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

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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

pip install tableschema-sql

Storage

Package implements Tabular Storage interface.

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

from sqlalchemy import create_engine
from tableschema_sql import Storage

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

Then we could interact with storage:

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.

API Reference

Snapshot

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

Detailed

Contributing

Please read the contribution guideline:

How to Contribute

Thanks!

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