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Generate SQL tables, load and extract data, based on JSON Table Schema descriptors.

Project description

# jsontableschema-sql-py

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Generate and load SQL tables based on JSON Table Schema descriptors.

> Version `v0.3` contains breaking changes:
- renamed `Storage.tables` to `Storage.buckets`
- changed `Storage.read` to read into memory
- added `Storage.iter` to yield row by row

## Getting Started

### Installation

```bash
pip install jsontableschema-sql
```

### Storage

Package implements [Tabular Storage](https://github.com/frictionlessdata/jsontableschema-py#storage) interface.

SQLAlchemy is used as sql wrapper. We can get storage this way:

```python
from sqlalchemy import create_engine
from jsontableschema_sql import Storage

engine = create_engine('sqlite:///:memory:', prefix='prefix')
storage = Storage(engine)
```

Then we could interact with storage:

```python
storage.buckets
storage.create('bucket', descriptor)
storage.delete('bucket')
storage.describe('bucket') # return descriptor
storage.iter('bucket') # yield rows
storage.read('bucket') # return rows
storage.write('bucket', rows)
```

### Mappings

```
schema.json -> SQL table schema
data.csv -> SQL talbe data
```

### Drivers

SQLAlchemy is used - [docs](http://www.sqlalchemy.org/).

## API Reference

### Snapshot

https://github.com/frictionlessdata/jsontableschema-py#snapshot

### Detailed

- [Docstrings](https://github.com/frictionlessdata/jsontableschema-py/tree/master/jsontableschema/storage.py)
- [Changelog](https://github.com/frictionlessdata/jsontableschema-sql-py/commits/master)

## Contributing

Please read the contribution guideline:

[How to Contribute](CONTRIBUTING.md)

Thanks!

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