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SQLAlchemy backend for Telethon session storage

Project description

A Telethon session storage implementation backed by SQLAlchemy.

Installation

telethon-session-sqlalchemy @ PyPI

pip install telethon-session-sqlalchemy

Usage

This session implementation can store multiple Sessions in the same database, but to do this, each session instance needs to have access to the same models and database session.

To get started, you need to create an AlchemySessionContainer which will contain that shared data. The simplest way to use AlchemySessionContainer is to simply pass it the database URL:

from alchemysession import AlchemySessionContainer
container = AlchemySessionContainer('postgres://user:pass@localhost/telethon')

If you already have SQLAlchemy set up for your own project, you can also pass the engine separately:

my_sqlalchemy_engine = sqlalchemy.create_engine('...')
container = AlchemySessionContainer(engine=my_sqlalchemy_engine)

By default, the session container will manage table creation/schema updates/etc automatically. If you want to manage everything yourself, you can pass your SQLAlchemy Session and declarative_base instances and set manage_tables to False:

from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import orm
import sqlalchemy
...
session_factory = orm.sessionmaker(bind=my_sqlalchemy_engine)
session = session_factory()
my_base = declarative_base()
...
container = AlchemySessionContainer(
    session=session, table_base=my_base, manage_tables=False
)

You always need to provide either engine or session to the container. If you set manage_tables=False and provide a session, engine is not needed. In any other case, engine is always required.

After you have your AlchemySessionContainer instance created, you can create new sessions by calling new_session:

session = container.new_session('some session id')
client = TelegramClient(session)

where some session id is an unique identifier for the session.

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