Load Launch Library 2 data to DuckDB

Launch Library 2 is a database API providing information on rocket launches, space events, and related spaceflight data. Everything needed to build a working Launch Library 2 → 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 Launch Library 2 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 Launch Library 2 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 Launch Library 2 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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Launch Library 2 API at a glance

These values come from the Launch Library 2 API documentation. Check them against the vendor's current reference before relying on them in production.

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How do I authenticate with the Launch Library 2 API?

The API uses Token authentication. Requests must include an 'Authorization' header with the value 'Token <your_api_key>'.

1. Get your credentials

To obtain an API key for the Launch Library 2 (LL2) API, first navigate to The Space Devs support website (thespacedevs.com/supportus). You must have a Patreon account to generate an API key, as access tiers are managed via Patreon. Log in with your Patreon account on the website to access your user dashboard, where you can then generate or manage your unique API key.

2. Add them to .dlt/secrets.toml

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[sources.launch_library_2_source]
api_key = "Token your_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.

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What Launch Library 2 data can I load into DuckDB?

These are the Launch Library 2 endpoints dlt can load into DuckDB:

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How do I load only new Launch Library 2 records?

Launch Library 2 exposes offset on 2.2.0/launch/, 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": "launch", "endpoint": {
    "path": "2.2.0/launch/",
    "data_selector": "results",
    "incremental": {"cursor_path": "offset", "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 Launch Library 2 pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading launches and events from the Launch Library 2 API into DuckDB:

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

@dlt.source
def launch_library_2_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://ll.thespacedevs.com/2.3.0/",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "launch", "endpoint": {"path": "2.2.0/launch/", "data_selector": "results"}},
            {"name": "launch_upcoming", "endpoint": {"path": "2.2.0/launch/upcoming/", "data_selector": "results"}}
        ],
    }
    yield from rest_api_resources(config)


def load_launch_library_2_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="launch_library_2_pipeline",
        destination="duckdb",
        dataset_name="launch_library_2_data",
    )
    load_info = pipeline.run(launch_library_2_source())
    print(load_info)


if __name__ == "__main__":
    load_launch_library_2_to_duckdb()

Run it with python launch_library_2_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 Launch Library 2 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("launch_library_2_pipeline").dataset()
df = data.launch.df()
print(df.head())

SQL:

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SELECT * FROM launch_library_2_data.launch LIMIT 10;

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

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How do I deploy the Launch Library 2 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 Launch Library 2 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 Launch Library 2 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