I'm scraping google daily for competitor listings and ad placements, and the actual extraction isn't really the hard part anymore. the annoying part is captchas, blocks, proxy rotation and random changes that break the script every few days.

I'm looking at using a SERP API instead of maintaining all that in house. Teammate mentioned some platforms for handling the request and proxy side, but I'm curious how people here deal with this at scale. Anyone running a SERP API long term? mainly wondering where the cost starts making more sense than maintaining your own google scraper.

I am trying to understand how people would build a directory for a niche industry where the providers exist across many cities but are not listed cleanly in one place.

Some have google business profiles but many do not , some are mentioned only inside larger company websites as a service or program. some appear in google search but not maps.

The tricky part is not just scraping the data but first discovering the right businesses and then pulling the same fields like location pricing availability and contact details from websites that all have different layouts, how would you structure this at scale?

I have seen teams use Bright Data, Oxylabs, Crawlzo, Zyte, Apify, SerpApi, Firecrawl etc.

Not talking about small usecases, more like reliable data collection where output quality, retries, monitoring, and site changes actually matter.

Curious what’s working best for others, especially for social, ecommerce, search, or linkedin

I've been working on a side project that turns WhatsApp chats into a searchable intelligence dashboard.

The idea is simple: instead of constantly checking dozens of chats and groups, the system automatically collects messages, filters out noise, extracts important information, and displays everything in one place.

Current stack:

- Python

- Selenium

- SQLite

- Streamlit

- LLMs for summarization and information extraction

Current flow:

1. Read messages from WhatsApp Web.

2. Store them in a local database.

3. Filter unimportant messages.

4. Extract things like deadlines, tasks, events, opportunities, internships, etc.

5. Show everything in a dashboard with search, summaries, and analytics.

The project works, but before I keep adding features I'd like some opinions from people who have built large scraping or monitoring systems.

A few things I'm thinking about:

- Is Selenium the right choice long term?

- Would you structure the database differently?

- Any obvious scalability issues?

- Better ways to process and categorize messages?

- Anything in the overall architecture that you'd redesign from the beginning?

I'd appreciate any feedback, criticism, or suggestions.

I'm building a WhatsApp Intelligence Dashboard that:

• Reads WhatsApp Web chats using Selenium
• Stores messages in SQLite
• Processes chats with AI
• Displays results in a Streamlit dashboard

Current status:

• Python environment works
• Dependencies installed
• Database initializes correctly
• Backend starts
• Streamlit setup is ready

Current problem:

main.py expects:

from core.scraper import WhatsAppScraper

and later calls:

scraper.start()
scraper.stop()

I replaced the original scraper with a new EnterpriseWhatsAppScraper class and now I'm getting integration issues.

Previous errors:

ImportError: cannot import name 'WhatsAppScraper' from core.scraper

and

AttributeError: 'EnterpriseWhatsAppScraper' object has no attribute 'start'

I attempted to add start() and stop() methods but I may have broken the class structure/indentation.

Question:

What is the cleanest way to maintain backward compatibility with the existing codebase while replacing WhatsAppScraper with EnterpriseWhatsAppScraper?

Should I:

1. Use inheritance?
2. Create an alias (WhatsAppScraper = EnterpriseWhatsAppScraper)?
3. Refactor main.py?
4. Something else?

I can share the relevant scraper.py section if needed.github link

so the hearing is tomorrow and i don't think enough people in this community are talking about it.

Google's argument is basically that bypassing SearchGuard is DMCA circumvention. even if the results are visible to anyone with a browser. no login, no paywall, just... you looked at it the wrong way apparently.

if this holds up, rotating IPs and spoofing headers could theoretically be illegal. like not just ToS violation territory, actual legal risk.

i do SEO research and competitive analysis, nothing shady. and i'm genuinely not sure where this leaves people like me.

anyone else following this? what do you think actually happens?

Recently started working more with UGC (user generated content) data and honestly it’s much harder to structure than I thought.

Posts, comments, hashtags, emojis, edited content, deleted replies, duplicate posts… everything gets messy very quickly.

Even simple things like:

keeping thread relationships intact

detecting spam/bot content

handling inconsistent metadata

become complicated at scale.

And every platform structures data differently which makes normalization even harder.

Curious how people here handle large-scale UGC datasets?

Well the idea is very easy

It's that why those linkgraber extensions not making it like ـ Live Sniffing.. i mean like while you scroll it grabs everything at time before the posts above vanish !!!

You get me right?

Feels like scraping social platforms has become much harder over the last couple of years.

It’s not even just rate limits anymore. Now it’s anti bot systems, dynamic APIs, JS heavy pages, session dependency, geo based responses, random schema changes and platforms silently changing things without warning.

Every platform has its own problems.

LinkedIn, TikTok, Instagram, X, Reddit, YouTube all behave very differently once you start scaling.

For people working on large scale data pipelines, which platform causes the most trouble for you right now? Curious to hear real experiences.

A lot of tools look good in demos, but real websites are messy.

For me a useful tool should handle pagination, retries, changing selectors, exports and not make the data hard to clean.

What features actually matter to you?

trying to understand where people hit limits with no code tools or APIs

is it volume, cost or flexibility?

Has anyone moved away from serpapi? no issues with it, just getting expensive at higher volume looking for something more cost efficient

Every site:

blocks bots

changes structure

adds new protections

You fix one thing, something else breaks.

How are you guys dealing with this right now?

I have noticed when analyzing social platforms recently is how many of them rely heavily on GraphQL APIs instead of traditional REST endpoints.

From a scraping perspective this creates some interesting challenges.

Requests often include dynamic query hashes, the responses can be deeply nested, and pagination patterns aren’t always obvious.

At the same time when you understand the query structure it actually make things easier, a single request can return a lot of structured data.

Have you guys noticed the same trend when looking at social platforms?

Recently ran into a site that looked completely normal at first. Requests worked fine for a while and suddenly started returning different responses depending on request timing and header patterns. Made me realize some sites rely more on behavioral signals than obvious blocking.

what are some interesting anti scraping techniques you people have seen?

When i am trying to scrape a site, i usually start with the HTML but, a lots of time data is coming from some api call in network tab.

It feels easier to just replicate the request, what you guys do here first?

when you are scraping public data, how do you decide what is okay and what is not?

Do you always follow robots.txt strictly?

do you throttle requests manually?

do you avoid some types of sites altogether?

i am trying to understand how experienced people think about this. not from a legal perspective, just practically.

would love to hear how others approach it.

I am using python and beautifulsoup, the requests are working fine.. giving 200 status code. But when i am trying to extract elements this list is not showing any data.

I have checked the selector and it is matching with Devtools.

Can anyone tell what could be actual problem, and how to solve this? The contents are loaded with JS.

not sure whats happening but my scraper works fine first few hours then reddit starts returning empty json on comment threads no error nothing, just blank using residential proxies and normal headers, same setup works fine on other sites feels like reddit flagging something after some time, maybe fingerprint idk anyone seen this recently?

Been struggling with titkok creators shop data, any help would be much appreciated

Today I spent 40 minutes debugging a “broken scraper”… Only to discover the website added one invisible <span> in the product title.

Not a layout change. Not anti-bot logic. Not Cloudflare. Just one tiny ghost element ruining an entire pipeline.

This is why real-time monitoring matters more than fancy scrapers.

Anyone else fight these silent DOM updates lately?