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# Container

## Why Would You Use Containers?

The Container entity represents a logical grouping of entities, such as datasets, data processing instances, or even other containers. It helps users organize and manage metadata in a hierarchical structure, making it easier to navigate and understand relationships between different entities.

#### How is a Container related to other entities?

1. **Parent-Child Relationship** : Containers can contain other entities such as datasets, charts, dashboards, data jobs, ML models, and even other containers (nested containers). For example, a dataset can have a container aspect that links it to the schema or folder (container) it belongs to.

2. **Hierarchical Organization** : Containers can be nested, forming a hierarchy (e.g., a database container contains schema containers, which contain table containers). This enables a folder-like browsing experience in the DataHub UI.

3. **Relationships in the Metadata Model** : Many entities (datasets, data jobs, ML models, etc.) have a container aspect that links them to their parent container. Containers themselves can have a parentContainer aspect for nesting.

### Goal Of This Guide

This guide will show you how to

- Create a container

## Prerequisites

For this tutorial, you need to deploy DataHub Quickstart and ingest sample data.
For detailed steps, please refer to [Datahub Quickstart Guide](/docs/quickstart.md).

## Create Container

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```python
{{ inline /metadata-ingestion/examples/library/create_container.py show_path_as_comment }}
```

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