README.md

Packages and Virtual environment

Virtual environments are an important component of Python project. They provide an isolated, self-contained environment in which project-specific libraries can be installed without affecting the system-wide installation of Python. This ensures that different projects can have their own packages, dependencies, versions and configurations, avoiding potential conflicts.

Such packages and dependencies can be installed using a package installer called pip, which will be presented below. Thus, thanks to these components it is possible to create a project with specific packages/libraries and isolate them from the rest of the system.

venv

venv is a module built into Python 3 that allows you to create lightweight virtual environments effortlessly. To create a virtual environment using venv, navigate to your project directory in the terminal and run the following commands:

python3 -m venv env

This creates a virtual environment named env in your project directory. Activate the virtual environment using:

On Windows:

.\venv\Scripts\activate

On macOS/Linux:

source venv/bin/activate

Once activated, the terminal prompt will change, indicating that you are now working within the virtual environment. When you finish working on the current project or need to run a different project, remember to deactivate the virtual environment by simply typing deactivate in the terminal.

deactivate

Pip

Once the virtual environment is activated, the libraries needed for the project must be installed via the pip package installer. Please note: such libraries work only when the virtual environment is activated. pip is the default package installer for Python. It manages Python packages and dependencies from PyPI. PyPI is a repository of software packages developed and maintained by the Python community. pip interacts with PyPI to download and install packages.

Installing a Package:

pip install package_name

Uninstalling a Package:

pip uninstall package_name

Freezing

If we need to run the project on a machine other than the current one, it is important to export the used package information so that we can reinstall and reset everything on a new machine. In this regard, we can freeze the environment.

Freezing an environment means recording the specific versions of software libraries and dependencies used in a project. This ensures that the project can be recreated at any time in the future with the exact same configuration, minimizing the risk of compatibility issues. When multiple developers or teams work on a project, they must have a consistent development environment. Freezing the environment allows everyone to work with the same set of dependencies, reducing the possibility of errors or discrepancies between different configurations.

Freeze the environment at the end of the coding session, in case new dependencies have been installed, and put in requirements.txt.

pip freeze > requirements.txt

A requirements.txt file is a common convention in Python projects used to specify the dependencies required for the project to run. It contains a list of Python packages along with their version numbers. This file is used by package management tools (pip) to install the necessary dependencies for the project.

# requirements.txt
numpy==1.21.3
pandas==1.3.4
matplotlib==3.4.3

To reconfigure the same environment in the new machine, after create a new virtual environment with venv, installs packages listed in a requirements file.

pip install -r requirements.txt

Deactivate virtual environment:

deactivate

Remove virtual environment:

rm -rf venv/

The official guide can be found here

Conda

An alternative to create a virtual enviroment is to use conda that allows you to choose and use a python version instead of exploiting the current installed one

Installation of miniconda

1. Create a directory to install minicaonda in

mkdir -p ~/miniconda3

2. Download latest miniconda version

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh

3. Run the install script

bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3

4. Delete the intall script

rm -rf ~/miniconda3/miniconda.sh

5. Add a conda initialize to your bash and zsh

~/miniconda3/bin/conda init bash
~/miniconda3/bin/conda init zsh

6. Verify the installaton

conda list

Create a conda virtual enviroment:

conda create -n envname python=x.x anaconda

Activate and initialize a conda virtual enviroment:

conda activate envname
pip install -r requirements.txt

Deactivate virtual environment:

conda deactivate

Remove virtual environment:

conda remove --name envname --all

The official guide can be found here