Galileo Financial Technologies Python API Docs | dltHub

Galileo is a platform to build and scale financial products and provide program-level REST APIs for account, card, transaction, events, and risk management. The REST API base URL is https://api.galileo-ft.com and Authentication uses provider credentials (Provider ID, username and password) over TLS..

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 Galileo Financial Technologies data in under 10 minutes.

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What data can I load from Galileo Financial Technologies?

Here are some of the endpoints you can load from Galileo Financial Technologies:

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How do I authenticate with the Galileo Financial Technologies API?

Requests must be made over HTTPS and include the provider username and password, typically via HTTP Basic Authentication.

1. Get your credentials

1. Contact Galileo sales/onboarding team to request API access.
2. Complete the onboarding questionnaire.
3. Galileo will provision a Provider ID, username, and password and share the secure web address.
4. Record these credentials for use in your dlt configuration.

2. Add them to .dlt/secrets.toml

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[sources.galileo_phone_validation_source]
provider_id = "YOUR_PROVIDER_ID"
username = "YOUR_USERNAME"
password = "YOUR_PASSWORD"

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 Galileo Financial Technologies 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 galileo_phone_validation_pipeline.py

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

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Pipeline galileo_phone_validation_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset galileo_phone_validation_data
The duckdb destination used duckdb:/galileo_phone_validation.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 galileo_phone_validation_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 phone_validation and accounts from the Galileo Financial Technologies 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 galileo_phone_validation_source(provider_id=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.galileo-ft.com",
            "auth": {
                "type": "http_basic",
                "password": provider_id,
            },
        },
        "resources": [
            {"name": "phone_validation", "endpoint": {"path": "api/v1/validation/phone"}},
            {"name": "accounts", "endpoint": {"path": "api/v1/accounts", "data_selector": "accounts"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="galileo_phone_validation_pipeline",
        destination="duckdb",
        dataset_name="galileo_phone_validation_data",
    )
    load_info = pipeline.run(galileo_phone_validation_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("galileo_phone_validation_pipeline").dataset()
sessions_df = data.phone_validation.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM galileo_phone_validation_data.phone_validation LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("galileo_phone_validation_pipeline").dataset()
data.phone_validation.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 Galileo Financial Technologies 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 Errors

• Return a 401 Unauthorized when provider credentials are missing or invalid. Verify that the Provider ID, username and password are correct and sent over HTTPS.

Rate Limits

• The API enforces rate limits per provider; exceeding the limit results in a 429 Too Many Requests response. The exact limits are not published, so monitor response headers for X-RateLimit-Remaining and implement exponential back‑off.

Pagination

• List endpoints return paginated results using page and pageSize query parameters. The response includes a nextPageToken when more records are available.

General Errors

• Errors are returned as JSON objects containing code and message fields. Common HTTP status codes include 400 (bad request), 404 (not found), and 500 (internal server error).

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