app/core/parsers/apple.py

@@ -11,7 +11,7 @@ class AppleNotesParser(BaseNotesParser):
     """Parser for Apple Notes format training data."""
     
     def __init__(self):
-        super().__init__("apple.md", unique_apple_exercises_mapper)
+        super().__init__("complete_data/apple.md", unique_apple_exercises_mapper)
     
     def filter_training_data(self, training_data: str) -> str:
         """Filter Apple-specific training data format."""

app/core/parsers/obsidian.py

@@ -11,7 +11,7 @@ class ObsidianNotesParser(BaseNotesParser):
 
     def __init__(self):
         super().__init__(
-            data_file_name="obsidian.md",
+            data_file_name="complete_data/obsidian.md",
             exercise_mapper=obsidian_unique_exercies_mapping,
         )
 

app/sandbox.py

@@ -5,28 +5,23 @@ from pprint import pprint
 
 
 om = ObsidianNotesParser()
-obsidian_result = defaultdict(int)
-o_mapped_trainings = om.parse_and_map_training_data()
-for training in o_mapped_trainings:
-    for exercise in training.exercises:
-        obsidian_result[exercise.name] += 1
+o_mapped_trainings = om.parse_training_data()
 
 am = AppleNotesParser()
-apple_result = defaultdict(int)
-a_mapped_trainings = am.parse_and_map_training_data()
-for training in a_mapped_trainings:
-    for exercise in training.exercises:
-        apple_result[exercise.name] += 1
+a_mapped_trainings = am.parse_training_data()
 
-print(f"apple trainings:\t{len(a_mapped_trainings)}")
-print(f"osididian trainings:\t{len(o_mapped_trainings)}")
+combined_list = o_mapped_trainings + a_mapped_trainings
+print(len(combined_list))
 
-overall_trainings = a_mapped_trainings + o_mapped_trainings
-print(f"overall trainings:\t{len(overall_trainings)}")
-    
-overall_result = defaultdict(int)
-for training in overall_trainings:
-    for exercise in training.exercises:
-        overall_result[exercise.name] += 1
+comb_uniques_names = defaultdict(int)
+exercise_names = list()
 
-pprint(overall_result)
+for training in combined_list:
+    if training.exercises:
+        for exercise in training.exercises:
+            exercise_names.append(exercise.name)
+            comb_uniques_names[exercise.name] += 1
+
+
+# pprint(set(exercise_names))
+pprint(comb_uniques_names)