Python SDK

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。

安装与配置

通过 pip 安装包：

pip install brightdata-sdk

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:
    ...

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)}")

import asyncio
from brightdata import BrightDataClient

async def main():
    async with BrightDataClient() as client:
        result = await client.scrape_url("https://example.com")
        print(result.data)

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

if __name__ == "__main__":
    asyncio.run(main())

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")

from brightdata import BrightDataClient

client = BrightDataClient()

# 抓取单个 URL
result = client.scrape_url("https://example.com")

# 并发抓取多个 URL
urls = [
    "https://example1.com",
    "https://example2.com",
    "https://example3.com"
]
results = client.scrape_url(urls)

for r in results:
    if r.success:
        print(f"Success: {r.data[:200]}...")
        r.save_to_file(f"result_{hash(r.data)}.json")

当处理多个查询或 URL 时，请求会并发执行以获得最佳性能。

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"
    )

# Async：按 URL 采集，然后按参数发现
from brightdata import BrightDataClient

async with BrightDataClient() as client:
    profiles = await client.scrape.linkedin.profiles(
        url="https://www.linkedin.com/in/johndoe"
    )
    companies = await client.scrape.linkedin.companies(
        url="https://www.linkedin.com/company/bright-data"
    )
    jobs = await client.scrape.linkedin.jobs(
        url="https://www.linkedin.com/jobs/view/123456"
    )
    posts = await client.scrape.linkedin.posts(
        url="https://www.linkedin.com/feed/update/urn:li:activity:123"
    )

    # 按参数发现
    job_results = await client.search.linkedin.jobs(
        keyword="python developer",
        location="New York",
        remote=True
    )
    profile_results = await client.search.linkedin.profiles(
        firstName="John",
        lastName="Doe"
    )

# Sync
from brightdata import SyncBrightDataClient

with SyncBrightDataClient() as client:
    profiles = client.scrape.linkedin.profiles(url="https://www.linkedin.com/in/johndoe")
    companies = client.scrape.linkedin.companies(
        url="https://www.linkedin.com/company/bright-data"
    )
    jobs = client.scrape.linkedin.jobs(url="https://www.linkedin.com/jobs/view/123456")
    posts = client.scrape.linkedin.posts(
        url="https://www.linkedin.com/feed/update/urn:li:activity:123"
    )

# Async
from brightdata import BrightDataClient

async with BrightDataClient() as client:
    await client.scrape.facebook.posts_by_profile(
        url="https://www.facebook.com/nasa", num_of_posts=10
    )
    await client.scrape.facebook.posts_by_group(
        url="https://www.facebook.com/groups/example"
    )
    await client.scrape.facebook.posts_by_url(
        url="https://www.facebook.com/post/123456"
    )
    await client.scrape.facebook.comments(
        url="https://www.facebook.com/post/123456", num_of_comments=100
    )
    await client.scrape.facebook.reels(url="https://www.facebook.com/nasa")

    await client.scrape.instagram.profiles(url="https://www.instagram.com/nasa/")
    await client.scrape.instagram.posts(url="https://www.instagram.com/p/Cuf4s0MNqNr")
    await client.scrape.instagram.reels(
        url="https://www.instagram.com/reel/C5Rdyj_q7YN/"
    )
    await client.scrape.instagram.comments(
        url="https://www.instagram.com/p/CesFC7JLyFl/"
    )

# Sync
from brightdata import SyncBrightDataClient

with SyncBrightDataClient() as client:
    client.scrape.facebook.posts_by_profile(
        url="https://www.facebook.com/nasa", num_of_posts=10
    )
    client.scrape.instagram.profiles(url="https://www.instagram.com/nasa/")

# Async
from brightdata import BrightDataClient

async with BrightDataClient() as client:
    profiles = await client.scrape.tiktok.profiles(
        url="https://www.tiktok.com/@username"
    )
    posts = await client.scrape.tiktok.posts(
        url="https://www.tiktok.com/@user/video/7433494424040017194"
    )
    comments = await client.scrape.tiktok.comments(
        url="https://www.tiktok.com/@user/video/7216019547806092550"
    )
    fast_posts = await client.scrape.tiktok.posts_by_profile_fast(
        url="https://www.tiktok.com/@bbc"
    )
    search = await client.scrape.tiktok.posts_by_search_url_fast(
        url="https://www.tiktok.com/search?q=cats", num_of_posts=10
    )

# Async
from brightdata import BrightDataClient

async with BrightDataClient() as client:
    videos = await client.scrape.youtube.videos(
        url="https://www.youtube.com/watch?v=dQw4w9WgXcQ",
        transcription_language="English"
    )
    channels = await client.scrape.youtube.channels(
        url="https://www.youtube.com/@MrBeast/about"
    )
    comments = await client.scrape.youtube.comments(
        url="https://www.youtube.com/watch?v=dQw4w9WgXcQ", num_of_comments=100
    )

# Async
from brightdata import BrightDataClient

async with BrightDataClient() as client:
    posts = await client.scrape.reddit.posts(
        url="https://www.reddit.com/r/python/comments/abc123/"
    )
    by_keyword = await client.scrape.reddit.posts_by_keyword(
        keyword="machine learning", sort_by="Top", date="Past week"
    )
    by_subreddit = await client.scrape.reddit.posts_by_subreddit(
        url="https://www.reddit.com/r/datascience/"
    )
    comments = await client.scrape.reddit.comments(
        url="https://www.reddit.com/r/python/comments/abc123/", days_back=30
    )

# Async
from brightdata import BrightDataClient

async with BrightDataClient() as client:
    posts = await client.scrape.pinterest.posts(
        url="https://www.pinterest.com/pin/3166662230556591/"
    )
    profiles = await client.scrape.pinterest.profiles(
        url="https://www.pinterest.com/boredpanda/"
    )

    # 按参数发现
    by_keyword = await client.search.pinterest.posts_by_keyword(
        keyword="spaghetti recipes"
    )
    by_profile = await client.search.pinterest.posts_by_profile(
        url="https://www.pinterest.com/grandmapowpow/", num_of_posts=20
    )

# Sync
from brightdata import SyncBrightDataClient

with SyncBrightDataClient() as client:
    posts = client.scrape.pinterest.posts(
        url="https://www.pinterest.com/pin/3166662230556591/"
    )
    profiles = client.scrape.pinterest.profiles(
        url="https://www.pinterest.com/boredpanda/"
    )

# Async
from brightdata import BrightDataClient

async with BrightDataClient() as client:
    result = await client.scrape.chatgpt.prompt(
        prompt="Explain async programming", web_search=True
    )
    batch = await client.scrape.chatgpt.prompts(
        prompts=["Explain Python", "Explain JavaScript"]
    )

# Sync
from brightdata import SyncBrightDataClient

with SyncBrightDataClient() as client:
    result = client.scrape.chatgpt.prompt(
        prompt="Explain async programming", web_search=True
    )
    batch = client.scrape.chatgpt.prompts(
        prompts=["Explain Python", "Explain JavaScript"]
    )

from brightdata import BrightDataClient

async with BrightDataClient() as client:
    parts = await client.scrape.digikey.products(
        url="https://www.digikey.com/en/products/detail/abc"
    )
    answer = await client.scrape.perplexity.search(
        url="https://www.perplexity.ai/search?q=battery+tech"
    )

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"
    )

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")

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。

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())

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()

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

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())

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

更新内容

功能	说明
Discover API	`client.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 Studio	`client.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 API	`client.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 scrapers	`client.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

概览

产品

管理 API

安装与配置

配置

基本用法

发起抓取和网络搜索

使用平台专用 scrapers 提取结构化数据

使用 AI 排序搜索网页（Discover API）

运行您的自定义 Scraper Studio scrapers

Datasets API

使用 dataclass 负载实现类型安全

连接至 Scraping Browser

使用 CLI 工具

异步用法获取更高性能

资源

GitHub 仓库

示例目录

PyPI 页面

更新内容

​安装与配置

​配置

​基本用法

​发起抓取和网络搜索

​使用平台专用 scrapers 提取结构化数据

​使用 AI 排序搜索网页（Discover API）

​运行您的自定义 Scraper Studio scrapers

​Datasets API

​使用 dataclass 负载实现类型安全

​连接至 Scraping Browser

​使用 CLI 工具

​异步用法获取更高性能

​资源

GitHub 仓库

示例目录

PyPI 页面

​更新内容

安装与配置

配置

基本用法

发起抓取和网络搜索

使用平台专用 scrapers 提取结构化数据

使用 AI 排序搜索网页（Discover API）

运行您的自定义 Scraper Studio scrapers

Datasets API

使用 dataclass 负载实现类型安全

连接至 Scraping Browser

使用 CLI 工具

异步用法获取更高性能

资源

更新内容