Dropshipping Product Research API Guide

import requests, os

H = {"x-api-key": os.environ["SCAVIO_API_KEY"]}

def search_platform(query: str, platform: str):
    """Search a platform and return structured results."""
    resp = requests.post("https://api.scavio.dev/api/v1/search",
        headers=H, json={"query": query, "platform": platform})
    return resp.json().get("organic_results", [])

def find_trending_products(categories: list):
    """Search Amazon for trending products in each category."""
    products = []
    for cat in categories:
        results = search_platform(f"best selling {cat} 2026", "amazon")
        for r in results[:5]:
            products.append({
                "category": cat,
                "title": r.get("title", ""),
                "price": r.get("price"),
                "rating": r.get("rating"),
                "url": r.get("link", ""),
                "platform": "amazon",
            })
    return products

categories = ["kitchen gadgets", "phone accessories", "home organization"]
trending = find_trending_products(categories)
# 3 categories = 3 API calls = $0.015

def cross_check_prices(products: list):
    """Check Walmart and Google for price comparisons."""
    enriched = []
    for p in products[:10]:  # Top 10 products
        short_title = " ".join(p["title"].split()[:5])

        # Check Walmart price
        walmart = search_platform(short_title, "walmart")
        walmart_price = walmart[0].get("price") if walmart else None

        # Check Google Shopping for demand
        google = search_platform(f"{short_title} buy", "google")
        has_ads = bool(any("ad" in str(r).lower() for r in google[:3]))

        enriched.append({
            **p,
            "walmart_price": walmart_price,
            "has_google_ads": has_ads,
            "demand_signal": "high" if has_ads else "moderate",
        })
    return enriched

# 10 products x 2 platforms = 20 API calls = $0.10
enriched = cross_check_prices(trending)

import csv
from datetime import date

def daily_product_report(categories: list, output_file: str = None):
    """Generate daily product opportunity report."""
    trending = find_trending_products(categories)
    enriched = cross_check_prices(trending)

    # Score opportunities
    for p in enriched:
        score = 0
        if p.get("has_google_ads"):
            score += 2  # demand signal
        if p.get("rating") and float(str(p["rating"]).replace(",", ".")) >= 4.0:
            score += 1  # quality signal
        p["opportunity_score"] = score

    # Sort by score
    enriched.sort(key=lambda x: x["opportunity_score"], reverse=True)

    # Export to CSV
    if output_file and enriched:
        with open(output_file, "w", newline="") as f:
            writer = csv.DictWriter(f, fieldnames=enriched[0].keys())
            writer.writeheader()
            writer.writerows(enriched)

    return enriched

# Total daily cost: ~25 API calls = $0.125/day = $3.75/mo
report = daily_product_report(
    ["kitchen gadgets", "phone accessories", "home organization"],
    f"products_{date.today().isoformat()}.csv"
)