Alpaca Markets Python API Docs | dltHub

Alpaca Markets is an API-first platform that provides real-time market pricing data and historical data for stocks and crypto, enabling anyone to access modern trading solutions. The REST API base URL is https://api.alpaca.markets and Most requests require authentication by passing an API key and secret pair in HTTP request headers..

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 Alpaca Markets data in under 10 minutes.

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What data can I load from Alpaca Markets?

Here are some of the endpoints you can load from Alpaca Markets:

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How do I authenticate with the Alpaca Markets API?

Authentication for most market data endpoints involves providing an API key and secret in the HTTP headers APCA-API-KEY-ID and APCA-API-SECRET-KEY. The Broker API uses client credentials to exchange for an access token, which is then used as a Bearer token.

1. Get your credentials

Instructions for obtaining API credentials from the provider's dashboard are not available in the provided documentation.

2. Add them to .dlt/secrets.toml

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[sources.alpaca_markets_source]
api_key_id = "your_api_key_id_here"
api_secret_key = "your_api_secret_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 Alpaca Markets 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 alpaca_markets_pipeline.py

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

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Pipeline alpaca_markets_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset alpaca_markets_data
The duckdb destination used duckdb:/alpaca_markets.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 alpaca_markets_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 stock_quotes and stock_bars from the Alpaca Markets 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 alpaca_markets_source(api_key_id, api_secret_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.alpaca.markets",
            "auth": {
                "type": "api_key",
                "api_key_id, api_secret_key": api_key_id, api_secret_key,
            },
        },
        "resources": [
            {"name": "stock_quotes", "endpoint": {"path": "v1/stocks/{symbol}/quotes", "data_selector": "quotes"}},
            {"name": "stock_bars", "endpoint": {"path": "v1/stocks/{symbol}/bars", "data_selector": "bars"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="alpaca_markets_pipeline",
        destination="duckdb",
        dataset_name="alpaca_markets_data",
    )
    load_info = pipeline.run(alpaca_markets_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("alpaca_markets_pipeline").dataset()
sessions_df = data.stockquotes.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM alpaca_markets_data.stockquotes LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("alpaca_markets_pipeline").dataset()
data.stockquotes.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 Alpaca Markets 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

Alpaca Markets APIs require authentication using an API key and secret. Ensure that APCA-API-KEY-ID and APCA-API-SECRET-KEY headers are correctly set for market data endpoints. For the Broker API, an OAuth2 token obtained via client credentials must be used as a Bearer token. Incorrect or missing credentials will result in authentication errors.

API Domain Mismatch

Alpaca APIs are hosted on different domains for trading, market data, and paper trading. Ensure you are using the correct base URL for the specific API you are trying to access (e.g., api.alpaca.markets for Trading API, data.alpaca.markets for Market Data API, paper-api.alpaca.markets for Paper Trading). Using the wrong domain can lead to connection issues or unexpected responses.

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