Problem:
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Single Source Shortest Path

For a given weighted graph $G = (V, E)$, find the shortest path from a source to each vertex. For each vertex $u$, print the total weight of edges on the shortest path from vertex $0$ to $u$.

Input

In the first line, an integer $n$ denoting the number of vertices in $G$ is given. In the following $n$ lines, adjacency lists for each vertex $u$ are respectively given in the following format:

$u$ $k$ $v_1$ $c_1$ $v_2$ $c_2$ ... $v_k$ $c_k$

Vertices in $G$ are named with IDs $0, 1, ..., n-1$. $u$ is ID of the target vertex and $k$ denotes its degree. $v_i (i = 1, 2, ... k)$ denote IDs of vertices adjacent to $u$ and $c_i$ denotes the weight of a directed edge connecting $u$ and $v_i$ (from $u$ to $v_i$).

Output

For each vertex, print its ID and the distance separated by a space character in a line respectively. Print in order of vertex IDs.

Constraints

$1 \leq n \leq 100$

$0 \leq c_i \leq 100,000$

$|E| \leq 10,000$

All vertices are reachable from vertex $0$

Sample Input 1

5
0 3 2 3 3 1 1 2
1 2 0 2 3 4
2 3 0 3 3 1 4 1
3 4 2 1 0 1 1 4 4 3
4 2 2 1 3 3

Sample Output 1

0 0
1 2
2 2
3 1
4 3

Reference

Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. The MIT Press.

Solution in Ruby (judge verdict: Accepted)

# NOTE: I would like to use pqueue as gem library
# (from: https://github.com/rubyworks/pqueue)
# Priority queue with array based heap.
#
# A priority queue is like a standard queue, except that each inserted
# elements is given a certain priority, based on the result of the
# comparison block given at instantiation time. Also, retrieving an element
# from the queue will always return the one with the highest priority
# (see #pop and #top).
#
# The default is to compare the elements in repect to their #<=> method.
# For example, Numeric elements with higher values will have higher
# priorities.
#
# Note that as of version 2.0 the internal queue is kept in the reverse order
# from how it was kept in previous version. If you had used #to_a in the
# past then be sure to adjust for the priorities to be ordered back-to-front
# instead of the oterh way around.
#
class PQueue

  #
  VERSION = "2.1.0"  #:erb: VERSION = "<%= version %>"

  #
  # Returns a new priority queue.
  #
  # If elements are given, build the priority queue with these initial
  # values. The elements object must respond to #to_a.
  #
  # If a block is given, it will be used to determine the priority between
  # the elements. The block must must take two arguments and return `1`, `0`,
  # or `-1` or `true`, `nil` or `false. It should return `0` or `nil` if the
  # two arguments are considered equal, return `1` or `true` if the first
  # argument is considered greater than the later, and `-1` or `false` if
  # the later is considred to be greater than the first.
  #
  # By default, the priority queue retrieves maximum elements first
  # using the #<=> method.
  #
  def initialize(elements=nil, &block) # :yields: a, b
    @que = []
    @cmp = block || lambda{ |a,b| a <=> b }
    replace(elements) if elements
  end

  protected

  #
  # The underlying heap.
  #
  attr_reader :que #:nodoc:

  public

  #
  # Priority comparison procedure.
  #
  attr_reader :cmp

  #
  # Returns the size of the queue.
  #
  def size
    @que.size
  end

  #
  # Alias of size.
  #
  alias length size

  #
  # Add an element in the priority queue.
  #
  def push(v)
    @que << v
    reheap(@que.size-1)
    self
  end

  #
  # Traditional alias for #push.
  #
  alias enq push

  #
  # Alias of #push.
  #
  alias :<< :push

  #
  # Get the element with the highest priority and remove it from
  # the queue.
  #
  # The highest priority is determined by the block given at instantiation
  # time.
  #
  # The deletion time is O(log n), with n is the size of the queue.
  #
  # Return nil if the queue is empty.
  #
  def pop
    return nil if empty?
    @que.pop
  end

  #
  # Traditional alias for #pop.
  #
  alias deq pop

  # Get the element with the lowest priority and remove it from
  # the queue.
  #
  # The lowest priority is determined by the block given at instantiation
  # time.
  #
  # The deletion time is O(log n), with n is the size of the queue.
  #
  # Return nil if the queue is empty.
  #
  def shift
    return nil if empty?
    @que.shift
  end

  #
  # Returns the element with the highest priority, but
  # does not remove it from the queue.
  #
  def top
    return nil if empty?
    return @que.last
  end

  #
  # Traditional alias for #top.
  #
  alias peek top

  #
  # Returns the element with the lowest priority, but
  # does not remove it from the queue.
  #
  def bottom
    return nil if empty?
    return @que.first
  end

  #
  # Add more than one element at the same time. See #push.
  #
  # The elements object must respond to #to_a, or be a PQueue itself.
  #
  def concat(elements)
    if empty?
      if elements.kind_of?(PQueue)
        initialize_copy(elements)
      else
        replace(elements)
      end
    else
      if elements.kind_of?(PQueue)
        @que.concat(elements.que)
        sort!
      else
        @que.concat(elements.to_a)
        sort!
      end
    end
    return self
  end

  #
  # Alias for #concat.
  #
  alias :merge! :concat

  #
  # Return top n-element as a sorted array.
  #
  def take(n=@size)
    a = []
    n.times{a.push(pop)}
    a
  end

  #
  # Returns true if there is no more elements left in the queue.
  #
  def empty?
    @que.empty?
  end

  #
  # Remove all elements from the priority queue.
  #
  def clear
    @que.clear
    self
  end

  #
  # Replace the content of the heap by the new elements.
  #
  # The elements object must respond to #to_a, or to be
  # a PQueue itself.
  #
  def replace(elements)
    if elements.kind_of?(PQueue)
      initialize_copy(elements)
    else
      @que.replace(elements.to_a)
      sort!
    end
    self
  end

  #
  # Return a sorted array, with highest priority first.
  #
  def to_a
    @que.dup
  end

  #
  # Return true if the given object is present in the queue.
  #
  def include?(element)
    @que.include?(element)
  end

  #
  # Push element onto queue while popping off and returning the next element.
  # This is qquivalent to successively calling #pop and #push(v).
  #
  def swap(v)
    r = pop
    push(v)
    r
  end

  #
  # Iterate over the ordered elements, destructively.
  #
  def each_pop #:yields: popped
    until empty?
      yield pop
    end
    nil
  end

  #
  # Pretty inspection string.
  #
  def inspect
    "<#{self.class}: size=#{size}, top=#{top || "nil"}>"
  end

  #
  # Return true if the queues contain equal elements.
  #
  def ==(other)
    size == other.size && to_a == other.to_a
  end

  private

  #
  #
  #
  def initialize_copy(other)
    @cmp  = other.cmp
    @que  = other.que.dup
    sort!
  end

  #
  # The element at index k will be repositioned to its proper place.
  #
  # This, of course, assumes the queue is already sorted.
  #
  def reheap(k)
    return self if size <= 1

    que = @que.dup

    v = que.delete_at(k)
    i = binary_index(que, v)

    que.insert(i, v)

    @que = que

    return self
  end

  #
  # Sort the queue in accorance to the given comparison procedure.
  #
  def sort!
    @que.sort! do |a,b|
      case @cmp.call(a,b)
      when  0, nil   then  0
      when  1, true  then  1
      when -1, false then -1
      else
        warn "bad comparison procedure in #{self.inspect}"
        0
      end
    end
    self
  end

  #
  # Alias of #sort!
  #
  alias heapify sort!

  #
  def binary_index(que, target)
    upper = que.size - 1
    lower = 0

    while(upper >= lower) do
      idx  = lower + (upper - lower) / 2
      comp = @cmp.call(target, que[idx])

      case comp
      when 0, nil
        return idx
      when 1, true
        lower = idx + 1
      when -1, false
        upper = idx - 1
      else
      end
    end
    lower
  end

end # class PQueue

ToNode = Struct.new(:id, :weight)

N = gets.to_i

$graph       = Hash.new{|h,k| h[k] = Hash.new(Float::INFINITY)}
$q = PQueue.new([{id: 0, weight: 0}] + (1...N).each.map{|i| {id: i, weight: Float::INFINITY}}){|n1, n2| n1[:weight] < n2[:weight]}

# p $q.to_a

while (line = gets)
  node_id, _, *nodes = line.split(' ').map(&:to_i)
  # $graph[node_id] = nodes.each_slice(2).map{|id, weight| ToNode.new(id, weight)}

  nodes.each_slice(2){|id, weight|
    $graph[node_id][id] = weight
  }
end

$visited_nodes = []


$start_node_id = 0
# Min Distance '0' to `key`
$weights = Hash.new(Float::INFINITY)
$weights[$start_node_id] = 0
$visited_nodes.push($start_node_id)

while !$q.empty?
  min_node = $q.pop
  # p min_node
  # p ['min', min_node]
  u = min_node[:id]
  nodes = $graph[u]
  # p ['u', u, 'nodes', nodes]
  nodes.each{|v, weight|
    alt = $weights[u] + weight
    if $weights[v] > alt
      $weights[v] = alt
      $q.push({id: v, weight: alt})
    end
    # p ['alt', alt]
  }
  # break
end


# while $visited_nodes.size != N
#   # Node which should be visited
#   next_visit_node = nil
#   min_weight = Float::INFINITY
#
#   $visited_nodes.each{|node_id|
#     to_nodes = $graph[node_id]
#     w        = $weights[node_id]
#     to_nodes.each{|n|
#       if !$weights.has_key?(n.id)
#         weight = w + n.weight
#         if weight < min_weight
#           min_weight = weight
#           next_visit_node = {id: n.id, weight: weight}
#         end
#       end
#     }
#   }
#
#   $visited_nodes.push(next_visit_node[:id])
#   $weights[next_visit_node[:id]] = next_visit_node[:weight]
# end
#
$weights
  .sort_by{|k, v| k}
  .each{|node, weight|
    puts("#{node} #{weight}")
  }