Load Electricity Maps data to DuckDB
Build a Electricity Maps to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Electricity Maps API base URL, auth, endpoints, and incremental loading.
Electricity Maps is an API providing real-time, historical, and forecasted electricity data including carbon intensity, energy mix, and pricing for zones worldwide. Everything needed to build a working Electricity Maps → 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 Electricity Maps to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from Electricity Maps 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 Electricity Maps 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.
Electricity Maps API at a glance
| Base URL | https://api.electricitymaps.com/v3 |
| Example endpoint | GET v4/zones |
| Authentication | all requests require an 'auth-token' header containing the API key — sent in the auth-token header |
| Pagination | Not paginated |
| API reference | https://app.electricitymaps.com/developer-hub/api/getting-started |
These values come from the Electricity Maps API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the Electricity Maps API?
All API requests (except for /zones) must be authorized by including an API token in the 'auth-token' header. Basic Authentication is also supported as an alternative.
1. Get your credentials
To obtain your API credentials, navigate to the Electricity Maps dashboard at https://app.electricitymaps.com/dashboard. Sign in or create an account, then proceed to the API access page to generate or retrieve your API token. You may also explore the Developer Hub to request a trial or test with a token in the API playground.
2. Add them to .dlt/secrets.toml
[sources.electricity_maps_source] api_key = "your_auth_token_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 Electricity Maps data can I load into DuckDB?
These are the Electricity Maps endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| zones | /v4/zones | GET | Returns all zones mapped by Electricity Maps. | |
| data_centers | /v4/data-centers | GET | Returns all available data centers. | |
| carbon_intensity_latest | /v4/carbon-intensity/latest | GET | Returns the latest carbon intensity for a zone. | |
| electricity_mix_latest | /v4/electricity-mix/latest | GET | Returns the latest electricity mix for a zone. | |
| electricity_flows_latest | /v4/electricity-flows/latest | GET | Returns the latest electricity flows for a zone. |
How do I load only new Electricity Maps records?
The Electricity Maps 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": "zones", "endpoint": { "path": "v4/zones", # 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 Electricity Maps pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading /v3/zones and /v3/latest from the Electricity Maps API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def electricity_maps_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.electricitymaps.com/v3", "auth": {"type": "api_key", "api_key": api_key, "name": "auth-token", "location": "header"}, }, "resources": [ {"name": "zones", "endpoint": {"path": "v4/zones"}}, {"name": "carbon_intensity_latest", "endpoint": {"path": "v4/carbon-intensity/latest"}} ], } yield from rest_api_resources(config) def load_electricity_maps_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="electricity_maps_pipeline", destination="duckdb", dataset_name="electricity_maps_data", ) load_info = pipeline.run(electricity_maps_source()) print(load_info) if __name__ == "__main__": load_electricity_maps_to_duckdb()
Run it with python electricity_maps_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 Electricity Maps 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("electricity_maps_pipeline").dataset() df = data.zones.df() print(df.head())
SQL:
SELECT * FROM electricity_maps_data.zones LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the Electricity Maps 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 Electricity Maps 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 Electricity Maps 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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