Implement multiprocessing

src/main.py

@@ -1,6 +1,9 @@
 import os
+from multiprocessing import Process, Queue
 from lifecycle import Lifecycle
 from file import File
+from time import sleep
+import time
 
 param_example = {'population_size': 10,
                  'elite': round(0.1 * 10),
@@ -8,20 +11,55 @@ param_example = {'population_size': 10,
                  'iter': 1000}
 
 
+def gen_param(pop, elite, crossover, iter):
+    return {'population_size': pop,
+            'elite': round(elite * pop),
+            'crossover': round(crossover * pop),
+            'iter': iter}
+
+
+outputs = Queue()
+
+
+def run_instance(instance, output_list):
+    instance.start()
+    output_list.put(instance.get_csv())
+    print(instance.id)
+
+
 def cls():
     os.system('cls' if os.name == 'nt' else 'clear')
 
 
 output_file = File("output.csv", ['id', 'best_fit'] + list(param_example))
 
-ga = Lifecycle(1, param_example)
-
-ga.start()
-
 output_file.write_header()
 
-output_file.write_row(ga.get_csv())
+instances = list()
+
+id = 0
+
+for i in [x * 0.01 for x in range(20, 80, 5)]:
+    instances.append(Process(name="Thread-%d" % i, target=run_instance,
+                            args=[Lifecycle(id, gen_param(20, 0.1, i, 50)), outputs]))
+    id += 1
+
+start_time = time.time()
+
+for instance in instances:
+    instance.start()
+
+while len([t for t in instances if t.is_alive()]) != 0:
+    print("here")
+    sleep(1)
+
+end_time = time.time()
+
+while not outputs.empty():
+    output_file.write_row(outputs.get())
 
 output_file.close()
 
-ga.generate_graph(show=True)
+print("Execution took %f seconds" % (end_time - start_time))
+
+#ga.generate_graph(show=True)

src/population.py

@@ -94,5 +94,11 @@ class Population(object):
 
         self.mutate(10)
 
+        self.check_termination()
+
     def remove_member(self, member):
         self.members.remove(member)
+
+    def check_termination(self):
+        # todo: complete
+        pass