Right now, 10 million bots handle messages from over 1 billion Telegram users – and not some simple chatbots like most would think, but payments, running games, managing communities, and automating entire businesses. So, here’s exactly how these bots work under the hood!
BotFather Controls Everything – Your First 5 Minutes with Telegram’s API
Every Telegram bot starts with BotFather – you message @BotFather, type /newbot, pick a name, and you get a 46-character token that looks like “123456:ABC-DEF1234ghIkl-zyx57W2v1u123ew11”. Such a token serves as your bot’s password – so, lose it and someone else controls your bot.
But what happens next is that your Python script uses this token to connect to Telegram’s Bot API at api.telegram.org. So, every time someone messages your bot, Telegram’s servers catch that message first. They don’t forward it directly to your code, but store it and wait for your bot to either ask for it (polling) or they push it to your server (webhooks).
The numbers are exploding, though. Telegram processes 15 billion messages each day, and bots can handle groups with 200,000 members. Each bot processes up to 30 messages per second –that’s the hard limit Telegram sets to prevent spam. Your bot can send files up to 50 MB and receive files up to 20 MB through the API.
Impressive Python Libraries – PTB vs Aiogram in 2025
Two Python libraries dominate Telegram bot development. Python-telegram-bot (PTB) hit version 22.3 in July 2025 and completely rebuilt itself around asyncio since version 20. Aiogram reached version 3.22 and took a different approach – they built everything async from day one.
So, the real difference is that PTB gives you both high-level and low-level access so you can use simple decorators for basic commands or get deeper into the Telegram API. Aiogram assumes you know asyncio and throws you straight into async/await patterns. Both require Python 3.9 or newer.
The async shift changed everything. Your bot now handles thousands of users at the same time without freezing. One user triggers a database query that takes 5 seconds? No problem – other users keep chatting without delays. Well, he old synchronous approach would’ve made everyone wait in line.
Telegram Casino Bots Generate Millions – Technical Architecture Behind Gaming
Gaming bots show Telegram’s true potential – we’re talking full casino experiences running inside a chat app. Players find out how to play at Telegram casinos without downloading anything, accessing slots, poker, and live dealer games through bot commands and inline keyboards.
The architecture gets complex fast – casino bots maintain WebSocket connections for real-time gameplay, process crypto payments through Telegram’s payment API, and store game states in Redis for millisecond response times. They also handle provably fair algorithms that let players verify each game’s randomness.
Recent data shows 20% of Telegram’s billion users play at least one game monthly. So, that’s 200 million potential players. Casino bots make money through the instant play idea – that means no registration, no downloads, just click and play. The bots track statistics, manage wallets, and even have some anti-fraud systems, all while keeping response times under 100 milliseconds.
Webhooks Beat Polling – Production Bots Never Use getUpdates
Beginners love polling because it’s simple. Your bot asks Telegram, “Got any messages?” every second. Easy to code, works on your laptop, needs no public server. But polling is wasteful – a bot with zero users still makes 86,400 requests daily just checking for messages that don’t exist.
Webhooks flip the model – you give Telegram a URL like https://yourbot.com/webhook, and Telegram sends updates there instantly. No wasted requests or delays, which is perfect for serverless platforms.
Setting up webhooks requires more work, though. You need a domain, SSL certificate, and one of four specific ports: 443, 80, 88, or 8443. Telegram won’t accept other ports. You also must handle Telegram’s IP ranges (149.154.160.0/20 and 91.108.4.0/22) and validate the secret token header to prevent fake requests.
Deployment Strategies That Keep Bots Running 24/7
Forget regular VPS hosting, since modern bots run on PythonAnywhere (free tier handles small bots), Heroku (though they killed free tier), or containerized on Google Cloud Run. The smart money uses Docker containers with GitHub Actions for automatic deployment.
Your bot runs in a Docker container, environment variables store secrets, Redis handles session data, PostgreSQL stores user data, and Cloudflare protects your webhook endpoint. You implement health checks that restart frozen bots, log everything to know failures, and use Sentry for error tracking.
Real Performance Numbers from Production Bots
India leads with 70.48 million Telegram downloads, with 45% of the population using it, making it the biggest market yet. The average user spends 3 hours 45 minutes each month on Telegram, with sessions lasting about 1 minute 21 seconds. Your bot needs to handle both quick commands and long conversations.
Memory leaks kill long-running Python bots – clean up conversation handlers, use weak references for temporary data, and implement connection pooling for databases. Keep looking at everything – response times, error rates, user engagement. A well-optimized bot handles 1,000 concurrent users on a $5/month server.
The Takeaway
Building Telegram bots with Python is much more than coding – you have to know how to handle massive infrastructure that handles billions of messages. So, the best is to start simple with polling for testing, switch to webhooks for production, and always think about scale. The combination of Telegram’s free Bot API and Python’s async capabilities means a solo developer can build bots serving millions.
