Osano Python API Docs | dltHub

Osano is a data privacy and consent management platform that provides REST APIs for managing cookie consent configurations, consent/subject profiles (Unified Consent), data discovery (data stores and fields), subject rights requests (DSARs), connectors and related resources. The REST API base URL is https://api.osano.com (Customer REST API v1) Unified Consent base URL: https://uc.api.osano.com (UC Core API v2) and all requests require an Osano API key in the x-osano-api-key header; UC endpoints may require x-uc-api-key (Unified Consent token) instead..

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 Osano data in under 10 minutes.

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What data can I load from Osano?

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

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How do I authenticate with the Osano API?

Osano uses API keys. For the Customer REST API and many v1 endpoints include the API key in the x-osano-api-key header. The Unified Consent Core API accepts x-osano-api-key for Osano-level operations and x-uc-api-key for scoped Unified Consent operations; Unified Consent API keys can be created via the /v2/token/create endpoint.

1. Get your credentials

1. Sign in to your Osano account at https://my.osano.com. 2) Navigate to Settings -> API Keys (or https://my.osano.com/api-keys). 3) Create a new API key (admin privileges required). Copy and store it securely — it cannot be viewed again. 4) For Unified Consent scoped keys, call POST https://uc.api.osano.com/v2/token/create with customerId and configId to generate an x-uc-api-key.

2. Add them to .dlt/secrets.toml

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[sources.osano_source]
api_key = "your_osano_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 Osano 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 osano_pipeline.py

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

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Pipeline osano_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset osano_data
The duckdb destination used duckdb:/osano.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 osano_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 cookie_consent_configs and data_stores from the Osano 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 osano_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.osano.com (Customer REST API v1) Unified Consent base URL: https://uc.api.osano.com (UC Core API v2)",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "cookie_consent_configs", "endpoint": {"path": "v1/cookie-consent/configs", "data_selector": "items"}},
            {"name": "data_stores", "endpoint": {"path": "v1/data-discovery/data-stores", "data_selector": "items"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="osano_pipeline",
        destination="duckdb",
        dataset_name="osano_data",
    )
    load_info = pipeline.run(osano_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("osano_pipeline").dataset()
sessions_df = data.cookie_consent_configs.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM osano_data.cookie_consent_configs LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("osano_pipeline").dataset()
data.cookie_consent_configs.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 Osano 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 the x-osano-api-key header is missing, invalid, or expired the API returns 401 Unauthorized. Ensure you copied the API key at creation time and pass it exactly as: x-osano-api-key: <API_KEY>. For Unified Consent endpoints that require a scoped token, create an x-uc-api-key via POST /v2/token/create and include x-uc-api-key header.

Rate limits and pagination

List endpoints are paginated. Responses include an items array and may include a next field containing a pagination token; request subsequent pages with ?next=. Most list endpoints support limit (1..500) and default limit=100. Respect 429 Too Many Requests responses; implement exponential backoff when receiving 429.

Common error responses

• 400 Bad Request: malformed parameters or validation errors.
• 401 Unauthorized: missing/invalid API key.
• 403 Forbidden: insufficient privileges for the API key (admin-only operations require admin-scoped keys).
• 404 Not Found: resource not found (invalid IDs).
• 409 Conflict: e.g., trying to send duplicate summary notifications for DSARs.
• 429 Too Many Requests: rate limit exceeded—retry with backoff.
• 500+ Server Errors: retry with backoff and report to Osano support if persistent.

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