Overview - PyCharter
Description: Data Contract Management, ETL Pipelines, and Quality Assurance for Python

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# Tutorials

Step-by-step guides to master PyCharter's features.

## Learning Path

We recommend following these tutorials in order:

    graph LR
        A[ETL Pipelines] --> B[Contracts & Validation]
        B --> C[Quality Monitoring]
        C --> D[Metadata Store]
        D --> E[REST API & UI]

## Available Tutorials

- Building ETL Pipelines

  Learn to build data pipelines with extractors, transformers, and loaders.

  Duration: 30 minutes

  Start Tutorial

- Data Contracts & Validation

  Define contracts, coercion rules, and validation logic for your data.

  Duration: 25 minutes

  Start Tutorial

- Data Quality Monitoring

  Monitor quality metrics, track violations, and set threshold alerts.

  Duration: 20 minutes

  Start Tutorial

- Metadata Store & Schema Registry

  Store, version, and retrieve schemas using different backends.

  Duration: 20 minutes

  Start Tutorial

- REST API & Web UI

  Use PyCharter's API server and interactive web interface.

  Duration: 15 minutes

  Start Tutorial

## Prerequisites

Before starting the tutorials, ensure you have:

- Python 3.11+ installed
- PyCharter installed (`pip install pycharter[api,ui,etl]`)
- Basic knowledge of Python async/await
- Familiarity with JSON Schema (helpful but not required)

## Tutorial Format

Each tutorial includes:

1. Overview - What you'll learn
2. Prerequisites - What you need before starting
3. Step-by-step instructions - Hands-on coding
4. Code examples - Copy-paste ready snippets
5. Exercises - Practice what you've learned
6. Next steps - Where to go from here

## Getting Help

If you get stuck:

- Check the API Reference for detailed documentation
- Search GitHub Issues
- Ask on GitHub Discussions