Searchspring Python API Docs | dltHub

Searchspring is a site search and merchandising platform providing REST APIs to retrieve search results, personalization, recommendations, and indexing functionality. The REST API base URL is https://{siteId}.a.searchspring.io and Requests require site-specific API keys (account details) and rely on siteId-based endpoints; tracking cookies and account tokens used for some personalization endpoints..

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 Searchspring data in under 10 minutes.

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What data can I load from Searchspring?

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

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How do I authenticate with the Searchspring API?

Searchspring uses site-specific endpoints (siteId in hostname) and account credentials shown in the Searchspring Management Console (Account details). Some endpoints require a management API key (found in My Account) or the site-specific API key passed as query parameters or headers; tracking cookies (user tracking) are required for analytics/personalization features.

1. Get your credentials

1. Log in to Searchspring Management Console. 2) Open My Account / Account details. 3) Copy the API key or account credentials listed under Account details (Management Console). 4) Use the provided siteId (found in account) as the host prefix for API requests. 5) For personalization, ensure tracking cookies are enabled and include shopper/cart/lastViewed parameters; if using personalization POST preflight, include the same credentials.

2. Add them to .dlt/secrets.toml

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[sources.searchspring_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 Searchspring 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 searchspring_pipeline.py

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

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Pipeline searchspring_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset searchspring_data
The duckdb destination used duckdb:/searchspring.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 searchspring_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 search and autocomplete from the Searchspring 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 searchspring_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{siteId}.a.searchspring.io",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "search", "endpoint": {"path": "api/search/search.json", "data_selector": "results"}},
            {"name": "autocomplete", "endpoint": {"path": "api/suggest/suggest.json", "data_selector": "results"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="searchspring_pipeline",
        destination="duckdb",
        dataset_name="searchspring_data",
    )
    load_info = pipeline.run(searchspring_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("searchspring_pipeline").dataset()
sessions_df = data.search.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM searchspring_data.search LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("searchspring_pipeline").dataset()
data.search.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 Searchspring 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

Ensure the correct siteId is used in the hostname (https://{siteId}.a.searchspring.io) and that the API key from My Account / Account details is provided. Missing or invalid account credentials will return 401/403 responses from Searchspring endpoints.

Personalization preflight

If using personalization (shopper, cart, lastViewed) you must call the preflightCache endpoint before calling autocomplete or search. GET supports up to 2048 chars; use POST for larger payloads.

Rate limits and tracking cookies

Searchspring requires tracking cookies for certain endpoints; if cookies are blocked personalization and reporting may fail. Rate limits are enforced per account (refer to your Searchspring account manager); implement retries with exponential backoff for 429 responses.

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