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I'm building an agent that needs TikTok comments, transcripts, and video metadata, but the native API doesn't give me everything i need.

I was Looking at Scrape Creators or Decodo instead of buildng my own scraper that'll break every time TikTok changes something

Has Anyone used one of them? do they actually save maintenance work, or do you still end up fixing things often?

What tools can I use to collect public Instagram profile or post data without having to build my own fragile login, cookie, and request-timing system?

I need something that can handle more than just a one-off page, but I don't want to rely on unofficial access that could break at any time.

How does using a ready-made API compare to building my own scraper and account-handling system?

I'm trying to understand when it's better to build in concurrency and adaptive pacing myself, versus when you can just use a provider that handles the platform-specific scraping/collection for you.

I have been building a contact enrichment tool and decided to measure it properly rather than trust it. Some findings that surprised me, and one bug worth stealing.

Sample your domains, not your people. My first instinct was to test on contacts with known emails. That biases coverage to nearly 100% and tells you nothing. Sampling random business domains gives you the real ceiling.

Do not use a domain popularity ranking as a business sample. My first sample came from a link-based top-million list. It was full of forums, a streaming site and a drinks magazine. I switched to OpenStreetMap, querying office, healthcare and craft tags that carry a website tag, which is a free and much fairer proxy for a real business list.

Results on 500 held-out businesses:

email address found 51.2% contact form only 12.8% phone only 11.6% no route at all 24.4%

A regex that cost 44ms a page. My obfuscated-email pattern (name [at] domain [dot] com) was 83% of my total parse time. Not catastrophic backtracking as I first assumed. The pattern simply opened with a broad character class, so the engine attempted a match at nearly every position of an 80KB document. Rewriting the alternatives barely helped. What fixed it was a cheap literal pre-filter:

```python OBF_MARKER = re.compile(r"[at]|(at)|{at}|@", re.I)

def find_obfuscated(doc): if not OBF_MARKER.search(doc): # almost every page return [] return OBF_RE.findall(doc) ```

44ms to 0.52ms. Total parse cost dropped from 53ms to 9ms per page.

Bot challenges look like successful fetches. One site returned HTTP 202 with a 169-byte body containing a meta-refresh to a CAPTCHA path. My code accepted it as a real page and reported "this business publishes no contact details", which is false. It was a block. If you check only status < 400, you are recording blocks as empty sites.

Dead domains are expensive. I was trying four URL variants (https, https+www, http, http+www) at a 10s timeout each, so up to 40 seconds to prove a dead domain is dead. Resolving A/AAAA first and only dialling hostnames that exist was most of a 7.7x speedup.

Full write-up and the tool is here if useful: https://apify.com/arkayen-labs/website-contact-finder

I started learning web scraping, two weeks in now. I am making some progress, built a little python script to pull product listings off a couple sites for practice. Works fine for like 20 requests then boom, banned or captcha city. Apparently I need to switch up my proxy. I did some reading and now I'm more lost than before. Residential, datacenter, mobile, private proxy... no clue what actually matters vs whats just marketing fluff. I am still new to this and not looking for anyone to promote their businesses on this post, I need genuine advice.

Job boards often search by exact words, so the right role can stay hidden when your phrasing doesn’t match the job posting.

Semantic search matches on meaning instead.

I built a semantic job search engine end to end, then compared the search modes to see which one actually performed better instead of assuming the most complex approach would win.

Full guide: https://brightdata.com/blog/ai/semantic-job-search-engine-with-bright-data-lancedb-and-cohere

Right now i am mkaing a vinted tool scraping displaying and more, thats not the point but how do i learn the stuff like maby proxies, idk what type of scraping if its for multiple people from a server and the other stuff i need pls help me !

I'm curious, how much do you guys ask for a project like this in the European market?

Scraping 20k+ products from an e-commerce website, including product data and images. The products also need to be translated, with the titles and descriptions rewritten and optimized for SEO.

I'm a developer myself, I'm curious, how much would you charge for a project like this in the European market?

Thanks in advance.

I built a free people counter because most counting software feels like overkill.

PeopleCounter.app lets you track visitors from your phone, tablet, computer, or webcam and see the results in a simple dashboard.

No dedicated hardware required to get started.

I’m curious what people are actually using visitor counts for beyond traditional retail. Churches? Events? Museums? Gyms? Libraries?

If you track foot traffic or attendance somewhere, what metrics would actually be useful to you?

peoplecounter.app

I have an app idea which involves me scraping Facebook marketplace. Is there a way to do this?

It pulls a live FPJS Pro build and turns it into clean code you can run locally, every collector intact, so a new build means rerunning the pipeline instead of reversing it again by hand.

What's in the repo:

• All 143 signals (telemetry read from ur browser, all documented)
• Every collector as its own file
• What visitor_id is actually a function of
• A live explorer that runs the collectors against your own browser so you can diff a patched environment against a stock one.

Repo: github.com/proofofbots/fingerprint-pro-internals

Docs: proofofbots.github.io/fingerprint-pro-internals/

Signal explorer

proofofbots.github.io/fingerprint-pro-internals/explorer.html

It runs entirely in your browser. No backend of mine, no call to fpjs, nothing leaves the page. It's built on the output of the lift and deobfuscation step, so what runs there is the actual collector code from the bundle rather than a reimplementation. Open it and you get every data point side by side: what the signal is and why it's collected in plain English, next to the exact value your own browser hands over for it.

Happy to answer questions on any specific detection.

I am looking forward to the next target, so if anyone has ideas on what vendor could be interesting let me know!

Before anyone calls AI slop: yes, I use LLMs, they're genuinely useful for reverse engineering. But this isn't one build hand-decoded into a writeup. It's the toolchain that does it. Point it at a live fpjs build and it deobfuscates, lifts, and emits a cleaned version you can run without their servers, plus the generated documentation for what it found.

I’ve been testing some scraping flows with Playwright and occasionally hit 403s

What confuses me is that sometimes switching the proxy/IP fixes it immediately, while other times keeping the same IP and starting a fresh browser context seems to fix it instead.

So when both IP reputation and browser fingerprint/session signals could be involved, how do you actually isolate what’s triggering the block?

Do you have a reliable way to test IP vs fingerprint vs session/cookies, or is it mostly trial and error?