Building a Content Aggregator with Python

Introduction
Prerequisites
Setup
Creating the Content Aggregator
Conclusion

Introduction

In this tutorial, we will explore how to build a content aggregator using Python. A content aggregator collects data from multiple sources and presents it in a unified format. By the end of this tutorial, you will be able to scrape data from websites, store the collected data, and display it on a webpage.

Prerequisites

Before starting this tutorial, you should have a basic understanding of Python programming language and some familiarity with web scraping concepts. Knowledge of HTML, CSS, and JavaScript will also be helpful but not mandatory.

Setup

To follow along with this tutorial, you need to have Python installed on your system. You can download and install Python from the official website (https://www.python.org). Additionally, we will be using the following libraries:

BeautifulSoup: A Python library for parsing HTML and XML documents.
Requests: A library for making HTTP requests in Python.

You can install these libraries using the following command: pip install beautifulsoup4 requests

Creating the Content Aggregator

Scraping the Websites

First, let’s scrape the websites to collect the desired content. We will be scraping news articles from two different websites: Website A and Website B.

Start by importing the necessary libraries:

 import requests
 from bs4 import BeautifulSoup

Use the requests library to fetch the HTML content of Website A:

 response_a = requests.get('https://www.website-a.com')
 html_a = response_a.text

Parse the HTML content using BeautifulSoup:

 soup_a = BeautifulSoup(html_a, 'html.parser')

Use BeautifulSoup to find the relevant elements containing the news articles:
```
 articles_a = soup_a.find_all('article')
```

Repeat the above steps for Website B:

 response_b = requests.get('https://www.website-b.com')
 html_b = response_b.text
 soup_b = BeautifulSoup(html_b, 'html.parser')
 articles_b = soup_b.find_all('div', class_='news-article')

Storing the Data

To store the scraped data, we will use a SQLite database. SQLite is a lightweight database engine that does not require a separate server process.

Import the sqlite3 library:
```
 import sqlite3
```

Connect to the SQLite database and create a table to store the articles:

 conn = sqlite3.connect('articles.db')
 c = conn.cursor()
 c.execute("CREATE TABLE IF NOT EXISTS articles (title TEXT, source TEXT, url TEXT)")

Iterate over the scraped articles from Website A and insert them into the database:

 for article in articles_a:
     title = article.find('h2').text
     url = article.find('a')['href']
     c.execute("INSERT INTO articles VALUES (?, ?, ?)", (title, 'Website A', url))

Repeat the same process for the articles from Website B:

 for article in articles_b:
     title = article.find('h3').text
     url = article.find('a')['href']
     c.execute("INSERT INTO articles VALUES (?, ?, ?)", (title, 'Website B', url))

Displaying the Aggregated Content

Now that we have scraped and stored the articles, let’s create a basic web page to display the aggregated content.

Create a new Python file named app.py and import the necessary libraries:
```
 from flask import Flask, render_template
 import sqlite3
```
Create a Flask application:
```
 app = Flask(__name__)
```

Define a route to handle the homepage:

 @app.route('/')
 def index():
     conn = sqlite3.connect('articles.db')
     c = conn.cursor()
     c.execute("SELECT * FROM articles")
     articles = c.fetchall()
     return render_template('index.html', articles=articles)

Create an HTML template file named index.html and add the following code:

 <!DOCTYPE html>
 <html>
 <head>
     <title>Content Aggregator</title>
 </head>
 <body>
     <h1>Content Aggregator</h1>
     <ul>
	        
     </ul>
 </body>
 </html>

Run the Flask application:
```
 if __name__ == '__main__':
     app.run()
```
Now, if you navigate to http://localhost:5000 in your web browser, you should see the aggregated content from both websites.

Conclusion

In this tutorial, we have learned how to build a content aggregator using Python. We have covered the process of scraping websites, storing the data in a SQLite database, and displaying the aggregated content on a webpage. This project can be expanded further by adding more websites to scrape or by adding additional features such as user authentication or filtering. Using the concepts learned in this tutorial, you can create your own content aggregator tailored to your specific needs.

Published: 15 August 2022