Creating a universal e-commerce product data extractor

Ecom
1

Hey everyone, I’m trying to make a tool that can grab product info from different online stores. The idea is to search for an item on Google, then go through the results and pull out details like the product name, price, and seller. I’ve looked around but haven’t found much that fits what I need. I checked out Diffbot, but it wasn’t perfect - some info was wrong or missing.

I’m wondering if anyone knows if this is doable and how I might go about it. Are there any tricks or tools that could help? Or is this just too big a job to tackle? I’d really appreciate any advice or pointers you all might have!

Here’s a basic example of what I’m thinking:

def search_and_extract(product):
    results = google_search(product)
    product_data = []
    for link in results:
        page_content = fetch_page(link)
        item_info = extract_product_info(page_content)
        product_data.append(item_info)
    return product_data

def extract_product_info(content):
    # This is where the magic would happen
    # to pull out name, price, seller, etc.
    pass

Any thoughts on how to make this work across different sites?

2

Creating a universal e-commerce product extractor is indeed a challenging task. One approach you might consider is utilizing machine learning techniques, specifically Natural Language Processing (NLP), to identify and extract relevant product information across various website structures. Libraries like spaCy or NLTK could be beneficial for this purpose. Additionally, implementing a robust error handling system is crucial, as website structures can change frequently. Remember to respect each website’s robots.txt file and terms of service to ensure ethical scraping practices. It’s a complex project, but with persistence and continuous refinement, you could develop a valuable tool for e-commerce analysis.

3

Wow, that’s an interesting project you’ve got there, Jade! Have you thought about using a mix of techniques? Maybe combine web scraping with some AI magic?

I’ve been tinkering with something similar and found that using a combination of BeautifulSoup for basic structure parsing and then feeding that into a pre-trained NER (Named Entity Recognition) model can work wonders. It’s not perfect, but it gets you a good starting point.

What about caching results to speed things up? And hey, have you considered reaching out to some e-commerce platforms directly? Some might have APIs that could make your life easier.

Just curious - what’s your end goal with this tool? Are you planning to use it for price comparison or something else? It’d be cool to hear more about your plans!

4

hey jade, that’s a pretty ambitious project! extracting product data from various sites can be trcky. have u considered using beautifulsoup or scrapy for web scraping? they’re pretty good at pulling out structured data. also, maybe look into using regula expressions to match common patterns for prices and product names. good luck with ur project!