Python SDK
The official DataBlue Python SDK is published on PyPI as datablue==2.1.0. It provides sync and async clients for scraping, crawling, search, map, extraction, and documented Data APIs.
Install
Example
pip install datablue==2.1.0Sync Client
Example
from datablue import DataBlue
with DataBlue(api_key="wh_your_api_key") as client:
page = client.scrape("https://example.com", formats=["markdown", "links"])
print(page.data.markdown)
serp = client.google_serp(
query="best crm software",
country="US",
results=10,
)
print(serp["data"])Async Client
Example
from datablue import AsyncDataBlue
async with AsyncDataBlue(api_key="wh_your_api_key") as client:
result = await client.scrape("https://example.com")
print(result.data.markdown)Core Methods
| Method | Use |
|---|---|
scrape() | Fetch one URL with markdown, HTML, links, screenshot, or extraction options. |
crawl() / start_crawl() | Crawl a site synchronously or start a job and poll status. |
search() | Run web search and return results through DataBlue. |
map() | Discover URLs from a site without scraping every page. |
data_api() | Call documented /v1/data/* endpoints with current params. |
get_data_job_status() | Poll native Data API async jobs returned with job_id and status_url. |
google_serp() | Convenience helper for the documented Google SERP endpoint. |
Data APIs
Use named helpers for stable documented APIs, or use data_api() when you want the SDK to follow the live docs without waiting for a new SDK release.
Example
from datablue import DataBlue
with DataBlue(api_key="wh_your_api_key") as client:
products = client.data_api(
"amazon/products",
query="wireless mouse",
domain="amazon.com",
num_results=10,
)
print(products["data"])When a heavy Data API returns a queued job, use the returned job_id with the status helper.
Example
job = client.amazon_store(url="https://www.amazon.com/stores/example")
status = client.get_data_job_status(job["job_id"])
print(status["status"])