diff --git a/setup.py b/setup.py
index 94da1c2..0bd3e91 100644
--- a/setup.py
+++ b/setup.py
@@ -5,7 +5,7 @@ with open("README.md", "r") as fh:
 
 setup(
     name='EasyGA',
-    version='0.0.6',
+    version='0.0.7',
     description='A ubiquitous or general purpuse GA',
     py_modules=["EasyGA"],
     package_dir={'':'src'},
diff --git a/src/EasyGA.py b/src/EasyGA.py
index c874907..88e5914 100644
--- a/src/EasyGA.py
+++ b/src/EasyGA.py
@@ -1,8 +1,9 @@
+from initialization.random_initialization import random_initialization
+
 def check_gene(value):
     assert value != "" , "Gene can not be empty"
     return value
 
-
 ## Your main structure
 class gene:
     # Defults
@@ -20,10 +21,6 @@ class gene:
     def get_value(self):
         return self.value
 
-    # Should the gene creation of the genes veriation be
-    # included in the gene class or should the use just
-    # assign value to the gene and we move on?
-
 class chromosome:
     # Defults
         # fitness = double, genes = [gene,gene,gene,etc]
@@ -37,10 +34,31 @@ class chromosome:
     def add_gene(self,gene):
         self.genes.append(gene)
 
+    def print_chromosome(self):
+        for i in range(len(self.genes)):
+            print(f"[{self.genes[i].get_value()}],", end = '')
+
+
 class population:
     # chromosomes = [chromosome,chromosome,etc]
-    def __init__(self, chromosome):
+    def __init__(self):
         self.chromosomes = []
 
-class ga:
-    pass
+    def add_chromosome(self,chromosome):
+        self.chromosomes.append(chromosome)
+
+class GA:
+    def __init__(self, population_size, chromosome_length, user_gene_function):
+        # User defined variables
+        self.population_size = population_size
+        self.chromosome_length = chromosome_length
+        self.user_gene_function = user_gene_function
+        # setup required variables
+        self.population = []
+        # Setup ga implimentation structure
+        self.initialization_impl = random_initialization()
+
+
+    def initialize(self):
+        # Create the initial population
+        self.population = self.initialization_impl.initialize(self.population_size, self.chromosome_length, self.user_gene_function)
diff --git a/src/example.py b/src/example.py
new file mode 100644
index 0000000..1f1ab53
--- /dev/null
+++ b/src/example.py
@@ -0,0 +1,15 @@
+import random
+import EasyGA
+
+def user_gene_function():
+    return random.randint(1, 100)
+
+Population_size = 10
+Chromosome_length = 10
+
+ga = EasyGA.GA(Population_size, Chromosome_length,user_gene_function)
+
+# Setup the GA's population,chromosomes and genes
+ga.initialize()
+
+print(ga.population.chromosomes[0].print_chromosome())
diff --git a/src/initialization/initialization.py b/src/initialization/initialization.py
new file mode 100644
index 0000000..d66d8ba
--- /dev/null
+++ b/src/initialization/initialization.py
@@ -0,0 +1,3 @@
+class initialization:
+    def initialize(self, population_size, chromosome_length,user_defined_function):
+        return []  # return an array of chromosomes for generation 0
diff --git a/src/initialization/random_initialization.py b/src/initialization/random_initialization.py
new file mode 100644
index 0000000..334d720
--- /dev/null
+++ b/src/initialization/random_initialization.py
@@ -0,0 +1,20 @@
+from initialization.initialization import initialization
+import EasyGA as ga
+import random
+
+class random_initialization(initialization):
+    def initialize(self, population_size, chromosome_length,user_defined_function):
+        # Create the population object
+        population = ga.population()
+        # Fill the population with chromosomes
+        for i in range(population_size):
+            #Create the chromosome object
+            chromosome = ga.chromosome()
+            #Fill the Chromosome with genes
+            for j in range(chromosome_length):
+                # File the gene object with a value
+                    # Where the user function is being implimented ---
+                chromosome.add_gene(ga.gene(user_defined_function()))
+                    # --------
+            population.add_chromosome(chromosome)
+        return population