Telegram Scraper with Python: Extract Data from Groups and Channels (2026)

Telegram's open API makes it one of the most accessible messaging platforms for data extraction. Researchers, analysts, journalists, and developers use Python scrapers to archive public channel messages, analyze group discussions, monitor competitor announcements, or build datasets for academic research.

This guide covers how to build a Telegram scraper with Python using the Telethon library — the most capable tool for this use case in 2026. We'll cover ethical considerations and legal constraints alongside the technical implementation. Explore related resources in Developer Tools and OSINT Research.

What Is a Telegram Scraper?

A Telegram scraper is a script that uses Telegram's API to programmatically read and extract data from groups, channels, or chat histories. Unlike a Telegram bot (which reacts to incoming messages), a scraper uses a user account or a Telegram API client to actively fetch data.

Common use cases:

• Archiving public channel message history for research
• Monitoring specific channels for keywords (price alerts, news events)
• Extracting member lists from public groups for analysis
• Building training datasets from publicly available text
• Journalistic investigation of public Telegram groups
• Competitive intelligence (monitoring public announcements)

Setting Up Telethon for Scraping

Telethon is a Python library that implements Telegram's MTProto protocol, giving you access to everything a Telegram user account can see and do.

Prerequisites

1. Get Telegram API credentials: Go to my.telegram.org → "API Development Tools" → create an application. You'll receive an api_id (integer) and api_hash (string).
2. Install Telethon:

pip install telethon python-dotenv

# .env
TELEGRAM_API_ID=12345678
TELEGRAM_API_HASH=abcdef1234567890abcdef1234567890
TELEGRAM_PHONE=+1234567890

First connection and authentication

import os
from telethon import TelegramClient
from dotenv import load_dotenv

load_dotenv()

api_id   = int(os.environ["TELEGRAM_API_ID"])
api_hash = os.environ["TELEGRAM_API_HASH"]
phone    = os.environ["TELEGRAM_PHONE"]

# Session file stores authentication — don't commit it
client = TelegramClient("scraper_session", api_id, api_hash)

async def main():
    await client.start(phone=phone)
    print("Connected as:", await client.get_me())

with client:
    client.loop.run_until_complete(main())

On first run, Telegram sends a verification code to your Telegram app. Enter it in the terminal. The session is saved to scraper_session.session — subsequent runs won't ask for the code again.

Scraping Members from a Telegram Group

import os, csv, asyncio
from telethon import TelegramClient
from telethon.tl.functions.channels import GetParticipantsRequest
from telethon.tl.types import ChannelParticipantsSearch
from dotenv import load_dotenv

load_dotenv()

client = TelegramClient(
    "scraper_session",
    int(os.environ["TELEGRAM_API_ID"]),
    os.environ["TELEGRAM_API_HASH"]
)

async def scrape_members(group_username: str, output_file: str):
    await client.start(os.environ["TELEGRAM_PHONE"])

    group = await client.get_entity(group_username)

    all_members = []
    offset = 0
    limit  = 200

    while True:
        result = await client(GetParticipantsRequest(
            channel=group,
            filter=ChannelParticipantsSearch(""),
            offset=offset,
            limit=limit,
            hash=0
        ))

        if not result.users:
            break

        all_members.extend(result.users)
        offset += len(result.users)

        print(f"Fetched {len(all_members)} members so far...")

        # Respect rate limits — don't flood Telegram's API
        await asyncio.sleep(1)

    print(f"Total members: {len(all_members)}")

    # Write to CSV
    with open(output_file, "w", newline="", encoding="utf-8") as f:
        writer = csv.writer(f)
        writer.writerow(["id", "username", "first_name", "last_name", "phone"])
        for user in all_members:
            writer.writerow([
                user.id,
                user.username or "",
                user.first_name or "",
                user.last_name or "",
                user.phone or ""  # Usually empty for privacy
            ])

    print(f"Saved to {output_file}")

with client:
    client.loop.run_until_complete(
        scrape_members("@example_group", "members.csv")
    )

Important: Phone numbers are almost never returned — Telegram protects them for user privacy. Only the user's own account can see its own phone number.

Scraping Messages from Channels

import os, json, asyncio
from telethon import TelegramClient
from telethon.tl.types import MessageMediaPhoto, MessageMediaDocument
from datetime import datetime
from dotenv import load_dotenv

load_dotenv()

client = TelegramClient(
    "scraper_session",
    int(os.environ["TELEGRAM_API_ID"]),
    os.environ["TELEGRAM_API_HASH"]
)

async def scrape_messages(
    channel: str,
    limit: int = 1000,
    output_file: str = "messages.json"
):
    await client.start(os.environ["TELEGRAM_PHONE"])

    entity = await client.get_entity(channel)
    messages = []

    async for msg in client.iter_messages(entity, limit=limit):
        media_type = None
        if isinstance(msg.media, MessageMediaPhoto):
            media_type = "photo"
        elif isinstance(msg.media, MessageMediaDocument):
            media_type = "document"

        messages.append({
            "id":         msg.id,
            "date":       msg.date.isoformat(),
            "text":       msg.text or "",
            "views":      msg.views or 0,
            "forwards":   msg.forwards or 0,
            "media_type": media_type,
            "reply_to":   msg.reply_to_msg_id,
        })

        if len(messages) % 100 == 0:
            print(f"Scraped {len(messages)} messages...")
            await asyncio.sleep(0.5)  # Be gentle with the API

    with open(output_file, "w", encoding="utf-8") as f:
        json.dump(messages, f, ensure_ascii=False, indent=2)

    print(f"Saved {len(messages)} messages to {output_file}")

with client:
    client.loop.run_until_complete(
        scrape_messages("@telegram", limit=500, output_file="telegram_channel.json")
    )

Ethical and Legal Considerations

Telegram scraping exists in a complex ethical and legal landscape. Before running any scraper, understand:

What's generally acceptable:

• Scraping public channels for research, archiving, or journalistic purposes
• Monitoring your own groups and channels
• Building datasets from public, openly licensed content
• Academic research with appropriate IRB approval (for research involving people)

What's problematic or prohibited:

• Scraping private groups without the consent of members — this violates privacy expectations even if you're technically a member
• Mass-collecting user data (IDs, usernames) for commercial use without user consent — violates GDPR in Europe and similar laws elsewhere
• Using scraped data to spam users — violates Telegram's ToS and anti-spam laws
• Flooding the API — Telegram rate-limits aggressively; aggressive scraping leads to account bans
• Violating Telegram's ToS — using scrapers for mass data collection may result in account termination

Rate limiting best practices:

• Add asyncio.sleep(1) between paginated requests
• Use asyncio.sleep(0.5) between individual message fetches in loops
• Never fetch more data than you need
• Run scrapers during off-peak hours to reduce server load

FAQ

Do I need a Telegram account to scrape?

Yes. Telethon uses the MTProto protocol which requires authentication as a Telegram user. You cannot scrape Telegram data anonymously — a phone number is required to obtain API credentials and authenticate.

Can I scrape private groups?

Technically yes, if you're a member. Ethically and legally, you should not without the explicit consent of group administrators and members. Telegram's ToS prohibit unauthorized data collection.

My account got banned after scraping. What happened?

Telegram's anti-spam system detected unusual API usage patterns — too many requests in a short time, or patterns matching known mass-scraping behavior. Telegram temporarily bans accounts that violate rate limits. If the ban is temporary (FloodWaitError), wait the specified time. If permanent, you'll need a new account (and should revisit your rate-limiting strategy).

Is there an alternative to using my personal account?

You can create a dedicated Telegram account for scraping using a secondary phone number or a virtual number (see our SMS bots guide). This isolates scraping activity from your personal account.

How do I handle FloodWaitError?

from telethon.errors import FloodWaitError
import asyncio

try:
    result = await client(some_request)
except FloodWaitError as e:
    print(f"Rate limited. Waiting {e.seconds} seconds...")
    await asyncio.sleep(e.seconds + 5)  # Add buffer
    result = await client(some_request)  # Retry