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python3-semantic_version-2.10.0-1.lbn36.noarch: Introduction This small python library provides a few tools to handle SemVer_ in Python. It follows strictly the 2.0.0 version of the SemVer scheme. :target:

python3-selenium-4.18.1-1.lbn36.noarch: The selenium package is used automate web browser interaction from Python. Several browsers/drivers are supported (Firefox, Chrome, Internet Explorer, PhantomJS), as well as the Remote protocol.

python3-secretstorage-3.3.1-4.fc36.noarch: This module provides a way for securely storing passwords and other secrets. It uses D-Bus Secret Service API that is supported by GNOME Keyring (>= 2.30) and KSecretsService. The main classes provided are secretstorage.Item, representing a secret item (that has a label, a secret and some attributes) and secretstorage.Collection, a place items are stored in. SecretStorage supports most of the functions provided by Secret Service, including creating and deleting items and collections, editing items, locking and unlocking collections (asynchronous unlocking is also supported).

python3-scipy-1.10.1-2.lbn36.x86_64: Scipy is open-source software for mathematics, science, and engineering. The core library is NumPy which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers.

python3-scikit-learn-1.0.2-2.fc36.x86_64: Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts.

python3-scikit-image-0.19.3-1.lbn36.x86_64: The scikit-image SciKit (toolkit for SciPy) extends scipy.ndimage to provide a versatile set of image processing routines.

python3-savitar-4.13.1-1.fc36.x86_64: Savitar is a C++ implementation of 3mf loading with SIP Python bindings. 3mf is a 3D printing file format. The Python bindings.

python3-s3transfer-0.11.2-1.lbn36.noarch: S3transfer is a Python library for managing Amazon S3 transfers. Python 3 version.

python3-rx-1.6.1-1.lbn36.noarch: is a library for composing asynchronous and event-based programs using observable collections and LINQ-style query operators in Python.

python3-rwproperty-1.0-1.lbn36.noarch: Read & write properties :Author: Philipp von Weitershausen :Email: philikon@philikon.de :License: Zope Public License, v2.1Motivation -Using method decorators and descriptors like property, we can easily create computed attributes: >>> class JamesBrown(object): ... @property ... def feel(self): ... return self._feelAn attribute like this cannot be written, though. You would have to do...

python3-ruamel-yaml-clib-0.2.7-1.lbn36.x86_64: It is the C based reader/scanner and emitter for ruamel.yaml.

python3-ruamel-yaml-0.17.21-1.lbn36.x86_64: ruamel.yaml is a YAML 1.2 loader/dumper package for Python. It is a derivative of Kirill Simonov’s PyYAML 3.11

python3-rtree-0.9.7-4.fc36.noarch: Rtree is a ctypes Python wrapper of the spatialindex library, that provides a number of advanced spatial indexing features for the spatially curious Python user. These features include: -Nearest neighbor search -Intersection search -Multi-dimensional indexes -Clustered indexes (store Python pickles directly with index entries) -Bulk loading -Deletion -Disk serialization -Custom storage implementation (to implement spatial indexing in ZODB, for example)

python3-rsa-4.9-6.lbn36.noarch: Python-RSA is a pure-Python RSA implementation. It supports encryption and decryption, signing and verifying signatures, and key generation according to PKCS#1 version 1.5. It can be used as a Python library as well as on the command-line.

python3-rq-1.16.2-1.lbn36.noarch: RQ (Redis Queue) is a simple Python library for queueing jobs and processing them in the background with workers. It is backed by Redis and it is designed to have a low barrier to entry. It should be integrated in your web stack easily. RQ requires Redis >= 3.0.0. Full documentation can be found here. Support RQ If you find RQ useful, please consider supporting this project via Tidelift. Getting started First, run a Redis server, of course: $ redis-server To put jobs on queues, you don't have to do anything special, just define your typically lengthy or blocking function: import requests def count_words_at_url(url): """Just an example function that's called async.""" resp = requests.get(url) return len(resp.text.split()) You do use the excellent requests package, don't you? Then, create an RQ queue: from redis import Redis from rq import Queue queue = Queue(connection=Redis()) And enqueue the function call: from my_module import count_words_at_url job = queue.enq

python3-rpmfile-2.0.0-1.lbn36.noarch: rpmfile[![Build Status]( [![Actions Status]( [![PyPI version]( for inspecting RPM files in python. This module is modeled after the [tarfile]( module. Installconsole $ python -m pip install -U rpmfile If you want to use rpmfile with zstd compressed rpms, you'll need to install

python3-rpmautospec-0.7.2-2.lbn36.noarch: A package and CLI tool to generate RPM release fields and changelogs.

python3-rpm-spec-0.11-1.lbn36.noarch: [![pytest status](https://github.com/bkircher/python-rpm- spec/workflows/tests/badge.svg)](https://github.com/bkircher/python-rpm- spec/actions) [![PyPI version](https://badge.fury.io/py/python-rpm- spec.svg)](https://badge.fury.io/py/python-rpm-spec) python-rpm-spec is a Python library for parsing RPM spec files. *tl;dr* If you want to quickly parse a spec file on the...

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