Load Proffix data to DuckDB
Build a Proffix to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Proffix API base URL, auth, endpoints, and incremental loading.
Proffix is an ERP software system that provides a REST API for accessing and managing business entities and data. Everything needed to build a working Proffix → 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 Proffix to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from Proffix 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 Proffix 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.
Proffix API at a glance
| Base URL | https://{hostname}/pxapi/V4/ |
| Example endpoint | GET PRO/Info |
| Authentication | all requests require an API key as a query parameter and an Accept header |
| API reference | https://portal.proffix.net:11011/api-docs/ |
These values come from the Proffix API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the Proffix API?
Authentication is performed by passing an API key as a URL query parameter named 'key'. Additionally, all requests must include the header 'Accept: application/json'.
1. Get your credentials
To obtain API credentials for the Proffix REST API: 1. Access the Proffix server where the Proffix software is installed. 2. Launch the 'Proffix Server-Manager' application (often found on the desktop or via the Start menu). 3. Within the Proffix Server-Manager, navigate to the configuration settings for the REST API instance. 4. Within this interface, you can generate or retrieve the API key required for authentication. This key is typically used as a query parameter (named 'key') in your API requests. Ensure that the Proffix user account used has the necessary permissions granted for REST API access.
2. Add them to .dlt/secrets.toml
[sources.proffix_source] api_key = "your_proffix_api_key_here"
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 Proffix data can I load into DuckDB?
These are the Proffix endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| pro_info | PRO/Info | GET | General API information | |
| pro_mitarbeiter | PRO/Mitarbeiter | GET | List of employees | |
| adr_adresse | ADR/Adresse | GET | List of addresses | |
| auf_dokument | AUF/Dokument | GET | List of orders/documents | |
| fib_buchung | FIB/Buchung | GET | List of accounting entries |
How do I load only new Proffix records?
The Proffix API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.
{"name": "pro_info", "endpoint": { "path": "PRO/Info", # Replace with a field that increases on every write. "incremental": {"cursor_path": "REPLACE_ME", "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 Proffix pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading PRO/Info and PRO/Login from the Proffix API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def proffix_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://{hostname}/pxapi/V4/", "auth": {"type": "api_key", "api_key": api_key, "name": "key"}, }, "resources": [ {"name": "pro_info", "endpoint": {"path": "PRO/Info"}}, {"name": "pro_mitarbeiter", "endpoint": {"path": "PRO/Mitarbeiter"}} ], } yield from rest_api_resources(config) def load_proffix_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="proffix_pipeline", destination="duckdb", dataset_name="proffix_data", ) load_info = pipeline.run(proffix_source()) print(load_info) if __name__ == "__main__": load_proffix_to_duckdb()
Run it with python proffix_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 Proffix 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("proffix_pipeline").dataset() df = data.pro_info.df() print(df.head())
SQL:
SELECT * FROM proffix_data.pro_info LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the Proffix 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 Proffix loads into governed, documented models.
- Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.
What other destinations can I load Proffix data to?
dlt loads into any of these — only the destination argument changes:
| Destination | Example 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.
Next steps
Was this page helpful?
Community Hub
Need more dlt context for Proffix to DuckDB?
Request dlt skills, commands, AGENT.md files, and AI-native context.