Load Words API data to DuckDB
Build a Words API to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Words API API base URL, auth, endpoints, and incremental loading.
Words API is a RESTful English-language dictionary, thesaurus, and lexical-relationship service providing definitions, synonyms, antonyms, pronunciation, and other linguistic metadata for over 150,000 words. Everything needed to build a working Words 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 Words API to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from Words 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 Words 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.
Words API API at a glance
| Base URL | https://wordsapiv1.p.rapidapi.com |
| Example endpoint | GET words/ |
| Records found at | results.data |
| Authentication | all requests require RapidAPI authentication headers — sent in the X-RapidAPI-Key header |
| Also required | X-RapidAPI-Host |
| Pagination | Page-number |
| API reference | https://www.wordsapi.com/docs/ |
These values come from the Words API API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the Words API API?
Authentication is managed via the RapidAPI marketplace, requiring two headers for every request: X-RapidAPI-Key (your subscription key) and X-RapidAPI-Host (wordsapiv1.p.rapidapi.com).
1. Get your credentials
- Sign up for a free account at the RapidAPI marketplace (https://rapidapi.com/). 2. Search for the 'Words API' in the RapidAPI catalog. 3. Subscribe to a pricing plan (a free tier is available). 4. Upon subscription, you will be assigned an API key, which can be found in your RapidAPI Developer Dashboard under 'My Apps' -> 'Security' or the API's 'Endpoints' tab under 'Header Parameters' as X-RapidAPI-Key.
2. Add them to .dlt/secrets.toml
[sources.words_api_source] x_rapidapi_key = "your_actual_api_key_here" x_rapidapi_host = "wordsapiv1.p.rapidapi.com"
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 Words API data can I load into DuckDB?
These are the Words API endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| word | words/{word} | GET | Get full lexical entry for a single word. | |
| rhymes | words/{word}/rhymes | GET | Get rhymes for a word. | |
| syllables | words/{word}/syllables | GET | Get syllable breakdown for a word. | |
| pronunciation | words/{word}/pronunciation | GET | Get IPA pronunciation for a word. | |
| search | words/ | GET | results.data | Search words with filters (requires page/limit for pagination). |
How do I load only new Words API records?
The Words 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": "search", "endpoint": { "path": "words/", # 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 Words API pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading /words/{word} and /words/ from the Words API API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def words_api_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://wordsapiv1.p.rapidapi.com", "auth": {"type": "api_key", "api_key": api_key, "name": "X-RapidAPI-Key", "location": "header"}, }, "resources": [ {"name": "search", "endpoint": {"path": "words/", "data_selector": "results.data"}}, {"name": "word", "endpoint": {"path": "words/{word}"}} ], } yield from rest_api_resources(config) def load_words_api_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="words_api_pipeline", destination="duckdb", dataset_name="words_api_data", ) load_info = pipeline.run(words_api_source()) print(load_info) if __name__ == "__main__": load_words_api_to_duckdb()
Run it with python words_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 Words 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("words_api_pipeline").dataset() df = data.search.df() print(df.head())
SQL:
SELECT * FROM words_api_data.search LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the Words 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 Words API 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 Words API 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.
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