DEV Community: Sami

How to Scrape Kick.com Streamer Data in 2026: Profiles, Live Streams, VODs & Rankings

Sami — Tue, 14 Apr 2026 01:38:52 +0000

TL;DR: Want to skip the coding and scrape Kick.com right now? Jump to the pre-built solution that extracts streamer profiles, live streams, VODs, clips, and channel rankings — no API key, no proxy, no browser needed.

Why Scrape Kick.com in 2026?

Kick.com has emerged as one of the fastest-growing live streaming platforms in the world. With creators migrating from Twitch due to better revenue splits, Kick streaming data has become a goldmine for marketers, analysts, and developers.

Whether you're tracking Kick streamer analytics, monitoring live viewership trends, or researching influencer marketing opportunities, having access to structured Kick.com data is essential.

What Can You Do With Kick.com Data?

Influencer marketing — Identify top Kick streamers for brand partnerships based on audience size, category, and engagement
Esports analytics — Track competitive gaming trends and viewership across categories
Brand monitoring — Monitor sponsorship ROI across Kick channels in real time
Competitive streaming intelligence — Compare channel performance and growth patterns
Content research — Discover trending categories, formats, and top-performing clips

The DIY Approach: Scraping Kick.com With Python

Kick.com exposes internal API endpoints that return structured JSON data. Here's how to build a basic Kick scraper with Python:

Setting Up Your Environment

pip install curl-cffi asyncio

Basic Kick.com Channel Scraper

import asyncio
from curl_cffi.requests import AsyncSession

BASE = "https://kick.com"
HEADERS = {
    "Accept": "application/json",
    "Referer": "https://kick.com/",
    "Accept-Language": "en-US,en;q=0.9",
}

async def scrape_kick_channel(channel_name: str):
    """Scrape a Kick.com channel profile."""
    async with AsyncSession() as session:
        url = f"{BASE}/api/v2/channels/{channel_name}"
        response = await session.get(
            url, headers=HEADERS, impersonate="chrome"
        )
        if response.status_code == 200:
            data = response.json()
            return {
                "channelName": channel_name,
                "displayName": data.get("user", {}).get("username"),
                "followersCount": data.get("followersCount"),
                "isLive": data.get("livestream") is not None,
                "verified": data.get("verified", False),
            }
        return None

# Usage
result = asyncio.run(scrape_kick_channel("xqc"))
print(result)

The Challenges of DIY Kick Scraping

Building your own Kick.com scraper sounds straightforward, but you'll quickly run into problems:

Challenge	Impact
TLS fingerprinting	Kick detects standard HTTP clients — you need impersonation
Rate limiting	Too many requests get your IP temporarily blocked
API endpoint changes	Kick regularly updates internal API routes
Data normalization	Raw API responses need heavy parsing for clean output
Multiple data modes	Profiles, streams, VODs, and clips each require different endpoints
Infrastructure costs	Running scrapers 24/7 requires servers, monitoring, and maintenance

The Pre-Built Solution: Kick.com Streamer & Channel Analytics

Instead of maintaining your own scraper, the Kick.com Streamer & Channel Analytics actor on Apify handles everything for you — 4 scraping modes in one tool.

Why Use This Actor?

No API key required — accesses Kick.com's public API endpoints directly
No proxy needed — direct HTTP requests work without proxy rotation
No browser needed — pure HTTP requests, no Playwright or Puppeteer overhead
Lightweight — runs on 256 MB RAM with pure HTTP requests
Pay per result — just $0.005 per data point ($5 per 1,000 results)
Structured output — clean JSON ready for analytics, dashboards, or integrations

The 4 Scraping Modes

Mode 1: Channel Profiles (`channel_details`)

Get complete Kick streamer profiles with follower counts, live status, social links, and more:

{
  "mode": "channel_details",
  "channelNames": ["xqc", "amouranth", "trainwreckstv"]
}

Returns: display name, bio, avatar, banner, follower count, live status, current viewers, category, verified badge, subscriber badges, social links (Instagram, Twitter, YouTube, Discord, TikTok), and creation date.

Mode 2: Live Streams (`live_streams`)

Discover who's streaming live on Kick right now, filtered by category and minimum viewers:

{
  "mode": "live_streams",
  "category": "just-chatting",
  "minViewers": 100,
  "maxResults": 20,
  "sortBy": "viewers"
}

Returns: channel name, viewer count, stream title, category, start time, thumbnail, language, tags, and maturity rating.

Mode 3: VODs & Clips (`channel_videos`)

Extract past broadcasts and Kick clips from any channel:

{
  "mode": "channel_videos",
  "channelNames": ["xqc"],
  "videoType": "clips",
  "maxResults": 10
}

Returns: clip ID, title, duration, views, likes, category, thumbnail, video URL, creator name, and creation date.

Mode 4: Channel Rankings (`top_channels`)

Get a ranked list of top Kick channels sorted by live viewer count:

{
  "mode": "top_channels",
  "sortBy": "viewers",
  "category": "just-chatting",
  "maxResults": 25
}

Returns: rank, channel name, bio, avatar, current viewers, stream title, category, affiliate status, and social links.

How to Get Started

Sign up for a free Apify account
Go to the Kick.com Streamer & Channel Analytics actor page
Click "Try for free"
Select your scraping mode and enter your parameters
Hit Start and get structured data in seconds

Export Your Data Anywhere

Results are stored in an Apify dataset and can be exported as:

JSON — for APIs and applications
CSV — spreadsheet-ready for analysis
Excel (.xlsx) — direct download
XML — for legacy system integration

Plus, integrate directly with Google Sheets, Zapier, Make, and more.

DIY vs. Pre-Built: The Comparison

Feature	DIY Python Scraper	Kick.com Analytics Actor
Setup time	Hours to days	2 minutes
API key needed	No	No
Proxy needed	Sometimes	Never
Browser needed	No	No
TLS fingerprinting	Must handle yourself	Built-in
4 scraping modes	Build each separately	All included
Data normalization	Manual parsing	Clean JSON output
Rate limit handling	Your problem	Handled automatically
API change updates	You maintain it	Maintained for you
Scheduling	Cron jobs + servers	Built-in Apify scheduler
Cost	Server + dev time	$0.005/result

Real-World Use Case Workflows

Influencer Marketing Agency

Use channel_details mode to bulk-analyze potential Kick partners:

{
  "mode": "channel_details",
  "channelNames": ["streamer1", "streamer2", "streamer3", "streamer4"]
}

Then filter by follower count, live status, and engagement to find the best fits for your brand campaigns.

Esports Data Dashboard

Combine live_streams and top_channels modes on a schedule to build a real-time Kick viewership dashboard:

{
  "mode": "live_streams",
  "category": "fortnite",
  "minViewers": 500,
  "sortBy": "viewers"
}

Schedule runs every 5 minutes for real-time monitoring, or daily for trend analysis.

Content Creator Research

Use channel_videos mode to analyze what's performing on Kick clips:

{
  "mode": "channel_videos",
  "channelNames": ["xqc", "adin"],
  "videoType": "clips",
  "maxResults": 50
}

Discover trending content formats, optimal clip lengths, and high-engagement topics.

Frequently Asked Questions

Does this need an API key to scrape Kick.com?

No. The Kick.com Streamer & Channel Analytics actor uses Kick.com's publicly accessible internal API endpoints. No authentication required.

Does it need a proxy?

No. Direct HTTP requests work without any proxy rotation needed.

Can I track live viewership on Kick in real time?

Yes. The live_streams mode returns real-time viewer counts for all currently live streams. Schedule runs every 5 minutes for continuous monitoring.

What data formats can I export?

JSON, CSV, Excel (.xlsx), and XML — all available directly from the Apify dashboard or API. Plus direct integrations with Google Sheets, Zapier, and Make.

How does Kick.com scraping compare to Twitch scraping?

Both platforms expose internal API endpoints, but Kick's API is generally more open and doesn't require authentication tokens. The same developer also offers a Twitch Streamer & Channel Analytics actor for complete cross-platform streaming intelligence.

Is scraping Kick.com legal?

This actor only accesses Kick.com's publicly available API endpoints. It does not bypass any authentication, CAPTCHA, or rate-limiting mechanisms. No private or user-authenticated data is accessed.

Start Scraping Kick.com Today

Ready to extract Kick.com streamer data at scale? The Kick.com Streamer & Channel Analytics actor on Apify gives you everything you need — 4 scraping modes, clean JSON output, and zero infrastructure to maintain.

Try it free on Apify →

No API key. No proxy. No browser. Just data.

How to Scrape RedNote (Xiaohongshu) Data in 2026: The Complete Guide

Sami — Tue, 14 Apr 2026 01:16:00 +0000

RedNote (小红书 / Xiaohongshu) exploded onto the global stage in January 2025 when millions of TikTok users migrated to the platform during the US TikTok ban uncertainty. What was once a Chinese-only lifestyle app suddenly became a cross-cultural phenomenon with 300+ million monthly active users.

For marketers, researchers, and e-commerce brands, RedNote scraping is now essential for consumer insights — but extracting data from Xiaohongshu is notoriously difficult. The platform is built for the Chinese market, uses aggressive anti-bot measures, and has no public API.

TL;DR: If you want structured RedNote data without building a scraper, skip to The Pre-Built RedNote Scraper — no API key needed, works out of the box.

This guide covers how Xiaohongshu scraping works, what data you can extract, the technical challenges involved, and practical solutions for getting reliable data at scale.

Why RedNote Data Matters in 2026

RedNote isn't just "Chinese Instagram." It's a hybrid of Instagram, Pinterest, and Amazon Reviews — users post product reviews, travel guides, fashion inspiration, skincare routines, and restaurant recommendations, all with purchase links and brand tags.

Brand intelligence: Global brands like Estée Lauder, Nike, and Dyson actively monitor RedNote to understand how Chinese consumers perceive their products. A single viral Xiaohongshu post can drive millions in sales.

Trend forecasting: Beauty, fashion, and food trends often start on RedNote months before they hit Western markets. K-beauty routines, "clean girl" aesthetics, and matcha everything all gained traction on Xiaohongshu first.

E-commerce research: RedNote's integration with e-commerce means posts include real purchase data, price comparisons, and authentic reviews — invaluable for product research and market analysis.

Influencer marketing: Brands entering the Chinese market need to identify RedNote KOLs (Key Opinion Leaders) in their niche and analyze their engagement rates before investing in partnerships.

The Technical Challenge of Scraping Xiaohongshu

RedNote is one of the harder platforms to scrape:

No public API. Unlike Twitter/X, Reddit, or Telegram, Xiaohongshu offers no official API for developers. Everything must be reverse-engineered.

Chinese-first infrastructure. The platform is built for Chinese users. Content is primarily in Chinese, and the web version behaves differently from international access points.

Anti-bot protection. RedNote uses request signature verification (the X-s and X-t headers), cookie-based session management, rate limiting, and dynamic page rendering. This makes scraping RedNote significantly harder than most Western platforms.

What Data Can You Extract from RedNote?

Post/Note Data

Title and full text content
Images and video URLs
Likes, comments, shares, and saves counts
Post date and tagged topics/hashtags
Tagged products with prices
Location tags

User Profile Data

Username, display name, bio
Follower/following counts
Total likes received
Verification status

Engagement Metrics

Like-to-follower ratio
Average engagement per post
Posting frequency
Content category distribution

How to Scrape RedNote: Web vs Mobile API

Approach 1: Web Scraping (xiaohongshu.com)

import httpx
from bs4 import BeautifulSoup

async def fetch_note(note_id: str):
    url = f"https://www.xiaohongshu.com/explore/{note_id}"

    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
        "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
        "Referer": "https://www.xiaohongshu.com/",
    }

    async with httpx.AsyncClient() as client:
        response = await client.get(url, headers=headers)

    if response.status_code == 200:
        return parse_note_html(response.text)
    elif response.status_code == 461:
        raise SignatureRequired("Request needs signing")

The 461 status code is RedNote's signature challenge — requiring custom X-s and X-t headers that change with every request.

The Xiaohongshu Signature Problem

Both web and mobile approaches hit RedNote's signature verification. Solutions:

Browser automation — Use Playwright to run RedNote's own JavaScript. Most reliable but slowest (1-3 seconds per request).

Signature reverse engineering — Faster but breaks whenever RedNote updates their code (happens frequently).

Hybrid approach — Browser automation for session setup, then direct HTTP for batch extraction. Best balance of speed and reliability.

Handling RedNote Rate Limits

Xiaohongshu throttles aggressively:

Search requests: ~20 per minute
Note detail pages: ~30 per minute
User profiles: ~15 per minute
IP blocks: 1-24 hours after sustained high volume

import asyncio
import random

async def rate_limited_request(url, **kwargs):
    delay = random.uniform(2.0, 5.0)
    await asyncio.sleep(delay)

    response = await client.get(url, **kwargs)

    if response.status_code == 429:
        wait = random.uniform(30, 60)
        await asyncio.sleep(wait)
        return await rate_limited_request(url, **kwargs)

    return response

Pro tip: Use residential proxies for any serious volume. Datacenter IPs get blocked almost immediately by Xiaohongshu.

Processing Chinese Content from RedNote

def extract_hashtags(text: str):
    """Extract both Latin and Chinese hashtags from Xiaohongshu posts"""
    import re
    pattern = r'#[\w\u4e00-\u9fff\u3400-\u4dbf]+'
    return re.findall(pattern, text)

Since the TikTok migration of 2025, many RedNote channels now post bilingual content, making the platform increasingly accessible to global researchers and marketers.

The Pre-Built RedNote Scraper

Building and maintaining a Xiaohongshu scraper is a significant time investment — the signature algorithm changes frequently, rate limits require constant tuning, and edge cases add up fast. I've been maintaining one for over a year so you don't have to.

I built the RedNote Xiaohongshu Scraper on Apify that handles all of this — and it's free to try.

Why use it instead of building your own?

Feature	DIY Scraper	My Apify RedNote Scraper
Setup time	Days/weeks	30 seconds
Signature handling	You reverse-engineer it	Built-in & auto-updated
Proxy management	You manage it	Built-in residential proxies
Rate limit handling	You build it	Built-in
Chinese text processing	You build it	Built-in
JSON/CSV export	You build it	Built-in
Scheduled monitoring	You build it	Built-in
Maintenance when RedNote updates	On you	On me

What you can do with it:

Search by keyword — find posts matching any topic, brand, or product in Chinese or English
Scrape user profiles — extract all posts from specific creators or KOLs
Extract by URL — paste specific post URLs for structured data
Full metadata — likes, comments, shares, saves, images, videos, tagged products
No API key needed — runs on Apify's infrastructure with proxy management built in

It currently serves brands, agencies, and researchers with a 90%+ success rate across thousands of extractions.

→ Try the RedNote Xiaohongshu Scraper on Apify (Free Trial)

Common Use Cases for RedNote Scraping

Brand Monitoring on Xiaohongshu

Search for your brand name (Chinese and English), extract matching posts, set up scheduled runs for new mentions. Critical for any brand selling in China.

Competitor Analysis on RedNote

Extract competitor's last 100-200 posts, sort by engagement rate, analyze what topics and formats drive the most saves. On RedNote, saves = purchase intent, making this metric more valuable than likes.

KOL/Influencer Identification

Search niche keywords, collect top-performing post authors, filter by engagement rate — micro-KOLs with 10K-50K followers often drive more conversions than celebrity influencers on Xiaohongshu.

Trend Research & Product Discovery

Track emerging keywords over time, analyze which products get tagged most, cross-reference with Western platforms to spot trends early. Many global brands use this to predict Western trends 3-6 months early.

FAQ

Can I scrape RedNote without an API?

Yes, but it's technically challenging due to signature verification. The easiest approach is using a pre-built RedNote scraper that handles the anti-bot measures for you.

Is scraping Xiaohongshu legal?

Scraping publicly available data is generally legal. However, always respect rate limits and the platform's terms. Using the data for competitive intelligence and market research is standard practice.

What's the best RedNote scraper in 2026?

The RedNote Xiaohongshu Scraper on Apify is the most maintained option with the highest success rate. It handles signature changes, proxy rotation, and rate limiting automatically.

Can I scrape RedNote in English?

Yes. Since the 2025 TikTok migration, RedNote has significantly more English content. The scraper extracts content in any language and you can search using English or Chinese keywords.

How do I monitor my brand on Xiaohongshu?

Use a RedNote scraper with scheduled runs — search for your brand name weekly, compare engagement metrics over time, and track new mentions automatically.

Conclusion

RedNote is arguably the most valuable social media platform for consumer insights into the Chinese market. The scraping challenge is real but solvable.

If you want production-ready Xiaohongshu data without the maintenance headache, try my RedNote Scraper on Apify — it's free to start and handles all the anti-bot complexity covered in this article.

Questions about RedNote scraping? Drop a comment below.

How to Scrape Telegram Channels in 2026 (Without API Keys or Phone Numbers)

Sami — Tue, 14 Apr 2026 01:11:26 +0000

Telegram has 950+ million monthly active users and has become the go-to platform for crypto communities, news channels, research groups, and brand communications. If you need to scrape Telegram channels, extract messages, reactions, media, or metadata from public Telegram channels — for OSINT research, competitive analysis, crypto monitoring, or academic projects — this guide covers everything you need to know.

I'll walk through the two main approaches to Telegram scraping, the technical pitfalls that break most implementations, and a ready-to-use Telegram scraper that actually works in production.

TL;DR: If you just want a working solution, skip to The Pre-Built Telegram Scraper — no API keys, no phone number, no setup required.

Why Scraping Telegram Is Different from Other Platforms

Most social media platforms require you to fight anti-bot systems — CAPTCHAs, IP blocks, browser fingerprinting. Telegram is different for one critical reason: it was built for developer access.

Telegram offers two paths to data extraction:

Path 1: The web preview endpoint (t.me/s/channelname) renders public channel messages as plain HTML. No login. No API keys. No JavaScript rendering needed. You can curl it directly and parse the HTML. This is what makes Telegram one of the easiest platforms to scrape — yet most existing Telegram scraper tools still manage to fail at it.

Path 2: The Telegram API via Telethon gives you full access to message history, member lists, media files, and reply threads. It requires API credentials from my.telegram.org and a phone number for authentication, but provides complete data that the web preview can't match.

How to Scrape Telegram Channels Without Authentication

Every public Telegram channel has a web preview at https://t.me/s/CHANNEL_NAME. This page contains the latest messages rendered as server-side HTML — no JavaScript execution required. This is the fastest way to scrape Telegram messages without any setup.

Here's the basic structure of a Python Telegram scraper:

import httpx
from bs4 import BeautifulSoup

async def scrape_telegram_channel(channel_name: str):
    url = f"https://t.me/s/{channel_name}"

    async with httpx.AsyncClient() as client:
        response = await client.get(url, headers={
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
        })

    soup = BeautifulSoup(response.text, "lxml")
    messages = []

    for widget in soup.select(".tgme_widget_message_wrap"):
        message = widget.select_one(".tgme_widget_message")
        if not message:
            continue

        msg_data = {
            "id": extract_message_id(message),
            "text": extract_text(message),
            "date": extract_date(message),
            "views": extract_views(message),
            "reactions": extract_reactions(message),
            "media": extract_media(message),
        }
        messages.append(msg_data)

    return messages

The key CSS selectors for Telegram data extraction:

.tgme_widget_message_text — message content (preserves formatting)
.tgme_widget_message_date time — timestamp (in the datetime attribute)
.tgme_widget_message_views — view count
.tgme_widget_message_forwarded_from — forwarded channel info
.tgme_widget_message_photo_wrap — photo containers
.tgme_widget_message_video — video elements

Telegram Message Pagination

The web preview doesn't show all messages at once. To scrape older Telegram messages, use the before parameter:

url = f"https://t.me/s/{channel_name}?before={last_message_id}"

Keep requesting with decreasing message IDs until you get an empty response. This typically gives you access to the latest 500-1,000 messages depending on the channel.

Extracting Telegram Reactions Data

Telegram added reactions in 2022, and the web preview includes them — useful for sentiment analysis on Telegram:

def extract_reactions(message_element):
    reactions = {}
    for reaction in message_element.select(".tgme_widget_message_reaction"):
        emoji = reaction.select_one(".tgme_widget_message_reaction_emoji")
        count = reaction.select_one(".tgme_widget_message_reaction_count")
        if emoji and count:
            reactions[emoji.text.strip()] = int(count.text.strip().replace(",", ""))
    return reactions

Scraping Telegram with Telethon (Full API Access)

For complete Telegram message history, member data, or private channels you belong to, you need the Telegram API via Telethon:

pip install telethon

from telethon import TelegramClient
from telethon.sessions import StringSession

async def scrape_with_telethon(api_id, api_hash, session, channel):
    client = TelegramClient(StringSession(session), api_id, api_hash)
    await client.start()

    entity = await client.get_entity(channel)

    messages = []
    async for message in client.iter_messages(entity, limit=1000):
        messages.append({
            "id": message.id,
            "date": message.date.isoformat(),
            "text": message.text,
            "views": message.views,
            "forwards": message.forwards,
            "sender_id": message.sender_id,
            "reply_to": message.reply_to_msg_id,
            "pinned": message.pinned,
            "media_type": type(message.media).__name__ if message.media else None,
        })

    return messages

Handling Telegram FloodWaitError

This is where every Telegram scraper breaks. Telegram enforces rate limits through FloodWaitError — when you hit the limit, the API tells you exactly how many seconds to wait:

from telethon.errors import FloodWaitError
import asyncio

async def safe_api_call(coro, max_retries=3):
    for attempt in range(max_retries):
        try:
            return await coro
        except FloodWaitError as e:
            wait = e.seconds + 5
            print(f"Rate limited. Waiting {wait}s...")
            await asyncio.sleep(wait)
    raise Exception("Max retries exceeded")

The key insight: don't try to avoid FloodWaitError — expect it and handle it gracefully.

Getting Telegram API Credentials

Go to my.telegram.org
Log in with your phone number
Click "API development tools"
Create a new application
Save your api_id and api_hash

Common Pitfalls That Break Telegram Scrapers

After building my own Telegram channel scraper and testing against a dozen others, here are the failure modes I've seen:

Not handling empty channels. Some channels have web preview disabled. Your scraper should detect this and return a clear message instead of crashing.

Ignoring forwarded message metadata. Many crypto and news channels are mostly forwards. If you don't extract the forwarded_from field, you lose critical context.

Breaking on media-only messages. Messages with only photos/videos and no text are common. Scrapers that assume every message has text crash or skip these silently.

Not normalizing channel input. Users will provide t.me/channel, https://t.me/channel, @channel, or just channel. Handle all formats.

Crashing on rate limits instead of waiting. This alone accounts for most 1-star reviews on existing Telegram scrapers.

The Pre-Built Telegram Scraper

If you don't want to build and maintain this yourself, I built a Telegram Channel Scraper on Apify that handles all of the above — and it's free to try.

Why use it instead of building your own?

Feature	DIY Scraper	My Apify Telegram Scraper
Setup time	Hours/days	30 seconds
API keys needed	Yes (Telethon mode)	No (default mode)
Phone number needed	Yes (Telethon mode)	No (default mode)
Handles rate limits	You build it	Built-in
Media extraction	You build it	Built-in
Reactions data	You build it	Built-in
JSON/CSV export	You build it	Built-in
Scheduled runs	You build it	Built-in
Cloud infrastructure	You manage it	Managed for you

It runs in two modes:

No-auth mode (default): paste a channel URL, get messages back. No API keys, no phone number, no setup. Try it free →
Telethon mode: provide your API credentials for full message history and member data.

It handles FloodWaitError automatically, never crashes on edge cases, extracts reactions and media metadata, and outputs clean JSON or CSV.

→ Try the Telegram Channel Scraper on Apify (Free Trial)

Use Cases for Telegram Scraping

Crypto monitoring — Track token announcements, pump signals, and community sentiment across Telegram groups
OSINT research — Monitor extremist channels, propaganda networks, or misinformation campaigns
Competitive intelligence — Track competitor announcements and community engagement
Academic research — Collect datasets for NLP, sentiment analysis, or social network studies
Brand monitoring — Track mentions and discussions about your brand across Telegram channels
News aggregation — Build feeds from curated Telegram news channels

FAQ

Can I scrape Telegram without an API key?

Yes. Public Telegram channels have a web preview at t.me/s/channelname that can be scraped without any authentication. My Telegram Channel Scraper uses this approach by default.

Is scraping Telegram legal?

Scraping publicly available data is generally legal in most jurisdictions. Telegram's web previews are designed to be publicly accessible. Always check your local laws and Telegram's Terms of Service.

How many messages can I extract from Telegram?

Using the web preview, you can typically access the latest 500-1,000 messages. With Telethon API access, you can extract the entire message history.

What's the best Telegram scraper in 2026?

For no-setup scraping, the Telegram Channel Scraper on Apify is the fastest option — paste a URL, get structured data. For full API access, Telethon is the standard Python library.

Can I scrape Telegram groups?

Web preview scraping works only for public channels. For groups, you need Telethon with API credentials and you must be a member of the group.

Conclusion

Telegram is one of the most scraping-friendly platforms out there — public data is genuinely accessible, the API is well-documented, and there's no aggressive anti-bot system. The challenge isn't access — it's reliability.

If you want a production-ready Telegram scraper without building anything, try my Telegram Channel Scraper on Apify — it's free to start and handles all the edge cases covered in this article.

If you have questions about Telegram scraping, feel free to reach out in the comments.

DEV Community: Sami

How to Scrape Kick.com Streamer Data in 2026: Profiles, Live Streams, VODs & Rankings

Why Scrape Kick.com in 2026?

What Can You Do With Kick.com Data?

The DIY Approach: Scraping Kick.com With Python

Setting Up Your Environment

Basic Kick.com Channel Scraper

The Challenges of DIY Kick Scraping

The Pre-Built Solution: Kick.com Streamer & Channel Analytics

Why Use This Actor?

The 4 Scraping Modes

Mode 1: Channel Profiles (channel_details)

Mode 2: Live Streams (live_streams)

Mode 3: VODs & Clips (channel_videos)

Mode 4: Channel Rankings (top_channels)

How to Get Started

Export Your Data Anywhere

DIY vs. Pre-Built: The Comparison

Real-World Use Case Workflows

Influencer Marketing Agency

Esports Data Dashboard

Content Creator Research

Frequently Asked Questions

Does this need an API key to scrape Kick.com?

Does it need a proxy?

Can I track live viewership on Kick in real time?

What data formats can I export?

How does Kick.com scraping compare to Twitch scraping?

Is scraping Kick.com legal?

Start Scraping Kick.com Today

How to Scrape RedNote (Xiaohongshu) Data in 2026: The Complete Guide

Why RedNote Data Matters in 2026

The Technical Challenge of Scraping Xiaohongshu

What Data Can You Extract from RedNote?

Post/Note Data

User Profile Data

Engagement Metrics

How to Scrape RedNote: Web vs Mobile API

Approach 1: Web Scraping (xiaohongshu.com)

The Xiaohongshu Signature Problem

Handling RedNote Rate Limits

Processing Chinese Content from RedNote

The Pre-Built RedNote Scraper

Why use it instead of building your own?

What you can do with it:

Common Use Cases for RedNote Scraping

Brand Monitoring on Xiaohongshu

Competitor Analysis on RedNote

KOL/Influencer Identification

Trend Research & Product Discovery

FAQ

Can I scrape RedNote without an API?

Is scraping Xiaohongshu legal?

What's the best RedNote scraper in 2026?

Can I scrape RedNote in English?

How do I monitor my brand on Xiaohongshu?

Conclusion

How to Scrape Telegram Channels in 2026 (Without API Keys or Phone Numbers)

Why Scraping Telegram Is Different from Other Platforms

How to Scrape Telegram Channels Without Authentication

Telegram Message Pagination

Extracting Telegram Reactions Data

Scraping Telegram with Telethon (Full API Access)

Handling Telegram FloodWaitError

Getting Telegram API Credentials

Common Pitfalls That Break Telegram Scrapers

The Pre-Built Telegram Scraper

Why use it instead of building your own?

Use Cases for Telegram Scraping

FAQ

Can I scrape Telegram without an API key?

Is scraping Telegram legal?

How many messages can I extract from Telegram?

What's the best Telegram scraper in 2026?

Can I scrape Telegram groups?

Conclusion

Mode 1: Channel Profiles (`channel_details`)

Mode 2: Live Streams (`live_streams`)

Mode 3: VODs & Clips (`channel_videos`)

Mode 4: Channel Rankings (`top_channels`)