Automating Telegram with ProxyTee: A Comprehensive Guide

Telegram, a popular messaging platform known for its robust security features, offers more than just casual chats. It’s a hub for niche communities and marketing opportunities. But managing large groups and extracting valuable data manually can be daunting. That’s where automation comes in.

What is Telegram Automation?

Telegram automation involves using bots and scripts to perform repetitive tasks. This could include sending automated messages, setting reminders, or downloading media. However, a particularly useful application is data collection. By combining Telegram bots with reliable Datacenter Proxies from ProxyTee, you can automate the process of extracting group member information or gathering other forms of data.

Telegram’s flexibility with proxies makes it an excellent platform for data scraping and automation. ProxyTee offers the tools you need to start or improve your process with reliable and affordable solutions. From unlimited bandwidth to a global network, and auto rotation, ProxyTee helps ensure seamless operations, allowing you to concentrate on your goals without IP related interruptions. Unlimited Residential Proxies are an ideal option to boost your tasks with its rotating, global IPs.

The Need for Telegram Proxies

Data collection isn’t always smooth; you might face connectivity or location restrictions. That’s where proxies come in. They allow you to route your IP address through a remote server, providing added privacy and enabling access to geo-restricted content. Telegram supports proxies, making it a useful platform for marketing, research, and product development.

ProxyTee offers a range of solutions tailored for these needs. You can easily add proxies in the Telegram app by navigating to Settings > Data and Storage > Proxy Settings > Add Proxy. The platform’s API, along with readily available documentation, makes the whole process legitimate and feasible.

Understanding Telegram Channels and Groups

Before diving in, it’s important to know the difference between Telegram channels and groups. Channels are primarily for broadcasting, with only admins able to post messages, while groups are open for all members to participate in conversations. Though it’s not possible to scrape subscriber details from a channel (admins only can see the list), extracting posts is viable. On the other hand, scraping member details from a group is quite achievable.

How to Scrape Telegram Group Members Using ProxyTee

To begin, you’ll need a few things:

1. Your Telegram credentials
2. A Datacenter Proxy from ProxyTee. ProxyTee provides affordable and reliable datacenter proxies which ideal for this task due to its fast speed and affordability.
3. Python 3
4. The Telethon library for Telegram API interactions.

1️⃣ Step 1 – Getting Telegram Credentials

Go to my.telegram.org, log in, and create an app to get your api_id and api_hash, essential for using the API. Make sure not using any VPN or proxies during creating the application.

2️⃣ Step 2 – Setting Up ProxyTee Proxies

For this tutorial, Datacenter Proxies will suffice. ProxyTee‘s dashboard makes setup simple: after logging in and choose Pricing section, you will find a plan suitable for your need. Select the user:pass authentication method and copy proxy information into the code:

proxy = { 'proxy_type': 'http',  'addr': '1.1.1.1', 'port': 5555, 'username': 'your_username', 'password': 'your_pass',}

3️⃣ Step 3 – Installing Telethon Library

Install Telethon library with below command in terminal:

python pip install telethon

4️⃣ Step 4 – Setting Up the Script and Logging In

Import the required modules and login using your Telegram credentials:

from telethon.sync import TelegramClient api_id = 123456 api_hash = 'YOUR_API_HASH' phone = '+111111111111' TelegramClient(phone, api_id, api_hash, proxy={'proxy_type': python_socks.ProxyType.HTTP, 'addr': '1.1.1.1',  'port': 5555, 'username': 'your_username', 'password': 'your_pass'})

Log in by running:

client.connect() if not client.is_user_authorized(): client.send_code_request(phone) client.sign_in(phone, input('Enter the code: '))

5️⃣ Step 5 – Creating a Chat List

Now create an empty chat list using the following code block:

from telethon.tl.functions.messages import GetDialogsRequest from telethon.tl.types import InputPeerEmpty chats = [] last_date = None chunk_size = 200 groups = [] result = client(GetDialogsRequest(offset_date=last_date, offset_id=0, offset_peer=InputPeerEmpty(), limit=chunk_size, hash = 0 ) ) chats.extend(result.chats)

After this step, you will retrieve a list of recent chats, and we can pick which megagroup to start scraping next.

6️⃣ Step 6 – Selecting a Group to Scrape Members

Display the list of available groups and prompt the user to select one to scrape member details from:

for chat in chats:     try:         if chat.megagroup == True:            groups.append(chat)    except:       continue print('Choose a group to scrape members from:') i=0 for g in groups: print(str(i) + '- ' + g.title)  i+=1 g_index = input("Enter a Number: ") target_group=groups[int(g_index)]

7️⃣ Step 7 – Exporting Member Details

Export the member list by using function get_participants. To retrieve the maximum amount of members, we need to set the aggressive flag to True.

all_participants = [] all_participants = client.get_participants(target_group, aggressive=True)

8️⃣ Step 8 – Saving the Data in a CSV File

Save scraped details into a CSV file for further analysis.

import csv with open("members.csv","w",encoding='UTF-8') as f:  writer = csv.writer(f,delimiter=",",lineterminator="\n")  writer.writerow(['username','user id', 'access hash','name','group', 'group id'])  for user in all_participants:  if user.username:   username= user.username  else:   username= ""  if user.first_name:   first_name= user.first_name  else:   first_name= ""  if user.last_name:  last_name= user.last_name  else:   last_name= ""  name = (first_name + ' ' + last_name).strip()  writer.writerow([username,user.id,user.access_hash,name,target_group.title, target_group.id])  print('Members scraped successfully.')

After you run the code, you will get the data output as a member.csv file. 🚀