OpusWatch Python API Docs | dltHub

OpusWatch is a REST/event-driven API platform used by Opus family products to programmatically interact with their job/task/process management systems and to submit or receive events and operational data. The REST API base URL is https://externalclientapi.opus4business.com and Authentication is performed with an API token supplied as a Bearer token in the Authorization header..

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 OpusWatch data in under 10 minutes.

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What data can I load from OpusWatch?

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

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How do I authenticate with the OpusWatch API?

Requests must include an Authorization header with a Bearer token (e.g., Authorization: Bearer <token>). Some products also accept an API key/secret pair as defined in their Swagger UI.

1. Get your credentials

1. Contact your Opus product administrator to enable API access for your account.
2. Log into the product’s developer portal (e.g., Opus4Business customer portal or Opus2 developer site).
3. Navigate to the API/Integration section and create a new API client or token.
4. Record the generated token (or client ID/secret).
5. If an ID/secret pair is issued, exchange it for a Bearer token at the token endpoint.
6. Verify the token by calling a known endpoint such as /api/events or a system‑info GET request.

2. Add them to .dlt/secrets.toml

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[sources.opus_watch_source]
api_token = "your_opus_api_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 OpusWatch 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 opus_watch_pipeline.py

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

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Pipeline opus_watch_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset opus_watch_data
The duckdb destination used duckdb:/opus_watch.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 opus_watch_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 api/events and swagger from the OpusWatch 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 opus_watch_source(api_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://externalclientapi.opus4business.com",
            "auth": {
                "type": "bearer",
                "token": api_token,
            },
        },
        "resources": [
            {"name": "opus_events", "endpoint": {"path": "api/events"}},
            {"name": "opus4business_swagger", "endpoint": {"path": "(use the Swagger UI at externalclientapi.opus4business.com to discover)"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="opus_watch_pipeline",
        destination="duckdb",
        dataset_name="opus_watch_data",
    )
    load_info = pipeline.run(opus_watch_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("opus_watch_pipeline").dataset()
sessions_df = data.opus_events.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM opus_watch_data.opus_events LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("opus_watch_pipeline").dataset()
data.opus_events.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 OpusWatch 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 that the Bearer token is correct, not expired, and included exactly as Authorization: Bearer <token>.

Rate limiting and throttling

The public docs do not publish a fixed rate limit. If a 429 Too Many Requests response is returned, implement exponential back‑off and contact your account manager for higher quotas.

Pagination and selectors

The exact JSON key that contains record arrays is only documented inside the product‑specific Swagger UI. Access the Swagger UI (e.g., https://externalclientapi.opus4business.com/swagger/ui/index#/) to view response examples and determine the correct selector such as results, data, or a resource‑specific key. Guessing selectors will result in parsing errors.

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