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DreamDB Python SDK

Python bindings for the DreamDB multimodal versioned data lake — image + audio + text + embeddings + scalar metadata on content-addressed object storage, with vector and metadata filters for ML training pipelines.

Quick start

from pathlib import Path
from tempfile import TemporaryDirectory
import dreamdb as db

with TemporaryDirectory(prefix="dreamdb-quickstart-") as directory:
    backend = Path(directory).as_uri()
    schema = db.Schema().add_scalar_string("label")
    ds = db.Dataset.create("example", schema, backend=backend)
    ds.append_many([{"_anchor": 1, "label": "cat"}])
    reopened = db.Dataset.open("example", backend=backend)
    assert reopened.count() == 1

For trained vector indexes, use the versioned index guide. The feature examples cover Python 0.0.11, including entity keys, progressive geometry and structured arrays. Older packages do not necessarily expose these methods.

Build from source

pip install maturin
cd dreamdb-dataset-python
maturin develop --release

This produces the dreamdb package installed into the current virtualenv. Importing it gives the Schema and Dataset classes shown above.

Metadata

Release files for dreamdb 0.0.12

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Table of built distributions (wheels) for dreamdb 0.0.12
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dreamdb-0.0.12-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.8 abi3 Linux glibc 2.17+ x86-64 Details
dreamdb-0.0.12-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl CPython 3.8 abi3 Linux glibc 2.17+ ARM64 Details
dreamdb-0.0.12-cp38-abi3-macosx_11_0_arm64.whl CPython 3.8 abi3 macOS 11.0+ ARM64 Details

Total release size: 16.1 MB

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Tags CPython 3.8 Linux glibc 2.17+ x86-64 abi3
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