Load Amazon Advertising data to DuckDB

Amazon Advertising is a REST API that enables advertisers and partners to programmatically manage Amazon advertising resources and retrieve reporting data. Everything needed to build a working Amazon Advertising → 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 Amazon Advertising 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 Amazon Advertising 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 Amazon Advertising 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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Amazon Advertising API at a glance

These values come from the Amazon Advertising API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Amazon Advertising API?

All requests require the Authorization: Bearer <access_token> header and the Amazon-Advertising-API-ClientId header for authentication.

1. Get your credentials

1. Apply for access at the Amazon Ads API website (advertising.amazon.com/about-api) and log in with your Amazon account.
2. Complete the registration form and wait for approval.
3. Upon approval, you will receive an invitation with a sign-up link. Log in and accept the Amazon Ads API terms.
4. Navigate to the Login with Amazon (LWA) developer console and register an application to generate your Client ID and Client Secret.
5. In the Amazon Ads Advanced Tools Center, link your registered LWA application to your advertising account.
6. Generate a one-time Authorization Code by constructing an authorization URL and visiting it in your browser.
7. Exchange this Authorization Code for a long-lived Refresh Token using the /auth/o2/token endpoint. Store this Refresh Token securely along with your Client ID and Client Secret.

2. Add them to .dlt/secrets.toml

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[sources.amazon_advertising_source]
client_id = "your_lwa_client_id"
client_secret = "your_lwa_client_secret"
refresh_token = "your_refresh_token"

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 Amazon Advertising data can I load into DuckDB?

These are the Amazon Advertising endpoints dlt can load into DuckDB:

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How do I load only new Amazon Advertising records?

Amazon Advertising exposes cursorId on v2/attribution/reports, 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": "attribution_reports", "endpoint": {
    "path": "v2/attribution/reports",
    "data_selector": "reports",
    "incremental": {"cursor_path": "cursorId", "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 Amazon Advertising pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /v2/profiles and /v2/campaigns from the Amazon Advertising API into DuckDB:

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

@dlt.source
def amazon_advertising_source(client_id=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://advertising-api.amazon.com",
            "auth": {"type": "bearer", "token": client_id},
        },
        "resources": [
            {"name": "attribution_reports", "endpoint": {"path": "v2/attribution/reports", "data_selector": "reports"}},
            {"name": "sponsored_products_campaigns", "endpoint": {"path": "v3/sp/campaigns", "data_selector": "campaigns"}}
        ],
    }
    yield from rest_api_resources(config)


def load_amazon_advertising_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="amazon_advertising_pipeline",
        destination="duckdb",
        dataset_name="amazon_advertising_data",
    )
    load_info = pipeline.run(amazon_advertising_source())
    print(load_info)


if __name__ == "__main__":
    load_amazon_advertising_to_duckdb()

Run it with python amazon_advertising_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 Amazon Advertising 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("amazon_advertising_pipeline").dataset()
df = data.attribution_reports.df()
print(df.head())

SQL:

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SELECT * FROM amazon_advertising_data.attribution_reports LIMIT 10;

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

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How do I deploy the Amazon Advertising 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 Amazon Advertising 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 Amazon Advertising 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