Modified items

All recently modified items, latest first.

python3-linecache2-1.0.0-32.fc36.noarch: A backport of linecache to older supported Pythons.

python3-libsss_nss_idmap-2.9.3-1.lbn36.x86_64: The python3-libsss_nss_idmap contains the bindings so that libsss_nss_idmap can be used by Python applications.

python3-librepo-1.19.0-1.lbn36.x86_64: Python 3 bindings for the librepo library.

python3-libipa_hbac-2.9.3-1.lbn36.x86_64: The python3-libipa_hbac contains the bindings so that libipa_hbac can be used by Python applications.

python3-libcst-0.4.9-1.lbn36.x86_64: LibCST parses Python 3.0 -> 3.11 source code as a CST tree that keeps all formatting details (comments, whitespaces, parentheses, etc). It’s useful for building automated refactoring (codemod) applications and linters. LibCST creates a compromise between an Abstract Syntax Tree (AST) and a traditional Concrete Syntax Tree (CST). By carefully reorganizing and naming node types and fields, we’ve created a lossless CST that looks and feels like an AST.

python3-lazy-object-proxy-1.7.1-2.fc36.x86_64: A fast and thorough lazy object proxy.

python3-kubernetes-24.2.0-4.fc36.noarch: Python client for the kubernetes API.

python3-kfp-server-api-1.8.5-1.lbn36.noarch: This file contains REST API specification for Kubeflow Pipelines. The file is autogenerated from the swagger definition. noqa: E501

python3-jupyter-sphinx-0.3.2-3.fc36.noarch: Jupyter-Sphinx enables running code embedded in Sphinx documentation and embedding output of that code into the resulting document. It has support for rich output such as images and even Jupyter interactive widgets.

python3-jupyter-polymake-0.16-18.20180129.7049940.fc36.noarch: This package contains a Jupyter kernel for polymake.

python3-jupyter-packaging-0.12.3-1.lbn36.noarch: Jupyter Packaging Tools to help build and install Jupyter Python packages that require a pre-build step that may include JavaScript build steps. Install pip install jupyter-packaging Usage There are three ways to use jupyter-packaging in another package. In general, you should not depend on jupyter_packaging as a runtime dependency, only as a build dependency. As a Build Requirement Use a pyproject.toml file as outlined in pep-518. An example: [build-system] requires = ["jupyter_packaging>=0.10,<2"] build-backend = "setuptools.build_meta" Below is an example setup.py using the above config. It assumes the rest of your metadata is in setup.cfg. We wrap the import in a try/catch to allow the file to be run without jupyter_packaging so that python setup.py can be run directly when not building. from setuptools import setup try: from jupyter_packaging import wrap_installers, npm_builder builder = npm_builder() cmdclass = wrap_installers(pre_develop=builder, pre_dist=builder)

python3-jupyter-kernel-test-0.6.0-1.lbn36.noarch: jupyter_kernel_test is a tool for testing Jupyter kernels. It tests kernels for successful code execution and conformance with the Jupyter Messaging Protocol (currently 5.0). Install Install it with pip (python3.4 or greater required): pip3 install jupyter_kernel_test Usage To use it, you need to write a (python) unittest file containing code samples in the relevant language which test various parts of the messaging protocol. A short example is given below, and you can also refer to the test_ipykernel.py and test_irkernel.py files for complete examples. Some parts of the messaging protocol are relevant only to the browser-based notebook (rich display) or console interfaces (code completeness, history searching). Only parts of the spec for which you provide code samples are tested. Run this file directly using python, or use nosetests or py.test to find and run it. Example import unittest import jupyter_kernel_test class MyKernelTests(jupyter_kernel_test.KernelTests):

python3-jupyter-kernel-singular-0.9.9-8.fc36.noarch: This package contains a Jupyter kernel for Singular, to enable using Jupyter as the front end for Singular.

python3-jupyter-console-6.6.3-1.lbn36.noarch: Jupyter Console A terminal-based console frontend for Jupyter kernels. This code is based on the single-process IPython terminal. Install with pip: pip install jupyter-console Install with conda: conda install -c conda-forge jupyter_console Start: jupyter console Help: jupyter console -h Jupyter Console allows for console-based interaction with non-python Jupyter kernels such as IJulia, IRKernel. To start the console with a particular kernel, ask for it by name:: jupyter console --kernel=julia-0.4 A list of available kernels can be seen with:: jupyter kernelspec list Release build: $ pip install pep517 $ python -m pep517.build . Resources Project Jupyter website Documentation for Jupyter Console [PDF] Documentation for Project Jupyter [PDF] Issues Technical support - Jupyter Google Group About the Jupyter Development Team The Jupyter Development Team is the set of all contributors to the Jupyter project. This includes all of the Jupyter subprojects. The core team that coordi

python3-jupyter-c-kernel-1.2.2-14.fc36.noarch: Minimalistic C kernel for Jupyter

python3-jsonpath-ng-1.7.0-1.lbn36.noarch: Python JSONPath Next-Generation A final implementation of JSONPath for Python that aims to be standard compliant, including arithmetic and binary comparison operators, as defined in the original JSONPath proposal_.

python3-jsondate-0.1.2-1.lbn36.noarch: ======== jsondate ======== Sick of rewriting the same JSON datetime handling code for each project? ``jsondate`` is a drop-in replacement for Python's standard ``json`` library that adds sensible handling of ``datetime`` and ``date`` objects. ``jsondate`` uses ISO8601 for encoding ``datetime`` objects and the date-specific part of ISO6801 for encoding ``date`` objects. Example:: ...


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