diff --git a/profiling/__init__.py b/profiling/__init__.py
index 139597f9cb07c5d48bed18984ec4747f4b4f3438..34c8fe901fd5efd3428df1304e8159bc5f173c3c 100644
--- a/profiling/__init__.py
+++ b/profiling/__init__.py
@@ -1,2 +1,3 @@
-
+from .generate_testsets import *
+from profiling.performance import find_index_range, gen_random_timestamps
 
diff --git a/profiling/generate_testsets.py b/profiling/generate_testsets.py
index 9ec68ba9fb964249b3d13f1441212618680c0e60..9d95cc3405fa7be21ab474302cd237f3e7a54489 100644
--- a/profiling/generate_testsets.py
+++ b/profiling/generate_testsets.py
@@ -49,22 +49,36 @@ def get_random_df_and_dios(rowsz, colsz, freq='1min', disalign=True, randstart=T
     return df, dios
 
 
-def get_testset(rows, cols, freq='1s', disalign=True, randstart=True, storagedir='testsets', noresult=False):
+def get_testset(rows, cols, freq='1s', disalign=True, randstart=True, storagedir=None, noresult=False):
+    if storagedir is None:
+        storagedir = os.path.dirname(__file__)
+        storagedir = os.path.join(storagedir, 'testsets')
+
     fname = f'set_f{freq}_d{disalign}_r{randstart}_dim{rows}x{cols}.pkl'
     fpath = os.path.join(storagedir, fname)
+
+    # try to get pickled data
     try:
         with open(fpath, 'rb') as fh:
             if noresult:
                 return
             tup = pickle.load(fh)
+
+            # file/data was present
+            return tup
     except (pickle.UnpicklingError, FileNotFoundError):
-        df, dios = _gen_testset(rowsz=rows, colsz=cols, freq=freq, disalign=disalign, randstart=randstart)
-        df = df.sort_index(axis=0, level=0)
-        df_type_a = df.copy().stack(dropna=False).sort_index(axis=0, level=0).copy()
-        df_type_b = df.copy().unstack().sort_index(axis=0, level=0).copy()
-        tup = df, df_type_a, df_type_b, dios
-        with open(fpath, 'wb') as fh:
-            pickle.dump(tup, fh)
+        pass
+
+    # generate testset(s)
+    df, dios = _gen_testset(rowsz=rows, colsz=cols, freq=freq, disalign=disalign, randstart=randstart)
+    df = df.sort_index(axis=0, level=0)
+    df_type_a = df.copy().stack(dropna=False).sort_index(axis=0, level=0).copy()
+    df_type_b = df.copy().unstack().sort_index(axis=0, level=0).copy()
+    tup = df, df_type_a, df_type_b, dios
+
+    # store testsets
+    with open(fpath, 'wb') as fh:
+        pickle.dump(tup, fh)
 
     if noresult:
         return
diff --git a/tests/tests.py b/tests/tests.py
index be2407e86f50ce5b8fdba35d57e781ee31af628a..c9c2f63f31ae768392a3bccb08642405a8df3d54 100644
--- a/tests/tests.py
+++ b/tests/tests.py
@@ -1,8 +1,10 @@
 from dios import *
+from profiling import *
 import pandas as pd
 import datetime as dt
 import numpy as np
 
+
 v0 = 'var0'
 v1 = 'var1'
 v2 = 'var2'
@@ -135,7 +137,7 @@ def test_setitem():
 def test_integrity():
     rows = 1000
     cols = 10
-    df, _, _, dios = get_testset(1000, 10, storagedir='../dios/profiling/testsets')
+    df, _, _, dios = get_testset(1000, 10)
 
     v = var_prefix + str(np.random.randint(0, cols))
     t = find_index_range(dios)