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Setting up tables and encodings

superduperdb has flexible support for data-types. In both MongoDB and SQL databases, one uses superduperdb.Encoder to define one's own data-types.


To do that, one instantiates the Encoder class with functions which go to-and-from bytes.

Here is an Encoder which encodes numpy.ndarray instances to bytes:

import numpy

my_array = Encoder(
encoder=lambda x: memoryview(x).tobytes(),
decode=lambda x: numpy.frombuffer(x),

Here's a more interesting Encoder which encoders audio from numpy.array format to .wav file bytes:

import librosa
import io
import soundfile

def decoder(x):
buffer = io.BytesIO(x)
return librosa.load(buffer)

def encoder(x):
buffer = io.BytesIO()
return buffer.getvalue()

audio = Encoder('audio', encoder=encoder, decoder=decoder)

It's completely open to the user how exactly the encoder and decoder arguments are set.

You may include these Encoder instances in models, data-inserts and more. You can also directly register the Encoder instances in the system, using:


To reload (for instance in another session) do:

my_array_reloaded = db.load('encoder', 'my_array')
audio_reloaded = db.load('encoder', 'audio')

Schemas for SQL

For SQL databases, one needs to define a schemas to work with tables in superduperdb. The superduperdb.Schema builds on top of Encoder and allows developers to combine standard data-types traditionall used in SQL data-bases, with bespoke data-types via Encoder, as defined by, for instance, audio above.

To register/ create a Table with a Schema in superduperdb, one uses superduperdb.backends.ibis.Table:

from superduperdb.backends.ibis import Table, dtype
from superduperdb import Schema

fields={'txt': dtype('str'), 'audio': audio, 'array': my_array}

In this invocation, we create a Table with 2 columns, one with str values and one with audio values. When data is inserted using the db connection, it is inserted into those columns, and the audio component is used to convert the data into bytes.