File size: 12,289 Bytes
c14ceee | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 | """Returns module — the credit-note lens nobody reads: 14% of billing documents are refunds.
Governing question: WHERE DO RETURNS CONCENTRATE — WHICH SKUs (quality signal), WHICH
CUSTOMERS (behavior signal), WHICH CATEGORIES (product-line signal), WHICH SUPPLIERS
(sourcing-quality signal) AND WHICH AGENTS (book-behavior signal) — AND IS THE RATE MOVING?
Odoo has no return-reason field, so the concentration IS the diagnostic. Rates are always shown
next to raw $ — a big seller with average rate is noise; a small line with 4x the company rate
is the finding.
Supplier attribution: curated procurement map (default_code) first, else the DOMINANT vendor
from confirmed PO history (most units bought), else '(no supplier data)'. Agent attribution:
the customer's res.partner agent — credit-note team_id is NOT trustworthy.
Company-level (credit notes carry team_id=1 for everything). READ-ONLY.
"""
import sys
import datetime as dt
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
import core.odoo as O
import core.periods as P
import modules.customers as cust_mod
import modules.procurement as proc_mod
_EX_MOVE = [] # posted customer docs only
def _mdom(move_type, a, b):
return [('move_type', '=', move_type), ('state', '=', 'posted'),
('invoice_date', '>=', a), ('invoice_date', '<=', b)]
def _ldom(move_type, a, b):
return [('move_id.move_type', '=', move_type), ('parent_state', '=', 'posted'),
('move_id.invoice_date', '>=', a), ('move_id.invoice_date', '<=', b),
('product_id', '!=', False)]
def build(t=None):
t = t or P.today()
d12 = (t - dt.timedelta(days=365)).isoformat()
d13m = (t.replace(day=1) - dt.timedelta(days=380)).replace(day=1).isoformat()
ti = t.isoformat()
# ---- headline + monthly (from the MOVES — count + untaxed value) -----------------------
def _monthly(mt):
out = {}
for g in O.read_group('account.move', _mdom(mt, d13m, ti),
['amount_untaxed:sum'], ['invoice_date:month'], lazy=False):
k = g.get('invoice_date:month')
out[str(k)] = {'value': g.get('amount_untaxed') or 0.0, 'n': g.get('__count') or 0}
return out
ref_m, inv_m = _monthly('out_refund'), _monthly('out_invoice')
months = sorted(set(ref_m) | set(inv_m),
key=lambda m: dt.datetime.strptime(m, '%B %Y'))
monthly = []
for m in months:
r, i = ref_m.get(m, {'value': 0, 'n': 0}), inv_m.get(m, {'value': 0, 'n': 0})
monthly.append({'month': m, 'refund_value': r['value'], 'n_refunds': r['n'],
'invoice_value': i['value'], 'n_invoices': i['n'],
'rate_pct': (r['value'] / i['value'] * 100) if i['value'] else None})
# ---- by customer (moves, 12m) ----------------------------------------------------------
def _by_partner(mt):
out = {}
for g in O.read_group('account.move', _mdom(mt, d12, ti),
['amount_untaxed:sum'], ['partner_id'], lazy=False):
pid = O.m2o_id(g.get('partner_id'))
if pid:
out[pid] = {'name': O.m2o_name(g.get('partner_id')),
'value': g.get('amount_untaxed') or 0.0, 'n': g.get('__count') or 0}
return out
ref_c, inv_c = _by_partner('out_refund'), _by_partner('out_invoice')
by_customer = []
for pid, r in ref_c.items():
inv = inv_c.get(pid, {'value': 0.0, 'n': 0})
by_customer.append({'pid': pid, 'customer': r['name'], 'ret_value': r['value'],
'n_refunds': r['n'], 'invoiced': inv['value'],
'rate_pct': (r['value'] / inv['value'] * 100) if inv['value'] else None})
by_customer.sort(key=lambda x: -x['ret_value'])
# ---- by SKU (refund LINES vs invoice LINES, 12m) ----------------------------------------
def _by_product(mt):
out = {}
for g in O.read_group('account.move.line', _ldom(mt, d12, ti),
['price_subtotal:sum', 'quantity:sum'], ['product_id'], lazy=False):
pid = O.m2o_id(g.get('product_id'))
if pid:
out[pid] = {'value': g.get('price_subtotal') or 0.0,
'qty': g.get('quantity') or 0.0}
return out
ref_p, inv_p = _by_product('out_refund'), _by_product('out_invoice')
# meta for the UNION of refunded + sold products (category/supplier denominators need the
# invoice side too)
all_pids = list(set(ref_p) | set(inv_p))
meta = {}
for i in range(0, len(all_pids), 5000):
for p in O.search_read('product.product',
[('id', 'in', all_pids[i:i + 5000]),
('active', 'in', [True, False])],
['default_code', 'name', 'categ_id']):
meta[p['id']] = p
by_sku = []
for pid, r in ref_p.items():
inv = inv_p.get(pid, {'value': 0.0, 'qty': 0.0})
m = meta.get(pid, {})
by_sku.append({'pid': pid, 'code': (m.get('default_code') or '').strip() or f'#{pid}',
'product': m.get('name') or '',
'ret_value': r['value'], 'ret_units': r['qty'],
'sold_value': inv['value'], 'sold_units': inv['qty'],
'rate_pct': (r['value'] / inv['value'] * 100) if inv['value'] else None})
by_sku.sort(key=lambda x: -x['ret_value'])
# ---- by CATEGORY (product-line signal: which kinds of products come back) ---------------
def _cat_of(pid):
return O.m2o_name((meta.get(pid) or {}).get('categ_id')) or '(none)'
cat = {}
for pid, r in ref_p.items():
e = cat.setdefault(_cat_of(pid), {'ret_value': 0.0, 'ret_units': 0.0,
'sold_value': 0.0, 'n_skus': 0})
e['ret_value'] += r['value']
e['ret_units'] += r['qty']
e['n_skus'] += 1
for pid, r in inv_p.items():
e = cat.setdefault(_cat_of(pid), {'ret_value': 0.0, 'ret_units': 0.0,
'sold_value': 0.0, 'n_skus': 0})
e['sold_value'] += r['value']
by_category = [{'category': k, **v,
'rate_pct': (v['ret_value'] / v['sold_value'] * 100)
if v['sold_value'] else None}
for k, v in cat.items() if v['ret_value'] > 0]
by_category.sort(key=lambda x: -x['ret_value'])
# ---- by SUPPLIER (sourcing-quality signal) ----------------------------------------------
# dominant vendor per product from confirmed PO history (most units bought), one grouped read
po_vendor, _best_q = {}, {}
try:
for g in O.read_group('purchase.order.line',
[('order_id.state', 'in', ('purchase', 'done')),
('product_id', '!=', False)],
['product_qty:sum'], ['product_id', 'partner_id'], lazy=False):
pid = O.m2o_id(g.get('product_id'))
q = g.get('product_qty') or 0.0
v = O.m2o_name(g.get('partner_id'))
if pid and v and q > _best_q.get(pid, 0.0):
_best_q[pid] = q
po_vendor[pid] = v
except Exception:
pass
sup_map = proc_mod.suppliers()
def _vendor_of(pid):
code = ((meta.get(pid) or {}).get('default_code') or '').strip()
cur = sup_map.get(code) or {}
return (cur.get('vendor') or '').strip() or po_vendor.get(pid) or '(no supplier data)'
sup = {}
for pid, r in ref_p.items():
e = sup.setdefault(_vendor_of(pid), {'ret_value': 0.0, 'ret_units': 0.0,
'sold_value': 0.0, 'n_skus': 0})
e['ret_value'] += r['value']
e['ret_units'] += r['qty']
e['n_skus'] += 1
for pid, r in inv_p.items():
e = sup.setdefault(_vendor_of(pid), {'ret_value': 0.0, 'ret_units': 0.0,
'sold_value': 0.0, 'n_skus': 0})
e['sold_value'] += r['value']
by_supplier = [{'supplier': k, **v,
'rate_pct': (v['ret_value'] / v['sold_value'] * 100)
if v['sold_value'] else None}
for k, v in sup.items() if v['ret_value'] > 0]
by_supplier.sort(key=lambda x: -x['ret_value'])
# ---- by AGENT (book-behavior signal; agent = the customer's res.partner agent, NOT the
# credit-note team_id). Denominator = the agent's WHOLE invoiced book, not just refunders.
attrs = cust_mod._partner_attrs(list(set(ref_c) | set(inv_c)))
def _agent_of(pid):
return (attrs.get(pid) or {}).get('agent') or '(none)'
ag = {}
for pid, r in ref_c.items():
e = ag.setdefault(_agent_of(pid), {'ret_value': 0.0, 'n_refunds': 0, 'invoiced': 0.0,
'top_customer': '', 'top_value': 0.0, 'top_pid': None})
e['ret_value'] += r['value']
e['n_refunds'] += r['n']
if r['value'] > e['top_value']:
e['top_value'] = r['value']
e['top_customer'] = r['name']
e['top_pid'] = pid
for pid, r in inv_c.items():
e = ag.setdefault(_agent_of(pid), {'ret_value': 0.0, 'n_refunds': 0, 'invoiced': 0.0,
'top_customer': '', 'top_value': 0.0, 'top_pid': None})
e['invoiced'] += r['value']
by_agent = [{'agent': k, **v,
'rate_pct': (v['ret_value'] / v['invoiced'] * 100) if v['invoiced'] else None}
for k, v in ag.items() if v['ret_value'] > 0]
by_agent.sort(key=lambda x: -x['ret_value'])
# ---- headline ---------------------------------------------------------------------------
n_ref = sum(r['n'] for r in ref_c.values())
ref_val = sum(r['value'] for r in ref_c.values())
n_inv = sum(r['n'] for r in inv_c.values())
inv_val = sum(r['value'] for r in inv_c.values())
top10 = sum(r['ret_value'] for r in by_sku[:10])
return {'monthly': monthly, 'by_customer': by_customer, 'by_sku': by_sku,
'by_category': by_category, 'by_supplier': by_supplier, 'by_agent': by_agent,
'n_refunds': n_ref, 'refund_value': ref_val,
'n_invoices': n_inv, 'invoice_value': inv_val,
'doc_rate_pct': (n_ref / n_inv * 100) if n_inv else None,
'value_rate_pct': (ref_val / inv_val * 100) if inv_val else None,
'top10_share_pct': (top10 / ref_val * 100) if ref_val else None,
'window': (d12, ti)}
def validate(t=None, team_id=None, pre=None):
t = t or P.today()
b = pre or build(t)
d12, ti = b['window']
checks = []
srv_val = O.sum_field('account.move', _mdom('out_refund', d12, ti), 'amount_untaxed')
a = sum(r['ret_value'] for r in b['by_customer'])
checks.append({'check': 'Returns: Σ(per-customer refunds) == server Σ(credit-note untaxed)',
'a': round(a, 2), 'b': round(srv_val, 2), 'gap': round(a - srv_val, 2),
'ok': abs(a - srv_val) <= max(1.0, abs(srv_val) * 0.001)})
srv_line = O.sum_field('account.move.line', _ldom('out_refund', d12, ti), 'price_subtotal')
a2 = sum(r['ret_value'] for r in b['by_sku'])
checks.append({'check': 'Returns: Σ(per-SKU refund lines) == server Σ(refund product lines)',
'a': round(a2, 2), 'b': round(srv_line, 2), 'gap': round(a2 - srv_line, 2),
'ok': abs(a2 - srv_line) <= max(1.0, abs(srv_line) * 0.001)})
# the three new rollups are re-groupings of the SAME universes — they must tie exactly
for key, base, label in (('by_category', a2, 'per-SKU lines'),
('by_supplier', a2, 'per-SKU lines'),
('by_agent', sum(r['ret_value'] for r in b['by_customer']),
'per-customer refunds')):
s = sum(r['ret_value'] for r in b[key])
checks.append({'check': f'Returns: Σ({key}) == Σ({label})',
'a': round(s, 2), 'b': round(base, 2), 'gap': round(s - base, 2),
'ok': abs(s - base) <= 1.0})
return checks
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