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.
Publisher identity
New Manifest publications record the Python distribution version, shared core
build identity and operation in the existing writer tag. Optional
dataset.set_application(name, revision) identifies your application on later
publications; reopening a Dataset resets that optional pair. This does not label
retained payloads or prove execution. See publisher provenance
for limits, build configuration and historical/operator behavior.
1 maintainer
Metadata
1 maintainer
Release files for dreamdb 0.0.13
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dreamdb-0.0.13-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl | CPython 3.8 | abi3 | Linux glibc 2.17+ x86-64 | Details |
| dreamdb-0.0.13-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl | CPython 3.8 | abi3 | Linux glibc 2.17+ ARM64 | Details |
| dreamdb-0.0.13-cp38-abi3-macosx_11_0_arm64.whl | CPython 3.8 | abi3 | macOS 11.0+ ARM64 | Details |
Total release size: 16.2 MB
Release files / dreamdb-0.0.13-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
| Download URL | dreamdb-0.0.13-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl |
|---|---|
| Size | 5.7 MB |
| Tags | CPython 3.8 Linux glibc 2.17+ x86-64 abi3 |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / dreamdb-0.0.13-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
| Download URL | dreamdb-0.0.13-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl |
|---|---|
| Size | 5.3 MB |
| Tags | CPython 3.8 Linux glibc 2.17+ ARM64 abi3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
d656d0eeaf51a2b2b479fc062d95dd25b6c3392a3046edbc9e6ab729a5bf0e36
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 15, 2026.
Transparency logRelease files / dreamdb-0.0.13-cp38-abi3-macosx_11_0_arm64.whl
| Download URL | dreamdb-0.0.13-cp38-abi3-macosx_11_0_arm64.whl |
|---|---|
| Size | 5.1 MB |
| Tags | CPython 3.8 abi3 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 15, 2026.
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