Project

taskinator

0.02
Low commit activity in last 3 years
A long-lived project that still receives updates
Simple process orchestration
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 Dependencies

Runtime

>= 3.2.2
~> 0.3
>= 1.8.2
>= 3.2.1
~> 1.4.0
~> 0.2
 Project Readme

Taskinator

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A simple orchestration library for running complex processes or workflows in Ruby. Processes are defined using a simple DSL, where the sequences and tasks are defined. Processes can then be queued for execution. Sequences can be synchronous or asynchronous, and the overall process can be monitored for completion or failure.

Processes and tasks are executed by background workers and you can use any one of the following gems:

The configuration and state of each process and their respective tasks is stored using Redis key/values.

Requirements

The latest MRI (2.1, 2.0) version. Other versions/VMs are untested but might work fine. MRI 1.9 is not supported.

Redis 2.4 or greater is required.

One of the following background worker queue gems: resque, sidekiq or delayed_job.

NOTE: resque or sidekiq is recommended since they use Redis as a backing store as well.

Installation

Add this line to your application's Gemfile:

gem 'taskinator'

And then execute:

$ bundle

Or install it yourself as:

$ gem install taskinator

Usage

Definition

Start by creating a "process" module and extending Taskinator::Definition.

require 'taskinator'
module MyProcess
  extend Taskinator::Definition

end

Define the process using the define_process method.

module MyProcess
  extend Taskinator::Definition

  # defines a process
  define_process do

  end
end

The define_process method optionally takes the list of expected arguments which are used to validate the arguments supplied when creating a new process. These should be specified with symbols.

module MyProcess
  extend Taskinator::Definition

  # defines a process
  define_process :date, :options do
    # ...
  end
end

# when creating a process, 2 arguments are expected
process = MyProcess.create_process Date.today, :option_1 => true

NOTE: The current implementation performs a naive check on the count of arguments.

Next, specify the tasks with their corresponding implementation methods, that make up the process, using the task method and providing the method to execute for the task.

module MyProcess
  extend Taskinator::Definition

  define_process do
    task :first_work_step
    task :second_work_step
  end

  def first_work_step
    # TODO: supply implementation
  end

  def second_work_step
    # TODO: supply implementation
  end
end

More complex processes may define sequential or concurrent steps, using the sequential and concurrent methods respectively.

module MyProcess
  extend Taskinator::Definition

  define_process do
    concurrent do
      # these tasks will be executed concurrently
      task :work_step_1
      task :work_step_2
    end

    sequential do
      # thes tasks will be executed sequentially
      task :work_step_3
      task :work_step_4
    end
  end

  def work_step_1
    # TODO: supply implementation
  end

  ...

  def work_step_N
    # TODO: supply implementation
  end

end

It is likely that you already have worker classes for one of the queueing libraries, such as resque or delayed_job, and wish to reuse them for executing them in the sequence defined by the process definition.

Define a job step, providing the class of the worker, and then taskinator will execute that worker as part of the process definition. The job step will be queued and executed on same queue as configured by delayed_job, or that of the worker for resque and sidekiq.

# E.g. A resque worker
class DoSomeWork
  queue :high_priority

  def self.perform(arg1, arg2)
    # code to do the work
  end
end

module MyProcess
  extend Taskinator::Definition

  # when creating the process, supply the same arguments
  # that the DoSomeWork worker expects

  define_process do
    job DoSomeWork
  end
end

You can also define data driven tasks using the for_each method, which takes an iterator method name as an argument. The iterator method yields the parameters necessary for the task or job. Notice that the task method takes a parameter in this case, which will be the return values provided by the iterator.

module MyProcess
  extend Taskinator::Definition

  define_process do
    for_each :yield_data_elements do
      task :work_step
    end
  end

  def yield_data_elements
    # TODO: supply implementation to yield elements
    yield 1
  end

  def work_step(data_element)
    # TODO: supply implementation
  end
end

It is possible to branch the process logic based on the options hash passed in when creating a process. The options? method takes the options key as an argument and calls the supplied block if the option is present and it's value is truthy.

module MyProcess
  extend Taskinator::Definition

  define_process do

    option?(:some_setting) do
      task :prerequisite_step
    end

    task :work_step

  end

  def prerequisite_step
    # ...
  end

  def work_step
    # ...
  end

end

# now when creating the process, the `:some_setting` option can be used to branch the logic
process1 = MyProcess.create_process :some_setting => true
process1.tasks.count #=> 2

process2 = MyProcess.create_process
process2.tasks.count #=> 1

In addition, it is possible to transform the arguments used by a task or job, by including a transform step in the definition. Similarly for the for_each method, transform takes a method name as an argument. The transformer method must yield the new arguments as required.

module MyProcess
  extend Taskinator::Definition

  # this process is created with a hash argument

  define_process do
    transform :convert_args do
      task :work_step
    end
  end

  def convert_args(options)
    yield *[options[:date_from], options[:date_to]]
  end

  def work_step(date_from, date_to)
    # TODO: supply implementation
  end
end

Processes can be composed of other processes too:

module MySubProcessA
  ...
end

module MySubProcessB
  ...
end

module MyProcess
  extend Taskinator::Definition

  define_process do
    sub_process MySubProcessA
    sub_process MySubProcessB
  end
end

Any combination or nesting of task, sequential, concurrent and for_each steps are possible. E.g.

module MyProcess
  extend Taskinator::Definition

  define_process do
    for_each :data_elements do
      task :work_step_begin

      concurrent do
        for_each :sub_data_elements do
          task :work_step_all_at_once
        end
      end

      sub_process MySubProcess

      sequential do
        for_each :sub_data_elements do
          task :work_step_one_by_one
        end
      end

      task :work_step_end
    end
  end

  # "task" and "iterator" methods omitted for brevity

end

In this example, the work_step_begin is executed, followed by the work_step_all_at_once steps which are executed concurrently, then the sub process MySubProcess is created and executed, followed by the work_step_one_by_one tasks which are executed sequentially and finally the work_step_end is executed.

It is also possible to embed conditional logic within the process definition stages in order to produce steps based on the required logic. All builder methods are available within the scope of the define_process block. These methods include args and options which are passed into the create_process method of the definition.

E.g.

module MyProcess
  extend Taskinator::Definition

  define_process do
    task :task_1
    task :task_2
    task :task_3 if args[3] == 1
    task :send_notification if options[:send_notification]
  end

  # "task" methods are omitted for brevity

end

# when creating this proces, you supply to option when calling `create_process`
# in this example, 'args' will be an array [1,2,3] and options will be a Hash {:send_notification => true}
MyProcess.create_process(1, 2, 3, :send_notification => true)

Execution

A process is executed by calling the generated create_process method on your "process" module.

process = MyProcess.create_process
process.enqueue!

Or, to start immediately, call the start! method.

process = MyProcess.create_process
process.start!

Arguments

Argument handling for defining and executing process definitions is where things can get trickey. This may be something that gets refactored down the line.

To best understand how arguments are handled, you need to break it down into 3 phases. Namely:

  • Definition,
  • Creation and
  • Execution

Firstly, a process definition is declarative in that the define_process and a mix of sequential, concurrent, for_each, task and job directives provide the way to specify the sequencing of the steps for the process. Taskinator will interprete this definition and execute each step in the desired sequence or concurrency.

Consider the following process definition:

module MySimpleProcess
  extend Taskinator::Definition

  # definition

  define_process do
    task :work_step_1
    task :work_step_2

    for_each :additional_step do
      task :work_step_3
    end
  end

  # creation

  def additional_step(options)
    options.steps.each do |k, v|
      yield k, v
    end
  end

  # execution

  def work_step_1(options)
    # ...
  end

  def work_step_2(options)
    # ...
  end

  def work_step_3(k, v)
    # ...
  end

end

There are three tasks; namely :work_step_1, :work_step_2 and :work_step_3.

The third task, :work_step_3, is built up using the for_each iterator, which means that the number of :work_step_3 tasks will depend on how many times the additional_step iterator method yields to the definition.

This brings us to the creation part. When create_process is called on the given module, you provide arguments to it, which will get passed onto the respective task and for_each iterator methods.

So, considering the MySimpleProcess module shown above, work_step_1, work_step_2 and work_step_3 methods each expect arguments. These will ultimately come from the arguments passed into the create_process method.

E.g.

# Given an options hash
options = {
  :opt1 => true,
  :opt2 => false,
  :steps => {
    :a => 1,
    :b => 2,
    :c => 3,
  }
}

# You create the process, passing in the options hash
process = MySimpleProcess.create_process(options)

To best understand how the process is created, consider the following "procedural" code for how it could work.

# A process, which maps the target and a list of steps
class Process
  attr_reader :target
  attr_reader :tasks

  def initialize(target)
    @target = target
    @tasks = []
  end
end

# A task, which maps the method to call and it's arguments
class Task
  attr_reader :method
  attr_reader :args

  def initialize(method, args)
    @method, @args = method, args
  end
end

# Your module, with the methods which do the actual work
module MySimpleProcess

  def self.work_step_1(options) ...
  def self.work_step_2(options) ...
  def self.work_step_3(k, v) ...

end

# Now, the creation phase of the definition
# create a process, providing the module

process = Process.new(MySimpleProcess)

# create the first and second tasks, providing the method
# for the task and it's arguments, which are the options defined above

process.tasks << Task.new(:work_step_1, options)
process.tasks << Task.new(:work_step_2, options)

# iterate over the steps hash in the options, and add the third step
# this time specify the key and value as the
# arguments for the work_step_3 method

options.steps.each do |k, v|
  process.tasks << Task.new(:work_step_3, [k, v])
end

# we now have a process with the tasks defined

process.tasks  #=> [<Task :method=>work_step_1, :args=>options, ...> ,
               #    <Task :method=>work_step_2, :args=>options, ...>,
               #    <Task :method=>work_step_3, :args=>[:a, 1], ...>,
               #    <Task :method=>work_step_3, :args=>[:b, 2], ...>,
               #    <Task :method=>work_step_3, :args=>[:c, 3], ...>]

Finally, for the execution phase, the process and tasks will act on the supplied module.

# building out the "Process" class
class Process
  #...

  def execute
    tasks.each {|task| task.execute(target) )
  end
end

# and the "Task" class
class Task
  #...

  def execute(target)
    puts "Calling '#{method}' on '#{target.name}' with #{args.inspect}..."
    target.send(method, *args)
  end
end

# executing the process iterates over each task and
# the target modules method is called with the arguments

process.execute

# Calling 'work_step_1' on 'MySimpleProcess' with {:opt1 => true, :opt2 => false, ...}
# Calling 'work_step_2' on 'MySimpleProcess' with {:opt1 => true, :opt2 => false, ...}
# Calling 'work_step_3' on 'MySimpleProcess' with [:a, 1]
# Calling 'work_step_3' on 'MySimpleProcess' with [:b, 2]
# Calling 'work_step_3' on 'MySimpleProcess' with [:c, 3]

In reality, each task is executed by a worker process, possibly on another host, so the execution process isn't as simple, but this example should help you to understand conceptually how the process is executed, and how the arguments are propagated through.

Monitoring

To monitor the state of the processes, use the Taskinator::Api::Processes class. This is still a work in progress.

processes = Taskinator::Api::Processes.new
processes.each do |process|
  # => output the unique process identifier and current state
  puts [:process, process.uuid, process.current_state]
end

Configuration

Redis

By default Taskinator assumes Redis is located at localhost:6397. This is fine for development, but for many production environments you will need to point to an external Redis server. You may also what to use a namespace for the Redis keys. NOTE: The configuration hash must have symbolized keys.

Taskinator.configure do |config|
 config.redis = {
   :url => 'redis://redis.example.com:7372/12',
   :namespace => 'mynamespace'
 }
end

Or, alternatively, via an ENV variable

Set the REDIS_PROVIDER environment variable to the Redis server url. E.g. On Heroku, with RedisGreen: set REDIS_PROVIDER=REDISGREEN_URL and Taskinator will use the value of the REDISGREEN_URL environment variable when connecting to Redis.

You may also use the generic REDIS_URL which may be set to your own private Redis server.

The Redis configuration leverages the same setup as sidekiq. For advanced options, checkout the Sidekiq Advanced Options wiki for more information.

Queues

By default the queue names for process and task workers is default, however, you can specify the queue names as follows:

Taskinator.configure do |config|
  config.queue_config = {
    :process_queue => :default,
    :task_queue => :default
  }
end

Instrumentation

It is possible to instrument processes, tasks and jobs by providing an instrumeter such as ActiveSupport::Notifications.

Taskinator.configure do |config|
  config.instrumenter = ActiveSupport::Notifications
end

Alternatively, you can use the built-in instrumenter for logging to the console for debugging:

Taskinator.configure do |config|
  config.instrumenter = Taskinator::ConsoleInstrumenter.new
end

The following instrumentation events are issued:

Event When
taskinator.process.created After a root process gets created
taskinator.process.saved After a root process has been persisted to Redis
taskinator.process.enqueued After a process or subprocess is enqueued for processing
taskinator.process.processing When a process or subprocess is processing
taskinator.process.paused When a process or subprocess is paused
taskinator.process.resumed When a process or subprocess is resumed
taskinator.process.completed After a process or subprocess has completed processing
taskinator.process.cancelled After a process or subprocess has been cancelled
taskinator.process.failed After a process or subprocess has failed
taskinator.task.enqueued After a task has been enqueued
taskinator.task.processing When a task is processing
taskinator.task.completed After a task has completed
taskinator.task.cancelled After a task has been cancelled
taskinator.task.failed After a task has failed

For all events, the data included contains the following information:

Key Value
:type The type name of the component reporting the event
:process_uuid The UUID of the root process
:process_options Options hash of the root process
:uuid The UUID of the respective task, job or sub process
:options Options hash of the component
:state State of the component
:percentage_completed The percentage of completed tasks
:percentage_failed The percentage of failed tasks
:percentage_cancelled The percentage of cancelled tasks

Notes

The persistence logic is decoupled from the implementation, so it is possible to implement another backing store if required.

Contributing

  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request

License

MIT Copyright (c) 2014 Chris Stefano

Portions of code are from the Sidekiq project, Copyright (c) Contributed Systems LLC.

Inspiration

Inspired by the sidekiq and workflow gems.

For other workflow solutions, checkout Stonepath, the now deprecated ruote gem and workflow. Alternatively, for a robust enterprise ready solution checkout the AWS Flow Framework for Ruby.