Modified items

All recently modified items, latest first.

python3-numpy-stl-2.16.3-1.fc36.x86_64: Simple library to make working with STL files (and 3D objects in general) fast and easy. Due to all operations heavily relying on NumPy this is one of the fastest STL editing libraries for Python available.

python3-numpy-f2py-2.2.4-1.lbn36.x86_64: This package includes a version of f2py that works properly with NumPy.

python3-numpy-2.2.4-1.lbn36.x86_64: NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. Also included in this package is a version of f2py that works properly with NumPy.

python3-numexpr-2.10.2-2.lbn36.x86_64: The numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It’s the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime.

python3-notebook-7.2.0-1.lbn36.noarch: The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Notebook has support for multiple programming languages, sharing, and interactive widgets.

python3-nosexcover-1.0.11-1.lbn36.noarch: nose-xmlcover --A companion to the built-in nose.plugins.cover, this plugin will write out an XML coverage report to a file named coverage.xml.It will honor all the options you pass to the Nose coverage plugin < especially --cover- package.UsageYou can not use both --with-xcoverage and --with- coverage. Using --with-xcover implies --with-coverageIf you want to change the name of the output file...

python3-nftables-1.0.1-3.fc36.x86_64: The nftables python module provides an interface to libnftables via ctypes.

python3-newt-0.52.21-12.lbn36.x86_64: The python3-newt package contains the Python 3 bindings for the newt library providing a python API for creating text mode interfaces.

python3-networkx-3.4.2-1.lbn36.noarch: NetworkX is a Python 3 package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

python3-netifaces-0.11.0-2.fc36.x86_64: This package provides a cross platform API for getting address information from network interfaces.

python3-netaddr-shell-0.8.0-8.fc36.noarch: An IPython-based shell environment for the netaddr library

python3-netaddr-1.2.1-1.lbn36.noarch: A Python library for representing and manipulating network addresses. Provides support for: Layer 3 addresses IPv4 and IPv6 addresses, subnets, masks, prefixes iterating, slicing, sorting, summarizing and classifying IP networks dealing with various ranges formats (CIDR, arbitrary ranges and globs, nmap) set based operations (unions, intersections etc) over IP addresses and subnets parsing a large variety of different formats and notations looking up IANA IP block information generating DNS reverse lookups supernetting and subnetting Layer 2 addresses representation and manipulation MAC addresses and EUI-64 identifiers looking up IEEE organisational information (OUI, IAB) generating derived IPv6 addresses Documentation: https:/netaddr.readthedocs.io/en/latest/ Source code repository: https:/github.com/netaddr/netaddr/ PyPI page: https:/pypi.org/project/netaddr/ Share and enjoy!

python3-nest-asyncio-1.6.0-5.lbn36.noarch: By design asyncio does not allow its event loop to be nested. This presents a practical problem: When in an environment where the event loop is already running it's impossible to run tasks and wait for the result. Trying to do so will give the error "RuntimeError: This event loop is already running". The issue pops up in various environments, such as web servers, GUI applications and in Jupyter notebooks. This module patches asyncio to allow nested use of asyncio.run and loop.run_until_complete.

python3-nbformat-5.9.2-1.lbn36.noarch: This package contains the base implementation of the Jupyter Notebook format, and Python APIs for working with notebooks.

python3-nbconvert-7.16.4-1.lbn36.noarch: nbconvert Jupyter Notebook Conversion The nbconvert tool, jupyter nbconvert, converts notebooks to various other formats via Jinja templates. The nbconvert tool allows you to convert an .ipynb notebook file into various static formats including: HTML LaTeX PDF Reveal JS Markdown (md) ReStructured Text (rst) executable script Usage From the command line, use nbconvert to convert a Jupyter notebook (input) to a a different format (output). The basic command structure is: $ jupyter nbconvert --to <output format> <input notebook> where <output format> is the desired output format and <input notebook> is the filename of the Jupyter notebook. Example: Convert a notebook to HTML Convert Jupyter notebook file, mynotebook.ipynb, to HTML using: $ jupyter nbconvert --to html mynotebook.ipynb This command creates an HTML output file named mynotebook.html. Dev Install Check if pandoc is installed (pandoc --version); if needed, install: sudo apt-get install pandoc Or brew install pandoc I

python3-nbclient-0.5.10-2.fc36.noarch: NBClient, a client library for programmatic notebook execution, is a tool for running Jupyter Notebooks in different execution contexts. NBClient was spun out of nbconvert (formerly ExecutePreprocessor). NBClient lets you execute notebooks.

python3-mypy_extensions-1.0.0-4.lbn36.noarch: The "mypy_extensions" module defines experimental extensions to the standard "typing" module that are supported by the mypy typechecker. Python 3 version.

python3-munkres-1.1.2-11.fc36.noarch: The Munkres module provides an implementation of the Munkres algorithm (also called the Hungarian algorithm or the Kuhn-Munkres algorithm). The algorithm models an assignment problem as an NxM cost matrix, where each element represents the cost of assigning the ith worker to the jth job, and it figures out the least-cost solution, choosing a single item from each row and column in the matrix, such that no row and no column are used more than once.

python3-multipart-0.2.5-3.lbn36.noarch: This module provides a parser for the multipart/form-data format. It can read from a file, a socket or a WSGI environment. The parser can be used to replace cgi.FieldStorage to work around its limitations.


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