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Load Bible API data to DuckDB

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

SourceBible APIBible API API DocumentationDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

API.Bible provides a REST API for accessing Bible content including various translations and languages. Everything needed to build a working Bible 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 Bible 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 Bible 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 Bible 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.


Bible API API at a glance

Base URLhttps://rest.api.bible/v1
Example endpointGET v1/bibles
Records found atdata
Authenticationall requests require an 'api-key' header — sent in the api-key header
PaginationCursor-based via page_token, next cursor at meta.next_page_token, page size via page_size (default 1, max 99). Use page_token from the previous response's next_page_token to fetch subsequent pages. page_size must be between 1 and 99; API.Bible also supports page_size=* only under specific field conditions.
API referencehttps://scripture.api.bible/docs

These values come from the Bible API API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the Bible API API?

All requests must include a header named 'api-key' containing the user's secret API key.

1. Get your credentials

  1. Register or sign in as a developer at https://scripture.api.bible. 2. Navigate to the dashboard after your account/application is approved. 3. Locate the 'Apps' section or 'Dashboard settings' to create a new app. 4. Retrieve your secret API key from the application details or API Keys section.

2. Add them to .dlt/secrets.toml

[sources.bible_api_source] api_key = "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.


What Bible API data can I load into DuckDB?

These are the Bible API endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
bibles/v1/biblesGETdataReturns a list of available Bible versions.
bible_books/v1/bibles/{bible_id}/booksGETdataReturns a list of books for a specific Bible.
bible_chapters/v1/bibles/{bible_id}/books/{book_id}/chaptersGETdataReturns a list of chapters for a specific book.
bible_verses/v1/bibles/{bible_id}/books/{book_id}/chapters/{chapter_id}/versesGETdataReturns a list of verses for a specific chapter.
bible_details/v1/bibles/{bible_id}GETdataReturns metadata for a specific Bible version.

How do I load only new Bible API records?

The Bible API 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": "bibles", "endpoint": { "path": "v1/bibles", # 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 Bible API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /bibles and /bibles/{bibleId}/passages/{passageId} from the Bible API API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def bible_api_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://rest.api.bible/v1", "auth": {"type": "api_key", "api_key": api_key, "name": "api-key", "location": "header"}, }, "resources": [ {"name": "bibles", "endpoint": {"path": "v1/bibles", "data_selector": "data"}}, {"name": "bible_books", "endpoint": {"path": "v1/bibles/{bible_id}/books", "data_selector": "data"}} ], } yield from rest_api_resources(config) def load_bible_api_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="bible_api_pipeline", destination="duckdb", dataset_name="bible_api_data", ) load_info = pipeline.run(bible_api_source()) print(load_info) if __name__ == "__main__": load_bible_api_to_duckdb()

Run it with python bible_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 Bible 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("bible_api_pipeline").dataset() df = data.bibles.df() print(df.head())

SQL:

SELECT * FROM bible_api_data.bibles LIMIT 10;

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


How do I deploy the Bible 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 Bible 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 Bible 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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