Three workstreams:
1. Playtomic full data extraction & transform pipeline:
- Expand venue bounding boxes from 4 to 23 regions (global coverage)
- New staging models for court resources, opening hours, and slot-level
availability with real prices from the Playtomic API
- Foundation fact tables for venue capacity and daily occupancy/revenue
- City-level pricing benchmarks replacing hardcoded country estimates
- Planner defaults now use 3-tier cascade: city data → country → fallback
2. Transactional email i18n:
- _t() helper in worker.py with ~70 translation keys (EN + DE)
- All 8 email handlers translated, lang passed in task payloads
3. Resend audiences restructured to 3 named audiences (free plan limit)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
91 lines
3.5 KiB
SQL
91 lines
3.5 KiB
SQL
-- Daily venue-level availability, pricing, occupancy, and revenue estimates.
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-- Aggregates slot-level data from stg_playtomic_availability into per-venue
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-- per-day statistics, then calculates occupancy by comparing available hours
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-- against total capacity from fct_venue_capacity.
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--
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-- Occupancy = 1 - (available_court_hours / capacity_court_hours_per_day)
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-- Revenue estimate = booked_court_hours × avg_price_of_available_slots
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--
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-- Peak hours defined as 17:00–21:00 (captures main evening rush across markets).
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MODEL (
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name foundation.fct_daily_availability,
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kind FULL,
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cron '@daily',
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grain (snapshot_date, tenant_id)
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);
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WITH slot_agg AS (
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SELECT
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a.snapshot_date,
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a.tenant_id,
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-- Slot counts: each row is one 60-min available slot on one court
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COUNT(*) AS available_slot_count,
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COUNT(DISTINCT a.resource_id) AS courts_with_availability,
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-- Available (unbooked) court-hours: slots are on 30-min increments for 60-min bookings
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-- Each available start_time represents a 60-min bookable window
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ROUND(COUNT(*) * 1.0, 2) AS available_court_hours,
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-- Pricing stats (60-min slots only)
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ROUND(MEDIAN(a.price_amount), 2) AS median_price,
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ROUND(AVG(a.price_amount), 2) AS avg_price,
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MIN(a.price_amount) AS min_price,
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MAX(a.price_amount) AS max_price,
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-- Peak: 17:00–21:00
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ROUND(MEDIAN(a.price_amount) FILTER (
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WHERE a.slot_start_time::TIME >= '17:00:00'
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AND a.slot_start_time::TIME < '21:00:00'
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), 2) AS median_price_peak,
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-- Off-peak: everything outside 17:00–21:00
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ROUND(MEDIAN(a.price_amount) FILTER (
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WHERE a.slot_start_time::TIME < '17:00:00'
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OR a.slot_start_time::TIME >= '21:00:00'
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), 2) AS median_price_offpeak,
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MAX(a.price_currency) AS price_currency,
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MAX(a.captured_at_utc) AS captured_at_utc
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FROM staging.stg_playtomic_availability a
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WHERE a.price_amount IS NOT NULL
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AND a.price_amount > 0
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GROUP BY a.snapshot_date, a.tenant_id
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)
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SELECT
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sa.snapshot_date,
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sa.tenant_id,
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cap.country_code,
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cap.city,
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cap.active_court_count,
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cap.capacity_court_hours_per_day,
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sa.available_slot_count,
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sa.courts_with_availability,
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sa.available_court_hours,
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-- Occupancy: (capacity - available) / capacity
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CASE
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WHEN cap.capacity_court_hours_per_day > 0
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THEN ROUND(
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1.0 - (sa.available_court_hours / cap.capacity_court_hours_per_day),
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4
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)
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ELSE NULL
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END AS occupancy_rate,
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-- Estimated booked court-hours
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ROUND(
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GREATEST(cap.capacity_court_hours_per_day - sa.available_court_hours, 0),
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2
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) AS booked_court_hours,
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-- Estimated daily revenue: booked hours × avg price
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ROUND(
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GREATEST(cap.capacity_court_hours_per_day - sa.available_court_hours, 0)
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* sa.avg_price,
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2
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) AS estimated_revenue_eur,
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-- Pricing
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sa.median_price,
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sa.avg_price,
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sa.min_price,
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sa.max_price,
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sa.median_price_peak,
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sa.median_price_offpeak,
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sa.price_currency,
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sa.captured_at_utc
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FROM slot_agg sa
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JOIN foundation.fct_venue_capacity cap ON sa.tenant_id = cap.tenant_id
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