Skip to main content

Dreamlake

A simple and flexible SDK for ML experiment tracking and data storage.

Features

  • Three Usage Styles: Decorator, context manager, or direct instantiation
  • Dual Operation Modes: Remote (API server) or local (filesystem)
  • Auto-creation: Automatically creates namespace, workspace, and folder hierarchy
  • Upsert Behavior: Updates existing episodes or creates new ones
  • Simple API: Minimal configuration, maximum flexibility
  • Time-Based Queries: MCAP-like API for querying track data by timestamp ranges
  • Multi-Modal Sync: Timestamp inheritance for synchronizing pose, images, and sensor data

Installation

Using uv (recommended) Using pip
uv add dreamlake@0.4.2
pip install dreamlake==0.7.1

CLI (deprecated — use the standalone DreamLake CLI)

The Python CLI bundled in this package is deprecated, and this package no longer installs a dreamlake console script. Install the standalone DreamLake CLI instead — same commands, flags, and env vars (including artifact push and the workflow group), plus environment switching (dreamlake env use):

curl -fsSL https://dl.dreamlake.ai/install.sh | bash

The CLI code stays in this package for now. The internal artifact|workflow append-local writers are NOT deprecated — they remain the canonical DreamDB writers that dreamlake-server spawns, reachable via python -m dreamlake.cli (point WORKFLOWS_APPLY_BIN at a wrapper that invokes it).

Quick Start

Remote Mode (with API Server)

from dreamlake import Episode

with Episode(
    name="my-experiment",
    workspace="my-workspace",
    remote="https://cu3thurmv3.us-east-1.awsapprunner.com",
    api_key="your-jwt-token"
) as episode:
    print(f"Episode ID: {episode.id}")

Local Mode (Filesystem)

from dreamlake import Episode

with Episode(
    name="my-experiment",
    workspace="my-workspace",
    local_path=".dreamlake"
) as episode:
    pass  # Your code here

See examples/ for more complete examples.

Development Setup

Installing Dev Dependencies

To contribute to Dreamlake or run tests, install the development dependencies:

Using uv (recommended) Using pip
uv sync --extra dev
pip install -e ".[dev]"

This installs:

  • pytest>=8.0.0 - Testing framework
  • pytest-asyncio>=0.23.0 - Async test support
  • sphinx>=7.2.0 - Documentation builder
  • sphinx-rtd-theme>=2.0.0 - Read the Docs theme
  • sphinx-autobuild>=2024.0.0 - Live preview for documentation
  • myst-parser>=2.0.0 - Markdown support for Sphinx
  • ruff>=0.3.0 - Linter and formatter
  • mypy>=1.9.0 - Type checker

Running Tests

Using uv Using pytest directly
uv run pytest
pytest

Building Documentation

Documentation is built using Sphinx with Read the Docs theme.

Build docs Live preview Clean build
uv run python -m sphinx -b html docs docs/_build/html
uv run sphinx-autobuild docs docs/_build/html
rm -rf docs/_build

The live preview command starts a local server and automatically rebuilds when files change.

Alternatively, you can use the Makefile from within the docs directory:

cd docs
make html          # Build HTML documentation
make clean         # Clean build files

For maintainers, to build and publish a new release: uv build && uv publish

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dreamlake-0.7.1.tar.gz (157.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dreamlake-0.7.1-py3-none-any.whl (192.1 kB view details)

Uploaded Python 3

File details

Details for the file dreamlake-0.7.1.tar.gz.

File metadata

  • Download URL: dreamlake-0.7.1.tar.gz
  • Upload date:
  • Size: 157.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.2

File hashes

Hashes for dreamlake-0.7.1.tar.gz
Algorithm Hash digest
SHA256 ac433aa7a4d341a4e7b5922e7e5a928d8b211867e1e0e850bdf9138650e8fd58
MD5 137ba173aa8cc58ca11f8ca96885cb03
BLAKE2b-256 6052ee9e4579b4765fdf102bc192d27b34c0ef5339a7157d8a03071a29f860e0

See more details on using hashes here.

File details

Details for the file dreamlake-0.7.1-py3-none-any.whl.

File metadata

  • Download URL: dreamlake-0.7.1-py3-none-any.whl
  • Upload date:
  • Size: 192.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.2

File hashes

Hashes for dreamlake-0.7.1-py3-none-any.whl
Algorithm Hash digest
SHA256 1842c30661c18ffdc68efaafde07296760bc6a9b4de18246dfe761e4fe7889c8
MD5 fa06fb5ce01759d939d5bae579a57023
BLAKE2b-256 e86b3effad5132054eb265b3d552fc9127a441ec7be0cc782b05580c36ddfbf9

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page