This package provides a Python wrapper around libevdev, taking advantage of libevdev's advanced event handling. Documentation is available at https://python-libevdev.readthedocs.io/en/latest/. libevdev makes it easy to:

• read and parse events from an input device;

• create a virtual input device and make it send events;

• duplicate an existing device and modify the event stream.

For information about libevdev, see: https://freedesktop.org/wiki/Software/libevdev/.

Überzug is a command line util which draws images on terminals by using child windows. The advantages of using Überzug are:

• No race conditions as a new window is created to display images.

• Expose events will be processed, so images will be redrawn on switch workspaces.

• Tmux support (excluding multi pane windows).

• Terminals without the WINDOWID environment variable are supported.

• Chars are used as position - and size unit.

• No memory leak (/ unlimited cache).

iniparse is a INI parser for Python which is:

• Compatible with ConfigParser: Backward compatible implementations of ConfigParser, RawConfigParser, and SafeConfigParser are included that are API-compatible with the Python standard library.

• Preserves structure of INI files: Order of sections & options, indentation, comments, and blank lines are preserved as far as possible when data is updated.

• More convenient: Values can be accessed using dotted notation (cfg.user.name), or using container syntax (cfg['user']['name']).

Autograd can automatically differentiate native Python and NumPy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily. The main intended application of Autograd is gradient-based optimization.

Channels wraps Django's native asynchronous view support, allowing Django projects to handle not only HTTP, but protocols that require long-running connections too - WebSockets, MQTT, chatbots, amateur radio, and more. It does this while preserving Django's synchronous nature, allowing you to choose how you write your code - synchronous, fully asynchronous, or a mixture of both.

Channels also bundles this event-driven architecture with channel layers, a system that allows you to easily communicate between processes, and separate your project into different processes.

Astrocut provides tools for making cutouts from sets of astronomical images with shared footprints. It is under active development.

Three main areas of functionality are included:

• solving the specific problem of creating image cutouts from sectors of Transiting Exoplanet Survey Satellite full-frame images

• general fits file cutouts including from single images and sets of images with the shared WCS/pixel scale

• cutout post-processing functionality, including centering cutouts along a path (for moving targets) and combining cutouts

This package provides a resampling-based inference based on data resampling and permutation.

Features:

• Bootstrap resampling: ordinary or balanced with optional stratification

• Extended bootstrap resampling: also varies sample size

• Parametric resampling: Gaussian, Poisson, gamma, etc.)

• Jackknife estimates of bias and variance of any estimator

• Compute bootstrap confidence intervals (percentile or BCa) for any estimator

• Permutation-based variants of traditional statistical tests (USP test of independence and others)

• Tools for working with empirical distributions (CDF, quantile, etc.)

pythonOCC is a 3D CAD/PLM development library for the Python programming language. It provides 3D hybrid modeling, data exchange (support for the STEP/IGES file format), GUI management support (wxPython, PyQt, python-xlib), parametric modeling, and advanced meshing features. pythonOCC is built upon the OpenCASCADE 3D modeling kernel and the salomegeom and salomesmesh packages. Some high level packages (for parametric modeling, topology, data exchange, webservices, etc.) extend the builtin features of those libraries to enable highly dynamic and modular programming of any CAD application.

This package contains a Python module that forms the core of audit2allow, a part of the package policycoreutils. The sepolgen library contains: Reference Policy Representation, which are Objects for representing policies and the reference policy interfaces. It has objects and algorithms for representing access and sets of access in an abstract way and searching that access. It also has a parser for reference policy "headers". It contains infrastructure for parsing SELinux related messages as produced by the audit system. It has facilities for generating policy based on required access.

fMRIPrep is a fMRI data preprocessing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to variations in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting. It performs basic processing steps (coregistration, normalization, unwarping, noise component extraction, segmentation, skull-stripping, etc.) providing outputs that can be easily submitted to a variety of group level analyses, including task-based or resting-state fMRI, graph theory measures, and surface or volume-based statistics.

This package provides an object type which efficiently represents an array of booleans. Bitarrays are sequence types and behave very much like usual lists. Eight bits are represented by one byte in a contiguous block of memory. The user can select between two representations: little-endian and big-endian. All of the functionality is implemented in C. Methods for accessing the machine representation are provided. This can be useful when bit level access to binary files is required, such as portable bitmap image files. Also, when dealing with compressed data which uses variable bit length encoding, you may find this module useful.

This package provides an object type which efficiently represents an array of booleans. Bitarrays are sequence types and behave very much like usual lists. Eight bits are represented by one byte in a contiguous block of memory. The user can select between two representations: little-endian and big-endian. All of the functionality is implemented in C. Methods for accessing the machine representation are provided. This can be useful when bit level access to binary files is required, such as portable bitmap image files. Also, when dealing with compressed data which uses variable bit length encoding, you may find this module useful.

This package provides a Python library intended for use in automated tests. One difficulty when testing software is that the code under test might need to read or write to files in the local file system. If the file system is not set up in just the right way, it might cause a spurious error during the test. The pyfakefs library provides a solution to problems like this by mocking file system interactions. In other words, it arranges for the code under test to interact with a fake file system instead of the real file system. The code under test requires no modification to work with pyfakefs.

Pingouin is a statistical package written in Python 3 and based mostly on Pandas and NumPy. Its features include

• ANOVAs: N-ways, repeated measures, mixed, ancova

• Pairwise post-hocs tests (parametric and non-parametric) and pairwise correlations

• Robust, partial, distance and repeated measures correlations

• Linear/logistic regression and mediation analysis

• Bayes Factors

• Multivariate tests

• Reliability and consistency

• Effect sizes and power analysis

• Parametric/bootstrapped confidence intervals around an effect size or a correlation coefficient

• Circular statistics

• Chi-squared tests

• Plotting: Bland-Altman plot, Q-Q plot, paired plot, robust correlation, and more

Eventlet is a concurrent networking library for Python that allows you to change how you run your code, not how you write it. It uses epoll or libevent for highly scalable non-blocking I/O. Coroutines ensure that the developer uses a blocking style of programming that is similar to threading, but provide the benefits of non-blocking I/O. The event dispatch is implicit, which means you can easily use Eventlet from the Python interpreter, or as a small part of a larger application.

Note: In Guix, this package assumes the environment variable EVENTLET_NO_GREENDNS defaults to yes. To try to use it, set it to anything else.

Pymodbus is a full Modbus protocol implementation using asyncio, tornado or twisted for its asynchronous communications core. It includes the following client features:

• full read/write protocol on discrete and register

• most of the extended protocol (diagnostic/file/pipe/setting/information)

• TCP, UDP, Serial ASCII, Serial RTU, and Serial Binary

• asynchronous and synchronous versions

• payload builder/decoder utilities

• pymodbus read eval print loop (REPL).

It also includes the following server features:

• can function as a fully implemented Modbus server

• TCP, UDP, Serial ASCII, Serial RTU, and Serial Binary

• asynchronous and synchronous versions

• full server control context (device information, counters, etc)

• a number of backing contexts (database, redis, sqlite, a slave device).

Grandalf is a Python package made for experimentations with graphs drawing algorithms. It is written in pure Python, and currently implements two layouts: the Sugiyama hierarchical layout and the force-driven or energy minimization approach. While not as fast or featured as graphviz or other libraries like OGDF (C++), it provides a way to walk and draw graphs no larger than thousands of nodes, while keeping the source code simple enough to tweak and hack any part of it for experimental purpose. With a total of about 1500 lines of Python, the code involved in drawing the Sugiyama (dot) layout fits in less than 600 lines. The energy minimization approach is comprised of only 250 lines!

Grandalf does only 2 not-so-simple things:

• computing the nodes (x,y) coordinates (based on provided nodes dimensions, and a chosen layout)

• routing the edges with lines or nurbs

It doesn’t depend on any GTK/Qt/whatever graphics toolkit. This means that it will help you find where to draw things like nodes and edges, but it’s up to you to actually draw things with your favorite toolkit.

bx-python provides tools for manipulating biological data, particularly multiple sequence alignments.

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Asyncio IRC bot framework

Zope Internationalization Support

Software Heritage vault

Jalali datetime binding for python.