Aissa
5d60d33db1
Volledige Foodlinkk Command Center uitbreiding met social automatisering, reclamefolder filters, Proxmox monitoring en documentatie.
105 lines
4.1 KiB
Python
105 lines
4.1 KiB
Python
"""Market trends feed for kant-en-klaar / halal ready meals."""
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from __future__ import annotations
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from typing import Any
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from app.db import execute_returning, fetch_all, json_param
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TREND_SEEDS = [
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{
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"category": "kant-en-klaar",
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"trend_name": "Halal ready-meals groei stedelijk",
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"description": "Stedelijke gebieden met hoge niet-westerse bevolking tonen vraag naar halal kant-en-klaar zonder voldoende schap-aanbod.",
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"source": "CBS + retail intelligence",
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"confidence_score": 0.82,
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"opportunity_score": 0.88,
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"related_products": ["halal maaltijden", "microwave meals", "salades"],
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"action_items": ["Target Plus/Jumbo regio's met halal-gap score >60", "Pilot schap bij 3 filialen"],
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},
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{
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"category": "halal",
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"trend_name": "Certificering als vertrouwen-driver",
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"description": "Filialen met halal-certificering maar beperkt ready-meal assortiment = upsell kans voor Foodlinkk.",
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"source": "halal_registry + CRM",
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"confidence_score": 0.75,
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"opportunity_score": 0.80,
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"related_products": ["HQC gecertificeerde maaltijden"],
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"action_items": ["Match HQC stores met CRM pipeline", "Cross-sell bestaande klanten"],
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},
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{
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"category": "kant-en-klaar",
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"trend_name": "Convenience trend post-COVID",
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"description": "Gemiddeld inkomen en eenpersoonshuishoudens correleren met groei kant-en-klaar segment.",
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"source": "CBS kerncijfers",
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"confidence_score": 0.70,
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"opportunity_score": 0.72,
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"related_products": ["single-serve", "meal kits"],
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"action_items": ["Filter winkels op huishoudens + inkomen >€35k"],
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},
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]
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def refresh_trends_from_social() -> dict[str, Any]:
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"""Derive trend signals from social mentions keywords."""
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mentions = fetch_all(
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"""SELECT platform, text, sentiment_score, created_at FROM social_mentions
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WHERE created_at > NOW() - interval '30 days'
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ORDER BY created_at DESC LIMIT 100"""
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)
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keywords = {
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"halal": 0, "kant-en-klaar": 0, "ready meal": 0, "meal prep": 0,
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"supermarkt": 0, "schap": 0, "afhalen": 0,
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}
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for m in mentions:
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text = (m.get("text") or "").lower()
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for kw in keywords:
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if kw in text:
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keywords[kw] += 1
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created = 0
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for kw, count in keywords.items():
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if count < 1:
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continue
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execute_returning(
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"""INSERT INTO market_trends (category, trend_name, description, source,
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confidence_score, opportunity_score, related_products, data_source)
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VALUES (%s, %s, %s, 'social_mentions', %s, %s, %s, 'live_feed')
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RETURNING id""",
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(
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"kant-en-klaar" if "meal" in kw or "kant" in kw else "halal",
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f"Social buzz: {kw} ({count} mentions)",
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f"{count} vermeldingen afgelopen 30 dagen rond '{kw}'.",
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min(0.95, 0.5 + count * 0.05),
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min(0.95, 0.4 + count * 0.06),
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[kw],
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),
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)
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created += 1
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for seed in TREND_SEEDS:
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exists = fetch_all(
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"SELECT id FROM market_trends WHERE trend_name = %s LIMIT 1",
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(seed["trend_name"],),
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)
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if not exists:
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execute_returning(
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"""INSERT INTO market_trends (category, trend_name, description, source,
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confidence_score, opportunity_score, related_products, action_items, data_source)
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VALUES (%s,%s,%s,%s,%s,%s,%s,%s,'seed') RETURNING id""",
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(
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seed["category"], seed["trend_name"], seed["description"], seed["source"],
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seed["confidence_score"], seed["opportunity_score"],
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seed["related_products"], seed["action_items"],
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),
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)
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created += 1
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return {"trends_created": created, "keyword_hits": keywords}
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def list_live_trends(limit: int = 20) -> list[dict[str, Any]]:
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return fetch_all(
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"""SELECT * FROM market_trends ORDER BY updated_at DESC NULLS LAST, created_at DESC LIMIT %s""",
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(limit,),
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)
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