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Load Rocketlane data to DuckDB

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

SourceRocketlaneDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

Rocketlane is a customer onboarding platform that provides a RESTful API for interacting with projects, tasks, and other resources. Everything needed to build a working Rocketlane → 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 Rocketlane 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 Rocketlane 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 Rocketlane 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.


Rocketlane API at a glance

Base URLhttps://api.rocketlane.com/api/1.0
Example endpointGET 1.0/projects
Records found atdata
Authenticationall requests require an 'api-key' header — sent in the api-key header
PaginationCursor-based via pageToken, next cursor at pagination.nextPageToken, page size via limit (default 100)
Incremental fieldpageToken
Record idid
API referencehttps://developer.rocketlane.com/docs/authentication

These values come from the Rocketlane API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the Rocketlane API?

Authentication is performed by passing an API key in the request header named 'api-key'. The API key is generated via the Rocketlane application settings.

1. Get your credentials

  1. Log in to your Rocketlane account. 2. Click your profile icon located in the vertical navigation bar on the left. 3. Select Settings from the menu. 4. Navigate to the API section (also referred to as the Developer Console). 5. Click the Create API key button. 6. Provide a name for the API key and click Add to generate it. 7. Copy the generated API key immediately and store it securely, as it will be used in the api-key header for all requests.

2. Add them to .dlt/secrets.toml

[sources.rocketlane_source] api_key = "your_rocketlane_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 Rocketlane data can I load into DuckDB?

These are the Rocketlane endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
projects/1.0/projectsGETdataRetrieve a list of projects
tasks/1.0/tasksGETdataRetrieve a list of tasks
time_entries/1.0/time-entriesGETdataRetrieve a list of time entries
invoices/1.0/invoicesGETdataRetrieve a list of invoices
templates/1.0/templatesGETdataRetrieve a list of templates

How do I load only new Rocketlane records?

Rocketlane exposes pageToken on 1.0/projects, 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": "projects", "endpoint": { "path": "1.0/projects", "data_selector": "data", "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.


What does the generated Rocketlane pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading projects and tasks from the Rocketlane API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def rocketlane_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.rocketlane.com/api/1.0", "auth": {"type": "api_key", "api_key": api_key, "name": "api-key", "location": "header"}, }, "resources": [ {"name": "projects", "endpoint": {"path": "1.0/projects", "data_selector": "data"}}, {"name": "tasks", "endpoint": {"path": "1.0/tasks", "data_selector": "data"}} ], } yield from rest_api_resources(config) def load_rocketlane_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="rocketlane_pipeline", destination="duckdb", dataset_name="rocketlane_data", ) load_info = pipeline.run(rocketlane_source()) print(load_info) if __name__ == "__main__": load_rocketlane_to_duckdb()

Run it with python rocketlane_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 Rocketlane 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("rocketlane_pipeline").dataset() df = data.projects.df() print(df.head())

SQL:

SELECT * FROM rocketlane_data.projects LIMIT 10;

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


How do I deploy the Rocketlane 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 Rocketlane 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 Rocketlane 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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