Assembled Python API Docs | dltHub

Assembled is a workforce management platform for support teams that provides forecasting, scheduling, real‑time agent states and reporting via a REST API. The REST API base URL is https://api.assembledhq.com/v0 and All requests use HTTP Basic Auth with an API key as the username and no password.

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 Assembled data in under 10 minutes.

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What data can I load from Assembled?

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

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How do I authenticate with the Assembled API?

The API uses API keys (prefixed sk_live_*) authenticated via HTTP Basic Auth: provide the API key as the basic auth username and leave the password blank. Requests must be made over HTTPS and may include an API-Version header for versioning.

1. Get your credentials

1. Log in to your Assembled account at https://app.assembledhq.com.
2. Go to Settings → API.
3. Create or copy an API key (keys are prefixed with sk_live_).
4. Use that key as the HTTP Basic Auth username (no password) for API calls.

2. Add them to .dlt/secrets.toml

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[sources.assembled_source]
api_key = "sk_live_your_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 Assembled 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 assembled_pipeline.py

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

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Pipeline assembled_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset assembled_data
The duckdb destination used duckdb:/assembled.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 assembled_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 people and agent_states from the Assembled 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 assembled_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.assembledhq.com/v0",
            "auth": {
                "type": "http_basic",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "people", "endpoint": {"path": "people", "data_selector": "people"}},
            {"name": "agent_states", "endpoint": {"path": "agents/state", "data_selector": "agent_states"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="assembled_pipeline",
        destination="duckdb",
        dataset_name="assembled_data",
    )
    load_info = pipeline.run(assembled_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("assembled_pipeline").dataset()
sessions_df = data.people.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM assembled_data.people LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("assembled_pipeline").dataset()
data.people.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 Assembled 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 you are using your API key as the HTTP Basic Auth username, leave the password blank, and ensure the request is made over HTTPS. Check that the key has the sk_live_ prefix and has not been revoked in Settings → API.

Rate limiting

A 429 Too Many Requests response indicates the rate limit has been exceeded. The default limit is 300 requests per minute (5 req/s) with bursts of up to 20 requests. Back off and retry after a pause; contact support@assembled.com for higher limits.

Pagination and selectors

List endpoints return objects where the records are nested under a named key (e.g., people, teams, roles, agent_states, requirements). Use the exact JSON key as the dlt data selector. Endpoints that return a single object (e.g., /v0/people/:id) have no selector. Some endpoints return top‑level arrays.

Common HTTP errors

• 400 Bad Request – invalid IDs or parameters.
• 401 Unauthorized – authentication issues as described above.
• 429 Too Many Requests – rate limiting.
• 500‑599 – server errors; retry with exponential backoff.

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