module TSort

TSort implements topological sorting using Tarjan’s algorithm for strongly connected components.

TSort is designed to be able to be used with any object which can be interpreted as a directed graph.

TSort requires two methods to interpret an object as a graph, tsort_each_node and tsort_each_child.

The equality of nodes are defined by eql? and hash since TSort uses Hash internally.

A Simple Example

The following example demonstrates how to mix the TSort module into an existing class (in this case, Hash). Here, we’re treating each key in the hash as a node in the graph, and so we simply alias the required tsort_each_node method to Hash’s #each_key method. For each key in the hash, the associated value is an array of the node’s child nodes. This choice in turn leads to our implementation of the required tsort_each_child method, which fetches the array of child nodes and then iterates over that array using the user-supplied block.

require 'tsort'

class Hash
  include TSort
  alias tsort_each_node each_key
  def tsort_each_child(node, &block)
    fetch(node).each(&block)
  end
end

{1=>[2, 3], 2=>[3], 3=>[], 4=>[]}.tsort
#=> [3, 2, 1, 4]

{1=>[2], 2=>[3, 4], 3=>[2], 4=>[]}.strongly_connected_components
#=> [[4], [2, 3], [1]]

A More Realistic Example

A very simple ‘make’ like tool can be implemented as follows:

require 'tsort'

class Make
  def initialize
    @dep = {}
    @dep.default = []
  end

  def rule(outputs, inputs=[], &block)
    triple = [outputs, inputs, block]
    outputs.each {|f| @dep[f] = [triple]}
    @dep[triple] = inputs
  end

  def build(target)
    each_strongly_connected_component_from(target) {|ns|
      if ns.length != 1
        fs = ns.delete_if {|n| Array === n}
        raise TSort::Cyclic.new("cyclic dependencies: #{fs.join ', '}")
      end
      n = ns.first
      if Array === n
        outputs, inputs, block = n
        inputs_time = inputs.map {|f| File.mtime f}.max
        begin
          outputs_time = outputs.map {|f| File.mtime f}.min
        rescue Errno::ENOENT
          outputs_time = nil
        end
        if outputs_time == nil ||
           inputs_time != nil && outputs_time <= inputs_time
          sleep 1 if inputs_time != nil && inputs_time.to_i == Time.now.to_i
          block.call
        end
      end
    }
  end

  def tsort_each_child(node, &block)
    @dep[node].each(&block)
  end
  include TSort
end

def command(arg)
  print arg, "\n"
  system arg
end

m = Make.new
m.rule(%w[t1]) { command 'date > t1' }
m.rule(%w[t2]) { command 'date > t2' }
m.rule(%w[t3]) { command 'date > t3' }
m.rule(%w[t4], %w[t1 t3]) { command 'cat t1 t3 > t4' }
m.rule(%w[t5], %w[t4 t2]) { command 'cat t4 t2 > t5' }
m.build('t5')

Bugs

References

1.  Tarjan, "Depth First Search and Linear Graph Algorithms",

SIAM Journal on Computing, Vol. 1, No. 2, pp. 146-160, June 1972.

TSort implements topological sorting using Tarjan’s algorithm for strongly connected components.

TSort is designed to be able to be used with any object which can be interpreted as a directed graph.

TSort requires two methods to interpret an object as a graph, tsort_each_node and tsort_each_child.

The equality of nodes are defined by eql? and hash since TSort uses Hash internally.

A Simple Example

The following example demonstrates how to mix the TSort module into an existing class (in this case, Hash). Here, we’re treating each key in the hash as a node in the graph, and so we simply alias the required tsort_each_node method to Hash’s #each_key method. For each key in the hash, the associated value is an array of the node’s child nodes. This choice in turn leads to our implementation of the required tsort_each_child method, which fetches the array of child nodes and then iterates over that array using the user-supplied block.

require 'tsort'

class Hash
  include TSort
  alias tsort_each_node each_key
  def tsort_each_child(node, &block)
    fetch(node).each(&block)
  end
end

{1=>[2, 3], 2=>[3], 3=>[], 4=>[]}.tsort
#=> [3, 2, 1, 4]

{1=>[2], 2=>[3, 4], 3=>[2], 4=>[]}.strongly_connected_components
#=> [[4], [2, 3], [1]]

A More Realistic Example

A very simple ‘make’ like tool can be implemented as follows:

require 'tsort'

class Make
  def initialize
    @dep = {}
    @dep.default = []
  end

  def rule(outputs, inputs=[], &block)
    triple = [outputs, inputs, block]
    outputs.each {|f| @dep[f] = [triple]}
    @dep[triple] = inputs
  end

  def build(target)
    each_strongly_connected_component_from(target) {|ns|
      if ns.length != 1
        fs = ns.delete_if {|n| Array === n}
        raise TSort::Cyclic.new("cyclic dependencies: #{fs.join ', '}")
      end
      n = ns.first
      if Array === n
        outputs, inputs, block = n
        inputs_time = inputs.map {|f| File.mtime f}.max
        begin
          outputs_time = outputs.map {|f| File.mtime f}.min
        rescue Errno::ENOENT
          outputs_time = nil
        end
        if outputs_time == nil ||
           inputs_time != nil && outputs_time <= inputs_time
          sleep 1 if inputs_time != nil && inputs_time.to_i == Time.now.to_i
          block.call
        end
      end
    }
  end

  def tsort_each_child(node, &block)
    @dep[node].each(&block)
  end
  include TSort
end

def command(arg)
  print arg, "\n"
  system arg
end

m = Make.new
m.rule(%w[t1]) { command 'date > t1' }
m.rule(%w[t2]) { command 'date > t2' }
m.rule(%w[t3]) { command 'date > t3' }
m.rule(%w[t4], %w[t1 t3]) { command 'cat t1 t3 > t4' }
m.rule(%w[t5], %w[t4 t2]) { command 'cat t4 t2 > t5' }
m.build('t5')

Bugs

References

    1. Tarjan, “Depth First Search and Linear Graph Algorithms”,

SIAM Journal on Computing, Vol. 1, No. 2, pp. 146-160, June 1972.

Constants

VERSION