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trendyol-analiz/backend/main.py
furkanyigit34 982ad96f3f feat: /api/product/lookup endpoint eklendi 
Ne yaptık:
- product_lookup_cache (BoundedCache 500 item, 1h TTL) eklendi
- IP rate limiter: 10 istek/IP/dakika
- _TRENDYOL_URL_RE regex ile URL'den ürün ID'si çekme
- GET /api/product/lookup endpoint: orderCount/favoriteCount/pageViewCount/basketCount döner
- Circuit breaker ve cache entegrasyonu

Neden yaptık:
- "Ne Kadar Sattı?" sayfası için gerekli Python servisi altyapısı.
  Kullanıcı Trendyol URL'si yapıştırıyor, sosyal kanıt verisi alıyor.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 12:35:45 +03:00

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"""
FastAPI Backend for Trendyol Admin Panel
"""
from fastapi import FastAPI, HTTPException, Depends, BackgroundTasks, Request, Security
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import StreamingResponse
from fastapi.security import APIKeyHeader
import asyncio
import json as json_module
from sqlalchemy.orm import Session
from sqlalchemy import func
from typing import List, Optional
from pydantic import BaseModel
from datetime import datetime
import uuid
from functools import lru_cache
import numpy as np
import random
import requests
import time
import re
from collections import OrderedDict
from threading import Lock
import os
from database import SessionLocal, Category, Snapshot, Report, EnrichmentError, ReportQueue, init_db
from google_trends_helper import estimate_traffic_sources, fetch_google_trends
from logging_config import setup_logging, get_logger, set_correlation_id, set_report_id, log_timing
# Initialize logging first, then database
setup_logging()
log_http = get_logger("http")
log_scraper = get_logger("scraper")
log_social = get_logger("social")
log_cache = get_logger("cache")
log_db = get_logger("db")
log_sse = get_logger("sse")
log_api = get_logger("api")
log_keywords = get_logger("keywords")
init_db()
# ============================================================================
# API KEY AUTHENTICATION
# ============================================================================
API_KEY = os.getenv("API_KEY")
if not API_KEY:
import warnings
warnings.warn("API_KEY env var not set! API authentication disabled in development.")
API_KEY_HEADER = APIKeyHeader(name="X-API-Key", auto_error=False)
# Paths that do not require API key authentication
PUBLIC_PATHS = {"/health"}
async def verify_api_key(request: Request, api_key: Optional[str] = Security(API_KEY_HEADER)):
"""
Global dependency that validates X-API-Key header.
Skips authentication for public paths (health check, docs).
"""
if request.url.path in PUBLIC_PATHS:
return
if not API_KEY:
# API_KEY env var not set — authentication disabled
return
if not api_key or api_key != API_KEY:
raise HTTPException(
status_code=401,
detail="Invalid or missing API key"
)
# GS1 Barcode Prefix to Country Mapping (EAN-13 / EAN-8)
# Source: https://www.gs1.org/standards/id-keys/company-prefix
BARCODE_PREFIX_TO_COUNTRY = {
# Turkey
"869": "Türkiye",
# Europe
"300": "Fransa", "301": "Fransa", "302": "Fransa", "303": "Fransa", "304": "Fransa",
"305": "Fransa", "306": "Fransa", "307": "Fransa", "308": "Fransa", "309": "Fransa",
"310": "Fransa", "311": "Fransa", "312": "Fransa", "313": "Fransa", "314": "Fransa",
"315": "Fransa", "316": "Fransa", "317": "Fransa", "318": "Fransa", "319": "Fransa",
"320": "Fransa", "321": "Fransa", "322": "Fransa", "323": "Fransa", "324": "Fransa",
"325": "Fransa", "326": "Fransa", "327": "Fransa", "328": "Fransa", "329": "Fransa",
"330": "Fransa", "331": "Fransa", "332": "Fransa", "333": "Fransa", "334": "Fransa",
"335": "Fransa", "336": "Fransa", "337": "Fransa", "338": "Fransa", "339": "Fransa",
"340": "Fransa", "341": "Fransa", "342": "Fransa", "343": "Fransa", "344": "Fransa",
"345": "Fransa", "346": "Fransa", "347": "Fransa", "348": "Fransa", "349": "Fransa",
"350": "Fransa", "351": "Fransa", "352": "Fransa", "353": "Fransa", "354": "Fransa",
"355": "Fransa", "356": "Fransa", "357": "Fransa", "358": "Fransa", "359": "Fransa",
"360": "Fransa", "361": "Fransa", "362": "Fransa", "363": "Fransa", "364": "Fransa",
"365": "Fransa", "366": "Fransa", "367": "Fransa", "368": "Fransa", "369": "Fransa",
"370": "Fransa", "371": "Fransa", "372": "Fransa", "373": "Fransa", "374": "Fransa",
"375": "Fransa", "376": "Fransa", "377": "Fransa", "378": "Fransa", "379": "Fransa",
"380": "Bulgaristan",
"383": "Slovenya",
"385": "Hırvatistan",
"387": "Bosna Hersek",
"389": "Karadağ",
"400": "Almanya", "401": "Almanya", "402": "Almanya", "403": "Almanya", "404": "Almanya",
"405": "Almanya", "406": "Almanya", "407": "Almanya", "408": "Almanya", "409": "Almanya",
"410": "Almanya", "411": "Almanya", "412": "Almanya", "413": "Almanya", "414": "Almanya",
"415": "Almanya", "416": "Almanya", "417": "Almanya", "418": "Almanya", "419": "Almanya",
"420": "Almanya", "421": "Almanya", "422": "Almanya", "423": "Almanya", "424": "Almanya",
"425": "Almanya", "426": "Almanya", "427": "Almanya", "428": "Almanya", "429": "Almanya",
"430": "Almanya", "431": "Almanya", "432": "Almanya", "433": "Almanya", "434": "Almanya",
"435": "Almanya", "436": "Almanya", "437": "Almanya", "438": "Almanya", "439": "Almanya",
"440": "Almanya",
"450": "Japonya", "451": "Japonya", "452": "Japonya", "453": "Japonya", "454": "Japonya",
"455": "Japonya", "456": "Japonya", "457": "Japonya", "458": "Japonya", "459": "Japonya",
"460": "Rusya", "461": "Rusya", "462": "Rusya", "463": "Rusya", "464": "Rusya",
"465": "Rusya", "466": "Rusya", "467": "Rusya", "468": "Rusya", "469": "Rusya",
"470": "Kırgızistan",
"471": "Tayvan",
"474": "Estonya",
"475": "Letonya",
"476": "Azerbaycan",
"477": "Litvanya",
"478": "Özbekistan",
"479": "Sri Lanka",
"480": "Filipinler",
"481": "Belarus",
"482": "Ukrayna",
"483": "Türkmenistan",
"484": "Moldova",
"485": "Ermenistan",
"486": "Gürcistan",
"487": "Kazakistan",
"488": "Tacikistan",
"489": "Hong Kong",
"490": "Japonya", "491": "Japonya", "492": "Japonya", "493": "Japonya", "494": "Japonya",
"495": "Japonya", "496": "Japonya", "497": "Japonya", "498": "Japonya", "499": "Japonya",
# Asia Pacific
"500": "İngiltere", "501": "İngiltere", "502": "İngiltere", "503": "İngiltere", "504": "İngiltere",
"505": "İngiltere", "506": "İngiltere", "507": "İngiltere", "508": "İngiltere", "509": "İngiltere",
"520": "Yunanistan", "521": "Yunanistan",
"528": "Lübnan",
"529": "Kıbrıs",
"530": "Arnavutluk",
"531": "Makedonya",
"535": "Malta",
"539": "İrlanda",
"540": "Belçika", "541": "Belçika", "542": "Belçika", "543": "Belçika", "544": "Belçika",
"545": "Belçika", "546": "Belçika",
"560": "Portekiz",
"569": "İzlanda",
"570": "Danimarka", "571": "Danimarka", "572": "Danimarka", "573": "Danimarka", "574": "Danimarka",
"575": "Danimarka", "576": "Danimarka", "577": "Danimarka", "578": "Danimarka", "579": "Danimarka",
"590": "Polonya",
"594": "Romanya",
"599": "Macaristan",
"600": "Güney Afrika", "601": "Güney Afrika",
"603": "Gana",
"604": "Senegal",
"608": "Bahreyn",
"609": "Moritanya",
"611": "Fas",
"613": "Cezayir",
"615": "Nijerya",
"616": "Kenya",
"618": "Fildişi Sahili",
"619": "Tunus",
"620": "Tanzanya",
"621": "Suriye",
"622": "Mısır",
"623": "Brunei",
"624": "Libya",
"625": "Ürdün",
"626": "İran",
"627": "Kuveyt",
"628": "Suudi Arabistan",
"629": "Birleşik Arap Emirlikleri",
"640": "Finlandiya", "641": "Finlandiya", "642": "Finlandiya", "643": "Finlandiya",
"644": "Finlandiya", "645": "Finlandiya", "646": "Finlandiya", "647": "Finlandiya",
"648": "Finlandiya", "649": "Finlandiya",
"690": "Çin", "691": "Çin", "692": "Çin", "693": "Çin", "694": "Çin",
"695": "Çin", "696": "Çin", "697": "Çin", "698": "Çin", "699": "Çin",
"700": "Norveç", "701": "Norveç", "702": "Norveç", "703": "Norveç", "704": "Norveç",
"705": "Norveç", "706": "Norveç", "707": "Norveç", "708": "Norveç", "709": "Norveç",
"729": "İsrail",
"730": "İsveç", "731": "İsveç", "732": "İsveç", "733": "İsveç", "734": "İsveç",
"735": "İsveç", "736": "İsveç", "737": "İsveç", "738": "İsveç", "739": "İsveç",
"740": "Guatemala",
"741": "El Salvador",
"742": "Honduras",
"743": "Nikaragua",
"744": "Kosta Rika",
"745": "Panama",
"746": "Dominik Cumhuriyeti",
"750": "Meksika",
"754": "Kanada", "755": "Kanada",
"759": "Venezuela",
"760": "İsviçre", "761": "İsviçre", "762": "İsviçre", "763": "İsviçre", "764": "İsviçre",
"765": "İsviçre", "766": "İsviçre", "767": "İsviçre", "768": "İsviçre", "769": "İsviçre",
"770": "Kolombiya", "771": "Kolombiya",
"773": "Uruguay",
"775": "Peru",
"777": "Bolivya",
"778": "Arjantin", "779": "Arjantin",
"780": "Şili",
"784": "Paraguay",
"786": "Ekvador",
"789": "Brezilya", "790": "Brezilya",
"800": "İtalya", "801": "İtalya", "802": "İtalya", "803": "İtalya", "804": "İtalya",
"805": "İtalya", "806": "İtalya", "807": "İtalya", "808": "İtalya", "809": "İtalya",
"810": "İtalya", "811": "İtalya", "812": "İtalya", "813": "İtalya", "814": "İtalya",
"815": "İtalya", "816": "İtalya", "817": "İtalya", "818": "İtalya", "819": "İtalya",
"820": "İtalya", "821": "İtalya", "822": "İtalya", "823": "İtalya", "824": "İtalya",
"825": "İtalya", "826": "İtalya", "827": "İtalya", "828": "İtalya", "829": "İtalya",
"830": "İtalya", "831": "İtalya", "832": "İtalya", "833": "İtalya", "834": "İtalya",
"835": "İtalya", "836": "İtalya", "837": "İtalya", "838": "İtalya", "839": "İtalya",
"840": "İspanya", "841": "İspanya", "842": "İspanya", "843": "İspanya", "844": "İspanya",
"845": "İspanya", "846": "İspanya", "847": "İspanya", "848": "İspanya", "849": "İspanya",
"850": "Küba",
"858": "Slovakya",
"859": "Çekya",
"860": "Sırbistan",
"865": "Moğolistan",
"867": "Kuzey Kore",
"868": "Türkiye",
"870": "Hollanda", "871": "Hollanda", "872": "Hollanda", "873": "Hollanda", "874": "Hollanda",
"875": "Hollanda", "876": "Hollanda", "877": "Hollanda", "878": "Hollanda", "879": "Hollanda",
"880": "Güney Kore",
"884": "Kamboçya",
"885": "Tayland",
"888": "Singapur",
"890": "Hindistan", "891": "Hindistan", "892": "Hindistan", "893": "Hindistan",
"894": "Hindistan", "895": "Hindistan", "896": "Hindistan", "897": "Hindistan",
"898": "Hindistan", "899": "Hindistan",
"900": "Avusturya", "901": "Avusturya", "902": "Avusturya", "903": "Avusturya",
"904": "Avusturya", "905": "Avusturya", "906": "Avusturya", "907": "Avusturya",
"908": "Avusturya", "909": "Avusturya",
"930": "Avustralya", "931": "Avustralya", "932": "Avustralya", "933": "Avustralya",
"934": "Avustralya", "935": "Avustralya", "936": "Avustralya", "937": "Avustralya",
"938": "Avustralya", "939": "Avustralya",
"940": "Yeni Zelanda", "941": "Yeni Zelanda", "942": "Yeni Zelanda", "943": "Yeni Zelanda",
"944": "Yeni Zelanda", "945": "Yeni Zelanda", "946": "Yeni Zelanda", "947": "Yeni Zelanda",
"948": "Yeni Zelanda", "949": "Yeni Zelanda",
"955": "Malezya",
"958": "Makao",
# North America
"000": "ABD/Kanada", "001": "ABD/Kanada", "002": "ABD/Kanada", "003": "ABD/Kanada",
"004": "ABD/Kanada", "005": "ABD/Kanada", "006": "ABD/Kanada", "007": "ABD/Kanada",
"008": "ABD/Kanada", "009": "ABD/Kanada", "010": "ABD/Kanada", "011": "ABD/Kanada",
"012": "ABD/Kanada", "013": "ABD/Kanada", "019": "ABD/Kanada",
"020": "ABD/Kanada", "021": "ABD/Kanada", "022": "ABD/Kanada", "023": "ABD/Kanada",
"024": "ABD/Kanada", "025": "ABD/Kanada", "026": "ABD/Kanada", "027": "ABD/Kanada",
"028": "ABD/Kanada", "029": "ABD/Kanada", "030": "ABD/Kanada", "031": "ABD/Kanada",
"032": "ABD/Kanada", "033": "ABD/Kanada", "034": "ABD/Kanada", "035": "ABD/Kanada",
"036": "ABD/Kanada", "037": "ABD/Kanada", "038": "ABD/Kanada", "039": "ABD/Kanada",
"040": "ABD/Kanada", "041": "ABD/Kanada", "042": "ABD/Kanada", "043": "ABD/Kanada",
"044": "ABD/Kanada", "045": "ABD/Kanada", "046": "ABD/Kanada", "047": "ABD/Kanada",
"048": "ABD/Kanada", "049": "ABD/Kanada", "050": "ABD/Kanada", "051": "ABD/Kanada",
"052": "ABD/Kanada", "053": "ABD/Kanada", "054": "ABD/Kanada", "055": "ABD/Kanada",
"056": "ABD/Kanada", "057": "ABD/Kanada", "058": "ABD/Kanada", "059": "ABD/Kanada",
"060": "ABD/Kanada", "061": "ABD/Kanada", "062": "ABD/Kanada", "063": "ABD/Kanada",
"064": "ABD/Kanada", "065": "ABD/Kanada", "066": "ABD/Kanada", "067": "ABD/Kanada",
"068": "ABD/Kanada", "069": "ABD/Kanada", "070": "ABD/Kanada", "071": "ABD/Kanada",
"072": "ABD/Kanada", "073": "ABD/Kanada", "074": "ABD/Kanada", "075": "ABD/Kanada",
"076": "ABD/Kanada", "077": "ABD/Kanada", "078": "ABD/Kanada", "079": "ABD/Kanada",
"080": "ABD/Kanada", "081": "ABD/Kanada", "082": "ABD/Kanada", "083": "ABD/Kanada",
"084": "ABD/Kanada", "085": "ABD/Kanada", "086": "ABD/Kanada", "087": "ABD/Kanada",
"088": "ABD/Kanada", "089": "ABD/Kanada", "090": "ABD/Kanada", "091": "ABD/Kanada",
"092": "ABD/Kanada", "093": "ABD/Kanada", "094": "ABD/Kanada", "095": "ABD/Kanada",
"096": "ABD/Kanada", "097": "ABD/Kanada", "098": "ABD/Kanada", "099": "ABD/Kanada",
"100": "ABD/Kanada", "101": "ABD/Kanada", "102": "ABD/Kanada", "103": "ABD/Kanada",
"104": "ABD/Kanada", "105": "ABD/Kanada", "106": "ABD/Kanada", "107": "ABD/Kanada",
"108": "ABD/Kanada", "109": "ABD/Kanada", "110": "ABD/Kanada", "111": "ABD/Kanada",
"112": "ABD/Kanada", "113": "ABD/Kanada", "114": "ABD/Kanada", "115": "ABD/Kanada",
"116": "ABD/Kanada", "117": "ABD/Kanada", "118": "ABD/Kanada", "119": "ABD/Kanada",
"120": "ABD/Kanada", "121": "ABD/Kanada", "122": "ABD/Kanada", "123": "ABD/Kanada",
"124": "ABD/Kanada", "125": "ABD/Kanada", "126": "ABD/Kanada", "127": "ABD/Kanada",
"128": "ABD/Kanada", "129": "ABD/Kanada", "130": "ABD/Kanada", "131": "ABD/Kanada",
"132": "ABD/Kanada", "133": "ABD/Kanada", "134": "ABD/Kanada", "135": "ABD/Kanada",
"136": "ABD/Kanada", "137": "ABD/Kanada", "138": "ABD/Kanada", "139": "ABD/Kanada",
}
def get_country_from_barcode(barcode: str) -> str:
"""
Extract country from barcode prefix (first 3 digits)
Returns country name or 'Bilinmeyen' if not found
"""
if not barcode or len(barcode) < 3:
return "Bilinmeyen"
prefix = barcode[:3]
return BARCODE_PREFIX_TO_COUNTRY.get(prefix, "Bilinmeyen")
app = FastAPI(
title="Trendyol Admin API",
version="1.0.0",
dependencies=[Depends(verify_api_key)]
)
# Base directory for resolving relative paths
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
# File paths - configurable via environment variables for Docker deployment
# Local development: uses relative paths from backend directory
# Docker: uses /data/* directories mounted as volumes
REPORTS_DIR = os.getenv("REPORTS_DIR", os.path.join(BASE_DIR, "..", "reports"))
CATEGORIES_DIR = os.getenv("CATEGORIES_DIR", os.path.join(BASE_DIR, "..", "categories"))
CATEGORY_TREE_PATH = os.getenv("CATEGORY_TREE_PATH", os.path.join(BASE_DIR, "..", "trendyol_category_tree.json"))
DATABASE_PATH = os.getenv("DATABASE_PATH", os.path.join(BASE_DIR, "trendyol.db"))
# CORS for React admin panel
# Security: Environment-based origin control
allowed_origins = []
if os.getenv("ENV", "development") == "production":
allowed_origins = [
"https://trendyol.194.187.253.230.sslip.io",
]
else:
allowed_origins = [
"http://localhost:5173",
"http://localhost:3000",
"http://127.0.0.1:5173",
]
app.add_middleware(
CORSMiddleware,
allow_origins=allowed_origins,
allow_credentials=True,
allow_methods=["GET", "POST", "PUT", "DELETE", "OPTIONS"],
allow_headers=["Content-Type", "Authorization"],
)
# ── Category Tree API (from JSON, no DB) ──────────────────────────────────────
_category_tree_cache = None
def _load_category_tree():
global _category_tree_cache
if _category_tree_cache is not None:
return _category_tree_cache
try:
with open(CATEGORY_TREE_PATH, 'r', encoding='utf-8') as f:
_category_tree_cache = json_module.load(f)
log_api.info(f"Category tree loaded: {len(_category_tree_cache)} categories")
except FileNotFoundError:
log_api.warning(f"Category tree file not found: {CATEGORY_TREE_PATH}")
_category_tree_cache = []
return _category_tree_cache
@app.get("/api/category-tree")
def get_category_tree():
"""Full flat category list from JSON (3971 items, ~800KB)"""
tree = _load_category_tree()
return tree
@app.get("/api/category-tree/roots")
def get_category_tree_roots():
"""Top-level categories only"""
tree = _load_category_tree()
return [c for c in tree if c.get("level") == 0]
@app.get("/api/category-tree/{category_id}/children")
def get_category_tree_children(category_id: int):
"""Direct children of a category"""
tree = _load_category_tree()
return [c for c in tree if c.get("parentId") == category_id]
@app.get("/api/category-tree/search")
def search_category_tree(q: str):
"""Search categories by name (min 2 chars)"""
if len(q) < 2:
return []
tree = _load_category_tree()
q_lower = q.lower()
results = [c for c in tree if q_lower in c.get("name", "").lower()]
return results[:50]
# Dependency to get DB session
def get_db():
db = SessionLocal()
try:
yield db
finally:
db.close()
# ============================================================================
# HEALTH CHECK ENDPOINT (Docker/Coolify)
# ============================================================================
@app.get("/health")
async def health_check():
"""
Health check endpoint for Docker HEALTHCHECK and Coolify monitoring.
Returns service status, database connectivity, and storage availability.
"""
try:
# Check database connection
db_path = os.getenv("DATABASE_PATH", os.path.join(BASE_DIR, "trendyol.db"))
db_exists = os.path.exists(db_path)
# Check data directories
categories_dir = CATEGORIES_DIR
reports_dir = os.getenv("REPORTS_DIR", REPORTS_DIR)
return {
"status": "healthy",
"timestamp": datetime.utcnow().isoformat(),
"database": {
"exists": db_exists,
"path": db_path
},
"storage": {
"categories": os.path.exists(categories_dir),
"reports": os.path.exists(reports_dir)
},
"version": "1.0.0"
}
except Exception as e:
raise HTTPException(
status_code=503,
detail=f"Health check failed: {str(e)}"
)
# ============================================================================
# TRENDYOL API HELPER FUNCTIONS
# ============================================================================
TRENDYOL_HEADERS = {
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36",
"Accept": "application/json",
"Referer": "https://www.trendyol.com/",
"Connection": "keep-alive"
}
# Bounded cache with TTL to prevent memory leaks
class BoundedCache:
"""Thread-safe cache with size limit and TTL"""
def __init__(self, maxsize=100, ttl=3600):
self.cache = OrderedDict()
self.maxsize = maxsize
self.ttl = ttl
self.lock = Lock()
self.timestamps = {}
def get(self, key):
with self.lock:
if key not in self.cache:
return None
# Check TTL
if time.time() - self.timestamps.get(key, 0) > self.ttl:
del self.cache[key]
del self.timestamps[key]
return None
# Move to end (LRU)
self.cache.move_to_end(key)
return self.cache[key]
def set(self, key, value):
with self.lock:
if key in self.cache:
self.cache.move_to_end(key)
self.cache[key] = value
self.timestamps[key] = time.time()
# Evict oldest if over limit
if len(self.cache) > self.maxsize:
oldest = next(iter(self.cache))
del self.cache[oldest]
del self.timestamps[oldest]
def __setitem__(self, key, value):
"""Support cache[key] = value syntax"""
self.set(key, value)
def __getitem__(self, key):
"""Support cache[key] syntax"""
result = self.get(key)
if result is None:
raise KeyError(key)
return result
def __contains__(self, key):
"""Support 'in' operator for cache key checking"""
with self.lock:
if key not in self.cache:
return False
# Check TTL
if time.time() - self.timestamps.get(key, 0) > self.ttl:
del self.cache[key]
del self.timestamps[key]
return False
return True
# Bounded caches for external API aggregations (prevent memory leaks)
reviews_cache = BoundedCache(maxsize=100, ttl=3600)
social_proof_cache = BoundedCache(maxsize=100, ttl=3600)
scraping_progress = BoundedCache(maxsize=50, ttl=7200)
dashboard_cache = BoundedCache(maxsize=50, ttl=3600)
enrichment_progress = BoundedCache(maxsize=50, ttl=7200)
product_lookup_cache = BoundedCache(maxsize=500, ttl=3600)
# IP rate limiter for public product lookup
_product_lookup_ip_cache: dict = {}
_product_lookup_ip_lock = Lock()
_PRODUCT_LOOKUP_MAX = 10 # per IP per minute
_TRENDYOL_URL_RE = re.compile(r'trendyol\.com/.*?-p-(\d+)', re.IGNORECASE)
def _check_ip_rate_limit(ip: str) -> bool:
now = time.time(); cutoff = now - 60.0
with _product_lookup_ip_lock:
ts = [t for t in _product_lookup_ip_cache.get(ip, []) if t > cutoff]
if len(ts) >= _PRODUCT_LOOKUP_MAX:
_product_lookup_ip_cache[ip] = ts; return False
ts.append(now); _product_lookup_ip_cache[ip] = ts; return True
# DISABLED: Questions, similar products, and followers features removed per user request
# questions_cache = {}
# similar_cache = {}
# followers_cache = {}
def _extract_price(p):
"""Extract selling price from product, handling both old and Search API formats"""
pr = p.get("price", {})
if isinstance(pr, (int, float)):
return pr
return pr.get("sellingPrice") or pr.get("discountedPrice") or pr.get("current") or pr.get("originalPrice") or pr.get("old") or 0
def _chunked(seq, size):
for i in range(0, len(seq), size):
yield seq[i:i+size]
def _safe_int(val):
try:
pass
# Convert abbreviated counts like "10B+" if present
s = str(val)
if s.endswith("B+"):
return int(s[:-2]) * 1_000_000_000
if s.endswith("M+"):
return int(s[:-2]) * 1_000_000
if s.endswith("K+"):
return int(s[:-2]) * 1_000
return int(float(s))
except Exception:
return 0
# ----------------------------------------------------------------------------
# Path validation helper (security: prevent path traversal)
# ----------------------------------------------------------------------------
import os
from pathlib import Path
# Define safe base directories
BASE_DIR = Path(__file__).parent.parent
SAFE_DIRS = {
"categories": BASE_DIR / "categories",
"reports": BASE_DIR / "reports",
"incoming": BASE_DIR / "incoming"
}
def validate_safe_path(filepath: str, directory_type: str) -> Path:
"""
Validate that a file path is within allowed directory.
Prevents path traversal attacks.
Args:
filepath: Relative or absolute file path
directory_type: One of 'categories', 'reports', 'incoming'
Returns:
Resolved Path object
Raises:
ValueError: If path is outside allowed directory or invalid type
"""
base_dir = SAFE_DIRS.get(directory_type)
if not base_dir:
raise ValueError(f"Invalid directory type: {directory_type}")
# Convert to Path and resolve
if os.path.isabs(filepath):
resolved_path = Path(filepath).resolve()
else:
resolved_path = (base_dir / filepath).resolve()
# Ensure path is within allowed directory
try:
resolved_path.relative_to(base_dir)
except ValueError:
raise ValueError(f"Path traversal detected: {filepath}")
return resolved_path
# ----------------------------------------------------------------------------
# Robust HTTP helper: shared session, retries, rate limiting
# ----------------------------------------------------------------------------
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry
import threading
_retry_strategy = Retry(
total=5, # More retries to handle rate limiting
connect=3,
read=3,
backoff_factor=2.0, # Longer backoff: 2s, 4s, 8s, 16s, 32s
status_forcelist=[429, 500, 502, 503, 504],
allowed_methods=["HEAD", "GET", "OPTIONS"]
)
_http_adapter = HTTPAdapter(max_retries=_retry_strategy, pool_connections=100, pool_maxsize=200)
_session = requests.Session()
_session.headers.update(TRENDYOL_HEADERS)
_session.cookies.update({"storefrontId": "1", "language": "tr", "countryCode": "TR"})
_session.mount("https://", _http_adapter)
_DEFAULT_TIMEOUT = 30 # Longer timeout to avoid premature failures
class _RateLimiter:
def __init__(self, rate_per_sec: float):
self.min_interval = 1.0 / max(rate_per_sec, 0.1)
self._lock = threading.Lock()
self._next_time = 0.0
def wait(self):
with self._lock:
now = time.monotonic()
if self._next_time <= now:
self._next_time = now + self.min_interval
return
sleep_for = self._next_time - now
self._next_time += self.min_interval
actual_sleep = max(0, sleep_for) + random.uniform(0.0, 0.05)
log_http.debug(f"Rate limiter sleeping {actual_sleep:.3f}s")
time.sleep(actual_sleep)
_trendyol_limiter = _RateLimiter(rate_per_sec=1.5) # ~0.67s between requests (safe for Trendyol rate limits)
# Circuit Breaker for Social Proof endpoint
class _CircuitBreaker:
def __init__(self, failure_threshold: int = 3, reset_timeout: float = 300.0):
self.failure_threshold = failure_threshold
self.reset_timeout = reset_timeout
self._failures = 0
self._opened_at = None
self._lock = threading.Lock()
def is_open(self) -> bool:
"""Check if circuit is open (blocking requests)"""
with self._lock:
if self._opened_at is None:
return False
# Auto-reset after timeout
if time.monotonic() - self._opened_at > self.reset_timeout:
self._failures = 0
self._opened_at = None
log_social.warning(
"Circuit breaker auto-reset to CLOSED (half-open recovery)",
extra={"cb_state": "closed", "failures": 0},
)
return False
return True
def record_failure(self):
"""Record a failure and potentially open the circuit"""
with self._lock:
self._failures += 1
if self._failures >= self.failure_threshold and self._opened_at is None:
self._opened_at = time.monotonic()
log_social.critical(
f"Circuit breaker OPENED after {self._failures} consecutive failures",
extra={"cb_state": "open", "failures": self._failures},
)
else:
log_social.warning(
f"Circuit breaker failure #{self._failures}/{self.failure_threshold}",
extra={"cb_state": "degraded", "failures": self._failures},
)
def record_success(self):
"""Record a success and reset the circuit"""
with self._lock:
was_open = self._opened_at is not None
self._failures = 0
self._opened_at = None
if was_open:
log_social.info(
"Circuit breaker reset to CLOSED after success",
extra={"cb_state": "closed", "failures": 0},
)
def get_status(self) -> dict:
"""Get current circuit status"""
with self._lock:
if self._opened_at is None:
return {"status": "closed", "failures": self._failures}
time_since_open = time.monotonic() - self._opened_at
time_until_reset = max(0, self.reset_timeout - time_since_open)
return {
"status": "open",
"failures": self._failures,
"time_until_reset": round(time_until_reset, 1)
}
_social_proof_breaker = _CircuitBreaker(failure_threshold=5, reset_timeout=60.0)
def _http_get(url: str, params: dict) -> requests.Response:
"""GET with shared session, retry, timeout, and rate limiting."""
_trendyol_limiter.wait()
start = time.monotonic()
try:
resp = _session.get(url, params=params, timeout=_DEFAULT_TIMEOUT)
elapsed_ms = round((time.monotonic() - start) * 1000, 1)
log_http.debug(
f"{resp.status_code} {url}",
extra={
"url": url,
"status_code": resp.status_code,
"response_time_ms": elapsed_ms,
"response_size": len(resp.content),
},
)
return resp
except requests.exceptions.Timeout:
elapsed_ms = round((time.monotonic() - start) * 1000, 1)
log_http.warning(
f"TIMEOUT {url} after {elapsed_ms}ms",
extra={"url": url, "error_type": "timeout", "response_time_ms": elapsed_ms},
)
raise
except requests.exceptions.ConnectionError as e:
elapsed_ms = round((time.monotonic() - start) * 1000, 1)
log_http.warning(
f"CONNECTION_ERROR {url}: {e}",
extra={"url": url, "error_type": "connection", "response_time_ms": elapsed_ms},
)
raise
except requests.exceptions.RequestException as e:
elapsed_ms = round((time.monotonic() - start) * 1000, 1)
log_http.error(
f"REQUEST_ERROR {url}: {e}",
extra={"url": url, "error_type": "request", "response_time_ms": elapsed_ms},
)
raise
from typing import Optional as _Optional
def _log_enrichment_error(db: Session, *, report_id: _Optional[int], product_id: _Optional[int], merchant_id: _Optional[int],
endpoint: str, error_type: str, message: str, status_code: _Optional[int] = None, attempt: int = 1):
try:
db.add(EnrichmentError(
report_id=report_id,
product_id=product_id,
merchant_id=merchant_id,
endpoint=endpoint,
error_type=error_type,
message=message[:400] if message else None,
status_code=status_code,
attempt=attempt
))
db.commit()
except Exception as exc:
# Avoid crashing on logging failures
log_db.warning(f"Failed to persist enrichment error: {exc}", exc_info=True)
db.rollback()
def load_report_products(db: Session, report_id: int):
"""Load all product dicts for a report from stored category JSON files."""
import json, os
from collections import defaultdict
report = db.query(Report).filter(Report.id == report_id).first()
if not report:
raise HTTPException(status_code=404, detail="Report not found")
if not report.json_file_path or not os.path.exists(report.json_file_path):
raise HTTPException(status_code=404, detail="Report data file not found")
try:
with open(report.json_file_path, 'r', encoding='utf-8') as f:
report_data = json.load(f)
except Exception as e:
raise HTTPException(status_code=500, detail=f"Error reading report file: {str(e)}")
all_products = []
categories_data = defaultdict(list)
for detail in report_data.get("details", []):
if detail.get("success") and detail.get("file_path"):
file_path = detail["file_path"]
if os.path.exists(file_path):
try:
with open(file_path, 'r', encoding='utf-8') as f:
cat_data = json.load(f)
products = cat_data.get("products", [])
file_category_name = cat_data.get("category_name", detail.get("category_name", ""))
# Add file-level category_name to each product if product's category is empty
for product in products:
# Check if product has category field
product_category = product.get("category", {})
if isinstance(product_category, dict):
# If category.name is empty or missing, use file-level category_name
if not product_category.get("name"):
product["category"] = {
"id": product_category.get("id", 0),
"name": file_category_name
}
elif not product_category:
# If category field doesn't exist, create it
product["category"] = {
"id": 0,
"name": file_category_name
}
all_products.extend(products)
categories_data[detail["category_name"]].extend(products)
except Exception:
continue
return all_products, categories_data
# Persistent cache helpers
def _ensure_dir(path: str):
import os
os.makedirs(path, exist_ok=True)
def _save_json(path: str, data):
import json
_ensure_dir(os.path.dirname(path))
with open(path, 'w', encoding='utf-8') as f:
json.dump(data, f, ensure_ascii=False, indent=2)
def _load_json(path: str):
import json, os
if os.path.exists(path):
with open(path, 'r', encoding='utf-8') as f:
return json.load(f)
return None
def fetch_product_reviews(product_id: int, page: int = 0, page_size: int = 5):
"""Ürün yorumlarını çeker"""
url = "https://apigw.trendyol.com/discovery-storefront-trproductgw-service/api/review-read/product-reviews/detailed"
params = {
"contentId": product_id,
"page": page,
"pageSize": page_size,
"culture": "tr-TR",
"showReviewWithSizeFeedback": True,
"channelId": 1
}
try:
resp = _http_get(url, params)
if resp.status_code == 200:
return resp.json()
except Exception as e:
log_social.warning(f"Review API error for product {product_id}: {e}")
return None
def fetch_social_proof(product_ids: list):
"""Sosyal kanıt verilerini çeker (görüntülenme, sipariş sayıları)"""
url = "https://apigw.trendyol.com/discovery-storefront-trproductgw-service/api/social-proof/"
params = {
"contentIds": ",".join(map(str, product_ids)),
"culture": "tr-TR",
"channelId": 1
}
try:
resp = _http_get(url, params)
if resp.status_code == 200:
data = resp.json()
# API doğrudan product ID'leri key olarak döndürüyor
# Convert to list format for easier processing
result = []
for product_id_str, product_data in data.items():
product_id = int(product_id_str)
social_proofs = product_data.get("socialProofs", [])
# Parse social proof metrics
metrics = {"contentId": product_id}
for proof in social_proofs:
proof_id = proof.get("id", "")
count_str = proof.get("count", "0")
# Convert count string to integer (e.g., "10B+" -> 10000)
count = _parse_social_count(count_str)
if proof_id == "page-view-count":
metrics["pageViewCount"] = count
elif proof_id == "order-count":
metrics["orderCount"] = count
elif proof_id == "basket-count":
metrics["basketCount"] = count
elif proof_id == "favorite-count":
metrics["favoriteCount"] = count
result.append(metrics)
return {"result": result} if result else data
except Exception as e:
log_social.warning(f"Social Proof API error: {e}")
return None
def _parse_social_count(count_str: str) -> int:
"""Parse social proof count string like '10B+', '75,2B' to integer"""
if not count_str:
return 0
try:
pass
# Remove '+' and replace ',' with '.'
clean = count_str.replace('+', '').replace(',', '.')
# Check if it has 'B' (bin = thousand in Turkish)
if 'B' in clean or 'b' in clean:
pass
# '10B' -> 10000, '75.2B' -> 75200
num = float(clean.replace('B', '').replace('b', ''))
return int(num * 1000)
# Try to parse as float
return int(float(clean))
except (ValueError, TypeError, AttributeError):
return 0
def fetch_merchant_questions(product_id: int, page: int = 0, page_size: int = 4):
"""Satıcı sorularını çeker"""
url = f"https://apigw.trendyol.com/discovery-pdp-websfxmerchantquestions-santral/{product_id}/questions/answered/filter"
params = {
"excludeTag": False,
"page": page,
"size": page_size,
"culture": "tr-TR",
"channelId": 1
}
try:
resp = _http_get(url, params)
if resp.status_code == 200:
return resp.json()
except Exception as e:
log_social.warning(f"Merchant Questions API error for product {product_id}: {e}")
return None
def fetch_similar_products(product_id: int, page: int = 0, page_size: int = 8):
"""Benzer ürünleri çeker"""
url = f"https://apigw.trendyol.com/discovery-storefront-trproductgw-service/api/reco-products/{product_id}"
params = {
"page": page,
"size": page_size,
"stampType": "TypeA",
"isDynamicRendering": False,
"culture": "tr-TR",
"recoType": "similar",
"channelId": 1
}
try:
resp = _http_get(url, params)
if resp.status_code == 200:
return resp.json()
except Exception as e:
log_social.warning(f"Similar Products API error for product {product_id}: {e}")
return None
def fetch_merchant_followers(merchant_id: int):
"""Satıcı takipçi sayısını çeker"""
url = f"https://apigw.trendyol.com/discovery-pdp-websfxsellerstorefollow-santral/{merchant_id}/follower-count"
params = {
"culture": "tr-TR",
"channelId": 1
}
try:
resp = _http_get(url, params)
if resp.status_code == 200:
return resp.json()
except Exception as e:
log_social.warning(f"Merchant Followers API error for merchant {merchant_id}: {e}")
return None
# Pydantic models for API
class CategoryBase(BaseModel):
name: str
parent_id: Optional[int] = None
trendyol_category_id: Optional[int] = None
trendyol_url: Optional[str] = None
path_model: Optional[str] = None
is_active: bool = True
class CategoryCreate(CategoryBase):
pass
class CategoryUpdate(BaseModel):
name: Optional[str] = None
parent_id: Optional[int] = None
trendyol_category_id: Optional[int] = None
trendyol_url: Optional[str] = None
path_model: Optional[str] = None
is_active: Optional[bool] = None
class CategoryResponse(CategoryBase):
id: int
created_at: datetime
children_count: int = 0
class Config:
from_attributes = True
class SnapshotResponse(BaseModel):
id: int
category_id: int
snapshot_month: str
total_products: int
avg_price: int
json_file_path: Optional[str]
scraped_at: datetime
class Config:
from_attributes = True
# Root endpoint
@app.get("/")
def root():
return {
"message": "Trendyol Admin API",
"version": "1.0.0",
"endpoints": {
"categories": "/categories",
"category_detail": "/categories/{id}",
"category_children": "/categories/{id}/children",
"main_categories": "/categories/main",
"snapshots": "/snapshots"
}
}
# Get all categories
@app.get("/categories", response_model=List[CategoryResponse])
def get_categories(db: Session = Depends(get_db), skip: int = 0, limit: int = 200):
"""Get all categories with pagination (OPTIMIZED: single query for children counts)"""
categories = db.query(Category).offset(skip).limit(limit).all()
# OPTIMIZATION: Get all children counts in a single query using GROUP BY
children_counts_query = db.query(
Category.parent_id,
func.count(Category.id).label('count')
).filter(Category.parent_id.isnot(None)).group_by(Category.parent_id).all()
# Convert to dict for fast lookup
children_counts = {parent_id: count for parent_id, count in children_counts_query}
result = []
for cat in categories:
# Fast O(1) lookup instead of N database queries
children_count = children_counts.get(cat.id, 0)
cat_dict = {
"id": cat.id,
"name": cat.name,
"parent_id": cat.parent_id,
"trendyol_category_id": cat.trendyol_category_id,
"trendyol_url": cat.trendyol_url,
"is_active": cat.is_active,
"created_at": cat.created_at,
"children_count": children_count
}
result.append(CategoryResponse(**cat_dict))
return result
# Get main categories (no parent)
@app.get("/categories/main", response_model=List[CategoryResponse])
def get_main_categories(db: Session = Depends(get_db)):
"""Get only main categories (parent_id is NULL) - OPTIMIZED"""
categories = db.query(Category).filter(Category.parent_id == None).all()
# OPTIMIZATION: Get all children counts in a single query
children_counts_query = db.query(
Category.parent_id,
func.count(Category.id).label('count')
).filter(Category.parent_id.isnot(None)).group_by(Category.parent_id).all()
children_counts = {parent_id: count for parent_id, count in children_counts_query}
result = []
for cat in categories:
# Fast O(1) lookup
children_count = children_counts.get(cat.id, 0)
cat_dict = {
"id": cat.id,
"name": cat.name,
"parent_id": cat.parent_id,
"trendyol_category_id": cat.trendyol_category_id,
"trendyol_url": cat.trendyol_url,
"path_model": cat.path_model,
"is_active": cat.is_active,
"created_at": cat.created_at,
"children_count": children_count
}
result.append(CategoryResponse(**cat_dict))
return result
# Get category by ID
@app.get("/categories/{category_id}", response_model=CategoryResponse)
def get_category(category_id: int, db: Session = Depends(get_db)):
"""Get a specific category by ID"""
category = db.query(Category).filter(Category.id == category_id).first()
if not category:
raise HTTPException(status_code=404, detail="Category not found")
# Count children manually
children_count = db.query(Category).filter(Category.parent_id == category.id).count()
cat_dict = {
"id": category.id,
"name": category.name,
"parent_id": category.parent_id,
"trendyol_category_id": category.trendyol_category_id,
"trendyol_url": category.trendyol_url,
"path_model": category.path_model,
"is_active": category.is_active,
"created_at": category.created_at,
"children_count": children_count
}
return CategoryResponse(**cat_dict)
# Get category children (subcategories)
@app.get("/categories/{category_id}/children", response_model=List[CategoryResponse])
def get_category_children(category_id: int, db: Session = Depends(get_db)):
"""Get all subcategories of a category - OPTIMIZED"""
# Verify parent exists
parent = db.query(Category).filter(Category.id == category_id).first()
if not parent:
raise HTTPException(status_code=404, detail="Parent category not found")
# Get children
children = db.query(Category).filter(Category.parent_id == category_id).all()
# OPTIMIZATION: Get all children counts in a single query
children_counts_query = db.query(
Category.parent_id,
func.count(Category.id).label('count')
).filter(Category.parent_id.isnot(None)).group_by(Category.parent_id).all()
children_counts = {parent_id: count for parent_id, count in children_counts_query}
result = []
for cat in children:
# Fast O(1) lookup
children_count = children_counts.get(cat.id, 0)
cat_dict = {
"id": cat.id,
"name": cat.name,
"parent_id": cat.parent_id,
"trendyol_category_id": cat.trendyol_category_id,
"trendyol_url": cat.trendyol_url,
"path_model": cat.path_model,
"is_active": cat.is_active,
"created_at": cat.created_at,
"children_count": children_count
}
result.append(CategoryResponse(**cat_dict))
return result
# Create new category
@app.post("/categories", response_model=CategoryResponse, status_code=201)
def create_category(category: CategoryCreate, db: Session = Depends(get_db)):
"""Create a new category"""
# Verify parent exists if parent_id provided
if category.parent_id:
parent = db.query(Category).filter(Category.id == category.parent_id).first()
if not parent:
raise HTTPException(status_code=404, detail="Parent category not found")
# Create new category
db_category = Category(
name=category.name,
parent_id=category.parent_id,
trendyol_category_id=category.trendyol_category_id,
trendyol_url=category.trendyol_url,
path_model=category.path_model,
is_active=category.is_active
)
db.add(db_category)
db.commit()
db.refresh(db_category)
cat_dict = {
"id": db_category.id,
"name": db_category.name,
"parent_id": db_category.parent_id,
"trendyol_category_id": db_category.trendyol_category_id,
"trendyol_url": db_category.trendyol_url,
"path_model": db_category.path_model,
"is_active": db_category.is_active,
"created_at": db_category.created_at,
"children_count": 0
}
return CategoryResponse(**cat_dict)
# Update category
@app.put("/categories/{category_id}", response_model=CategoryResponse)
def update_category(category_id: int, category: CategoryUpdate, db: Session = Depends(get_db)):
"""Update an existing category"""
db_category = db.query(Category).filter(Category.id == category_id).first()
if not db_category:
raise HTTPException(status_code=404, detail="Category not found")
# Update only provided fields
if category.name is not None:
db_category.name = category.name
if category.parent_id is not None:
if category.parent_id > 0:
parent = db.query(Category).filter(Category.id == category.parent_id).first()
if not parent:
raise HTTPException(status_code=404, detail="Parent category not found")
db_category.parent_id = category.parent_id if category.parent_id > 0 else None
if category.trendyol_category_id is not None:
db_category.trendyol_category_id = category.trendyol_category_id
if category.trendyol_url is not None:
db_category.trendyol_url = category.trendyol_url
if category.path_model is not None:
db_category.path_model = category.path_model
if category.is_active is not None:
db_category.is_active = category.is_active
db.commit()
db.refresh(db_category)
# Count children manually
children_count = db.query(Category).filter(Category.parent_id == db_category.id).count()
cat_dict = {
"id": db_category.id,
"name": db_category.name,
"parent_id": db_category.parent_id,
"trendyol_category_id": db_category.trendyol_category_id,
"trendyol_url": db_category.trendyol_url,
"path_model": db_category.path_model,
"is_active": db_category.is_active,
"created_at": db_category.created_at,
"children_count": children_count
}
return CategoryResponse(**cat_dict)
# Delete category
@app.delete("/categories/{category_id}")
def delete_category(category_id: int, db: Session = Depends(get_db)):
"""Delete a category"""
db_category = db.query(Category).filter(Category.id == category_id).first()
if not db_category:
raise HTTPException(status_code=404, detail="Category not found")
# Check if category has children
children_count = db.query(Category).filter(Category.parent_id == db_category.id).count()
if children_count > 0:
raise HTTPException(
status_code=400,
detail="Cannot delete category with subcategories. Delete children first."
)
db.delete(db_category)
db.commit()
return {"message": "Category deleted successfully", "id": category_id}
# Bulk import categories with hierarchy
class BulkCategoryItem(BaseModel):
name: str
parent_name: Optional[str] = None
trendyol_category_id: Optional[int] = None
trendyol_url: Optional[str] = None
path_model: Optional[str] = None
class BulkCategoryImport(BaseModel):
categories: List[BulkCategoryItem]
clear_existing: bool = False
@app.post("/categories/bulk-import")
def bulk_import_categories(data: BulkCategoryImport, db: Session = Depends(get_db)):
"""Bulk import categories with hierarchy support.
Categories are processed in order: parent categories should come before children.
Uses parent_name to establish parent-child relationships."""
if data.clear_existing:
db.query(Category).delete()
db.commit()
name_to_id = {}
created = 0
errors = []
for item in data.categories:
parent_id = None
if item.parent_name:
parent_id = name_to_id.get(item.parent_name)
if parent_id is None:
# Try to find by name in DB
parent = db.query(Category).filter(Category.name == item.parent_name).first()
if parent:
parent_id = parent.id
name_to_id[item.parent_name] = parent.id
else:
errors.append(f"Parent '{item.parent_name}' not found for '{item.name}'")
continue
db_cat = Category(
name=item.name,
parent_id=parent_id,
trendyol_category_id=item.trendyol_category_id,
trendyol_url=item.trendyol_url,
path_model=item.path_model,
is_active=True
)
db.add(db_cat)
db.flush()
name_to_id[item.name] = db_cat.id
created += 1
db.commit()
return {
"message": f"Imported {created} categories",
"created": created,
"errors": errors[:20],
"error_count": len(errors)
}
@app.post("/categories/seed-from-json")
def seed_from_json_endpoint(clear_existing: bool = True):
"""Seed categories from trendyol_categories.json file"""
from category_seeder import seed_from_json
try:
stats = seed_from_json(clear_existing=clear_existing)
return {"message": "Seed tamamlandı", **stats}
except FileNotFoundError:
raise HTTPException(status_code=404, detail="trendyol_categories.json not found")
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
# Get all snapshots
@app.get("/snapshots", response_model=List[SnapshotResponse])
def get_snapshots(db: Session = Depends(get_db), skip: int = 0, limit: int = 100):
"""Get all snapshots with pagination"""
snapshots = db.query(Snapshot).offset(skip).limit(limit).all()
return snapshots
# Get snapshots for a category
@app.get("/categories/{category_id}/snapshots", response_model=List[SnapshotResponse])
def get_category_snapshots(category_id: int, db: Session = Depends(get_db)):
"""Get all snapshots for a specific category"""
# Verify category exists
category = db.query(Category).filter(Category.id == category_id).first()
if not category:
raise HTTPException(status_code=404, detail="Category not found")
snapshots = db.query(Snapshot).filter(Snapshot.category_id == category_id).all()
return snapshots
# Get products for a category from JSON file
@app.get("/categories/{category_id}/products")
def get_category_products(category_id: int, db: Session = Depends(get_db)):
"""Get products from category JSON file"""
import json
import os
# Get category from DB
category = db.query(Category).filter(Category.id == category_id).first()
if not category:
raise HTTPException(status_code=404, detail="Category not found")
# Build JSON file path
trendyol_id = category.trendyol_category_id
if not trendyol_id:
raise HTTPException(status_code=400, detail="Category has no Trendyol ID")
# Search for JSON file in categories folder
categories_dir = CATEGORIES_DIR
json_files = [f for f in os.listdir(categories_dir) if f.endswith(f"_{trendyol_id}.json")]
if not json_files:
raise HTTPException(status_code=404, detail=f"No JSON file found for category {trendyol_id}")
json_path = os.path.join(categories_dir, json_files[0])
# Read JSON file
try:
with open(json_path, 'r', encoding='utf-8') as f:
data = json.load(f)
return {
"category_id": category_id,
"category_name": category.name,
"trendyol_category_id": trendyol_id,
"total_products": len(data.get("products", [])),
"products": data.get("products", [])
}
except Exception as e:
raise HTTPException(status_code=500, detail=f"Error reading JSON file: {str(e)}")
# Helper: recursively collect scrapable categories (those with trendyol_category_id)
def collect_scrapable_categories(db: Session, category_ids: list) -> list:
"""
Given a list of category IDs, collect ALL leaf categories with path_model or trendyol_category_id.
Always recurses into children to find every scrapable category in the tree.
Returns list of (path_model, name, trendyol_category_id) tuples.
"""
result = []
seen = set()
def _collect(cat_ids):
if not cat_ids:
return
cats = db.query(Category).filter(Category.id.in_(cat_ids)).all()
for cat in cats:
if cat.id in seen:
continue
seen.add(cat.id)
# Check children first
children = db.query(Category).filter(Category.parent_id == cat.id).all()
if children:
# Has children — recurse deeper
child_ids = [c.id for c in children]
_collect(child_ids)
elif cat.path_model:
# Leaf category with path_model — scrape via Search API
result.append((cat.path_model, cat.name, cat.trendyol_category_id))
elif cat.trendyol_category_id:
# Fallback: no path_model but has category_id (legacy)
result.append((None, cat.name, cat.trendyol_category_id))
_collect(category_ids)
return result
# Scraping endpoint
@app.post("/api/scrape/category/{category_id}")
def scrape_category_data(category_id: int, db: Session = Depends(get_db)):
"""
Scrape all subcategories of a main category
"""
from scraper import scrape_multiple_categories
# Get main category
main_category = db.query(Category).filter(Category.id == category_id).first()
if not main_category:
raise HTTPException(status_code=404, detail="Category not found")
# Get all subcategories
sub_categories = db.query(Category).filter(Category.parent_id == category_id).all()
if not sub_categories:
raise HTTPException(status_code=404, detail="No subcategories found")
# Collect scrapable categories (recursively resolve those without trendyol_category_id)
sub_ids = [sc.id for sc in sub_categories]
categories_to_scrape = collect_scrapable_categories(db, sub_ids)
if not categories_to_scrape:
raise HTTPException(status_code=400, detail="No scrapable categories found (missing path_model/trendyol_category_id)")
# Start scraping — convert to legacy format for scrape_multiple_categories
# Only categories with trendyol_category_id can use the old API
legacy_cats = [(cat_id, name) for (pm, name, cat_id) in categories_to_scrape if cat_id]
results = scrape_multiple_categories(legacy_cats, delay=2.0) if legacy_cats else {
"successful": 0, "failed": 0, "total_products": 0, "details": []
}
# Create snapshots for successful scrapes
for detail in results["details"]:
if detail["success"]:
sub_cat = db.query(Category).filter(
Category.trendyol_category_id == detail["category_id"]
).first()
if sub_cat:
snapshot = Snapshot(
category_id=sub_cat.id,
snapshot_month=datetime.now().strftime("%Y-%m"),
total_products=detail["total_products"],
avg_price=0,
json_file_path=detail["file_path"],
scraped_at=datetime.now()
)
db.add(snapshot)
db.commit()
return {
"main_category": main_cat["name"],
"total_subcategories": len(categories_to_scrape),
"successful": results["successful"],
"failed": results["failed"],
"total_products": results["total_products"],
"details": results["details"]
}
# Report Models
class ReportCreate(BaseModel):
name: str
category_id: int
subcategory_ids: Optional[List[int]] = None # Optional: If provided, create report only for these subcategories
class ReportUpdate(BaseModel):
name: str # Only name can be updated
class ReportResponse(BaseModel):
id: int
name: str
category_id: int
category_name: str
total_products: int
total_subcategories: int
json_file_path: Optional[str]
html_file_path: Optional[str]
created_at: datetime
class Config:
from_attributes = True
# Get all reports
@app.get("/api/reports", response_model=List[ReportResponse])
def get_reports(db: Session = Depends(get_db)):
"""Get all saved reports"""
reports = db.query(Report).order_by(Report.created_at.desc()).all()
# Load category names from JSON tree
tree = _load_category_tree()
tree_by_id = {c["id"]: c for c in tree}
result = []
for report in reports:
cat = tree_by_id.get(report.category_id)
result.append({
"id": report.id,
"name": report.name,
"category_id": report.category_id,
"category_name": cat["name"] if cat else "Unknown",
"total_products": report.total_products,
"total_subcategories": report.total_subcategories,
"json_file_path": report.json_file_path,
"html_file_path": report.html_file_path,
"created_at": report.created_at
})
return result
# Get single report
@app.get("/api/reports/create")
async def create_report(
name: str,
category_id: int,
subcategory_ids: Optional[str] = None,
db: Session = Depends(get_db)
):
"""
Create a new report with real-time progress streaming (SSE)
SYNCHRONOUS: Report only saved when 100% complete
Accepts GET request for EventSource compatibility
"""
log_api.info(f"Report create request: name={name}, category_id={category_id}")
# ── Use JSON category tree (no DB dependency) ──
tree = _load_category_tree()
tree_by_id = {c["id"]: c for c in tree}
main_cat = tree_by_id.get(category_id)
if not main_cat:
raise HTTPException(status_code=404, detail=f"Category {category_id} not found in category tree")
# Find all leaf categories under this category (recursive)
def _find_leaves(parent_id):
children = [c for c in tree if c.get("parentId") == parent_id]
if not children:
# This is a leaf — return itself
cat = tree_by_id.get(parent_id)
if cat:
path_model = (cat.get("url") or "").lstrip("/") or None
return [(path_model, cat["name"], cat["id"])]
return []
leaves = []
for child in children:
leaves.extend(_find_leaves(child["id"]))
return leaves
categories_to_scrape = _find_leaves(category_id)
if not categories_to_scrape:
raise HTTPException(status_code=400, detail="No scrapable categories found")
# Generate unique task ID
task_id = str(uuid.uuid4())
# Helper functions for non-blocking I/O
import json as _json_mod
def _write_json(path, data):
with open(path, 'w', encoding='utf-8') as f:
_json_mod.dump(data, f, ensure_ascii=False, indent=2)
def _read_json(path):
with open(path, 'r', encoding='utf-8') as f:
return _json_mod.load(f)
def _db_save(db, report):
db.add(report)
db.commit()
db.refresh(report)
# Stream progress with SSE
main_cat_name = main_cat["name"]
async def progress_stream():
"""Generator that yields real-time progress events"""
set_correlation_id(task_id)
set_report_id(category_id)
log_sse.info(f"SSE stream started: task={task_id}, category={main_cat_name}")
try:
# Send initial info
yield f"data: {json_module.dumps({'type': 'info', 'message': f'📂 {main_cat_name} kategorisi seçildi', 'progress': 0})}\n\n"
await asyncio.sleep(0.1)
yield f"data: {json_module.dumps({'type': 'info', 'message': f'📊 {len(categories_to_scrape)} alt kategori bulundu', 'progress': 0})}\n\n"
await asyncio.sleep(0.1)
yield f"data: {json_module.dumps({'type': 'info', 'message': '🚀 Veri çekimi başlatılıyor...', 'progress': 5})}\n\n"
await asyncio.sleep(0.5)
# Start synchronous scraping with progress updates
from scraper import TrendyolSearchScraper, TrendyolScraper
import json
import os
from datetime import datetime
import time
results = {
"successful": 0,
"failed": 0,
"total_products": 0,
"details": []
}
# Scrape each category with real-time updates
for idx, (path_model, cat_name, cat_id) in enumerate(categories_to_scrape, 1):
progress = int((idx / len(categories_to_scrape)) * 80) + 10
yield f"data: {json_module.dumps({'type': 'processing', 'message': f'🔍 [{idx}/{len(categories_to_scrape)}] {cat_name} çekiliyor...', 'progress': progress, 'current': idx, 'total': len(categories_to_scrape)})}\n\n"
await asyncio.sleep(0.1)
try:
if path_model:
# New Search API — works for both -c and -s categories
yield f"data: {json_module.dumps({'type': 'api', 'message': f'🌐 API: Trendyol Search - {path_model}', 'progress': progress})}\n\n"
await asyncio.sleep(0.1)
scraper = TrendyolSearchScraper(path_model)
products = await asyncio.get_event_loop().run_in_executor(None, scraper.fetch_all_products)
# Search API socialProofs boş döner — Top Rankings API'den zenginleştir
if products and cat_id and not any(p.get("socialProofs") for p in products):
try:
top_scraper = TrendyolScraper(cat_id, page_size=20)
top_products = await asyncio.get_event_loop().run_in_executor(
None, lambda: top_scraper.fetch_all_products(delay=0.5, max_pages=5)
)
if top_products:
# ID bazlı socialProofs eşleştirme
social_map = {}
for tp in top_products:
tid = tp.get("id") or tp.get("contentId")
sp = tp.get("socialProofs", [])
if tid and sp:
social_map[int(tid)] = sp
if social_map:
for p in products:
pid = p.get("id")
if pid and int(pid) in social_map:
p["socialProofs"] = social_map[int(pid)]
log_sse.info(f"Enriched {len(social_map)} products with socialProofs from Top Rankings API")
except Exception as e:
log_sse.warning(f"Top Rankings socialProofs enrichment failed: {e}")
elif cat_id:
# Legacy fallback — old top-rankings API
yield f"data: {json_module.dumps({'type': 'api', 'message': f'🌐 API: Trendyol Best Seller - Kategori ID: {cat_id}', 'progress': progress})}\n\n"
await asyncio.sleep(0.1)
scraper = TrendyolScraper(cat_id)
products = await asyncio.get_event_loop().run_in_executor(None, scraper.fetch_all_products)
else:
products = []
if products:
# Save to file — use cat_id if available, else derive from path_model
os.makedirs(CATEGORIES_DIR, exist_ok=True)
file_id = cat_id if cat_id else path_model.replace("/", "_")
filename = f"{CATEGORIES_DIR}/{cat_name.replace(' ', '_')}_{file_id}.json"
data = {
"category_id": cat_id,
"path_model": path_model,
"category_name": cat_name,
"total_products": len(products),
"scraped_at": datetime.now().isoformat(),
"products": products
}
await asyncio.to_thread(_write_json, filename, data)
results["successful"] += 1
results["total_products"] += len(products)
results["details"].append({
"category_id": cat_id,
"path_model": path_model,
"category_name": cat_name,
"success": True,
"total_products": len(products),
"file_path": filename
})
yield f"data: {json_module.dumps({'type': 'success', 'message': f'✅ {cat_name} tamamlandı - {len(products)} ürün bulundu', 'progress': progress})}\n\n"
await asyncio.sleep(0.1)
else:
results["failed"] += 1
results["details"].append({
"category_id": cat_id,
"path_model": path_model,
"category_name": cat_name,
"success": False,
"total_products": 0,
"file_path": None
})
yield f"data: {json_module.dumps({'type': 'warning', 'message': f'⚠️ {cat_name} - Ürün bulunamadı', 'progress': progress})}\n\n"
await asyncio.sleep(0.1)
except Exception as e:
results["failed"] += 1
results["details"].append({
"category_id": cat_id,
"path_model": path_model,
"category_name": cat_name,
"success": False,
"total_products": 0,
"file_path": None
})
yield f"data: {json_module.dumps({'type': 'error', 'message': f'❌ {cat_name} - Hata: {str(e)}', 'progress': progress})}\n\n"
await asyncio.sleep(0.1)
# Rate limiting (non-blocking)
await asyncio.sleep(1.5)
# Generate report file
yield f"data: {json_module.dumps({'type': 'info', 'message': '📝 Rapor dosyası oluşturuluyor...', 'progress': 88})}\n\n"
await asyncio.sleep(0.5)
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
safe_name = name.lower().replace(" ", "_").replace("ı", "i").replace("ş", "s").replace("ğ", "g").replace("ü", "u").replace("ö", "o").replace("ç", "c")
reports_dir = REPORTS_DIR
os.makedirs(reports_dir, exist_ok=True)
json_filename = f"{reports_dir}/{safe_name}_{timestamp}.json"
combined_data = {
"report_name": name,
"category": main_cat_name,
"created_at": datetime.now().isoformat(),
"total_subcategories": len(categories_to_scrape),
"total_products": results["total_products"],
"details": results["details"]
}
await asyncio.to_thread(_write_json, json_filename, combined_data)
# Save to database
yield f"data: {json_module.dumps({'type': 'info', 'message': '💾 Veritabanına kaydediliyor...', 'progress': 93})}\n\n"
await asyncio.sleep(0.5)
new_report = Report(
name=name,
category_id=category_id, # Trendyol API category ID
total_products=results["total_products"],
total_subcategories=len(categories_to_scrape),
json_file_path=json_filename,
html_file_path=None,
created_at=datetime.now()
)
try:
await asyncio.to_thread(_db_save, db, new_report)
except Exception as db_err:
log_sse.warning(f"DB save failed (non-critical): {db_err}")
# Still continue — report JSON is already saved
# Start enrichment if DB save succeeded
import threading
report_id_for_enrich = getattr(new_report, 'id', None)
enrich_status = {"status": "skipped"}
if report_id_for_enrich:
enrichment_progress[report_id_for_enrich] = {"status": "queued", "step": "queued"}
threading.Thread(
target=_enrich_report_task,
args=(report_id_for_enrich,),
daemon=True
).start()
log_sse.info(f"Background enrichment started for report {report_id_for_enrich}")
# Wait for enrichment to complete, sending progress updates via SSE
yield f"data: {json_module.dumps({'type': 'info', 'message': '📊 Sosyal kanıt verileri toplanıyor...', 'progress': 90})}\n\n"
await asyncio.sleep(0.5)
progress_key = f"social_{report_id_for_enrich}"
max_wait = 600 # 10 dakika max
waited = 0
while waited < max_wait:
enrich_status = enrichment_progress.get(report_id_for_enrich) or {}
if enrich_status.get("status") in ("completed", "error"):
break
social_progress = enrichment_progress.get(progress_key) or {}
sp_processed = social_progress.get("processed", 0)
sp_total = social_progress.get("total", 0)
sp_pct = social_progress.get("progress", 0)
if sp_total > 0:
overall_pct = 90 + int(sp_pct * 0.09)
yield f"data: {json_module.dumps({'type': 'info', 'message': f'📊 Sosyal kanıt: {sp_processed}/{sp_total} ürün (%{sp_pct})', 'progress': overall_pct})}\n\n"
await asyncio.sleep(3)
waited += 3
enrich_status = enrichment_progress.get(report_id_for_enrich) or {}
if enrich_status.get("status") == "completed":
yield f"data: {json_module.dumps({'type': 'info', 'message': '✅ Sosyal kanıt tamamlandı!', 'progress': 99})}\n\n"
elif enrich_status.get("status") == "error":
err_msg = str(enrich_status.get("error", ""))[:100]
yield f"data: {json_module.dumps({'type': 'warning', 'message': f'⚠️ Sosyal kanıt hatası: {err_msg}', 'progress': 99})}\n\n"
else:
yield f"data: {json_module.dumps({'type': 'warning', 'message': '⚠️ Sosyal kanıt zaman aşımı, arka planda devam ediyor...', 'progress': 99})}\n\n"
else:
yield f"data: {json_module.dumps({'type': 'info', 'message': '📊 Rapor JSON olarak kaydedildi (DB atlandı)', 'progress': 99})}\n\n"
await asyncio.sleep(0.1)
# Final success message
yield f"data: {json_module.dumps({'type': 'complete', 'message': '✅ Rapor başarıyla oluşturuldu!', 'progress': 100, 'report_id': report_id_for_enrich, 'total_products': results['total_products'], 'successful': results['successful'], 'enrichment_status': enrich_status.get('status', 'unknown')})}\n\n"
await asyncio.sleep(0.1)
except asyncio.CancelledError:
log_sse.warning(f"SSE stream cancelled (client disconnect): task={task_id}")
return
except Exception as e:
log_sse.error(f"SSE stream error: task={task_id}, error={e}", exc_info=True)
yield f"data: {json_module.dumps({'type': 'error', 'message': f'❌ Kritik hata: {str(e)}', 'progress': -1})}\n\n"
return StreamingResponse(progress_stream(), media_type="text/event-stream")
# ============================================================================
# QUEUE ENDPOINTS (new — replaces SSE for SellerX Java backend)
# ============================================================================
class QueueSubmitRequest(BaseModel):
name: str
category_id: int
@app.post("/api/queue/submit", status_code=202)
def submit_to_queue(req: QueueSubmitRequest, db: Session = Depends(get_db)):
"""Submit a report generation task to the queue. Returns 202 Accepted."""
# Validate category exists
tree = _load_category_tree()
tree_by_id = {c["id"]: c for c in tree}
if req.category_id not in tree_by_id:
raise HTTPException(status_code=404, detail=f"Category {req.category_id} not found")
queue_item = ReportQueue(
report_name=req.name,
category_id=req.category_id,
status="PENDING",
progress=0,
)
db.add(queue_item)
db.commit()
db.refresh(queue_item)
# Calculate position in queue
position = db.query(func.count(ReportQueue.id)).filter(
ReportQueue.status == "PENDING",
ReportQueue.created_at <= queue_item.created_at,
).scalar() or 1
log_api.info(f"Queue submit: id={queue_item.id}, name={req.name}, category={req.category_id}, position={position}")
return {"queue_id": queue_item.id, "status": "PENDING", "position": position}
@app.get("/api/queue/{queue_id}/status")
def get_queue_status(queue_id: int, db: Session = Depends(get_db)):
"""Get the status of a queued report task."""
item = db.query(ReportQueue).filter(ReportQueue.id == queue_id).first()
if not item:
raise HTTPException(status_code=404, detail="Queue item not found")
return {
"queue_id": item.id,
"status": item.status,
"progress": item.progress,
"message": item.message or "",
"result_report_id": item.result_report_id,
"error": item.error,
}
@app.get("/api/queue/active")
def get_queue_info(db: Session = Depends(get_db)):
"""Get queue overview: pending and processing counts."""
pending = db.query(func.count(ReportQueue.id)).filter(ReportQueue.status == "PENDING").scalar() or 0
processing = db.query(func.count(ReportQueue.id)).filter(ReportQueue.status == "PROCESSING").scalar() or 0
return {"pending_count": pending, "processing_count": processing}
# Update report
@app.get("/api/reports/{report_id}", response_model=ReportResponse)
def get_report(report_id: int, db: Session = Depends(get_db)):
"""Get a specific report by ID"""
report = db.query(Report).filter(Report.id == report_id).first()
if not report:
raise HTTPException(status_code=404, detail="Report not found")
tree = _load_category_tree()
cat = next((c for c in tree if c["id"] == report.category_id), None)
return {
"id": report.id,
"name": report.name,
"category_id": report.category_id,
"category_name": cat["name"] if cat else "Unknown",
"total_products": report.total_products,
"total_subcategories": report.total_subcategories,
"json_file_path": report.json_file_path,
"html_file_path": report.html_file_path,
"created_at": report.created_at
}
# Progress tracking (in-memory)
scraping_progress = {}
# Get scraping progress
@app.get("/api/reports/progress/{task_id}")
def get_scraping_progress(task_id: str):
"""Get real-time scraping progress"""
if task_id not in scraping_progress:
raise HTTPException(status_code=404, detail="Task not found")
return scraping_progress[task_id]
# Background task for scraping
def scrape_in_background(task_id: str, report_name: str, category_id: int, categories_to_scrape: list, category_name: str):
"""Background task that handles scraping with progress updates"""
from scraper import TrendyolSearchScraper, TrendyolScraper
import json
import os
from datetime import datetime
import time
# Initialize progress
scraping_progress[task_id] = {
"status": "running",
"progress": 0,
"current": 0,
"total": len(categories_to_scrape),
"current_category": "",
"logs": [],
"successful": 0,
"failed": 0,
"total_products": 0
}
def add_log(message: str, log_type: str = "info"):
"""Add log to progress"""
timestamp = datetime.now().strftime("%H:%M:%S")
scraping_progress[task_id]["logs"].append({
"timestamp": timestamp,
"message": message,
"type": log_type
})
add_log(f"📂 {category_name} kategorisi seçildi")
add_log(f"📊 {len(categories_to_scrape)} alt kategori bulundu")
add_log("🚀 Veri çekimi başlatılıyor...")
# Scrape each category
results = {
"successful": 0,
"failed": 0,
"total_products": 0,
"details": []
}
for idx, (path_model, cat_name, cat_id) in enumerate(categories_to_scrape, 1):
scraping_progress[task_id]["current"] = idx
scraping_progress[task_id]["current_category"] = cat_name
scraping_progress[task_id]["progress"] = int((idx / len(categories_to_scrape)) * 80) + 10
add_log(f"🔍 [{idx}/{len(categories_to_scrape)}] {cat_name} çekiliyor...")
try:
if path_model:
scraper = TrendyolSearchScraper(path_model)
elif cat_id:
scraper = TrendyolScraper(cat_id)
else:
add_log(f"⚠️ {cat_name} - path_model veya cat_id yok, atlanıyor", "warning")
results["failed"] += 1
scraping_progress[task_id]["failed"] += 1
continue
products = scraper.fetch_all_products()
if products:
# Save to file
os.makedirs(CATEGORIES_DIR, exist_ok=True)
file_id = cat_id if cat_id else path_model.replace("/", "_")
filename = f"{CATEGORIES_DIR}/{cat_name.replace(' ', '_')}_{file_id}.json"
data = {
"category_id": cat_id,
"path_model": path_model,
"category_name": cat_name,
"total_products": len(products),
"scraped_at": datetime.now().isoformat(),
"products": products
}
with open(filename, 'w', encoding='utf-8') as f:
json.dump(data, f, ensure_ascii=False, indent=2)
results["successful"] += 1
results["total_products"] += len(products)
results["details"].append({
"category_id": cat_id,
"path_model": path_model,
"category_name": cat_name,
"success": True,
"total_products": len(products),
"file_path": filename
})
scraping_progress[task_id]["successful"] += 1
scraping_progress[task_id]["total_products"] += len(products)
add_log(f"✅ {cat_name} tamamlandı - {len(products)} ürün", "success")
else:
results["failed"] += 1
results["details"].append({
"category_id": cat_id,
"path_model": path_model,
"category_name": cat_name,
"success": False,
"total_products": 0,
"file_path": None
})
scraping_progress[task_id]["failed"] += 1
add_log(f"⚠️ {cat_name} - Ürün bulunamadı", "warning")
except Exception as e:
results["failed"] += 1
results["details"].append({
"category_id": cat_id,
"path_model": path_model,
"category_name": cat_name,
"success": False,
"total_products": 0,
"file_path": None
})
scraping_progress[task_id]["failed"] += 1
add_log(f"❌ {cat_name} - Hata: {str(e)}", "error")
# Rate limiting
time.sleep(2.0)
# Generate report file
scraping_progress[task_id]["progress"] = 90
add_log("📝 Rapor dosyası oluşturuluyor...")
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
safe_name = report_name.lower().replace(" ", "_").replace("ı", "i").replace("ş", "s").replace("ğ", "g").replace("ü", "u").replace("ö", "o").replace("ç", "c")
reports_dir = REPORTS_DIR
os.makedirs(reports_dir, exist_ok=True)
json_filename = f"{reports_dir}/{safe_name}_{timestamp}.json"
combined_data = {
"report_name": report_name,
"category": category_name,
"created_at": datetime.now().isoformat(),
"total_subcategories": len(categories_to_scrape),
"total_products": results["total_products"],
"details": results["details"]
}
with open(json_filename, 'w', encoding='utf-8') as f:
json.dump(combined_data, f, ensure_ascii=False, indent=2)
# Save to database
scraping_progress[task_id]["progress"] = 95
add_log("💾 Veritabanına kaydediliyor...")
db = SessionLocal()
try:
new_report = Report(
name=report_name,
category_id=category_id,
total_products=results["total_products"],
total_subcategories=len(categories_to_scrape),
json_file_path=json_filename,
html_file_path=None,
created_at=datetime.now()
)
db.add(new_report)
db.commit()
db.refresh(new_report)
# Mark as completed
scraping_progress[task_id]["status"] = "completed"
scraping_progress[task_id]["progress"] = 100
scraping_progress[task_id]["report_id"] = new_report.id
add_log(f"✅ Rapor başarıyla oluşturuldu!", "success")
add_log(f"📊 Toplam {results['successful']} kategori, {results['total_products']} ürün", "success")
except Exception as e:
scraping_progress[task_id]["status"] = "failed"
add_log(f"❌ Veritabanı hatası: {str(e)}", "error")
finally:
db.close()
# Create report with real-time SSE progress (SYNCHRONOUS)
@app.put("/api/reports/{report_id}")
def update_report(report_id: int, report: ReportUpdate, db: Session = Depends(get_db)):
"""Update report name"""
db_report = db.query(Report).filter(Report.id == report_id).first()
if not db_report:
raise HTTPException(status_code=404, detail="Report not found")
db_report.name = report.name
db.commit()
db.refresh(db_report)
return {"message": "Report updated successfully", "id": report_id, "name": report.name}
# Delete report
@app.delete("/api/reports/{report_id}")
def delete_report(report_id: int, db: Session = Depends(get_db)):
"""Delete a report"""
report = db.query(Report).filter(Report.id == report_id).first()
if not report:
raise HTTPException(status_code=404, detail="Report not found")
# Delete files if exist
import os
import shutil
if report.json_file_path and os.path.exists(report.json_file_path):
os.remove(report.json_file_path)
if report.html_file_path and os.path.exists(report.html_file_path):
os.remove(report.html_file_path)
# Delete enrich directory if exists
enrich_dir = f"{REPORTS_DIR}/enrich_{report_id}"
if os.path.exists(enrich_dir):
shutil.rmtree(enrich_dir)
db.delete(report)
db.commit()
return {"message": "Report deleted successfully", "id": report_id}
# Get dashboard data for a report
# Cache for dashboard data (max 10 reports, 1 hour TTL)
from functools import lru_cache
from datetime import timedelta
import hashlib
dashboard_cache = {}
DASHBOARD_CACHE_TTL = 3600 # 1 hour in seconds
@app.get("/api/reports/{report_id}/dashboard-data")
def get_dashboard_data(report_id: int, db: Session = Depends(get_db)):
"""
Dashboard verisi döndür — konsolide dosya varsa oku, yoksa yerinde oluştur.
"""
from data_consolidator import load_consolidated_report, build_consolidated_report, save_consolidated_report
# 1. Konsolide dosyayı oku (hızlı yol)
data = load_consolidated_report(report_id, REPORTS_DIR)
if data:
log_cache.info(f"Konsolide dosyadan yüklendi: report {report_id}")
return data
# 2. Eski raporlar için fallback: yerinde oluştur ve kaydet (lazy migration)
log_cache.info(f"Konsolide dosya yok, oluşturuluyor: report {report_id}")
report = db.query(Report).filter(Report.id == report_id).first()
if not report:
raise HTTPException(status_code=404, detail="Report not found")
if not report.json_file_path or not os.path.exists(report.json_file_path):
raise HTTPException(status_code=404, detail="Report data file not found")
data = build_consolidated_report(report_id, db, REPORTS_DIR)
if not data:
raise HTTPException(status_code=500, detail="Failed to build consolidated report")
save_consolidated_report(report_id, data, REPORTS_DIR)
return data
# ============================================================================
# NEW: External API aggregations (Reviews, Social Proof, Q&A, Similar, Followers)
# ============================================================================
class AggregationParams(BaseModel):
refresh: Optional[bool] = False
per_product_limit: Optional[int] = None # None = API default
batch_size: Optional[int] = 50
# DISABLED: Reviews feature removed per user request
# @app.get("/api/reports/{report_id}/reviews-summary")
def reviews_summary_disabled(report_id: int, refresh: bool = False, db: Session = Depends(get_db)):
return {"error": "Reviews feature is disabled"}
# Try persistent cache first
if not refresh:
persisted = _load_json(f"{REPORTS_DIR}/enrich_{report_id}/reviews.json")
if persisted:
return {"source": "file", **persisted}
cache_key = f"{report_id}"
if not refresh and cache_key in reviews_cache:
return {"source": "cache", **reviews_cache[cache_key]}
try:
all_products, _ = load_report_products(db, report_id)
product_ids = [p.get("id") for p in all_products if p.get("id")]
total = len(product_ids)
summary = {
"total_products": total,
"processed": 0,
"total_reviews": 0,
"rating_histogram": {"5": 0, "4": 0, "3": 0, "2": 0, "1": 0},
"tags": {},
"sample_reviews": []
}
for pid in product_ids:
data = fetch_product_reviews(pid, page=0, page_size=5)
if not data:
_log_enrichment_error(db, report_id=report_id, product_id=int(pid), merchant_id=None,
endpoint="reviews", error_type="request_failed",
message="reviews request failed or timed out")
continue
summary["processed"] += 1
result = data.get("result", {}) if isinstance(data, dict) else {}
summary_data = result.get("summary", {})
# rating histogram - API'de "ratingCounts" olarak geliyor
rating_counts = summary_data.get("ratingCounts", []) or summary_data.get("ratingHistogram", [])
for h in rating_counts:
k = str(h.get("rate", "") or h.get("rating", ""))
v = h.get("count", 0)
if k in summary["rating_histogram"]:
summary["rating_histogram"][k] += v
# total reviews
total_review_count = summary_data.get("totalCommentCount") or summary_data.get("totalCount") or 0
summary["total_reviews"] += total_review_count
# tags - API'de "tags" olarak geliyor (tagCloud değil)
tags = summary_data.get("tags", []) or summary_data.get("tagCloud", [])
for tag in tags:
t = tag.get("name") or tag.get("tag")
c = tag.get("count", 0)
if t:
summary["tags"][t] = summary["tags"].get(t, 0) + c
# samples - API'de "reviews" olarak geliyor (content değil)
reviews = result.get("reviews", []) or result.get("content", [])
for r in reviews[:2]:
summary["sample_reviews"].append({
"product_id": pid,
"rating": r.get("rate") or r.get("rating"),
"helpful": r.get("likeCount", 0),
"with_image": bool(r.get("imageUrls") or r.get("hasImage")),
"text": (r.get("comment") or "")[:200]
})
# small pacing, limiter already active
time.sleep(0.01)
# top tags
summary["top_tags"] = sorted(
[{"tag": t, "count": c} for t, c in summary["tags"].items()],
key=lambda x: x["count"], reverse=True
)[:30]
payload = {"source": "live", "summary": summary}
reviews_cache[cache_key] = payload
return payload
except Exception as e:
return {"error": str(e), "note": "Network or parsing issue", "summary": {}}
@app.get("/api/reports/{report_id}/social-proof/progress")
def social_proof_progress(report_id: int):
"""Check social proof enrichment progress"""
progress_key = f"social_{report_id}"
if progress_key in enrichment_progress:
return enrichment_progress.get(progress_key)
return {"status": "not_started", "progress": 0}
@app.get("/api/reports/{report_id}/social-proof")
def social_proof(report_id: int, refresh: bool = False, batch_size: int = 5, db: Session = Depends(get_db)):
# Try persistent cache first
if not refresh:
persisted = _load_json(f"{REPORTS_DIR}/enrich_{report_id}/social.json")
if persisted:
pass
# Transform cache data to frontend format
agg = {
"products": persisted.get("products", 0),
"total": persisted.get("total", {}),
"missing": persisted.get("missing", 0)
}
details = persisted.get("details", {})
# Build ALL products list (not just top 20)
details_list = [
{"product_id": int(pid), **vals}
for pid, vals in details.items()
]
# Sort by page_views (descending) - ALL products
all_by_views = sorted(details_list, key=lambda x: x.get("page_views", 0), reverse=True)
# Sort by orders (descending) - ALL products
all_by_orders = sorted(details_list, key=lambda x: x.get("orders", 0), reverse=True)
return {
"source": "file",
"aggregation": agg,
"details": details,
"top_by_views": all_by_views, # All products sorted by views
"top_by_orders": all_by_orders # All products sorted by orders
}
cache_key = f"{report_id}:b{batch_size}"
if not refresh and cache_key in social_proof_cache:
return {"source": "cache", **social_proof_cache[cache_key]}
# Initialize progress tracking
progress_key = f"social_{report_id}"
enrichment_progress.set(progress_key, {
"status": "in_progress",
"progress": 0,
"total": 0,
"processed": 0,
"message": "Sosyal kanıt verileri toplanıyor..."
})
try:
all_products, _ = load_report_products(db, report_id)
product_ids = [p.get("id") for p in all_products if p.get("id")]
total_products = len(product_ids)
# Update total count
enrichment_progress.set(progress_key, {
"status": "in_progress",
"progress": 0,
"total": total_products,
"processed": 0,
"message": f"0 / {total_products} ürün işlendi"
})
# Map product id to a short display name
product_info = {}
for p in all_products:
pid = p.get("id")
if not pid:
continue
name = (p.get("name") or "Unknown")
brand = p.get("brand", {}).get("name")
if brand:
display = f"{brand} - {name}"[:80]
else:
display = name[:80]
product_info[int(pid)] = {"name": display}
agg = {
"products": len(product_ids),
"total": {"page_views": 0, "orders": 0, "baskets": 0, "favorites": 0},
"missing": 0
}
details = {}
processed = 0
for chunk in _chunked(product_ids, max(1, batch_size)):
data = fetch_social_proof(chunk)
if not data:
agg["missing"] += len(chunk)
# log per chunk
_log_enrichment_error(db, report_id=report_id, product_id=None, merchant_id=None,
endpoint="social", error_type="request_failed",
message=f"social-proof batch failed for {len(chunk)} items")
time.sleep(0.02)
processed += len(chunk)
# Update progress
progress_pct = int((processed / total_products) * 100)
enrichment_progress.set(progress_key, {
"status": "in_progress",
"progress": progress_pct,
"total": total_products,
"processed": processed,
"message": f"{processed} / {total_products} ürün işlendi"
})
continue
items = data.get("result") or data.get("items") or []
for it in items:
pid = it.get("contentId") or it.get("id")
pv = _safe_int(it.get("pageViewCount") or it.get("page-view-count") or 0)
od = _safe_int(it.get("orderCount") or it.get("order-count") or 0)
bk = _safe_int(it.get("basketCount") or it.get("basket-count") or 0)
fv = _safe_int(it.get("favoriteCount") or it.get("favorite-count") or 0)
if pid is None:
continue
details[int(pid)] = {"page_views": pv, "orders": od, "baskets": bk, "favorites": fv}
agg["total"]["page_views"] += pv
agg["total"]["orders"] += od
agg["total"]["baskets"] += bk
agg["total"]["favorites"] += fv
processed += len(chunk)
# Update progress after each chunk
progress_pct = int((processed / total_products) * 100)
enrichment_progress.set(progress_key, {
"status": "in_progress",
"progress": progress_pct,
"total": total_products,
"processed": processed,
"message": f"{processed} / {total_products} ürün işlendi"
})
time.sleep(0.01)
# Build top lists
details_list = [
{"product_id": pid, **vals, **(product_info.get(pid, {}))}
for pid, vals in details.items()
]
top_by_views = sorted(details_list, key=lambda x: x.get("page_views", 0), reverse=True)[:20]
top_by_orders = sorted(details_list, key=lambda x: x.get("orders", 0), reverse=True)[:20]
result = {"aggregation": agg, "details": details, "top_by_views": top_by_views, "top_by_orders": top_by_orders}
social_proof_cache[cache_key] = result
# Mark as completed
enrichment_progress.set(progress_key, {
"status": "completed",
"progress": 100,
"total": total_products,
"processed": total_products,
"message": f"Tamamlandı! {total_products} ürün işlendi"
})
return result
except Exception as e:
log_api.error(f"Enrichment failed for report: {e}", exc_info=True)
# Mark as failed
enrichment_progress.set(progress_key, {
"status": "failed",
"progress": 0,
"total": 0,
"processed": 0,
"message": f"Hata: {str(e)}"
})
return {"error": str(e), "note": "Network or parsing issue", "aggregation": {}, "details": {}}
@app.get("/api/reports/{report_id}/sales-analytics")
def sales_analytics(report_id: int):
"""
Fast sales analytics endpoint - returns top products by orders
"""
try:
# Load social proof data
social_data = _load_json(f"{REPORTS_DIR}/enrich_{report_id}/social.json")
if not social_data:
return {"error": "Social proof data not found"}
social_details = social_data.get("details", {})
# Build enriched product list from social proof data
enriched_products = []
for pid_str, social_vals in social_details.items():
# Social data already has name, brand, price
enriched = {
"id": int(pid_str),
"name": social_vals.get("name", ""),
"brand": social_vals.get("brand", "Unknown"),
"price": social_vals.get("price", 0),
"page_views": social_vals.get("page_views", 0),
"orders": social_vals.get("orders", 0),
"baskets": social_vals.get("baskets", 0),
"favorites": social_vals.get("favorites", 0)
}
# Calculate conversion rates
views = enriched["page_views"]
baskets = enriched["baskets"]
orders = enriched["orders"]
enriched["view_to_basket_rate"] = (baskets / views * 100) if views > 0 else 0
enriched["basket_to_order_rate"] = (orders / baskets * 100) if baskets > 0 else 0
enriched["view_to_order_rate"] = (orders / views * 100) if views > 0 else 0
# Calculate performance score (0-100)
# Weighted: orders (40%), conversion rate (30%), views (20%), favorites (10%)
max_orders = max([s.get("orders", 0) for s in social_details.values()]) or 1
max_views = max([s.get("page_views", 0) for s in social_details.values()]) or 1
max_favs = max([s.get("favorites", 0) for s in social_details.values()]) or 1
order_score = (orders / max_orders) * 40
conversion_score = enriched["view_to_order_rate"] * 3 # Scale 0-30
view_score = (views / max_views) * 20
fav_score = (enriched["favorites"] / max_favs) * 10
enriched["performance_score"] = min(100, order_score + conversion_score + view_score + fav_score)
enriched_products.append(enriched)
# Return top products by orders
top_by_orders = sorted(enriched_products, key=lambda x: x.get("orders", 0), reverse=True)[:20]
# Aggregate totals for sales funnel
total_views = sum(p.get("page_views", 0) for p in enriched_products)
total_baskets = sum(p.get("baskets", 0) for p in enriched_products)
total_orders = sum(p.get("orders", 0) for p in enriched_products)
return {
"top_products_by_orders": top_by_orders,
"total_views": total_views,
"total_baskets": total_baskets,
"total_orders": total_orders,
"view_to_basket_rate": round((total_baskets / total_views * 100), 2) if total_views > 0 else 0,
"basket_to_order_rate": round((total_orders / total_baskets * 100), 2) if total_baskets > 0 else 0,
"view_to_order_rate": round((total_orders / total_views * 100), 2) if total_views > 0 else 0,
}
except Exception as e:
return {"error": str(e), "note": "Failed to generate sales analytics"}
# ============================================================================
# KEYWORD ANALYSIS
# ============================================================================
# Türkçe stop words listesi
TURKISH_STOP_WORDS = {
've', 'ile', 'için', 'bir', 'bu', 'şu', 'o', 'de', 'da', 'ki',
'mi', 'mı', 'mu', 'mü', 'ise', 'olan', 'olarak', 'gibi',
'kadar', 'daha', 'en', 'çok', 'az', 'var', 'yok', 'veya',
'ile', 'ancak', 'ama', 'fakat', 'lakin', 'çünkü', 'zira',
'şöyle', 'böyle', 'nasıl', 'ne', 'neden', 'niçin', 'niye',
'a', 'e', 'i', 'ı', 'o', 'ö', 'u', 'ü' # Tek harfler
}
def normalize_turkish(text: str) -> str:
"""Türkçe karakterleri normalize eder"""
replacements = {
'İ': 'i', 'I': 'ı',
'Ş': 'ş', 'ş': 'ş',
'Ğ': 'ğ', 'ğ': 'ğ',
'Ü': 'ü', 'ü': 'ü',
'Ö': 'ö', 'ö': 'ö',
'Ç': 'ç', 'ç': 'ç'
}
for old, new in replacements.items():
text = text.replace(old, new)
return text
def extract_keywords_from_text(text: str, min_length: int = 3, stop_words: set = None) -> list:
"""
Metinden keyword'leri çıkarır.
Args:
text: Analiz edilecek metin
min_length: Minimum keyword uzunluğu
stop_words: Stop words seti (None ise TURKISH_STOP_WORDS kullanılır)
Returns:
Keyword listesi
"""
if not text or not isinstance(text, str):
return []
if stop_words is None:
stop_words = TURKISH_STOP_WORDS
# 1. Küçük harfe çevir
text = text.lower()
# 2. Türkçe karakterleri normalize et
text = normalize_turkish(text)
# 3. Noktalama işaretlerini temizle
text = re.sub(r'[^\w\s]', ' ', text)
# 4. Sayıları temizle
text = re.sub(r'\d+', '', text)
# 5. Fazla boşlukları temizle
text = re.sub(r'\s+', ' ', text).strip()
# 6. Tokenize
tokens = text.split()
# 7. Filtrele
keywords = [
token for token in tokens
if len(token) >= min_length
and token not in stop_words
and not token.isdigit()
and token.isalpha() # Sadece harf içeren
]
return keywords
def generate_ngrams(tokens: list, min_n: int = 1, max_n: int = 3) -> list:
"""
Generate N-grams from a list of tokens.
Args:
tokens: List of words (tokens)
min_n: Minimum N-gram size (default: 1 = single words)
max_n: Maximum N-gram size (default: 3 = trigrams)
Returns:
List of N-grams as strings
Example:
tokens = ["mini", "buzdolabı", "beyaz"]
min_n=1, max_n=3 →
["mini", "buzdolabı", "beyaz", # 1-grams
"mini buzdolabı", "buzdolabı beyaz", # 2-grams
"mini buzdolabı beyaz"] # 3-grams
"""
ngrams = []
for n in range(min_n, max_n + 1):
# Generate all n-grams of size n
for i in range(len(tokens) - n + 1):
ngram = ' '.join(tokens[i:i+n])
ngrams.append(ngram)
return ngrams
@app.get("/api/reports/{report_id}/keyword-analysis")
def keyword_analysis(
report_id: int,
min_frequency: int = 3,
min_length: int = 3,
category_filter: Optional[str] = None,
top_n: int = 50, # DEPRECATED: Use page/per_page instead
# Pagination parameters
page: int = 1, # Page number (1-indexed)
per_page: int = 100, # Keywords per page
# N-gram (word count) filters
min_word_count: Optional[int] = 1, # Minimum number of words in keyword (1-5)
max_word_count: Optional[int] = 3, # Maximum number of words in keyword (1-5)
# Advanced filters
min_views: Optional[int] = None,
max_views: Optional[int] = None,
min_orders: Optional[int] = None,
max_orders: Optional[int] = None,
min_reviews: Optional[int] = None,
max_reviews: Optional[int] = None,
min_conversion_rate: Optional[float] = None,
max_conversion_rate: Optional[float] = None,
min_avg_price: Optional[float] = None,
max_avg_price: Optional[float] = None,
sort_by: str = "frequency", # frequency, views, orders, reviews, conversion_rate
sort_order: str = "desc", # asc, desc
competition_level: Optional[str] = None, # low, medium, high
min_potential_score: Optional[float] = None, # 0-100
db: Session = Depends(get_db)
):
"""
Ürün adlarından keyword çıkarır ve N-gram analizi yapar.
Args:
report_id: Rapor ID
min_frequency: Minimum keyword geçme sayısı (default: 3)
min_length: Minimum karakter uzunluğu (default: 3)
min_word_count: Minimum kelime sayısı (1-5, default: 1)
max_word_count: Maximum kelime sayısı (1-5, default: 3)
category_filter: Belirli kategoriye göre filtreleme (opsiyonel)
top_n: Top N keyword göster (default: 50)
N-gram Examples:
min_word_count=1, max_word_count=1 → "mini", "buzdolabı", "beyaz"
min_word_count=2, max_word_count=2 → "mini buzdolabı", "buzdolabı beyaz"
min_word_count=2, max_word_count=3 → "mini buzdolabı", "beyaz buzdolabı", "mini buzdolabı modelleri"
Returns:
Keyword analiz sonuçları
"""
log_keywords.info(f"Keyword analysis: report={report_id}, min_freq={min_frequency}, word_count={min_word_count}-{max_word_count}, top_n={top_n}")
try:
log_keywords.info("Ürünler yükleniyor...")
# Load products
all_products, categories_data = load_report_products(db, report_id)
log_keywords.info(f"{len(all_products) if all_products else 0} ürün yüklendi")
if not all_products:
log_keywords.warning("Rapor için ürün bulunamadı!")
return {"error": "No products found for this report"}
# Load social proof data
log_keywords.info("Social proof data yükleniyor...")
social_json_path = os.path.join(REPORTS_DIR, f"enrich_{report_id}", "social.json")
social_data = _load_json(social_json_path)
social_details = social_data.get("details", {}) if social_data else {}
log_keywords.info(f"Social proof data yüklendi: {len(social_details)} ürün")
# Filter by category if specified
if category_filter:
all_products = [
p for p in all_products
if (p.get("category", {}).get("name") if isinstance(p.get("category"), dict) else p.get("category")) == category_filter
]
# Step 1: Extract keywords from all product names (OPTIMIZED)
log_keywords.info(f"Keyword extraction başlatılıyor... ({len(all_products)} ürün)")
keyword_to_products = {} # {keyword: [product_ids]}
product_keywords_map = {} # {product_id: [keywords]}
# Pre-compile regex patterns for better performance
import re
stop_words = TURKISH_STOP_WORDS
processed_count = 0
start_time = time.time()
for product in all_products:
product_id = product.get("id")
if not product_id:
continue
product_name = product.get("name", "")
if not product_name:
continue
# Extract keywords (optimized inline version)
text = product_name.lower()
text = normalize_turkish(text)
text = re.sub(r'[^\w\s]', ' ', text)
text = re.sub(r'\d+', '', text)
text = re.sub(r'\s+', ' ', text).strip()
tokens = text.split()
# Filter tokens by character length and stop words
filtered_tokens = [
token for token in tokens
if len(token) >= min_length
and token not in stop_words
and not token.isdigit()
and token.isalpha()
]
# Generate N-grams (1-word, 2-word, 3-word, etc.)
keywords = generate_ngrams(filtered_tokens, min_n=min_word_count, max_n=max_word_count)
product_keywords_map[product_id] = keywords
# Group by keyword
for keyword in keywords:
if keyword not in keyword_to_products:
keyword_to_products[keyword] = []
keyword_to_products[keyword].append(product_id)
processed_count += 1
if processed_count % 500 == 0:
elapsed = time.time() - start_time
rate = processed_count / elapsed if elapsed > 0 else 0
remaining = (len(all_products) - processed_count) / rate if rate > 0 else 0
log_keywords.info(f"İşlenen ürün: {processed_count}/{len(all_products)} ({rate:.0f} ürün/sn, ~{remaining:.0f}s kaldı)")
elapsed_total = time.time() - start_time
log_keywords.info(f"Keyword extraction tamamlandı: {len(keyword_to_products)} unique keyword ({elapsed_total:.2f}s)")
# Step 2: Separate rare keywords (frequency 1-2) and common keywords (>= min_frequency)
log_keywords.info(f"Keyword ayrıştırma: rare (1-2) vs common (>={min_frequency})")
rare_keywords = {
kw: product_ids
for kw, product_ids in keyword_to_products.items()
if 1 <= len(product_ids) <= 2
}
filtered_keywords = {
kw: product_ids
for kw, product_ids in keyword_to_products.items()
if len(product_ids) >= min_frequency
}
log_keywords.info(f"Rare keywords: {len(rare_keywords)} | Common keywords: {len(filtered_keywords)}")
# Step 3: Calculate metrics for each keyword (OPTIMIZED)
log_keywords.info(f"Metrikler hesaplanıyor... ({len(filtered_keywords)} keyword)")
keyword_metrics = []
# Create product lookup dict for faster access
product_dict = {p.get("id"): p for p in all_products if p.get("id")}
metric_count = 0
metric_start_time = time.time()
for keyword, product_ids in filtered_keywords.items():
# Get category distribution and metrics
category_counts = {}
category_metrics = {} # {category: {views, orders, reviews, baskets, favorites, product_count}}
total_views = 0
total_orders = 0
total_baskets = 0
total_favorites = 0
total_reviews = 0
keyword_products = []
for pid in product_ids:
# Find product (using dict lookup for O(1) instead of O(n))
product = product_dict.get(pid)
if not product:
continue
# Get category
category = product.get("category", {})
if isinstance(category, dict):
category_name = category.get("name", "Uncategorized")
else:
category_name = category if category else "Uncategorized"
category_counts[category_name] = category_counts.get(category_name, 0) + 1
# Initialize category metrics if not exists
if category_name not in category_metrics:
category_metrics[category_name] = {
"views": 0,
"orders": 0,
"reviews": 0,
"baskets": 0,
"favorites": 0,
"product_count": 0
}
# Get social proof
social = social_details.get(str(pid), {})
views = social.get("page_views", 0) or 0
orders = social.get("orders", 0) or 0
baskets = social.get("baskets", 0) or 0
favorites = social.get("favorites", 0) or 0
# Get review count from multiple possible locations
review_count = 0
# Try rating_count field first
if product.get("rating_count"):
review_count = int(product.get("rating_count", 0) or 0)
# Try rating object with totalCount or totalComments
elif product.get("rating"):
rating_obj = product.get("rating")
if isinstance(rating_obj, dict):
review_count = int(rating_obj.get("totalComments", 0) or rating_obj.get("totalCount", 0) or 0)
elif isinstance(rating_obj, (int, float)):
pass
# If rating is just a number, no review count available
review_count = 0
# Add to category metrics
category_metrics[category_name]["views"] += views
category_metrics[category_name]["orders"] += orders
category_metrics[category_name]["reviews"] += review_count
category_metrics[category_name]["baskets"] += baskets
category_metrics[category_name]["favorites"] += favorites
category_metrics[category_name]["product_count"] += 1
# Add to totals
total_views += views
total_orders += orders
total_baskets += baskets
total_favorites += favorites
total_reviews += review_count
# Store product info
keyword_products.append({
"id": pid,
"name": product.get("name", "")[:50],
"category": category_name,
"brand": product.get("brand", {}).get("name", "Unknown") if isinstance(product.get("brand"), dict) else "Unknown",
"views": views,
"orders": orders,
"reviews": review_count,
"price": _extract_price(product),
"image_url": product.get("imageUrl", "") or (product.get("images", [])[0] if product.get("images") else "https://via.placeholder.com/150"),
"url": product.get("url", "") or f"https://www.trendyol.com/p/{pid}"
})
product_count = len(product_ids)
# Calculate averages
avg_views = total_views / product_count if product_count > 0 else 0
avg_orders = total_orders / product_count if product_count > 0 else 0
avg_reviews = total_reviews / product_count if product_count > 0 else 0
conversion_rate = (total_orders / total_views * 100) if total_views > 0 else 0
# Top categories with metrics
top_categories = []
for cat, count in category_counts.items():
cat_metrics = category_metrics.get(cat, {})
cat_views = cat_metrics.get("views", 0)
cat_orders = cat_metrics.get("orders", 0)
cat_reviews = cat_metrics.get("reviews", 0)
cat_conversion = (cat_orders / cat_views * 100) if cat_views > 0 else 0
top_categories.append({
"category": cat,
"count": count,
"percentage": (count / product_count * 100),
"total_views": cat_views,
"total_orders": cat_orders,
"total_reviews": cat_reviews,
"conversion_rate": round(cat_conversion, 2)
})
top_categories = sorted(
top_categories,
key=lambda x: x["count"],
reverse=True
)[:10] # Show top 10 categories
# Filter products with sales > 0, then sort by orders and take top 10
products_with_sales = [p for p in keyword_products if p["orders"] > 0]
top_products = sorted(
products_with_sales,
key=lambda x: x["orders"],
reverse=True
)[:10]
keyword_metrics.append({
"keyword": keyword,
"frequency": product_count,
"categories": category_counts,
"top_categories": top_categories,
"performance": {
"total_views": total_views,
"total_orders": total_orders,
"total_baskets": total_baskets,
"total_favorites": total_favorites,
"total_reviews": total_reviews,
"avg_views_per_product": round(avg_views, 2),
"avg_orders_per_product": round(avg_orders, 2),
"avg_reviews_per_product": round(avg_reviews, 2),
"conversion_rate": round(conversion_rate, 2)
},
"products": top_products # Top 10 products by sales
})
metric_count += 1
if metric_count % 50 == 0:
elapsed_metric = time.time() - metric_start_time
rate = metric_count / elapsed_metric if elapsed_metric > 0 else 0
remaining = (len(filtered_keywords) - metric_count) / rate if rate > 0 else 0
log_keywords.info(f"İşlenen keyword: {metric_count}/{len(filtered_keywords)} ({rate:.1f} keyword/sn, ~{remaining:.0f}s kaldı)")
metric_elapsed = time.time() - metric_start_time
log_keywords.info(f"Metrikler hesaplandı: {len(keyword_metrics)} keyword ({metric_elapsed:.2f}s)")
# Step 4: Apply advanced filters
# print(f"🔍 Gelişmiş filtreler uygulanıyor...")
filtered_metrics = keyword_metrics.copy()
# Views filter
if min_views is not None:
filtered_metrics = [kw for kw in filtered_metrics if kw["performance"]["total_views"] >= min_views]
if max_views is not None:
filtered_metrics = [kw for kw in filtered_metrics if kw["performance"]["total_views"] <= max_views]
# Orders filter
if min_orders is not None:
filtered_metrics = [kw for kw in filtered_metrics if kw["performance"]["total_orders"] >= min_orders]
if max_orders is not None:
filtered_metrics = [kw for kw in filtered_metrics if kw["performance"]["total_orders"] <= max_orders]
# Reviews filter
if min_reviews is not None:
filtered_metrics = [kw for kw in filtered_metrics if kw["performance"]["total_reviews"] >= min_reviews]
if max_reviews is not None:
filtered_metrics = [kw for kw in filtered_metrics if kw["performance"]["total_reviews"] <= max_reviews]
# Conversion rate filter
if min_conversion_rate is not None:
filtered_metrics = [kw for kw in filtered_metrics if kw["performance"]["conversion_rate"] >= min_conversion_rate]
if max_conversion_rate is not None:
filtered_metrics = [kw for kw in filtered_metrics if kw["performance"]["conversion_rate"] <= max_conversion_rate]
# Average price filter (calculate from products)
if min_avg_price is not None or max_avg_price is not None:
filtered_by_price = []
for kw in filtered_metrics:
if kw["products"]:
avg_price = sum(p.get("price", 0) for p in kw["products"]) / len(kw["products"])
if min_avg_price is not None and avg_price < min_avg_price:
continue
if max_avg_price is not None and avg_price > max_avg_price:
continue
filtered_by_price.append(kw)
filtered_metrics = filtered_by_price
# Competition level filter (based on frequency)
if competition_level:
total_keywords_count = len(keyword_metrics)
if total_keywords_count > 0:
if competition_level == "low":
pass
# Bottom 33% - low competition
sorted_freqs = sorted([kw["frequency"] for kw in keyword_metrics])
threshold = sorted_freqs[int(total_keywords_count * 0.33)] if sorted_freqs else 0
filtered_metrics = [kw for kw in filtered_metrics if kw["frequency"] <= threshold]
elif competition_level == "high":
pass
# Top 33% - high competition
sorted_freqs = sorted([kw["frequency"] for kw in keyword_metrics], reverse=True)
threshold = sorted_freqs[int(total_keywords_count * 0.33)] if sorted_freqs else float('inf')
filtered_metrics = [kw for kw in filtered_metrics if kw["frequency"] >= threshold]
# medium is between low and high, no filter needed
# Potential score filter (high conversion + low competition)
if min_potential_score is not None:
pass
# Calculate potential score: (conversion_rate * 0.6) + ((100 - normalized_frequency) * 0.4)
max_freq = max([kw["frequency"] for kw in filtered_metrics]) if filtered_metrics else 1
for kw in filtered_metrics:
normalized_freq = (kw["frequency"] / max_freq) * 100 if max_freq > 0 else 0
potential = (kw["performance"]["conversion_rate"] * 0.6) + ((100 - normalized_freq) * 0.4)
kw["potential_score"] = round(potential, 2)
filtered_metrics = [kw for kw in filtered_metrics if kw.get("potential_score", 0) >= min_potential_score]
log_keywords.info(f"Filtreleme sonrası: {len(filtered_metrics)} keyword kaldı")
# Step 5: Sort by selected criteria
log_keywords.info(f"Sıralama yapılıyor: {sort_by} ({sort_order})...")
reverse_order = sort_order == "desc"
if sort_by == "frequency":
filtered_metrics.sort(key=lambda x: x["frequency"], reverse=reverse_order)
elif sort_by == "views":
filtered_metrics.sort(key=lambda x: x["performance"]["total_views"], reverse=reverse_order)
elif sort_by == "orders":
filtered_metrics.sort(key=lambda x: x["performance"]["total_orders"], reverse=reverse_order)
elif sort_by == "reviews":
filtered_metrics.sort(key=lambda x: x["performance"]["total_reviews"], reverse=reverse_order)
elif sort_by == "conversion_rate":
filtered_metrics.sort(key=lambda x: x["performance"]["conversion_rate"], reverse=reverse_order)
elif sort_by == "potential_score":
pass
# Calculate if not already calculated
max_freq = max([kw["frequency"] for kw in filtered_metrics]) if filtered_metrics else 1
for kw in filtered_metrics:
if "potential_score" not in kw:
normalized_freq = (kw["frequency"] / max_freq) * 100 if max_freq > 0 else 0
kw["potential_score"] = round((kw["performance"]["conversion_rate"] * 0.6) + ((100 - normalized_freq) * 0.4), 2)
filtered_metrics.sort(key=lambda x: x.get("potential_score", 0), reverse=reverse_order)
# Pagination logic
import math
total_keywords = len(filtered_metrics)
total_pages = math.ceil(total_keywords / per_page) if per_page > 0 else 1
# Calculate offset and limit
start_index = (page - 1) * per_page
end_index = start_index + per_page
# Get paginated keywords
paginated_keywords = filtered_metrics[start_index:end_index]
log_keywords.info(f"Sayfa {page}/{total_pages} - {len(paginated_keywords)} keyword (toplam: {total_keywords})")
# Step 6: Process rare keywords (frequency 1-2) - Limited to top 100 for performance
log_keywords.info(f"Rare keywords işleniyor... ({len(rare_keywords)} keyword)")
rare_metrics = []
rare_count = 0
for keyword, product_ids in rare_keywords.items():
# Get category distribution and metrics (simplified version)
total_views = 0
total_orders = 0
total_baskets = 0
for pid in product_ids:
product = product_dict.get(pid)
if not product:
continue
# Get social proof
social = social_details.get(str(pid), {})
total_views += social.get("contentViewCount", 0)
total_orders += social.get("totalOrder", 0)
total_baskets += social.get("totalBasket", 0)
# Only include rare keywords that have actual sales
if total_orders > 0:
rare_metrics.append({
"keyword": keyword,
"frequency": len(product_ids),
"performance": {
"total_views": total_views,
"total_orders": total_orders,
"total_baskets": total_baskets,
"conversion_rate": round((total_orders / total_views * 100) if total_views > 0 else 0, 2)
}
})
rare_count += 1
if rare_count >= 100: # Limit to 100 rare keywords for performance
break
# Sort rare keywords by orders (most promising first)
rare_metrics.sort(key=lambda x: x["performance"]["total_orders"], reverse=True)
log_keywords.info(f"Rare keywords işlendi: {len(rare_metrics)} keyword (top 100)")
# Step 7: Build category × keyword matrix
category_keyword_matrix = {}
for kw_data in paginated_keywords:
keyword = kw_data["keyword"]
for cat, count in kw_data["categories"].items():
if cat not in category_keyword_matrix:
category_keyword_matrix[cat] = {}
category_keyword_matrix[cat][keyword] = count
# Step 7: Calculate insights
most_frequent = paginated_keywords[:10] if paginated_keywords else []
best_performing = sorted(
keyword_metrics,
key=lambda x: x["performance"]["total_orders"],
reverse=True
)[:10]
result = {
"total_keywords": total_keywords,
"total_products_analyzed": len(all_products),
"keywords": paginated_keywords,
"rare_keywords": rare_metrics, # NEW: Rare keywords (frequency 1-2)
"total_rare_keywords": len(rare_keywords), # NEW: Total count of rare keywords
"category_keyword_matrix": category_keyword_matrix,
"pagination": {
"page": page,
"per_page": per_page,
"total_pages": total_pages,
"total_items": total_keywords,
"has_next": page < total_pages,
"has_previous": page > 1
},
"insights": {
"most_frequent_keywords": [{"keyword": kw["keyword"], "frequency": kw["frequency"]} for kw in most_frequent],
"best_performing_keywords": [{"keyword": kw["keyword"], "total_orders": kw["performance"]["total_orders"]} for kw in best_performing]
}
}
log_keywords.info(f"Keyword analysis completed: {result['total_keywords']} common, {result['total_rare_keywords']} rare, {result['total_products_analyzed']} ürün")
return result
except Exception as e:
import traceback
error_trace = traceback.format_exc()
log_keywords.error(f"Keyword analysis error: {e}", exc_info=True)
return {"error": str(e), "traceback": error_trace, "note": "Failed to generate keyword analysis"}
# ============================================================================
# PRODUCT FINDER
# ============================================================================
@app.get("/api/reports/{report_id}/product-finder")
def product_finder(
report_id: int,
keywords: Optional[str] = None,
keyword_logic: str = "and", # and, or, not
min_views: Optional[int] = None,
max_views: Optional[int] = None,
min_orders: Optional[int] = None,
max_orders: Optional[int] = None,
min_reviews: Optional[int] = None,
max_reviews: Optional[int] = None,
min_conversion_rate: Optional[float] = None,
max_conversion_rate: Optional[float] = None,
min_price: Optional[float] = None,
max_price: Optional[float] = None,
min_rating: Optional[float] = None,
max_rating: Optional[float] = None,
min_rating_count: Optional[int] = None,
max_rating_count: Optional[int] = None,
categories: Optional[str] = None, # comma-separated
brands: Optional[str] = None, # comma-separated
origin_countries: Optional[str] = None, # comma-separated
competition_level: Optional[str] = None,
min_potential_score: Optional[float] = None,
sort_by: str = "orders",
sort_order: str = "desc",
page: int = 1,
per_page: int = 50,
db: Session = Depends(get_db)
):
"""
Gelişmiş filtrelerle ürün arama ve bulma.
Args:
report_id: Rapor ID
keywords: Virgülle ayrılmış keyword listesi
keyword_logic: "and", "or", "not"
... (diğer filtreler)
page: Sayfa numarası
per_page: Sayfa başına ürün sayısı
Returns:
Filtrelenmiş ürün listesi
"""
log_api.info(f"Product finder: report={report_id}, page={page}, per_page={per_page}")
try:
pass
# Load products
all_products, categories_data = load_report_products(db, report_id)
log_api.info(f"{len(all_products)} ürün yüklendi")
if not all_products:
return {
"total_products": 0,
"page": page,
"per_page": per_page,
"total_pages": 0,
"products": []
}
# Load social proof data
social_data = _load_json(f"{REPORTS_DIR}/enrich_{report_id}/social.json")
social_details = social_data.get("details", {}) if social_data else {}
log_api.info(f"Social proof data yüklendi: {len(social_details)} ürün")
# Create product lookup dict
product_dict = {p.get("id"): p for p in all_products if p.get("id")}
# Filter products
filtered_products = []
# Parse filter lists
category_list = [c.strip() for c in categories.split(",")] if categories else []
brand_list = [b.strip() for b in brands.split(",")] if brands else []
origin_list = [o.strip() for o in origin_countries.split(",")] if origin_countries else []
keyword_list = [k.strip().lower() for k in keywords.split(",")] if keywords else []
# Calculate competition levels (category-based)
category_product_counts = {}
for product in all_products:
category = product.get("category", {})
if isinstance(category, dict):
cat_name = category.get("name", "Uncategorized")
else:
cat_name = category if category else "Uncategorized"
category_product_counts[cat_name] = category_product_counts.get(cat_name, 0) + 1
for product in all_products:
product_id = product.get("id")
if not product_id:
continue
# Get social proof
social = social_details.get(str(product_id), {})
views = social.get("page_views", 0) or 0
orders = social.get("orders", 0) or 0
baskets = social.get("baskets", 0) or 0
favorites = social.get("favorites", 0) or 0
# Get review count
review_count = 0
if product.get("rating_count"):
review_count = int(product.get("rating_count", 0) or 0)
elif product.get("rating"):
rating_obj = product.get("rating")
if isinstance(rating_obj, dict):
review_count = int(rating_obj.get("totalComments", 0) or rating_obj.get("totalCount", 0) or 0)
# Get rating
rating = 0
if product.get("rating"):
rating_obj = product.get("rating")
if isinstance(rating_obj, dict):
rating = float(rating_obj.get("averageRating", 0) or 0)
elif isinstance(rating_obj, (int, float)):
rating = float(rating_obj)
# Get price
price = _extract_price(product)
# Get category
category = product.get("category", {})
if isinstance(category, dict):
category_name = category.get("name", "Uncategorized")
else:
category_name = category if category else "Uncategorized"
# Get brand
brand = product.get("brand", {})
if isinstance(brand, dict):
brand_name = brand.get("name", "Unknown")
else:
brand_name = brand if brand else "Unknown"
# Get origin country
origin_country = product.get("origin_country", "Unknown")
# Calculate conversion rate
conversion_rate = (orders / views * 100) if views > 0 else 0
# Keyword filter
if keyword_list:
product_name = (product.get("name", "") or "").lower()
if keyword_logic == "and":
if not all(kw in product_name for kw in keyword_list):
continue
elif keyword_logic == "or":
if not any(kw in product_name for kw in keyword_list):
continue
elif keyword_logic == "not":
if any(kw in product_name for kw in keyword_list):
continue
# Views filter
if min_views is not None and views < min_views:
continue
if max_views is not None and views > max_views:
continue
# Orders filter
if min_orders is not None and orders < min_orders:
continue
if max_orders is not None and orders > max_orders:
continue
# Reviews filter
if min_reviews is not None and review_count < min_reviews:
continue
if max_reviews is not None and review_count > max_reviews:
continue
# Conversion rate filter
if min_conversion_rate is not None and conversion_rate < min_conversion_rate:
continue
if max_conversion_rate is not None and conversion_rate > max_conversion_rate:
continue
# Price filter
if min_price is not None and price < min_price:
continue
if max_price is not None and price > max_price:
continue
# Rating filter
if min_rating is not None and rating < min_rating:
continue
if max_rating is not None and rating > max_rating:
continue
# Rating count filter
if min_rating_count is not None and review_count < min_rating_count:
continue
if max_rating_count is not None and review_count > max_rating_count:
continue
# Category filter
if category_list and category_name not in category_list:
continue
# Brand filter
if brand_list and brand_name not in brand_list:
continue
# Origin country filter
if origin_list and origin_country not in origin_list:
continue
# Competition level filter
if competition_level:
cat_count = category_product_counts.get(category_name, 0)
total_cat_count = len(category_product_counts)
if total_cat_count > 0:
sorted_counts = sorted(category_product_counts.values())
low_threshold = sorted_counts[int(total_cat_count * 0.33)] if sorted_counts else 0
high_threshold = sorted_counts[int(total_cat_count * 0.67)] if sorted_counts else float('inf')
if competition_level == "low" and cat_count > low_threshold:
continue
elif competition_level == "high" and cat_count < high_threshold:
continue
# Potential score filter
if min_potential_score is not None:
max_cat_count = max(category_product_counts.values()) if category_product_counts else 1
normalized_competition = (cat_count / max_cat_count) * 100 if max_cat_count > 0 else 0
potential = (conversion_rate * 0.6) + ((100 - normalized_competition) * 0.4)
if potential < min_potential_score:
continue
# Add product to results
filtered_products.append({
"id": product_id,
"name": product.get("name", ""),
"category": category_name,
"brand": brand_name,
"price": round(price, 2),
"rating": round(rating, 2),
"rating_count": review_count,
"views": views,
"orders": orders,
"reviews": review_count,
"baskets": baskets,
"favorites": favorites,
"conversion_rate": round(conversion_rate, 2),
"origin_country": origin_country,
"image_url": product.get("imageUrl", ""),
"barcode": product.get("barcode", "")
})
log_api.info(f"Filtreleme sonrası: {len(filtered_products)} ürün kaldı")
# Sort products
reverse_order = sort_order == "desc"
if sort_by == "views":
filtered_products.sort(key=lambda x: x["views"], reverse=reverse_order)
elif sort_by == "orders":
filtered_products.sort(key=lambda x: x["orders"], reverse=reverse_order)
elif sort_by == "reviews":
filtered_products.sort(key=lambda x: x["reviews"], reverse=reverse_order)
elif sort_by == "conversion_rate":
filtered_products.sort(key=lambda x: x["conversion_rate"], reverse=reverse_order)
elif sort_by == "price":
filtered_products.sort(key=lambda x: x["price"], reverse=reverse_order)
elif sort_by == "rating":
filtered_products.sort(key=lambda x: x["rating"], reverse=reverse_order)
# Pagination
total_products = len(filtered_products)
total_pages = (total_products + per_page - 1) // per_page
start_idx = (page - 1) * per_page
end_idx = start_idx + per_page
paginated_products = filtered_products[start_idx:end_idx]
log_api.info(f"Sayfalama: {len(paginated_products)} ürün (sayfa {page}/{total_pages})")
return {
"total_products": total_products,
"page": page,
"per_page": per_page,
"total_pages": total_pages,
"products": paginated_products
}
except Exception as e:
import traceback
error_trace = traceback.format_exc()
log_api.error(f"Product finder error: {e}", exc_info=True)
return {
"error": str(e),
"total_products": 0,
"page": page,
"per_page": per_page,
"total_pages": 0,
"products": []
}
# DISABLED: Questions feature removed per user request
# @app.get("/api/reports/{report_id}/questions-summary")
# def questions_summary(report_id: int, refresh: bool = False, db: Session = Depends(get_db)):
# # Try persistent cache first
# if not refresh:
# persisted = _load_json(f"{REPORTS_DIR}/enrich_{report_id}/questions.json")
# if persisted:
# return {"source": "file", **persisted}
# cache_key = f"{report_id}"
# if not refresh and cache_key in questions_cache:
# return {"source": "cache", **questions_cache[cache_key]}
#
# try:
# all_products, _ = load_report_products(db, report_id)
# product_ids = [p.get("id") for p in all_products if p.get("id")]
# summary = {"total_products": len(product_ids), "processed": 0, "total_questions": 0, "top_topics": {}, "sample": []}
#
# for pid in product_ids:
# data = fetch_merchant_questions(pid, page=0, page_size=5)
# if not data:
# _log_enrichment_error(db, report_id=report_id, product_id=int(pid), merchant_id=None,
# endpoint="questions", error_type="request_failed",
# message="questions request failed or timed out")
# continue
# summary["processed"] += 1
# res = data.get("result") or {}
# summary_data = res.get("summary", {})
#
# # Total questions - API'de summary.totalCount olarak geliyor
# total_q = summary_data.get("totalCount") or res.get("totalElements") or res.get("total") or 0
# summary["total_questions"] += total_q
#
# # Questions - API'de "questions" olarak geliyor (content değil)
# questions = res.get("questions", []) or res.get("content", [])
# for q in questions[:2]:
# # Question text - API'de "text" ve "originalText" var
# title = q.get("text") or q.get("originalText") or q.get("title") or q.get("question") or ""
#
# # Answer - API'de nested answer object var
# answer_obj = q.get("answer", {})
# if isinstance(answer_obj, dict):
# answer = answer_obj.get("text") or answer_obj.get("originalText") or ""
# else:
# answer = str(answer_obj) if answer_obj else ""
#
# # Topic - demo'da tag'ler var ama her soru için yok
# topic = q.get("topic") or q.get("category") or "Genel"
# summary["top_topics"][topic] = summary["top_topics"].get(topic, 0) + 1
# summary["sample"].append({"product_id": pid, "title": title[:120], "answer": answer[:160]})
# time.sleep(0.01)
#
# top_topics = sorted([{ "topic": k, "count": v } for k, v in summary["top_topics"].items()], key=lambda x: x["count"], reverse=True)[:30]
# result = {"summary": {**summary, "top_topics": top_topics}}
# questions_cache[cache_key] = result
# return result
# except Exception as e:
# return {"error": str(e), "note": "Network or parsing issue", "summary": {}}
# DISABLED: Similar products feature removed per user request
# @app.get("/api/reports/{report_id}/similar-summary")
# def similar_summary(report_id: int, refresh: bool = False, db: Session = Depends(get_db)):
# # Try persistent cache first
# if not refresh:
# persisted = _load_json(f"{REPORTS_DIR}/enrich_{report_id}/similar.json")
# if persisted:
# return {"source": "file", **persisted}
# cache_key = f"{report_id}"
# if not refresh and cache_key in similar_cache:
# return {"source": "cache", **similar_cache[cache_key]}
#
# try:
# all_products, _ = load_report_products(db, report_id)
# product_ids = [p.get("id") for p in all_products if p.get("id")]
# counter = {}
# examples = []
# for pid in product_ids:
# data = fetch_similar_products(pid, page=0, page_size=8)
# if not data:
# _log_enrichment_error(db, report_id=report_id, product_id=int(pid), merchant_id=None,
# endpoint="similar", error_type="request_failed",
# message="similar request failed or timed out")
# continue
# res = data.get("result") or data
# items = res.get("products") or res.get("items") or []
# sim_ids = []
# for it in items:
# sid = it.get("id") or it.get("productId")
# if sid:
# sidi = int(sid)
# sim_ids.append(sidi)
# counter[sidi] = counter.get(sidi, 0) + 1
# if sim_ids:
# examples.append({"product_id": pid, "similar": sim_ids[:5]})
# time.sleep(0.01)
#
# top_similars = sorted([{ "product_id": k, "count": v } for k, v in counter.items()], key=lambda x: x["count"], reverse=True)[:50]
# result = {"top_similar_products": top_similars, "examples": examples[:50]}
# similar_cache[cache_key] = result
# return result
# except Exception as e:
# return {"error": str(e), "note": "Network or parsing issue", "top_similar_products": []}
# DISABLED: Followers feature removed per user request
# @app.get("/api/reports/{report_id}/merchants/followers")
# def merchant_followers(report_id: int, refresh: bool = False, db: Session = Depends(get_db)):
# # Try persistent cache first
# if not refresh:
# persisted = _load_json(f"{REPORTS_DIR}/enrich_{report_id}/followers.json")
# if persisted:
# return {"source": "file", **persisted}
# cache_key = f"{report_id}"
# if not refresh and cache_key in followers_cache:
# return {"source": "cache", **followers_cache[cache_key]}
#
# try:
# all_products, _ = load_report_products(db, report_id)
# merchant_ids = []
# for p in all_products:
# merchant_listings = p.get("merchantListings", [])
# if merchant_listings:
# merchant = merchant_listings[0].get("merchant", {})
# mid = merchant.get("id")
# if mid:
# merchant_ids.append(int(mid))
# merchant_ids = sorted(list(set(merchant_ids)))
#
# details = {}
# for mid in merchant_ids:
# data = fetch_merchant_followers(mid)
# count = 0
# if data:
# res = data.get("result") or data
# count = res.get("followerCount") or res.get("count") or 0
# else:
# _log_enrichment_error(db, report_id=report_id, product_id=None, merchant_id=int(mid),
# endpoint="followers", error_type="request_failed",
# message="followers request failed or timed out")
# details[mid] = {"followers": _safe_int(count)}
# time.sleep(0.01)
#
# # top merchants by followers
# top_merchants = sorted([
# {"merchant_id": mid, "followers": info["followers"]}
# for mid, info in details.items()
# ], key=lambda x: x["followers"], reverse=True)[:50]
#
# result = {"total_merchants": len(merchant_ids), "details": details, "top_merchants": top_merchants}
# followers_cache[cache_key] = result
# return result
# except Exception as e:
# return {"error": str(e), "note": "Network or parsing issue", "details": {}, "top_merchants": []}
# ============================================================================
# ENRICHMENT MOTORU (Arka Plan Toplama + Kalıcı Cache)
# ============================================================================
# enrichment_progress already defined at line 343 as BoundedCache
def _enrich_build_product_info(all_products):
info = {}
for p in all_products:
pid = p.get("id")
if not pid:
continue
name = (p.get("name") or "Unknown")
brand = p.get("brand", {}).get("name")
display = f"{brand} - {name}" if brand else name
info[int(pid)] = {"name": display[:120]}
return info
def _enrich_report_task(report_id: int):
import time
db = SessionLocal()
try:
enrichment_progress[report_id] = {"status": "running", "step": "init", "done": 0, "total": 2}
all_products, _ = load_report_products(db, report_id)
product_ids = [p.get("id") for p in all_products if p.get("id")]
product_info = _enrich_build_product_info(all_products)
base_dir = f"{REPORTS_DIR}/enrich_{report_id}"
_ensure_dir(base_dir)
# DISABLED: Reviews feature removed per user request
# 1) Reviews - REMOVED
# enrichment_progress[report_id] = {"status": "running", "step": "reviews", "done": 0, "total": 2}
# rev_payload = reviews_summary(report_id, refresh=True, db=db) or {}
# _save_json(f"{base_dir}/reviews.json", rev_payload)
# time.sleep(0.1)
# 2) Social Proof
enrichment_progress[report_id] = {"status": "running", "step": "social", "done": 0, "total": 1}
soc_payload = social_proof(report_id, refresh=True, db=db) or {}
# ürün isimlerini detaylara iliştir
if soc_payload and soc_payload.get("details"):
details = soc_payload["details"]
enriched_details = {int(pid): {**vals, **product_info.get(int(pid), {})} for pid, vals in details.items()}
soc_payload["details"] = enriched_details
_save_json(f"{base_dir}/social.json", soc_payload)
time.sleep(0.1)
# Enrichment bitti, konsolide dosya oluştur
enrichment_progress[report_id] = {"status": "running", "step": "consolidate", "done": 1, "total": 2}
try:
from data_consolidator import build_consolidated_report, save_consolidated_report
consolidated = build_consolidated_report(report_id, db, REPORTS_DIR, social_data=soc_payload)
if consolidated:
save_consolidated_report(report_id, consolidated, REPORTS_DIR)
log_api.info(f"Konsolide rapor oluşturuldu: report {report_id}")
except Exception as ce:
log_api.warning(f"Konsolidasyon hatası (enrichment devam eder): {ce}", exc_info=True)
# DISABLED: Questions, similar products, and followers removed per user request
# # 3) Questions
# enrichment_progress[report_id] = {"status": "running", "step": "questions", "done": 2, "total": 5}
# q_payload = questions_summary(report_id, refresh=True, db=db) or {}
# _save_json(f"{base_dir}/questions.json", q_payload)
# time.sleep(0.1)
#
# # 4) Similar
# enrichment_progress[report_id] = {"status": "running", "step": "similar", "done": 3, "total": 5}
# s_payload = similar_summary(report_id, refresh=True, db=db) or {}
# _save_json(f"{base_dir}/similar.json", s_payload)
# time.sleep(0.1)
#
# # 5) Followers
# enrichment_progress[report_id] = {"status": "running", "step": "followers", "done": 4, "total": 5}
# f_payload = merchant_followers(report_id, refresh=True, db=db) or {}
# _save_json(f"{base_dir}/followers.json", f_payload)
# time.sleep(0.1)
# Invalidate dashboard cache so next request gets fresh data with social proof
cache_key = f"dashboard_{report_id}"
if isinstance(dashboard_cache, dict) and cache_key in dashboard_cache:
del dashboard_cache[cache_key]
elif hasattr(dashboard_cache, 'cache') and cache_key in dashboard_cache.cache:
del dashboard_cache.cache[cache_key]
log_api.info(f"Dashboard cache invalidated for report {report_id} after enrichment")
enrichment_progress[report_id] = {"status": "completed", "step": "done", "done": 2, "total": 2}
except Exception as e:
enrichment_progress[report_id] = {"status": "error", "error": str(e)}
finally:
db.close()
@app.post("/api/reports/{report_id}/enrich/start")
def start_enrichment(report_id: int, background: BackgroundTasks):
enrichment_progress[report_id] = {"status": "queued", "step": "queued"}
background.add_task(_enrich_report_task, report_id)
return {"status": "started", "report_id": report_id}
@app.get("/api/reports/{report_id}/enrich/status")
def enrichment_status(report_id: int):
result = enrichment_progress.get(report_id)
return result if result is not None else {"status": "unknown"}
# ============================================================================
# HIDDEN CHAMPIONS ENDPOINT
# ============================================================================
@app.get("/api/reports/{report_id}/hidden-champions")
def get_hidden_champions(
report_id: int,
min_rating: float = 4.5,
max_review_count: int = 50,
social_multiplier: float = 1.5,
min_score: int = 30,
min_orders: int = 0, # Minimum satış sayısı (0 = sosyal veri yoksa da göster)
limit: int = 50,
db: Session = Depends(get_db)
):
"""
Gizli şampiyonları bul (özelleştirilmiş filtreler)
Rating >= 4.5, Yorum < 50, Orders >= 1, Social Proof kategorinin 1.5 katı üzerinde
"""
try:
from analytics.champion_finder import HiddenChampionFinder
all_products, categories_data = load_report_products(db, report_id)
social_data = _load_json(f"{REPORTS_DIR}/enrich_{report_id}/social.json") or {}
finder = HiddenChampionFinder()
filters = {
"min_rating": min_rating,
"max_review_count": max_review_count,
"social_multiplier": social_multiplier,
"min_score": min_score,
"min_orders": min_orders, # Minimum satış kontrolü
"limit": limit
}
# Sync olarak çalıştır
result = finder.find(all_products, social_data, filters)
return result
except HTTPException:
raise
except Exception as e:
import traceback
return {
"error": str(e),
"traceback": traceback.format_exc(),
"total_found": 0,
"hidden_champions": []
}
# ============================================================================
# ANALYTICS TEST ENDPOINT
# ============================================================================
@app.get("/api/reports/{report_id}/test-analytics")
def test_analytics(report_id: int, db: Session = Depends(get_db)):
"""
Test endpoint: HHI Index ve Risk Skoru hesaplama testi
Mevcut bir raporun analytics metriklerini test eder
"""
from analytics.metrics import (
calculate_hhi_index,
calculate_competition_score_from_hhi,
get_rating_value,
get_review_count
)
import os
import json
try:
pass
# 1. Raporu yükle
report = db.query(Report).filter(Report.id == report_id).first()
if not report:
raise HTTPException(status_code=404, detail="Report not found")
# 2. Ürünleri yükle
all_products, categories_data = load_report_products(db, report_id)
if not all_products:
return {
"error": "No products found in report",
"report_id": report_id,
"report_name": report.name
}
# 3. HHI Index hesapla
hhi_index = calculate_hhi_index(all_products)
# 4. Rekabet skoru hesapla
competition_score = calculate_competition_score_from_hhi(hhi_index)
# 5. Marka dağılımı (Counter ile optimize edildi)
from collections import Counter
brand_names = [
p.get("brand", {}).get("name", "Unknown")
for p in all_products
if p.get("brand", {}).get("name")
]
brand_counts = Counter(brand_names)
top_brands = brand_counts.most_common(10)
# 6. Basit risk skoru (sadece rekabet bazlı)
# Bu basit bir test, tam risk skoru için risk_analyzer.py gerekli
risk_level = "DÜŞÜK" if competition_score >= 70 else "ORTA" if competition_score >= 50 else "YÜKSEK"
# 7. Ek metrikler
total_products = len(all_products)
total_brands = len(brand_counts)
# Ortalama rating
ratings = [get_rating_value(p) for p in all_products if get_rating_value(p) > 0]
avg_rating = sum(ratings) / len(ratings) if ratings else 0
# Ortalama fiyat
prices = [_extract_price(p) for p in all_products if _extract_price(p) > 0]
avg_price = sum(prices) / len(prices) if prices else 0
# 8. HHI yorumu ve stratejik tavsiye
if hhi_index < 1500:
hhi_comment = "Düşük konsantrasyon (rekabetçi pazar)"
strategic_advice = "Marka sadakati yok, SEO ve doğru fiyatlama ile pazar payı kapma potansiyeli yüksek!"
market_opportunity_score = round(100 - (hhi_index / 15), 2)
elif hhi_index < 2500:
hhi_comment = "Orta konsantrasyon"
strategic_advice = "Orta seviye rekabet var, marka gücü ve fiyat stratejisi önemli."
market_opportunity_score = round(70 - ((hhi_index - 1500) / 10), 2)
else:
hhi_comment = "Yüksek konsantrasyon (tekelci pazar)"
strategic_advice = "Güçlü markalar hakim, giriş için yüksek yatırım gerekli."
market_opportunity_score = round(max(0, 55 - ((hhi_index - 2500) / 50)), 2)
# Top 10 marka toplam payı
top_10_total_share = sum((count / total_products) * 100 for _, count in top_brands)
# Stratejik yorum (HHI düşükse)
if hhi_index < 100 and top_10_total_share < 20:
strategic_advice = f"Marka sadakati yok, SEO ve doğru fiyatlama ile pazar payı kapma potansiyeli %{market_opportunity_score:.0f}!"
return {
"success": True,
"report_id": report_id,
"report_name": report.name,
"metrics": {
"total_products": total_products,
"total_brands": total_brands,
"avg_rating": round(avg_rating, 2),
"avg_price": round(avg_price, 2)
},
"hhi_analysis": {
"hhi_index": hhi_index,
"comment": hhi_comment,
"competition_score": round(competition_score, 2),
"risk_level": risk_level,
"strategic_advice": strategic_advice,
"market_opportunity_score": market_opportunity_score,
"top_10_market_share": round(top_10_total_share, 2)
},
"top_brands": [
{
"brand": brand,
"product_count": count,
"market_share": round((count / total_products) * 100, 2)
}
for brand, count in top_brands
],
"market_share_validation": {
"top_10_total_share": round(sum((count / total_products) * 100 for _, count in top_brands), 2),
"all_brands_total_share": 100.0, # Doğrulama için
"total_brands_count": total_brands
},
"test_result": {
"hhi_calculated": hhi_index > 0,
"competition_score_calculated": competition_score >= 0,
"status": "✅ Test başarılı" if hhi_index > 0 and competition_score >= 0 else "❌ Test başarısız"
}
}
except HTTPException:
raise
except Exception as e:
import traceback
return {
"success": False,
"error": str(e),
"traceback": traceback.format_exc(),
"report_id": report_id
}
# ============================================================================
# GOOGLE TRENDS & TRAFFIC SOURCES ENDPOINTS
# ============================================================================
@app.get("/api/products/traffic-sources")
async def get_traffic_sources_bulk(product_names: str):
"""
Get estimated traffic sources for multiple products
Args:
product_names: Comma-separated product names
Returns:
Dict with traffic source estimates for each product
"""
try:
# Split product names
names_list = [name.strip() for name in product_names.split(',')]
results = {}
for product_name in names_list[:10]: # Limit to 10 products at once
if not product_name:
continue
# Use default social proof values (will be replaced with real data in frontend)
traffic_data = estimate_traffic_sources(
product_name=product_name,
instagram_views=0,
tiktok_views=0,
twitter_shares=0
)
results[product_name] = traffic_data
return {
'success': True,
'results': results,
'total': len(results)
}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/products/traffic-sources/estimate")
async def estimate_product_traffic_sources(request_data: dict):
"""
Estimate traffic sources for a single product with social proof data
Request Body:
{
"product_name": "Casio Edifice Kol Saati",
"instagram_views": 10000,
"tiktok_views": 5000,
"twitter_shares": 500
}
Returns:
Traffic source percentage distribution
"""
try:
product_name = request_data.get('product_name', '')
instagram_views = request_data.get('instagram_views', 0)
tiktok_views = request_data.get('tiktok_views', 0)
twitter_shares = request_data.get('twitter_shares', 0)
if not product_name:
raise HTTPException(status_code=400, detail="product_name is required")
# Estimate traffic sources
traffic_data = estimate_traffic_sources(
product_name=product_name,
instagram_views=instagram_views,
tiktok_views=tiktok_views,
twitter_shares=twitter_shares
)
return {
'success': True,
'product_name': product_name,
'traffic_sources': traffic_data
}
except HTTPException:
raise
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.get("/api/google-trends/test")
async def test_google_trends(product_name: str = "iPhone 15"):
"""
Test endpoint for Google Trends API
Args:
product_name: Product name to search (default: iPhone 15)
Returns:
Google Trends data
"""
try:
trends_data = fetch_google_trends(product_name)
return {
'success': True,
'product_name': product_name,
'trends_data': trends_data
}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
# ---------------------------------------------------------------------------
# Periodic resource logger (runs every 60s in background)
# ---------------------------------------------------------------------------
_resource_logger = get_logger("resources")
async def _periodic_resource_log():
"""Log cache sizes and circuit breaker state every 60 seconds."""
while True:
await asyncio.sleep(60)
try:
cb_status = _social_proof_breaker.get_status()
_resource_logger.info(
"Resource snapshot",
extra={
"cache_size": len(dashboard_cache) if isinstance(dashboard_cache, dict) else len(dashboard_cache.cache),
"cb_state": cb_status["status"],
"failures": cb_status["failures"],
},
)
except Exception:
pass # Never crash the background task
@app.on_event("startup")
async def _start_resource_logger():
asyncio.create_task(_periodic_resource_log())
_resource_logger.info("Periodic resource logger started (60s interval)")
# ── Queue Worker Lifecycle ──────────────────────────────────────────────
_queue_worker = None
@app.on_event("startup")
async def _start_queue_worker():
global _queue_worker
from queue_worker import QueueWorker
_queue_worker = QueueWorker(poll_interval=2.0)
_queue_worker.start()
@app.on_event("shutdown")
async def _stop_queue_worker():
global _queue_worker
if _queue_worker:
_queue_worker.stop()
_queue_worker = None
# ---------------------------------------------------------------------------
# Public product lookup endpoint (Ne Kadar Sattı? feature)
# ---------------------------------------------------------------------------
@app.get("/api/product/lookup", dependencies=[Depends(verify_api_key)])
def product_lookup(url: str, request: Request):
ip = request.headers.get("X-Forwarded-For", request.client.host or "unknown").split(",")[0].strip()
if not _check_ip_rate_limit(ip):
raise HTTPException(status_code=429, detail="Çok fazla istek. Bir dakika sonra tekrar deneyin.")
if not url or "trendyol.com" not in url.lower():
raise HTTPException(status_code=400, detail="Geçerli bir Trendyol URL'si girin.")
m = _TRENDYOL_URL_RE.search(url)
if not m:
raise HTTPException(status_code=400, detail="URL'den ürün ID'si alınamadı.")
product_id = int(m.group(1))
cached = product_lookup_cache.get(str(product_id))
if cached:
return {"source": "cache", "productId": product_id, **cached}
if _social_proof_breaker.is_open():
raise HTTPException(status_code=503, detail="Servis geçici olarak kullanılamıyor.")
data = fetch_social_proof([product_id])
if not data:
_social_proof_breaker.record_failure()
raise HTTPException(status_code=404, detail="Bu ürün için veri bulunamadı.")
items = data.get("result") or []
pd_item = next((it for it in items if it.get("contentId") == product_id), None)
if not pd_item:
raise HTTPException(status_code=404, detail="Sosyal kanıt verisi bulunamadı.")
result = {k: pd_item.get(k, 0) for k in ["orderCount", "favoriteCount", "pageViewCount", "basketCount"]}
product_lookup_cache.set(str(product_id), result)
_social_proof_breaker.record_success()
return {"source": "live", "productId": product_id, **result}
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8001)
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