OnlineProxy

Honestly none of this is verifiable, no run counts, no bytes per flow, no failure rates, so I'd not treat it as real measurements. The pricing also switches quietly, since 65 rub per 1000 solves is about 0.065 each, and 20-30 rub on one failed registration only works at the 1.5 smartcaptcha rate. That makes the two orders of magnitude headline lean on the cheap solver while the failure math leans on the expensive one request.sizes() or CDP encodedDataLength are the easiest hooks, but they show what the browser saw and not what the provider billed

None of the 3 feeds gives a real ATS apply link, even remoteok's apply_url points back to its own pages so normalized company plus title with seniority split out is pretty much your only cross board key. The 8 out of 585 run is hard to read since minsalaryusd 120000 was just an example input, so either the run dropped the unsalaried and non USD jobs or it only pulled a small slice of the 99k himalayas jobs. I'd publish the disclosure rate next to every salary average cause WWR has no salary field and the stats only describe employers who disclose. The himalayas cursor can still miss a job that gets updated mid walk, so keep the seen set and rerun now and then

Ran the math on the freshness gate, on a 30 min cadence it never opens, and right at the 22.5 minute boundary one missed scrape kills it. Bigger issue is customer_cost returning 0 for unavailable items, so an unavailable own_offer divides by zero, and the same bug stays quiet when a promo beats price plus fees, own_cost goes negative and you fire an undercut alert exactly when you're winning. Unavailable should just be None. Also repeat scrapes of one store share cache and session state so thats not real corroboration, and the hardcoded 0.15 threshold should come from per category economics

Missing the failure I hit most, spawn npx ENOENT. Absolute npx path alone doesn't fix it, you also need env.PATH set in mcp.json with your node bin dir. On fnm use aliases default bin, not fnm_multishells, those are temporary. Windows path in the table is wrong too, it's userprofile cursor mcp json not appdata cursor. Also proxy_country needs premium_proxy true in manual mode, auto handles it automatically. On the 99.93 figure, Scrapeway clocked them at 17 %, but Scrapeway is tied to Scrapfly, a direct competitor. Neither side is neutral so test your own urls

Zero rejections with zero input is just a dead scraper so alert on rejection counts alongside input volume. The 10% cap only bounds single steps, compounding still walks you to the floor, so use a windowed cumulative drift breaker instead of counting consecutive capped moves, which is gameable by alternating capped and accepted ones Real bug in the guard too, if the price already sits below the floor a capped up move at current_price * 1.1 can still ship below it, clamp to max(floor_price, upper_bound). Tie the floor to current landed cost and say whether 20% means margin on price or markup on cost, those give different numbers. Add a per unit multipack check with an override lane for clearance stuff, and make rule_set_version and segment_version real columns in pricing_decisions so old prices stay explainable

That 8 minute default feels more unsupported than outright broken, same controls with only staleness different and it still passed their own check. Whether surge windows need more slack is really a question for the volatility data. Capture skew still works when captures aren't simultaneous, but it misses staleness at the source, so caches need their own detection. The generated timestamp helps when exposed but caches can overwrite it and it's unclear if it means issued or rendered, so pair it with cart vs checkout divergence and observed volatility, and just persist eligibility and cache age at capture time since neither rebuilds after the fact. Also the session_state_unknown check is treated as fatal but the article never shows how that flag actually gets set, if it comes from real line items it's fine, if it's weaker a flipped session could slip through so that reads more like a gap to clarify than a confirmed bug

testing three unrelated networks before blaming the IP is the step most people skip, and identical 429s on all three points to the fingerprint being the real issue here. so "not about your IP" doesn't hold up everywhere, there are reports of clean human browsers still catching code 11 on hetzner and code 99 on VPN until the VPN dropped. so a good client helps but a flagged exit can still sink you. also the camoufox switch changed engine, protocol, TLS and fingerprint all at once so it proves the recipe works, not which part actually mattered. same with the turnstile details, that's only ONE page's behavior. and nobody circled back to the opening question about whose accounts these are and under what authority, that's the part I'd actually want answered.

default celery is at most once delivery, so a crashed worker just loses the task, which hurts with flaky selenium runs. acks_late plus redis visibility_timeout fixes that, but then your writes need to be idempotent, upsert on a URL hash, and cap each task with soft_time_limit and time_limit so a hung browser doesn't get redelivered while still running. For retries, narrow autoretry_for to real transient errors, add backoff with jitter, and use a redis token bucket per domain since rate_limit only applies per worker. And yeah headless chromium eats way more memory than plain HTTP, so I check for a json endpoint before firing up a browser

The 429 thing bugs me most, your text says it just means overuse but the code treats it exactly like a 5xx and gives it the same escalating cooldown as a dead proxy. Retry after headers are also messier than people expect, sometimes missing, sometimes a full date instead of seconds, and 503s throw them too plus the limit might be on your account not the proxy so a separate throttle counter would help. Also that 403 branch quietly calls mark_success and wipes the fail streak even though 403 could mean banned, bad auth or just a url everyone gets blocked on. While you're in there, lok fail_count if this runs across threads, and narrow that bare except requestexception down to connectionerror and Timeout or you'll end up blaming the proxy for stuff like invalidURL that's actually your own mistake

For a beginner guide the browser vs http split works as a starting point but in production most people just mix both. I run the browser once to grab tokens or the request shape, then replay that over cheap http at volume and only bring out the full browser when nothing else works. Also a lot of js heavy retail sites hydrate from embedded state, like the data blob next.js dumps into the page, or from internal json and graphQL endpoints, so you can often skip the browser. Client still has to pass TLS fingerprint checks just to pull the html tho, and digging those APIs out takes real work and breaks silently once a private endpoint changes. Playwright has basically taken over as default for new projects, selenium 4 is still fine for legacy code or grid. Log the context with each availability record, location, variant, fulfillment, account state, timestamp, since availability shifts around constantly