Amazon Sidewalk Mobile SDK Python API Docs | dltHub

Amazon Sidewalk Mobile SDK is a mobile SDK that enables mobile apps to scan for, securely connect to, register/deregister, and communicate with Amazon Sidewalk endpoint devices (BLE) and to interact with the Sidewalk cloud using Login with Amazon (LWA) tokens. The REST API base URL is N/A and SDK operations require a Login with Amazon (LWA) auth token; the mobile app must obtain and supply this token to the SDK..

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 Amazon Sidewalk Mobile SDK data in under 10 minutes.

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What data can I load from Amazon Sidewalk Mobile SDK?

Here are some of the endpoints you can load from Amazon Sidewalk Mobile SDK:

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How do I authenticate with the Amazon Sidewalk Mobile SDK API?

The Mobile SDK integrates with Login with Amazon (LWA). The app must obtain a user Auth Token via LWA and provide it to the SDK (SidewalkAuthProviding.getToken()/SDK configuration). The docs state the iOS SDK also requires OpenSSL; the account must be linked to a Ring account for registered devices to be returned.

1. Get your credentials

1. Register app with Login with Amazon (LWA) via developer.amazon.com. 2) Integrate LWA SDK in your mobile app. 3) Prompt user to sign in with Amazon and request scope(s). 4) Obtain the user Auth Token (LWA access token) from LWA SDK. 5) Provide/refresh this token to the Sidewalk Mobile SDK via the SidewalkAuthProviding/getToken integration.

2. Add them to .dlt/secrets.toml

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[sources.amazon_sidewalk_mobile_sdk_source]
auth_token = "your_lwa_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 Amazon Sidewalk Mobile SDK 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 amazon_sidewalk_mobile_sdk_pipeline.py

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

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Pipeline amazon_sidewalk_mobile_sdk_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset amazon_sidewalk_mobile_sdk_data
The duckdb destination used duckdb:/amazon_sidewalk_mobile_sdk.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 amazon_sidewalk_mobile_sdk_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 scan and register_device from the Amazon Sidewalk Mobile SDK 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 amazon_sidewalk_mobile_sdk_source(auth_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "N/A",
            "auth": {
                "type": "bearer",
                "token": auth_token,
            },
        },
        "resources": [
            {"name": "scan", "endpoint": {"path": "scan()"}},
            {"name": "register_device", "endpoint": {"path": "registerDevice()"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="amazon_sidewalk_mobile_sdk_pipeline",
        destination="duckdb",
        dataset_name="amazon_sidewalk_mobile_sdk_data",
    )
    load_info = pipeline.run(amazon_sidewalk_mobile_sdk_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("amazon_sidewalk_mobile_sdk_pipeline").dataset()
sessions_df = data.scan.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM amazon_sidewalk_mobile_sdk_data.scan LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("amazon_sidewalk_mobile_sdk_pipeline").dataset()
data.scan.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 Amazon Sidewalk Mobile SDK 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

LWA Authentication Failures and Ring Account Linking

Ensure your mobile app correctly integrates with the Login with Amazon (LWA) SDK to obtain and refresh user Auth Tokens. Without a valid LWA token, SDK operations will fail. Additionally, for registered devices to be returned by the Amazon Sidewalk cloud, the user's Amazon account must be linked to a Ring account. If not linked, the cloud will not provide device information.

BLE Permissions and Connection Failures

Since the Amazon Sidewalk Mobile SDK communicates with edge devices over Bluetooth Low Energy (BLE), ensure your mobile application has the necessary BLE permissions granted by the user. Connection failures can occur due to insufficient permissions, devices being out of range, or interference.

Deprecated uploadDeviceMetrics and Behavioral Notes

The uploadDeviceMetrics API has been deprecated. Developers should avoid using it. Be aware that the iOS SDK requires OpenSSL for certain functionalities.

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