Paradex Python API Docs | dltHub

Paradex API allows public and private endpoint access; public endpoints list markets, while private endpoints require JWT authentication for secure access. To start, call public endpoints like market listings. For private endpoints, follow authentication procedures. The REST API base URL is https://api.prod.paradex.trade/v1 and All non‑public requests require a JWT Bearer token; read‑only access uses Bearer tokens..

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 Paradex data in under 10 minutes.

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What data can I load from Paradex?

Here are some of the endpoints you can load from Paradex:

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How do I authenticate with the Paradex API?

Paradex uses JWT‑based authentication. Include an Authorization: Bearer <TOKEN> header for private endpoints; trading requests may also require PARADEX-STARKNET-ACCOUNT and PARADEX-STARKNET-SIGNATURE headers when using subkeys.

1. Get your credentials

1. Log into the Paradex web UI and navigate to Wallet → Key Management or Account Security.
2. Click Add New Key and select Readonly Token to generate a read‑only JWT. Copy the token.
3. For trading, choose Subkey (or export the main private key), then use the subkey public key with the /auth/{public_key} endpoint to obtain a JWT and sign requests with the subkey private key.
4. Store the token or subkey securely and revoke/rotate it from the Key Management dashboard when needed.

2. Add them to .dlt/secrets.toml

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[sources.paradex_source]
api_key = "your_readonly_jwt_here"

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.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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

1. Install the dlt AI Workbench:

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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:

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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 Paradex 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:

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python paradex_pipeline.py

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

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

Inspect your pipeline and data:

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dlt pipeline paradex_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.

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Python pipeline example

This example loads markets and account from the Paradex API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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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": "markets", "endpoint": {"path": "v1/markets", "data_selector": "results"}},
            {"name": "account", "endpoint": {"path": "v1/account"}}
        ],
    }
    yield from rest_api_resources(config)


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

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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):

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import dlt

data = dlt.pipeline("paradex_pipeline").dataset()
sessions_df = data.markets.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM paradex_data.markets LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("paradex_pipeline").dataset()
data.markets.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load Paradex 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.

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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.

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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