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Load Plentymarkets data to DuckDB

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

SourcePlentymarketsREST API :: Developers documentationDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

Plentymarkets is an e-commerce platform offering a REST API to access shop data. Everything needed to build a working Plentymarkets → 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 Plentymarkets 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 Plentymarkets 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 Plentymarkets 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.


Plentymarkets API at a glance

Base URLhttps://api.plentymarkets.com/rest
Example endpointGET rest/items
Records found atentries
Authenticationall requests require a Bearer token — sent in the Authorization header, prefixed Bearer
PaginationNot paginated
Incremental fieldupdatedAt
Record idid
API referencehttps://developers.plentymarkets.com/en-gb/developers/main/rest-api-guides/getting-started.html

These values come from the Plentymarkets API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the Plentymarkets API?

All requests require a Bearer token in the 'Authorization' header, which is obtained by POSTing credentials to the '/rest/login' endpoint.

1. Get your credentials

To obtain credentials for the PlentyONE/Plentymarkets REST API, you need a user account with appropriate permissions. First, navigate to Setup » Settings » User » Accounts in your PlentyONE backend to ensure you have a dedicated API user or account. Second, go to Setup » Settings » User » Rights » User to grant that account the necessary API permissions (REST API rights are not activated by default). Finally, navigate to Setup » Settings » API » Data to copy the REST-API HTTP Endpoint. You will use your PlentyONE system's login credentials (username and password) to authenticate via the /rest/login endpoint to obtain an access token.

2. Add them to .dlt/secrets.toml

[sources.plentymarkets_source] api_endpoint = "https://p{myPID}.my.plentysystems.com/rest" username = "your_username" password = "your_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.


What Plentymarkets data can I load into DuckDB?

These are the Plentymarkets endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
items/rest/itemsGETentriesGet list of items
item_variations/rest/items/variationsGETentriesGet list of item variations
properties/rest/items/propertiesGETentriesGet list of properties
attributes/rest/items/attributesGETentriesGet list of attributes
warehouses/rest/stockmanagement/warehousesGETentriesGet list of warehouses

How do I load only new Plentymarkets records?

Plentymarkets exposes updatedAt on rest/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.

{"name": "items", "endpoint": { "path": "rest/items", "data_selector": "entries", "incremental": {"cursor_path": "updatedAt", "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 Plentymarkets pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /rest/login and /rest/logout from the Plentymarkets API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def plentymarkets_source(access_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.plentymarkets.com/rest", "auth": {"type": "bearer", "token": access_token}, }, "resources": [ {"name": "items", "endpoint": {"path": "rest/items", "data_selector": "entries"}}, {"name": "stock_entries", "endpoint": {"path": "rest/stockmanagement/stock", "data_selector": "entries"}} ], } yield from rest_api_resources(config) def load_plentymarkets_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="plentymarkets_pipeline", destination="duckdb", dataset_name="plentymarkets_data", ) load_info = pipeline.run(plentymarkets_source()) print(load_info) if __name__ == "__main__": load_plentymarkets_to_duckdb()

Run it with python plentymarkets_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 Plentymarkets 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("plentymarkets_pipeline").dataset() df = data.items.df() print(df.head())

SQL:

SELECT * FROM plentymarkets_data.items LIMIT 10;

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


How do I deploy the Plentymarkets 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 Plentymarkets 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 Plentymarkets 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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