style

datascout/_datascout.py

@@ -20,6 +20,7 @@ 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
 
@@ -104,6 +105,7 @@ def _convert_dict_list(data, in_memory=False, split_to_list=False, verbose=False
 # Functions needed to re-merge 1D arrays of 1D arrays into 2D arrays
 """
 
+
 def _merge_to_2D(val, string_as_obj=False, verbose=False):
     """
     _merge_to_2D(val, string_as_obj=False, verbose=False)
@@ -181,6 +183,8 @@ def _revert_dict_list(data, in_memory=False, string_as_obj=False, verbose=False)
 # 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
 ):
@@ -195,7 +199,7 @@ 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 
+    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):
@@ -282,10 +286,11 @@ def _convert_parrow_data(
 
 
 """
-###### 
+######
 # 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(
         input_dict, in_memory=False, split_to_list=False, verbose=False
@@ -310,10 +315,12 @@ 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 are the following ones:
 """
 
+
 def dict_to_pandas(input_dict):
     if not isinstance(input_dict, list):
         input_dict = [input_dict]
@@ -406,10 +413,12 @@ 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 is None:
         filename = datetime.now().strftime("%Y.%m.%d.%H.%M.%S.%f")
@@ -442,10 +451,12 @@ 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):
     """
     Look inside data (assumed to be a dict) and tell if some fields are actually lists.

docs/source/conf.py

@@ -16,11 +16,11 @@ copyright = "{0}, CERN".format(datetime.datetime.now().year)
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.
 extensions = [
-    'acc_py_sphinx.theme',
-    'sphinx.ext.autodoc',
-    'sphinx.ext.autosummary',
-    'sphinx.ext.doctest',
-    'sphinx.ext.napoleon',
+    "acc_py_sphinx.theme",
+    "sphinx.ext.autodoc",
+    "sphinx.ext.autosummary",
+    "sphinx.ext.doctest",
+    "sphinx.ext.napoleon",
 ]