Sony Camera Remote API Python API Docs | dltHub

Sony Camera Remote API allows remote control of Sony cameras via dedicated SDK. The latest version supports multiple new models, including the α7R II. For detailed API documentation, visit the official Sony developer site. The REST API base URL is http://<camera_ip>/sony and No API key; authentication is performed via local Wi‑Fi pairing with the camera..

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 Sony Camera Remote API data in under 10 minutes.

---

What data can I load from Sony Camera Remote API?

Here are some of the endpoints you can load from Sony Camera Remote API:

---

How do I authenticate with the Sony Camera Remote API API?

The camera exposes the API over HTTP on its local IP; authentication is handled by pairing the client device with the camera’s Wi‑Fi and granting permission on the camera. No additional headers are needed.

1. Get your credentials

1. Power on the Sony camera and enable the Smart Remote Control / Remote API app (install the PlayMemories Remote app if necessary). 2) Connect your computer or mobile device to the camera's Wi‑Fi network (the camera acts as an access point). 3) On the camera, accept the permission prompt to allow remote API access. After pairing, you can send JSON‑RPC requests to the camera’s API endpoints; no dashboard credentials are required.

2. Add them to .dlt/secrets.toml

Copy
[sources.sony_camera_remote_api_source]
# No API key required for Camera Remote API; local Wi-Fi pairing

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.

---

How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

Copy
uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

Copy
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:

Copy
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 Sony Camera Remote API 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:

Copy
python sony_camera_remote_api_pipeline.py

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

Copy
Pipeline sony_camera_remote_api_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset sony_camera_remote_api_data
The duckdb destination used duckdb:/sony_camera_remote_api.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

Copy
dlt pipeline sony_camera_remote_api_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.

---

Python pipeline example

This example loads get_available_api_list and get_method_types from the Sony Camera Remote API API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

Copy
import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def sony_camera_remote_api_source(None=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "http://<camera_ip>/sony",
            "auth": {
                "type": "none",
                "": None,
            },
        },
        "resources": [
            {"name": "get_available_api_list", "endpoint": {"path": "sony/camera", "data_selector": "result"}},
            {"name": "get_method_types", "endpoint": {"path": "sony/camera", "data_selector": "result"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="sony_camera_remote_api_pipeline",
        destination="duckdb",
        dataset_name="sony_camera_remote_api_data",
    )
    load_info = pipeline.run(sony_camera_remote_api_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.

---

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):

Copy
import dlt

data = dlt.pipeline("sony_camera_remote_api_pipeline").dataset()
sessions_df = data.get_available_api_list.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM sony_camera_remote_api_data.get_available_api_list LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("sony_camera_remote_api_pipeline").dataset()
data.get_available_api_list.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

---

What destinations can I load Sony Camera Remote API 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.

---

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.

Copy
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