diff --git a/setup.py b/setup.py
new file mode 100644
index 0000000..159c41d
--- /dev/null
+++ b/setup.py
@@ -0,0 +1,9 @@
+from setuptools import setup, find_packages
+
+setup(
+    name='starpy',
+    version="0.0.001",
+    extras_require=dict(tests=['pytest']),
+    packages=find_packages(where='starpy'),
+    package_dir={"": "starpy"},
+)
diff --git a/Allocated_Score.py b/starpy/Allocated_Score.py
similarity index 100%
rename from Allocated_Score.py
rename to starpy/Allocated_Score.py
diff --git a/STAR.py b/starpy/STAR.py
similarity index 100%
rename from STAR.py
rename to starpy/STAR.py
diff --git a/starpy/__init__.py b/starpy/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/conftest.py b/tests/conftest.py
new file mode 100644
index 0000000..99a4a50
--- /dev/null
+++ b/tests/conftest.py
@@ -0,0 +1,22 @@
+import pytest
+import pandas as pd
+
+
+@pytest.fixture()
+def original_example() -> pd:
+    # load_configuration
+    # load_all_votes(test_file_1)
+    Candidates = ['A1', 'A2', 'A3', 'A4', 'B1', 'B2', 'B3', 'B4', 'C1', 'C2', 'C3', 'C4']
+    Red = 61 * [[5.0, 5.0, 5.0, 5.0, 3.0, 3.0, 3.0, 3.0, 0.0, 0.0, 0.0, 0.0]]
+    blue = 39 * [[0.0, 0.0, 0.0, 0.0, 3.0, 3.0, 3.0, 3.0, 5.0, 5.0, 5.0, 5.0]]
+    tie_breaker = [[2.0, 3.0, 4.0, 5.0, 2.0, 3.0, 4.0, 5.0, 2.0, 3.0, 4.0, 5.0]]
+    all_parties = Red + blue + tie_breaker
+
+    s = pd.DataFrame(all_parties, columns=Candidates)
+
+    return s
+
+@pytest.fixture()
+def original_results() -> list:
+    return ['A4']
+
diff --git a/test_STAR_edge_cases.py b/tests/test_STAR_edge_cases.py
similarity index 95%
rename from test_STAR_edge_cases.py
rename to tests/test_STAR_edge_cases.py
index 28877bf..a2133ec 100644
--- a/test_STAR_edge_cases.py
+++ b/tests/test_STAR_edge_cases.py
@@ -1,10 +1,3 @@
-import json
-import pandas as pd
-import numpy as np
-from STAR import STAR, TrueTie
-import pytest
-
-
 class TestSTAR:
     pass
     # def test_election_with_one_record_only(self):
diff --git a/test_STAR_multi_winner_allocated_score.py b/tests/test_STAR_multi_winner_allocated_score.py
similarity index 98%
rename from test_STAR_multi_winner_allocated_score.py
rename to tests/test_STAR_multi_winner_allocated_score.py
index 93fa8eb..284d15c 100644
--- a/test_STAR_multi_winner_allocated_score.py
+++ b/tests/test_STAR_multi_winner_allocated_score.py
@@ -6,8 +6,9 @@
 """
 
 import pandas as pd
-import numpy as np
-from Allocated_Score import Allocated_Score 
+import sys
+sys.path.append('.')
+from starpy.Allocated_Score import Allocated_Score
 
 # #Centerist bias 3 
 # Candidates = ['A','B','C']
diff --git a/test_STAR_single_winner.py b/tests/test_STAR_single_winner.py
similarity index 92%
rename from test_STAR_single_winner.py
rename to tests/test_STAR_single_winner.py
index 87767ea..e12c8a2 100644
--- a/test_STAR_single_winner.py
+++ b/tests/test_STAR_single_winner.py
@@ -6,24 +6,15 @@
 
 import json
 import pandas as pd
-import numpy as np
-from STAR import STAR, TrueTie
-import pytest
+import sys
+sys.path.append('.')
+from starpy.STAR import STAR, TrueTie
 
 
 class TestSTAR:
-    def test_original_example(self):
-        Candidates = ['A1','A2','A3','A4','B1','B2','B3','B4','C1','C2','C3','C4']
-        Red = 61 * [[5.0,5.0,5.0,5.0,3.0,3.0,3.0,3.0,0.0,0.0,0.0,0.0]]
-        blue = 39 * [[0.0,0.0,0.0,0.0,3.0,3.0,3.0,3.0,5.0,5.0,5.0,5.0]]
-        tie_breaker = [[2.0,3.0,4.0,5.0,2.0,3.0,4.0,5.0,2.0,3.0,4.0,5.0]]
-        all_parties = Red + blue + tie_breaker
-
-        S = pd.DataFrame(all_parties, columns= Candidates)
-
-        results = STAR(S)
-        print(json.dumps(results, indent = 2)) #TODO: write printing function to make this look good
-        assert results['elected'] == ['A4']
+    def test_original_example(self, original_example, original_results):
+        results = STAR(original_example)
+        assert results['elected'] == original_results
 
     def test_tennessee(self):
         # Standard Tennessee example