diff --git a/core.py b/core.py
index 6260339cd529f4a103ad13743c4cd044a4576bf3..1c48cda43b91099348dd9fc99b846258516a0ab4 100644
--- a/core.py
+++ b/core.py
@@ -59,7 +59,6 @@ def runner(meta, flagger, data, flags=None, nodata=np.nan):
         if varname not in flags and (varname in data or varname not in data and assign is True):
             col_flags = flagger.initFlags(pd.DataFrame(index=data.index, columns=[varname]))
             flags = col_flags if flags.empty else flags.join(col_flags)
-    print(flags.columns.values)
 
     # NOTE:
     # the outer loop runs over the flag tests, the inner one over the
diff --git a/test/common.py b/test/common.py
index d4bd05aea77f167216908b40690ae8fdaf963cbf..ef27df36a70cb4c7d3d312a96e93ca89dd086e86 100644
--- a/test/common.py
+++ b/test/common.py
@@ -1,9 +1,14 @@
 #! /usr/bin/env python
 # -*- coding: utf-8 -*-
 
+import io
+import re
+
 import numpy as np
 import pandas as pd
 
+from core import prepareMeta
+
 
 def initData(cols=2, start_date="2017-01-01", end_date="2017-12-31", freq="1h"):
     dates = pd.date_range(start="2017-01-01", end="2017-12-31", freq="1h")
@@ -12,3 +17,9 @@ def initData(cols=2, start_date="2017-01-01", end_date="2017-12-31", freq="1h"):
     for col in range(1, cols+1):
         data[f"var{col}"] = dummy*(col)
     return pd.DataFrame(data, index=dates)
+
+
+def initMeta(metastring, data):
+    fobj = io.StringIO(re.sub("\n[ \t]+", "\n", metastring))
+    meta = pd.read_csv(fobj)
+    return prepareMeta(meta, data)
diff --git a/test/flagger/test_dmpflagger.py b/test/flagger/test_dmpflagger.py
index c4c0491a543762dc35af49d64a601c8a530e9a0b..8f45288e8c011caa118e01ec52756d8b9704e12d 100644
--- a/test/flagger/test_dmpflagger.py
+++ b/test/flagger/test_dmpflagger.py
@@ -2,27 +2,27 @@
 # -*- coding: utf-8 -*-
 
 import pandas as pd
-from ..common import initData
+
+from ..common import initData, initMeta
 from core import runner, prepareMeta
 from flagger.dmpflagger import DmpFlagger, FlagFields
 
 
 def test_basic():
 
+    flagger = DmpFlagger()
     data = initData()
     var1, var2, *_ = data.columns
     var1mean = data[var1].mean()
     var2mean = data[var2].mean()
 
-    meta = [
-        [var1, f"generic, {{func: this < {var1mean}}}", "range, {min: 10, max: 20, comment: saqc}"],
-        [var2, f"generic, {{func: this > {var2mean}, cause: error}}"],
-    ]
-    meta = prepareMeta(
-        pd.DataFrame(meta, columns=["headerout", "Flag_1", "Flag_2"]),
-        data)
+    metastring = f"""
+    headerout, Flag_1, Flag_2
+    {var1},"generic, {{func: this < {var1mean}}}","range, {{min: 10, max: 20, comment: saqc}}"
+    {var2},"generic, {{func: this > {var2mean}, cause: error}}"
+    """
+    meta = initMeta(metastring, data)
 
-    flagger = DmpFlagger()
     data, flags = runner(meta, flagger, data)
 
     col1 = data[var1]
@@ -47,14 +47,12 @@ def test_flagOrder():
     fmin = flagger.flags.min()
     fmax = flagger.flags.max()
 
-    meta = [
-        [var, f"generic, {{func: this > mean(this), flag: {fmax}}}"],
-        [var, f"generic, {{func: this >= min(this), flag: {fmin}}}"],
-    ]
-
-    meta = prepareMeta(
-        pd.DataFrame(meta, columns=["headerout", "Flag_1"]),
-        data)
+    metastring = f"""
+    headerout,Flag
+    {var},"generic, {{func: this > mean(this), flag: {fmax}}}"
+    {var},"generic, {{func: this >= min(this), flag: {fmin}}}"
+    """
+    meta = initMeta(metastring, data)
 
     pdata, pflags = runner(meta, flagger, data)