diff --git a/python/nonogram_default_search.py b/python/nonogram_default_search.py
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+# Copyright 2010 Hakan Kjellerstrand hakank@bonetmail.com, lperron@google.com
+#
+# Licensed 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
+#
+# Unless required by applicable law or agreed to in writing, 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.
+
+"""
+
+  Nonogram  (Painting by numbers) in Google CP Solver.
+
+  http://en.wikipedia.org/wiki/Nonogram
+  '''
+  Nonograms or Paint by Numbers are picture logic puzzles in which cells in a
+  grid have to be colored or left blank according to numbers given at the
+  side of the grid to reveal a hidden picture. In this puzzle type, the
+  numbers measure how many unbroken lines of filled-in squares there are
+  in any given row or column. For example, a clue of '4 8 3' would mean
+  there are sets of four, eight, and three filled squares, in that order,
+  with at least one blank square between successive groups.
+
+  '''
+
+  See problem 12 at http://www.csplib.org/.
+
+  http://www.puzzlemuseum.com/nonogram.htm
+
+  Haskell solution:
+  http://twan.home.fmf.nl/blog/haskell/Nonograms.details
+
+  Brunetti, Sara & Daurat, Alain (2003)
+  'An algorithm reconstructing convex lattice sets'
+  http://geodisi.u-strasbg.fr/~daurat/papiers/tomoqconv.pdf
+
+"""
+
+import sys
+
+from constraint_solver import pywrapcp
+
+
+#
+# Make a transition (automaton) list of tuples from a
+# single pattern, e.g. [3,2,1]
+#
+def make_transition_tuples(pattern):
+  p_len = len(pattern)
+  num_states = p_len + sum(pattern)
+
+  # this is for handling 0-clues. It generates
+  # just the minimal state
+  if num_states == 0:
+    return [(1, 0, 1)], 1
+
+  tuples = []
+
+  # convert pattern to a 0/1 pattern for easy handling of
+  # the states
+  tmp = [0];
+  c = 0
+  for pattern_index in range(p_len):
+    tmp.extend([1] * pattern[pattern_index])
+    tmp.append(0)
+
+  for i in range(num_states):
+    state = i + 1
+    if tmp[i] == 0:
+      tuples.append((state, 0, state))
+      tuples.append((state, 1, state + 1))
+    else:
+      if i < num_states - 1:
+        if tmp[i + 1] == 1:
+          tuples.append((state, 1, state + 1))
+        else:
+          tuples.append((state, 0, state + 1))
+  tuples.append((num_states, 0, num_states))
+  return (tuples, num_states)
+
+
+#
+# check each rule by creating an automaton and transition constraint.
+#
+def check_rule(rules, y):
+  cleaned_rule = [rules[i] for i in range(len(rules)) if rules[i] > 0]
+  (transition_tuples, last_state) = make_transition_tuples(cleaned_rule)
+  
+  initial_state = 1
+  accepting_states = [last_state]
+
+  solver = y[0].solver()
+  solver.Add(solver.TransitionConstraint(y,
+                                         transition_tuples,
+                                         initial_state,
+                                         accepting_states))
+
+def main(rows, row_rule_len, row_rules, cols, col_rule_len, col_rules):
+
+  # Create the solver.
+  solver = pywrapcp.Solver('Nonogram')
+
+  #
+  # variables
+  #
+  board = {}
+  for i in range(rows):
+    for j in range(cols):
+      board[i, j] = solver.IntVar(0, 1, 'board[%i, %i]' % (i, j))
+
+  board_flat = [board[i, j] for i in range(rows) for j in range(cols)]
+
+  # Flattened board for labeling.
+  # This labeling was inspired by a suggestion from
+  # Pascal Van Hentenryck about my (hakank's) Comet
+  # nonogram model.
+  board_label = []
+  if rows * row_rule_len < cols * col_rule_len:
+    for i in range(rows):
+      for j in range(cols):
+        board_label.append(board[i, j])
+  else:
+    for j in range(cols):
+      for i in range(rows):
+        board_label.append(board[i, j])
+
+  #
+  # constraints
+  #
+  for i in range(rows):
+    check_rule(row_rules[i], [board[i, j] for j in range(cols)])
+
+  for j in range(cols):
+    check_rule(col_rules[j], [board[i, j] for i in range(rows)])
+
+
+  #
+  # solution and search
+  #
+  parameters = pywrapcp.DefaultPhaseParameters()
+  parameters.heuristic_period = 200000
+  
+  db = solver.DefaultPhase(board_label, parameters)  
+
+  print 'before solver, wall time = ', solver.wall_time(), 'ms'
+  solver.NewSearch(db)
+
+  num_solutions = 0
+  while solver.NextSolution():
+    print
+    num_solutions += 1
+    for i in range(rows):
+      row = [board[i, j].Value() for j in range(cols)]
+      row_pres = []
+      for j in row:
+        if j == 1:
+          row_pres.append('#')
+        else:
+          row_pres.append(' ')
+      print '  ', ''.join(row_pres)
+
+    print
+    print '  ', '-' * cols
+
+    if num_solutions >= 2:
+      print '2 solutions is enough...'
+      break
+
+  solver.EndSearch()
+  print
+  print 'num_solutions:', num_solutions
+  print 'failures:', solver.failures()
+  print 'branches:', solver.branches()
+  print 'wall_time:', solver.wall_time(), 'ms'
+
+
+#
+# Default problem
+#
+# From http://twan.home.fmf.nl/blog/haskell/Nonograms.details
+# The lambda picture
+#
+rows = 12
+row_rule_len = 3
+row_rules = [
+    [0,0,2],
+    [0,1,2],
+    [0,1,1],
+    [0,0,2],
+    [0,0,1],
+    [0,0,3],
+    [0,0,3],
+    [0,2,2],
+    [0,2,1],
+    [2,2,1],
+    [0,2,3],
+    [0,2,2]
+    ]
+
+cols = 10
+col_rule_len = 2
+col_rules = [
+    [2,1],
+    [1,3],
+    [2,4],
+    [3,4],
+    [0,4],
+    [0,3],
+    [0,3],
+    [0,3],
+    [0,2],
+    [0,2]
+    ]
+
+
+if __name__ == '__main__':
+  if len(sys.argv) > 1:
+    file = sys.argv[1]
+    execfile(file)
+  main(rows, row_rule_len, row_rules, cols, col_rule_len, col_rules)