python3-klepto

Persistent caching to memory, disk or database

klepto extends Python's lru_cache to utilise different keymaps and alternate caching algorithms. This package also has archiving capabilities for longer-term storage. It uses a simple dictionary-style interface for all caches and archives, and all caches can be applied to any Python function as a decorator.

python3-dict2css

μ-library for transforming Python Dicts to CSS (Python 3)

This package provides an API similar to the json and toml modules, with dump and load functions.

rdflib-endpoint

SPARQL endpoint for RDFLib - command line tool

rdflib-endpoint is a SPARQL endpoint based on RDFLib to easily serve RDF files locally, machine learning models, or any other logic implemented in Python via custom SPARQL functions.

python3-mystic

Constrained nonlinear optimization

The mystic framework provides a collection of optimization algorithms and tools that allows the user to more robustly (and easily) solve hard optimization problems for machine learning, uncertainty quantification and AI. mystic gives the user fine-grained power to both monitor and steer optimizations as the fit processes are running. Users can customize optimizer stop conditions, where both compound and user-provided conditions may be used. Optimizers can save state, can be reconfigured dynamically, and can be restarted from a saved solver or from a results file. All solvers can also leverage parallel computing, either within each iteration or as an ensemble of solvers.

python3-bleak

Bluetooth Low Energy platform agnostic client

Bleak is an acronym for Bluetooth Low Energy platform Agnostic Klient.

lua-resty-lrucache

Simple LRU cache for the ngx_lua module

The LRU cache resides completely in the Lua VM and is subject to Lua GC. As such, do not expect it to get shared across the OS process boundary. The upside is that you can cache arbitrary complex Lua values (such as deep nested Lua tables) without the overhead of serialization (as with ngx_lua's shared dictionary API). The downside is that your cache is always limited to the current OS process (i.e. the current Nginx worker process). It does not really make much sense to use this library in the context of init_by_lua because the cache will not get shared by any of the worker processes (unless you just want to "warm up" the cache with predefined items which will get inherited by the workers via fork()).