Python For Linux And Devops Engineers

A comprehensive course to empower Linux and DevOps engineers with Python for automation and orchestration

What you'll learn

Configure Python environments on Linux systems, using editors like VSCode or Vim, and manage virtual environments effectively

Write Python scripts using fundamental syntax, data types, control structures, and data structures like lists and dictionaries

Automate system tasks with Python, including file handling, text processing with regular expressions, and OS interactions

Apply Python in DevOps workflows to automate Git operations, manage CI/CD pipelines, and interact with tools like Ansible, Docker, and Kubernetes

Requirements

Basic Knowledge of Linux: Familiarity with Linux operating systems and command-line interface

Understanding of DevOps Concepts: Basic awareness of DevOps practices and tools

Prior Programming Experience (Beneficial but Not Required): Some experience with programming concepts can be helpful

Access to a Linux System: A computer running a Linux distribution to install Python and other tools

Text Editor or IDE: Tools like VSCode or Vim installed for writing and editing code

Internet Connection: For downloading software, accessing online resources, and working with cloud services

Description

Welcome to our Python course tailored for Linux and DevOps engineers. In this course, we'll start by setting up your Python environment on Linux systems, exploring different text editors and IDEs like VSCode and Vim, and managing virtual environments.We'll cover the basics of Python, including its syntax, data types, and how to perform input and output operations. You'll learn about control structures like conditional statements and loops, as well as fundamental data structures such as lists, tuples, sets, and dictionaries.Functions and modules are essential parts of Python programming. We'll learn how to define functions, work with different types of arguments, and organize code using modules and packages. We'll also delve into file handling, exception management, and interacting with the operating system using Python's built-in modules.Automation is a key aspect of DevOps, so we'll focus on writing scripts to automate system tasks, process text with regular expressions, and parse configuration files. Networking topics will include basic socket programming and working with web services and APIs.We'll explore how to interact with databases, perform CRUD operations, and use Object-Relational Mappers like SQLAlchemy. The course also integrates DevOps tools, showing how to automate Git operations, manage CI/CD pipelines, and work with infrastructure as code using Ansible and cloud SDKs.Containerization and orchestration topics will cover automating Docker and interacting with Kubernetes using Python. We'll emphasize secure coding practices, testing, and debugging to ensure your code is reliable and safe.In the advanced section, we'll touch on concurrency, parallelism, and packaging your Python applications for distribution. Finally, you'll apply what you've learned in a capstone project, developing an automation tool or script relevant to your work.We hope this course provides you with practical skills to enhance your efficiency and encourages continuous learning in your DevOps journey.

Overview

Section 1: Course Overview

Lecture 1 Introduction to the Course

Lecture 2 Objectives and learning outcomes

Lecture 3 Importance of Python in Linux and DevOps

Lecture 4 Overview of tools and technologies to be used

Section 2: Section 1: Getting Started with Python

Lecture 5 Basic syntax and semantics

Lecture 6 Code Structure

Lecture 7 Variables, data types, and type casting

Lecture 8 Operators and expressions

Lecture 9 Lab: Basics

Section 3: Section 2: Control Flow and Data Structures

Lecture 10 Conditional statements (if, elif, else)

Lecture 11 Looping Constructs (for, while)

Lecture 12 Lab: Looping Constructs (for, while)

Lecture 13 Loop Control Statements (break, continue, pass)

Lecture 14 Lab: Loop Control Statements (break, continue, pass)

Lecture 15 Lists, Tuples, Sets, and Dictionaries

Lecture 16 Lab: Lists, Tuples, Sets, and Dictionaries

Lecture 17 List Comprehensions and Generator Expressions

Lecture 18 Lab: List Comprehensions and Generator Expressions

Lecture 19 Working with Collections and Iterables

Lecture 20 Lab: Working with Collections and Iterables

Section 4: Section 3: Functions and Modules

Lecture 21 Introduction to Functions in Python

Lecture 22 Lab: Converting Celsius to Fahrenheit

Lecture 23 Default Arguments and Variable Length Arguments

Lecture 24 Lab: Create a Function to Accept Variable Arguments & Calculate Their Average

Lecture 25 Introduction to Lambda Functions

Lecture 26 Lab: Use Lambda Functions to Filter out Odd Numbers From a List of Integers

Lecture 27 Importing built-in Modules

Lecture 28 Lab: Using the time Module to Measure Function Execution Time

Lecture 29 Creating Custom Modules and Packages

Lecture 30 Lab: Creating a Custom Module for File Operations

Lecture 31 Understanding Scope and Namespaces

Lecture 32 Lab: Experimenting with global and nonlocal in Nested Functions

Section 5: File Handling and Exception Management

Lecture 33 Reading from and Writing to files

Lecture 34 Lab: Python File Operations

Lecture 35 Working with Directories Using os and shutil Modules

Lecture 36 Lab: Python Directory Management

Lecture 37 Parsing Configuration Files (INI, JSON and YAML)

Lecture 38 Lab: Parsing Configuration Files

Lecture 39 Exception Handling in Python

Lecture 40 Lab: Exception Handling in Python

Section 6: Working with the Operating System

Lecture 41 Environment Variables

Lecture 42 Lab: Environment Variables

Lecture 43 File and Directory Operations

Lecture 44 Lab: File and Directory Operations

Lecture 45 System Specific Parameters and Functions

This course is tailored for Linux and DevOps engineers who are eager to enhance their automation and scripting capabilities using Python. It's ideal for system administrators, network engineers, and DevOps professionals who have a basic understanding of Linux operating systems and command-line interfaces. Whether you're new to programming or looking to expand your existing skill set, this course offers practical insights into leveraging Python for automating system tasks, managing infrastructure, and integrating with DevOps tools like Git, CI/CD pipelines, Ansible, Docker, and Kubernetes. If you're committed to improving efficiency, embracing automation, and advancing your career in the DevOps field, this course will provide valuable knowledge and hands-on experience