Load Transistor data to DuckDB
Build a Transistor to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Transistor API base URL, auth, endpoints, and incremental loading.
Transistor is a podcast hosting and analytics platform that provides a REST API to manage shows, episodes, and analytics data. Everything needed to build a working Transistor → 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 Transistor to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from Transistor 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 Transistor 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.
Transistor API at a glance
| Base URL | https://api.transistor.fm/v1/ |
| Example endpoint | GET v1/shows |
| Records found at | data |
| Authentication | all requests require an x-api-key header — sent in the x-api-key header |
| Pagination | Page-number page size via pagination[per] (default 10). Pagination is controlled by page number and per-page resource count using query parameters named pagination[page] (default 0) and pagination[per] (default 10). The documentation provided does not mention any cursor/max-results limit or a max page size value. |
| Record id | id |
| API reference | https://developers.transistor.fm/ |
These values come from the Transistor API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the Transistor API?
The Transistor API requires an HTTP header named 'x-api-key' containing your unique API key, which can be generated in the Account Area of your Transistor dashboard.
1. Get your credentials
- Log in to your Transistor.fm account at https://dashboard.transistor.fm/. 2. Navigate to the Account page (often via the profile icon). 3. Locate the API Access section at https://dashboard.transistor.fm/account. 4. Copy the displayed API key from this section for use in your application.
2. Add them to .dlt/secrets.toml
[sources.transistor_source] transistor_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 Transistor data can I load into DuckDB?
These are the Transistor endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| shows | v1/shows | GET | data | Retrieve a paginated list of shows |
| episodes | v1/episodes | GET | data | Retrieve a paginated list of episodes |
| show_details | v1/shows/:id | GET | data | Retrieve a single show |
| episode_details | v1/episodes/:id | GET | data | Retrieve a single episode |
| subscribers | v1/subscribers | GET | data | Retrieve a paginated list of subscribers |
How do I load only new Transistor records?
The Transistor 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": "shows", "endpoint": { "path": "v1/shows", # 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 Transistor pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading /v1/shows and /v1/subscribers from the Transistor API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def transistor_source(access_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.transistor.fm/v1/", "auth": {"type": "api_key", "api_key": access_token, "name": "x-api-key", "location": "header"}, }, "resources": [ {"name": "shows", "endpoint": {"path": "v1/shows", "data_selector": "data"}}, {"name": "episodes", "endpoint": {"path": "v1/episodes", "data_selector": "data"}} ], } yield from rest_api_resources(config) def load_transistor_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="transistor_pipeline", destination="duckdb", dataset_name="transistor_data", ) load_info = pipeline.run(transistor_source()) print(load_info) if __name__ == "__main__": load_transistor_to_duckdb()
Run it with python transistor_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 Transistor 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("transistor_pipeline").dataset() df = data.episodes.df() print(df.head())
SQL:
SELECT * FROM transistor_data.episodes LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the Transistor 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 Transistor 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 Transistor 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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