Open Government, Spain Python API Docs | dltHub
Build a Open Government, Spain-to-database pipeline in Python using dlt with AI Workbench support for Claude Code, Cursor, and Codex.
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The Open Government API of Spain provides access to the Government's data catalogue and primary sector taxonomy. It uses URIs for queries and offers documentation and examples. The API aims to improve transparency and data reuse. The REST API base URL is https://datos.gob.es/apidata and No authentication required (public API)..
dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading Open Government, Spain data in under 10 minutes.
What data can I load from Open Government, Spain?
Here are some of the endpoints you can load from Open Government, Spain:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| catalog_dataset | /catalog/dataset | GET | dataset | Obtain datasets in the catalogue (supports pagination, sorting and many filter paths such as /title/{title}, /publisher/{id}, /theme/{id}, /format/{format}, /spatial/{...}) |
| catalog_dataset_id | /catalog/dataset/{id} | GET | Obtain a dataset by its id (single dataset object) | |
| catalog_distribution | /catalog/distribution | GET | distribution | List all distributions (files/resources) |
| catalog_distribution_dataset | /catalog/distribution/dataset/{id} | GET | Distributions for a specific dataset id | |
| catalog_publisher | /catalog/publisher | GET | publisher | List publishers in the catalogue |
How do I authenticate with the Open Government, Spain API?
The datos.gob.es apidata is a public API; requests do not require credentials. Response format defaults to JSON and can be changed via the Accept header or URL extension (e.g., .json).
1. Get your credentials
No credentials needed — the API is public. Simply call endpoints directly; optionally set the Accept header or use .json/.xml/.csv extensions to request a specific response format.
2. Add them to .dlt/secrets.toml
[sources.open_government_spain_source]
dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.
How do I set up and run the pipeline?
Set up a virtual environment and install dlt:
uv venv && source .venv/bin/activate uv pip install "dlt[workspace]"
1. Install the dlt AI Workbench:
dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex
This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →
2. Install the rest-api-pipeline toolkit:
dlt ai toolkit rest-api-pipeline install
This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →
3. Start LLM-assisted coding:
Use /find-source to load data from the Open Government, Spain API into DuckDB.
The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.
4. Run the pipeline:
python open_government_spain_pipeline.py
If everything is configured correctly, you'll see output like this:
Pipeline open_government_spain_pipeline load step completed in 0.26 seconds 1 load package(s) were loaded to destination duckdb and into dataset open_government_spain_data The duckdb destination used duckdb:/open_government_spain.duckdb location to store data Load package 1749667187.541553 is LOADED and contains no failed jobs
Inspect your pipeline and data:
dlt pipeline open_government_spain_pipeline show
This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.
Python pipeline example
This example loads catalog_dataset and catalog_distribution from the Open Government, Spain API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def open_government_spain_source(=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://datos.gob.es/apidata", "auth": { "type": "none", "": , }, }, "resources": [ {"name": "catalog_dataset", "endpoint": {"path": "catalog/dataset", "data_selector": "dataset"}}, {"name": "catalog_distribution", "endpoint": {"path": "catalog/distribution", "data_selector": "distribution"}} ], } yield from rest_api_resources(config) def get_data() -> None: pipeline = dlt.pipeline( pipeline_name="open_government_spain_pipeline", destination="duckdb", dataset_name="open_government_spain_data", ) load_info = pipeline.run(open_government_spain_source()) print(load_info)
To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.
How do I query the loaded data?
Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.
Python (pandas DataFrame):
import dlt data = dlt.pipeline("open_government_spain_pipeline").dataset() sessions_df = data.catalog_dataset.df() print(sessions_df.head())
SQL (DuckDB example):
SELECT * FROM open_government_spain_data.catalog_dataset LIMIT 10;
In a marimo or Jupyter notebook:
import dlt data = dlt.pipeline("open_government_spain_pipeline").dataset() data.catalog_dataset.df().head()
See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.
What destinations can I load Open Government, Spain data to?
dlt supports loading into any of these destinations — only the destination parameter changes:
| Destination | Example value |
|---|---|
| DuckDB (local, default) | "duckdb" |
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.
Next steps
Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:
data-exploration— Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.dlthub-runtime— Deploy, schedule, and monitor your pipeline in production.
dlt ai toolkit data-exploration install dlt ai toolkit dlthub-runtime install
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