Load WhatsApp 360Dialog data to DuckDB

360dialog provides a WhatsApp Business API platform for managing WhatsApp messages programmatically. Everything needed to build a working WhatsApp 360Dialog → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your WhatsApp 360Dialog to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from WhatsApp 360Dialog to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the WhatsApp 360Dialog API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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WhatsApp 360Dialog API at a glance

These values come from the WhatsApp 360Dialog API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the WhatsApp 360Dialog API?

Authentication is performed by passing an API key in the 'D360-API-KEY' header with every request.

1. Get your credentials

To obtain an API key for your 360dialog WhatsApp Business account: 1. Log in to the 360dialog Client Hub (hub.360dialog.com). 2. Navigate to the 'Channels' section and select the specific WhatsApp channel. 3. Locate the 'API Settings' section. 4. Click the three-dot menu and select 'Generate new API Key'. 5. Type 'GENERATE' to confirm, and click the 'Generate new API key' button. Copy the key immediately, as it is displayed only once. Note: If your account is managed by an integration partner, this option may be hidden; in that case, contact your partner to request access.

2. Add them to .dlt/secrets.toml

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[sources.whatsapp_360dialog_source]
d360_api_key = "your_api_key_here"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What WhatsApp 360Dialog data can I load into DuckDB?

These are the WhatsApp 360Dialog endpoints dlt can load into DuckDB:

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How do I load only new WhatsApp 360Dialog records?

WhatsApp 360Dialog exposes after on groups, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "active_groups", "endpoint": {
    "path": "groups",
    "data_selector": "data.groups",
    "incremental": {"cursor_path": "after", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated WhatsApp 360Dialog pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /messages and /configs/webhook from the WhatsApp 360Dialog API into DuckDB:

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

@dlt.source
def whatsapp_360dialog_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://waba-v2.360dialog.io",
            "auth": {"type": "api_key", "api_key": api_key, "name": "D360-API-KEY", "location": "header"},
        },
        "resources": [
            {"name": "active_groups", "endpoint": {"path": "groups", "data_selector": "data.groups"}},
            {"name": "whatsapp_business_profile", "endpoint": {"path": "whatsapp_business_profile", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def load_whatsapp_360dialog_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="whatsapp_360dialog_pipeline",
        destination="duckdb",
        dataset_name="whatsapp_360dialog_data",
    )
    load_info = pipeline.run(whatsapp_360dialog_source())
    print(load_info)


if __name__ == "__main__":
    load_whatsapp_360dialog_to_duckdb()

Run it with python whatsapp_360dialog_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query WhatsApp 360Dialog data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("whatsapp_360dialog_pipeline").dataset()
df = data.active_groups.df()
print(df.head())

SQL:

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SELECT * FROM whatsapp_360dialog_data.active_groups LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the WhatsApp 360Dialog to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw WhatsApp 360Dialog loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load WhatsApp 360Dialog data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack