This package provides a Zarr I/O backend for the HDMF.

Backport of pathlib ABCs.

This package provides a small utility for simplifying and cleaning up argument parsing scripts.

Compute a single hash of the file contents of a directory.

The pyjson-tricks package brings several pieces of functionality to python handling of JSON files:

• Store and load numpy arrays in human-readable format.

• Store and load class instances both generic and customized.

• Store and load date/times as a dictionary (including timezone).

• Preserve map order using OrderedDict.

• Allow for comments in json files by starting lines with #.

• Sets, complex numbers, Decimal, Fraction, enums, compression, duplicate keys, pathlib Paths, bytes, ...

As well as compression and disallowing duplicate keys.

Table logger using Rich, aimed at PyTorch Lightning logging.

Features

• display your training logs with pretty rich tables

• describe your fields with goal, format and name

• a field descriptor can be matched with any regex

• a field name can be computed as a regex substitution

• works in Jupyter notebooks as well as in a command line

• integrates easily with Pytorch Lightning

The Enable project provides two related multi-platform packages for drawing GUI objects.

• Enable: an object drawing library that supports containment and event notification.

• Kiva: a multi-platform DisplayPDF vector drawing engine.

A Python module to read Matlab files. This module works with both the old (< 7.3) and the new (>= 7.3) HDF5 based format. The output should be the same for both kinds of files.

This package provides a hierarchical data modeling framework for modern science data standards.

The Traits library is designed to enhance object-oriented programming in Python by providing a way to define and manage attributes of objects more effectively.

Fief is an open-source platform to manage users and authentication in your applications.

Key features:

• Pre-built login and registration pages

• Users management dashboard

• SDK for the most popular languages and frameworks

• Integrations for the most popular no-code tools

This package provides a flexible utility for flattening and unflattening dict-like objects in Python.

This package introduces a function decorator preventing a function from being called more often than that allowed by the API provider. This should prevent API providers from banning your applications by conforming to their rate limits.

distinctipy is a lightweight python package providing functions to generate colours that are visually distinct from one another.

This package provides functions for 3D coordinate transformations.

Python Bindings for the NVIDIA Management Library.

Easily pick a place to store data for your Python code.

h5io is a package designed to facilitate saving some standard Python objects into the forward-compatible HDF5 format. It is a higher-level package than h5py.

pybind11 is a lightweight header-only library that exposes C++ types in Python and vice versa, mainly to create Python bindings of existing C++ code. Its goals and syntax are similar to the Boost.Python library: to minimize boilerplate code in traditional extension modules by inferring type information using compile-time introspection.

TensorFlow is a flexible platform for building and training machine learning models. It provides a library for high performance numerical computation and includes high level Python APIs, including both a sequential API for beginners that allows users to build models quickly by plugging together building blocks and a subclassing API with an imperative style for advanced research.

JAX is Autograd and XLA, brought together for high-performance numerical computing, including large-scale machine learning research. With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order.

Protocol Buffers are a way of encoding structured data in an efficient yet extensible format. Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats.

ScotchPy is a python module to interface the Scotch/PT-Scotch graph partitioner library.

TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFlow ecosystem, TensorFlow Probability provides integration of probabilistic methods with deep networks, gradient-based inference via automatic differentiation, and scalability to large datasets and models via hardware acceleration (e.g., GPUs) and distributed computation.