Load Paradex data to DuckDB

Paradex is a decentralized derivatives trading platform providing a REST API for accessing market data and private account operations. Everything needed to build a working Paradex → 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 Paradex 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 Paradex 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 Paradex 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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Paradex API at a glance

These values come from the Paradex API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Paradex API?

Private REST API endpoints require a JWT provided as a Bearer token in the Authorization header. Users must first generate this JWT by authenticating with their wallet via the auth endpoint.

1. Get your credentials

1. Log into your Paradex account on the official web UI (https://app.paradex.trade). 2. Navigate to the 'Wallet' tab or 'Account Security' settings to find the 'Key Management' section. 3. For read-only access (recommended for data pipelines), click '+ Add New Key' and select 'Readonly Token' to generate and copy the JWT. 4. For trading access, select 'Subkeys' to generate a subkey; you will receive a private key that must be stored securely, as it is only displayed once.

2. Add them to .dlt/secrets.toml

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[sources.paradex_source]
api_key = "your_readonly_jwt_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 Paradex data can I load into DuckDB?

These are the Paradex endpoints dlt can load into DuckDB:

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How do I load only new Paradex records?

The Paradex 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.

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{"name": "orders", "endpoint": {
    "path": "orders",
    # 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.

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What does the generated Paradex pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading markets and account from the Paradex API into DuckDB:

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

@dlt.source
def paradex_source(token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.prod.paradex.trade/v1",
            "auth": {"type": "bearer", "token": token},
        },
        "resources": [
            {"name": "orders", "endpoint": {"path": "orders", "data_selector": "results"}},
            {"name": "trades", "endpoint": {"path": "trades", "data_selector": "results"}}
        ],
    }
    yield from rest_api_resources(config)


def load_paradex_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="paradex_pipeline",
        destination="duckdb",
        dataset_name="paradex_data",
    )
    load_info = pipeline.run(paradex_source())
    print(load_info)


if __name__ == "__main__":
    load_paradex_to_duckdb()

Run it with python paradex_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 Paradex 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("paradex_pipeline").dataset()
df = data.orders.df()
print(df.head())

SQL:

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SELECT * FROM paradex_data.orders LIMIT 10;

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

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How do I deploy the Paradex 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 Paradex 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 Paradex 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