71 lines
2.3 KiB
Python
71 lines
2.3 KiB
Python
"""Supplier scoring.
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Weighted score (0-100):
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40% price — cheaper supplier cost vs. the eligible pool
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20% inventory — stock sufficiency for the requested qty
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15% speed — shipping_time ('3-5 days' -> avg days)
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10% fulfillment — supplier_performance.fulfillment_rate
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10% returns — inverse of supplier_performance.return_rate
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5% history — reliability_score blended with stock_accuracy
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"""
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import re
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def _num(value, default=0.0):
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try:
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return float(value or 0)
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except (TypeError, ValueError):
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return default
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def _shipping_days(sp):
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text = (sp.shipping_time or "").strip()
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numbers = re.findall(r"\d+", text)
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if not numbers:
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return 5.0
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return float(sum(int(n) for n in numbers)) / len(numbers)
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def score_supplier(db, supplier, sp, qty, price_pool=None):
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perf = supplier.performance
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# 1) price (40%) — cheaper than pool average is better
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cost = _num(sp.supplier_cost)
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if price_pool and price_pool.get("avg_cost"):
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avg = price_pool["avg_cost"]
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price_score = max(0.0, 100.0 - (cost / avg - 1.0) * 100.0)
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else:
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price_score = 50.0
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# 2) inventory (20%) — can we fill the quantity?
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inventory = int(sp.supplier_inventory or 0)
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inv_score = 100.0 if inventory >= qty else max(0.0, (inventory / qty) * 100.0)
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# 3) speed (15%) — fewer shipping days is better
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days = _shipping_days(sp)
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speed_score = max(0.0, 100.0 - days * 12.0)
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# 4) fulfillment (10%)
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fulfillment = 100.0 if perf is None else _num(perf.fulfillment_rate, 100.0)
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# 5) returns (10%) — 0% returns = 100 points, 20% returns = 0 points
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return_rate = 0.0 if perf is None else _num(perf.return_rate, 0.0)
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returns_score = max(0.0, 100.0 - return_rate * 5.0)
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# 6) history (5%) — reliability blended with stock accuracy
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reliability = _num(supplier.reliability_score, 50.0)
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if perf is None:
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history_score = reliability
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else:
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history_score = 0.5 * reliability + 0.5 * _num(perf.stock_accuracy, 100.0)
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total = (
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0.40 * price_score
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+ 0.20 * inv_score
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+ 0.15 * speed_score
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+ 0.10 * fulfillment
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+ 0.10 * returns_score
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+ 0.05 * history_score
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)
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return round(min(100.0, max(0.0, total)), 2)
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