Getting started
Contents
Getting started#
This mini-tutorial will help you set up a working Python
environment on a Linux system.
This will allow you to work with other peoples Python
tools and start writing your own scripts.
Some concepts#
First, let’s go over a few important concepts.
What is Python
?#
Python
is a widely used general-purpose programming language, known for its emphasis on code readability.
How do I get Python
?#
Python
comes preinstalled on Mac OS, most Linux distributions and is easily installed on Windows.
Warning
The system often depends on the preinstalled Python
installation for various operations.
Modifying the system installation is not recommended.
Instead of using the preinstalled version of Python
, it is recommended to work using what are called
virtual environments.
Setting up and managing virtual environments, including package management, is the focus of this mini-tutorial.
What is a Python
package?#
When you write code, you may want to use some parts other people have written, rather than rewriting everything from scratch. If you reference and external code in your code, we say that your code depends on that external code.
In Python
, people often package up their code and make it available on the
Python Package Index for others to download and use in their programs.
Setting up your environment#
Installing miniconda3
#
In this tutorial, we will use a lightweight installation of conda called Miniconda3 to manage our software environments.
Note
conda
is not Python
specific, it can be used as a general software environment solution.
This is useful if you use software which has many specific dependencies and requires activation prior to usage.
Follow the installation instructions here.
Creating a new conda environment#
The following command will create a new conda
environment called py38
with Python
version 3.8.
conda create --name py38 python=3.8
This environment can be activated with conda activate py38
and deactivated with conda deactivate
.
Installing packages#
Once your environment is active, any packages you install will be installed into this environment, isolated
from your system Python
installation and other conda
environments.
Packages can be installed with either conda install <package-name>
or pip install <package-name>
.