metad 0.0.2
A hierarchical representation for the structure of a relational database.
License: MIT license
Requires Python: >=3.5
Keywords: metad metad MetaData

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<i>An open source project from Data to AI Lab at MIT.</i>
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# MetaData

This project aims to formally define a JSON schema which captures the structure of a relational database.

- JSON Schema: https://data-dev.github.io/MetaData/schema.html
- Documentation: https://data-dev.github.io/MetaData
- Homepage: https://github.com/data-dev/MetaData
- License: [MIT](LICENSE)

# Install

## Requirements

**MetaData** has been developed and tested on [Python 3.5, 3.6, 3.7 and 3.8](https://www.python.org/downloads/)

Also, although it is not strictly required, the usage of a [virtualenv](https://virtualenv.pypa.io/en/latest/)
is highly recommended in order to avoid interfering with other software installed in the system
in which **MetaData** is run.

## Install with pip

The easiest and recommended way to install **MetaData** is using [pip](
https://pip.pypa.io/en/stable/):

```bash
pip install metad
```

This will pull and install the latest stable release from [PyPi](https://pypi.org/).

If you want to install from source or contribute to the project please read the
[Contributing Guide](https://hdi-project.github.io/MetaData/contributing.html#get-started).

# Quickstart

In this short tutorial we will guide you through a series of steps that will help you
getting started with **MetaData**.

## Creating Metadata Objects

You can also help create Metadata objects from scratch. The following code will create a
`MetaData` object, add a table, and then save it to a JSON file.

```python3
from metad import MetaData

metadata = MetaData()

metadata.add_table({
    "id": "users",
    "name": "users",
    "primary_key": "id",
    "fields": [
        {"name": "id", "data_type": "id"},
        {"name": "name", "data_type": "text"}
    ],
})
```

Then, to export this object to a JSON file, you can run the following:

```python3
metadata.to_json("your_metadata.json")
```

## Validating JSON Files

The core functionality of this library is to validate JSON files. The following code will load
the metadata file for the `hello_world` dataset and validate it.

```python3
from metad import MetaData

metadata = MetaData.from_json("your_metadata.json")
metadata.validate()
```

# What's next?

For more details about **MetaData** and all its possibilities and features, please check the
[documentation site](https://data-dev.github.io/MetaData/).


# History

## 0.0.1 (2020-06-08)

* Populate data subtype in MySQL connector - [Issue #11](https://github.com/data-dev/MetaData/issues/11) by @k15z
* Modifying the schema to support non-unique table names - [Issue #13](https://github.com/data-dev/MetaData/issues/13) by @k15z

## 0.0.1 (2020-05-22)

* First release on PyPI.