Gorgias Python API Docs | dltHub

Gorgias is a customer support help desk platform that provides a REST API for managing tickets, users, macros, and other resources. The REST API base URL is https://{your-domain}.gorgias.com/api and All requests require HTTP Basic authentication using an API token..

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 Gorgias data in under 10 minutes.

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What data can I load from Gorgias?

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

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How do I authenticate with the Gorgias API?

Authentication is performed via HTTP Basic auth where the API token is base64‑encoded and sent in the Authorization: Basic <token> header. The token can be retrieved from the Gorgias dashboard under Settings → You → REST API.

1. Get your credentials

1. Log in to your Gorgias account.
2. Click Settings in the left navigation.
3. Choose You.
4. Select REST API.
5. Copy the API token displayed; this token will be used for HTTP Basic authentication.
6. Keep the token secret and store it in your dlt secrets.toml file.

2. Add them to .dlt/secrets.toml

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[sources.gorgias_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 Gorgias 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 gorgias_pipeline.py

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

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Pipeline gorgias_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset gorgias_data
The duckdb destination used duckdb:/gorgias.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 gorgias_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 tickets and users from the Gorgias 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 gorgias_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{your-domain}.gorgias.com/api",
            "auth": {
                "type": "http_basic",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "tickets", "endpoint": {"path": "api/tickets", "data_selector": "data"}},
            {"name": "users", "endpoint": {"path": "api/users", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="gorgias_pipeline",
        destination="duckdb",
        dataset_name="gorgias_data",
    )
    load_info = pipeline.run(gorgias_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("gorgias_pipeline").dataset()
sessions_df = data.tickets.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM gorgias_data.tickets LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("gorgias_pipeline").dataset()
data.tickets.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 Gorgias 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

• 401 Unauthorized – The API token is missing, malformed, or invalid. Verify that the token from Settings → You → REST API is correctly base64‑encoded and placed in the Authorization: Basic <token> header.

Rate limiting

• 429 Too Many Requests – Gorgias enforces a rate limit per account. Reduce request frequency or implement exponential backoff and respect the Retry-After header if present.

Pagination quirks

• List endpoints may return a top‑level array or a paginated object with a data field and pagination cursors (next_page_url). Check the response structure and follow the next_page_url until it is null.

Unexpected response formats

• Some list endpoints return a top‑level array while others nest results under data. Inspect the first page of each endpoint to determine the correct data_selector for the dlt resource configuration.

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