export SCRAPELESS_API_TOKEN=sk_your_token_here

{
  "actor": "scraper.amazon",
  "input": {
    "type":     "rufus",
    "keywords": "macbook air m3 是否适合视频编辑",
    "domain":   "www.amazon.es"
  }
}

{
  "html": "id:CHUNK_0\nevent:context\ndata:{...}\n\nid:CHUNK_1\nevent:affordance\n...",
  "metadata": {
    "rawUrl": "https://api.scrapeless.com/storage/scrapeless.scraper.amazon/.../<id>.html",
    "type":   "rufus"
  },
  "result": {
    "request_context":   { "requestId": "TMWTVKB12QFTQEV9D2GJ", "sessionId": "257-9398007-5193547", "bsr": {...} },
    "user_query":        "macbook air m3适合视频编辑吗",
    "interim_messages":  ["检查中...", "收集数据中…"],
    "products":          [ { "asin": "B08N5TLVQ2", "title": "苹果MacBook Air...", "rating": "4.8", "reviews": "2.045", ... }, ... ],
    "related_questions": ["MacBook Air与MacBook Pro的区别", "哪个MacBook更适合学生？", ...],
    "feedback_controls": { "groupId": "...", "text": "..." }
  }
}

import os
import requests

URL = "https://api.scrapeless.com/api/v1/scraper/request"
HEADERS = {
    "x-api-token":  os.environ["SCRAPELESS_API_TOKEN"],
    "Content-Type": "application/json",
}
BODY = {
    "actor": "scraper.amazon",
    "input": {
        "type":     "rufus",
        "keywords": "macbook air m3适合视频编辑吗",
        "domain":   "www.amazon.es",
    },
}

resp = requests.post(URL, headers=HEADERS, json=BODY, timeout=60)
resp.raise_for_status()
data = resp.json()

# 解析的Rufus输出
for product in data["result"]["products"]:
    print(f"{product['asin']}  {product['rating']}★  {product['title'][:80]}")

print("\n相关问题：")
for q in data["result"]["related_questions"]:
    print(f"  - {q}")

const URL = "https://api.scrapeless.com/api/v1/scraper/request";

const resp = await fetch(URL, {
  method: "POST",
  headers: {
    "x-api-token":  process.env.SCRAPELESS_API_TOKEN,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    actor: "scraper.amazon",
    input: {
      type:     "rufus",
      keywords: "macbook air m3适合视频编辑吗",
      domain:   "www.amazon.es",
    },
  }),
});
if (!resp.ok) throw new Error(`HTTP ${resp.status}: ${await resp.text()}`);

const data = await resp.json();

for (const p of data.result.products) {
  console.log(`${p.asin}  ${p.rating}★  ${p.title.slice(0, 80)}`);
}

console.log("\n相关问题：");

for (const q of data.result.related_questions) {
  console.log(`  - ${q}`);
}

import os, json, requests

resp = requests.post(URL, headers=HEADERS, json={
    "actor": "scraper.amazon",
    "input": {
        "type":         "rufus",
        "keywords":     "macbook air m3 适合视频编辑吗",
        "domain":       "www.amazon.es",
        "is_sse_data":  True,
    },
}, stream=True, timeout=60)

event_type, data_buf = None, []
for line in resp.iter_lines(decode_unicode=True):
    if line is None:
        continue
    if line.startswith("event:"):
        event_type = line[len("event:"):].strip()
    elif line.startswith("data:"):
        data_buf.append(line[len("data:"):])
    elif line == "":
        if event_type and data_buf:
            payload = json.loads("".join(data_buf))
            print(event_type, "->", str(payload)[:120])
        event_type, data_buf = None, []

const resp = await fetch(URL, {
  method: "POST",
  headers: { "x-api-token": process.env.SCRAPELESS_API_TOKEN, "Content-Type": "application/json" },
  body: JSON.stringify({
    actor: "scraper.amazon",
    input: {
      type: "rufus", keywords: "macbook air m3 适合视频编辑吗",
      domain: "www.amazon.es", is_sse_data: true,
    },
  }),
});

const reader = resp.body.getReader();
const decoder = new TextDecoder("utf-8");
let buf = "";
while (true) {
  const { value, done } = await reader.read();
  if (done) break;
  buf += decoder.decode(value, { stream: true });
  const frames = buf.split("\n\n");
  buf = frames.pop();
  for (const frame of frames) {
    const lines = frame.split("\n");
    const evtLine = lines.find(l => l.startsWith("event:"));
    const dataLine = lines.find(l => l.startsWith("data:"));
    if (evtLine && dataLine) {
      const event = evtLine.slice("event:".length).trim();
      const data  = JSON.parse(dataLine.slice("data:".length));
      console.log(event, "->", JSON.stringify(data).slice(0, 120));
    }
  }
}