aiogram vs python-telegram-bot vs pyTelegramBotAPI: How to Choose
Basics3 minInnovialabs editorial team
In short
Pick aiogram for complex async bots with dialogs and load, python-telegram-bot when documentation and stability matter most, and pyTelegramBotAPI for simple bots and learning.
The short answer
All three libraries are mature and maintained, so the right choice depends on your project rather than on a single "best" framework:
- aiogram is fully asynchronous, built around routers, filters and a built-in finite state machine. It suits production bots with many users and complex flows.
- python-telegram-bot (PTB) is also asynchronous, with exceptionally thorough documentation, many examples, a built-in job queue and persistence.
- pyTelegramBotAPI (telebot) has the lowest learning curve: decorators and very few concepts. It offers both a synchronous and an async client.
Side-by-side comparison
| Criterion | aiogram | python-telegram-bot | pyTelegramBotAPI |
|---|---|---|---|
| Execution model | async only (asyncio) | async | sync by default, AsyncTeleBot available |
| Code structure | routers, filters, middleware | handlers, ConversationHandler | decorators on the bot object |
| State (FSM) | built-in FSM, memory and Redis storage | ConversationHandler + persistence | states with memory or Redis storage |
| Scheduling | third-party (e.g. APScheduler) | built-in JobQueue | third-party |
| Docs | good; community mostly Russian- and Ukrainian-speaking | the most detailed, with a wiki and many examples | simple, many examples in the repo |
| Learning curve | medium | medium | low |
Bot API coverage is similar across the three: each project ships updates after Telegram releases. Before you start, check the changelog for the specific recent feature you need, such as new payment methods or Mini App support.
Why async matters
A bot spends most of its time waiting: for Telegram, the database or an external API. In synchronous code each wait blocks processing, so under load users end up waiting for each other. In async code other updates are handled while one request waits.
A practical rule:
- an internal bot for a team, simple notifications or a small audience can be synchronous;
- a public bot, broadcasts, CRM or payment integrations call for an async approach.
Note that an async framework does not help if your handlers call blocking libraries, such as a synchronous database driver. Use async drivers or move heavy work to background workers.
FSM and multi-step dialogs
Almost every business bot collects data step by step: name, phone, address, confirmation. That requires a state machine.
- aiogram describes states with a
StatesGroupclass, and you can switch storage from memory to Redis so state survives restarts. - PTB offers
ConversationHandlerwith explicit entry points, states and fallbacks, pluspersistenceto keep data between restarts. - telebot also has states and storage backends, but branching flows usually take more code.
A minimal aiogram 3 handler looks like this:
from aiogram import Router, F
from aiogram.types import Message
router = Router()
@router.message(F.text == "/start")
async def start(message: Message):
await message.answer("Hi! How can I help?")
Picks by project type
- Learning, prototypes, a one-evening bot: pyTelegramBotAPI.
- Support or sales bot with forms and branches: aiogram or PTB.
- High load, broadcasts, many integrations: aiogram.
- Team that values docs and built-in reminders scheduling: python-telegram-bot.
- Team already experienced with one of them: stay with it; knowing the tool matters more than the differences between them.
Common mistakes
- Following outdated tutorials. Both aiogram and PTB had major breaking releases, and old code will not run on current versions.
- Keeping state only in memory in production, so users get lost mid-dialog after a restart.
- Mixing sync and async calls without knowing where the event loop gets blocked.
- Choosing by GitHub stars instead of by how naturally the framework expresses your flows.