Test de résistance de rentabilité des produits Amazon FBA

import requests, os, json

API_KEY = os.environ["SCAVIO_API_KEY"]
H = {"x-api-key": API_KEY, "Content-Type": "application/json"}
TH = {"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"}

def search_amazon(product: str) -> dict:
    resp = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers=H,
        json={"query": product, "platform": "amazon"},
        timeout=15,
    )
    results = resp.json().get("organic_results", [])
    prices = [r.get("price", 0) for r in results if r.get("price")]
    reviews = [r.get("reviews", 0) for r in results if r.get("reviews")]
    return {
        "competitor_count": len(results),
        "price_min": min(prices) if prices else 0,
        "price_max": max(prices) if prices else 0,
        "avg_reviews": sum(reviews) / len(reviews) if reviews else 0,
    }

def search_google_demand(product: str) -> dict:
    resp = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers=H,
        json={"query": f"buy {product}", "country_code": "us"},
        timeout=15,
    )
    data = resp.json()
    results = data.get("organic_results", [])
    buying_intent = sum(1 for r in results if any(kw in r.get("title", "").lower() for kw in ["buy", "best", "review", "price", "deal"]))
    return {"result_count": len(results), "buying_intent_signals": buying_intent, "has_shopping": "shopping_results" in data}

def search_tiktok_trend(product: str) -> dict:
    resp = requests.post(
        "https://api.scavio.dev/api/v1/tiktok/search",
        headers=TH,
        json={"query": product},
        timeout=15,
    )
    results = resp.json().get("results", [])
    return {"tiktok_results": len(results), "trending": len(results) > 5}

def stress_test(product: str) -> dict:
    amazon = search_amazon(product)
    google = search_google_demand(product)
    tiktok = search_tiktok_trend(product)

    score = 0
    if amazon["competitor_count"] < 15: score += 25
    if amazon["avg_reviews"] < 500: score += 20
    if amazon["price_max"] > 25: score += 20
    if google["buying_intent_signals"] > 3: score += 15
    if tiktok["trending"]: score += 20

    return {
        "product": product, "score": score,
        "verdict": "GO" if score >= 60 else "MAYBE" if score >= 40 else "NO-GO",
        "amazon": amazon, "google": google, "tiktok": tiktok,
    }

result = stress_test("portable blender for smoothies")
print(f"Product: {result['product']}")
print(f"Score: {result['score']}/100 -> {result['verdict']}")
print(f"Amazon: {result['amazon']['competitor_count']} competitors, {result['amazon']['price_min']}-{result['amazon']['price_max']} USD")
print(f"TikTok trending: {result['tiktok']['trending']}")

const H = {'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'};
const TH = {'Authorization': 'Bearer '+process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'};

async function searchAmazon(product) {
  const r = await fetch('https://api.scavio.dev/api/v1/search', {method:'POST', headers:H, body:JSON.stringify({query:product, platform:'amazon'})});
  const results = (await r.json()).organic_results || [];
  const prices = results.map(r=>r.price).filter(Boolean);
  const reviews = results.map(r=>r.reviews).filter(Boolean);
  return {competitorCount:results.length, priceMin:Math.min(...prices)||0, priceMax:Math.max(...prices)||0, avgReviews:reviews.length?reviews.reduce((a,b)=>a+b,0)/reviews.length:0};
}

async function searchGoogleDemand(product) {
  const r = await fetch('https://api.scavio.dev/api/v1/search', {method:'POST', headers:H, body:JSON.stringify({query:'buy '+product, country_code:'us'})});
  const data = await r.json();
  const results = data.organic_results || [];
  const buyingIntent = results.filter(r=>['buy','best','review','price','deal'].some(kw=>(r.title||'').toLowerCase().includes(kw))).length;
  return {resultCount:results.length, buyingIntentSignals:buyingIntent, hasShopping:'shopping_results' in data};
}

async function searchTiktokTrend(product) {
  const r = await fetch('https://api.scavio.dev/api/v1/tiktok/search', {method:'POST', headers:TH, body:JSON.stringify({query:product})});
  const results = (await r.json()).results || [];
  return {tiktokResults:results.length, trending:results.length>5};
}

async function stressTest(product) {
  const [amazon, google, tiktok] = await Promise.all([searchAmazon(product), searchGoogleDemand(product), searchTiktokTrend(product)]);
  let score = 0;
  if (amazon.competitorCount<15) score+=25;
  if (amazon.avgReviews<500) score+=20;
  if (amazon.priceMax>25) score+=20;
  if (google.buyingIntentSignals>3) score+=15;
  if (tiktok.trending) score+=20;
  const verdict = score>=60?'GO':score>=40?'MAYBE':'NO-GO';
  return {product, score, verdict, amazon, google, tiktok};
}

const result = await stressTest('portable blender for smoothies');
console.log('Product: '+result.product);
console.log('Score: '+result.score+'/100 -> '+result.verdict);
console.log('Amazon: '+result.amazon.competitorCount+' competitors, $'+result.amazon.priceMin+'-$'+result.amazon.priceMax);
console.log('TikTok trending: '+result.tiktok.trending);