A Guide to Using Python Venv (including conda, poetry, pipenv and uv)

Conda is a popular package and environment management tool widely used in scientific computing and data science, particularly for handling Python projects. Here's a basic guide on how to use Conda.

Conda

Conda can be installed as part of the Anaconda or Miniconda distributions:

• Anaconda: Includes Conda, Python, and a large collection of pre-installed packages suited for scientific applications.
• Miniconda: Includes only Conda and Python, allowing for a lighter installation with the flexibility to install only the packages you need.

Installation Steps

1. Download the installer:
   • For Anaconda, visit Anaconda Downloads
   • For Miniconda, visit Miniconda Downloads
2. Run the installer:
   • On Windows, double-click the downloaded .exe file.
   • On macOS and Linux, open a terminal and run the downloaded .sh file by typing bash <filename>.sh.
3. Follow the on-screen instructions to complete the installation.

Managing Environments

Conda allows you to create isolated environments to manage different project dependencies separately.

Creating an Environment

conda create --name myenv python=3.8

Creating from yaml file:

conda env create -f environment.yml

Deleting an Environment

conda env remove --name gpt

Activating an Environment

conda activate myenv

Deactivating an Environment

conda deactivate

Managing Packages

Conda can install, update, and remove packages within an environment.

Installing a Package

conda install numpy

Listing Installed Packages

conda list

Updating a Package

conda update numpy

Removing a Package

conda remove numpy

FAQ

Additional Resources

• Conda Official Documentation
• Conda Cheat Sheet

Using Conda effectively can simplify package management and help maintain reproducibility of scientific computations. Explore the official documentation for more in-depth information.