Search Results for "linux packages"

Conda is an open-source package management system and environment management system that runs on Windows, macOS, and Linux. Conda quickly installs, runs, and updates packages and their dependencies. Conda easily creates, saves, loads, and switches between environments on your local computer. It was created for Python programs but it can package and distribute software for any language. Conda as a package manager helps you find and install packages. If you need a package that requires a different version of Python, you do not need to switch to a different environment manager because conda is also an environment manager. ...

pipx is a tool to help you install and run end-user applications written in Python. It's roughly similar to macOS's brew, JavaScript's npx, and Linux's apt. It's closely related to pip. In fact, it uses pip, but is focused on installing and managing Python packages that can be run from the command line directly as applications. pip is a general-purpose package installer for both libraries and apps with no environment isolation. pipx is made specifically for application installation, as it...

Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks.

Molecule project is designed to aid in the development and testing of Ansible roles. Molecule provides support for testing with multiple instances, operating systems and distributions, virtualization providers, test frameworks and testing scenarios. Molecule encourages an approach that results in consistently developed roles that are well-written, easily understood and maintained. Molecule supports only the latest two major versions of Ansible (N/N-1), meaning that if the latest version is...

The 'pysourceinfo' package provides source information on Python runtime objects based on 'inspect', 'sys', 'os', and 'imp'. The covered objects include packages, modules, functions, methods, scripts, and classes by two views: - File System View - packages, modules, and linenumbers - based on files and paths - Runtime Object View - callables, classes, and containers - based on in-memory RTTI / introspection The supported platforms are: - Linux, BSD, Unix, OS-X, Cygwin, and Windows - Python2, Python3 - CPython, PyPy Object addresses within modules - Object Identifier OID - and the display of the runtime call flow are supported by 'PyStackInfo'. ...