Load Outbrain Amplify data to DuckDB

Outbrain Amplify is an advertising API for managing campaigns, promoted links, and retrieving performance analytics for the Outbrain content discovery platform. Everything needed to build a working Outbrain Amplify → 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.

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Build your Outbrain Amplify 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 Outbrain Amplify 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 Outbrain Amplify 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.

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Outbrain Amplify API at a glance

These values come from the Outbrain Amplify API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Outbrain Amplify API?

Authentication requires a two-step process: first, use HTTP Basic authentication (username:password) against the /login endpoint to retrieve an 'OB-TOKEN-V1' token. This token must then be included in the 'OB-TOKEN-V1' HTTP header for all subsequent API requests.

1. Get your credentials

To obtain credentials for the Outbrain Amplify API, follow these steps: 1. If you do not have an Outbrain account, register for one on the Outbrain website. 2. Visit the 'Outbrain Amplify Request API Access' page (https://www.outbrain.com/partner-api/) and submit the application form. 3. Provide detailed information regarding your intended use of the API. 4. Once your request is evaluated and approved, you will be able to use your Outbrain username and password to authenticate via the /login endpoint. 5. Perform a GET request to the /login endpoint using HTTP Basic Authentication (Base64 encoded username:password) to retrieve an OB-TOKEN-V1 token. This token must be included in the 'OB-TOKEN-V1' header for all subsequent API requests.

2. Add them to .dlt/secrets.toml

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[sources.outbrain_amplify_source]
username = "your_outbrain_email_or_username"
password = "your_outbrain_password"

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.

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What Outbrain Amplify data can I load into DuckDB?

These are the Outbrain Amplify endpoints dlt can load into DuckDB:

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How do I load only new Outbrain Amplify records?

Outbrain Amplify exposes offset on marketers/{marketerId}/campaigns, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "campaigns", "endpoint": {
    "path": "marketers/{marketerId}/campaigns",
    "data_selector": "campaigns",
    "incremental": {"cursor_path": "offset", "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.

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What does the generated Outbrain Amplify pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /login and /marketers (or campaigns) from the Outbrain Amplify API into DuckDB:

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

@dlt.source
def outbrain_amplify_source(ob_token_v1=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.outbrain.com/amplify/v0.1",
            "auth": {"type": "api_key", "api_key": ob_token_v1, "name": "OB-TOKEN-V1", "location": "header"},
        },
        "resources": [
            {"name": "campaigns", "endpoint": {"path": "marketers/{marketerId}/campaigns", "data_selector": "campaigns"}},
            {"name": "campaign_details", "endpoint": {"path": "campaigns/{campaignId}"}}
        ],
    }
    yield from rest_api_resources(config)


def load_outbrain_amplify_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="outbrain_amplify_pipeline",
        destination="duckdb",
        dataset_name="outbrain_amplify_data",
    )
    load_info = pipeline.run(outbrain_amplify_source())
    print(load_info)


if __name__ == "__main__":
    load_outbrain_amplify_to_duckdb()

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

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How do I query Outbrain Amplify 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):

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import dlt

data = dlt.pipeline("outbrain_amplify_pipeline").dataset()
df = data.campaigns.df()
print(df.head())

SQL:

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SELECT * FROM outbrain_amplify_data.campaigns LIMIT 10;

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

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How do I deploy the Outbrain Amplify 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 Outbrain Amplify loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Outbrain Amplify 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.

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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