Firstpromoter Python API Docs | dltHub

FirstPromoter is an affiliate and referral tracking platform that provides REST APIs to programmatically access promoters, referrals, campaigns, payments, reports and related data. The REST API base URL is v2: https://api.firstpromoter.com/api/v2 v1 (legacy): https://firstpromoter.com/api/v1 and v2: Bearer token plus Account-ID header; v1: X-API-KEY header..

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 Firstpromoter data in under 10 minutes.

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What data can I load from Firstpromoter?

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

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How do I authenticate with the Firstpromoter API?

v2 requires the Authorization header with a Bearer API key and the Account-ID header for the target account. v1 expects the X-API-KEY header with the API key.

1. Get your credentials

1. Log in to the FirstPromoter dashboard. 2) Navigate to Settings → Integrations → Manage API Keys. 3) Create a new API key (provide a name) and copy the token. 4) Note your Account ID shown in the integrations/API panel (required for v2 requests).

2. Add them to .dlt/secrets.toml

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[sources.firstpromoter_source]
api_key = "your_api_key_here"
account_id = "your_account_id_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 Firstpromoter 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 firstpromoter_pipeline.py

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

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Pipeline firstpromoter_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset firstpromoter_data
The duckdb destination used duckdb:/firstpromoter.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 firstpromoter_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 referrals and affiliates from the Firstpromoter 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 firstpromoter_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "v2: https://api.firstpromoter.com/api/v2
v1 (legacy): https://firstpromoter.com/api/v1",
            "auth": {
                "type": "bearer",
                "token": api_key,
            },
        },
        "resources": [
            {"name": "referrals", "endpoint": {"path": "company/referrals"}},
            {"name": "affiliates", "endpoint": {"path": "company/affiliates"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="firstpromoter_pipeline",
        destination="duckdb",
        dataset_name="firstpromoter_data",
    )
    load_info = pipeline.run(firstpromoter_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("firstpromoter_pipeline").dataset()
sessions_df = data.referrals.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM firstpromoter_data.referrals LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("firstpromoter_pipeline").dataset()
data.referrals.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 Firstpromoter 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 you receive 401/403, ensure you send the correct headers: v2 requires Authorization: Bearer <token> and Account-ID: <account_id>. v1 requires X-API-KEY: <api_key>. Verify the token is active and not revoked.

Rate limits

FirstPromoter enforces 400 requests per minute per account (v2). Exceeding this limit returns 429 Too Many Requests. Implement exponential backoff retries.

Pagination and iterating lists

List endpoints use page (default 1) and per_page (default 20, max 100) query parameters. Continue fetching pages until the returned array is empty or a Link header indicates no further pages.

Common error codes

• 401 Unauthorized – invalid or missing credentials
• 403 Forbidden – insufficient permissions or account mismatch
• 404 Not Found – requested resource does not exist
• 429 Too Many Requests – rate limit exceeded
• 422 Unprocessable Entity – invalid request parameters

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