mirror of
https://github.com/nethunterzist/trendyol-analiz
synced 2026-07-01 09:27:03 +00:00
c7be57064b
- FastAPI backend with Python - React + Vite admin panel - PostgreSQL database - Trendyol marketplace analytics - GitHub Actions CI/CD workflow Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
314 lines
13 KiB
Python
314 lines
13 KiB
Python
"""
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Hidden Champion Finder - Gizli şampiyon bulucu
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Özelleştirilmiş filtreler ile fırsat ürünlerini bulur
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"""
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from typing import Dict, List, Any, Optional
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from collections import defaultdict
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from .metrics import (
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get_rating_value,
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get_review_count,
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calculate_potential_score
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)
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class HiddenChampionFinder:
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"""
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Gizli şampiyonları bulan sınıf
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Parçalı pazarlarda (düşük HHI) özelleştirilmiş filtreler kullanır
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"""
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def find(
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self,
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products: List[Dict],
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social_data: Dict,
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filters: Optional[Dict] = None
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) -> Dict[str, Any]:
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"""
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Gizli şampiyonları bul (async)
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Özelleştirilmiş Filtreler:
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- Rating >= 4.6 (yüksek kalite)
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- Review count < 30 (henüz keşfedilmemiş)
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- Social proof (views/baskets) kategorinin 2 katı üzerinde
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Args:
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products: Ürün listesi
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social_data: Sosyal kanıt verileri
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filters: Filtreleme kriterleri
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Returns:
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Gizli şampiyon listesi
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"""
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if filters is None:
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filters = {
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"min_rating": 4.6,
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"max_review_count": 30,
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"social_multiplier": 2.0, # Kategori ortalamasının 2 katı
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"min_score": 70,
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"limit": 50
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}
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# Kategori bazlı ürün sayıları (competition level için)
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category_counts = defaultdict(int)
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category_products = defaultdict(list)
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for p in products:
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category = p.get("category", {}).get("name", "Unknown")
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if isinstance(category, dict):
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category = category.get("name", "Unknown")
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category_counts[category] += 1
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category_products[category].append(p)
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# Kategori bazlı ortalama social proof hesapla
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category_avg_social = {}
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social_details = social_data.get("details", {})
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for category, cat_products in category_products.items():
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total_views = 0
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total_baskets = 0
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count = 0
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for product in cat_products:
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pid = str(product.get("id"))
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if pid in social_details:
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views = social_details[pid].get("page_views", 0) or 0
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baskets = social_details[pid].get("baskets", 0) or 0
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if views > 0:
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total_views += views
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total_baskets += baskets
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count += 1
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if count > 0:
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category_avg_social[category] = {
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"avg_views": total_views / count,
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"avg_baskets": total_baskets / count
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}
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else:
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category_avg_social[category] = {
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"avg_views": 0,
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"avg_baskets": 0
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}
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hidden_champions = []
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for product in products:
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# Temel veriler
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rating = get_rating_value(product)
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review_count = get_review_count(product)
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pid = str(product.get("id"))
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social = social_details.get(pid, {})
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page_views = social.get("page_views", 0) or 0
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orders = social.get("orders", 0) or 0
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baskets = social.get("baskets", 0) or 0
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favorites = social.get("favorites", 0) or 0
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conversion_rate = (orders / page_views * 100) if page_views > 0 else 0
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# Kategori bilgisi
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category = product.get("category", {})
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if isinstance(category, dict):
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category_name = category.get("name", "Unknown")
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else:
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category_name = category if category else "Unknown"
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# Competition level
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category_count = category_counts.get(category_name, 0)
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if category_count < 100:
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competition_level = "low"
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elif category_count < 500:
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competition_level = "medium"
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else:
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competition_level = "high"
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# Kategori ortalaması ile karşılaştır
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cat_avg = category_avg_social.get(category_name, {"avg_views": 0, "avg_baskets": 0})
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threshold_views = cat_avg["avg_views"] * filters.get("social_multiplier", 2.0)
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threshold_baskets = cat_avg["avg_baskets"] * filters.get("social_multiplier", 2.0)
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# Eğer kategori ortalaması 0 veya çok düşükse, minimum threshold kullan
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min_views_threshold = 100 # Minimum görüntülenme
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min_baskets_threshold = 5 # Minimum sepet
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# Threshold'ları ayarla
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if threshold_views < min_views_threshold:
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threshold_views = min_views_threshold
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if threshold_baskets < min_baskets_threshold:
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threshold_baskets = min_baskets_threshold
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# Minimum Orders kontrolü (satış verisi çok önemli)
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min_orders = filters.get("min_orders", 1) # Varsayılan: en az 1 satış
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# Özelleştirilmiş Filtreleme (daha esnek)
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passes_filter = (
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rating >= filters.get("min_rating", 4.6) and
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review_count < filters.get("max_review_count", 30) and
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review_count >= 1 and # En az 1 yorum olmalı
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orders >= min_orders and # EN AZ 1 SATIŞ OLMALI (satış verisi çok önemli)
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(page_views >= threshold_views or page_views >= min_views_threshold) and # Kategori ortalamasının üzerinde VEYA minimum threshold
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(baskets >= threshold_baskets or baskets >= min_baskets_threshold) and # Sepet de kategori ortalamasının üzerinde VEYA minimum
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(conversion_rate >= 1.0 or page_views >= 500) # Minimum %1 conversion VEYA yüksek görüntülenme
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)
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if passes_filter:
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# Potential score hesapla
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potential_score = calculate_potential_score(
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page_views, orders, review_count, conversion_rate, competition_level
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)
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# Hidden champion score hesapla
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hidden_champion_score = self._calculate_hidden_champion_score(
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rating, potential_score, conversion_rate, competition_level,
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page_views, threshold_views, baskets, threshold_baskets
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)
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# Min score kontrolü
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if hidden_champion_score >= filters.get("min_score", 70):
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# Trendyol linki oluştur
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product_url = product.get("url", "")
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if product_url:
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# URL relative ise (örn: /kumtel/urun-p-123), başına domain ekle
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if product_url.startswith("/"):
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product_url = f"https://www.trendyol.com{product_url}"
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elif not product_url.startswith("http"):
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product_url = f"https://www.trendyol.com{product_url}"
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elif product.get("id"):
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# Eğer url yoksa, product_id'den oluştur
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product_url = f"https://www.trendyol.com/urun/{product.get('id')}"
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else:
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product_url = ""
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# Görsel URL'i al (imageUrl veya images array'inden ilk eleman)
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image_url = product.get("imageUrl", "")
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if not image_url:
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# images array'inden ilk elemanı al
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images = product.get("images", [])
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if images and len(images) > 0:
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image_url = images[0] if isinstance(images[0], str) else str(images[0])
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# Eğer hala boşsa, boş string olarak bırak
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if not image_url:
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image_url = ""
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hidden_champions.append({
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"product_id": product.get("id"),
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"name": product.get("name", ""),
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"brand": product.get("brand", {}).get("name", "Unknown"),
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"category": category_name,
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"rating": round(rating, 2),
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"review_count": review_count,
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"price": product.get("price", {}).get("sellingPrice", 0),
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"page_views": page_views,
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"orders": orders,
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"baskets": baskets,
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"favorites": favorites,
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"conversion_rate": round(conversion_rate, 2),
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"competition_level": competition_level,
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"potential_score": potential_score,
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"hidden_champion_score": hidden_champion_score,
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"image": image_url, # Sosyal kanıt sekmesiyle uyumlu olması için "image" kullan
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"image_url": image_url, # Geriye dönük uyumluluk için
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"url": product_url, # Sosyal kanıt sekmesiyle uyumlu olması için "url" kullan
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"product_url": product_url, # Geriye dönük uyumluluk için
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"social_performance": {
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"views_vs_category_avg": round((page_views / cat_avg["avg_views"]) if cat_avg["avg_views"] > 0 else 0, 2),
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"baskets_vs_category_avg": round((baskets / cat_avg["avg_baskets"]) if cat_avg["avg_baskets"] > 0 else 0, 2),
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"category_avg_views": round(cat_avg["avg_views"], 0),
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"category_avg_baskets": round(cat_avg["avg_baskets"], 0)
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}
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})
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# Skora göre sırala
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hidden_champions.sort(key=lambda x: x["hidden_champion_score"], reverse=True)
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# Limit
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result = hidden_champions[:filters.get("limit", 50)]
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return {
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"total_found": len(hidden_champions),
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"hidden_champions": result,
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"summary": {
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"avg_score": round(sum(hc["hidden_champion_score"] for hc in result) / len(result), 2) if result else 0,
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"avg_rating": round(sum(hc["rating"] for hc in result) / len(result), 2) if result else 0,
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"avg_conversion": round(sum(hc["conversion_rate"] for hc in result) / len(result), 2) if result else 0,
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"low_competition_count": len([hc for hc in result if hc["competition_level"] == "low"]),
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"avg_social_performance": round(
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sum(hc["social_performance"]["views_vs_category_avg"] for hc in result) / len(result), 2
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) if result else 0
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},
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"filters_applied": filters
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}
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def _calculate_hidden_champion_score(
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self,
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rating: float,
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potential_score: float,
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conversion_rate: float,
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competition_level: str,
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page_views: int,
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threshold_views: float,
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baskets: int,
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threshold_baskets: float
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) -> float:
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"""
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Gizli şampiyon skoru hesapla (özelleştirilmiş)
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Formül:
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- Rating skoru: 30 puan (4.6+ = 30, 4.8+ = 35)
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- Potential score: 25 puan
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- Conversion rate: 20 puan
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- Social performance bonus: 15 puan (kategori ortalamasının üzerinde)
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- Competition level: 10 puan
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"""
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score = 0
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# 1. Rating skoru (30 puan)
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if rating >= 4.8:
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score += 35
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elif rating >= 4.6:
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score += 30
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elif rating >= 4.5:
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score += 25
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elif rating >= 4.0:
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score += 15
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else:
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score += 0
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# 2. Potansiyel skoru (25 puan)
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score += (potential_score / 100) * 25
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# 3. Conversion rate skoru (20 puan)
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if conversion_rate >= 5:
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score += 20
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elif conversion_rate >= 3:
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score += 15
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elif conversion_rate >= 2:
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score += 10
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else:
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score += 5
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# 4. Social performance bonus (15 puan)
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# Kategori ortalamasının ne kadar üzerinde?
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views_multiplier = (page_views / threshold_views) if threshold_views > 0 else 0
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baskets_multiplier = (baskets / threshold_baskets) if threshold_baskets > 0 else 0
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avg_multiplier = (views_multiplier + baskets_multiplier) / 2
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if avg_multiplier >= 3.0:
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score += 15 # Kategori ortalamasının 3+ katı
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elif avg_multiplier >= 2.5:
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score += 12
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elif avg_multiplier >= 2.0:
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score += 10
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else:
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score += 5
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# 5. Rekabet seviyesi skoru (10 puan)
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if competition_level == "low":
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score += 10
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elif competition_level == "medium":
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score += 7
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else:
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score += 3
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return min(100, round(score, 2))
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