Scrape online reading lists

To scrape online reading lists, you’ll need to identify the sources (e.g., university websites, Goodreads, blogs, or online syllabi), parse the web content, and extract relevant information such as book titles, authors, and categories. Here’s a high-level guide to help you get started, along with a sample Python script using requests and BeautifulSoup.

Step 1: Identify Target Websites

Choose websites that publish reading lists, such as:

• University course pages (e.g., Harvard, MIT)

• Goodreads lists (e.g., “Top 100 Books of All Time”)

• Book blogs (e.g., Modern Mrs. Darcy, Book Riot)

• Library websites

• Online syllabi (e.g., Open Syllabus Project)

Step 2: Use Python Libraries

Install necessary libraries:

bash
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pip install requests beautifulsoup4

Step 3: Basic Scraper Example

Here’s a script to scrape reading lists from a sample URL:

python
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import requests
from bs4 import BeautifulSoup

url = "https://www.goodreads.com/list/show/1.Best_Books_Ever"  # Sample Goodreads list
headers = {'User-Agent': 'Mozilla/5.0'}

response = requests.get(url, headers=headers)
soup = BeautifulSoup(response.text, 'html.parser')

books = []

for book_item in soup.select('a.bookTitle'):
    title = book_item.get_text(strip=True)
    link = "https://www.goodreads.com" + book_item['href']
    books.append({'title': title, 'link': link})

for book in books:
    print(book)

Step 4: Scraping Academic Lists Example

For university course pages:

python
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url = "https://ocw.mit.edu/courses/literature/21l-003-introduction-to-fiction-fall-2003/readings/"
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')

readings = []

for li in soup.select('li'):
    text = li.get_text(strip=True)
    if "by" in text.lower():
        readings.append(text)

for reading in readings:
    print(reading)

Step 5: Handling Pagination and JS-rendered Pages

For paginated content, loop through URLs using parameters like ?page=2.
For JavaScript-rendered sites (e.g., dynamic Goodreads pages), use Selenium:

bash
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pip install selenium

python
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from selenium import webdriver
from bs4 import BeautifulSoup
import time

driver = webdriver.Chrome()
driver.get("https://www.goodreads.com/list/show/1.Best_Books_Ever")
time.sleep(3)

soup = BeautifulSoup(driver.page_source, 'html.parser')
driver.quit()

titles = [a.get_text(strip=True) for a in soup.select('a.bookTitle')]
print(titles)

Step 6: Store Data

Use pandas or export to CSV:

python
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import pandas as pd

df = pd.DataFrame(books)
df.to_csv("reading_list.csv", index=False)

Legal & Ethical Considerations

• Check each site’s terms of service.

• Respect robots.txt and rate-limit your requests.

• Do not overload servers or scrape private content.

Let me know if you want a script for a specific site or format.