Load 0x data to DuckDB

0x API is a decentralized exchange aggregator service providing liquidity for token swaps across multiple blockchain networks. Everything needed to build a working 0x → 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.

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Build your 0x to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from 0x 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 0x 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.

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0x API at a glance

These values come from the 0x API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the 0x API?

Requests require an '0x-api-key' header for the API key and an '0x-version' header (typically set to 'v2') to specify the API version.

1. Get your credentials

1. Navigate to the 0x Dashboard at https://dashboard.0x.org/apps and click Sign Up to create an account. 2. Once logged in, click Create an app. 3. Enter your app name and select the required 0x products (e.g., Swap API). 4. After the app is created, navigate to the API Keys section within your app's dashboard view. 5. Click to reveal and copy your API key.

2. Add them to .dlt/secrets.toml

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[sources._0x_source]
0x_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.

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What 0x data can I load into DuckDB?

These are the 0x endpoints dlt can load into DuckDB:

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How do I load only new 0x records?

0x exposes cursor on trade-analytics/swap, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "trade_analytics_swap", "endpoint": {
    "path": "trade-analytics/swap",
    "data_selector": "records",
    "incremental": {"cursor_path": "cursor", "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.

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What does the generated 0x pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /swap/permit2/quote and /swap/allowance-holder/quote from the 0x API into DuckDB:

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

@dlt.source
def _0x_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.0x.org",
            "auth": {"type": "api_key", "api_key": api_key, "name": "0x-api-key", "location": "header"},
        },
        "resources": [
            {"name": "trade_analytics_swap", "endpoint": {"path": "trade-analytics/swap", "data_selector": "records"}},
            {"name": "trade_analytics_gasless", "endpoint": {"path": "trade-analytics/gasless", "data_selector": "records"}}
        ],
    }
    yield from rest_api_resources(config)


def load__0x_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="_0x_pipeline",
        destination="duckdb",
        dataset_name="_0x_data",
    )
    load_info = pipeline.run(_0x_source())
    print(load_info)


if __name__ == "__main__":
    load__0x_to_duckdb()

Run it with python _0x_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query 0x 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):

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import dlt

data = dlt.pipeline("_0x_pipeline").dataset()
df = data.trade_analytics_swap.df()
print(df.head())

SQL:

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SELECT * FROM _0x_data.trade_analytics_swap LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the 0x 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 0x loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load 0x data to?

dlt loads into any of these — only the destination argument changes:

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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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack