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Step-by-Step Guide to Creating an AWS RDS Database Instance

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 Amazon Relational Database Service (AWS RDS) makes it easy to set up, operate, and scale a relational database in the cloud. Instead of managing servers, patching OS, and handling backups manually, AWS RDS takes care of the heavy lifting so you can focus on building applications and data pipelines. In this blog, we’ll walk through how to create an AWS RDS instance , key configuration choices, and best practices you should follow in real-world projects. What is AWS RDS? AWS RDS is a managed database service that supports popular relational engines such as: Amazon Aurora (MySQL / PostgreSQL compatible) MySQL PostgreSQL MariaDB Oracle SQL Server With RDS, AWS manages: Database provisioning Automated backups Software patching High availability (Multi-AZ) Monitoring and scaling Prerequisites Before creating an RDS instance, make sure you have: An active AWS account Proper IAM permissions (RDS, EC2, VPC) A basic understanding of: ...
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How to write Regular expression Quickly in python and Examples

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Regular Expressions purpose is to find matching string in another string. You will get either 'True' or 'False' as a response. I am not sharing here how to play tennis. My intention is if you just follow ideas, you can play tennis today.

Python supports regular expressions. It has a special library to work with these. I have shared best examples for your quick reference.
 

Python Regular Expressions

  1. What is a regular expression
  2. How does python support
  3. Best examples


1. What is regular expression


>>> haystack = 'My phone number is 213-867-5309.' 
>>> '213-867-5309' in haystack
True


This is just a fundamental use of the regular expression. The real use of Regular Expression comes here. That is - to find if the main has any valid phone number.


Regular expressions also called regexes.

2. Why do we need regx

  1. Data mining - to get required data if it is present are not
  2. Data validations - to get an answer if the received string is valid or not.

Python support


Python has its own regular expression library. That is called re. What you need to do is just import it.

>>>import re


When data matches and not matches

  1. If a match found, it returns the String
  2. If there is no match, it will return null


Example for regex


>>> import re
>>> re.search(r'fox', 'The quick brown fox jumped...')
<_sre.SRE_Match object; span=(16, 19), match='fox'>

Notes: The returned string is 'fox'.


Matching string


>>> match = re.search(r'fox', 'The quick brown fox jumped...')
>>> match.group() 'fox'

Notes: The returned string is 'fox'.



Multiple matches

>>> import re >>> re.findall(r'o', 'The quick brown fox jumped...')
['o', 'o']

Notes: It returns multiple strings.

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