Step 1: Configuring Proxy Settings
This step is crucial for allowing the system to access the internet to download packages.

export http_proxy="http://username:password@172.16.0.1:3128"
export https_proxy="http://username:password@172.16.0.1:3128"

Please note that password has to be entered in http url-encode format only.
For example, a password like p@ssword should be entered as p%40ssword.

Persistent Settings: To ensure these settings are active every time you log in, add these lines to your ~/.bashrc file.

Step 2: Load Anaconda Module

module avail anaconda
Choose the version you want and load it. 

module load anaconda3/2024.10

Step 3: Create a Conda Environment
Creating a separate environment for each project prevents conflicts between different package versions.

conda create --name myenv python=3.10
Replace myenv with a descriptive name for your environment.

Specify the Python version you need, such as 3.8, 3.9, or 3.10.

Step 4: Activate the Environment

You must activate the environment to make it the default for your current shell session. This allows you to use its specific Python version and installed packages.

conda activate myenv
Your command prompt will change to show the environment name, like (myenv) [user@host ~]$.

Step 5: Install Libraries and Packages
Now that your environment is active, you can install the packages you need using conda.

conda install numpy pandas matplotlib
Simply list the names of the packages you want to install.

Conda will automatically resolve and install any dependencies.

Step 6: Using Pip
It is sometimes necessary to use pip, Python's native package manager, to install packages that aren't available through Conda's channels.

Always ensure your Conda environment is active before using pip.

pip install package1 package2

Step 7: List Installed Packages
To check what packages are installed in your current environment, use the conda list command. This is useful for verifying versions and dependencies.

conda list

Step 8: Deactivate the Environment
When you are finished working on your project, you should deactivate the environment to return to the default base environment.

conda deactivate