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Load Amazon Selling Partner API data to DuckDB

Build a Amazon Selling Partner API to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Amazon Selling Partner API API base URL, auth, endpoints, and incremental loading.

SourceAmazon Selling Partner APIAmazon Selling Partner API API DocumentationDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

Amazon Selling Partner API (SP-API) is a REST-based API that allows Amazon selling partners to programmatically access their data on orders, shipments, payments, and more. Everything needed to build a working Amazon Selling Partner API → 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 Amazon Selling Partner API to DuckDB pipeline

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

Prompt
Run uvx dlthub-init@latest to build a pipeline from Amazon Selling Partner API 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 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.


Amazon Selling Partner API API at a glance

Base URLhttps://sellingpartnerapi-na.amazon.com
Example endpointGET listings/2021-08-01/items/{sellerId}
Records found atitems
AuthenticationAuthentication requires LWA OAuth2 token acquisition followed by AWS SigV4 request signing and an x-amz-access-token header — sent in the x-amz-access-token header
Also requiredhost, x-amz-date, user-agent
PaginationCursor-based via pageToken (SP-API docs say to pass pagination nextToken/previousToken as the pageToken query parameter in the next request for search operations) / paginationToken (for searchOrders), next cursor at pagination.nextToken (and pagination.previousToken), page size via pageSize (searchCatalogItems/searchListingsItems) and MaxResultsPerPage (getOrders) (default 10, max 20). For searchCatalogItems/searchListingsItems pagination, when the response exceeds the pageSize, include pagination.nextToken or pagination.previousToken as the pageToken parameter on the next request; the last page has no nextToken. For searchOrders (Orders API), pagination uses pagination.nextToken and you pass it as the paginationToken query parameter; NextToken expires after 24 hours.
Incremental fieldlastUpdatedDate
API referencehttps://developer-docs.amazon.com/sp-api/docs/connecting-to-the-selling-partner-api

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


How do I authenticate with the Amazon Selling Partner API API?

Authentication involves exchanging a Login with Amazon (LWA) refresh token for an access token via a POST request to https://api.amazon.com/auth/o2/token, then signing each SP-API request using AWS Signature Version 4 (SigV4) including an 'x-amz-access-token' header. For restricted operations, a Restricted Data Token (RDT) is used in place of the standard access token.

1. Get your credentials

  1. Log in to your Professional Seller Central account. 2. Navigate to Apps and Services, then select Develop Apps. 3. Click Proceed to Developer Profile (if new) to submit your organization's details, security information, and use cases. 4. Once your developer profile is approved, return to the Develop Apps page. 5. Click Add new app client to register your application. 6. Upon successful registration, you will be provided with your Client ID and Client Secret in the application details section. 7. To obtain a Refresh Token, follow the Login with Amazon (LWA) OAuth 2.0 authorization workflow: request authorization from a selling partner, and upon their consent, exchange the authorization code for a refresh token.

2. Add them to .dlt/secrets.toml

[sources.amazon_selling_partner_api_source] client_id = "amzn1.application-oa2-client.xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" client_secret = "amzn1.oa2-cs.v1.xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" refresh_token = "Atzr|IwEBIBxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"

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 Amazon Selling Partner API data can I load into DuckDB?

These are the Amazon Selling Partner API endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
listings/listings/2021-08-01/items/{sellerId}GETitemsSearch listings items with pagination and sorting.
catalog_items/catalog/2022-04-01/itemsGETitemsSearch catalog items with pagination.
orders/orders/v0/ordersGETordersSearch orders with filtering and pagination.
feeds/feeds/2021-06-30/feedsGETfeedsReturns a list of feeds.
reports/reports/2021-06-30/reportsGETreportsReturns a list of reports.

How do I load only new Amazon Selling Partner API records?

Amazon Selling Partner API exposes lastUpdatedDate on listings/2021-08-01/items/{sellerId}, 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.

{"name": "listings", "endpoint": { "path": "listings/2021-08-01/items/{sellerId}", "data_selector": "items", "incremental": {"cursor_path": "lastUpdatedDate", "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 Amazon Selling Partner API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading https://sellingpartnerapi-na.amazon.com and https://sellingpartnerapi-eu.amazon.com from the Amazon Selling Partner API API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def amazon_selling_partner_api_source(lwa_refresh_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://sellingpartnerapi-na.amazon.com", "auth": {"type": "api_key", "api_key": lwa_refresh_token, "name": "x-amz-access-token", "location": "header"}, }, "resources": [ {"name": "listings", "endpoint": {"path": "listings/2021-08-01/items/{sellerId}", "data_selector": "items"}}, {"name": "orders", "endpoint": {"path": "orders/v0/orders", "data_selector": "orders"}} ], } yield from rest_api_resources(config) def load_amazon_selling_partner_api_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="amazon_selling_partner_api_pipeline", destination="duckdb", dataset_name="amazon_selling_partner_api_data", ) load_info = pipeline.run(amazon_selling_partner_api_source()) print(load_info) if __name__ == "__main__": load_amazon_selling_partner_api_to_duckdb()

Run it with python amazon_selling_partner_api_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 Amazon Selling Partner API 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):

import dlt data = dlt.pipeline("amazon_selling_partner_api_pipeline").dataset() df = data.listings.df() print(df.head())

SQL:

SELECT * FROM amazon_selling_partner_api_data.listings LIMIT 10;

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


How do I deploy the Amazon Selling Partner API 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 API 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 Amazon Selling Partner API data to?

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

DestinationExample value
PostgreSQL"postgres"
BigQuery"bigquery"
Snowflake"snowflake"
Redshift"redshift"
Databricks"databricks"
Filesystem (S3, GCS, Azure)"filesystem"

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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