Load Amazon selling partner data to DuckDB

Amazon Selling Partner API (SP-API) is a REST-based API that enables developers to programmatically access their Amazon selling data. Everything needed to build a working Amazon selling partner → 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 selling partner 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 selling partner 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 selling partner 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 selling partner API at a glance

These values come from the Amazon selling partner API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Amazon selling partner API?

The API uses Login with Amazon (LWA) OAuth 2.0 to exchange a refresh token for an access token via a POST request to https://api.amazon.com/auth/o2/token, which is then passed as an x-amz-access-token header in SP-API requests.

1. Get your credentials

1. Log in to your Professional Seller Central account. 2. Navigate to Apps and Services > Develop Apps to access the Developer Central dashboard. 3. Complete the Developer Profile form and submit it for evaluation. 4. Once approved, proceed to register your application in the Solution Provider Portal. 5. In your application's details, you will be able to view your 'Client identifier' (Client ID) and 'Client secret'. 6. To obtain a refresh token, authorize your application via the OAuth 2.0 workflow (or 'Create Token' for sandbox applications in the Solution Provider Portal).

2. Add them to .dlt/secrets.toml

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[sources.amazon_selling_partner_source]
client_id = "amzn1.application-oa2-client.your_client_id_here"
client_secret = "amzn1.oa2-cs.v1.your_client_secret_here"
refresh_token = "Atzr|your_refresh_token_here"
region = "NA" # Options: NA, EU, FE

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 selling partner data can I load into DuckDB?

These are the Amazon selling partner endpoints dlt can load into DuckDB:

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How do I load only new Amazon selling partner records?

Amazon selling partner exposes pageToken on catalog/2022-04-01/items, 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": "search_catalog_items", "endpoint": {
    "path": "catalog/2022-04-01/items",
    "data_selector": "items",
    "incremental": {"cursor_path": "pageToken", "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 selling partner pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading orders and feeds from the Amazon selling partner API into DuckDB:

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

@dlt.source
def amazon_selling_partner_source(refresh_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://sellingpartnerapi-na.amazon.com, https://sellingpartnerapi-eu.amazon.com, https://sellingpartnerapi-fe.amazon.com",
            "auth": {"type": "bearer", "token": refresh_token},
        },
        "resources": [
            {"name": "search_catalog_items", "endpoint": {"path": "catalog/2022-04-01/items", "data_selector": "items"}},
            {"name": "search_orders", "endpoint": {"path": "orders/v0/orders", "data_selector": "orders"}}
        ],
    }
    yield from rest_api_resources(config)


def load_amazon_selling_partner_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="amazon_selling_partner_pipeline",
        destination="duckdb",
        dataset_name="amazon_selling_partner_data",
    )
    load_info = pipeline.run(amazon_selling_partner_source())
    print(load_info)


if __name__ == "__main__":
    load_amazon_selling_partner_to_duckdb()

Run it with python amazon_selling_partner_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 selling partner 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_selling_partner_pipeline").dataset()
df = data.search_orders.df()
print(df.head())

SQL:

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SELECT * FROM amazon_selling_partner_data.search_orders LIMIT 10;

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

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How do I deploy the Amazon selling partner 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 selling partner 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 selling partner 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