Storage Engines¶

Every time you login to Telegram, some personal piece of data are created and held by both parties (the client, Pyrofork and the server, Telegram). This session data is uniquely bound to your own account, indefinitely (until you logout or decide to manually terminate it) and is used to authorize a client to execute API calls on behalf of your identity.

Persisting Sessions¶

In order to make a client reconnect successfully between restarts, that is, without having to start a new authorization process from scratch each time, Pyrofork needs to store the generated session data somewhere.

Different Storage Engines¶

Pyrofork offers two different types of storage engines: a File Storage and a Memory Storage. These engines are well integrated in the framework and require a minimal effort to set up. Here’s how they work:

File Storage¶

This is the most common storage engine. It is implemented by using SQLite, which will store the session details. The database will be saved to disk as a single portable file and is designed to efficiently store and retrieve data whenever they are needed.

To use this type of engine, simply pass any name of your choice to the name parameter of the Client constructor, as usual:

from pyrogram import Client

async with Client("my_account") as app:
    print(await app.get_me())

Once you successfully log in (either with a user or a bot identity), a session file will be created and saved to disk as my_account.session. Any subsequent client restart will make Pyrofork search for a file named that way and the session database will be automatically loaded.

Memory Storage¶

In case you don’t want to have any session file saved to disk, you can use an in-memory storage by passing True to the in_memory parameter of the Client constructor:

from pyrogram import Client

async with Client("my_account", in_memory=True) as app:
    print(await app.get_me())

This storage engine is still backed by SQLite, but the database exists purely in memory. This means that, once you stop a client, the entire database is discarded and the session details used for logging in again will be lost forever.

Mongodb Storage¶

In case you want to have persistent session but you don’t have persistent storage you can use mongodb storage by passing mongodb config as dict to the mongodb parameter of the Client constructor:

Using async_pymongo (Recommended for python3.9+):

from async_pymongo import AsyncClient
from pyrogram import Client

conn = AsyncClient("mongodb://...")

async with Client("my_account", mongodb=dict(connection=conn, remove_peers=False)) as app:
    print(await app.get_me())

Using motor:

from motor.motor_asyncio import AsyncIOMotorClient
from pyrogram import Client

conn = AsyncIOMotorClient("mongodb://...")

async with Client("my_account", mongodb=dict(connection=conn, remove_peers=False)) as app:
    print(await app.get_me())

This storage engine is backed by MongoDB, a session will be created and saved to mongodb database. Any subsequent client restart will make PyroFork search for a database named that way and the session database will be automatically loaded.

Session Strings¶

In case you want to use an in-memory storage, but also want to keep access to the session you created, call export_session_string() anytime before stopping the client…

from pyrogram import Client

async with Client("my_account", in_memory=True) as app:
    print(await app.export_session_string())

…and save the resulting string. You can use this string by passing it as Client argument the next time you want to login using the same session; the storage used will still be in-memory:

from pyrogram import Client

session_string = "...ZnUIFD8jsjXTb8g_vpxx48k1zkov9sapD-tzjz-S4WZv70M..."

async with Client("my_account", session_string=session_string) as app:
    print(await app.get_me())

Session strings are useful when you want to run authorized Pyrofork clients on platforms where their ephemeral filesystems makes it harder for a file-based storage engine to properly work as intended.