Scanning all new published packages on PyPI I know that the quality is often quite bad. I try to filter out the worst ones and list here the ones which might be worth a look, being followed or inspire you in some way.

• datafaucet
Productivity Utilities for Data Science with Python Notebooks

• discovery-engines
Discovery Engines

• diva-framework
The DIVA Framework is a software framework designedto provide an architecture and a set of software modules whichwill facilitate the development of DIVA analytics

• embedeval
NLP Embeddings Evaluation Tool

• fastautoml
Fast Auto-machine Learning

• garnn
TensorFlow implementation of the Graphical Attention Recurrent Neural Net Model

• livelex
The livelex lexer. This module is designed to parse text using rules, which are regular-expression based. Rules are grouped into lexicons, and lexicons are grouped into a Language object. Every lexicon has its own set of rules that describe the text that is expected in that context.

• mlpug
A machine learning library agnostic framework for model training

• ninja4datascience
Data Science Ninja to help you to make your coding part easy

• pvlink
ParaView-Web RemoteRenderer in Jupyter

• tacs
TOML yet Another Configuration System. TACS was created as a lightweight library to define and manage system configurations, such as those commonly found in software designed for scientific experimentation. These ‘configurations’ typically cover concepts like hyperparameters used in training a machine learning model or configurable model hyperparameters, such as the depth of a convolutional neural network. Since you’re doing science, reproducibility is paramount and thus you need a reliable way to serialize experimental configurations. TACS uses TOML as a simple, human readable serialization format. The paradigm is: `your code + a TACS config for experiment E (+ external dependencies + hardware + other nuisance terms …) = reproducible experiment E`. While you might not be able to control everything, at least you can control your code and your experimental configuration. YACS is here to help you with that.

• ulangel
All-in-one framework for NLP Transfer Learning Classification