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

# Python SDK Setup Guide

This guide walks you through installing and configuring the Elementary Python SDK to report assets, test results, and execution metadata from your Python pipelines.

## Installation

The Python SDK is installed via pip. Installation instructions and package requirements will be provided when you get access to the beta.

## Configuration

The Python SDK requires configuration to connect to your Elementary Cloud environment. You'll need:

1. **Elementary Cloud API Key** - Get this from your Elementary Cloud account settings
2. **Environment ID** - Your Elementary environment identifier

Configuration can be done via environment variables or a configuration file, similar to how the Elementary CLI is configured.

## Basic Concepts

The SDK is designed to work with any Python testing framework. The core functionality includes:

* **Reporting assets** - Tables, files, vector stores, or any data entity produced by your Python pipeline
* **Reporting test results** - Results from any testing framework (Great Expectations, pytest, custom frameworks, etc.)
* **Tracking execution metadata** - Pipeline runs, timing, status, and errors
* **Reporting lineage** - Connecting Python assets to upstream and downstream dependencies

## Integration with Existing Frameworks

The SDK works with any Python testing framework. You can wrap your existing tests to report results to Elementary without changing your test logic:

* **Great Expectations** - Report GE validation results
* **Pytest** - Report pytest test outcomes
* **Custom frameworks** - Report results from any homegrown testing solution
* **DQX and other tools** - The SDK is framework-agnostic

## Reporting Execution Metadata

Track pipeline execution details including:

* Pipeline name and environment
* Start and end times
* Duration
* Success/failure status
* Error messages and stack traces

## Reporting Lineage

Connect your Python assets to upstream and downstream dependencies, creating a complete lineage graph that includes:

* Python pipeline outputs
* dbt models
* Warehouse tables
* Unstructured data sources
* Vector stores
* ML model outputs

## Next Steps

* See [Usage Examples](/cloud/python-sdk/usage-examples) for conceptual examples
* Learn about the [SDK Overview](/cloud/python-sdk/overview)

## Need Help?

If you need assistance with setup or have questions about the SDK, [reach out to the team](https://meetings-eu1.hubspot.com/joost-boonzajer-flaes/intro-call-docs?uuid=17a4a61f-d0d3-4cbc-9362-56e37483f6f5).