Load Scrapingbee data to DuckDB

ScrapingBee is a web scraping API that provides access to headless browsers, proxy rotation, and data extraction through an HTTP REST interface. Everything needed to build a working Scrapingbee → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

---

Build your Scrapingbee to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from Scrapingbee to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the Scrapingbee API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

---

Scrapingbee API at a glance

These values come from the Scrapingbee API reference — the authoritative source if anything here looks out of date.

---

How do I authenticate with the Scrapingbee API?

The recommended authentication method is to include the API key in the 'Authorization' HTTP header using the 'Bearer' scheme, such as 'Authorization: Bearer YOUR-API-KEY'. Passing the API key as a query string parameter ('api_key') is also supported but has been marked as deprecated.

1. Get your credentials

To obtain your ScrapingBee API key: 1. Navigate to the ScrapingBee Dashboard and sign in. 2. Once logged in, go to your Account Settings. 3. Look for the 'API key' tab or section to view your current key. You can also generate a new key or change your existing one from this same location. If you do not have an account, you must register at their website to receive one.

2. Add them to .dlt/secrets.toml

Copy
[sources.scrapingbee_source]
scrapingbee_api_key = "your_api_key_here"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

---

What Scrapingbee data can I load into DuckDB?

These are the Scrapingbee endpoints dlt can load into DuckDB:

---

How do I load only new Scrapingbee records?

The Scrapingbee API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

Copy
{"name": "html_api", "endpoint": {
    "path": "api/v1",
    # Replace with a field that increases on every write.
    "incremental": {"cursor_path": "REPLACE_ME", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

---

What does the generated Scrapingbee pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /api/v1/ and /api/v1/amazon/product from the Scrapingbee API into DuckDB:

Copy
import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def scrapingbee_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://app.scrapingbee.com/api/v1",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "html_api", "endpoint": {"path": "api/v1", "data_selector": "body"}},
            {"name": "fast_search", "endpoint": {"path": "api/v1/fast_search", "data_selector": "results"}}
        ],
    }
    yield from rest_api_resources(config)


def load_scrapingbee_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="scrapingbee_pipeline",
        destination="duckdb",
        dataset_name="scrapingbee_data",
    )
    load_info = pipeline.run(scrapingbee_source())
    print(load_info)


if __name__ == "__main__":
    load_scrapingbee_to_duckdb()

Run it with python scrapingbee_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

---

How do I query Scrapingbee data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

Copy
import dlt

data = dlt.pipeline("scrapingbee_pipeline").dataset()
df = data.html_api.df()
print(df.head())

SQL:

Copy
SELECT * FROM scrapingbee_data.html_api LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

---

How do I deploy the Scrapingbee to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw Scrapingbee loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

---

What other destinations can I load Scrapingbee data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

---

Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack