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本指南介绍如何安装 Bright Data Python SDK 并调用其全部功能：URL 抓取、搜索引擎、平台专用 scrapers（LinkedIn、Amazon、Instagram、TikTok、YouTube、Reddit、Pinterest、ChatGPT、Perplexity、Digikey）、Discover API、Scraper Studio、数据集与 Browser API。 Final Banner Pn

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安装与配置

通过 pip 安装包： 
pip install brightdata-sdk

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配置

您必须提供您的 API token。可在 Bright Data 控制面板 中找到。 选项 1：环境变量（推荐） 
export BRIGHTDATA_API_TOKEN="your_api_token_here"
选项 2：直接初始化 
# 异步客户端
from brightdata import BrightDataClient

async with BrightDataClient(token="your_api_token_here") as client:
    ...

# 同步客户端
from brightdata import SyncBrightDataClient

with SyncBrightDataClient(token="your_api_token_here") as client:
    ...

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基本用法

简单脚本使用 SyncBrightDataClient。需要高并发时配合 asyncio 使用 BrightDataClient。 
from brightdata import SyncBrightDataClient

with SyncBrightDataClient() as client:
    # 抓取 URL
    data = client.scrape_url("https://example.com")
    print(f"Result: {data.data}")

    # Google 搜索
    search = client.search.google(query="Bright Data")
    print(f"Found: {len(search.data)}")

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发起抓取和网络搜索

from brightdata import BrightDataClient

client = BrightDataClient()

# Google 搜索
results = client.search.google(
    query="best shoes of 2025",
    location="United States",
    language="en",
    num_results=20
)

# Bing 搜索
results = client.search.bing(
    query="python tutorial",
    location="United States"
)

# Yandex 搜索
results = client.search.yandex(
    query="latest news",
    location="Germany"
)

if results.success:
    print(f"Cost: ${results.cost:.4f}")
    print(f"Time: {results.elapsed_ms():.2f}ms")
当处理多个查询或 URL 时，请求会并发执行以获得最佳性能。

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使用平台专用 scrapers 提取结构化数据

从 Amazon、LinkedIn、Facebook、Instagram、TikTok、YouTube、Reddit、Pinterest、ChatGPT、Perplexity 与 Digikey 提取结构化数据。 
# Async
from brightdata import BrightDataClient

async with BrightDataClient() as client:
    products = await client.scrape.amazon.products(url="https://amazon.com/dp/B0CRMZHDG8")
    reviews = await client.scrape.amazon.reviews(
        url="https://amazon.com/dp/B0CRMZHDG8",
        pastDays=30,
        keyWord="quality"
    )
    sellers = await client.scrape.amazon.sellers(
        url="https://amazon.com/sp?seller=AXXXXXXXXXXX"
    )

# Sync
from brightdata import SyncBrightDataClient

with SyncBrightDataClient() as client:
    products = client.scrape.amazon.products(url="https://amazon.com/dp/B0CRMZHDG8")
    reviews = client.scrape.amazon.reviews(
        url="https://amazon.com/dp/B0CRMZHDG8",
        pastDays=30,
        keyWord="quality"
    )
    sellers = client.scrape.amazon.sellers(
        url="https://amazon.com/sp?seller=AXXXXXXXXXXX"
    )

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使用 AI 排序搜索网页（Discover API）

# Async
from brightdata import BrightDataClient

async with BrightDataClient() as client:
    result = await client.discover(
        query="AI trends 2026",
        intent="latest technology developments"
    )
    # result.data 形如 [{ title, link, description, relevance_score }]

    # 手动：触发、等待并获取
    job = await client.discover_trigger(
        query="SaaS pricing",
        intent="competitor pricing strategies"
    )
    await job.wait(timeout=60)
    data = await job.fetch()

# Sync
from brightdata import SyncBrightDataClient

with SyncBrightDataClient() as client:
    result = client.discover(
        query="AI trends 2026",
        intent="latest technology developments"
    )

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运行您的自定义 Scraper Studio scrapers

# Async
from brightdata import BrightDataClient

async with BrightDataClient() as client:
    data = await client.scraper_studio.run(
        collector="c_abc123",
        input={"url": "https://example.com/product/1"}
    )
    job = await client.scraper_studio.trigger(
        "c_abc123", {"url": "https://example.com/product/1"}
    )
    data = await job.wait_and_fetch(timeout=120)
    status = await client.scraper_studio.status("j_abc123")

# Sync
from brightdata import SyncBrightDataClient

with SyncBrightDataClient() as client:
    data = client.scraper_studio.run(
        collector="c_abc123",
        input={"url": "https://example.com/product/1"}
    )
    status = client.scraper_studio.status("j_abc123")

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Datasets API

访问预先采集的数据快照。 
from brightdata import SyncBrightDataClient

with SyncBrightDataClient() as client:
    # 1. 申请带筛选条件的快照
    print("Requesting snapshot...")
    snapshot_id = client.datasets.imdb_movies(
        filter={"name": "year", "operator": "=", "value": 2024},
        records_limit=10
    )

    # 2. 下载（SDK 会自动轮询）
    print(f"Snapshot {snapshot_id} ready. Downloading...")
    data = client.datasets.imdb_movies.download(snapshot_id)
    print(f"Downloaded {len(data)} records.")
在 IDE 中将鼠标悬停在 BrightDataClient 类或其任意方法上，即可查看可用参数、类型提示与使用示例。SDK 提供完整的 IntelliSense 支持。

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使用 dataclass 负载实现类型安全

SDK 提供带运行时校验和辅助属性的 dataclass payloads。 
from brightdata import BrightDataClient
from brightdata.payloads import (
    AmazonProductPayload,
    LinkedInJobSearchPayload,
    ChatGPTPromptPayload
)

client = BrightDataClient()

# 带校验的 Amazon 商品
amazon_payload = AmazonProductPayload(
    url="https://amazon.com/dp/B123456789",
    reviews_count=50  # 运行时校验
)
print(f"ASIN: {amazon_payload.asin}")  # 辅助属性
print(f"Domain: {amazon_payload.domain}")

# LinkedIn 招聘搜索
linkedin_payload = LinkedInJobSearchPayload(
    keyword="python developer",
    location="San Francisco",
    remote=True
)
print(f"Remote search: {linkedin_payload.is_remote_search}")

# 与客户端一起使用
result = client.scrape.amazon.products(**amazon_payload.to_dict())

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连接至 Scraping Browser

通过 Browser API 将 Playwright 连接到 Bright Data 的云端浏览器。 
from brightdata import BrightDataClient
from playwright.async_api import async_playwright

client = BrightDataClient(
    browser_username="brd-customer-xxxx-zone-scraping_browser1",
    browser_password="YOUR_ZONE_PASSWORD",
)

async with async_playwright() as pw:
    browser = await pw.chromium.connect_over_cdp(client.browser.get_connect_url())
    page = await browser.new_page()
    await page.goto("https://example.com", timeout=120000)
    print(await page.content())
    await browser.close()

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使用 CLI 工具

SDK 提供命令行界面以便在终端中使用。 
# 搜索操作
brightdata search google "python tutorial" --location "United States"
brightdata search linkedin jobs --keyword "python developer" --remote

# 抓取操作
brightdata scrape amazon products "https://amazon.com/dp/B123"
brightdata scrape linkedin profiles "https://linkedin.com/in/johndoe"

# 通用网页抓取
brightdata scrape generic "https://example.com" --output-format pretty

# 将结果保存到文件
brightdata search google "AI news" --output-file results.json

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异步用法获取更高性能

并发操作时，将 URL 列表传递给 scrape_url，并在异步上下文管理器中运行。 
import asyncio
from brightdata import BrightDataClient

async def main():
    async with BrightDataClient() as client:
        results = await client.scrape_url([
            "https://example1.com",
            "https://example2.com",
            "https://example3.com",
        ], mode="async", poll_timeout=180)

        for result in results:
            print(result.data)

asyncio.run(main())

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资源

GitHub 仓库

查看源代码、示例并贡献代码

示例目录

覆盖所有功能的 10+ 个示例

PyPI 页面

包列表与发布历史

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更新内容

功能说明
Discover APIclient.discover() / client.discover_trigger()：基于意图的 AI 相关性排序网页搜索。同步与异步客户端均可使用。
Scraper Studioclient.scraper_studio.run/trigger/status()：触发并获取您的自定义 Scraper Studio scrapers。同步与异步客户端均可使用。
Browser APIclient.browser.get_connect_url()：将 Playwright/Puppeteer 连接到 Bright Data 的云端浏览器。取代 client.connect_browser()。
新增 scrapersclient.scrape.* 新增 TikTok、YouTube、Reddit、Pinterest、Digikey、Perplexity
平台搜索client.search.linkedin / amazon / instagram / tiktok / youtube / pinterest / chatgpt：按参数发现内容，而不仅是按 URL。
126+ 数据集通过 client.datasets.* 访问完整目录，支持 .sample() 与 .download()
完整的同步支持SyncBrightDataClient 现已覆盖全部功能：scrapers、search、discover、scraper studio、browser