A Telegram bot for playing the question-answer-question-answer party game, written in Python 3 and based on the Python Telegram Bot, SQLAlchemy and CherryPy libraries.
The original game is played with pen and paper: Each player gets a sheet of paper and writes down an arbitrary question. Then, they pass the sheet to the next player, who writes down an answer to the question and fold the sheet to hide the original question. The sheet is passed on to the next player, the task of whom is to find a question that is answered by the given answer. It might be the original question or not. Sometimes not even close—nobody knows until the end of the game. The sheet is folded again and the next player has to answer the new question—without knowing the previous questions and answers.
As soon as one of the sheets is full of questions and answers or the players no longer want to go on, all sheets are finished by making sure they end with an answer. Then, the folding opened up, so everyone can enjoy the amusing chains of questions and answers.
To play this game in Telegram chats, this bot can be added to any number of Telegram groups.
In each group, a game can be created (/newgame) and joined by multiple group members (/join).
Each player must also start a private chat with the bot.
When the game is started (/start_game), the bot asks every player privately for a question.
The player answer with their question and the bot passes it privatly to the next player.
If the next player is still working on his previous sheet, all incoming sheets are queued.
This way, a player may also play several games in parallel—they are still always asked for one sheet at a time.
The bot supports synchronous and asynchronous games:
In a synchronous game (default and /set_synchronous), the sheets are not passed on to the next player until all players have finished writing their question/answer.
In an asynchronous game, the sheets are immediately passed on to the next player—as long as they are not busy with another sheet.
When the game is finished—either when the target number of rounds (number of players or /set_rounds) is reached or when manually stopped (/stop_game, /immediately_stop_game)—, the virtual sheets are presented via a web server.
The bot is built on the SQLAlchemy ORM framework.
The object-relational datamodel is defined in qaqa_bot.model.
The full business logic is contained in qaqa_bot.game, encapsulated in the GameServer class.
An instance of this class holds the game config, a database sessionmaker to generate individual database sessions, as well as a way to send outgoing messages (in the form of a callback function).
It provides specific methods for all interaction events that update the game state in the database and send messages as required.
The interaction with Telegram is provided by the quqa_bot.bot module, using the Python Telegram Bot library.
Instances of its Frontend class hold an Updater object to interact with the Telegram API and an GameServer object to do the game logic.
The class has different handlers for any kind of Telegram update (esp. commands and text messages), that are automatically registered with the Updater on initialization and use the GameServer's interaction methods to carry out the actions.
In addition, a web server is included for serving the resulting sheets of finished games.
(We first tried to deliver them as messages to the group chat, which unfortunately triggered Telegrams flood prevention reproducibly.)
The web frontend is built with the CherryPy web framework and its included WSGI web server.
In the qaqa_bot.web module, the Controller classes with endpoint handlers are defined.
The HTML templates are rendered with Mako and are located in qaqa_bot/templates/.
Incoming updates from the Telegram API (esp. incoming messages) are handled either by the Frontend on its own or with help of the GameServer:
Typically, response messages that do not require interaction with the database, are sent by the Frontend immediately.
(It may use the GameServer's get_translations() or translate_string() methods to get the correct translation according to the chat's preferred language.)
In the other case, the Frontend's handler method identifies the correct game action, determines the action's arguments from the update data, and calls the respective method of the GameServer.
The response message/s are sent by the GameServer.
We use Alembic to manage database migrations.
To allow easy packaging and automatic migrations (see Deployment instructions below), the database versions are stored in qaqa_bot/database_versions/.
However, you can still use the alembic cli tool normally.
For running this bot, a Python 3 environment (>= Python 3.6) with the dependencies (see requirements.txt) installed is required.
It is recommended to use a virtualenv environment for easier management and updating of dependencies.
Additionally, a database in one of the DBMS supported by SQLAlchemy is required, including the appropriate Python driver library. See https://docs.sqlalchemy.org/en/13/dialects/index.html for a list of supported database systems and instructions.
For a small installation, development and testing, an SQLite database is sufficient, which can be run with Python's integrated SQLite support.
For this purpose, use sqlite:////path/to/your/database.db as database connection string in the bot's config.toml.
However, we recommend to use a proper™ database server for production use.
For the web frontend, an HTTP reverse proxy with HTTPS support should be configured, which makes the internal HTTP port publicly available.
Typically, one would chose Apache (with a ProxyPass directive) or Nginx (with a proxy_pass command) and configure a Let's Encrypt TLS certificate.
Currently, the easiest setup is to clone this Git Repository and run the qaqa_bot python module from within it.
We may add proper Python packaging later, to make installation via pip possible.
- clone and enter repository
git clone https://gitea.nephos.link/michael/QAQABot.git cd QAQABot/ - setup virtualenv
python3 -m virtualenv -p python3 venv
- install requirements
venv/bin/pip install -r requirements.txt
- create a Telegram Bot account: follow the instructions at https://core.telegram.org/bots#creating-a-new-bot
- create
config.tomlInsertcp config.example.toml config.toml $EDITOR config.toml- the bot's username,
- the bot's API token (recived from the BotFather),
- your personal Telegram username (will be used in the bot's description and help texts), and
- the connection URL of your database.
- the public base URL of your web server (virtual host), which is used for links to the web frontend
- the internal HTTP listening port
- compile i18n message catalouges
pybabel compile -d qaqa_bot/i18n/ -D qaqa_bot
Run the following command in the repository directory:
venv/bin/python -m qaqa_botAt startup, the database will be initialized or upgraded automatically.
Additionally, the Telegram bot will be configured using the Telegram API.
To avoid this behaviour, add --no-init to the run command.
To run the database and bot setup manually, use --init-only.
You may also run database migrations with Alembic for full control: alembic upgrade head.
Simply update the git repository, comple the new translations and restart the bot for updating:
git pull
venv/bin/pybabel compile -d qaqa_bot/i18n/ -D qaqa_bot
venv/bin/python -m qaqa_botAs explained above, the database and Telegram bot settings will be updated automatically at startup.
This project is released under the Terms of the Apache License v2.0. See NOTICE and LICENSE files for more
information.
Creating a new database version:
alembic upgrade head
# do changes to model.py
alembic revision --autogenerate -m "do data things"
# revisit qaqa_bot/database_versions/*_do_data_things.py
git add qaqa_bot/model.py qaqa_bot/database_versionsUpdating i18n translation files:
pybabel extract -F babel.cfg -k "GetText" -k "NGetText:1,2" -o qaqa_bot.pot .
pybabel update -i qaqa_bot.pot -d qaqa_bot/i18n/ -D qaqa_botCompiling i18n translation files:
pybabel compile -d qaqa_bot/i18n/ -D qaqa_bot
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