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#Anaconda python 3.7 download linux install#

Historically, easy_install (part of python-setuptools) was used to install packages distributed as Eggs.

See the Python Packaging User Guide for the official best practices for package management. pipx and Conda integrate environment management into their workflows. Alternatively, pip install -user can be used to install packages into the user scheme instead of /usr. When installing packages using pip, it is recommended to use a virtual environment to prevent conflicts with system packages in /usr. Miniconda - A lightweight alternative to Anaconda which installs the package manager but does not install scientific computing packages by default.You can use Conda to install packages from the Anaconda repositories. Anaconda - An open source package management system and environment management system, originally created for Python programs.You can use pipx to install packages from the Python Package Index and other indexes. Focused on packages that can be run from the command line directly as applications. pipx - Closely related to pip, but creates, for the user running it, an isolated environment for each application and its associated packages, preventing conflicts with system packages.You can use pip to install packages from the Python Package Index and other indexes. pip(1) - The official package installer for Python.This is the preferred way to install system-wide packages. Official repositories and AUR - A large number of popular packages are available in the Arch repositories.There are several ways to install Python packages on Arch Linux: ptpython - An advanced Python REPL built with prompt-toolkit.Jupyter - A web-based computation application powered by IPython.IPython - A powerful interactive Python shell.bpython - A fancy interface for the Python interpreter.The python package includes an interactive Python shell/REPL which can be launched with the python command. Others are historically notable but are no longer maintained due to improvements in the most popular implementations. Some, such as Stackless, Pyston and Cinder are used internally at large technology companies. IronPython - An implementation of the Python programming language which is tightly integrated with.It includes a small subset of the Python standard library and is optimized to run on microcontrollers and in constrained environments. micropython - Python for microcontrollers.It can be used to embed Python scripting into Java programs or use Java libraries in Python programs.

Jython - An implementation of the Python language written in Java.

It has speed and memory usage advantages compared to CPython.

PyPy - A Python implementation written in Python.

Implementations available on Arch Linux include: These implementations are usually based on older versions of Python and are not fully compatible with CPython. However, there are also other implementations available. The python package installs CPython, the reference implementation of Python. You can also download the source for any release on the page. searching for python37 for Python 3.7 modules. You can also use pyenv to easily install and switch between multiple versions of Python.Įxtra modules/libraries for old versions of Python may be found on the AUR by searching for python, e.g. python3.7 for Python 3.7, allowing multiple versions to coexist on a system. See Status of Python versions.Įach of these packages installs a distinct binary named after the version number, e.g. Warning: Python versions before 3.7 have reached end of life and are unmaintained.

Python 2.7: python2 AUR ( unmaintained).

Python 3.6: python36 AUR ( unmaintained).

Previous and future versions of Python are available via the AUR, and may be useful for old applications that do not run on the current version, for programs intended to run on other versions, or just for curiosity: Finally, Python is portable: it runs on many Unix variants including Linux and macOS, and on Windows. It is also usable as an extension language for applications that need a programmable interface. It has interfaces to many system calls and libraries, as well as to various window systems, and is extensible in C or C++. Python combines remarkable power with very clear syntax. It supports multiple programming paradigms beyond object-oriented programming, such as procedural and functional programming. It incorporates modules, exceptions, dynamic typing, very high level dynamic data types, and classes. Python is an interpreted, interactive, object-oriented programming language.