> ## Documentation Index
> Fetch the complete documentation index at: https://docs.lume.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# API Overview

> A high-level overview of the Lume Python SDK

The Lume Python SDK is designed to be simple and intuitive. The API is centered around a few core functions and a primary data object, `LumeRun`.

This reference is divided into the following sections:

* **[Functions](/pages/libraries/python-ent/api/functions)**: Top-level functions like `lume.run()` for interacting with the Lume platform.
* **[Classes](/pages/libraries/python-ent/api/classes/lumerun)**: Core data objects, primarily the `LumeRun` object that represents a pipeline execution.
* **[Exceptions](/pages/libraries/python-ent/api/classes/exceptions)**: Custom exceptions raised by the SDK for specific error conditions.

## Authentication

The SDK authenticates automatically by reading the `LUME_API_KEY` from your environment variables. You can also initialize the client explicitly using the [`lume.init()`](/pages/libraries/python-ent/api/functions#init) function, which is useful in environments where you cannot set environment variables.

## Basic Workflow

The most common workflow involves two primary steps:

1. Calling `lume.run()` to trigger a new pipeline.
2. Using the returned `LumeRun` object to monitor the execution, either by blocking with `run.wait()` or by periodically checking its `status`.

```python theme={null}
import lume

# Trigger a run
run = lume.run(
    flow_version="my-flow:v1", 
    source_path="unique-batch-id-123"
)

# Wait for it to complete
run.wait()

# Check the final status
print(f"Run {run.id} finished with status: {run.status}")
```