Coupon-carrier Python API Docs | dltHub

Coupon Carrier is a service that helps manage and distribute unique coupon codes for marketing campaigns, primarily integrating with other applications through Zapier or private APIs. The REST API base URL is https://api.couponcarrier.io/v2 and All requests require an API key for authentication, typically used as the username in a basic authentication 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 Coupon-carrier data in under 10 minutes.

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What data can I load from Coupon-carrier?

Here are some of the endpoints you can load from Coupon-carrier:

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How do I authenticate with the Coupon-carrier API?

Authentication is performed using an API key. For basic authentication, the API key should be used as the username, and the password can be any value.

1. Get your credentials

Your API Key can be found under your account settings in the Coupon Carrier dashboard.

2. Add them to .dlt/secrets.toml

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[sources.coupon_carrier_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 Coupon-carrier 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 coupon_carrier_pipeline.py

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

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Pipeline coupon_carrier_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset coupon_carrier_data
The duckdb destination used duckdb:/coupon_carrier.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 coupon_carrier_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 No two commonly used endpoints can be identified from the provided documentation. from the Coupon-carrier 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 coupon_carrier_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.couponcarrier.io/v2",
            "auth": {
                "type": "http_basic",
                "username": api_key,
            },
        },
        "resources": [
            
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="coupon_carrier_pipeline",
        destination="duckdb",
        dataset_name="coupon_carrier_data",
    )
    load_info = pipeline.run(coupon_carrier_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("coupon_carrier_pipeline").dataset()
sessions_df = data.get_code.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM coupon_carrier_data.get_code LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("coupon_carrier_pipeline").dataset()
data.get_code.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 Coupon-carrier 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

API Access

Coupon Carrier does not offer a public API. Access to private APIs is granted on a case-by-case basis. If you require direct integration and Zapier does not meet your needs, you must contact Coupon Carrier for more information and potential access.

Authentication Issues

When using the API key for basic authentication, ensure your Coupon Carrier API key is used as the username. The password field can be set to any value, such as "blank". If authentication fails, verify that the API key is correctly entered and obtained from your account settings in the Coupon Carrier dashboard.

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