Modules and Packages

Virtual Environments

Python’s strength lies in its vast ecosystem of packages. However, managing dependencies between different projects can become a nightmare without proper tools. This is where virtual environments shine.

A virtual environment is an isolated space where you can install packages without affecting your system’s global Python installation or other projects. This prevents conflicts and ensures that each project has its own specific set of dependencies.

Creating a Virtual Environment:

The most common way is using venv (Python 3.3+):

python3 -m venv .venv  # Creates a virtual environment named '.venv' in the current directory

Other tools exist, like conda (often used with Anaconda):

conda create -n myenv python=3.9  # Creates a conda environment named 'myenv' with Python 3.9

Activating a Virtual Environment:

After creation, you need to activate it to use it:

• venv:

  • Linux/macOS: source .venv/bin/activate
  • Windows: .venv\Scripts\activate

• conda:

  • conda activate myenv

Installing Packages:

Once activated, use pip to install packages within the environment:

pip install requests numpy pandas

These packages will only be available within this specific environment.

Deactivating a Virtual Environment:

To exit the environment and return to your system’s default Python:

deactivate

Package Management with Pip (Conda Environments)