Kyve Network Python API Docs | dltHub

Kyve Network is a decentralized data archival and access platform that provides trustless REST APIs to retrieve verified historical blockchain data. The REST API base URL is https://data.services.kyve.network and public/free trustless endpoints; no API key required for KYVE Trustless API (public access)..

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 Kyve Network data in under 10 minutes.

---

What data can I load from Kyve Network?

Here are some of the endpoints you can load from Kyve Network:

---

How do I authenticate with the Kyve Network API?

The Trustless API is public and does not require authentication for KYVE‑hosted endpoints. Requests are standard HTTPS GETs; verification is done via Merkle proofs returned in responses, which clients validate against on‑chain Merkle roots.

1. Get your credentials

No credentials required for the hosted Trustless API. To run a private Trustless API or node, follow docs to run your own endpoint (see Run Your Own API Endpoint in KYVE docs).

2. Add them to .dlt/secrets.toml

Copy
[sources.kyve_network_source]
# No credentials required for public Trustless API

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:

Copy
uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

Copy
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:

Copy
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 Kyve Network 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:

Copy
python kyve_network_pipeline.py

If everything is configured correctly, you'll see output like this:

Copy
Pipeline kyve_network_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset kyve_network_data
The duckdb destination used duckdb:/kyve_network.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

Copy
dlt pipeline kyve_network_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 beacon_blob_sidecars and eth_blobs from the Kyve Network API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

Copy
import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def kyve_network_source(=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://data.services.kyve.network",
            "auth": {
                "type": "",
                "": ,
            },
        },
        "resources": [
            {"name": "beacon_blob_sidecars", "endpoint": {"path": "beacon/blob_sidecars", "data_selector": "data"}},
            {"name": "eth_blobs", "endpoint": {"path": "eth/eth_blobs", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="kyve_network_pipeline",
        destination="duckdb",
        dataset_name="kyve_network_data",
    )
    load_info = pipeline.run(kyve_network_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):

Copy
import dlt

data = dlt.pipeline("kyve_network_pipeline").dataset()
sessions_df = data.beacon_blob_sidecars.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM kyve_network_data.beacon_blob_sidecars LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("kyve_network_pipeline").dataset()
data.beacon_blob_sidecars.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 Kyve Network data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

---

Troubleshooting

Authentication failures

KYVE Trustless API endpoints hosted at data.services.kyve.network are public and do not require authentication. If running your own endpoint with access controls, ensure the server's configuration allows public GETs or provide credentials per your deployment.

Rate limits and pricing

The official KYVE Trustless API is free to use without query limits per the docs. Self‑hosted endpoints may impose limits depending on deployment and infra.

Pagination and large responses

Endpoints serving lists (e.g., bundles or collections) may provide pagination or query parameters; consult the specific dataset docs. For large data items, the Trustless API may redirect to storage provider URLs (S3/local) depending on server config; follow redirects to retrieve the actual payload.

Verification errors (Merkle proof mismatch)

If the returned inclusion proof does not reconstruct the on‑chain Merkle root, treat the data as invalid. Ensure you request the correct bundleId/chainId/poolId and fetch the corresponding bundle summary from an independent KYVE node to compare the merkle root.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

---

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.

Copy
dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack