{"id":823,"date":"2022-08-05T11:16:00","date_gmt":"2022-08-05T05:46:00","guid":{"rendered":"https:\/\/geekpython.in\/?p=823"},"modified":"2023-08-15T16:40:08","modified_gmt":"2023-08-15T11:10:08","slug":"how-to-create-virtual-environments-using-venv-in-python","status":"publish","type":"post","link":"https:\/\/geekpython.in\/how-to-create-virtual-environments-using-venv-in-python","title":{"rendered":"How To Create Virtual Environments Using venv In Python"},"content":{"rendered":"\n

Have you ever needed an isolated environment<\/strong> apart from your primary Python environment to manage the different versions of dependencies<\/strong> for your project?<\/p>\n\n\n\n

That is where the virtual environment<\/strong> comes into play.<\/p>\n\n\n\n

A virtual environment is a tool used to manage the dependencies required by the different projects separately by creating isolated virtual environments for them.<\/em><\/strong> This is used by most Python developers often.<\/p>\n\n\n\n

In this tutorial, we’ll learn how to use Python’s venv<\/code> module<\/a> to create and manage the virtual environments<\/a> for our project separately. Each environment created will be capable of managing different versions of the dependency and Python versions too.<\/p>\n\n\n\n

In the last, we’ll also see other options like virtualenv<\/code> and conda<\/code> to create virtual environments.<\/p>\n\n\n\n

<\/a>What is a virtual environment?<\/h1>\n\n\n\n

Well, till now, you’ve got a pretty good idea of a virtual environment.<\/p>\n\n\n\n

A virtual environment is a self-contained directory tree<\/strong> containing the specific Python version installed and some additional third-party applications.<\/p>\n\n\n\n

<\/a>Why do we need a virtual environment?<\/h1>\n\n\n\n

Why do we use a virtual environment when we don’t know why we need it?<\/p>\n\n\n\n

Suppose you are working on two Python projects based on web scraping<\/a>. Let’s say application_X<\/code> and application_Y<\/code> where application_X<\/em> uses beautifulsoup4=4.11.1<\/em><\/strong> and application_Y<\/em> uses beautifulsoup4=4.10.0<\/em><\/strong>. In this situation, the dependencies will conflict, and installing either version 4.11.1<\/em> or 4.10.0<\/em> will leave one of the applications unable to run.<\/p>\n\n\n\n

For such situations, virtual environments can be very helpful in managing the different dependencies for both projects.<\/p>\n\n\n\n

It is a good practice to use virtual environments<\/strong> for your project so that your project doesn’t conflict with one another regarding dependencies and the Python version.<\/p>\n\n\n\n

<\/a>How does a virtual environment work?<\/h1>\n\n\n\n

By default, the external packages we install using pip<\/em><\/strong> in our Python base environment rest inside a folder called site-packages\/<\/em><\/strong><\/p>\n\n\n\n

.\n\u2514\u2500\u2500 Python\/\n    \u251c\u2500\u2500 include\n    \u251c\u2500\u2500 Lib\/\n    \u2502   \u2514\u2500\u2500 site-packages\/\n    \u2502       \u251c\u2500\u2500 asgiref-3.5.2.dist-info \n    \u2502       \u251c\u2500\u2500 beautifulsoup4-4.11.1.dist-info\n    \u2502       \u251c\u2500\u2500 certifi-2022.6.15.dist-info\n    \u2502       \u251c\u2500\u2500 Django-4.0.6.dist-info\n    \u2502       \u251c\u2500\u2500 django\n    \u2502       \u251c\u2500\u2500 Flask-2.1.2.dist-info\n    \u2502       \u2514\u2500\u2500 flask\n    \u251c\u2500\u2500 libs\n    \u251c\u2500\u2500 Scripts\n    \u251c\u2500\u2500 tcl\n    \u2514\u2500\u2500 Tools<\/pre><\/div>\n\n\n\n
When we create a virtual environment using venv<\/code>, it re-creates the file and folder structure of the standard Python installation on our OS.<\/p>\n\n\n\n
Python also copies the folder structure or symlinks<\/a> into that folder, the Python executable with which we’ve created our virtual environment.<\/p>\n\n\n\n
A symlink is a symbolic link<\/strong> that points to another file and folder in our computer or a connected file system. So basically, when we create our virtual environment, that virtual environment points to the file and folder of the standard Python installation to create its own environment<\/strong>.<\/p>\n\n\n\n
The folder structure looks like this when we create our virtual environment.<\/p>\n\n\n\n
D:\n\u2502   pyvenv.cfg\n\u2502\n\u251c\u2500\u2500\u2500Include\n\u251c\u2500\u2500\u2500Lib\n\u2502   \u2514\u2500\u2500\u2500site-packages\n\u2502       \u2502   distutils-precedence.pth\n\u2502       \u251c\u2500\u2500\u2500pip\n\u2502       \u251c\u2500\u2500\u2500pip-22.0.4.dist-info\n\u2502       \u251c\u2500\u2500\u2500pkg_resources\n\u2502       \u251c\u2500\u2500\u2500setuptools\n\u2502       \u251c\u2500\u2500\u2500setuptools-58.1.0.dist-info\n\u2502       \u2514\u2500\u2500\u2500_distutils_hack                  \n\u2502\n\u2514\u2500\u2500\u2500Scripts\n        activate\n        activate.bat\n        Activate.ps1\n        deactivate.bat\n        pip.exe\n        pip3.10.exe\n        pip3.exe\n        python.exe\n        pythonw.exe<\/pre><\/div>\n\n\n\n
To list the directory tree, follow the steps below:<\/strong><\/p>\n\n\n\n
    \n
  1. cd<\/em><\/strong> into the virtual environment directory in your terminal.<\/li>\n<\/ol>\n\n\n\n
    PS> cd your\/virtual\/environment\/dir<\/pre><\/div>\n\n\n\n
      \n
    1. Then run the following command in your terminal<\/li>\n<\/ol>\n\n\n\n
      PS> tree \/F<\/pre><\/div>\n\n\n\n
      The above command will generate a directory tree with all the files. However, the tree generated by this command will be very long.<\/p>\n\n\n\n
      <\/a>Setting up a virtual environment<\/h1>\n\n\n\n
      Remember our two applications, application_X<\/em><\/strong>, and application_Y<\/em><\/strong>, both use different versions of Beautiful Soup v4.11.1<\/em><\/strong> and v4.10.0<\/em><\/strong>, respectively. If we try to install v4.10.0<\/em><\/strong> for application_Y<\/em><\/strong> and then try to install v4.11.1<\/em><\/strong> for application_X<\/em><\/strong> globally then v4.10.0<\/em><\/strong> will be overwritten.<\/p>\n\n\n\n
      PS> python -m pip install beautifulsoup4==4.10.0\nPS> python -m pip list\n\nPackage            Version\n------------------ -----------\nbeautifulsoup4     4.10.0<\/pre><\/div>\n\n\n\n
      PS> python -m pip install beautifulsoup4==4.11.1\nPS> python -m pip list\n\nPackage            Version\n------------------ -----------\nbeautifulsoup4     4.11.1<\/pre><\/div>\n\n\n\n
      But this won’t be a problem with the virtual environment if we create it for both of the applications.<\/p>\n\n\n\n
      <\/a>Creating a virtual environment<\/h3>\n\n\n\n
      To create a virtual environment, we’ll use Python’s venv<\/code> module.<\/p>\n\n\n\n
      PS> python -m venv my_venv<\/pre><\/div>\n\n\n\n
      Like the above command, we can create two separate virtual environments for our application_X<\/em> and application_Y<\/em>.<\/p>\n\n\n\n
      <\/a>Creating multiple virtual environments at once<\/h3>\n\n\n\n
      PS> python -m venv application_X application_Y<\/pre><\/div>\n\n\n\n
      The above command will create two separate virtual environments in the same directory. We can also specify different paths for our virtual environments<\/strong>.<\/p>\n\n\n\n
      PS> python -m venv application_X your\/full\/path\/to\/directory\/application_Y<\/pre><\/div>\n\n\n\n
      For example, I am creating an application_A in the root directory and another application in the sub-directory named app_b_path<\/code>.<\/p>\n\n\n\n
      Then the command will be –<\/p>\n\n\n\n
      PS> python -m venv application_A D:\\SACHIN\\Pycharm\\Virtual_environment\\app_b_path\\application_B<\/pre><\/div>\n\n\n\n
      Please look at the folder structure of the virtual environments we have created.<\/p>\n\n\n\n
      \"Virtual<\/figure>\n\n\n\n
      <\/a>Activating a virtual environment<\/h3>\n\n\n\n
      Great, our application has its virtual environment, but to start using it first, we must activate it.<\/p>\n\n\n\n
      The simple command for activating any virtual environment is to execute a script that comes with the installation.<\/p>\n\n\n\n
      PS> Scripts\\activate\n\n(application_A) PS><\/pre><\/div>\n\n\n\n
      Note: Before executing the above command, make sure to change the directory to the virtual environment.<\/strong><\/p>\n\n\n\n
      Or we can run the command <virtual_environment_directory\/Scripts\/activate<\/em><\/strong>\\> from the root directory.<\/p>\n\n\n\n
      PS> application_X\\Scripts\\activate\n\n(application_X) PS><\/pre><\/div>\n\n\n\n
      <\/a>Installing packages into it<\/h3>\n\n\n\n
      Now that we have created two separate virtual environments for our application_X<\/em><\/strong> and application_Y<\/em><\/strong>, we can install the external dependencies we need for our project.<\/p>\n\n\n\n
      Activating application_X<\/em><\/strong> and installing v4.11.1<\/em><\/strong> of beautifulsoup4<\/code><\/p>\n\n\n\n
      PS> application_X\\Scripts\\activate\n\n(application_X) PS> pip install beautifulsoup4==4.11.1\n\n(application_X) PS> pip list\n\nPackage        Version\n-------------- -----------\nbeautifulsoup4 4.11.1\npip            22.0.4\nsetuptools     58.1.0\nsoupsieve      2.3.2<\/pre><\/div>\n\n\n\n
      Activating application_Y<\/em><\/strong> and installing v4.10.0<\/em><\/strong> of beautifulsoup4<\/code><\/p>\n\n\n\n
      PS> application_Y\\Scripts\\activate\n\n(application_Y) PS> pip install beautifulsoup4==4.10.0\n\n(application_Y) PS> pip list\n\nPackage        Version\n-------------- -----------\nbeautifulsoup4 4.10.0\npip            22.0.4\nsetuptools     58.1.0\nsoupsieve      2.3.2<\/pre><\/div>\n\n\n\n
      We used pip<\/em><\/strong> to install the dependency just like we do globally in our standard Python Installation. Since we created and activated the virtual environments, pip will install the dependency in an isolated location.<\/p>\n\n\n\n
      Now you can understand how we can manage different versions of dependencies and avoid system pollution or conflict between external packages.<\/p>\n\n\n\n
      <\/a>Deactivate the virtual environment<\/h3>\n\n\n\n
      Once you are done with the virtual environment, you must deactivate it.<\/p>\n\n\n\n
      (application_Y) PS> deactivate\n\nPS><\/pre><\/div>\n\n\n\n
      After running the deactivate<\/code> command, your command prompt will return to its normal state. It means that you’ve successfully exited your virtual environment, and if you continue using Python or pip<\/code> in your command prompt, you’ll directly interact with globally installed Python.<\/p>\n\n\n\n
      <\/a>Other popular options<\/h1>\n\n\n\n
      Python’s venv<\/code> module is a great tool to work with virtual environments, and its main advantage is that it comes preinstalled with Python. But there are other popular options also available.<\/p>\n\n\n\n
        \n
      1. Virtualenv<\/li>\n\n\n\n
      2. Conda<\/li>\n<\/ol>\n\n\n\n
        <\/a>Virtualenv<\/h2>\n\n\n\n
        It is a tool for creating isolated Python environments. Virtualenv allows some great features that a typical in-built venv<\/code> module doesn’t provide.<\/p>\n\n\n\n