How To Create Virtual Environment And Install Specific Python Version

How To Set Up A Virtual Environment In Python Using Pip – Data Science
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How To Create Virtual Environment And Install Specific Python Version

Creating a virtual environment can be a great way to come up with a self-contained Python installation that you can use for projects or trying out new experiments. If you’re looking to get the most out your Python experience and want to deploy applications written in this language, then using a virtual environment is the way to go.

What is a Virtual Environment?

A virtual environment is an isolated python installation that lets you manage dependencies without affecting any other project that may be installed on your system. For example, if you want to try out a new package and not worry about it changing things outside that particular project, you can create a virtual environment. Virtual environments let you pick specific versions of packages, manage dependencies, and keep your system’s main Python installation untouched.

Picture of a virtual environment

What are the Benefits?

The main benefit of virtual environments is that it makes it easier to manage the dependencies of different projects. You can be sure that the packages that you need for a project are all in the same place and nothing will conflict with each other. It makes it much easier to experiment with new packages without worrying about it impacting other projects. There are lots of other benefits of virtual environment such as being able to name the virtual environment, testing code in different Python versions, and much more.

Preparation

To get started, you’ll want to make sure that you have a copy of Python installed on your system. You can easily download Python from the official website, or you may already have it installed. Once this is done, you’ll want to check what version of Python you have installed as it will be important when creating the virtual environment.

Installation

Once you have checked your Python version you can use the venv module to create the virtual environment. This is a standard module in Python 3.4 and later, so you don’t need to install it. Run the following command to create the virtual environment:

python -m venv /path/to/new/virtual/environment

Where the path is the name of the virtual environment that you want to create and the version of Python that you want to use (eg: python3.7). After it is done creating the environment, you will be ready to activate it. To do this, use the following command:

source /path/to/new/virtual/environment/bin/activate

This will activate your newly created virtual environment. You can tell if it is active by looking for the (venv) that appears in your command line. To deactivate the virtual environment, run the command deactivate.

Using the Virtual Environment

Once the virtual environment is active, you can install packages and use them in your project without worrying about them affecting other projects. To install a package in your virtual environment, you can use the command pip install <package-name>. This will then install the desired packages in your virtual environment.

If you ever want to check what packages you have in the virtual environment, you can use the pip freeze command. This will list all the packages in the virtual environment and the version numbers.

So, if you’re looking for a way to keep all your Python projects neatly organized and maintain a clean Python installation, then creating a virtual environment is a great way to do this. Virtual environments allow you to have different Python installations for different projects, so that you can test out packages without worrying about them affecting other projects. Plus, it is easy to set up and use and lets you maintain your system’s Python installation untouched.

‼️Video - How To Create Virtual Environment And Install Specific Python Version 👇

I recently wrote a scientific computing module in Python, which could not interface with Fortran subroutines, and I assumed that they would all have to be re-written using Python numerical packages like Numpy etc. I was wrong. It turns out that I could have had all the libraries compiled into my code, so as to make them available for import, without any trouble. The solution is a framework called moon-buggy.,Guests often ask about how to use our Python-based tools. We get the most questions about Virtual Environments. In this article we’re going to discuss how to manage Python virtual environments, why we recommend doing so, and what happens when you don’t. -

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Installing Python 3 on a Mac is pretty simple, as long as you know what you’re doing. Here’s a detailed look at the process, from start to finish. - Christopher Hendon and Siddharth Nitta were involved with the Association for Computing Machinery's Student Chapter at the University of California, Berkeley's ACM@Berkeley Collegiate Programming Contest team, which placed in the Top 3 at the world finals seven times, including 3rd in 2013,If you’ve been programming for any amount of time, you’ve probably heard the term ‘virtual environment’ before. But even if you’re a seasoned polyglot programmer, you may not have been using them. I’m writing this article to help you understand why they’re so important, and to help you get started using them in your projects.
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