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@ -10,7 +10,6 @@ PERIOD_DAYS = {
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"last_30": 30,
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"last_90": 90,
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"last_year": 365,
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"all_time": None,
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}
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PERIOD_LABELS = dict(PERIOD_CHOICES)
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@ -24,8 +23,10 @@ TIME_BOUND_TRENDS = {
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"mood-streaks",
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"mood-trajectory",
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"mood-weather",
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"peak-hours",
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"reading-pace-vs-activity",
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"trending-up",
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"weekly-rhythm",
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}
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TREND_PERIOD_OVERRIDES = {
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@ -37,9 +38,7 @@ def get_supported_periods(trend_slug):
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if trend_slug in TREND_PERIOD_OVERRIDES:
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slugs = TREND_PERIOD_OVERRIDES[trend_slug]
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return {s: PERIOD_LABELS[s] for s in slugs}
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if trend_slug in TIME_BOUND_TRENDS:
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return dict(PERIOD_LABELS)
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return {"all_time": PERIOD_LABELS["all_time"]}
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return dict(PERIOD_LABELS)
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def get_period_days(period):
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@ -66,7 +65,7 @@ def get_period_nav(current_period, trend_slug):
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return prev_period, next_period
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def compute_and_save_trend(user, slug, period="all_time"):
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def compute_and_save_trend(user, slug, period="last_30"):
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"""Compute a single trend for a given period and persist the result.
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Returns elapsed seconds on success, raises on failure.
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