CommCareHQ Python API Docs | dltHub

CommCareHQ is a platform for building and operating mobile health and case management applications. The REST API base URL is https://www.commcarehq.org/a/<domain>/api/ and All API requests require HTTP Basic authentication using a CommCare username and 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 CommCareHQ data in under 10 minutes.

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What data can I load from CommCareHQ?

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

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How do I authenticate with the CommCareHQ API?

CommCareHQ APIs use HTTP Basic authentication: include the username and password in the Authorization header (or use the -u flag in curl).

1. Get your credentials

1. Log in to CommCare HQ as an admin or a user with API permissions.
2. Navigate to the target project space (domain).
3. Create a new web or mobile user, or select an existing one.
4. Ensure the user has the "Can access API" permission for the domain.
5. Record the username (email) and password; these will be used as HTTP Basic credentials for API calls.

2. Add them to .dlt/secrets.toml

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[sources.commcarehq_source]
username = "your_commcare_username"
password = "your_commcare_password"

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 CommCareHQ 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 commcarehq_pipeline.py

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

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Pipeline commcarehq_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset commcarehq_data
The duckdb destination used duckdb:/commcarehq.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 commcarehq_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 case_v2 and form_submission_receiver from the CommCareHQ 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 commcarehq_source(username, password=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://www.commcarehq.org/a/<domain>/api/",
            "auth": {
                "type": "http_basic",
                "password": username, password,
            },
        },
        "resources": [
            {"name": "case_v2", "endpoint": {"path": "a/<domain>/api/case/v2/", "data_selector": "cases"}},
            {"name": "form_submission_receiver", "endpoint": {"path": "a/<domain>/receiver/api/"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="commcarehq_pipeline",
        destination="duckdb",
        dataset_name="commcarehq_data",
    )
    load_info = pipeline.run(commcarehq_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("commcarehq_pipeline").dataset()
sessions_df = data.case_v2.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM commcarehq_data.case_v2 LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("commcarehq_pipeline").dataset()
data.case_v2.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 CommCareHQ 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 HTTP 401 responses, verify that the username and password are correct and that the user has API access for the target domain.

Pagination

Case Data API v2 uses cursor‑style pagination; each response may contain a next link. Continue requesting the URL in next until it is absent.

Bulk request limits

GET bulk fetch via comma‑separated IDs is limited by URL length (≈100 IDs). Use the POST bulk_fetch endpoint for larger batches.

Form submission errors

The submission endpoint follows OpenRosa: 201 submit_success on success, 400 for malformed XML, 401 for auth failures, and 500 for server processing 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