Zoho Books Python API Docs | dltHub

Zoho Books API v3 is a REST API for managing accounting and financial operations within Zoho Books. The REST API base URL is https://www.zohoapis.com/books/v3 and All requests require an OAuth2 access token for authentication, passed 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 Zoho Books data in under 10 minutes.

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What data can I load from Zoho Books?

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

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How do I authenticate with the Zoho Books API?

The Zoho Books API uses OAuth2.0 for authentication. Access tokens must be included in the 'Authorization' header with the format 'Zoho-oauthtoken {access_token}'. Additionally, an 'organization_id' is required as a query parameter for every API request.

1. Get your credentials

To obtain API credentials, you will need to register your application with Zoho to get a client ID and client secret. Once you have these, you can generate an access token and a refresh token through the OAuth 2.0 flow. Access tokens expire after an hour, and a refresh token can be used to generate new access tokens by making a POST request to the Accounts URL with the refresh token, client ID, client secret, and grant type.

2. Add them to .dlt/secrets.toml

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[sources.zoho_books_source]
client_id = "your_client_id"
client_secret = "your_client_secret"
refresh_token = "your_refresh_token"
organization_id = "your_organization_id"

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 Books 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_books_pipeline.py

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

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Pipeline zoho_books_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset zoho_books_data
The duckdb destination used duckdb:/zoho_books.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_books_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 items from the Zoho Books 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_books_source(organization_id=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://www.zohoapis.com/books/v3",
            "auth": {
                "type": "oauth",
                "access_token": organization_id,
            },
        },
        "resources": [
            {"name": "invoices", "endpoint": {"path": "invoices", "data_selector": "invoices"}},
            {"name": "items", "endpoint": {"path": "items", "data_selector": "items"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="zoho_books_pipeline",
        destination="duckdb",
        dataset_name="zoho_books_data",
    )
    load_info = pipeline.run(zoho_books_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_books_pipeline").dataset()
sessions_df = data.invoices.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM zoho_books_data.invoices LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("zoho_books_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 Books 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 and Authorization Errors

• 401/403 Unauthorized/Forbidden: This error indicates that your access token is either invalid, expired, or you do not have the necessary permissions to access the requested resource. Ensure your access token is current and correctly included in the 'Authorization' header as 'Zoho-oauthtoken {access_token}'. If the token has expired (they expire after an hour), use your refresh token to generate a new one.

Rate Limit Exceeded

• 429 Too Many Requests: This error occurs when you have exceeded the API's rate limits. You should implement a retry mechanism with exponential backoff to handle these errors gracefully and avoid making too many requests in a short period.

Bad Request

• 400 Bad Request: This error typically means that your request was malformed or contained invalid parameters. Review your request payload and query parameters, especially the organization_id, to ensure they conform to the API documentation.

Server Errors

• 5xx Server Error: These errors indicate a problem on the Zoho Books API server side. While less common, if you encounter these, it's advisable to retry your request after a short delay. If the issue persists, check the Zoho Books API status page or contact their 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