CoinMarketCap Python API Docs | dltHub

CoinMarketCap is a cryptocurrency market data API providing real-time and historical pricing, market, exchange, fiat and metadata for cryptocurrencies and related resources. The REST API base URL is https://pro-api.coinmarketcap.com and all requests require an API key passed via header (preferred) or query param (legacy).

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 CoinMarketCap data in under 10 minutes.

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What data can I load from CoinMarketCap?

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

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How do I authenticate with the CoinMarketCap API?

Authentication uses a single API key. Include the key in the X-CMC_PRO_API_KEY HTTP header on every request (Accept: application/json recommended). As a convenience the key may be passed in the CMC_PRO_API_KEY query parameter, but header usage is strongly recommended for production.

1. Get your credentials

1. Visit https://coinmarketcap.com/api/ and sign up or log into Developer Portal. 2) Create or view a project/api key in the dashboard. 3) Copy the provided API Key string. 4) Use it in requests by setting X-CMC_PRO_API_KEY header or add CMC_PRO_API_KEY query param.

2. Add them to .dlt/secrets.toml

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[sources.coin_market_cap_source]
api_key = "your_api_key_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 CoinMarketCap 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 coin_market_cap_pipeline.py

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

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Pipeline coin_market_cap_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset coin_market_cap_data
The duckdb destination used duckdb:/coin_market_cap.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 coin_market_cap_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 cryptocurrency_listings_latest and cryptocurrency_quotes_latest from the CoinMarketCap 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 coin_market_cap_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://pro-api.coinmarketcap.com",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "cryptocurrency_listings_latest", "endpoint": {"path": "v1/cryptocurrency/listings/latest", "data_selector": "data"}},
            {"name": "cryptocurrency_quotes_latest", "endpoint": {"path": "v1/cryptocurrency/quotes/latest", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="coin_market_cap_pipeline",
        destination="duckdb",
        dataset_name="coin_market_cap_data",
    )
    load_info = pipeline.run(coin_market_cap_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("coin_market_cap_pipeline").dataset()
sessions_df = data.cryptocurrency_listings_latest.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM coin_market_cap_data.cryptocurrency_listings_latest LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("coin_market_cap_pipeline").dataset()
data.cryptocurrency_listings_latest.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 CoinMarketCap 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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Troubleshooting

Authentication failures

If the X-CMC_PRO_API_KEY header is missing or invalid the API returns HTTP 401 and a status.error_code (e.g. 1002/1001). Verify the API key value, ensure it's sent in X-CMC_PRO_API_KEY, and that the key is active for your plan.

Rate limits and throttling

Requests are rate-limited by API key and by IP. Exceeding per-minute, daily, or monthly limits returns HTTP 429 with status.error_code values such as 1008 (minute limit), 1009 (daily), or 1010 (monthly). Implement backoff (sleep/retry) and consider paging or plan upgrade.

Permission / plan errors

If an endpoint isn't permitted for your plan the API returns HTTP 403 with status.error_code like 1006. Check your subscription plan and the endpoint availability matrix on the Developer Portal.

Pagination and bundling quirks

Listing endpoints use start and limit query params for pagination. Many endpoints support bundling by id or symbol; when multiple identifiers are passed the data object is returned as a map keyed by the identifier (e.g. "BTC" or "1") instead of an array. Always read the top-level "data" key and handle both array and object-map shapes.

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

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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