| """Order Book — pre-season booking coverage (the forward view sitting unused in sale.order). |
| |
| Giftware pre-books: confirmed orders carry FUTURE delivery windows (commitment_date), so the |
| order book for the season is known months ahead. The curve compares THIS year's cumulative |
| booked $ for season delivery against last year's same-week curve — 20% under with 12 weeks to |
| go = cut the container program NOW; over = expand POs / push laggard agents. |
| |
| Season window: deliveries Aug 1 – Dec 31 (the Q4 giftware peak; env-overridable later if the |
| business adds a spring season). x-axis = weeks before Oct 1 (nominal peak). |
| """ |
| import datetime as dt |
|
|
| import core.odoo as O |
| import core.periods as P |
|
|
| SEASON_FROM = (8, 1) |
| SEASON_TO = (12, 31) |
| PEAK = (10, 1) |
|
|
|
|
| def _season_orders(year, team_id=None, cutoff=None): |
| """Confirmed orders with commitment_date inside `year`'s season window, booked up to |
| `cutoff` (order date). Returns [(order_date, amount)].""" |
| ex = O.excluded_partner_ids() |
| dom = [('state', 'in', ['sale', 'done']), |
| ('commitment_date', '>=', f'{year}-{SEASON_FROM[0]:02d}-{SEASON_FROM[1]:02d} 00:00:00'), |
| ('commitment_date', '<=', f'{year}-{SEASON_TO[0]:02d}-{SEASON_TO[1]:02d} 23:59:59')] |
| dom.append(('team_id', '=', team_id) if team_id is not None |
| else ('team_id', 'in', O.TEAM_IDS)) |
| if cutoff: |
| dom.append(('date_order', '<=', f'{cutoff} 23:59:59')) |
| if ex: |
| dom.append(('partner_id', 'not in', list(ex))) |
| rows = O.search_read('sale.order', dom, ['date_order', 'amount_untaxed']) |
| return [(str(r.get('date_order') or '')[:10], r.get('amount_untaxed') or 0.0) |
| for r in rows if r.get('date_order')] |
|
|
|
|
| def curve(team_id=None, t=None, years_back=2): |
| """Cumulative booked-$ curves, one per season year, aligned on weeks-before-peak. |
| The current year's curve stops at today; prior years run to their season end.""" |
| t = t or P.today() |
| ty = t.year |
| out_rows, totals = [], {} |
| for yr in range(ty - years_back, ty + 1): |
| peak = dt.date(yr, *PEAK) |
| cutoff = t.isoformat() if yr == ty else None |
| orders = _season_orders(yr, team_id, cutoff) |
| orders.sort() |
| cum = 0.0 |
| weekly = {} |
| for d, amt in orders: |
| cum += amt |
| wk = (peak - dt.date.fromisoformat(d)).days // 7 |
| weekly[wk] = cum |
| for wk, v in sorted(weekly.items(), reverse=True): |
| out_rows.append({'year': str(yr), 'weeks_before_peak': -wk, 'booked': v}) |
| totals[str(yr)] = cum |
| |
| wk_now = (dt.date(ty, *PEAK) - t).days // 7 |
| ly_same = 0.0 |
| for r in out_rows: |
| if r['year'] == str(ty - 1) and r['weeks_before_peak'] <= -wk_now: |
| ly_same = max(ly_same, r['booked']) |
| return {'rows': out_rows, 'totals': totals, |
| 'ty': str(ty), 'ly': str(ty - 1), |
| 'booked_ty': totals.get(str(ty), 0.0), 'ly_same_week': ly_same, |
| 'weeks_to_peak': wk_now} |
|
|
|
|
| def by_category(team_id=None, t=None): |
| """Booked $ per product category, this season TY vs LY-as-of-the-same-date. |
| (read_group cannot group by a dot-path — group by product, map to category locally.)""" |
| t = t or P.today() |
| ty = t.year |
| per_prod = {} |
| for yr, cut in ((ty, t.isoformat()), |
| (ty - 1, t.replace(year=ty - 1).isoformat())): |
| ex = O.excluded_partner_ids() |
| dom = [('order_id.state', 'in', ['sale', 'done']), |
| ('order_id.commitment_date', '>=', |
| f'{yr}-{SEASON_FROM[0]:02d}-{SEASON_FROM[1]:02d} 00:00:00'), |
| ('order_id.commitment_date', '<=', |
| f'{yr}-{SEASON_TO[0]:02d}-{SEASON_TO[1]:02d} 23:59:59'), |
| ('order_id.date_order', '<=', f'{cut} 23:59:59'), |
| ('product_id', '!=', False)] |
| dom.append(('order_id.team_id', '=', team_id) if team_id is not None |
| else ('order_id.team_id', 'in', O.TEAM_IDS)) |
| if ex: |
| dom.append(('order_partner_id', 'not in', list(ex))) |
| for g in O.read_group('sale.order.line', dom, ['price_subtotal:sum'], |
| ['product_id'], lazy=False): |
| pid = O.m2o_id(g.get('product_id')) |
| if not pid: |
| continue |
| e = per_prod.setdefault(pid, {'ty': 0.0, 'ly': 0.0}) |
| e['ty' if yr == ty else 'ly'] += g.get('price_subtotal') or 0.0 |
| cats = {} |
| pids = list(per_prod) |
| for i in range(0, len(pids), 2000): |
| for p in O.search_read('product.product', |
| [('id', 'in', pids[i:i + 2000]), |
| ('active', 'in', [True, False])], ['categ_id']): |
| cats[p['id']] = O.m2o_name(p.get('categ_id')) or '(none)' |
| out = {} |
| for pid, v in per_prod.items(): |
| cat = cats.get(pid, '(none)') |
| e = out.setdefault(cat, {'category': cat, 'ty': 0.0, 'ly': 0.0}) |
| e['ty'] += v['ty'] |
| e['ly'] += v['ly'] |
| rows = list(out.values()) |
| for r in rows: |
| r['delta_pct'] = ((r['ty'] / r['ly'] - 1) * 100.0) if r['ly'] else None |
| rows.sort(key=lambda x: -x['ty']) |
| return rows |
|
|
|
|
| def validate(t=None, team_id=None): |
| """The client-side cumulative end point ties one server-side aggregate over the exact |
| same domain (sum_field) — the independent arithmetic path.""" |
| t = t or P.today() |
| b = curve(team_id, t) |
| ty = int(b['ty']) |
| ex = O.excluded_partner_ids() |
| dom = [('state', 'in', ['sale', 'done']), |
| ('commitment_date', '>=', f'{ty}-{SEASON_FROM[0]:02d}-{SEASON_FROM[1]:02d} 00:00:00'), |
| ('commitment_date', '<=', f'{ty}-{SEASON_TO[0]:02d}-{SEASON_TO[1]:02d} 23:59:59'), |
| ('date_order', '<=', f'{t.isoformat()} 23:59:59')] |
| dom.append(('team_id', '=', team_id) if team_id is not None |
| else ('team_id', 'in', O.TEAM_IDS)) |
| if ex: |
| dom.append(('partner_id', 'not in', list(ex))) |
| srv = O.sum_field('sale.order', dom, 'amount_untaxed') |
| return [{'check': f'{ty} season booked $ — client cumulative vs server sum', |
| 'a': round(b['booked_ty'], 2), 'b': round(srv, 2), |
| 'gap': round(b['booked_ty'] - srv, 2), |
| 'ok': abs(b['booked_ty'] - srv) < 1.0}] |
|
|
