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Resources to get you started with Algorithmia

Scala

Updated

Available on GitHub.

This guide provides a walk-through of how to use the official Algorithmia Scala Client to call algorithms and manage data through the Algorithmia platform.

Here you will learn how to install the Algorithmia Scala Client, work with the Data API by uploading and downloading files, create and update directories and permission types and last, you’ll learn how to call an algorithm that summarizes text files.

To follow along you can create a new Scala project in the IDE of your choice.

Getting Started with Algorithmia

The Algorithmia Scala Client is published to Maven central and additional reference documentation can be found in the Algorithmia Client ScalaDocs and the Algorithmia API docs.

To get started, the Algorithmia Scala Client can be added as a library through Maven using your IDE of choice or you can download the JAR file and add it as a dependency in your POM file:

<dependency>
    <groupId>com.algorithmia</groupId>
    <artifactId>algorithmia-scala_2.11</artifactId>
    <version>0.9.2</version>
</dependency>

Authentication

Next, login to Algorithmia to get your API key:

Now import Algorithmia and create the client object by passing in your API key:

import com.algorithmia.{Algorithmia, AlgorithmiaClient}

val client = Algorithmia.client("YOUR_API_KEY");

Now you’re ready to start working with Algorithmia in Scala.

Working with Data Using the Data API

For application developers, Algorithmia’s Data Portal offers three different ways to store your data, all available via the Data API.

This guide will show you how to work with the Hosted Data option on the Algorithmia platform which is available to both algorithm and application developers.

Prerequisites

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. This will be used throughout the guide.

Create a Data Collection

This section will show how to create a data collection which is essentially a folder of data files hosted on Algorithmia for free.

Import the DataDirectory object to work with data collections:

import com.algorithmia.data._

Now create a data collection called nlp_directory:

// Instantiate a DataDirectory object, set your data URI and call create
val nlp_directory = client.dir("data://YOUR_USERNAME/nlp_directory")
try {
  if (nlp_directory.exists == false) {
    nlp_directory.create()
  }
} catch {
  case e: Exception => println("Data Directory Error: ", e.getMessage)
}

A Data URI uniquely identifies files and directories and contains a protocol “data://” and path “YOUR_USERNAME/data_collection”. For more information on the Data URI see the Data API Specification.

Instead of your username you can also use ‘.my’ when calling algorithms. For more information about the ‘.my’ pseudonym check out the Hosted Data Guide.

Work with Directory Permissions

When we created the data collection in the previous code snippet, the default setting is DataAclType.MY_ALGOS which is a permission type that allows other users on the platform to interact with your data through the algorithms you create if you decide to contribute to algorithm development. This means users can call your algorithm to perform an operation on your data stored in this collection, otherwise the algorithm you created would only work for you.

Here is how you check for the data collection’s permission type:

try {
  // Check if permissions is what you expect it to be.
  if (nlp_directory.getPermissions.read == DataMyAlgorithms) {
    System.out.println("acl is the default permissions type DataMyAlgorithms")
  }
} catch {
  case e: Exception => System.out.println("acl read problem: ", e.getMessage)
}

Now change those permissions to private:

try {
  // Update a directory to be public.
  nlp_directory.updatePermissions(DataAcl(read = DataPrivate))
  // Check if permissions is what you expect it to be.
  if (nlp_directory.getPermissions.read == DataPrivate) {
    System.out.println("acl is the default permissions type DataPrivate")
  }
} catch {
  case e: Exception => println("API Exception trying to update permissions: ", e.getMessage)
}

Notice that we changed our data collection to private, which means that only you will be able to read and write to your data collection.

Note that read access that is set to the default DataMyAlgorithms allows any algorithm you call to have access to your data collection so most often, this is the setting you want when you are calling an algorithm and are an application developer.

For more information on collection-based Access Control Lists (ACLs) and other data collection permissions go to the Hosted Data Guide.

Upload Data to your Data Collection

So far you’ve created your data collection and checked and updated directory permissions. Now you’re ready to upload the text file that you created at the beginning of the guide to your data collection using the Data API.

First add the necessary dependencies:

import java.io.File

Then upload your local file to the data collection using the .putFile() method:

try {
  // Upload contents of file as a string.
  val local_file: String = "/your_local_file_path/jack_london.txt"
  nlp_directory.putFile(new File(local_file))
  System.out.println("Successfully wrote file to data collection.")
} catch {
  case e: Exception => println("Error trying to upload file: " + e.getMessage)
}

This endpoint will replace a file if it already exists. If you wish to avoid replacing a file, check if the file exists before using this endpoint.

You can confirm that the file was created by navigating to Algorithmia’s Hosted Data Source and finding your data collection and file.

You can also upload your data through the UI on Algorithmia’s Hosted Data Source. For instructions on how to do this go to the Hosted Data Guide.

Downloading Data from a Data Collection

Next check if the file that you just uploaded to data collections exists and then download the contents of that file as a string:

// Download contents of file as a string
String text_file = "data://YOUR_USERNAME/nlp_directory/jack_london.txt";
try {
    if (client.file(text_file).exists()) {
        String input = client.file(text_file).getString();
    } else {
        System.out.println("Please check that your file exists");
    }
} catch (IOException e) {
    e.printStackTrace();
}

This will get your file as a string, saving it to the variable input.

Now you’ve seen how to upload a local data file, check if a file exists in a data collection, and download the file contents as a string.

For more methods on how to get a file using the Data API from a data collection go to the API Specification.

Call an Algorithm

Finally we are ready to call an algorithm. In this guide we’ll use the natural language processing algorithm called Summarizer. This algorithm results in a string that is the summary of the text content you pass in as the algorithm’s input.

A single algorithm may have different input and output types, or accept multiple types of input, so consult the algorithm’s description for usage examples specific to that algorithm.

This example shows the summary of the text file which we downloaded from our data collection and set as the variable called input in the previous code sample.

Add this import to call algorithms:

import com.algorithmia.algo.Algorithm

Create the algorithm object and pass in the variable input into algo.pipe():

val text_file: String = "data://YOUR_USERNAME/nlp_directory/jack_london.txt"
// Download contents of file as a string
try {
  if (client.file(text_file).exists) {
    val input: String = client.file(text_file).getString
    try {
      val algo: Algorithm = client.algo("nlp/Summarizer/0.1.3")
      val result: String = algo.pipe(input).asString
      System.out.println(result)
    } catch {
      case e: Exception => println("Algorithm error")
    }
  }
} catch {
  case e: Exception => println("Error trying to download file: ", e.getMessage)
}

This guide used the the first chapter of Jack London’s Burning Daylight and the Summarizer algorithm outputs:

“It was a quiet night in the Shovel. The miners were in from Moseyed Creek and the other diggings to the west, the summer washing had been good, and the men’s pouches were heavy with dust and nuggets. MacDonald grinned and nodded, and opened his mouth to speak, when the front door swung wide and a man appeared in the light.”

If you are interested in learning more about working with unstructured text data check out our guide Introduction to Natural Language Processing.

Conclusion

This guide covered installing Algorithmia via a POM file, uploading and downloading data to and from a user created data collection, checking if a file exists using the Data API, calling an algorithm, and handling errors.

For more information on the methods available using the Data API in Scala check out the Data API documentation or go to the Scala Client Docs for examples of executing common tasks with Algorithmia. For all available methods and versions go to the Algorithmia Scala Language Docs.

For convenience, here is the whole script available to run:

import java.io.File

import com.algorithmia.algo.Algorithm
import com.algorithmia.{Algorithmia, AlgorithmiaClient}
import com.algorithmia.data._

object ScalaGuide {
  val client: AlgorithmiaClient = Algorithmia.client("YOUR_API_KEY")

  def main(args: Array[String]): Unit = {

    // Instantiate a DataDirectory object, set your data URI and create directory.
    val nlp_directory: DataDirectory = client.dir("data://YOUR_USERNAME/nlp_directory")
    // This code snippet works
    try {
      if (nlp_directory.exists == false) {
        nlp_directory.create()
      } else {
        System.out.println("Directory already created")
      }
    } catch {
      case e: Exception => println("Data Directory Error trying to create a new directory: ", e.getMessage)
    }

    try {
      // Check if permissions is what you expect it to be.
      if (nlp_directory.getPermissions.read == DataMyAlgorithms) {
        System.out.println("acl is the default permissions type DataMyAlgorithms")
      }
    } catch {
      case e: Exception => System.out.println("acl read problem: ", e.getMessage)
    }
    try {
      // Update a directory to be public.
      nlp_directory.updatePermissions(DataAcl(read = DataPrivate))
      // Check if permissions is what you expect it to be.
      if (nlp_directory.getPermissions.read == DataPrivate) {
        System.out.println("acl is the default permissions type DataPrivate")
      }
    } catch {
      case e: Exception => println("API Exception trying to update permissions: ", e.getMessage)
    }

    try {
      // Upload contents of file as a string.
      val local_file: String = "/your_local_path/jack_london.txt"
      nlp_directory.putFile(new File(local_file))
      System.out.println("Successfully wrote file to data collection.")
    } catch {
      case e: Exception => println("Error trying to upload file: " + e.getMessage)
    }

    val text_file: String = "data://YOUR_USERNAME/nlp_directory/jack_london.txt"
    // Download contents of file as a string
    try {
      if (client.file(text_file).exists) {
        val input: String = client.file(text_file).getString
        try {
          val algo: Algorithm = client.algo("nlp/Summarizer/0.1.3")
          val result: String = algo.pipe(input).asString
          System.out.println(result)
        } catch {
          case e: Exception => println("Algorithm error")
        }
      }
    } catch {
      case e: Exception => println("Error trying to download file: ", e.getMessage)
    }
  }
}