Coalesce Python API Docs | dltHub

Coalesce is a REST API for managing Coalesce metadata, environments, nodes, runs and jobs and for programmatically submitting and inspecting runs and their results. The REST API base URL is https://app.coalescesoftware.io/api/v1 and all requests require a Bearer access 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 Coalesce data in under 10 minutes.

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What data can I load from Coalesce?

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

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How do I authenticate with the Coalesce API?

Coalesce uses Bearer token authentication. Include a header Authorization: Bearer and accept: application/json.

1. Get your credentials

1. Log in to the Coalesce web app for your deployment. 2) Open the Deploy tab in the UI. 3) Click "Generate Access Token" (or view existing tokens). 4) Copy the Access Token and use it as the Bearer token in API requests. 5) (Optional) If using an SSO subdomain, prepend your company subdomain to the base URL.

2. Add them to .dlt/secrets.toml

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[sources.coalesce_source]
access_token = "your_coalesce_access_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 Coalesce 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 coalesce_pipeline.py

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

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Pipeline coalesce_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset coalesce_data
The duckdb destination used duckdb:/coalesce.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 coalesce_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 environments and run_results from the Coalesce 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 coalesce_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://app.coalescesoftware.io/api/v1",
            "auth": {
                "type": "bearer",
                "token": access_token,
            },
        },
        "resources": [
            {"name": "environments", "endpoint": {"path": "api/v1/environments", "data_selector": "data"}},
            {"name": "run_results", "endpoint": {"path": "api/v1/runs/{runID}/results", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="coalesce_pipeline",
        destination="duckdb",
        dataset_name="coalesce_data",
    )
    load_info = pipeline.run(coalesce_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("coalesce_pipeline").dataset()
sessions_df = data.environments.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM coalesce_data.environments LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("coalesce_pipeline").dataset()
data.environments.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 Coalesce 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 see 401 Unauthorized, verify the Authorization header is present and the token is correct: Authorization: Bearer <Access Token>. Ensure the token was generated from the Deploy tab and the token's owner account is active.

Token lifecycle and SSO caveats

Access tokens do not expire automatically; they are invalidated when the user is deleted/disabled or changes password/email. SSO user changes do not automatically remove tokens—remove tokens or disable the user in Coalesce to revoke access.

Region / base URL mismatches

Use the deployment‑specific base URL for your account (see Coalesce base URLs list). If you use the wrong region/base URL you will see 404 or resource‑not‑found errors. For SSO customers prefix with your subdomain (e.g. https://mycompany.app.eu.coalescesoftware.io).

Common HTTP error codes

• 400: Bad request (invalid parameters).
• 401: Unauthorized (invalid/missing token).
• 403: Forbidden (insufficient permissions).
• 404: Not found (invalid resource or wrong base URL).
• 5xx: Server or upstream errors — retry or contact Coalesce support.

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