Zoho-projects Python API Docs | dltHub

Zoho Projects is a REST API for managing projects, tasks, time logs, users, forums and related project management resources in Zoho Projects. The REST API base URL is https://projectsapi.zoho.com/api/v3 and all requests require an OAuth2 access token sent in the Authorization header as 'Zoho-oauthtoken {access_token}'..

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-projects data in under 10 minutes.

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What data can I load from Zoho-projects?

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

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How do I authenticate with the Zoho-projects API?

Zoho Projects uses OAuth2.0 (authorization_code / self‑client flows). After obtaining an access token (valid ~1 hour) and a refresh token, include header: Authorization: Zoho-oauthtoken {access_token}. Token refresh is done via https://accounts.zoho.com/oauth/v2/token.

1. Get your credentials

1. Go to Zoho Developer Console (https://api-console.zoho.com/) and create a client (choose Web, Self Client, Mobile, etc.).
2. Note Client ID and Client Secret returned.
3. For web apps use the authorization code (redirect) flow to get a grant code; for back‑end jobs use Self‑Client to generate a grant token.
4. Exchange the grant token/code for access and refresh tokens by POSTing to https://accounts.zoho.com/oauth/v2/token with grant_type=authorization_code (or refresh_token when refreshing).
5. Include the access token in every API request as: Authorization: Zoho-oauthtoken {access_token}.

2. Add them to .dlt/secrets.toml

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[sources.zoho_projects_source]
client_id = "your_client_id"
client_secret = "your_client_secret"
refresh_token = "your_refresh_token"

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-projects 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_projects_pipeline.py

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

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Pipeline zoho_projects_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset zoho_projects_data
The duckdb destination used duckdb:/zoho_projects.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_projects_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 projects and tasks from the Zoho-projects 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_projects_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://projectsapi.zoho.com/api/v3",
            "auth": {
                "type": "bearer",
                "access_token": access_token,
            },
        },
        "resources": [
            {"name": "projects", "endpoint": {"path": "portal/[PORTALID]/projects", "data_selector": "projects"}},
            {"name": "tasks", "endpoint": {"path": "portal/[PORTALID]/projects/[PROJECTID]/tasks", "data_selector": "tasks"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="zoho_projects_pipeline",
        destination="duckdb",
        dataset_name="zoho_projects_data",
    )
    load_info = pipeline.run(zoho_projects_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_projects_pipeline").dataset()
sessions_df = data.projects.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM zoho_projects_data.projects LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("zoho_projects_pipeline").dataset()
data.projects.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-projects 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 INVALID_OAUTHTOKEN or HTTP 401/400 errors, refresh your access token using the refresh_token endpoint or re‑run the OAuth grant flow. Ensure you use the correct accounts domain (accounts.zoho.com or region‑specific) and include header exactly: Authorization: Zoho-oauthtoken {access_token}.

Rate limits

Zoho Projects enforces an API limit of 100 requests per 2 minutes. Exceeding the limit will block further requests for 30 minutes. Implement exponential backoff and request batching.

Pagination

Most listing endpoints support page and per_page query params and return page_info (per_page, has_next_page, count, page). Use these to iterate through results. The array of records is found under the resource‑specific key (e.g., projects, tasks, teams).

Common error payloads

Errors include an HTTP status and an error object with a machine‑parsable errorCode such as INVALID_OAUTHTOKEN, URL_RULE_NOT_CONFIGURED, or INTERNAL_SERVER_ERROR. Example:

{ "error": { "status_code": "403", "error_type": "OPERATIONAL_VALIDATION_ERROR", "details": [ { "message": "Access to this API is restricted for client users" } ] } }

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