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15 Python Tips : How to Write Code Effectively

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 Here are some Python tips to keep in mind that will help you write clean, efficient, and bug-free code.     Python Tips for Effective Coding 1. Code Readability and PEP 8  Always aim for clean and readable code by following PEP 8 guidelines.  Use meaningful variable names, avoid excessively long lines (stick to 79 characters), and organize imports properly. 2. Use List Comprehensions List comprehensions are concise and often faster than regular for-loops. Example: squares = [x**2 for x in range(10)] instead of creating an empty list and appending each square value. 3. Take Advantage of Python’s Built-in Libraries  Libraries like itertools, collections, math, and datetime provide powerful functions and data structures that can simplify your code.   For example, collections.Counter can quickly count elements in a list, and itertools.chain can flatten nested lists. 4. Use enumerate Instead of Range     When you need both the index ...
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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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