aiostep 0.3.6

A Python library to handle steps in aiogram framework.

Aiostep - Simple and Flexible State Management

Aiostep is a lightweight and flexible state management tool designed for Telegram bots and similar applications. It allows developers to track user states and manage transitions between them with ease. Whether you're building a multi-step form, handling complex user interactions, or simply need to store temporary user data, Aiostep makes it straightforward.

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Features

• Simple API: Intuitive methods for setting, getting, and deleting user states and associated data.
• Customizable Storage: Use in-memory storage or integrate with persistent options like Redis or file-based storage.
• Direct User Interaction: Easily ask questions and receive user responses directly within handlers, reducing boilerplate code.
• Extendable: Designed to integrate with existing frameworks such as aiogram.

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How It Works

User Interaction Methods

Aiostep provides three primary methods for interacting with users and managing multi-step processes:

1. wait_for:

   • Use this method to wait for a specific user response within the current handler.
   • Simplifies user interaction by reducing the need for separate handlers.

2. register_next_step:

   • Allows registering the next handler explicitly for a user.
   • Useful for chaining steps in a process.

3. States:

   • Define user states to manage stages in a multi-step workflow.
   • States can include optional callbacks for seamless navigation between steps.

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Installation

To start using Aiostep, simply install it via pip.

pip install --upgrade aiostep

If you want use RedisStateStorage, you should install aiostep with redis support:

pip install --upgrade aiostep[redis]

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Usage

Using wait_for and register_next_step

Aiostep offers two primary methods for managing direct user interactions:

1. wait_for:

• This method allows you to wait for a user response directly within the current handler.
• Requires the Listen middleware to be set up for intercepting subsequent user messages.

Example:

from aiostep import aiogram_dialect, wait_for

from aiogram import Dispatcher, filters
from aiogram.types import Message

dp = Dispatcher()
dp.message.outer_middleware(aiogram_dialect.Listen())

@dp.message(filters.CommandStart())
async def ask_question(message: Message):
    await message.reply("Please type something:")
    try:
        response = await wait_for(message.from_user.id, timeout=25)  # timeout is optional
    except TimeoutError:
        await message.reply("You took too long to answer.")
    else:
        await message.reply(f"You typed: {response.text}")

[!NOTE]
The timeout parameter is optional; if not provided, the bot will wait indefinitely for a response.

2. register_next_step

• Use this method to explicitly register the next handler for the user's response.
• Also requires the Listen middleware for processing follow-up messages.

Example:

import aiostep
from aiostep import aiogram_dialect

from aiogram import Dispatcher, filters
from aiogram.types import Message

dp = Dispatcher()
dp.message.outer_middleware(aiogram_dialect.Listen())

@dp.message(filters.CommandStart())
async def ask_question(message: Message):
    await aiostep.register_next_step(message.chat.id, handle_answer)
    await message.reply("What's your name?")

async def handle_answer(message: Message):
    await message.reply(f"Hello, {message.text}!")

Using States

Aiostep supports managing user states to handle multi-step workflows. Unlike the previous methods, managing states does not require the Listen middleware.

1. Memory State Storage:

• This is an in-memory implementation suitable for temporary state storage.

Example:

from aiostep import MemoryStateStorage
from aiostep.utils import IsState

from aiogram import Dispatcher, filters
from aiogram.types import Message

dp = Dispatcher()
state_manager = MemoryStateStorage()

@dp.message(filters.CommandStart())
async def start_process(message: Message):
    state_manager.set_state(
        user_id=message.from_user.id,
        state="STEP_ONE"
    )
    await message.reply("State set to STEP_ONE!")

@dp.message(IsState("STEP_ONE", state_manager))
async def handle_step_one(message: Message):
    await message.reply("You're in STEP_ONE.")
    state_manager.delete_state(
        user_id=message.from_user.id,
    )

Returning to Previous State:

from aiogram import F

@dp.message(F.text == "Back")
async def go_back(message: Message):
    step = state_manager.get_state(message.from_user.id)
    if step and step.callback:
        await step.callback(message)
    else:
        await message.reply("No previous state found.")

[!NOTE]
You should manually use getattr to find and call the back step handler if you use RedisStateStorage or FileStateStorage, because callbacks are saved as strings (function name)

@dp.message_handler(F.text == "Back")
async def go_back(message: Message):
   step = state_manager.get_state(message.from_user.id)
   if step and step.callback:
       callback = getattr(step.callback)
       await callback(message)
   else:
       await message.reply("No previous state found.")

2. Other Storage Options:

• File-based and Redis storage implementations are also available, providing similar functionality with persistent data storage.
• Simply replace MemoryStateStorage with FileStateStorage or RedisStateStorage when initializing the state manager.

[!NOTE]
Methods in MemoryStateStorage, FileStateStorage and RedisStateStorage are synchronous. If you want use asynchronous versions, use aiostep.asyncio:

from aiostep.asyncio import AsyncMemoryStateStorage
from aiostep.asyncio import AsyncFileStateStorage
from aiostep.asyncio import AsyncRedisStateStorage

3. Timeout States

To set a timeout (expiry) for the state storage, you can use the ex argument for both RedisStateStorage and FileStateStorage. But for MemoryStateStorage you need to pass a TTLCache if you want set timeout.

Here's how you can set it up:

• For MemoryStateStorage (using cachebox.TTLCache):

  from aiostep import MemoryStateStorage
  from cachebox import TTLCache  # cachetools.TTLCache also works
  
  # Create a TTLCache with a timeout of 200 seconds
  storage = MemoryStateStorage(TTLCache(0, 200))  # Timeout is 200 seconds
  

• For RedisStateStorage (using the ex argument for expiry time):

  from aiostep import RedisStateStorage
  from aiostep import FileStateStorage
  
  # Create RedisStateStorage with a timeout of 200 seconds
  storage = RedisStateStorage(db=0, ex=200)  # Timeout (expiry) is 200 seconds
  storage = FileStateStorage("path.txt", ex=200)  # Same as RedisStateStorage
  

In both cases, the state will automatically expire after the specified time, and the data will be removed from the storage.

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Using Data

Setting Data

state_manager.set_data(
    user_id=message.from_user.id,
    data={"key": "value"}
)

Getting Data

data = state_manager.get_data(user_id=message.from_user.id)
await message.reply(f"Your data: {data}")

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Important Notes

1. Callbacks:

   • Callbacks can be any callable object, such as functions.
   • In FileStateStorage and RedisStateStorage they are stored as strings (e.g. function name).

2. Storage Flexibility:

   • The memory-based implementation is ideal for development and testing.
   • Persistent storage like Redis is recommended for production.

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Future Plans

• Better Library Compatibility: Enhanced support for other Telegram bot libraries such as pyTelegramBotAPI and python-telegram-bot, in addition to aiogram.
• Improved Documentation: Detailed guides and best practices.

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License

This project is licensed under the MIT License. See the LICENSE file for more details.

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For more information or to contribute, visit our GitHub repository.