diff --git a/.gitignore b/.gitignore
index 7266dfdf..ddf94e8d 100644
--- a/.gitignore
+++ b/.gitignore
@@ -63,4 +63,7 @@ feature_dynamics_interpretation.pdf
 feature_dynamics_interpretation.md
 # dask
 dask-worker-space
-dask-worker-space/
\ No newline at end of file
+dask-worker-space/
+
+tests/*/__pycache__/
+tests/*/*/__pycache__/
\ No newline at end of file
diff --git a/tests/fixtures.py b/tests/fixtures.py
index 6cd35ffb..7fe306f3 100644
--- a/tests/fixtures.py
+++ b/tests/fixtures.py
@@ -1271,4 +1271,4 @@ def create_split_up_test_data_expected_tuples_wide(self):
                 ),
             ),
         ]
-        return (wide_test_data_expected_chunked_up_tuples, window_length)
+        return (wide_test_data_expected_chunked_up_tuples, window_length)
\ No newline at end of file
diff --git a/tests/units/feature_dynamics_extraction/test_feature_dynamics_data.py b/tests/units/feature_dynamics_extraction/test_feature_dynamics_data.py
index 9f3ec357..fc31a60d 100644
--- a/tests/units/feature_dynamics_extraction/test_feature_dynamics_data.py
+++ b/tests/units/feature_dynamics_extraction/test_feature_dynamics_data.py
@@ -235,4 +235,4 @@ def test_zero_split_size_dask(self):
         pass
 
     def test_fractional_split_size_dask(self):
-        pass
+        pass
\ No newline at end of file
diff --git a/tests/units/feature_dynamics_extraction/test_feature_dynamics_extraction.py b/tests/units/feature_dynamics_extraction/test_feature_dynamics_extraction.py
index d0cb807c..de9cf536 100644
--- a/tests/units/feature_dynamics_extraction/test_feature_dynamics_extraction.py
+++ b/tests/units/feature_dynamics_extraction/test_feature_dynamics_extraction.py
@@ -515,6 +515,87 @@ def test_extract_feature_dynamics_alphabetically_sorted(self):
 
             self.assertEqual(col_name_chunks, list(sorted(col_name_chunks)))
 
+    def test_extract_feature_dynamics_wide(self):
+        ts_wide_df,_,_ = self.create_simple_test_data_sample_wide()
+
+        fc_test_params = {"minimum": None}
+        window_length = 3
+
+        extracted_feature_dynamics = extract_feature_dynamics(
+            timeseries_container=ts_wide_df,
+            column_id="id",
+            column_sort="sort",
+            column_kind=None, #"kind", None since wide format
+            column_value=None, #"val",
+            n_jobs= 1,#self.n_jobs,
+            feature_timeseries_fc_parameters={window_length: fc_test_params},
+            feature_dynamics_fc_parameters={window_length: fc_test_params},
+        )
+
+        expected_ans = pd.DataFrame(
+            data={
+                'y1||minimum@window_3__minimum': {1: 1.0, 2: -34.0}, 
+                'y2||minimum@window_3__minimum': {1: -10.0, 2: 3.0}, 
+                'y3||minimum@window_3__minimum': {1: 4.0, 2: 1.0}
+                }
+            )
+
+        pd.testing.assert_frame_equal(extracted_feature_dynamics, expected_ans)
+    
+    def test_extract_feature_dynamics_long(self):
+
+        ts_long_df,_,_ = self.create_simple_test_data_sample_stacked()
+
+        fc_test_params = {"minimum": None}
+        window_length = 3
+
+        extracted_feature_dynamics = extract_feature_dynamics(
+            timeseries_container=ts_long_df,
+            column_id="id",
+            column_sort="sort",
+            column_kind="kind", #None since wide format
+            column_value="val",
+            n_jobs= 1,#self.n_jobs,
+            feature_timeseries_fc_parameters={window_length: fc_test_params},
+            feature_dynamics_fc_parameters={window_length: fc_test_params},
+        )
+
+        expected_ans = pd.DataFrame(
+            data={
+                'y1||minimum@window_3__minimum': {1: 1.0, 2: -34.0}, 
+                'y2||minimum@window_3__minimum': {1: -10.0, 2: 3.0}, 
+                'y3||minimum@window_3__minimum': {1: 4.0, 2: 1.0}
+                }
+            )
+
+        pd.testing.assert_frame_equal(extracted_feature_dynamics, expected_ans)
+
+    def test_extract_feature_dynamics_dict(self):
+        
+        ts_list_of_dicts = self.create_simple_test_data_sample_dict()
+        fc_test_params = {"minimum": None}
+        window_length = 3
+
+        extracted_feature_dynamics = extract_feature_dynamics(
+            timeseries_container=ts_list_of_dicts,
+            column_id="id",
+            column_sort="sort",
+            column_kind=None, #None since wide format
+            column_value="val",
+            n_jobs= 1,#self.n_jobs,
+            feature_timeseries_fc_parameters={window_length: fc_test_params},
+            feature_dynamics_fc_parameters={window_length: fc_test_params},
+        )
+
+        expected_ans = pd.DataFrame(
+            data={
+                'y1||minimum@window_3__minimum': {1: 1.0, 2: -34.0}, 
+                'y2||minimum@window_3__minimum': {1: -10.0, 2: 3.0}, 
+                'y3||minimum@window_3__minimum': {1: 4.0, 2: 1.0}
+                }
+            )
+
+        pd.testing.assert_frame_equal(extracted_feature_dynamics, expected_ans)
 
 class ParallelDynamicsExtractionTestCase(DataTestCase):
     def setUp(self):
diff --git a/tsfresh/feature_dynamics_extraction/feature_dynamics_utils.py b/tsfresh/feature_dynamics_extraction/feature_dynamics_utils.py
index 78e4e088..0f781b22 100644
--- a/tsfresh/feature_dynamics_extraction/feature_dynamics_utils.py
+++ b/tsfresh/feature_dynamics_extraction/feature_dynamics_utils.py
@@ -4,7 +4,7 @@
 import pandas as pd
 from pandas.api.types import is_numeric_dtype
 from typing import List
-from md2pdf.core import md2pdf
+#from md2pdf.core import md2pdf
 from tsfresh.feature_extraction import feature_calculators
 from tsfresh.utilities.string_manipulation import get_config_from_string
 from tsfresh.feature_extraction.data import (