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How to Build CI/CD Pipeline: GitHub to AWS

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 Creating a CI/CD pipeline to deploy a project from GitHub to AWS can be done using various AWS services like AWS CodePipeline, AWS CodeBuild, and optionally AWS CodeDeploy or Amazon ECS for application deployment. Below is a high-level guide on how to set up a basic GitHub to AWS pipeline: Prerequisites AWS Account : Ensure access to the AWS account with the necessary permissions. GitHub Repository : Have your application code hosted on GitHub. IAM Roles : Create necessary IAM roles with permissions to interact with AWS services (e.g., CodePipeline, CodeBuild, S3, ECS, etc.). AWS CLI : Install and configure the AWS CLI for easier management of services. Step 1: Create an S3 Bucket for Artifacts AWS CodePipeline requires an S3 bucket to store artifacts (builds, deployments, etc.). Go to the S3 service in the AWS Management Console. Create a new bucket, ensuring it has a unique name. Note the bucket name for later use. Step 2: Set Up AWS CodeBuild CodeBuild will handle the build proces
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Python Web data - How to Extract HTML Tags Easily

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With BeautifulSoup you can extract HTML and XML tags easily that present in Web data. Here is the best example of how to remove these.


The prime step of text analytics is cleaning. You can remove HTML tags using BeautifulSoup parser. Check out Python Logic and removing HTML tags. When analyzing web data, consider the below examples for your projects.


Python Ideas to Remove HTML tags
Python Ideas to Remove HTML tags


How I Removed Using BeautifulSoup

  1. Import BeautifulSoup
  2. Python Logic to Remove HTML tags
  3. Before and after executing the code

1. Import BeautifulSoup

import BeautifulSoup from bs4


2. Python BeautifulSoup: How to Remove HTML Tags

from bs4 import BeautifulSoup

soup = BeautifulSoup("<!DOCTYPE html><html><body><h1>My First Heading</h1><p>My first paragraph.</p></body></html>")

text = soup.get_text()

print(text)


3. Before and After Run

Before the run see the below code.


You need to import BeautifulSoup for Text analytics
Before Executing the code


After Run the tags are parsed. The means in the output tags removed.

I have shared Python sample logic on how to remove HTML tags. Also, given the package name you need. It is a useful example for text analytics.
Result after executing the code

Bottom-line of Result

Below are the steps you need for HTML tags parsing:
  1. Reads input HTML data
  2. Removes HTML tags
  3. Prints only text data

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