superduper-sql 0.6.1

`superduper_sql` is a plugin for SQL databases that allows you to use these databases as databackends for Superduper.

superduper_sql

superduper-sql is a plugin for SQL databackends that allows you to use these backends with superduper.

Superduper supports SQL databases via the ibis project. With superduper, queries may be built which conform to the ibis API, with additional support for complex data-types and vector-searches.

Installation

pip install superduper_sql

API

• Code
• API-docs

Class	Description
superduper_sql.data_backend.SQLDataBackend	sql data backend for the database.

Connection examples

MySQL

from superduper import superduper

db = superduper('mysql://<mysql-uri>')

Postgres

from superduper import superduper

db = superduper('postgres://<postgres-uri>')

Other databases

from superduper import superduper

db = superduper('<database-uri>')

Query examples

Inserting data

Table data must correspond to the Schema for that table. Either create a Schema and Table or use an auto-detected Schema. Once you've got a Schema, all data inserted must conform to that Schema:

import pandas

pandas.DataFrame([
    PIL.Image.open('image.jpg'), 'some text', 4,
    PIL.Image.open('other_image.jpg'), 'some other text', 3,
])

t.insert(dataframe.to_dict(orient='records'))

Selecting data

superduper supports selecting data via the ibis query API. For example:

db['my_table'].filter(t.rating > 3).limit(5).select(t.image).execute()

Vector-search

Vector-searches are supported via the like operator:

(
    db['my_table']
    .like({'text': 'something like this'}, vector_index='my-index')
    .filter(t.rating > 3)
    .limit(5)
    .select(t.image, t.id)
).execute()

Vector-searches are either first or last in a chain of operations:

(
    db['my_table']
    t.filter(t.rating > 3)
    .limit(5)
    .select(t.image, t.id)
    .like({'text': 'something like this'}, vector_index='my-index')
).execute()

Updating data

Updates are not covered for superduper SQL integrations.

Deleting data

db.databackend.drop_table('my-table')