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commit e819a2db0df2f60d3b0c83629057672f755436c4Author: Colin Powell <colin@unbl.ink>Date: Wed Jun 17 21:45:45 2026 -0400 [trends] Fix bug in mood trend generation@@ -88,7 +88,7 @@ fetching and simple saving. *** Metadata sources **** Scraper -* Backlog [0/20] :vrobbler:project:personal:+* Backlog [1/21] :vrobbler:project:personal: ** TODO [#C] Create small utility to clean up tracks scrobbled with wonky playback times :bug:music:scrobbles: :PROPERTIES: :ID: 702462cf-d54b-48c6-8a7c-78b8de751deb@@ -590,6 +590,10 @@ We should rename `email_scrobble_board_game` to reflect the fact that it's just a helper method to create board game scrobbles given a json blob. It's independent of the email flow it was originally creatdd for +** DONE Fix bug in generating mood trends :trends:+:PROPERTIES:+:ID: 8e75abfa-8e70-d85b-00a4-a4813bbce879+:END: * Version 54.4 [2/2] ** DONE [#A] Remove all-time trends :trends: :PROPERTIES:@@ -1,13 +1,10 @@ from collections import Counter, defaultdict-from datetime import timedelta -from django.db.models import Count, Q-from django.db.models.functions import Extract-from django.utils import timezone+from django.db.models import Q from scrobbles.models import Scrobble -def _mood_scrobbles(user, period="all_time"):+def _mood_scrobbles(user, period="last_30"): from trends.utils import get_date_range start, end = get_date_range(period)@@ -19,17 +16,25 @@ def _mood_scrobbles(user, period="all_time"): return Scrobble.objects.filter(filters).select_related("mood") +def _parse_quality(raw):+ try:+ return int(raw)+ except (TypeError, ValueError):+ return None++ def _avg_quality(values):- if not values:+ nums = [v for v in values if v is not None]+ if not nums: return 0.0- return round(sum(values) / len(values), 2)+ return round(sum(nums) / len(nums), 2) -def compute_mood_trajectory(user, period="all_time"):+def compute_mood_trajectory(user, period="last_30"): scrobbles = _mood_scrobbles(user, period).order_by("timestamp") by_date = defaultdict(list) for s in scrobbles:- quality = s.log.get("mood_quality")+ quality = _parse_quality(s.log.get("mood_quality")) if quality is not None: day_key = s.timestamp.strftime("%Y-%m-%d") by_date[day_key].append(quality)@@ -48,13 +53,13 @@ def compute_mood_trajectory(user, period="all_time"): return {"trajectory": trajectory} -def compute_mood_by_time(user, period="all_time"):+def compute_mood_by_time(user, period="last_30"): scrobbles = _mood_scrobbles(user, period) by_hour = defaultdict(list) by_day = defaultdict(list) for s in scrobbles:- quality = s.log.get("mood_quality")+ quality = _parse_quality(s.log.get("mood_quality")) if quality is not None and s.timestamp: by_hour[s.timestamp.hour].append(quality) by_day[s.timestamp.isoweekday()].append(quality)@@ -94,7 +99,7 @@ def compute_mood_by_time(user, period="all_time"): return {"hours": hours, "days": days} -def compute_mood_distribution(user, period="all_time"):+def compute_mood_distribution(user, period="last_30"): scrobbles = _mood_scrobbles(user, period) mood_counts = Counter() type_counts = Counter()@@ -120,7 +125,7 @@ def compute_mood_distribution(user, period="all_time"): } -def compute_mood_streaks(user, period="all_time"):+def compute_mood_streaks(user, period="last_30"): scrobbles = list( _mood_scrobbles(user, period).order_by("timestamp") )@@ -169,13 +174,13 @@ def compute_mood_streaks(user, period="all_time"): return {"streaks": streaks[:10], "current_streak": current_streak} -def compute_mood_weather(user, period="all_time"):+def compute_mood_weather(user, period="last_30"): scrobbles = _mood_scrobbles(user, period) by_condition = defaultdict(list) by_temp_range = defaultdict(list) for s in scrobbles:- quality = s.log.get("mood_quality")+ quality = _parse_quality(s.log.get("mood_quality")) if quality is None: continue desc = s.log.get("weather_description")@@ -183,7 +188,11 @@ def compute_mood_weather(user, period="all_time"): if desc: by_condition[desc].append(quality) if temp is not None:- bucket = f"{(int(temp) // 10) * 10}-{(int(temp) // 10) * 10 + 9}F"+ try:+ temp_f = float(temp)+ except (TypeError, ValueError):+ continue+ bucket = f"{(int(temp_f) // 10) * 10}-{(int(temp_f) // 10) * 10 + 9}F" by_temp_range[bucket].append(quality) conditions = [