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

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# Examples & Notebooks

PyCharter’s examples live in the docs/notebooks/ directory as Jupyter notebooks. They cover the same topics as the old `pycharter/examples` scripts and are kept in sync with the current API.

## Notebooks

Notebook | Contents
--- | ---
01 Getting Started | Validation, Validator class, a simple ETL pipeline, and a quality check.
02 ETL Pipelines | HTTP/file extraction, transformer showcase, chained transforms, config-driven pipelines.
03 Data Contracts | Parsing contracts (dict/file), building from artifacts, coercion and validation extensions.
04 Validation & Quality | Basic and batch validation, contract-based validation, QualityCheck, thresholds, DataProfiler.
05 Metadata Store | In-memory store, coercion/validation rules, versioning, production backends (Postgres, MongoDB, Redis, SQLite).
06 Schema Conversion | JSON Schema → Pydantic and Pydantic → JSON Schema; nested types, round-trip, formats.

## Where to run them

- Local: From the repo root, run `jupyter notebook docs/notebooks/` or open the `.ipynb` files in VS Code.
- Colab: Use the “Open in Colab” badge on each notebook when viewing the repo on GitHub (e.g. `docs/notebooks/01_getting_started.ipynb`).

## Related docs

- Quick Start
- Tutorials (markdown tutorials)
- API Reference