Tags
Language
Tags
June 2025
Su Mo Tu We Th Fr Sa
1 2 3 4 5 6 7
8 9 10 11 12 13 14
15 16 17 18 19 20 21
22 23 24 25 26 27 28
29 30 1 2 3 4 5
    Attention❗ To save your time, in order to download anything on this site, you must be registered 👉 HERE. If you do not have a registration yet, it is better to do it right away. ✌

    ( • )( • ) ( ͡⚆ ͜ʖ ͡⚆ ) (‿ˠ‿)
    SpicyMags.xyz

    Python Mastery: Devops, Automation, And Real-World Use Cases

    Posted By: ELK1nG
    Python Mastery: Devops, Automation, And Real-World Use Cases

    Python Mastery: Devops, Automation, And Real-World Use Cases
    Published 10/2024
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 2.23 GB | Duration: 9h 0m

    From Coding Fundamentals to Cloud Automation, GitHub Integration, CI/CD Automation with Jenkins and Game Development

    What you'll learn

    Python coding practice

    About Data Types in Python

    Regular Expression (regex) in Python

    How to identify and apply keywords in code

    How to declare and assign values to variables.

    The purpose and function of the return statement in functions.

    Python Functions: Definition and Usage

    Utilizing Modules in Function Design

    Organizing Your Code Using Python Packages

    The use of the sys module to access command line arguments

    The different types of operators in Python, including arithmetic, comparison, logical, and assignment operators.

    DevOps Use Cases with if..else..elif

    For/While Loops in Python: Syntax and Usage

    Real-time Use Case: Lists and Exception Handling in Python

    Python Script for Handling Exceptions Using Try Statements

    Integrating Python with GitHub Through the GitHub API

    Cloning a GitHub Repository with Python

    Performing operations on various AWS services like S3, EC2 using Boto3 Python Module

    Launching an EC2 Instance using Boto3 Python Module

    CI/CD Automation with Jenkins and Python

    Integrate GitHub Webhooks With Jenkins

    Develop Games in Python with PyCharm and ChatGPT

    Requirements

    Basic Computer Skills: Familiarity with using a computer and navigating the internet.

    No Prior Programming Experience Required: This course is designed for beginners, so no previous programming knowledge is necessary.

    Basic Knowledge of DevOps is required

    Description

    Python for DevOps means using Python to make DevOps tasks easier and more efficient. DevOps is all about automating tasks like building, testing, and deploying software quickly, as well as managing servers and infrastructure. Python is great for this because it’s simple to learn, and it has many tools and libraries that help automate these tasks. For example, you can use Python to automatically create servers, manage cloud services, and set up continuous integration and delivery (CI/CD) pipelines. Python helps DevOps teams work faster and more effectively by reducing manual work and making processes smoother.Course Outline:Section1: Introduction-> Introduction-> An overview of Python-> About Shell Scripting-> Python vs. Shell Scripting-> When to Use Python vs. Shell ScriptingSection2: How to Begin Practicing Python Coding-> Begin Python Coding Practice-> Visual Studio Code - Python Coding Practice-> PyCharm - IDEs-> Codespaces - Online Coding PlatformSection3: Python Data Types-> About Data Types in Python-> Lab - String Data Type-> Lab - Integer Data Type-> Lab - Float Data Type-> Lab - len(), Length of a string-> Lab - String upper(), lower()-> Lab - String replace()-> Lab - String split()-> Lab - Print specific object in split()-> About List in Python-> Lab - List Data Type-> Lab - Add and Modify in a List Data Type (Mutable)-> About Tuples in Python-> Lab - Tuples in Python-> About Sets in Python-> Lab - Sets in Python-> Dictionary in Python-> Lab - Dictionary in Python-> Use Cases in DevOps-> Boolean Data Types-> Lab - Boolean in Python-> Coding Exercise 1:Create a Python script to add two integers-> Coding Exercise 2:Create a python script to perform operation of floating-point-> Coding Exercise 3:Write a python script to determine the length of a string-> Coding Exercise 4:Create a python script to convert a string to uppercase and lowercase-> Coding Exercise 5:Create a Simple python Script to replace a substring within a string-> Coding Exercise 6:Create a Simple python script to Split the text of a string-> Coding Exercise 7:Create a python script to define a Variable and assign it a list of five integersSection4: Regular Expression (regex) in Python-> Overview of Regular Expressions in Python-> Lab - Using re. match() to Match Patterns at the Start of a String-> Lab - Using re. search() to Find Matches Anywhere in a String-> Lab - Using re. findall() to Search for All Matches in a String-> Regex Use Cases from a DevOps Perspective-> Coding Exercise 8:Regular Expression in python-> Section5: Mastering Keywords in Python-> Overview of Keywords in Python-> Common Python keywords-> Mastering Control Flow Keywords - if, else, for, and break-> Lab: Mastering Control Flow Keywords - continue, def, return, class, import etc.Section6: Working with Variables in Python-> Overview of Variables with Example-> Lab: Working with Float Variables in Python-> Lab: Defining Lists as Variables in Python-> Lab: Working with Dictionary Variables in Python-> Python Variables: Local vs Global Scope-> Lab: Working with Local Variables in Python-> Lab: Working with Global Variables in PythonSection7: Return Statement in Python-> Return Statement: An Overview with Syntax-> Lab: Creating Functions That Return Values-> Lab: Functions That Return Multiple Values-> Lab: Function for Identifying Even and Odd ValuesSection8: Python Functions: Definition and Usage-> Introduction to Functions in Python-> Advantages of functions in Python-> Lab: Functions with Parameters-> Lab: Functions with Return Value-> Lab: Designing Functions for Basic Arithmetic Operations-> Comparing Scripts: Using Functions vs. Not Using FunctionsSection9: Utilizing Modules in Function Design-> Introduction to Python Modules-> An Overview of Built-in Modules-> An Overview of User-defined Modules-> Lab: Essential Built-in Modules in Python-> Lab: OS and Math Modules-> Lab: Building Your Own ModulesSection 10: Python Packages: Organizing Your Code-> Introduction to Python Packages-> Key Concepts of Packages-> Advantages of Using Packages-> Lab: Creating Package Structures and Modules-> Importing Modules for Easier Access using __init__. py-> Creating a Main Python File to Utilize Your Package-> Importing Functions from a PackageSection 11: Command Line Arguments in Python-> Command Line Arguments with Practical Examples-> Lab: Script to Add Two Numbers (No Command Line Arguments)-> Lab: Working with sys. argv for Command Line Arguments-> Lab: Passing Multiple Arguments to Python Scripts-> Lab: Pass Arguments to Add Two Numbers-> Lab: Conditional Arithmetic via Script Arguments-> Lab: Conditional Arithmetic Using Script ArgumentsSection 12: Operators in Python: Concepts and Examples-> The Basics of Arithmetic Operators in Python-> Lab: Exploring Comparison (Relational) Operators-> Lab: Comparison Operators (=, >, >=, ==)-> Logical Operators: and, or, not-> Lab: Using 'and' , 'or' for Logical Operations-> Lab: Using 'not' for Logical Operations-> Assignment Operators in Python-> Lab: Understanding Different Assignment Operators-> Membership Operators: 'in' and 'not in'-> Lab: Using 'not in' Membership Operators-> Operators in DevOps: Practical Use Cases-> Use Cases for Operators in the DevOps WorkflowSection 13: Conditional Statements in Python-> Understanding 'if' statement in Python-> Understanding 'else'..'elif' statement in Python-> Lab: Implementing if..else Statements-> Lab: DevOps Use Cases with if..else..elifSection 14: Understanding Loops in Python-> For Loops in Python: Syntax and Usage-> While Loops in Python: Syntax and Usage-> Lab: Implementing For Loops-> Lab: Printing Ranges and Strings with For Loops-> Lab: Implementing Infinite While Loops-> Lab: Exploring Break Statements in PythonSection 15: Real-time Use Case: Lists and Exception Handling in Python-> Introduction to the Real-Time Project-> Lab: User Input for List Creation-> Lab: Understanding split function text.split()-> Lab: Identify modules and their functions-> Lab: Utilize a for loop to list files-> Exception Handling with Try Statement-> Lab: Python Script for Handling Exceptions Using Try Statements-> Lab: Handling Error - FileNotFoundError-> Lab: Handling Known Error - PermissionErrorSection 16: Integrating Python with GitHub-> Integrating Python with GitHub Through the GitHub API-> Lab: Install PyGithub and Generate a GitHub Access Token-> Lab: Retrieve User Login and Public Repos with Python-> Lab: Retrieve GitHub Account Repository List-> Lab: Create a New Repository with PythonSection 17: Cloning a GitHub Repository with Python-> Clone a Repository Using the Subprocess Module-> Lab: Clone a Repository with the Subprocess Module-> Lab: Using GitPython Library-> Lab: Handle Git Errors with Exception HandlingSection 18: Boto3 Python Module-> Introduction to the Boto3 Python Module-> Lab: Install Boto3 and Create an AWS User Account-> Lab: Configure GitHub Access from Codespaces via AWS CLI-> Lab: List All Buckets with Boto3-1-> Lab: List All Buckets with Boto3-2-> Lab: List All Buckets with Boto3-3-> Lab: Upload a File to a Bucket Using Boto3-> Lab: Download a File to a Bucket Using Boto3Section 19: Launching an EC2 Instance using Boto3 Python Module-> Project Overview-> Setting Up a User Account in AWS with IAM-> Set Up AWS CLI in Codespaces-> Begin Python Script: Import Boto3-> Include EC2 Attributes in Python Script-> Add Tag Specifications in Python Script-> Debug the Python Script Before Execution-> Access the EC2 Instance Launched via Python Script-> Update the Python Script to Add 20GB EBS Volume-> Run Python Script to Confirm EBS Volume-> Update Python Script to Include UserData-> Update Python Script to Include Apache Package-> Run the Revised Python Script and Validate-> Access the Apache ServerSection 20: CI/CD Automation with Jenkins and Python-> Project Overview-> Set Up a GitHub Repository for Your Project-> Write the Source Code in Python and Push to GitHub Repository-> Provision a Jenkins Server Instance in AWS-> Connect to the Jenkins Server and Install Java-> Install the Jenkins Package on the Server-> Set Up Jenkins Configuration-> Install Necessary Plugins on the Jenkins Server-> Add GitHub Credentials to the Jenkins Server-> First Stage of the Pipeline: Checkout the Project-> Build the Job-> Add a Stage for Installing Python Dependencies-> Add a Stage to Execute the Python Script-> Setting Up a User Account in AWS with IAM-> Create Access Keys for Jenkins Credentials-> Set Up Access Keys in Jenkins Pipeline-> Export AWS Credentials in Jenkins Pipeline-> Build the Job and Verify EC2 Instance Creation in AWS-> Access the Web Server Using URLSection 21: Integrate GitHub Webhooks With Jenkins-> Setup GitHub Webhooks in Jenkins-> GitHub hook trigger for GITScm polling-> Add Jenkins Webhook to GitHub Repository-> Test the Webhook by Editing the Python ScriptSection 22: Develop Games in Python with PyCharm and ChatGPT

    Overview

    Section 1: Introduction

    Lecture 1 Introduction

    Lecture 2 An overview of Python

    Lecture 3 About Shell Scripting

    Lecture 4 Python vs. Shell Scripting

    Lecture 5 When to Use Python vs. Shell Scripting

    Section 2: How to Begin Practicing Python Coding

    Lecture 6 Begin Python Coding Practice

    Lecture 7 Visual Studio Code - Python Coding Practice

    Lecture 8 PyCharm - IDEs

    Lecture 9 Codespaces - Online Coding Platform

    Section 3: Python Data Types

    Lecture 10 About Data Types in Python

    Lecture 11 Lab - String Data Type

    Lecture 12 Lab - Integer Data Type

    Lecture 13 Lab - Float Data Type

    Lecture 14 Lab - len(), Length of a string

    Lecture 15 Lab - String upper(), lower()

    Lecture 16 Lab - String replace()

    Lecture 17 Lab - String split()

    Lecture 18 Lab - Print specific object in split()

    Lecture 19 About List in Python

    Lecture 20 Lab - List Data Type

    Lecture 21 Lab - Add and Modify in a List Data Type (Mutable)

    Lecture 22 About Tuples in Python

    Lecture 23 Lab - Tuples in Python

    Lecture 24 About Sets in Python

    Lecture 25 Lab - Sets in Python

    Lecture 26 Dictionary in Python

    Lecture 27 Lab - Dictionary in Python

    Lecture 28 Use Cases in DevOps

    Lecture 29 Boolean Data Types

    Lecture 30 Lab - Boolean in Python

    Section 4: Regular Expression (regex) in Python

    Lecture 31 Overview of Regular Expressions in Python

    Lecture 32 Lab - Using re.match() to Match Patterns at the Start of a String

    Lecture 33 Lab - Using re.search() to Find Matches Anywhere in a String

    Lecture 34 Lab - Using re.findall() to Search for All Matches in a String

    Lecture 35 Regex Use Cases from a DevOps Perspective

    Section 5: Mastering Keywords in Python

    Lecture 36 Overview of Keywords in Python

    Lecture 37 Common Python keywords

    Lecture 38 Mastering Control Flow Keywords - if, else, for, and break

    Lecture 39 Lab: Mastering Control Flow Keywords - continue, def, return, class, import etc.

    Section 6: Working with Variables in Python

    Lecture 40 Overview of Variables with Example

    Lecture 41 Lab: Working with Float Variables in Python

    Lecture 42 Lab: Defining Lists as Variables in Python

    Lecture 43 Lab: Working with Dictionary Variables in Python

    Lecture 44 Python Variables: Local vs Global Scope

    Lecture 45 Lab: Working with Local Variables in Python

    Lecture 46 Lab: Working with Global Variables in Python

    Section 7: Return Statement in Python

    Lecture 47 Return Statement: An Overview with Syntax

    Lecture 48 Lab: Creating Functions That Return Values

    Lecture 49 Lab: Functions That Return Multiple Values

    Lecture 50 Lab: Function for Identifying Even and Odd Values

    Section 8: Python Functions: Definition and Usage

    Lecture 51 Introduction to Functions in Python

    Lecture 52 Advantages of functions in Python

    Lecture 53 Lab: Functions with Parameters

    Lecture 54 Lab: Functions with Return Value

    Lecture 55 Lab: Designing Functions for Basic Arithmetic Operations

    Lecture 56 Comparing Scripts: Using Functions vs. Not Using Functions

    Section 9: Utilizing Modules in Function Design

    Lecture 57 Introduction to Python Modules

    Lecture 58 An Overview of Built-in Modules

    Lecture 59 An Overview of User-defined Modules

    Lecture 60 Lab: Essential Built-in Modules in Python

    Lecture 61 Lab: OS and Math Modules

    Lecture 62 Lab: Building Your Own Modules

    Section 10: Python Packages: Organizing Your Code

    Lecture 63 Introduction to Python Packages

    Lecture 64 Key Concepts of Packages

    Lecture 65 Advantages of Using Packages

    Lecture 66 Lab: Creating Package Structures and Modules

    Lecture 67 Importing Modules for Easier Access using __init__.py

    Lecture 68 Creating a Main Python File to Utilize Your Package

    Lecture 69 Importing Functions from a Package

    Section 11: Command Line Arguments in Python

    Lecture 70 Command Line Arguments with Practical Examples

    Lecture 71 Lab: Script to Add Two Numbers (No Command Line Arguments)

    Lecture 72 Lab: Working with sys.argv for Command Line Arguments

    Lecture 73 Lab: Passing Multiple Arguments to Python Scripts

    Lecture 74 Lab: Pass Arguments to Add Two Numbers

    Lecture 75 Lab: Conditional Arithmetic via Script Arguments

    Lecture 76 Lab: Conditional Arithmetic Using Script Arguments

    Section 12: Operators in Python: Concepts and Examples

    Lecture 77 The Basics of Arithmetic Operators in Python

    Lecture 78 Lab: Exploring Comparison (Relational) Operators

    Lecture 79 Lab: Comparison Operators (=, >, >=, ==)

    Lecture 80 Logical Operators: and, or, not

    Lecture 81 Lab: Using 'and' , 'or' for Logical Operations

    Lecture 82 Lab: Using 'not' for Logical Operations

    Lecture 83 Assignment Operators in Python

    Lecture 84 Lab: Understanding Different Assignment Operators

    Lecture 85 Membership Operators: 'in' and 'not in'

    Lecture 86 Lab: Using 'not in' Membership Operators

    Lecture 87 Operators in DevOps: Practical Use Cases

    Lecture 88 Use Cases for Operators in the DevOps Workflow

    Section 13: Conditional Statements in Python

    Lecture 89 Understanding 'if' statement in Python

    Lecture 90 Understanding 'else'..'elif' statement in Python

    Lecture 91 Lab: Implementing if..else Statements

    Lecture 92 Lab: DevOps Use Cases with if..else..elif

    Section 14: Understanding Loops in Python

    Lecture 93 For Loops in Python: Syntax and Usage

    Lecture 94 While Loops in Python: Syntax and Usage

    Lecture 95 Lab: Implementing For Loops

    Lecture 96 Lab: Printing Ranges and Strings with For Loops

    Lecture 97 Lab: Implementing Infinite While Loops

    Lecture 98 Lab: Exploring Break Statements in Python

    Section 15: Real-time Use Case: Lists and Exception Handling in Python

    Lecture 99 Introduction to the Real-Time Project

    Lecture 100 Lab: User Input for List Creation

    Lecture 101 Lab: Understanding split function text.split()

    Lecture 102 Lab: Identify modules and their functions

    Lecture 103 Lab: Utilize a for loop to list files

    Lecture 104 Exception Handling with Try Statement

    Lecture 105 Lab: Python Script for Handling Exceptions Using Try Statements

    Lecture 106 Lab: Handling Error - FileNotFoundError

    Lecture 107 Lab: Handling Known Error - PermissionError

    Section 16: Integrating Python with GitHub

    Lecture 108 Integrating Python with GitHub Through the GitHub API

    Lecture 109 Lab: Install PyGithub and Generate a GitHub Access Token

    Lecture 110 Lab: Retrieve User Login and Public Repos with Python

    Lecture 111 Lab: Retrieve GitHub Account Repository List

    Lecture 112 Lab: Create a New Repository with Python

    Section 17: Cloning a GitHub Repository with Python

    Lecture 113 Clone a Repository Using the Subprocess Module

    Lecture 114 Lab: Clone a Repository with the Subprocess Module

    Lecture 115 Lab: Using GitPython Library

    Lecture 116 Lab: Handle Git Errors with Exception Handling

    Section 18: Boto3 Python Module

    Lecture 117 Introduction to the Boto3 Python Module

    Lecture 118 Lab: Install Boto3 and Create an AWS User Account

    Lecture 119 Lab: Configure GitHub Access from Codespaces via AWS CLI

    Lecture 120 Lab: List All Buckets with Boto3-1

    Lecture 121 Lab: List All Buckets with Boto3-2

    Lecture 122 Lab: List All Buckets with Boto3-3

    Lecture 123 Lab: Upload a File to a Bucket Using Boto3

    Lecture 124 Lab: Download a File to a Bucket Using Boto3

    Section 19: Launch EC2 Instance with Boto3 Python Module

    Lecture 125 Project Overview

    Lecture 126 Setting Up a User Account in AWS with IAM

    Lecture 127 Set Up AWS CLI in Codespaces

    Lecture 128 Begin Python Script: Import Boto3

    Lecture 129 Include EC2 Attributes in Python Script

    Lecture 130 Add Tag Specifications in Python Script

    Lecture 131 Debug the Python Script Before Execution

    Lecture 132 Access the EC2 Instance Launched via Python Script

    Lecture 133 Update the Python Script to Add 20GB EBS Volume

    Lecture 134 Run Python Script to Confirm EBS Volume

    Lecture 135 Update Python Script to Include UserData

    Lecture 136 Update Python Script to Include Apache Package

    Lecture 137 Run the Revised Python Script and Validate

    Lecture 138 Access the Apache Server

    Section 20: CI/CD Automation with Jenkins and Python

    Lecture 139 Project Overview

    Lecture 140 Set Up a GitHub Repository for Your Project

    Lecture 141 Write the Source Code in Python and Push to GitHub Repository

    Lecture 142 Provision a Jenkins Server Instance in AWS

    Lecture 143 Connect to the Jenkins Server and Install Java

    Lecture 144 Install the Jenkins Package on the Server

    Lecture 145 Set Up Jenkins Configuration

    Lecture 146 Install Necessary Plugins on the Jenkins Server

    Lecture 147 Add GitHub Credentials to the Jenkins Server

    Lecture 148 First Stage of the Pipeline: Checkout the Project

    Lecture 149 Build the Job

    Lecture 150 Add a Stage for Installing Python Dependencies

    Lecture 151 Add a Stage to Execute the Python Script

    Lecture 152 Setting Up a User Account in AWS with IAM

    Lecture 153 Create Access Keys for Jenkins Credentials

    Lecture 154 Set Up Access Keys in Jenkins Pipeline

    Lecture 155 Export AWS Credentials in Jenkins Pipeline

    Lecture 156 Build the Job and Verify EC2 Instance Creation in AWS

    Lecture 157 Access the Web Server Using URL

    Section 21: Integrate GitHub Webhooks with Jenkins

    Lecture 158 Setup GitHub Webhooks in Jenkins

    Lecture 159 GitHub hook trigger for GITScm polling

    Lecture 160 Add Jenkins Webhook to GitHub Repository

    Lecture 161 Test the Webhook by Editing the Python Script

    Lecture 162 Last Lecture

    Individuals with little or no prior programming experience who want to learn Python from scratch.,DevOps Professionals: Anyone interested in automation, cloud computing, and using Python for DevOps practices.,Students and Professionals: Anyone seeking to enhance their resume or career prospects by adding Python programming to their skill set.,Overall, this course is suitable for anyone eager to learn Python and apply it in real-world scenarios.