diff --git a/datascout/_datascout.py b/datascout/_datascout.py
index 4df2be1086c34473a2d6004c1312f31a5a0a79d9..cbcadec791f7f77fba50c9d0b58ef5803c5a9aa6 100644
--- a/datascout/_datascout.py
+++ b/datascout/_datascout.py
@@ -15,9 +15,10 @@ import scipy
 from pathlib import Path
 
 
+"""
 ######
 # Functions needed to split 2D arrays
-
+"""
 
 def _split_2D_array(val, in_memory=False, split_to_list=False, verbose=False):
     """It converts numpy 2D arrays into either 1D arrays or list of 1D arrays
@@ -71,7 +72,7 @@ def _convert_dict_list(data, in_memory=False, split_to_list=False, verbose=False
     It is up to the user to make a deepcopy, if desired, of the data before and/or after conversion.
 
     """
-    if in_memory == False:
+    if in_memory is False:
         data = copy.copy(data)
     if type(data) == list:
         for i in range(len(data)):
@@ -98,9 +99,10 @@ def _convert_dict_list(data, in_memory=False, split_to_list=False, verbose=False
     return data
 
 
+"""
 ######
 # Functions needed to re-merge 1D arrays of 1D arrays into 2D arrays
-
+"""
 
 def _merge_to_2D(val, string_as_obj=False, verbose=False):
     """
@@ -147,7 +149,7 @@ def _revert_dict_list(data, in_memory=False, string_as_obj=False, verbose=False)
 
     """
 
-    if in_memory == False:
+    if in_memory is False:
         data = copy.copy(data)
     if type(data) == list:
         for entry in data:
@@ -174,9 +176,11 @@ def _revert_dict_list(data, in_memory=False, string_as_obj=False, verbose=False)
     return data
 
 
-######
+"""
+#
 # CORE function of this project: it allows to convert a pyarrow object into a dict
 #
+"""
 def _convert_parrow_data(
     data, treat_str_arrays_as_str=True, use_list_for_2D_array=False
 ):
@@ -191,7 +195,8 @@ def _convert_parrow_data(
     if use_list_for_2D_array (default=False) it will try to use lists of 1D arrays instead of 2D arrays
 
     Typically the output should be a `dict`. If, however, one is trying to convert more complex structures
-    like a pyarrow Table or StructArray, the output will be a list of dictionaries, if more than one data records are found.
+    like a pyarrow Table or StructArray, the output will be a list of dictionaries if more than one data 
+    records are found.
     """
     if isinstance(data, pa.lib.Table):
         output = []
@@ -276,8 +281,10 @@ def _convert_parrow_data(
         return data
 
 
-###### Some important functions not so interesting for the standard user, but fundamental
-
+"""
+###### 
+# Some important functions not so interesting for the standard user, but fundamental
+"""
 
 def dict_to_pyarrow(input_dict):
     my_data_dict_converted = _convert_dict_list(
@@ -303,9 +310,9 @@ def pyarrow_to_dict(input_pa):
 def pyarrow_to_pandas(input_pa):
     return dict_to_pandas(pyarrow_to_dict(input_pa))
 
-
-####### The functions interesting for the user
-
+"""
+####### The functions interesting for the user are the following ones:
+"""
 
 def dict_to_pandas(input_dict):
     if not isinstance(input_dict, list):
@@ -399,11 +406,12 @@ def parquet_to_pandas(filename):
 def parquet_to_awkward(filename):
     return ak.from_parquet(filename)
 
-
+"""
 ####### Simple save/load functions for the user
+"""
 
 def save_dict(dictData, folderPath=None, filename=None, fileFormat="parquet"):
-    if filename == None:
+    if filename is None:
         filename = datetime.now().strftime("%Y.%m.%d.%H.%M.%S.%f")
     Path(folderPath).mkdir(parents=True, exist_ok=True)
     filename = os.path.join(folderPath, filename)
@@ -434,9 +442,9 @@ def load_dict(filename, fileFormat="parquet"):
     else:
         raise ValueError("Unknown file format ({})".format(fileFormat))
 
-
+"""
 ####### Some additional functions for debugging purposes
-
+"""
 
 def _find_lists(data, verbose=False):
     """