, and then filters out any empty strings. Once done, it passes back an Object containing the properties “text” (the raw text extracted from the file), and “words” (an Array of Arrays representing sentences and words) into the callback function:

Algorithmia = require("algorithmia");

// Note that you don't pass in your API key when creating an algorithm
client = Algorithmia.client()

exports.apply = function(input, cb) {
    if (typeof input != "string" && input["user_file"]) {
        client.file(input["user_file"]).get(function(err, data) {
            if(err) {
                cb(err, err.message);
            } else {
                var results = [];
                var sentences = data.split('.');
                for (var i=0; i<sentences.length; i++) {
                    var words = sentences[i].split(/\s/);
                    words = words.filter(function(word) {return word!="";});
                cb(null, {
                    "text": data,
                    "words": results
    } else {
        cb(null, "Please provide a value for 'user_file'");

After you paste the above code into the Algorithmia code editor you can compile and then test the example by passing in a file that you’ve hosted in Data Collections.

Following the example below, replace the path to your data collection with your user name (it will appear already if you are logged in), data collection name, and data file name which you can find under “My Collections” in Data Collections:

{"user_file": "data://YOUR_USERNAME/data_collection_dir/data_file.txt"}

You should get back an structure like this, but longer:

    "text":"It was a quiet night in the Shovel...",

Writing files for the user to consume

Sometimes it is more appropriate to write your output to a file than to return it directly to the caller. In these cases, you may need to create a temporary file, then copy it to a Data URI (usually one which the caller specified in their request, or a Temporary Algorithm Collection):

// {"target_file":"data://username/collection/filename.txt"}
var file_uri = input["target_file"];
var tempfile = "/tmp/"+uuidV4()+".tmp";

Calling Other Algorithms and Managing Data

To call other algorithms or manage data from your algorithm, use the Algorithmia NodeJS Client which is automatically available to any algorithm you create on the Algorithmia platform. For more detailed information on how to work with data see the Data API docs.

When designing your algorithm, don’t forget that there are special data directories, .session and .algo, that are available only to algorithms to help you manage data over the course of the algorithm execution.

You may call up to 24 other algorithms, either in parallel or recursively.

Error Handling

In order to provide the user with useful feedback, wrap error-prone actions in a try-catch block, and pass the error back as the first parameter to the callback function, so that users can receive this as an error object in the response:

try {
	x = parseInt(input)
} catch (error) {
	throw cb(error, input)

Algorithm Checklist

Before you are ready to publish your algorithm it’s important to go through this Algorithm Checklist and check out this blog post for Advanced Algorithm Development .

Both links will go over important best practices such as how to create a good algorithm description, add links to external documentation and other important information.

Publish Algorithm

Once you’ve developed your algorithm, you can publish it and make it available for others to use.

On the upper right hand side of the algorithm page you’ll see a purple button “Publish” which will bring up a modal:

Publish an algorithm

In this modal, you’ll see a Changes tab, a Sample I/O tab, and one called Versioning.

Changes shows you your commit history and release notes.

Sample I/O is where you’ll create your sample input and output for the user to try under Try the API in the Run tab. When you add a sample input, make sure to test it out with all the inputs that you accept since users will be able to test your algorithm with their own inputs.

Under the Versioning tab, you can select whether your algorithm will be for public use or private use as well as set the royalty. The algorithm can either be royalty-free or charge per-call. If you opt to have the algorithm charge a royalty, as the author, you will earn 70% of the royalty cost.

Check out Algorithm Pricing for more information on how much algorithms will cost to run.

Under Semantic Versioning you can choose which kind of release your change should fall under: Major, Minor, or Revision.

If you are satisfied with your algorithm and settings, go ahead and hit publish. Congratulations, you’re an algorithm developer!

Conclusion and Resources

In this guide we covered how to create an algorithm, work with different types of data and learned how to publish an algorithm.

For more resources: