Name HR Management Python API Docs | dltHub

Name HR Management API is a set of REST endpoints for HR systems (employee profiles, assignments, documents, lists‑of‑values and related HR resources) provided by multiple vendors. The REST API base URL is https://instance.servicenow.com/api/sn_hr_core/V1, https://{host}/hcmRestApi/resources/11.13.18.05, https://www.myhr-api.lu and ServiceNow and myHR use HTTP Basic authentication; Oracle HCM uses instance authentication (OAuth or session‑based)..

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 Name HR Management data in under 10 minutes.

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What data can I load from Name HR Management?

Here are some of the endpoints you can load from Name HR Management:

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How do I authenticate with the Name HR Management API?

ServiceNow and myHR require an Authorization header with Basic base64(username:password) and Accept: application/json. Oracle HCM requires a valid Oracle Cloud session token or OAuth Bearer token and standard Accept headers.

1. Get your credentials

1. ServiceNow: Sign in to your ServiceNow instance, go to System Web Services → REST API or ask an admin to create an integration user; note the username and password for Basic Auth.
2. myHR: Create a company account, log in, navigate to Company > Software Settings > Security > API Access and generate an API username and password.
3. Oracle HCM: Access your Oracle Cloud tenant, open Oracle Identity Cloud Service or Fusion Applications, create an Application User or OAuth client, and obtain the user/password or client‑id/secret as required.

2. Add them to .dlt/secrets.toml

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[sources.name_hr_management_source]
service_now_user = "your_username"
service_now_password = "your_password"
myhr_user = "your_api_username"
myhr_password = "your_api_password"
oracle_hcm_user = "your_oracle_user"
oracle_hcm_password = "your_oracle_password_or_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 Name HR Management 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 name_hr_management_pipeline.py

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

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Pipeline name_hr_management_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset name_hr_management_data
The duckdb destination used duckdb:/name_hr_management.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 name_hr_management_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 employees and check_in_documents from the Name HR Management 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 name_hr_management_source(username=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://instance.servicenow.com/api/sn_hr_core/V1, https://{host}/hcmRestApi/resources/11.13.18.05, https://www.myhr-api.lu",
            "auth": {
                "type": "http_basic",
                "password": username,
            },
        },
        "resources": [
            {"name": "employees", "endpoint": {"path": "api/sn_hr_core/V1/hr_rest_api/get_usa_employee_profile", "data_selector": "result"}},
            {"name": "check_in_documents", "endpoint": {"path": "hcmRestApi/resources/11.13.18.05/checkInDocuments"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="name_hr_management_pipeline",
        destination="duckdb",
        dataset_name="name_hr_management_data",
    )
    load_info = pipeline.run(name_hr_management_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("name_hr_management_pipeline").dataset()
sessions_df = data.employees.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM name_hr_management_data.employees LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("name_hr_management_pipeline").dataset()
data.employees.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 Name HR Management 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

ServiceNow and myHR return 401 Unauthorized when credentials are missing or invalid. Verify the Authorization header (Basic base64(username:password)) and Accept: application/json. For ServiceNow, ensure the account used has API access rights.

Pagination and limits

ServiceNow uses sysparm_limit and sysparm_offset for pagination and returns a Next-Page header indicating if more pages exist. myHR includes a pagination object in result responses — use the provided pagination metadata to iterate pages.

Common HTTP errors

• 200: OK
• 401: Unauthorized — check credentials
• 404: Not found — endpoint or resource id invalid
• 500: Internal Server Error — check request payload, headers, and contact provider 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