Lets go straight into the commands you will write for creating a virtual environment using anaconda Things in anaconda is a little bit different, after installing anaconda from their official website, you will be able to do whatever you want with the command line tools you will have.īy default, anaconda creates a virtual environment on its own, so once you have anaconda you will find something in the anaconda prompt which is (base) Whenever you want to exit from the virtual environment you created, you can type deactivate, and like nothing happened at all. Voila, Here is your virtual environment is ready and up to work, you can do whatever you want, it will be your own sandbox or playground. ![]() Then you will go to the directory created which is your virtual environment, go to a folder called Scripts and then type in your command line Once you created the directory for your project, you will create a new environment using the (venv) library by writing this commands If you didn't find the venv library in the list, you can simply type this command will provide a list of all the libraries you installed on the main environment of python. Python and Anaconda provides you a tool that you may install using (pip) which is called virtual environments or (venv), it creates a new and clean environment for you, and you can start installing your own libraries that you will use to avoid any kind of conflict that may happen between the libraries, so right now we have two environments, the first one the base one created with python during installation and the other one is the one we created for our project.įirst you will need to install python 3.X (X stands for whatever the version you are going install), and after this you will need to write in the terminal or the command line ![]() In such cases we should use the virtual environments, but what is virtual environments? ![]() Installing to much libraries may make a conflict between the dependencies the project may not work properly. Let me tell you something you already know, python is one of the easiest languages for development, and it’s pretty obvious that we can develop a lot of libraries using it also for specific use, something like Pandas or Numpy which are widely used in Data Science and machine learning domain are developed in python, and guess what, you can develop your own but that’s another topic we may discuss later.įirst of all, when you want to start a project using python, you should determine what kind of the project is and based on the diagrams, UMLs, Flowcharts and product owner opinion, you will start writing your own code, but here is the point. It’s quite clear that most of the developers who use python in their development cycle prefer using virtual environments to install their libraries and dependencies, But why we should create a virtual environment for the project we will work on?
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