#!/usr/bin/env python3
# -*- encoding: utf-8 -*-

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#  or more contributor license agreements.  See the NOTICE file
#  distributed with this work for additional information
#  regarding copyright ownership.  The ASF licenses this file
#  to you under the Apache License, Version 2.0 (the
#  "License"); you may not use this file except in compliance
#  with the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
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#  software distributed under the License is distributed on an
#  "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
#  KIND, either express or implied.  See the License for the
#  specific language governing permissions and limitations
#  under the License.

''' graph.py '''


################################################################################
class Graph(object):
  '''
  Adjacency list of edges in graph. This will correspond to the streams in a topology DAG.
  '''

  def __init__(self):
    # graph adjecency list. Implemented as a map with key = vertices and
    # values = set of Vertices in adjacency list.
    self.edges = {}

  # pylint: disable=invalid-name
  def add_edge(self, U, V):
    '''
    :param U:
    :param V:
    :return:
    '''
    if not U in self.edges:
      self.edges[U] = set()
    if not V in self.edges:
      self.edges[V] = set()
    if not V in self.edges[U]:
      self.edges[U].add(V)

  def __str__(self):
    return str(self.edges)

  def bfs_depth(self, U):
    '''
    Returns the maximum distance between any vertex and U in the connected
    component containing U
    :param U:
    :return:
    '''
    bfs_queue = [[U, 0]]  # Stores the vertices whose BFS hadn't been completed.
    visited = set()
    max_depth = 0
    while bfs_queue:
      [V, depth] = bfs_queue.pop()
      if max_depth < depth:
        max_depth = depth
      visited.add(V)
      adj_set = self.edges[V]
      for W in adj_set:
        if W not in visited:
          bfs_queue.append([W, depth + 1])
    return max_depth

  def diameter(self):
    '''
    Returns the maximum distance between any vertex and U in the connected
    component containing U
    :return:
    '''
    diameter = 0
    for U in self.edges:
      depth = self.bfs_depth(U)
      if depth > diameter:
        diameter = depth
    return diameter


################################################################################
class TopologyDAG(Graph):
  '''
  Creates graph from logical plan, a deeply nested map structure that looks
  like -
  {
   'spouts' -> {
      spout_name -> {
        'outputs' -> ['stream_name' -> stream_name]
      }
   },
   'bolts' -> {
     bolt_name -> {
       'outputs' -> ['stream_name'->sream_name],
       'inputs' -> ['stream_name'->stream_name,
                      'component_name'->component_name,
                      'grouping'->grouping_type]
     }
   }
  }
  '''

  def __init__(self, logical_plan):
    Graph.__init__(self)
    all_spouts = logical_plan['spouts']  # 'spouts' is required
    all_bolts = dict()
    if 'bolts' in logical_plan:
      all_bolts = logical_plan['bolts']
    stream_source = dict()  # Stores the mapping from input stream to component
    # Spout outputs
    for spout_name in all_spouts:
      for output_stream_data in all_spouts[spout_name]['outputs']:
        stream_name = output_stream_data['stream_name']
        stream_source[('%s,%s' % (spout_name, stream_name))] = spout_name
    # Bolt outputs
    for bolt_name in all_bolts:
      for output_stream_data in all_bolts[bolt_name]['outputs']:
        stream_name = output_stream_data['stream_name']
        stream_source[('%s,%s' % (bolt_name, stream_name))] = bolt_name

    # Add edges from stream_source to its destination.
    for bolt_name in all_bolts:
      for input_stream_data in all_bolts[bolt_name]['inputs']:
        stream_name = input_stream_data['stream_name']
        component_name = input_stream_data['component_name']
        stream_hash = ('%s,%s' % (component_name, stream_name))
        self.add_edge(stream_source[stream_hash], bolt_name)