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.
## Tabular Storage
Package implements [Tabular Storage](https://github.com/okfn/datapackage-storage-py#tabular-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.tables
storage.check('table_name') # check existence
storage.create('table_name', schema)
storage.delete('table_name')
storage.describe('table_name') # return schema
storage.read('table_name') # return data
storage.write('table_name', data)
```
## Mappings
```
schema.json -> SQL table schema
data.csv -> SQL talbe data
```
## Drivers
SQLAlchemy is used - [docs](http://www.sqlalchemy.org/).
## Documentation
API documentation is presented as docstings:
- [Storage](https://github.com/frictionlessdata/jsontableschema-sql-py/blob/master/jsontableschema_sql/storage.py)
## Contributing
Please read the contribution guideline:
[How to Contribute](CONTRIBUTING.md)
Thanks!
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[![Gitter](https://img.shields.io/gitter/room/frictionlessdata/chat.svg)](https://gitter.im/frictionlessdata/chat)
Generate and load SQL tables based on JSON Table Schema descriptors.
## Tabular Storage
Package implements [Tabular Storage](https://github.com/okfn/datapackage-storage-py#tabular-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.tables
storage.check('table_name') # check existence
storage.create('table_name', schema)
storage.delete('table_name')
storage.describe('table_name') # return schema
storage.read('table_name') # return data
storage.write('table_name', data)
```
## Mappings
```
schema.json -> SQL table schema
data.csv -> SQL talbe data
```
## Drivers
SQLAlchemy is used - [docs](http://www.sqlalchemy.org/).
## Documentation
API documentation is presented as docstings:
- [Storage](https://github.com/frictionlessdata/jsontableschema-sql-py/blob/master/jsontableschema_sql/storage.py)
## Contributing
Please read the contribution guideline:
[How to Contribute](CONTRIBUTING.md)
Thanks!
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