It is easier to manager AWS S3 buckets and objects from CLI. This tutorial explains the basics of how to manage S3 buckets and its objects using aws s3 cli using the following examples:

For quick reference, here are the commands. For details on how these commands work, read the rest of the tutorial.
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Sets are basically collection of certain items that are unordered. There is no specific order in which they are stored. In Python sets are same, but there are few differences with basic sets.

• The elements in python sets are unique, there can’t be duplicate items in python sets. If duplicate items entered, it will be ignored and final set will always contain unique elements.
• Python sets are mutable. But, its elements are immutable. Once entered items cannot be modified.
• Python set’s item cannot be accessed using indexes. There is no index attached to set items.

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What is Elasticsearch? In simple terms, we could possibly say elastic search is a NoSQL database. Since there are so many NoSQL databases, let us understand how Elasticsearch is different from them.
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Tuple is similar to List in python language, both are sequential, index based data structure.

The main difference between tuples and list is that tuples are immutable i.e. we cannot modify a tuple’s content but List is mutable data structure. Also, tuples uses parenthesis and list uses square brackets.

This article will discuss about following in Tuples:

1. Create an Empty Tuple
2. Create Tuple with Homogeneous Elements
3. Create Tuple with Heterogeneous Elements
4. Create Tuple with Single Element
5. Modify Elements of Tuple
6. Accessing Elements of Tuple – From the Front
7. Accessing Elements of Tuple – From the Back
8. Search Within a Tuple
9. Add Elements to a Tuple
10. Delete an Element from a Tuple
11. Iterate Over a Tuple
12. Concatenation of Tuples
13. Identify Length of a Tuple
14. Slice a Tuple
15. Count the Number of Elements in a Tuple
16. Identify the Index of an Element in a Tuple
17. All Tuple Examples in one Example tuples.py Program

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In your AWS environment, for configuration management, you can use AWS OpsWorks which provides managed instances of either Chef or Puppet. You have the following three options when using AWS OpsWorks.

1. AWS Opsworks for Chef Automate
2. AWS OpsWorks for Puppet Enterprise
3. AWS OpsWorks Stacks – This is for application modeling and management. You can model your app as a stack with different layers (e.g: web layer, db layer, etc.). This uses Chef solo in the backend to configure nodes.

This tutorial provides the following examples on how you can manage your AWS OpsWorks servers from CLI using aws opsworks-cm command.

1. Create OpsWorks Server (Chef or Puppet) using create-server
2. View OpsWorks Server Details using describe-servers
3. Delete an OpsWorks Server using delete-server
4. View Account Attributes and Server Events of a Server
5. Update Server Maintenance and Backup Window using update-server
6. Disable or Enable Automated Backups
7. Specify Backup Retention Count
8. Reset Chef Server’s Private Key (or) Update Puppet Admin Password
9. Take a Backup of OpsWorks Server using backup-server
10. View Available Backups using describe-backups
11. Delete an OpsWorks Backup using delete-backup
12. Restore OpsWorks Server from a Backup using restore-server

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OOP stands for Object Oriented Programming. This concept is a style of solving programming problems where properties and behavior of a real-life object is packaged as a single entity in the code.

This style of coding enables modularizing and scaling with least amount of issues.

Python is a dynamically typed, high level interpreted programming language. Python supports several OOP features including the following:

• Classes and Objects
• Encapsulation
• Inheritance
• Polymorphism

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While using git, for most part, you shouldn’t be working directly on the master branch.

Any development work, or hotfixes, or research work that you do, you’ll typically create a new branch, and make changes to your code on that branch.

If you are happy with your code changes on your branch, then you’ll merge it to the master branch.

Or, if you created a branch to quickly test something by making some code change without the intention of keeping your code change, then after your testing, you can simply discard your code changes by deleting the branch that you created for your testing purpose. This way, the code in your master branch is not affected.

This tutorial explains the following steps:

1. Create a new dev branch
2. Do your work on local dev branch
3. Push dev branch from your local to central git repository
4. Once your work is done, merge dev branch to master
5. Finally, delete the dev branch from both local and central git repository

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