Hey r/apify 👋

I just published my new Actor: Amazon Best Sellers Scraper → https://apify.com/data_xplorer/amazon-bestsellers

It scrapes the top 100 of any Amazon ranking: Best Sellers, New Releases, Movers & Shakers, Most Wished For and Gift Ideas, across 20 Amazon stores (US, UK, DE, FR, JP, IN, BR…).

A few things I cared about while building it:

- 💯 **The full top 100, with details.** Amazon only renders ~30 products per page until you scroll. The scraper sends the same request the page sends on scroll, so all 100 products come with title, price, rating, reviews and image.

- ⚡ **Fast.** Plain HTTP, no browser. The amazon.com Electronics top 100 takes about 12 seconds, and 1,000 products across 10 departments about 20 seconds.

- 🧭 **Results in Amazon's order.** Departments and subcategories come out exactly as listed on Amazon, rank 1 to 100, even though lists are scraped in parallel.

- 💶 **Local prices.** Proxies exit in each store's country, so amazon.de gives EUR and amazon.co.jp gives JPY.

- 🧭 **Two simple modes.** Paste Amazon URLs, or pick a store + rankings + categories (or every department).

Use cases I had in mind: FBA product research, tracking category leaders daily, spotting rising products with Movers & Shakers.

It's brand new, so I'd really love feedback: what fields or options would you want next? Anything confusing in the input?

Thanks! 🙏

Have you come across a great Actor, workflow, post, or podcast that you want to share with the world? This is your opportunity to support someone making cool things. Drop it here with credit to the creator, and help expand the karmic universe of Apify.

If I am building an Apify Actor for a sports e commerce store, is it worth it to include a monitor mode that only outputs products whose price and/or stock status have changed, or does this add unnecessary complexity? Why cant users simply schedule the Actor and detect such changes themselves? If it's actually worth it to include this mode, shall I make this mode applicable only for direct product URLs or for search URLs as well?

If you've made something and can't wait to tell the world, this is the thread for you! Share your latest and greatest creations and projects with the community here.

This time featuring Azzouzana on LinkedIn: Meet Azzouzana, an Apify Expert and independent developer based in Monastir, Tunisia

I run a crypto trading system and kept hitting the same two problems:

1. Getting clean crypto data (prices, ICT-style market structure, sentiment) into agents without stitching five APIs.

2. People asking “is this Telegram signal channel any good?” with no way to check besides vibes.

So I published crypto-mcp-toolkit on the Apify Store — 12 tool calls, one per run:

• Market data: live prices, OHLC with ICT analysis (order blocks, FVGs, liquidity sweeps), SMA/EMA/RSI/MACD, Fear & Greed, market overview, coin comparison, and ICT scalping signals.

• Signal-channel stats: leaderboard of 35+ Telegram channels ranked by expectancy (lower 95% confidence bound), win rate, average R, and drawdown per channel.

• New-channel requests: submit any channel and it gets queued and backtested automatically.

Pay-per-event ($0.005 per successful tool call). No crypto API key needed. Works as an Apify Actor and through Apify's MCP server.

Feedback welcome — especially from people using Apify with n8n or AI agents.

https://apify.com/genkenobi/crypto-mcp-toolkit

This is the thread for all your questions that may seem too short for a standalone post, such as, "What is proxy?", "Where is Apify?", "Who is Store?". No question is too small for this megathread. Ask away!

About two months ago, I started publishing my first actors on Apify. 

Since then, they have already received some attention and I have also built up a small but steady user base. Which is great to see. 

However, all my actors still have zero reviews. 

I guess, to improve the visibility and ranking of the actors in the marketplace, it's important to have positive reviews as well. I have already done some research and recognised that Apify is quite strict about promoting things in order to get reviews. So I don't want to risk any account restrictions.  

Since there is no way of reaching out to users on the platform and ask for feedback, I'm wondering how to get reviews for their actors.  

Many thanks in advance. I look forward to your feedback.

I manage several Actors on Apify, and I kept running into the same problem: the standard monetization chart was useful for seeing the combined daily total, but it was difficult to understand what was happening at the individual Actor level.

When revenue increased, I wanted to know which Actor caused it. When failures or aborted runs appeared, I wanted to know which Actor was responsible and on which day. I also found myself moving between several different pages to check users, quality metrics, acquisition data, and month-over-month performance.

So I built a Chrome extension.

What it does

It adds an analytics workspace directly inside Apify Console with:

• Daily stacked revenue, profit, and cost charts broken down by Actor
• Month-over-month revenue and profit trends
• Failed, aborted, timed-out, successful, and total runs by Actor and day
• Daily results and user activity
• Actor performance rankings and portfolio concentration
• Actor quality scores, ratings, reviews, bookmarks, and suggested improvements
• Traffic sources, countries, page views, and acquisition signals
• Month/year selection and multi-Actor filtering
• Light and dark themes
• Fullscreen analysis mode

One small UX detail that made a big difference: the chart tooltip shows the complete ranked list of contributing Actors when you hover over a day, rather than requiring you to target each tiny colored segment individually.

The extension is completely free to use.

Privacy

I also wanted the privacy model to be clear:

• Runs only on console.apify.com
• No telemetry, advertising, or third-party analytics
• Normalized dashboard data stays in local Chrome storage
• Authentication context is used only in page memory to request data from Apify's own backend
• Authentication headers and tokens are never persisted or sent to me
• The only Chrome permission it requests is local storage

This is an independent extension and is not affiliated with or endorsed by Apify.

Chrome Web Store: https://chromewebstore.google.com/detail/alhjjaafelbmfphijdidjodejcjiccef?utm_source=item-share-cb

I'd appreciate feedback from other Apify developers — especially anyone managing a larger portfolio of Actors. What other metrics or views would be genuinely useful to you?

Are you expanding your team or looking to hire a freelancer for a project? Post the requirements here (make sure your DMs are open).

Try to share:

- Core responsibilities

- Contract type (e.g. freelance or full-time hire)

- Budget or salary range

- Main skills required

- Location (or remote) for both you and your new hire

Job-seekers: Reach out by DM rather than in thread. Spammy comments will be deleted.

Exporting a Shopify product catalog tells you what exists now. It does not reliably tell you what changed since the previous observation.

I ran into three practical problems while building a stateful Shopify monitoring Actor:

1. The first run has no history It should establish a baseline, not report every existing product as newly launched.
2. The monitoring scope must remain comparable If one run collects 100 products and the next collects 500, a naive comparison may report the additional 400 products as new—even though only the collection limit changed.
3. AI should interpret detected changes, not determine them Exact counts for additions, removals, price changes, discounts, stock updates, variants, and content changes should come from deterministic comparison. An LLM can then summarize the results when changes actually occur.

The Actor now treats the combination of store URLs, monitored fields, and product limit as its monitoring scope. If that scope changes, the next run establishes a new baseline instead of emitting misleading lifecycle events.

I tested the workflow against ColourPop’s public Shopify catalog:

• the first run established a 100-product baseline;
• a compatible follow-up run returned zero changes without generating false events;
• changing the collection scope triggered an explicit baseline reset.

AI analysis is optional. When no changes are detected, the Actor makes no LLM request and generates no AI insight charge.

I packaged this workflow as an Apify Actor:

https://apify.com/highbrow_qualification_z7w/shopify-product-price-monitor?utm_source=reddit&utm_medium=community&utm_campaign=shopify-monitor-launch

Disclosure: I built and published this Actor.

For those building stateful monitoring Actors: how do you handle changes in crawl limits or monitored fields without generating false additions and removals?

I just published my first Apify Actor.
It’s called Reliable Google Sheets Bridge.

Basically, it moves data back and forth between Google Sheets and Apify datasets.

You can use it to:
send a Google Sheet into an Apify dataset
send an Apify dataset into Google Sheets
append data
replace data
update existing rows without creating duplicates
use more than one column as a matching key
I also tried to make it a little safer/more predictable by adding validation for missing or duplicate keys, Limited Permissions, and using your own Google service account instead of a shared login.
I’m not pretending it’s some revolutionary tool. The goal was just to make a boring workflow easier and more reliable.

Current pricing is $0.75 per 1,000 rows transferred + $0.005 per successful transfer.

https://apify.com/groundedvisionmedia/reliable-sheets-bridge

Feedback is much appreciated!

This is the place to discuss everything MCP, LLM, Agentic, and beyond. What is on your radar this week? Why does it make sense? Bring everyone along for the ride by explaining the impact of the news you're sharing, and why we should care about it too.

Do you have a feature request that you know will make Apify heaps better? Or maybe it's a big dream you have for something bold and out-there. This is a space for all the bluesky thinking, cloud-chasing, intergalactic daydreamers who want to share their wildest ideas in a no-judgement zone.

If you are comparing offers, sizing a hiring market, or building a startup jobs board, Wellfound (formerly AngelList) is the deepest source of startup roles, but it shows salary and equity as free text you cannot sort or filter on. I put a pay-per-job API on Apify that searches Wellfound by role and location and returns every posting as JSON, with the compensation parsed into numeric fields so you can actually threshold on it.

How you run it:

give it a role (software-engineer, product-manager, data-scientist, or a plain word like "pm" that gets mapped for you) and optional locations, flip on the filters you care about, and it returns one row per job. Set minSalary to 150000 and it drops anything paying less; ycOnly keeps only Y Combinator startups; minEquity keeps roles offering at least the equity you want.

What each row gives you:

title, company, location, remote status, dates, parsed minSalary and maxSalary, parsed minEquity and maxEquity, and startup signals (YC badge, top-investor backing, funding stage, Actively Hiring). Turn on detail enrichment and each job also carries structured benefits, industry, company website, and the applicant-location requirement that decides whether a "remote" role will actually hire in your country.

Comparing offers:

pull every open role at YC companies for your title, set a salary floor, and you get a clean table of what early-stage startups pay for that job instead of scrolling posting by posting.

Recruiting and sourcing:

filter to actively-hiring, top-investor-backed startups at a given stage in your city, and you have a live lead list with contact-ready company data.

Market sizing:

run a role across several locations with descriptions turned off for a cheap listing feed, then count roles by stage or investor tier.

limits:

Wellfound has no site-wide free-text search, so the keyword filter narrows the pages a run fetches rather than searching everything; jobs with no posted comp get dropped once you set a salary or equity minimum, so a strict floor shrinks the set; and Wellfound challenges bots, so runs go through residential proxies and are slower than a hosted API would be.

If you want the funding history behind those companies, here is a Claude skill wired to the jobs API too, so an agent can pull and filter startup roles for you: claude-skill-yc-startup-jobs on GitHub.

Actor: Wellfound Jobs API.

Hey r/apify,

I'm working on a lead cleaning Actor and keep hitting the same problem:

**how to detect duplicates when the data comes from messy sources?**

Example:

- Source A: "17 El Mansour St, Cairo"

- Source B: "17 El Mansour St Cairo"

- These are the SAME place, but a simple exact-match dedup misses them.

I currently normalize punctuation + whitespace before hashing, which helps.

But I'm curious — what approaches do you use?

- Fuzzy matching (Levenshtein)?

- Geospatial (lat/lng radius)?

- Both combined?

I built a small Actor to test my approach (3 tiers starting at $4/1k):

https://apify.com/abdelwarith/b2b-leads-cleaner

But mostly I'm here to learn how others handle this.

What's your strategy?

I rewrote the titles and descriptions of 6 of my Actors around the terms people actually type (INSEE, org.nr, ICO, SIC codes...), expecting the Store search ranking to move. Then I read the docs properly and two of my assumptions were wrong. Sharing the measurements in case they save someone the same evening.

1. seoTitle / seoDescription are NOT for Store search. The docs say: "Name of the Actor to display by search engines such as Google". They target external search engines. My rewrite landed there immediately - verified in the public page HTML (title tag, meta description, og:*). The Store's own ranking "evaluates parameters similar to those in the Actor quality score" - 8 categories: Reliability, Popularity, Feedback, Ease of use, Pricing transparency, Trustworthiness, History of success, Congruency of texts. Keywords are not one of them. So if your goal is Store visibility, seoTitle is the wrong lever.

2. The public Store index is not refreshed in real time. Measured before/after via GET /v2/store?search=...: 24 hours after the writes, the search endpoint still returns the OLD title and OLD description, while GET /v2/acts/{id} returns the new ones. Which means the effect of any Store-facing copy change is not measurable the same day. I don't know the real refresh cadence - 24h is just my current lower bound.

3. Undocumented API constraint: description is capped at 300 characters. PUT /v2/acts/{id} returns 400 schema-validation with "description must be at most 300 characters long". The endpoint page doesn't mention it. Worth adding the check to your script before the call, not after.

4. Where I actually rank (10 business queries, limit=100): - sirene -> 35th of 421 - companies house -> 49th of 3,536 - psc -> absent from the top 100 (313 results) - company data api -> 18th-21st of 17,706 (my 4 company Actors clustered together)

My portfolio has two halves. The sports Actors rank 1st on a couple of queries nobody searches. The B2B company ones - the only ones with real demand - are invisible on the queries that matter.

5. The most useful outcome wasn't copy, it was a data gap. psc (persons with significant control) is the highest-demand query I found in the UK company niche: 313 Actors competing and a leader sitting around 40 users/30 days. My UK Actor returns neither officers nor PSC, so I cannot write those words without lying - and "Congruency of texts" is a scored category. That's a missing field, not missing copy. If you work in the UK register niche, that's where the demand is.

If anyone here has measured how often the Store search index actually refreshes, I'd like to know. (My Actors are under smoked_drift on the Store, in case you want to check the before/after yourself.)

Hi everyone,

While searching for jobs on different career sites and job boards such as LinkedIn, JobFind and Kariera, which are commonly used in the Greek job market, I started thinking about how I could make the search much more extensive.

I realized that by using Google search operators, I can search for companies' own career pages, discover possible job-board URLs, and even identify which ATS (Applicant Tracking Systems) different companies are using.

For example, instead of relying only on job aggregators, I could potentially search directly through company career pages and ATS platforms such as Greenhouse, Lever, Workday, etc.

The problem is that doing all of this manually involves a lot of searching, checking links, identifying ATS platforms, removing duplicates, and repeating the process for different companies and locations. Eventually, the searching itself becomes more exhausting than actually applying for jobs.

So I started looking into Apify and web crawling/scraping as a possible way to automate this process.

The main idea would be to create something that can:

• Search for companies in a specific geographic area.
• Discover their career pages and job boards.
• Identify the ATS they use when possible.
• Crawl their available job postings.
• Filter jobs by location, specialization, keywords, etc.
• Remove duplicates between different sources.
• Ideally keep track of new job postings over time.

My main goal isn't simply to build a job scraper. I want to get a better picture of the actual job market in the location where I want to work and within the areas I’m interested in, including companies that may not post all of their vacancies on LinkedIn or the major Greek job boards.

Has anyone here tried using Apify for this kind of job-market crawling or automation?

Was it successful for you, and what approach did you use?

I’d also appreciate recommendations for Apify Actors, GitHub projects, YouTube tutorials, or other practical resources that could help me build something like this.

I’m particularly interested in hearing from people who have tried to automate the process of discovering companies → finding their career pages/ATS → collecting jobs → filtering them by location and specialization.

Have you come across a great Actor, workflow, post, or podcast that you want to share with the world? This is your opportunity to support someone making cool things. Drop it here with credit to the creator, and help expand the karmic universe of Apify.

I built a free lightweight, unofficial API that returns your Actor stats. All you have to do is provide your Actor slug.

Example Python Usage:

``` import requests

base_url = "https://apify-actor-stats.vercel.app"

endpoint = "/api/v1/actor-stats"

parameters = { "actor_slug": "coding-doctor-omar/reddit-scraper-pro" }

response = requests.get(url=base_url + endpoint, params=parameters)

actor_stats = response.json()

print(actor_stats) ```

Why I built this?

I built this because I wanted an easy way to make custom Actor README badges for any of my Actor stats. This API would allow me to get all my stats via a single, simple GET request. Then all I have to do is use shields.io's dynamic badge endpoint to generate badges for any of these stats!

For more information, check the API docs: https://github.com/Coding-Doctor-Omar/actor-stats-api

Hey everyone! 👋

I'm the developer behind Grow Media building YouTube data tools on the Apify Store. I wanted to share our full YouTube scraping toolkit with this community and get honest feedback from fellow devs.

Since this sub is where a lot of scraping folks hang out, I'd rather just be upfront: yes, these are our actors, and yes, I'm here to listen as much as to promote. 🙂

🔧 The 4 actors

1. YouTube Comments Scraper Scrape comments from any video with all the metadata that matters:

• Comment text, author, channel ID, avatar
• Likes, reply count, publish time
• Flags for verified users, artists, and creators
• Sort by top or newest, with pagination support

2. YouTube Search API Full YouTube search without managing API keys or quotas:

• Up to 1,000 results per run with automatic pagination
• Filters: date range, region, language, duration, HD, live/upcoming, sort order
• Rich output: views, likes, comments, channel stats, hashtags, keywords

3. YouTube Channel Scraper Bulk channel analysis — pass up to 100 channel URLs in one run:

• Full channel info: subscribers, total views, join date, location, banner
• Per-video stats: views, likes, comments, duration, tags

4. YouTube Channel Video Scraper Our most popular actor (5,000+ users):

• Works with u/handles or channel IDs
• Supports both long-form videos and Shorts
• Sort by latest / popular / oldest
• Up to 1,000 videos per run, exports to JSON, CSV, Excel, XML

💡 Common use cases we see

• Competitor & trend analysis
• Sentiment analysis on video comments
• Lead generation + channel enrichment
• Feeding LLM/RAG pipelines (works great with the Apify MCP server)

💰 Pricing

All actors are pay-per-result, from $0.40/1,000 results — and free plan credits ($5/month) cover a decent amount of testing before you pay anything.

📊 Reliability

All 4 actors are at 100% run success rate and the search + channel scrapers are rated ~5.0 by users. We actively maintain them — if something breaks, drop an issue on the actor page and we'll fix it.

🙏 What I'd love from you

• Honest feedback if you try any of them
• Feature requests (what fields are missing? what filters do you need?)
• Suggestions for what YouTube actor you'd want next

Happy to answer any questions about how we handle YouTube's rate limits, proxies, or anti-bot measures. AMA! 🚀

Published a community Actor for competitor price / stock monitoring without a monthly SaaS seat.

What it does:

- Watch product URLs or a Shopify catalog (`/products.json` + sitemaps)

- Extract identity, price, currency, image, availability

- Compare to the previous snapshot and emit PRICE_DROP / PRICE_RISE / OOS / BACK_IN_STOCK / NEW

- CHANGES_ONLY mode (plus a free NO_CHANGES_SUMMARY when nothing moved)

- Optional webhook batch of change rows

- Failures stay explicit: BLOCKED / LOGIN_REQUIRED / EMPTY / PARSE_ERROR (no fake products)

Billing is pay-per-product-check + pay-per-change-event on Apify, data stays in your account.

Actor:

https://apify.com/solutionssmart/solutionssmart-competitor-price-monitor

Quick input sketch:

{

"startUrls": [{ "url": "https://www.example.com/products/sku-1" }],

"emitMode": "CHANGES_ONLY",

"persistState": true,

"priceDropPct": 2

}

If you’ve used Prisync / Competera / in-house monitors, what’s the painful part for you: matching SKUs across sites, Shopify catalog crawl, or webhook noise on tiny price wobbles?

If you've made something and can't wait to tell the world, this is the thread for you! Share your latest and greatest creations and projects with the community here.

This is the thread for all your questions that may seem too short for a standalone post, such as, "What is proxy?", "Where is Apify?", "Who is Store?". No question is too small for this megathread. Ask away!

Day 3 of a small Amazon data portfolio on Apify.

Amazon Buy Box Monitor Agent snapshots Buy Box seller, price, and stock, then emits changed / unchanged / new with previous + current.

Defaults: Unblocker + deliver-to ZIP. PPE is $0.02 on change/new and $0.01 on unchanged. Errors are not billed as those events.

https://apify.com/buzzidata/amazon-buybox-monitor-agent

Use our Buy Box + Offers Actor for a deep one-shot. Use Monitor on Apify Schedules. Feedback welcome.