Virtualenv is a tool that creates an isolated environment separate from other projects. In this instance, we will be installing different Python versions, including their dependencies. Creating a virtual environment allows us to work on a Python project without affecting other projects that also use Python. It will utilize Python’s core files on the global environment to run, thus saving you disk space while providing the freedom to use different Python versions for separate apps or projects.
In this tutorial, we will consider how to enable both Python 2 and Python 3 for use on CentOS 8. In earlier distributions of CentOS, an unversioned Python command was available by default.
When the CentOS installation was complete, it was possible to drop into a Python shell by simply running the “python” command in a terminal.
Paradoxically, CentOS 8 does not have an unversioned Python command by default. This begs the question, why? RedHat states that this choice is by design “to avoid locking users into a specific version of Python.” Currently, RedHat 8 utilizes Python 3.6 implicitly by default, although Python 2.7 is additionally provided to maintain existing software.
In this tutorial, we are going to take a look at how to get started with TensorFlow on CentOS. We will be covering two methods. First, we will take a look at installing TensorFlow in a Python virtual environment via the Python package manager pip. After that, we will walk through installing TensorFlow via the Anaconda package manager. Finally, we will cover building a TensorFlow pip package from source.
In this tutorial, we are going to cover how to set up a Python virtual environment on CentOS. A Python virtual environment makes it possible to install Python packages into a discreet Python ecosystem that is entirely separate from your system’s default Python framework. This means that you do not have to worry about overwriting the installation of any current packages that might be defaulted to the existing version of Python on your system.
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This article outlines the process of configuring a Dedicated server for Python 3 web applications with Apache 2.4 using mod_wsgi.
What is mod_wsgi?
Mod_wsgi is an Apache module that allows Python web applications to function on a server. This module provides a web framework for Flask, Django, and other Python based frameworks to operate within a clustered server environment on a group of servers.
Flask is a micro web framework for Python that allows unlimited possibilities to the structure and format for building powerful web applications. This article demonstrates how to get started with Flask using Python 3.7 inside of a virtual environment.