Lmdb Python Packages

montydb

Monty, Mongo tinified. MongoDB implemented in Python !

lmdbm

Python DBM style wrapper of LMDB

zlmdb

Object-relational in-memory database layer based on LMDB

cengal-light

Bytecode manipulation in runtime, true shared memory, async LMDB, async Tkinter, async wxPython, async PySide, async PyQt, async loop with almost preemptive multitasking within the single thread, text parsing, rich introspection, etc.

torchtoolbox

🛠 Toolbox to extend PyTorch functionalities

cengal

Bytecode manipulation in runtime, true shared memory, async LMDB, async Tkinter, async wxPython, async PySide, async PyQt, async loop with almost preemptive multitasking within the single thread, text parsing, rich introspection, etc.

zcls

Object Classification Training Framework

hannoy

HNSW Approximate Nearest Neighbors in Rust, based on LMDB and optimized for memory usage

flaxkv

A high-performance dictionary database.

torchfurnace

A tool package for training model, pre-processing dataset and managing experiment record in pytorch AI tasks.

pnno

dataset or annotation file format conversion

greendb

server frontend for lmdb

flaxfile

🗲 A high-performance on-disk dictionary.

py-wsi

Python package for dealing with whole slide images (.svs) for machine learning, including intuitive, painless patch sampling using OpenSlide, automatic labeling from ImageScope XML annotation files, and functions for saving these patches and their meta data into lightning memory-mapped databases (LMDB) for quick reads.

aiolmdb

An asyncio wrapper around LMDB for Python.

nque

High-performance persistent FIFO queues with LMDB backend supporting both single-queue and multi-queue broadcast patterns.

lmdbm-lockable

Python DBM style wrapper of LMDB

pup-py-db

This is an experimental learning project to explore how vector databases work under the hood. Major components are being built step by step.

ml-pyxis

Tool for reading and writing datasets of tensors in a Lightning Memory-Mapped Database (LMDB). Designed to manage machine learning datasets with fast reading speeds.