[trends] Add time periods

vrobbler/apps/trends/utils.py

@@ -0,0 +1,80 @@
+import logging
+from datetime import timedelta
+
+from django.utils import timezone
+from trends.models import PERIOD_CHOICES, TrendResult
+
+logger = logging.getLogger(__name__)
+
+PERIOD_DAYS = {
+    "last_30": 30,
+    "last_90": 90,
+    "last_year": 365,
+    "all_time": None,
+}
+
+PERIOD_LABELS = dict(PERIOD_CHOICES)
+
+TIME_BOUND_TRENDS = {
+    "activity-distribution",
+    "concurrent-reading",
+    "concurrent-listening",
+    "reading-pace-vs-activity",
+    "trending-up",
+}
+
+TREND_PERIOD_OVERRIDES = {
+    "trending-up": ["last_30", "last_90", "last_year"],
+}
+
+
+def get_supported_periods(trend_slug):
+    if trend_slug in TREND_PERIOD_OVERRIDES:
+        slugs = TREND_PERIOD_OVERRIDES[trend_slug]
+        return {s: PERIOD_LABELS[s] for s in slugs}
+    if trend_slug in TIME_BOUND_TRENDS:
+        return dict(PERIOD_LABELS)
+    return {"all_time": PERIOD_LABELS["all_time"]}
+
+
+def get_period_days(period):
+    return PERIOD_DAYS.get(period)
+
+
+def get_date_range(period):
+    days = get_period_days(period)
+    if days is None:
+        return None, None
+    now = timezone.now()
+    return now - timedelta(days=days), now
+
+
+def get_period_nav(current_period, trend_slug):
+    supported = get_supported_periods(trend_slug)
+    keys = list(supported.keys())
+    try:
+        idx = keys.index(current_period)
+    except ValueError:
+        return None, None
+    prev_period = keys[idx - 1] if idx > 0 else None
+    next_period = keys[idx + 1] if idx < len(keys) - 1 else None
+    return prev_period, next_period
+
+
+def compute_and_save_trend(user, slug, period="all_time"):
+    """Compute a single trend for a given period and persist the result.
+
+    Returns elapsed seconds on success, raises on failure.
+    """
+    from trends.trends import TREND_REGISTRY
+
+    fn = TREND_REGISTRY[slug]
+    start = timezone.now()
+    data = fn(user, period=period)
+    TrendResult.objects.update_or_create(
+        user=user,
+        trend_slug=slug,
+        period=period,
+        defaults={"data": data, "computed_at": timezone.now()},
+    )
+    return (timezone.now() - start).total_seconds()