Etsy Python API Docs | dltHub

Etsy Open API v3 is a REST API that provides access to inventory, sales orders, and shop management on the Etsy platform. The REST API base URL is https://api.etsy.com/v3/ and All requests require an x‑api‑key header; OAuth2‑protected endpoints also require a Bearer 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 Etsy data in under 10 minutes.

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What data can I load from Etsy?

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

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How do I authenticate with the Etsy API?

Etsy API requires an x-api-key header with the app key and secret for all requests; endpoints that need OAuth2 scopes also require an Authorization: Bearer <token> header.

1. Get your credentials

1. Sign in to your Etsy account and go to the Developer portal.
2. Create a new app or select an existing app.
3. Copy the "API Key" and "Shared Secret" shown on the app details page; combine them as <key>:<secret> for the x-api-key header.
4. To get an OAuth2 token, send a POST request to https://api.etsy.com/v3/public/oauth/token with your client credentials and required scopes.
5. Extract the access_token field from the response and use it in the Authorization: Bearer <access_token> header.

2. Add them to .dlt/secrets.toml

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[sources.etsy_source]
api_key = "your_api_key_here"
shared_secret = "your_shared_secret_here"
access_token = "your_oauth2_token_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 Etsy 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 etsy_pipeline.py

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

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Pipeline etsy_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset etsy_data
The duckdb destination used duckdb:/etsy.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 etsy_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 listings_active and shops_listings from the Etsy 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 etsy_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.etsy.com/v3/",
            "auth": {
                "type": "api_key",
                "token": api_key,
            },
        },
        "resources": [
            {"name": "listings_active", "endpoint": {"path": "application/listings/active", "data_selector": "results"}},
            {"name": "shops_listings", "endpoint": {"path": "application/shops/{shop_id}/listings", "data_selector": "results"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="etsy_pipeline",
        destination="duckdb",
        dataset_name="etsy_data",
    )
    load_info = pipeline.run(etsy_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("etsy_pipeline").dataset()
sessions_df = data.listings_active.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM etsy_data.listings_active LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("etsy_pipeline").dataset()
data.listings_active.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 Etsy 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

If the x-api-key header is missing or malformed, the API returns a 401 Unauthorized response. Ensure the header value is <api_key>:<shared_secret>.

Rate limiting and pagination

The API caps the number of records per request to 100 (default 25). Use the limit and offset query parameters to page through results. The response includes a count field indicating the total number of available records.

Common HTTP errors

• 400 Bad Request – malformed query parameters.
• 403 Forbidden – insufficient OAuth scopes for the requested endpoint.
• 500 Internal Server Error – temporary server issues; retry with exponential backoff.

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