A virtual environment in Python is an isolated environment where you can have a specific version of Python and its packages, separate from the global Python installed on your system. This can be very useful when you have different projects requiring different versions of Python and its packages. Now, let's walk you through the process of creating a virtual environment in Python: You can create a virtual environment using `venv`, which is a standard module in Python 3. It does not come with Python 2.x versions. Here are the steps to follow: 1. First, open a terminal. 2. Use the `cd` command to navigate to the directory where you want to create the virtual environment. For example: ```bash cd /path/to/your/project ``` 3. Run the following command to create a new virtual environment. Replace `myenv` with whatever name you want to give to your virtual environment. ```bash python3 -m venv myenv ``` This command will create a new directory called `myenv` (or whatever name you provided) that contains the virtual environment. This includes a fresh copy of Python interpreter, the Pip package manager, standard python library and other supporting files. To start using this virtual environment, you need to activate it: - On macOS/Linux, you can do this by running this command: ```bash source myenv/bin/activate ``` - On Windows, use this command: ```bash .\myenv\Scripts\activate ``` Once your virtual environment is activated, the name of your virtual environment will appear on the left side of the terminal prompt. This is an indication that the environment is active. Now you can install packages into the isolated environment. For example, to install the latest version of django, you can type `pip install django`. To stop using the virtual environment and return to the normal environment, you simply need to deactivate it by running: ```bash deactivate ``` The name of the virtual environment should now be gone from the terminal prompt indicating that you are no longer in an activated environment. Remember, a virtual environment is a tool to keep the dependencies required by different projects in separate places by creating isolated Python environments for them. This is one of the many ways to manage dependencies in Python and it's a great way to ensure that your Python environment stays clean and manageable.