Check if a certain debug flag is enabled.

A list of color names and its values

Date formatting and parsing

HTTP proxying for the masses

This package includes WrapSpawner and ProfilesSpawner, which provide mechanisms for runtime configuration of spawners. The inspiration for their development was to allow users to select from a range of pre-defined batch job profiles, but their operation is completely generic.

Jupyter telemetry library

This package provides a spawner for Jupyterhub to spawn notebooks using batch resource managers.

LDAP Authenticator for JupyterHub

The SudoSpawner enables JupyterHub to spawn single-user servers without being root, by spawning an intermediate process via sudo, which takes actions on behalf of the user.

JupyterHub: A multi-user server for Jupyter notebooks

The systemdspawner enables JupyterHub to spawn single-user notebook servers using systemd.

An extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture.

TensorStore is a C++ and Python software library designed for storage and manipulation of large multi-dimensional arrays that:

• Provides advanced, fully composable indexing operations and virtual views.

• Provides a uniform API for reading and writing multiple array formats, including zarr and N5.

• Natively supports multiple storage systems, such as local and network filesystems, Google Cloud Storage, Amazon S3-compatible object stores, HTTP servers, and in-memory storage.

• Offers an asynchronous API to enable high-throughput access even to high-latency remote storage.

• Supports read caching and transactions, with strong atomicity, isolation, consistency, and durability (ACID) guarantees.

• Supports safe, efficient access from multiple processes and machines via optimistic concurrency.

sklearn-compat is a small Python package that help developer writing scikit-learn compatible estimators to support multiple scikit-learn versions.

EZyRB is a python library for the Model Order Reduction based on baricentric triangulation for the selection of the parameter points and on Proper Orthogonal Decomposition for the selection of the modes.

This package provides a Python library for outlier and anomaly detection, integrating classical and deep learning techniques .

Evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized.

This package is an integration module of Optuna, an automatic Hyperparameter optimization software framework. The modules in this package provide users with extended functionalities for Optuna in combination with third-party libraries such as PyTorch, sklearn, and TensorFlow.

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplifying ML compute. These are the provided Ray AI libraries:

• Data: Scalable datasets for ML;

• Train: Distributed training;

• Tune: Scalable hyperparameter tuning;

• RLlib: Scalable reinforcement learning;

• Serve: Scalable and programmable serving.

PyThresh is a comprehensive and scalable Python toolkit for thresholding outlier detection likelihood scores in univariate/multivariate data. It has been written to work in tandem with PyOD and has similar syntax and data structures. However, it is not limited to this single library.

PyThresh is meant to threshold likelihood scores generated by an outlier detector. It thresholds these likelihood scores and replaces the need to set a contamination level or have the user guess the amount of outliers that may exist in the dataset beforehand. These non-parametric methods were written to reduce the user's input/guess work and rather rely on statistics instead to threshold outlier likelihood scores. For thresholding to be applied correctly, the outlier detection likelihood scores must follow this rule: the higher the score, the higher the probability that it is an outlier in the dataset. All threshold functions return a binary array where inliers and outliers are represented by a 0 and 1 respectively.

PyThresh includes more than 30 thresholding algorithms. These algorithms range from using simple statistical analysis like the Z-score to more complex mathematical methods that involve graph theory and topology.

AlphaFold is an AI system developed by DeepMind that predicts a protein’s 3D structure from its amino acid sequence. It regularly achieves accuracy competitive with experiment.

Python bindings for KeOps, on CPUs and GPUs, with autodiff and without memory overflows.

imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-class imbalance.

This package provides a set of custom transformers, metrics and models complementing scikit-learn, which results from a collaboration between multiple companies in the Netherlands.