Storage Engines#

Every time you login to Telegram, some personal piece of data are created and held by both parties (the client, Pyrogram 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, Pyrogram needs to store the generated session data somewhere.

Different Storage Engines#

Pyrogram 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 Pyrogram 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.

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 Pyrogram clients on platforms where their ephemeral filesystems makes it harder for a file-based storage engine to properly work as intended.

Custom Storages#

If you want to use a custom storage engine, you can do so by implementing the Storage class. This class is an base class that defines the interface that all storage engines must implement.

This class is a class that cannot be instantiated, but can be used to define a common interface for its subclasses. In this case, the Storage class defines the interface that all storage engines must implement.

Custom Storage can be defined in Client by passing storage_engine parameter with a Storage subclass.

Example of File Storage (using `aiosqlite==0.20.0`)#

How to use this Storage Engine is shown below.

This storage is almost completely identical to the default File Storage, but instead has an extra dependency required to run it.

/path/to/your/file.session will be created if does not exist.

from pyrogram import Client
from pyrogram.storage.aio_sqlite_storage import AioSQLiteStorage

async with Client(
    "my_account",
    storage_engine=AioSQLiteStorage("/path/to/your/file.session")
) as app:
    await app.send_message(chat_id="me", text="Greetings from **Pyrogram**!")

Example of Telethon Storage#

If you want to use sessions from telethon in pyrogram (originally incompatible), you can use this storage.

This storage is almost completely identical and once used in pyrogram can be reused in telethon without breaking session integrity.

from pyrogram import Client
from .tele_storage import TelethonStorage  # assumes that the path downloaded is accurate

workdir = Path(__file__).parent
test_mode = False
is_bot = False # Pass True if your session is bot session

async with Client(
    "my_account",
    api_id=api_id,
    api_hash=api_hash,
    lang_code="ru",
    workdir=workdir,
    test_mode=test_mode,
    storage_engine=TelethonStorage(
        name="my_account",
        workdir=workdir,
        api_id=api_id,
        test_mode=test_mode,
        is_bot=is_bot
    )
) as app:
    await app.send_message(chat_id="me", text="Greetings from **Pyrogram**!")