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This gem provides a friendly client interface to the Algorithmia API, allowing you to call any of the algorithms on the Algorithmia Marketplace.
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 Dependencies

Development

~> 1.11
~> 11.1
~> 3.4

Runtime

~> 0.13
~> 2.0
 Project Readme

The Algorithmia Ruby Client

The Algorithmia Ruby client is a wrapper for making calls to the Algorithmia API and Data API.

With Algorithmia, you can leverage algorithms written in any language by including them in your Ruby project with a simple API call! Browse the collection of algorithms available on Algorithmia.com.

Getting started

The Algorithmia ruby client is available on rubygems. Simply add gem 'algorithmia' to your application's Gemfile and run bundle install.

Then create an Algorithmia client and authenticate with your API key:

require 'algorithmia'

client = Algorithmia.client('YOUR_API_KEY')

You are now ready to call algorithms.

Calling algorithms

The following examples of calling algorithms are organized by type of input/output which vary between algorithms.

Note: 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.

Text input/output

Call an algorithm with text input by simply passing a string into its pipe method. If the algorithm output is text, then the result field of the response will be a string.

algo = client.algo('demo/Hello/0.1.1')
puts algo.pipe('HAL 9000').result
# -> Hello HAL 900

JSON input/output

Call an algorithm with JSON input by simply passing in a type that can be serialized to JSON, like an Array or Hash. For algorithms that return JSON, the result field of the response will be the appropriate deserialized type.

algo = client.algo('WebPredict/ListAnagrams/0.1.0')
result = algo.pipe(["transformer", "terraforms", "retransform"]).result
# -> ["transformer","retransform"]

Alternatively, if your input is already serialized to JSON, you may call pipe_json:

algo = client.algo('WebPredict/ListAnagrams/0.1.0')
result = algo.pipe_json('["transformer", "terraforms", "retransform"]').result
# -> ["transformer","retransform"]

Binary input/output

Call an algorithm with Binary input by passing an ASCII-8BIT-encoded string into the pipe method. Similarly, if the algorithm response is binary data, then the result field of the response will be an ASCII-8BIT string. In practice, this involves working with methods like IO.binread and IO.binwrite.

input = File.binread("/path/to/bender.png")
result = client.algo("opencv/SmartThumbnail/0.1").pipe(input).result
# -> [ASCII-8BIT string of binary data]

Error handling

API errors and Algorithm exceptions will be raised when calling pipe:

client.algo('util/whoopsWrongAlgo').pipe('Hello, world!')
# -> Algorithmia::Errors::NotFoundError: algorithm algo://util/whoopsWrongAlgo not found

And you can rescue Algorithm errors separate from other errors:

begin
  client.algo('demo/Hello').pipe('world!')
rescue Algorithmia::Errors::AlgorithmError => e
  puts "Algorithm Error: #{e.message}"
  puts e.stacktrace
rescue => e
  puts "Error: #{e.message}"
end

Request options

The client exposes options that can configure algorithm requests. This includes support for changing the timeout or indicating that the API should include stdout in the response.

algo = client.algo('demo/Hello/0.1.1').set(timeout: 10, stdout: true)
response = algo.pipe('HAL 9000')
stdout = response.stdout

Note: stdout: true is ignored if you do not have access to the algorithm source.

Working with data

The Algorithmia Java client also provides a way to manage both Algorithmia hosted data and data from Dropbox or S3 accounts that you've connected to you Algorithmia account.

This client provides a DataFile type (generally created by client.file(uri)) and a DataDir type (generally created by client.dir(uri)) that provide methods for managing your data.

Create directories

Create directories by instantiating a DataDirectory object and calling create:

client.dir("data://.my/robots").create
client.dir("dropbox://robots").create

Upload files to a directory

Upload files by calling put on a DataFile object, or by calling putFile on a DataDirectory object.

robots = client.dir("data://.my/robots")

# Upload local file
robots.put_file("/path/to/Optimus_Prime.png")
# Write a text file
robots.file("Optimus_Prime.txt").put("Leader of the Autobots")
# Write a binary file
robots.file("Optimus_Prime.key").put([71, 101, 101, 107].pack('C*'))

Download contents of file

Download files by calling get or get_file on a DataFile object:

# Download file and get the file handle
t800File = client.file("data://.my/robots/T-800.png").get_file

# Get file's contents as a string
t800Text = client.file("data://.my/robots/T-800.txt").get

# Get file's contents as JSON
t800JsonString = client.file("data://.my/robots/T-800.txt").get
t800Json =  JSON.parse(t800JsonString)

# Get file's contents as a byte array
t800Bytes = client.file("data://.my/robots/T-800.png").get

Delete files and directories

Delete files and directories by calling delete on their respective DataFile or DataDirectory object. DataDirectories take an optional force parameter that indicates whether the directory should be deleted if it contains files or other directories.

client.file("data://.my/robots/C-3PO.txt").delete

client.dir("data://.my/robots").delete(false)

List directory contents

Iterate over the contents of a directory using the iterated returned by calling each, each_directory, or each_file on a DataDirectory object. If no block is given to the method, an enumerator will be returned.

# List top level directories
client.dir("data://.my").each_dir do |dir|
    puts "Directory " + dir.data_uri
end

# List files in the 'robots' directory
client.dir("data://.my/robots").each_file do |file|
    puts "File " + file.data_uri
end

# Iterate all directory contents
client.dir("dropbox://").each do |item|
    puts file.data_uri
end

Development

After checking out the repo, run bin/setup to install dependencies. Then, run rake spec to run the tests. You can also run bin/console for an interactive prompt that will allow you to experiment.

To install this gem onto your local machine, run bundle exec rake install. To release a new version, update the version number in version.rb, and then run bundle exec rake release, which will create a git tag for the version, push git commits and tags, and push the .gem file to rubygems.org.

Contributing

Bug reports and pull requests are welcome on GitHub. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.