brightdata-sdk 2.3.0

Modern async-first Python SDK for Bright Data APIs

Bright Data Python SDK

The official Python SDK for Bright Data APIs. Scrape any website, get SERP results, bypass bot detection and CAPTCHAs, and access 100+ ready-made datasets.

Installation

pip install brightdata-sdk

Configuration

Get your API Token from the Bright Data Control Panel:

export BRIGHTDATA_API_TOKEN="your_api_token_here"

Quick Start

This SDK is async-native. A sync client is also available (see Sync Client).

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)

asyncio.run(main())

Usage Examples

Web Scraping

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

Web Scraping Async Mode

For non-blocking web scraping, use mode="async". This triggers a request and returns a response_id, which the SDK automatically polls until results are ready:

async with BrightDataClient() as client:
    # Triggers request → gets response_id → polls until ready
    result = await client.scrape_url(
        url="https://example.com",
        mode="async",
        poll_interval=5,    # Check every 5 seconds
        poll_timeout=180    # Web Unlocker async can take ~2 minutes
    )
    print(result.data)

    # Batch scraping multiple URLs concurrently
    urls = ["https://example.com", "https://example.org", "https://example.net"]
    results = await client.scrape_url(url=urls, mode="async", poll_timeout=180)

How it works:

1. Sends request to /unblocker/req → returns response_id immediately
2. Polls /unblocker/get_result?response_id=... until ready or timeout
3. Returns the scraped data

When to use async mode:

• Batch scraping with many URLs
• Background processing while continuing other work

Performance note: Web Unlocker async mode typically takes ~2 minutes to complete. For faster results on single URLs, use the default sync mode (no mode parameter).

Search Engines (SERP)

async with BrightDataClient() as client:
    result = await client.search.google(query="python scraping", num_results=10)
    for item in result.data:
        print(item)

SERP Async Mode

For non-blocking SERP requests, use mode="async":

async with BrightDataClient() as client:
    # Non-blocking - polls for results
    result = await client.search.google(
        query="python programming",
        mode="async",
        poll_interval=2,   # Check every 2 seconds
        poll_timeout=30    # Give up after 30 seconds
    )

    for item in result.data:
        print(item['title'], item['link'])

When to use async mode:

• Batch operations with many queries
• Background processing while continuing other work
• When scraping may take longer than usual

Note: Async mode uses the same zones and returns the same data structure as sync mode - no extra configuration needed!

Web Scraper API

The SDK includes ready-to-use scrapers for popular websites: Amazon, LinkedIn, Instagram, Facebook, and more.

Pattern: client.scrape.<platform>.<method>(url)

Example: Amazon

async with BrightDataClient() as client:
    # Product details
    result = await client.scrape.amazon.products(url="https://amazon.com/dp/B0CRMZHDG8")

    # Reviews
    result = await client.scrape.amazon.reviews(url="https://amazon.com/dp/B0CRMZHDG8")

    # Sellers
    result = await client.scrape.amazon.sellers(url="https://amazon.com/dp/B0CRMZHDG8")

Available scrapers:

• client.scrape.amazon - products, reviews, sellers
• client.scrape.linkedin - profiles, companies, jobs, posts
• client.scrape.instagram - profiles, posts, comments, reels
• client.scrape.facebook - posts, comments, reels

Datasets API

Access 100+ ready-made datasets from Bright Data — pre-collected, structured data from popular platforms.

async with BrightDataClient() as client:
    # Filter a dataset — returns a snapshot_id
    snapshot_id = await client.datasets.imdb_movies(
        filter={"name": "title", "operator": "includes", "value": "black"},
        records_limit=5
    )

    # Download when ready (polls until snapshot is complete)
    data = await client.datasets.imdb_movies.download(snapshot_id)
    print(f"Got {len(data)} records")

    # Quick sample: .sample() auto-discovers fields, no filter needed
    # Works on any dataset
    snapshot_id = await client.datasets.imdb_movies.sample(records_limit=5)

Export results to file:

from brightdata.datasets import export

export(data, "results.json")   # JSON
export(data, "results.csv")    # CSV
export(data, "results.jsonl")  # JSONL

Available dataset categories:

• E-commerce: Amazon, Walmart, Shopee, Lazada, Zalando, Zara, H&M, Shein, IKEA, Sephora, and more
• Business intelligence: ZoomInfo, PitchBook, Owler, Slintel, VentureRadar, Manta
• Jobs & HR: Glassdoor (companies, reviews, jobs), Indeed (companies, jobs), Xing
• Reviews: Google Maps, Yelp, G2, Trustpilot, TrustRadius
• Social media: Pinterest (posts, profiles), Facebook Pages
• Real estate: Zillow, Airbnb, and 8+ regional platforms
• Luxury brands: Chanel, Dior, Prada, Balenciaga, Hermes, YSL, and more
• Entertainment: IMDB, NBA, Goodreads

Discover available fields:

metadata = await client.datasets.imdb_movies.get_metadata()
for name, field in metadata.fields.items():
    print(f"{name}: {field.type}")

Async Usage

Run multiple requests concurrently:

import asyncio
from brightdata import BrightDataClient

async def main():
    async with BrightDataClient() as client:
        urls = ["https://example.com/page1", "https://example.com/page2", "https://example.com/page3"]
        tasks = [client.scrape_url(url) for url in urls]
        results = await asyncio.gather(*tasks)

asyncio.run(main())

Manual Trigger/Poll/Fetch

For long-running scrapes:

async with BrightDataClient() as client:
    # Trigger
    job = await client.scrape.amazon.products_trigger(url="https://amazon.com/dp/B123")

    # Wait for completion
    await job.wait(timeout=180)

    # Fetch results
    data = await job.fetch()

Sync Client

For simpler use cases, use SyncBrightDataClient:

from brightdata import SyncBrightDataClient

with SyncBrightDataClient() as client:
    result = client.scrape_url("https://example.com")
    print(result.data)

    # All methods work the same
    result = client.scrape.amazon.products(url="https://amazon.com/dp/B123")
    result = client.search.google(query="python")

See docs/sync_client.md for details.

Troubleshooting

RuntimeError: SyncBrightDataClient cannot be used inside async context

# Wrong - using sync client in async function
async def main():
    with SyncBrightDataClient() as client:  # Error!
        ...

# Correct - use async client
async def main():
    async with BrightDataClient() as client:
        result = await client.scrape_url("https://example.com")

RuntimeError: BrightDataClient not initialized

# Wrong - forgot context manager
client = BrightDataClient()
result = await client.scrape_url("...")  # Error!

# Correct - use context manager
async with BrightDataClient() as client:
    result = await client.scrape_url("...")

License

MIT License