GreytHR Python API Docs | dltHub

GreytHR is a cloud HRMS platform offering REST APIs to access HR data (employees, attendance, leave, payroll, documents). The REST API base URL is https://api.greythr.com and all requests require an ACCESS-TOKEN header (bearer-style access token) and x-greythr-domain 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 GreytHR data in under 10 minutes.

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What data can I load from GreytHR?

Here are some of the endpoints you can load from GreytHR:

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How do I authenticate with the GreytHR API?

greytHR uses OAuth2/client-credentials style authentication to obtain an access token (or admin-generated access token). API requests must send the access token in the ACCESS-TOKEN header and include the x-greythr-domain header set to the company domain. Token acquisition may require client id/secret or greytHR admin-generated API credentials; some endpoints/documentation also reference Basic auth for token requests.

1. Get your credentials

1. Log in to greytHR admin portal (https://www.greythr.com/login). 2) As admin, create/register an API user or generate API credentials in the admin/API credentials section (see greythr support article "how to generate API credentials for the greythr admins"). 3) Use client id/secret or admin username/password to request an access token (OAuth2/client-credentials or token endpoint as documented). 4) Copy the returned access token (ACCESS-TOKEN) and place it into your dlt secrets along with your company's greythr domain (x-greythr-domain).

2. Add them to .dlt/secrets.toml

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[sources.greythr_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 GreytHR 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 greythr_pipeline.py

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

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Pipeline greythr_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset greythr_data
The duckdb destination used duckdb:/greythr.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 greythr_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 employee_list and employee_documents from the GreytHR 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 greythr_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.greythr.com",
            "auth": {
                "type": "bearer",
                "access_token": access_token,
            },
        },
        "resources": [
            {"name": "employee_list", "endpoint": {"path": "employee/v2/employees", "data_selector": "content"}},
            {"name": "employee_documents", "endpoint": {"path": "employee/v2/emp-docs/{employeeId}/{categoryId}"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="greythr_pipeline",
        destination="duckdb",
        dataset_name="greythr_data",
    )
    load_info = pipeline.run(greythr_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("greythr_pipeline").dataset()
sessions_df = data.employee_list.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM greythr_data.employee_list LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("greythr_pipeline").dataset()
data.employee_list.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 GreytHR 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 401/403 responses, verify that ACCESS-TOKEN is current and correct and that x-greythr-domain matches your company domain. Tokens may expire — re-request a token using client credentials or regenerate admin API credentials.

Pagination

Many greytHR list endpoints are paginated and require a page query parameter (page is mandatory for some endpoints). Responses use a paging wrapper (pages or page metadata) and the list of records is returned in the 'content' array for paginated endpoints.

Rate limits and errors

The public docs do not publish a fixed rate limit; if you receive 429 or throttling errors, back off and retry with exponential backoff. Typical API error responses include structured error objects with type/code (e.g., NOT-FOUND, ORGANIZATION-EXCEPTION) and standard HTTP status codes (400, 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