Load Zoho Inventory data to DuckDB

Zoho Inventory is an online inventory management REST API that lets you programmatically manage organizations, items, contacts, sales orders, packages and other inventory resources. Everything needed to build a working Zoho Inventory → 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 Zoho Inventory 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 Zoho Inventory 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 Zoho Inventory 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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Zoho Inventory API at a glance

These values come from the Zoho Inventory API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Zoho Inventory API?

Authentication is performed using OAuth 2.0. Requests require an 'Authorization' header with the format 'Zoho-oauthtoken {access_token}'.

1. Get your credentials

1. Go to the Zoho API Console.\n2. Select an application type (e.g., 'Server-based Application' or 'Self Client' for simple testing).\n3. Register your application to obtain a Client ID and Client Secret.\n4. Configure a Redirect URI (required for the OAuth flow).\n5. Use these credentials to initiate the OAuth 2.0 authorization code flow to obtain access_token and refresh_token for authenticating API requests. Note that Zoho has deprecated static Authtokens in favor of OAuth 2.0.

2. Add them to .dlt/secrets.toml

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[sources.zoho_inventory_source]
access_token = "REPLACE_ME"

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 Zoho Inventory data can I load into DuckDB?

These are the Zoho Inventory endpoints dlt can load into DuckDB:

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How do I load only new Zoho Inventory records?

Zoho Inventory exposes page on items, 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": "items", "endpoint": {
    "path": "items",
    "data_selector": "items",
    "incremental": {"cursor_path": "page", "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 Zoho Inventory pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /organizations and /items from the Zoho Inventory API into DuckDB:

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

@dlt.source
def zoho_inventory_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://www.zohoapis.com/inventory/v1",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "items", "endpoint": {"path": "items", "data_selector": "items"}},
            {"name": "purchase_orders", "endpoint": {"path": "purchaseorders", "data_selector": "purchaseorders"}}
        ],
    }
    yield from rest_api_resources(config)


def load_zoho_inventory_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="zoho_inventory_pipeline",
        destination="duckdb",
        dataset_name="zoho_inventory_data",
    )
    load_info = pipeline.run(zoho_inventory_source())
    print(load_info)


if __name__ == "__main__":
    load_zoho_inventory_to_duckdb()

Run it with python zoho_inventory_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 Zoho Inventory 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("zoho_inventory_pipeline").dataset()
df = data.items.df()
print(df.head())

SQL:

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SELECT * FROM zoho_inventory_data.items LIMIT 10;

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

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How do I deploy the Zoho Inventory 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 Zoho Inventory 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 Zoho Inventory 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