Anndata is a package for simple (functional) high-level APIs for data analysis pipelines. In this context, it provides an efficient, scalable way of keeping track of data together with learned annotations and reduces the code overhead typically encountered when using a mostly object-oriented library such as scikit-learn.
This library allows you to create a system tray icon. It makes it possible to specify an icon, a title and a callback for when the icon is activated. The icon and title can be changed after the icon has been created, and the visibility of the icon can be toggled.
Trimesh is a pure Python library for loading and using triangular meshes with an emphasis on watertight surfaces. The goal of the library is to provide a full featured and well tested Trimesh object which allows for easy manipulation and analysis, in the style of the Polygon object in the Shapely library.
The pip-run command provides on-demand temporary package installation for a single interpreter run. It replaces this series of commands:
$ virtualenv --python pythonX.X --system-site-packages /tmp/env $ /tmp/env/bin/pip install pkg1 pkg2 -r reqs.txt $ /tmp/env/bin/python ... $ rm -rf /tmp/env
The aiorpcX library is a generic asyncio implementation of RPC suitable for an application that is a client, server or both.
The package includes a module with full coverage of JSON RPC versions 1.0 and 2.0, JSON RPC protocol auto-detection, and arbitrary message framing. It also comes with a SOCKS proxy client.
The aiorpcX library is a generic asyncio implementation of RPC suitable for an application that is a client, server or both.
The package includes a module with full coverage of JSON RPC versions 1.0 and 2.0, JSON RPC protocol auto-detection, and arbitrary message framing. It also comes with a SOCKS proxy client.
Wcwidth measures the number of terminal column cells of wide-character codes. It is useful for those implementing a terminal emulator, or programs that carefully produce output to be interpreted by one. It is a Python implementation of the wcwidth and wcswidth C functions specified in POSIX.1-2001 and POSIX.1-2008.
Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains. Some of its key distinguishing features include: clear, readable syntax; strong introspection capabilities; intuitive object orientation; natural expression of procedural code; full modularity, supporting hierarchical packages; exception-based error handling; and very high level dynamic data types.
PySAML2 is a pure python implementation of SAML Version 2 Standard. It contains all necessary pieces for building a SAML2 service provider or an identity provider. The distribution contains examples of both.
This package was originally written to work in a WSGI environment, but there are extensions that allow you to use it with other frameworks.
zconfig is a configuration library intended for general use. It supports a hierarchical schema-driven configuration model that allows a schema to specify data conversion routines written in Python. Its model is very different from the model supported by the configparser module found in Python's standard library, and is more suitable to configuration-intensive applications.
The rencode module is a data structure serialization library, similar to bencode from the BitTorrent project. For complex, heterogeneous data structures with many small elements, r-encoding stake up significantly less space than b-encodings. This version of rencode is a complete rewrite in Cython to attempt to increase the performance over the pure Python module.
The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.
The ufoLib2 Python library is meant to be a thin representation of the Unified Font Object (UFO) version 3 data model, intended for programmatic manipulation and fast batch processing of UFOs. It resembles the defcon library, but does without notifications, the layout engine and other support classes. Where useful and possible, ufoLib2 tries to be API-compatible with defcon.
Whisper is one of three components within the Graphite project. Whisper is a fixed-size database, similar in design and purpose to RRD (round-robin-database). It provides fast, reliable storage of numeric data over time. Whisper allows for higher resolution (seconds per point) of recent data to degrade into lower resolutions for long-term retention of historical data.
Baycomp is a library for Bayesian comparison of classifiers. Functions in the library compare two classifiers on one or on multiple data sets. They compute three probabilities: the probability that the first classifier has higher scores than the second, the probability that differences are within the region of practical equivalence (rope), or that the second classifier has higher scores.
API to query the distutils metadata written in PKG-INFO inside a source distriubtion (an sdist) or a binary distribution (e.g., created by running bdist_egg). It can also query the EGG-INFO directory of an installed distribution, and the *.egg-info stored in a "development checkout" (e.g, created by running python setup.py develop).
TOML Kit is a 1.0.0rc1-compliant TOML library. It includes a parser that preserves all comments, indentations, whitespace and internal element ordering, and makes them accessible and editable via an intuitive API. It can also create new TOML documents from scratch using the provided helpers. Part of the implementation has been adapted, improved, and fixed from Molten.
PyTorch is a Python package that provides two high-level features:
tensor computation (like NumPy) with strong GPU acceleration;
deep neural networks (DNNs) built on a tape-based autograd system.
You can reuse Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed.
Note: currently this package does not provide GPU support.
PyTorch is a Python package that provides two high-level features:
tensor computation (like NumPy) with strong GPU acceleration;
deep neural networks (DNNs) built on a tape-based autograd system.
You can reuse Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed.
Note: currently this package does not provide GPU support.
Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays are accelerated and use less memory than doing the same calculation in Python. In addition, its multi-threaded capabilities can make use of all your cores, which may accelerate computations, most specially if they are not memory-bounded (e.g. those using transcendental functions).
Cartopy is a Python package designed to make drawing maps for data analysis and visualisation easy.
It features:
object oriented projection definitions
point, line, polygon and image transformations between projections
integration to expose advanced mapping in Matplotlib with a simple and intuitive interface
powerful vector data handling by integrating shapefile reading with Shapely capabilities
Passlib is a password hashing library for Python 2 & 3, which provides cross-platform implementations of over 30 password hashing algorithms, as well as a framework for managing existing password hashes. It's designed to be useful for a wide range of tasks, from verifying a hash found in /etc/shadow, to providing full-strength password hashing for multi-user application.
This package provides a Python implementation of the CANopen standard for CANs. The aim of the project is to support the most common parts of the CiA 301 standard in a simple Pythonic interface. It is mainly targeted for testing and automation tasks rather than a standard compliant master implementation.
msgspec is a fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML. It includes the following features:
High performance encoders/decoders for common protocols.
Support for a wide variety of Python types.
Zero-cost schema validation using familiar Python type annotations.
A speedy Struct type for representing structured data.