Zoho Invoice Python API Docs | dltHub

Zoho Invoice is a RESTful invoicing and billing API for creating, listing, and managing invoices, contacts, items, estimates and other accounting objects. The REST API base URL is https://www.zohoapis.com/invoice/v3 and All requests require OAuth2 access token sent as a Zoho-oauthtoken and the X-com-zoho-invoice-organizationid 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 Zoho Invoice data in under 10 minutes.

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What data can I load from Zoho Invoice?

Here are some of the endpoints you can load from Zoho Invoice:

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How do I authenticate with the Zoho Invoice API?

Use OAuth 2.0 to obtain an access_token (and refresh_token). Include headers: Authorization: Zoho-oauthtoken {access_token} and X-com-zoho-invoice-organizationid: {organization_id} on every request. JSON payloads are sent as application/json/form-data as documented.

1. Get your credentials

1. Register a client in Zoho API Console (provide redirect URI) to obtain client_id and client_secret. 2) Direct user to Zoho authorize URL to obtain authorization code. 3) Exchange authorization code for access_token and refresh_token via POST to https://accounts.zoho.com/oauth/v2/token with grant_type=authorization_code, client_id, client_secret, redirect_uri and code. 4) Use access_token in Authorization header; when it expires use refresh_token with grant_type=refresh_token to obtain a new access_token.

2. Add them to .dlt/secrets.toml

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[sources.zoho_invoice_source]
access_token = "your_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 Zoho Invoice 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 zoho_invoice_pipeline.py

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

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Pipeline zoho_invoice_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset zoho_invoice_data
The duckdb destination used duckdb:/zoho_invoice.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 zoho_invoice_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 invoices and contacts from the Zoho Invoice 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 zoho_invoice_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://www.zohoapis.com/invoice/v3",
            "auth": {
                "type": "bearer",
                "token": access_token,
            },
        },
        "resources": [
            {"name": "invoices", "endpoint": {"path": "invoices", "data_selector": "invoices"}},
            {"name": "contacts", "endpoint": {"path": "contacts", "data_selector": "contacts"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="zoho_invoice_pipeline",
        destination="duckdb",
        dataset_name="zoho_invoice_data",
    )
    load_info = pipeline.run(zoho_invoice_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("zoho_invoice_pipeline").dataset()
sessions_df = data.invoices.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM zoho_invoice_data.invoices LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("zoho_invoice_pipeline").dataset()
data.invoices.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 Zoho Invoice 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 Authorization header is missing/invalid or the access_token expired the API returns 401 or an error JSON. Ensure header: Authorization: Zoho-oauthtoken {access_token} and that access_token is refreshed using the refresh_token when expired.

Missing organization header

Most endpoints require X-com-zoho-invoice-organizationid. Calls without it will fail—include the organization ID header value for the target org.

Rate limits and 429 responses

Per-organization limits: 100 requests/minute and plan-based daily limits (e.g., Free plan 1000/day). Exceeding limits returns HTTP 429 and error codes such as {"code":45,...} or {"code":44,...}. Implement exponential backoff and respect concurrent call limits.

Pagination

List endpoints are paginated. Use page and per_page (or page param as documented) to iterate; responses include the array under the resource key (e.g., "invoices") and metadata in the response for paging. Fetch subsequent pages until array is empty.

Common error shapes

Errors are returned as JSON with numeric code and message, e.g. {"code":44,"message":"..."} or {"code":45,"message":"..."}; HTTP status codes reflect the error (401, 403, 404, 429, 500).

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