Infor CloudSuite Healthcare Python API Docs | dltHub

Infor CloudSuite uses the Infor ION API Gateway to provide a centralized, secure REST API management layer for accessing Infor OS services and business application APIs. The REST API base URL is The base URL for API calls is defined as the 'iu' (ION API URL) property in the tenant-specific .ionapi credential file. and all requests require an OAuth 2.0 Bearer token 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 add "dlt[hub]" and start loading Infor CloudSuite Healthcare data in under 10 minutes.

---

What data can I load from Infor CloudSuite Healthcare?

Here are some of the endpoints you can load from Infor CloudSuite Healthcare:

---

How do I authenticate with the Infor CloudSuite Healthcare API?

Authentication requires an OAuth 2.0 Bearer token obtained from the Infor Authorization Server using Client ID and Client Secret credentials, which is then passed in the Authorization HTTP header of API requests as 'Authorization: Bearer '.

1. Get your credentials

To obtain credentials for the Infor CloudSuite API, follow these steps in the Infor OS Portal: 1. Log into your Infor OS environment and navigate to the API Gateway application. 2. Select the 'Authorized Apps' tab. 3. Click 'Add New App' to create a new registration. 4. Specify a Name and select the appropriate Application Type (e.g., 'Backend Service' for server-to-server integrations). 5. If creating a Backend Service, enable the 'Create Service Account' toggle and specify a username. 6. Click 'Save' to register the application; this automatically generates the required Client ID and Client Secret. 7. Immediately click 'Download Credentials' to save the generated .ionapi file. This file is your only source for these credentials and must be stored securely.

2. Add them to .dlt/secrets.toml

Copy
[sources.infor_cloudsuite_healthcare_source]
infor_tenant_id = "your_tenant_id_from_ionapi_file"
infor_client_id = "ci_value_from_ionapi_file"
infor_client_secret = "cs_value_from_ionapi_file"
infor_service_account_access_key = "saak_value_from_ionapi_file"
infor_service_account_secret_key = "sask_value_from_ionapi_file"
infor_token_endpoint = "concat_of_pu_and_ot_from_ionapi_file"

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.

---

How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

Copy
uv init
uv add "dlt[hub]"

1. Install the dlt AI harness:

Copy
uv run dlthub 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:

Copy
uv run dlthub ai toolkit install rest-api-pipeline

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 Infor CloudSuite Healthcare 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:

Copy
uv run python infor_cloudsuite_healthcare_pipeline.py

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

Copy
Pipeline infor_cloudsuite_healthcare_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset infor_cloudsuite_healthcare_data
The duckdb destination used duckdb:/infor_cloudsuite_healthcare.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

Copy
uv run dlthub show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

---

Python pipeline example

This example loads token and revoke from the Infor CloudSuite Healthcare API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

Copy
import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def infor_cloudsuite_healthcare_source(ionapi_credentials=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "The base URL for API calls is defined as the 'iu' (ION API URL) property in the tenant-specific .ionapi credential file.",
            "auth": {"type": "bearer", "token": ionapi_credentials},
        },
        "resources": [
            {"name": "ion_documents", "endpoint": {"path": "ion-api/documents", "data_selector": "documents"}},
            {"name": "ln_odata", "endpoint": {"path": "lnapi/odata/{Resource}", "data_selector": "value"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="infor_cloudsuite_healthcare_pipeline",
        destination="duckdb",
        dataset_name="infor_cloudsuite_healthcare_data",
    )
    load_info = pipeline.run(infor_cloudsuite_healthcare_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.

---

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):

Copy
import dlt

data = dlt.pipeline("infor_cloudsuite_healthcare_pipeline").dataset()
sessions_df = data.ion_documents.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM infor_cloudsuite_healthcare_data.ion_documents LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("infor_cloudsuite_healthcare_pipeline").dataset()
data.ion_documents.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

---

What destinations can I load Infor CloudSuite Healthcare 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.

---

Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI harness:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-platform — Deploy, schedule, and monitor your pipeline in production.

Copy
uv run dlthub ai toolkit install data-exploration
uv run dlthub ai toolkit install dlthub-platform

• 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