backup

analyze.py

@@ -119,7 +119,8 @@ total_words = 0
 word_frequency = Counter()
 
 total_csv = [['day', 'entries', 'words']]
-daily_csv = [['day', 'entries', 'words', 'calories', 'protein']]
+daily_csv = [['day', 'entries', 'words', 'calories', 'carbs', 'fat', 'protein',
+    'sugar']]
 entry_csv = [['timestamp', 'words']]
 words_csv = [['word', 'count']]
 
@@ -137,6 +138,9 @@ for fpath in sorted((Path.home() / 'workspace' / 'journal').glob('*.md')):
     daily_words = 0
     daily_calories = 0.0
     daily_protein = 0.0
+    daily_carbs = 0.0
+    daily_fat = 0.0
+    daily_sugar = 0.0
 
     for (timestamp, content) in sorted(entries, key=lambda x: x[0]):
         timestamp = int(datetime.strptime(timestamp, '%Y-%m-%d %H:%M:%S').timestamp())
@@ -183,6 +187,9 @@ for fpath in sorted((Path.home() / 'workspace' / 'journal').glob('*.md')):
 
             daily_calories += food.get('Energy', 0.0)
             daily_protein += food.get('Protein', 0.0)
+            daily_fat += food.get('Fat', 0.0)
+            daily_carbs += food.get('Carbs', 0.0)
+            daily_sugar += food.get('Sugar', 0.0)
 
         words = ''.join(
             c if c in string.ascii_letters+"'" else ' '
@@ -196,8 +203,19 @@ for fpath in sorted((Path.home() / 'workspace' / 'journal').glob('*.md')):
 
         entry_csv.append([timestamp, entry_words])
 
-    daily_csv.append([day, daily_entries, daily_words, daily_calories,
-        daily_protein])
+    daily_macros = daily_protein + daily_fat + daily_carbs
+
+    daily_csv.append([
+        day,
+        daily_entries,
+        daily_words,
+        round(daily_calories, 2),
+        round(100 * (daily_carbs / daily_macros) if daily_carbs else 0, 2),
+        round(100 * (daily_fat / daily_macros) if daily_fat else 0, 2),
+        round(100 * (daily_protein / daily_macros) if daily_protein else 0, 2),
+        round(daily_protein, 2),
+        round(daily_sugar, 2)
+    ])
 
     total_entries += daily_entries
     total_words += daily_words