Can Pholcus be configured to only scrape new or updated content?

Pholcus is a distributed, high concurrency, and powerful web crawler software written in the Go language. It is primarily designed for web data mining, with flexibility and scalability in mind. However, unlike some other web scraping tools, Pholcus does not inherently provide a built-in feature to differentiate between new or updated content and content that has already been scraped.

To only scrape new or updated content, you would need to implement a custom solution. Here are a few strategies you might consider:

1. Timestamps: If the website you're scraping includes timestamps indicating when the content was last updated, you can compare these timestamps to the time of your last scrape. You would then only process content with a newer timestamp.

2. Content Hashing: Keep a record of hashes for the content you have already scraped. Before scraping a page, generate a hash for the current content and compare it to the stored hash. If the hash is different, the content has changed, and you should scrape it.

3. ETags / Last-Modified Headers: Use HTTP headers such as ETag or Last-Modified when making requests. These headers can inform you if the content has changed since the last request without needing to download the entire resource.

4. Sitemaps: Some websites provide sitemaps that include information about when each page was last updated. You can parse the sitemap and compare the last updated information with your last scrape timestamp.

5. Incremental IDs: If the content is associated with sequential or incremental IDs, you can store the last ID you scraped and start from the next one on subsequent scrapes.

Here's a conceptual example of how you might implement a timestamp-based check using Python with the requests and BeautifulSoup libraries. This assumes you're storing the last scrape timestamp somewhere, like a database or a file:

import requests
from bs4 import BeautifulSoup
import datetime

# Assume last_scrape_timestamp is the timestamp of your last successful scrape
last_scrape_timestamp = datetime.datetime(2023, 3, 31) # Example date

# URL to scrape
url = 'http://example.com/page-with-timestamps'

# Perform the HTTP request
response = requests.get(url)

# Check if the request was successful
if response.status_code == 200:
    # Parse the HTML content
    soup = BeautifulSoup(response.content, 'html.parser')

    # Find the timestamp element in the page (this is highly dependent on the page structure)
    timestamp_element = soup.find('time', attrs={'class': 'timestamp'})

    # Extract and parse the timestamp from the element
    page_timestamp = datetime.datetime.strptime(timestamp_element.text, '%Y-%m-%d %H:%M:%S')

    # Compare the page timestamp to the last scrape timestamp
    if page_timestamp > last_scrape_timestamp:
        # The content has been updated since the last scrape, so proceed with scraping
        # ... (Scraping logic here)

        # Update the last_scrape_timestamp to the current page's timestamp
        last_scrape_timestamp = page_timestamp
else:
    print(f"Failed to retrieve content, status code: {response.status_code}")

For JavaScript, assuming you're using Node.js with modules like axios and cheerio, the logic would be similar:

const axios = require('axios');
const cheerio = require('cheerio');

// Assume lastScrapeTimestamp is the timestamp of your last successful scrape
let lastScrapeTimestamp = new Date('2023-03-31T00:00:00Z');

// URL to scrape
const url = 'http://example.com/page-with-timestamps';

axios.get(url)
  .then(response => {
    // Load the HTML content into cheerio
    const $ = cheerio.load(response.data);

    // Find the timestamp element in the page (this is highly dependent on the page structure)
    const timestampElement = $('time.timestamp').text();

    // Extract and parse the timestamp from the element
    const pageTimestamp = new Date(timestampElement);

    // Compare the page timestamp to the last scrape timestamp
    if (pageTimestamp > lastScrapeTimestamp) {
      // The content has been updated since the last scrape, so proceed with scraping
      // ... (Scraping logic here)

      // Update the lastScrapeTimestamp to the current page's timestamp
      lastScrapeTimestamp = pageTimestamp;
    }
  })
  .catch(error => {
    console.error(`Failed to retrieve content: ${error}`);
  });

Remember, the actual implementation details will vary greatly depending on the structure of the website you're scraping, the nature of the changes you're tracking, and how you're storing previously scraped data. Additionally, always be sure to respect the website's robots.txt file and terms of service when scraping.