Python virtual environments are essential for managing dependencies and avoiding conflicts between projects. This guide will walk you through the process of creating and activating a virtual environment in Python.
Step 1: Navigate to Your Project Directory
Open your terminal and navigate to the directory where you want to set up your Python virtual environment. You can do this using the cd command:
cd /path/to/your/project
Step 2: Create the Virtual Environment
In the terminal, enter the following command to create a virtual environment. The name .venv is commonly used, but you can choose any name you prefer:
python3 -m venv .venv
Step 3: Define Your Project Dependencies
Create a text file named requirements.txt in your project directory. In this file, list the Python libraries you want to install for your project. For example:
flask
requests
numpy
Step 4: Activate the Virtual Environment
To start using the virtual environment, you need to activate it. Use the following command based on your operating system:
For Windows:
.\.venv\Scripts\activate
For macOS/Linux:
source .venv/bin/activate
Once activated, your terminal prompt will change to indicate that you are now working within the virtual environment.
Step 5: Upgrade pip
It’s a good practice to ensure that pip is up-to-date. Run the following command to upgrade pip:
.venv\Scripts\python.exe -m pip install --upgrade pip
Step 6: Install Project Dependencies
Finally, install the Python libraries listed in your requirements.txt file by running:
pip install -r requirements.txt
Top comments (4)
What do you find to be advantageous of Python venv over, for example, conda?
Using Python venv forces you to create a new env for every new project? While with conda, it is way easier to re-use envs, I feel.
Conda is all you need
How would that work using conda approach
How would that work using conda approach?