Load CoinPaprika data to DuckDB
Build a CoinPaprika to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the CoinPaprika API base URL, auth, endpoints, and incremental loading.
CoinPaprika is a cryptocurrency data platform providing market data such as coin prices, volumes, market caps, and historical trends via REST and WebSocket APIs. Everything needed to build a working CoinPaprika → 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 CoinPaprika to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from CoinPaprika 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 CoinPaprika 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.
CoinPaprika API at a glance
| Base URL | https://api-pro.coinpaprika.com/v1/ |
| Example endpoint | GET v1/coins |
| Authentication | all requests to pro/paid tiers require an Authorization header with the API key — sent in the Authorization header |
| Pagination | Not paginated |
| Record id | id |
| API reference | https://docs.coinpaprika.com/api-reference/rest-api/introduction |
These values come from the CoinPaprika API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the CoinPaprika API?
Requests to paid tiers require an API key to be passed in the Authorization header. No prefix (like 'Bearer') is used; the key is provided directly as the header value.
1. Get your credentials
To obtain an API key for CoinPaprika's paid plans, navigate to the official CoinPaprika API Developer Portal (https://coinpaprika.com/api/panel/) after signing in. If you do not have an account, visit the pricing page or API landing page to sign up for a plan. For the Free tier, no API key or registration is required.
2. Add them to .dlt/secrets.toml
[sources.coinpaprika_source] coinpaprika_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 CoinPaprika data can I load into DuckDB?
These are the CoinPaprika endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| coins | /v1/coins | GET | List all available coins | |
| tickers | /v1/tickers | GET | Get ticker data for all active coins | |
| ticker_by_id | /v1/tickers/{coin_id} | GET | Get ticker data for a specific coin | |
| exchanges | /v1/exchanges | GET | List all supported exchanges | |
| global | /v1/global | GET | Get global market overview | |
| search | /v1/search | GET | Search for currencies, exchanges, etc. |
How do I load only new CoinPaprika records?
The CoinPaprika 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": "coins", "endpoint": { "path": "v1/coins", # 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 CoinPaprika pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading /tickers and /key/info from the CoinPaprika API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def coinpaprika_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api-pro.coinpaprika.com/v1/", "auth": {"type": "api_key", "api_key": api_key, "name": "Authorization", "location": "header"}, }, "resources": [ {"name": "coins", "endpoint": {"path": "v1/coins"}}, {"name": "tickers", "endpoint": {"path": "v1/tickers"}} ], } yield from rest_api_resources(config) def load_coinpaprika_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="coinpaprika_pipeline", destination="duckdb", dataset_name="coinpaprika_data", ) load_info = pipeline.run(coinpaprika_source()) print(load_info) if __name__ == "__main__": load_coinpaprika_to_duckdb()
Run it with python coinpaprika_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 CoinPaprika 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("coinpaprika_pipeline").dataset() df = data.tickers.df() print(df.head())
SQL:
SELECT * FROM coinpaprika_data.tickers LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the CoinPaprika 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 CoinPaprika 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 CoinPaprika 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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