Clearslide Python API Docs | dltHub

Clearslide is a REST API platform that provides programmatic access to ClearSlide features (presentations, links, insights, users, uploads) for creating trackable links, listing content, and retrieving engagement data. The REST API base URL is https://platform.clearslide.com/v2 and all requests require a Bearer token for authentication.

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 Clearslide data in under 10 minutes.

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What data can I load from Clearslide?

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

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How do I authenticate with the Clearslide API?

ClearSlide uses OAuth2-style bearer token authorization. Include an Authorization header: Authorization: Bearer <your_token>.

1. Get your credentials

1. Sign up for a ClearSlide account (https://www.clearslide.com/freetrial).
2. Request an API account or API access from ClearSlide support / your ClearSlide account admin.
3. Follow ClearSlide OAuth 2.0 / Getting Started docs to generate an Authorization Token.
4. Use the provided token (sample format: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx) in the Authorization header.

2. Add them to .dlt/secrets.toml

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[sources.clearslide_source]
api_key = "your_bearer_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 Clearslide 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 clearslide_pipeline.py

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

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Pipeline clearslide_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset clearslide_data
The duckdb destination used duckdb:/clearslide.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 clearslide_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 presentations and insights from the Clearslide 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 clearslide_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://platform.clearslide.com/v2",
            "auth": {
                "type": "bearer",
                "token": api_key,
            },
        },
        "resources": [
            {"name": "presentations", "endpoint": {"path": "presentations", "data_selector": "data"}},
            {"name": "insights", "endpoint": {"path": "insights", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="clearslide_pipeline",
        destination="duckdb",
        dataset_name="clearslide_data",
    )
    load_info = pipeline.run(clearslide_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("clearslide_pipeline").dataset()
sessions_df = data.presentations.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM clearslide_data.presentations LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("clearslide_pipeline").dataset()
data.presentations.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 Clearslide 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 Unauthorized, verify the Authorization header is present and formatted as: Authorization: Bearer . Ensure the token is active and was provisioned by ClearSlide support or your account admin.

Rate limits and 429 responses

If you encounter HTTP 429 Too Many Requests, implement exponential backoff and retry logic. Consult ClearSlide support for account-specific limits.

Pagination and partial results

Many endpoints return results under the top-level "data" key. Check the API response for pagination links/metadata in the response (follow standard REST pagination fields provided by the API) and use provided query parameters (filters, page/limit) where available.

COMMON API ERRORS (summary): 401 Unauthorized (invalid/missing token), 403 Forbidden (insufficient scope), 404 Not Found (invalid resource id), 429 Too Many Requests (rate limit), 400 Bad Request (validation errors - constraintViolation payloads described in docs).

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