Taskinator

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.x or 3.x version. Other versions/VMs are untested, but might work fine. MRI 1.x 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 install

Or install it yourself as:

$ gem install taskinator

If you are using Taskinator within a Rails application, then add an initializer, such as config/initializers/taskinator.rb, with the following configuration content:

# config/initializers/taskinator.rb
Taskinator.configure do |config|

  # configure the queue adapter to use
  # can be :active_job, :delayed_job, :resque or :sidekiq
  config.queue_adapter = :resque

  # configure redis
  config.redis = {
    :url => 'redis://redis.example.com:7372/12',
    :namespace => 'mynamespace'
  }

end

See the configuration section below for more configuration details.

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

Data Driven Process Definitions

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

Branching

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

Argument Transformations

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

Subprocesses

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

Complex Process Definitions

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)

Reusing ActiveJob jobs

It is likely that you already have one or more jobs and want to reuse them within the process definition.

Define a job step, providing the class of the Active Job to run and then taskinator will invoke that job as part of the process.

The job step will be queued and executed on same queue as configured by the job.

# 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

Execution

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

process = MyProcess.create_process

And then enqueued for execution by calling the enqueue! method of the process.

process.enqueue!

Or, started immediately by calling the start! method of the process.

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

NOTE: This aspect of the library is still a work in progress.

Processes

To monitor the state of the processes, use the Taskinator::Api::Processes class.

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

Web UI

You can also install a web interface for your Rails application. Check https://github.com/bguban/taskinator_ui for details.

Debugging

To aid debugging specific processes and tasks, where the process or task identifier is known, it is possible to retrieve the specific task or process using Taskinator::Api.

To retrieve a specific process, given the process identifier:

process_id = "SUPPLY-PROCESS-IDENTIFIER"
process = Taskinator::Api.find_process(process_id)

puts process.inspect
puts process.definition
puts process.current_state
puts process.tasks
# etc...

The type of process may be one of the following:

Taskinator::Process::Sequential
Taskinator::Process::Concurrent

Then, to retrieve a specific task, given the task identifier:

task_id = "SUPPLY-TASK-IDENTIFIER"
task = Taskinator::Api.find_task(task_id)

puts task.inspect
puts task.class
puts task.definition
puts task.args                # for Step and Job types
puts task.sub_process.tasks   # for SubProcess type
# etc...

Depending on the type of task, different attributes will be available for inspection.

The types include:

Taskinator::Task::Step
Taskinator::Task::Job
Taskinator::Task::SubProcess

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|

  # redis configuration
  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 page for more information.

Queues

To configure the queue adapter to use, set config.queue_adapter to one of the following values:

:active_job
:delayed_job
:resque
:sidekiq

As follows:

Taskinator.configure do |config|

  # configure the queue adapter to use
  # can be :active_job, :delayed_job, :resque or :sidekiq
  config.queue_adapter = :resque

end

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|

  # queue configuration
  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|

  # configure instrumenter to use
  config.instrumenter = ActiveSupport::Notifications

end

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

Taskinator.configure do |config|

  # configure instrumenter to use
  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
`:definition`	The type name of the process definition
`: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

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

License

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.

Name		Name	Last commit message	Last commit date
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.github		.github
bin		bin
lib		lib
spec		spec
.gitignore		.gitignore
.rspec		.rspec
.ruby-gemset		.ruby-gemset
.ruby-version		.ruby-version
CHANGELOG.md		CHANGELOG.md
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
Gemfile		Gemfile
Gemfile.lock		Gemfile.lock
LICENSE.txt		LICENSE.txt
README.md		README.md
Rakefile		Rakefile
processes_workflow.png		processes_workflow.png
sequence.txt		sequence.txt
taskinator.gemspec		taskinator.gemspec
tasks_workflow.png		tasks_workflow.png

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Taskinator

Requirements

Installation

Usage

Definition

Data Driven Process Definitions

Branching

Argument Transformations

Subprocesses

Complex Process Definitions

Reusing ActiveJob jobs

Execution

Arguments

Monitoring

Processes

Web UI

Debugging

Configuration

Redis

Queues

Instrumentation

Notes

Contributing

License

Inspiration

About

Releases 2

Contributors 7

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License

virtualstaticvoid/taskinator

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Taskinator

Requirements

Installation

Usage

Definition

Data Driven Process Definitions

Branching

Argument Transformations

Subprocesses

Complex Process Definitions

Reusing ActiveJob jobs

Execution

Arguments

Monitoring

Processes

Web UI

Debugging

Configuration

Redis

Queues

Instrumentation

Notes

Contributing

License

Inspiration

About

Topics

Resources

License

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Releases 2

Contributors 7

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