Improved how dictionaries are handled

They are now dealt within in the same way as the tabulate package which assumes the keys are column labels and the values are iterables containing the column values.

Author: tleonhardt

examples/data_types.py

@@ -47,8 +47,7 @@
 print(iterable_of_dicts)
 print(tf.generate_table(iterable_of_dicts))
 
-dict_of_iterables = {(1, 2, 3, 4): 'a',
-                     (5, 6, 7, 8): 'b'}
+dict_of_iterables = d
 print("Data type: dict of iterables (dict keys iterated through as rows where each key must be a hashable iterable)")
 print(dict_of_iterables)
 print(tf.generate_table(dict_of_iterables))

tableformatter.py

@@ -4,6 +4,7 @@
 """
 import abc
 import enum
+import itertools
 import re
 import textwrap as textw
 from typing import List, Iterable, Optional, Tuple, Union, Callable
@@ -615,6 +616,12 @@ def generate_table(rows: Iterable[Union[Iterable, object]],
     :param row_tagger: decorator function to apply per-row options
     :return: formatted string containing the table
     """
+    # If a dictionary is passed in, then treat keys as column headers and values as column values
+    if isinstance(rows, dict):
+        if not columns:
+            columns = rows.keys()
+        rows = list(itertools.zip_longest(*rows.values()))  # columns have to be transposed
+
     # Extract column headers if this is a NumPy record array and columns weren't specified
     if not columns:
         try: