An example to demonstrate how custom filters work is to show how to create and use one for the
CallbackQueryHandler. Note that callback queries updates are only received by bots as result
of a user pressing an inline button attached to the bot’s message; create and authorize your bot,
then send a message with an inline keyboard to yourself. This allows you to test your filter by pressing the inline
from pyrogram.types import InlineKeyboardMarkup, InlineKeyboardButton await app.send_message( "username", # Change this to your username or id "Pyrogram custom filter test", reply_markup=InlineKeyboardMarkup( [[InlineKeyboardButton("Press me", "pyrogram")]] ) )
For this basic filter we will be using only the first parameter of
The heart of a filter is its callback function, which accepts three arguments (self, client, update) and returns
True, in case you want the update to pass the filter or
In this example we are matching the query data to “pyrogram”, which means that the filter will only allow callback queries containing “pyrogram” as data:
from pyrogram import filters async def func(_, __, query): return query.data == "pyrogram" static_data_filter = filters.create(func)
The first two arguments of the callback function are unused here and because of this we named them using underscores.
Finally, the filter usage remains the same:
@app.on_callback_query(static_data_filter) async def pyrogram_data(_, query): query.answer("it works!")
Filters with Arguments#
A more flexible filter would be one that accepts “pyrogram” or any other string as argument at usage time.
A dynamic filter like this will make use of named arguments for the
create() method and the
first argument of the callback function, which is a reference to the filter object itself holding the extra data passed
via named arguments.
This is how a dynamic custom filter looks like:
from pyrogram import filters def dynamic_data_filter(data): async def func(flt, _, query): return flt.data == query.data # "data" kwarg is accessed with "flt.data" above return filters.create(func, data=data)
And finally its usage:
@app.on_callback_query(dynamic_data_filter("pyrogram")) async def pyrogram_data(_, query): query.answer("it works!")
Method Calls Inside Filters#
The missing piece we haven’t covered yet is the second argument of a filter callback function, namely, the
argument. This is a reference to the
Client instance that is running the filter and it is useful in
case you would like to make some API calls before deciding whether the filter should allow the update or not:
async def func(_, client, query): # r = await client.some_api_method() # check response "r" and decide to return True or False ...