DEV Community: Charbel Daccache

Find TikTok Shop creators to seed your product (with their emails, in Python)

Charbel Daccache — Thu, 12 Nov 2026 14:00:00 +0000

If you sell physical products, the creators posting "TikTok made me buy it" videos are the people you want reviewing your stuff. Most of them never apply to affiliate programs, so you have to find them and email them. This post builds that list with a few lines of Python: creators who post product finds, their contact email, and enough stats to rank them.

Disclosure: I built the TikTok scraper used in this post.

Build the list

The TikTok Profile Scraper & Influencer Email Finder on Apify searches TikTok by keyword, reads each creator's profile and link-in-bio page, and keeps only the ones who publish an email.

pip install apify-client

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("scrape-lads/tiktok-profile-scraper").call(run_input={
    "searchKeywords": ["tiktok shop finds", "tiktok made me buy it", "amazon finds"],
    "onlyWithEmail": True,   # creators without an email are skipped and not charged
    "minFollowers": 5000,
    "maxResults": 100,
})
creators = list(client.dataset(run["defaultDatasetId"]).iterate_items())

Rank and export for your outreach tool

import csv

creators.sort(key=lambda c: c["followers"] or 0)  # smaller creators first: cheaper and more replies

with open("tiktok_shop_creators.csv", "w", newline="", encoding="utf-8") as f:
    w = csv.writer(f)
    w.writerow(["username", "followers", "email", "email_found_in", "tiktok_shop", "instagram", "profile"])
    for c in creators:
        w.writerow([c["username"], c["followers"], c["contactEmail"], c["contactEmailSource"],
                    c["tiktokShopSeller"], c["instagramUrl"], c["profileUrl"]])

Import the CSV into whatever you send with (Instantly, Lemlist, a Google Sheet plus mail merge).

What a real run looked like

A test run with the first two keywords, no follower filter and 25 results:

113 creators checked, 25 with a public email (22%). The other 88 cost nothing.
10 of the 25 emails came from the link-in-bio page, not the bio itself. If you only read bios, you miss 40% of the list.
Median audience around 68,000 followers, from 2,700 to 2.2 million.
Only 2 of the 25 had TikTok Shop seller status. Most product-finds creators are affiliates and reviewers, not shop owners. For seeding that's what you want; filter on tiktokShopSeller if you're after shops instead.

Tips

Mix "finds" keywords with your category ("kitchen gadgets finds", "skincare tiktok shop") to stay on-niche.
Use maxFollowers to keep the list to micro creators if your budget is free product rather than paid posts.
contactEmailSource tells you whether the address came from the bio or the link page, which helps when you personalize the first line.

These are public business contacts, but keep outreach relevant, honor opt-outs and follow the email rules where you and the creators are.

How to Scrape Reddit Posts and Comments Without the Reddit API (with Python)

Charbel Daccache — Tue, 10 Nov 2026 14:00:00 +0000

To scrape Reddit without the official API, read Reddit's public pages the way a logged-out visitor does: subreddit feeds, search results, user profiles and post threads. This guide shows how to do that with one API call and get posts, full comment threads, communities and users as clean JSON, with no API key, no OAuth app and no developer account.

This is part 4 of "How my fun projects turned into APIs". Each post takes one side project, explains how it works, and ends with something you can call from your own code. Part 1 covered finding TikTok creator emails, part 2 video transcripts, and part 3 recipes from cooking videos.

Why scraping Reddit got harder
How the Reddit scraper works
How to scrape Reddit in 4 steps
How to scrape Reddit with Python
How to scrape Reddit with JavaScript
What data you get from Reddit
How to find SaaS ideas on Reddit with AI tags
How much it costs
FAQ

Why scraping Reddit got harder

Reddit used to be the easiest site on the internet to get data from: add .json to a URL, or register a free API app. That changed:

Reddit's Data API now needs an approved app, has strict rate limits, and charges for commercial use.
Self-service API keys were closed in 2025.
Most old Reddit scraping tutorials and libraries rely on access that no longer works.

The project that started it

After three side projects, I had a different problem: I didn't know what to build next. The best ideas usually come from people describing a real problem in their own words, and the place they do that most is Reddit. Posts like "is there a tool that...", "alternative to X" and "I'd pay for something that...".

My plan was simple: search Reddit for those phrases across a few niches, read the threads, and make a list of problems people would pay to solve. Doing that by hand took an evening per niche, and the official API route meant applying for access and waiting.

So I wrote a scraper that reads the same public pages any logged-out visitor sees. First subreddit feeds, then keyword search, then full comment threads, because the best details are always in the replies. Then I added keyword filters to cut the noise, and finally AI tags that mark each post with its pain point, whether the person asks for a recommendation, and whether they say they'd pay.

The list of ideas was useful. The scraper was more useful, so I made it a public API.

How the Reddit scraper works

The tool is an Apify Actor called Reddit Scraper. It reads Reddit as a logged-out visitor, so it needs no login, no Reddit API key and no OAuth app.

It accepts four kinds of input:

Input	Example	What you get
Subreddit	`r/startups`, `reddit.com/r/startups/top/?t=month`	Posts in Hot, New, Top, Rising or Controversial order
Keyword search	`best crm for startups`	Matching posts from all of Reddit or one subreddit
User profile	`u/spez`	The user's posts
Post URL	`reddit.com/r/x/comments/abc123/...`	One post with its full comment thread

Keyword searches can also return comments, communities and users. Every post can bring its comments, with reply depth and parent ID, so you can rebuild the whole thread.

How to scrape Reddit in 4 steps

Create a free Apify account. Runs on the free plan work within the monthly credit.
Open Reddit Scraper and click Try for free.
Paste this input (switch the input editor to JSON):

{
  "searchTerms": ["best crm for small business"],
  "searchSort": "top",
  "time": "year",
  "searchFullPosts": true,
  "maxPostsPerSource": 50,
  "maxCommentsPerPost": 30
}

Click Start. Export the results as JSON, CSV or Excel, or read them through the API.

To get the top posts of a subreddit instead:

{
  "startUrls": ["https://www.reddit.com/r/startups/top/?t=month"],
  "maxPostsPerSource": 100,
  "skipStickied": true
}

How to scrape Reddit with Python

Install the client with pip install apify-client, then:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("scrape-lads/reddit-scraper").call(run_input={
    "searchTerms": ["notion", "obsidian"],
    "searchSort": "new",
    "postedAfter": "7 days",
    "maxPostsPerSource": 100,
    "maxCommentsPerPost": 20,
})

for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    if row["dataType"] == "post":
        print(f"[{row['score']}] r/{row['subreddit']}: {row['title']}")
    elif row["dataType"] == "comment":
        print("   ", row["body"][:100])

Your API token is in Apify Console under Settings → API & Integrations.

How to scrape Reddit with JavaScript

Install the client with npm install apify-client, then:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('scrape-lads/reddit-scraper').call({
  startUrls: ['https://www.reddit.com/r/SaaS/top/?t=month'],
  maxPostsPerSource: 50,
  maxCommentsPerPost: 10,
  commentSort: 'top',
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
const posts = items.filter((r) => r.dataType === 'post');
posts.forEach((p) => console.log(p.score, p.numComments, p.title));

What data you get from Reddit

Each row has a dataType: post, comment, community or user. A real post:

{
  "dataType": "post",
  "id": "1x4jwxm",
  "url": "https://www.reddit.com/r/tifu/comments/1x4jwxm/tifu_by_asking_my_coworker_about_her_kindle_that/",
  "title": "TIFU by asking my coworker about her Kindle that died",
  "author": "v-fee",
  "subreddit": "tifu",
  "createdAt": "2026-10-13T01:35:57.185Z",
  "score": 7296,
  "upvoteRatio": 0.98,
  "numComments": 273,
  "postType": "text"
}

A real comment:

{
  "dataType": "comment",
  "postId": "1qqxvlw",
  "parentId": "t3_1qqxvlw",
  "depth": 0,
  "author": "arlaneenalra",
  "body": "It's called a \"perishable skill\" you have to use it or you lose it.",
  "score": 1479,
  "createdAt": "2026-01-30T06:36:11.512Z"
}

Group	Fields
Posts	`title`, `body`, `author`, `subreddit`, `score`, `upvoteRatio`, `numComments`, `flair`, `postType`, `link`, `images`, `videoUrl`, `createdAt`
Comments	`body`, `author`, `score`, `postId`, `parentId`, `depth`, `createdAt`
Communities	`name`, `description`, `weeklyVisitors`, `weeklyContributions`
Users	`username`, `description`, `karma`

How to find SaaS ideas on Reddit with AI tags

This is the part I built the scraper for. Search for phrases people use when they need a tool, search comments too, and turn on AI tags:

{
  "searchTerms": ["looking for a tool", "is there an app that", "alternative to quickbooks"],
  "searchComments": true,
  "aiTagging": true,
  "maxPostsPerSource": 100
}

Every post and comment then gets tags like these (a real example):

{
  "aiTags": {
    "painPoint": "Auto reconciliation with QuickBooks was horrendous, manual fixes",
    "asksForRecommendation": false,
    "willingToPay": false,
    "featureRequest": "AI agent resolving transaction issues",
    "productsMentioned": ["Alternative Payments", "QuickBooks Premier", "FlexPoint"],
    "sentiment": "mixed"
  }
}

Filter the dataset on aiTags.willingToPay or aiTags.asksForRecommendation, and you have a list of people asking for what you might build. The tags are for sorting large lists, so spot-check the rows you act on.

How much it costs

$1 per 1,000 posts
$0.50 per 1,000 comments
$1 per 1,000 communities or users
+$1 per 1,000 for full text on search results, and +$1 per 1,000 for AI tags
$0.003 per run
Rows removed by your filters, and duplicates, are never charged

Example: 100 posts with 50 comments each (5,000 comments) cost about $2.60, or about $7.70 with AI tags.

FAQ

Can I scrape Reddit without an API key?

Yes. The scraper reads the public pages any logged-out visitor sees, so it needs no API key, OAuth app or developer account.

Does Reddit have an official API? Why not use it?

Reddit's Data API needs an approved app, has strict rate limits, and charges for commercial use. Self-service keys were closed in 2025. Scraping public pages avoids the approval process, and you pay only for the posts and comments you collect.

How many posts can I get from a subreddit?

Reddit lists up to about 1,000 posts per feed or search. To go further, combine sorts and time ranges (Top of the year, Top of the month, New), or schedule runs to collect new posts over time.

Can I scrape Reddit comments by keyword?

Yes. Set searchComments to true with your keywords. Comment search results include the full comment text and the post they belong to.

How do I monitor Reddit for my brand?

Search your brand name with searchSort: "new", turn on comment search, set postedAfter to 1 day, and schedule the run daily. Send new rows to Slack or Google Sheets with an Apify integration.

Is it legal to scrape Reddit?

The scraper collects only public posts and comments that any logged-out visitor can see. You are responsible for using the data in line with Reddit's terms and privacy laws such as GDPR.

Try it

Reddit Scraper: apify.com/scrape-lads/reddit-scraper
All my scrapers and APIs: scrapelads.com

Next in the series: remember the pet gear site from part 1? It needed live Amazon prices. Part 5 is the Amazon product scraper that keeps it up to date.

How to find local businesses without a website (Google Maps + Python)

Charbel Daccache — Sat, 07 Nov 2026 14:00:00 +0000

If you build websites for local businesses, the best prospects are easy to describe and annoying to find: a plumber with 200 good reviews and no website, a dentist whose site shows "Account Suspended", a roofer whose site still says © 2016 and doesn't work on a phone.

Google Maps lists all of them. Finding them by hand means opening every listing, clicking every website link and judging each site yourself. That's an evening per dozen businesses.

Here is how to do it in one run, with the reason attached to each business.

Disclosure: I build scrapers on Apify, including the Google Maps Scraper used below.

The idea

Pull every business of a type in a few ZIP codes from Google Maps.
Open each business's website and check it.
Keep the ones with a real problem: no website, a site that's down or suspended, no mobile version, no HTTPS, or a copyright notice five or more years old.

The tricky part is step 2. A naive check produces false alarms that would embarrass you in a cold email. Some examples I hit while building it:

Cloudflare answers HTTP 520 to cloud servers for sites that load fine at home. In one test run, 10 of 10 sites that looked "down" from a server were fine from a home connection.
A broken deep link isn't a broken site. Google listings often link to /contact/?utm_source=.... That page can 404 while the homepage works.
"© 2015" in the page source can come from a CSS library's license comment (animate.css has one), not from the site's footer.
One site that sends bytes forever can stall a whole scraper if every read doesn't have a hard deadline.

So the rules are strict. A site counts as down only after two failed tries and only if its homepage fails too. Bot walls and 520s are "unknown" and never claimed. Copyright years are read from the visible page only.

Running it

I'll use the Google Maps Scraper on Apify. No Google API key.

pip install apify-client

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("scrape-lads/google-maps-scraper").call(run_input={
    "searchTerms": ["plumber", "roofing contractor"],
    "locations": ["75201", "75204", "75206", "75214"],  # Dallas ZIP codes
    "websiteFilter": "needsWork",   # only businesses that need website work
    "scrapeContacts": True,         # emails from the business's own site
    "minReviews": 10,               # skip brand-new listings
})

for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row["name"], row.get("phone"), row["websiteStatus"], row["websiteIssues"])

websiteFilter: "needsWork" switches the website check on by itself. Each row comes back like this (made-up business, real shape):

{
  "name": "Prairie Roof Co.",
  "category": "Roofing contractor",
  "phone": "(214) 555-0163",
  "rating": 4.7,
  "reviewCount": 88,
  "website": "http://prairieroof.example/",
  "emails": [],
  "websiteStatus": "down",
  "websiteIssues": ["website is down: domain does not resolve"],
  "needsWebsiteWork": true
}

websiteStatus is one of ok, down, no-website or unknown. For ok sites, websiteIssues lists what's wrong: no HTTPS, no viewport tag, old copyright year, no contact form, no tap-to-call link, built with Wix or GoDaddy.

What a real run looks like

I ran 400 places (roofing and HVAC contractors in Dallas and Phoenix):

57 places (14%) needed website work
34 had no website at all
5 had a site that was down: four dead domains and one "Database Error" page, all confirmed by hand afterwards
18 had a working site with a strong problem, mostly an old copyright year or no HTTPS

So expect roughly 5 to 15% of a search to qualify. Google Maps returns about 120 to 200 places per search, so use several ZIP codes and two or three related business types to build a decent list.

Turning it into outreach

The reason is the opener. "Your website link on Google shows Account Suspended" gets a reply. "Do you need a new website?" doesn't.

A few practical notes:

Businesses with no website usually have no email (there's no site to find one on). Call them, or find their Facebook page.
emails only holds addresses on the business's own domain, or that clearly belong to it. Site footers often carry the web designer's address or a template placeholder, and those are dropped.
Cold outreach is regulated: CAN-SPAM in the US, GDPR in Europe. Keep it relevant and personal.

Cost

Pay per result: $1 per 1,000 places, plus $1 per 1,000 websites checked and $1 per 1,000 places with an email. Places the filter removes and sites it couldn't check are free. A list of 1,000 businesses that need website work costs about $2, and the Apify free plan's monthly credit covers a first test.

There's also a step-by-step guide with a ready-made input you can paste.

How to get YouTube transcripts in bulk without getting IP-blocked

Charbel Daccache — Thu, 05 Nov 2026 14:00:00 +0000

If you've used youtube-transcript-api from a laptop, it works. Put the same script on a server or run it over a few hundred videos and you start seeing RequestBlocked or IpBlocked. YouTube rate-limits caption requests per IP, and cloud IPs are blocked almost on sight.

You have three ways out:

Rotate residential proxies yourself. Works, but now you maintain a proxy pool, retries and a queue.
The official YouTube Data API. It only returns captions for videos you own, so it doesn't help here.
Use a hosted scraper that already handles the proxies. That's what this post shows.

Disclosure: I build scrapers on Apify, including the YouTube Transcript Scraper used below.

Getting transcripts for a list of videos

I'll use the YouTube Transcript Scraper on Apify. It takes any number of video URLs (or a channel URL) in one run and returns one row per video: the full transcript, timestamped segments, language and stats. No YouTube API key.

Install the client:

pip install apify-client

Then:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("scrape-lads/youtube-transcript-scraper").call(run_input={
    "urls": [
        "https://www.youtube.com/watch?v=aircAruvnKk",
        "https://www.youtube.com/watch?v=arj7oStGLkU",
        "https://youtu.be/dQw4w9WgXcQ",
    ],
    "includeSegments": True,
})

for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    if row["status"] == "success":
        print(row["title"], row["wordCount"], row["language"])
        print(row["transcript"][:200], "...")

Each row looks like this (trimmed):

{
  "url": "https://www.youtube.com/watch?v=aircAruvnKk",
  "status": "success",
  "title": "But what is a neural network? | Deep learning chapter 1",
  "language": "en",
  "transcriptSource": "subtitles",
  "wordCount": 3357,
  "transcript": "This is a 3. It's sloppily written ...",
  "segments": [{ "start": 4.2, "end": 5.4, "text": "This is a 3." }]
}

A whole channel

Swap urls for profiles and set how many of the newest videos you want:

run_input = {
    "profiles": ["https://www.youtube.com/@veritasium"],
    "maxVideosPerProfile": 25,
    "includeSegments": False,
}

Add "postedWithinDays": 7 and put it on a weekly schedule if you only want new uploads.

Subtitle files

"outputFormats": ["srt", "vtt"] adds ready-made SRT and WebVTT text to each row, which is handy for editors and translation tools.

What it doesn't do

It reads YouTube's own captions (creator-uploaded first, then auto-generated). Videos with no captions at all can only be transcribed when they're very short, because YouTube serves full audio only to signed-in players. Those rows come back as failed and aren't charged.
Private, members-only and deleted videos can't be read.

Cost

Pay per transcript, a fraction of a cent each, and failed or empty rows are free. The Apify free plan's monthly credit covers a few thousand transcripts, so you can test it on real data before paying anything.

If you're building a RAG pipeline or summarizing videos with an LLM, setting includeSegments to False gives you clean text that you can chunk straight away.

How to Extract a Recipe from a TikTok or Instagram Video as JSON (with Python)

Charbel Daccache — Tue, 03 Nov 2026 14:00:00 +0000

To extract a recipe from a TikTok, Instagram Reel or YouTube video, combine the caption, the spoken words and any recipe page the creator links to, then have an AI model turn them into structured ingredients and steps. This guide shows how to do that with one API call and get back clean recipe JSON: ingredients split into quantity, unit and item, numbered steps, times and servings.

This is part 3 of "How my fun projects turned into APIs". Each post takes one side project, explains how it works, and ends with something you can call from your own code. Part 1 covered finding TikTok creator emails, and part 2 covered video transcripts.

Why saving recipes from videos is so annoying
How the recipe extractor works
How to extract a recipe from a video in 4 steps
How to extract recipes with Python
How to extract recipes with JavaScript
What the recipe JSON looks like
How much it costs
FAQ

Why saving recipes from videos is so annoying

Short cooking videos are where a lot of people find recipes now. Saving one is still a mess:

The caption says "recipe in the comments" or "comment RECIPE and I'll DM you".
The amounts are only spoken, quickly, once.
Sometimes the full recipe is on the creator's blog, behind a link in the caption.
You end up pausing the video and typing it out by hand.

Every recipe and meal-planning app wants a "save from TikTok" button, and every one of them has to solve this.

The project that started it

In part 2 I built a transcript tool for a small study comparing TikTok recipes with the classic versions of the same dishes. The transcripts gave me the words, but a wall of text isn't a recipe. To compare dishes, I needed ingredients as data: "2 cups flour, sifted" as quantity 2, unit cup, item flour, note sifted.

So I fed the transcript and caption to an AI model and asked for structured JSON. The first version worked, and also made things up. When a creator said "a bit of salt", the model would sometimes write "1 tsp salt" as if it were a fact.

That led to the two rules the tool still follows. First, if the creator links a written recipe, read that page and use its exact amounts. Second, every ingredient must be backed by a quote from the source, and anything the source never states is flagged as inferred with low confidence.

By the end of the study I had a pipeline that turned any cooking video into reliable recipe JSON. That's exactly what recipe apps need, so I made it a public API.

How the recipe extractor works

The tool is an Apify Actor called Recipe Extractor. It works with TikTok videos, Instagram Reels, YouTube videos and Shorts, and regular recipe websites.

1. It collects every signal

For each URL it gathers the caption, the platform's own subtitles (TikTok speech-to-text, YouTube captions), any recipe page linked in the caption, and the video's cover image.

2. Exact recipes win

Many creators link the full written recipe. When they do, Recipe Extractor follows the link and reads the site's schema.org recipe data, so amounts are exact rather than guessed from speech. Those rows come back with method: "jsonld".

3. An AI model merges the rest

When there is no written recipe, an AI model (DeepSeek V4 Flash by default, Claude optional) merges the signals into one recipe. Each ingredient gets a confidence score and the source it came from, so your app can trust the exact amounts and send guesses to a quick human check.

4. You only pay for real recipes

Videos that aren't recipes, "comment RECIPE" videos with no recipe in them, and failed URLs are returned with a clear status and are free.

How to extract a recipe from a video in 4 steps

Create a free Apify account. The free plan's credit covers your first recipes.
Open Recipe Extractor and click Try for free.
Paste this input (switch the input editor to JSON):

{
  "urls": [
    "https://www.tiktok.com/@recipes/video/7447547249720053000",
    "https://www.instagram.com/reel/Dd-VQPnRz0t/",
    "https://youtube.com/shorts/PM4lHUNQSvY"
  ],
  "units": "metric",
  "includeNutrition": true
}

Click Start. Each URL becomes one row, usually within 10 to 30 seconds. Export the results as JSON, CSV or Excel, or read them through the API.

How to extract recipes with Python

Install the client with pip install apify-client, then:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("scrape-lads/recipe-extractor").call(run_input={
    "urls": ["https://www.instagram.com/reel/Dd-VQPnRz0t/"],
    "units": "metric",
})

for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    if row["status"] != "success":
        print(row["inputUrl"], row["status"])
        continue
    recipe = row["recipe"]
    print(recipe["title"], "-", recipe["servings"], "servings")
    for ing in recipe["ingredients"]:
        print(" ", ing["quantity"], ing["unit"], ing["item"], f"({ing['confidence']})")

Your API token is in Apify Console under Settings → API & Integrations.

How to extract recipes with JavaScript

Install the client with npm install apify-client, then:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('scrape-lads/recipe-extractor').call({
  urls: ['https://youtube.com/shorts/PM4lHUNQSvY'],
  units: 'us',
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
for (const row of items) {
  if (row.status !== 'success') continue;
  console.log(row.recipe.title);
  row.recipe.steps.forEach((s) => console.log(`${s.n}. ${s.text}`));
}

What the recipe JSON looks like

One row per URL. A shortened real result for an Instagram Reel whose creator linked their blog:

{
  "inputUrl": "https://www.instagram.com/reel/Dd-VQPnRz0t/",
  "status": "success",
  "recipe": {
    "title": "Spaghetti Squash Lasagna",
    "servings": 4,
    "times": { "prepMin": 10, "cookMin": 60, "totalMin": 70 },
    "ingredients": [
      {
        "raw": "1 pound lean ground beef",
        "quantity": 1,
        "unit": "lb",
        "item": "lean ground beef",
        "converted": { "quantity": 454, "unit": "g" },
        "confidence": 0.99,
        "source": "linked_recipe_page"
      }
    ],
    "steps": [
      { "n": 1, "text": "Preheat the oven to 400ºF.", "timestampSec": null }
    ],
    "cuisine": "Italian",
    "dietary": ["gluten-free"],
    "nutrition": { "estimated": false, "calories": 513, "proteinG": 34 }
  },
  "source": {
    "platform": "instagram",
    "author": "feelgoodfoodie",
    "linkedRecipeUrl": "https://feelgoodfoodie.net/recipe/spaghetti-squash-lasagna-boats/"
  },
  "overallConfidence": 0.99,
  "method": "jsonld"
}

Field	What it is
`recipe.ingredients[]`	`quantity`, `quantityMax` (ranges), `unit`, `item`, `note`, `optional`, `converted`, `confidence`, `source`
`recipe.steps[]`	Numbered steps, with `timestampSec` showing where each happens in the video
`recipe.times`, `recipe.servings`	Prep, cook and total minutes; servings as a number
`recipe.tags`, `cuisine`, `dietary`	For filtering and search
`recipe.nutrition`	Per serving; `estimated: true` when computed from ingredients
`status`	`success`, `incomplete`, `not_a_recipe` or `failed`
`method`	`jsonld` (exact written recipe) or `llm` (merged by the model)

Options worth knowing

units: original, metric or us, for grocery lists without your own conversion code.
translateTo: write the recipe in another language, for example English.
includeNutrition: per-serving calories and macros.
followRecipeLinks: read the written recipe linked from the caption (on by default, and worth keeping on).

How much it costs

$0.03 per successful recipe ($30 per 1,000)
$0.002 per run
Failed URLs, non-recipe videos and incomplete recipes are free
Higher Apify plans get volume discounts down to $0.018 per recipe

Example	Cost
1 TikTok recipe	$0.032
100 Instagram Reels, 60 of them full recipes	$1.80
1,000 YouTube recipe videos	about $30

FAQ

How do I save a recipe from TikTok?

Paste the TikTok link into the extractor. It reads the caption, TikTok's subtitles and any linked recipe page, and returns the recipe as structured JSON you can store in your app or a spreadsheet.

Can it get recipes from Instagram Reels?

Yes. Instagram publishes no subtitles, so Reels are read from the caption, linked recipe pages and the cover image. Reels whose recipe is only spoken come back as incomplete and are free.

What happens with "comment RECIPE" videos?

If the recipe isn't in the video's content, there's nothing to extract. The row comes back as incomplete, says so, and isn't charged.

Does it invent ingredient amounts?

Each ingredient must be backed by a quote from the source. Anything the source never states is flagged as inferred with low confidence, so your app can show it to the user for a quick check.

Is there an official API for recipes from TikTok or Instagram?

No. No platform offers an API that returns a recipe from a video. Their APIs give captions or metadata at best, and only to approved apps.

Does it download the videos?

No. It reads the public caption, public subtitles, linked pages and the cover image. It doesn't download or redistribute video.

Try it

Recipe Extractor: apify.com/scrape-lads/recipe-extractor
All my scrapers and APIs: scrapelads.com

Next in the series: after three side projects, I wanted to know what to build next, so I went looking for people asking for tools on Reddit. Part 4 is the Reddit scraper that came out of that.

How to Get a Transcript of a TikTok, Instagram Reel or YouTube Short (with Python)

Charbel Daccache — Tue, 27 Oct 2026 13:00:00 +0000

To get a transcript of a TikTok, Instagram Reel, YouTube Short or X video, read the platform's own subtitles when they exist, and transcribe the audio with speech-to-text when they don't. This guide shows how to do both automatically with one API call, for a list of links or a creator's latest videos, and get back clean text with timestamps.

This is part 2 of "How my fun projects turned into APIs". Each post takes one side project, explains how it works, and ends with something you can call from your own code. Part 1 covered finding TikTok creator emails.

Why short video transcripts are hard to get
How the video transcript scraper works
How to get a video transcript in 4 steps
How to get TikTok and Instagram transcripts with Python
How to get video transcripts with JavaScript
What data you get for each video
How much it costs
FAQ

Why short video transcripts are hard to get

For long YouTube videos, transcripts are easy: there's a button. For short-form video, every platform is different:

TikTok has captions on some videos and none on others.
YouTube Shorts usually have auto-captions, but there's no easy way to pull them in bulk.
Instagram Reels publish no subtitles at all.
X (Twitter) videos publish none either.

So you end up with four tools, four formats, and a lot of copy-paste.

The project that started it

After the pet site from part 1, my next weekend project was a small data study: do TikTok recipes actually match the classic versions of the same dishes on big recipe sites? I wanted to compare ingredients and steps across a few hundred cooking videos.

The captions were useless for that. Half of them said "recipe in the comments" or just listed hashtags. The real recipe was in what the creator said. So I needed what was spoken in each video, as text, for TikTok, Reels and Shorts at once.

I started with TikTok's own captions, which were fast and free when they existed. Then I hit the first Instagram Reel and found there were no captions to read. So I added a fallback: download the audio and run it through Whisper speech-to-text. Then I added YouTube, then X, and put everything in the same output format.

When the study was done, the transcript tool was more useful than the study. So I turned it into a public API.

How the video transcript scraper works

The tool is an Apify Actor called Video Transcript Scraper. It reads public videos as a logged-out visitor, so it needs no account, no cookies and no API key for any platform.

1. Platform subtitles first

TikTok captions and YouTube captions are the cheapest and most accurate source, because the creator or the platform already did the work. When they exist, the scraper uses them. Each row says whether the subtitles were written by the creator (creator) or generated by the platform (auto).

2. Whisper speech-to-text as the fallback

When a video has no subtitles (every Instagram Reel, X videos, and TikToks without captions), the scraper transcribes the audio with Whisper large-v3 turbo. It handles 90+ languages and is very accurate on clear speech. Every row says which method was used in transcriptSource, so you always know where the text came from.

3. Videos by link or by creator

You can paste video links, or paste a creator's profile and take their latest videos. That makes it easy to transcribe a creator's whole recent output in one run.

How to get a video transcript in 4 steps

Create a free Apify account. The free plan's monthly credit covers hundreds of transcripts.
Open Video Transcript Scraper and click Try for free.
Paste this input (switch the input editor to JSON):

{
  "urls": [
    "https://www.tiktok.com/@garyvee/video/7696603359335288078",
    "https://www.instagram.com/reel/Dd-VQPnRz0t/",
    "https://www.youtube.com/shorts/aNI2jv7lBPQ"
  ],
  "speechToText": "fallback",
  "includeSegments": true
}

Click Start. A few videos take seconds. Export the results as JSON, CSV or Excel, or read them through the API.

To transcribe a creator's latest videos instead, use profiles:

{
  "profiles": ["https://www.tiktok.com/@garyvee", "https://www.youtube.com/@MrBeast/shorts"],
  "maxVideosPerProfile": 10,
  "speechToText": "fallback"
}

How to get TikTok and Instagram transcripts with Python

Install the client with pip install apify-client, then:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("scrape-lads/video-transcript-scraper").call(run_input={
    "urls": [
        "https://www.tiktok.com/@garyvee/video/7696603359335288078",
        "https://www.instagram.com/reel/Dd-VQPnRz0t/",
    ],
    "speechToText": "fallback",
})

for video in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(video["platform"], video["transcriptSource"])
    print(video["transcript"][:200], "\n")

Your API token is in Apify Console under Settings → API & Integrations.

How to get video transcripts with JavaScript

Install the client with npm install apify-client, then:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('scrape-lads/video-transcript-scraper').call({
  profiles: ['https://www.tiktok.com/@garyvee'],
  maxVideosPerProfile: 5,
  speechToText: 'fallback',
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((v) => console.log(v.url, v.wordCount, v.transcript.slice(0, 120)));

What data you get for each video

One row per video, in the same format for all four platforms. A real result for an Instagram Reel:

{
  "url": "https://www.instagram.com/reel/Dd-VQPnRz0t/",
  "platform": "instagram",
  "status": "success",
  "author": "feelgoodfoodie",
  "durationSec": 30,
  "language": "en",
  "transcript": "If you want an easier way to cut spaghetti squash, microwave it first for three minutes. Then it's so much easier to cut in half...",
  "segments": [
    { "start": 0, "end": 2.5, "text": "If you want an easier way to cut spaghetti squash," },
    { "start": 2.5, "end": 4.4, "text": "microwave it first for three minutes." }
  ],
  "wordCount": 100,
  "transcriptSource": "speech-to-text",
  "stats": { "views": 171362, "likes": 2831, "comments": 357, "shares": null }
}

Field	What it is
`transcript`	The full transcript as one text
`segments`	`{ start, end, text }` with times in seconds
`transcriptSource`	`subtitles` (platform captions) or `speech-to-text` (Whisper)
`subtitleKind`	`creator` or `auto`
`language`	Two-letter language of the transcript
`author`, `caption`, `durationSec`, `publishedAt`	Video details
`stats`	Views, likes, comments and shares, when the platform shows them
`status`, `errorCode`	`success`, `no_transcript` or `failed`, with a reason

What people use it for

AI and RAG: feed creator videos into a knowledge base or a custom GPT.
Content research: see what top creators actually say in their hooks and calls to action.
Repurposing: turn short videos into blog posts, newsletters and captions.
Brand monitoring: search spoken mentions of products or competitors.

How much it costs

You pay per transcript, with no subscription:

$2 per 1,000 subtitle transcripts (TikTok and YouTube videos with captions)
$5 per 1,000 speech-to-text transcripts (Reels, X videos, videos without captions), covering the first minute of audio. Longer videos add $0.0025 per extra minute.
$0.005 per run
Failed, private, removed and silent videos are free

Example: 1,000 TikTok transcripts plus 1,000 Instagram Reels under a minute cost about $7.

FAQ

How do I get the transcript of an Instagram Reel?

Instagram doesn't publish subtitles for Reels, so the only way is to transcribe the audio. Paste the Reel link into the scraper and leave speech-to-text on "fallback". It returns the spoken text with timestamps.

Can I get a transcript of a TikTok video?

Yes. If the TikTok has captions, the scraper reads them directly. If it doesn't, it transcribes the audio with Whisper. Either way you get the same output format.

Is there an official API for TikTok or Instagram transcripts?

No. TikTok, Instagram and X have no public transcript API, and YouTube's Data API only lets video owners download captions. This scraper reads public subtitles where they exist and transcribes the speech where they don't.

Which languages are supported?

Whisper handles 90+ languages. Set the language field (for example es) to pick a specific subtitle track or help Whisper with a less common language.

Which videos can't be transcribed?

Private, deleted and age-restricted videos. Music-only videos come back as no_speech. None of these are charged.

Is it legal to scrape video transcripts?

The scraper only reads public videos anyone can watch without logging in. You are responsible for how you use the text: respect copyright and platform terms, and don't republish creators' content without permission.

Try it

Video Transcript Scraper: apify.com/scrape-lads/video-transcript-scraper
All my scrapers and APIs: scrapelads.com

Next in the series: the transcripts gave me the words, but I still had to turn them into actual recipes. Part 3 is about the tool that does that: video in, structured recipe JSON out.

How to Find TikTok Influencer Emails by Niche (with Python)

Charbel Daccache — Sat, 24 Oct 2026 20:32:02 +0000

To find TikTok influencer emails by niche, search a keyword such as "fitness coach", collect the creators behind the videos, then read each creator's bio and link-in-bio page for a contact email. This guide shows how to do that automatically with a TikTok email finder API, and returns one row per creator with their email, Instagram, YouTube and follower count.

This is part 1 of "How my fun projects turned into APIs". Each post takes one side project, explains how it works, and ends with something you can call from your own code.

Why finding TikTok creator emails is slow
How the TikTok email finder works
How to find TikTok influencer emails in 4 steps
How to get TikTok creator emails with Python
How to get TikTok creator emails with JavaScript
What data you get for each TikTok creator
How many TikTok creators have a public email
How much it costs
FAQ

Why finding TikTok creator emails is slow

TikTok has millions of creators, and very few of them are easy to contact. Whether you run influencer outreach, source UGC creators, or look for sponsorship partners, the manual process is the same:

Search a niche and scroll.
Open a profile and read the bio.
Find a Linktree instead of an email, and open that too.
Copy the email into a spreadsheet, then repeat a few hundred times.

The project that started it

A while ago I was building a small pet gear review site as a weekend project: honest roundups of chicken coops, dog crates and cat trees, paid for by affiliate links. The content was fine. The problem was that nobody knew it existed.

The obvious fix was TikTok. Pet creators with 5,000 to 50,000 followers have engaged audiences, and many of them happily review products in exchange for a free sample. So I opened a spreadsheet and started looking for pet creators to contact.

It went badly. After a whole evening of searching "backyard chickens" and "dog gear", I had a handful of emails. Most creators had no email in the bio, just a Linktree, and half of those Linktrees led to another page before I found a contact address. I kept thinking that every step I was doing by hand was the same few clicks, and a script could do them all.

So I wrote one. The first version took a list of TikTok usernames and pulled the email from each bio. Then I added keyword search so I didn't need the usernames. Then I added link-in-bio reading, because that was where most of the emails actually were. By the time it worked well for pet creators, I realised it worked for any niche: fitness coaches, skincare, cooking, finance.

That's when the side project turned into a public API that anyone can call: type a niche, get back a list of creators you can actually email.

How the TikTok email finder works

The tool is an Apify Actor called TikTok Profile Scraper. It reads public TikTok pages as a logged-out visitor, so it needs no TikTok account, no cookies and no API key. It solves three problems.

1. Finding creators by keyword, not just by username

TikTok has public topic pages for keywords. Each one lists roughly 60 to 120 recent videos, and every video has a creator behind it. The scraper reads the topic page, collects those creators, and skips private accounts, creators outside your follower range, and anyone it already checked.

A single broad word such as "skincare" often has no topic page of its own. In that case the scraper falls back to related topics such as "best skincare", "skincare tips" and "skincare review". Two- or three-word niche phrases work best.

2. Finding the email behind the link in bio

Many creators keep their business email off the bio and put it on a Linktree, hoo.be, Komi or personal website instead. After reading the profile, the scraper opens that link page (plus one contact page on the same site) and looks for an email there.

It also catches disguised emails such as name [at] gmail [dot] com, ranks outreach addresses like collab@ or business@ ahead of support@, and drops noreply@ addresses. It never guesses or generates an address.

That second step matters. In an October 2026 test run for "fitness coach", 13 of the 30 leads came from link-in-bio pages, not from the bio.

3. Paying only for creators you can contact

Most creators have no public email, so paying for every profile checked wastes money. Leads-only mode, on by default for keyword searches, saves and charges only the creators with a contact email. Creators without one are checked for free.

How to find TikTok influencer emails in 4 steps

Create a free Apify account. The free plan includes $5 of monthly credit.
Open TikTok Profile Scraper and click Try for free.
Paste this input (switch the input editor to JSON):

{
  "searchKeywords": ["skincare routine", "skincare influencer"],
  "onlyWithEmail": true,
  "minFollowers": 10000,
  "maxFollowers": 500000,
  "maxResults": 50
}

Click Start, then export the results as CSV, Excel or JSON, or send them to Google Sheets or your CRM through an Apify integration.

Already have a list of TikTok usernames? Use handles instead of searchKeywords:

{
  "handles": ["@noahbeck", "@drewafualo"],
  "onlyWithEmail": true,
  "maxResults": 100
}

How to get TikTok creator emails with Python

Install the client with pip install apify-client, then:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("scrape-lads/tiktok-profile-scraper").call(run_input={
    "searchKeywords": ["fitness coach", "personal trainer"],
    "onlyWithEmail": True,
    "minFollowers": 5000,
    "maxResults": 50,
})

for creator in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(creator["username"], creator["followers"], creator["contactEmail"])

Your API token is in Apify Console under Settings → API & Integrations.

How to get TikTok creator emails with JavaScript

Install the client with npm install apify-client, then:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('scrape-lads/tiktok-profile-scraper').call({
  searchKeywords: ['fitness coach', 'personal trainer'],
  onlyWithEmail: true,
  minFollowers: 5000,
  maxResults: 50,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((c) => console.log(c.username, c.followers, c.contactEmail));

To build a growing lead list, save the input as a task, schedule it weekly, and filter out usernames you already exported. Each run then adds only fresh creators.

What data you get for each TikTok creator

Every row has the same 39 fields. Here is a shortened real result:

{
  "username": "noahbeck",
  "displayName": "noah beck",
  "followers": 32677842,
  "likes": 2543936778,
  "postCount": 3421,
  "verified": true,
  "bioLink": "https://linktr.ee/noahbeck",
  "contactEmail": "noahbeck@underscoretalent.com",
  "contactEmailSource": "bioLink",
  "instagramUrl": "https://www.instagram.com/noahbeck",
  "youtubeUrl": "https://www.youtube.com/channel/UClPsjnF7D_Ar1ZSrEsnTxJA",
  "twitterUrl": "https://x.com/noahbeck",
  "tiktokShopSeller": false
}

Note contactEmailSource: "bioLink": this creator's bio has no email, and the scraper found it on their Linktree.

Group	Fields
Contact	`contactEmail`, `contactEmailSource`, `bioEmails`, `linkEmails`
Social profiles	Instagram, YouTube, X, Facebook, LinkedIn, Twitch, Snapchat, WhatsApp, Telegram
Audience	`followers`, `following`, `likes`, `postCount`, `avgLikesPerPost`
Profile	`bio`, `verified`, `language`, `businessCategory`, `tiktokShopSeller`

How many TikTok creators have a public email

In five keyword runs on October 1, 2026, the scraper checked 538 creators. 180 of them (33%) had a public contact email.

Niche	Creators with an email
"fitness coach" and "personal trainer"	24%
"vegan recipes" plus "home workout"	39%
"skincare" creators with 1,000+ followers	60%

Creators who want brand deals publish an email far more often than the average account, so setting a minimum follower count usually raises the hit rate.

How much it costs

You pay per result. Runtime and proxies are included.

$1.00 per 1,000 creators saved
+$3.00 per 1,000 emails found on a link-in-bio page
$0.005 per run
In leads-only mode, creators without an email are free

In testing, 1,000 leads with an email cost about $2.30. The Apify free plan's $5 monthly credit covers about 2,000 leads, so you can test it without paying anything.

FAQ

How do I find TikTok influencers in my niche?

Enter your niche as a keyword, for example "fitness coach" or "vegan recipes". The scraper collects the creators TikTok shows for that topic and related topics. Add a follower range to target nano, micro or macro influencers.

How do I find someone's email on TikTok?

Check their bio first, then the link under the bio. Most creators who accept brand deals put a business email in one of the two. To do this for many creators at once, paste their usernames into the scraper.

Can it get the email of any TikTok account?

No. It returns only emails the creator published on TikTok or on the page their bio links to. If a creator has no public email, there is no email to return.

Is there an official TikTok API for influencer search?

TikTok's Research API requires an approved research application, and the Creator Marketplace API is limited to approved partners. This scraper reads public pages with no approval or keys.

Can I filter TikTok creators by country?

TikTok does not publish an account's country, so no tool can filter on it reliably. Use the account language filter (for example en or es) and keywords in the local language instead.

Is scraping TikTok legal?

Collecting public data is generally legal in most jurisdictions, and this scraper only reads pages any logged-out visitor can see. You are responsible for how you use the data: follow privacy laws such as GDPR and CAN-SPAM, and use contact emails for relevant, honest outreach.

Try it

TikTok Profile Scraper: apify.com/scrape-lads/tiktok-profile-scraper
All my scrapers and APIs: scrapelads.com

That's part 1 of the series. If there's a TikTok field you wish this returned, tell me in the comments. I read all of them.

DEV Community: Charbel Daccache

Find TikTok Shop creators to seed your product (with their emails, in Python)

Build the list

Rank and export for your outreach tool

What a real run looked like

Tips

How to Scrape Reddit Posts and Comments Without the Reddit API (with Python)

Table of contents

Why scraping Reddit got harder

The project that started it

How the Reddit scraper works

How to scrape Reddit in 4 steps

How to scrape Reddit with Python

How to scrape Reddit with JavaScript

What data you get from Reddit

How to find SaaS ideas on Reddit with AI tags

How much it costs

FAQ

Can I scrape Reddit without an API key?

Does Reddit have an official API? Why not use it?

How many posts can I get from a subreddit?

Can I scrape Reddit comments by keyword?

How do I monitor Reddit for my brand?

Is it legal to scrape Reddit?

Try it

How to find local businesses without a website (Google Maps + Python)

The idea

Running it

What a real run looks like

Turning it into outreach

Cost

How to get YouTube transcripts in bulk without getting IP-blocked

Getting transcripts for a list of videos

A whole channel

Subtitle files

What it doesn't do

Cost

How to Extract a Recipe from a TikTok or Instagram Video as JSON (with Python)

Table of contents

Why saving recipes from videos is so annoying

The project that started it

How the recipe extractor works

1. It collects every signal

2. Exact recipes win

3. An AI model merges the rest

4. You only pay for real recipes

How to extract a recipe from a video in 4 steps

How to extract recipes with Python

How to extract recipes with JavaScript

What the recipe JSON looks like

Options worth knowing

How much it costs

FAQ

How do I save a recipe from TikTok?

Can it get recipes from Instagram Reels?

What happens with "comment RECIPE" videos?

Does it invent ingredient amounts?

Is there an official API for recipes from TikTok or Instagram?

Does it download the videos?

Try it

How to Get a Transcript of a TikTok, Instagram Reel or YouTube Short (with Python)

Table of contents

Why short video transcripts are hard to get

The project that started it

How the video transcript scraper works

1. Platform subtitles first

2. Whisper speech-to-text as the fallback

3. Videos by link or by creator

How to get a video transcript in 4 steps

How to get TikTok and Instagram transcripts with Python

How to get video transcripts with JavaScript

What data you get for each video

What people use it for

How much it costs

FAQ

How do I get the transcript of an Instagram Reel?

Can I get a transcript of a TikTok video?

Is there an official API for TikTok or Instagram transcripts?

Which languages are supported?

Which videos can't be transcribed?