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421 lines
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ReStructuredText
421 lines
15 KiB
ReStructuredText
.. _full-api:
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============
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The Full API
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============
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.. important::
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While you have access to this, you should always use the friendly
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methods listed on :ref:`client-ref` unless you have a better reason
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not to, like a method not existing or you wanting more control.
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.. contents::
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Introduction
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============
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The :ref:`telethon-client` doesn't offer a method for every single request
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the Telegram API supports. However, it's very simple to *call* or *invoke*
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any request defined in Telegram's API.
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This section will teach you how to use what Telethon calls the `TL reference`_.
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The linked page contains a list and a way to search through *all* types
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generated from the definition of Telegram's API (in ``.tl`` file format,
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hence the name). These types include requests and constructors.
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.. note::
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The reason to keep both https://tl.telethon.dev and this
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documentation alive is that the former allows instant search results
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as you type, and a "Copy import" button. If you like namespaces, you
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can also do ``from telethon.tl import types, functions``. Both work.
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Telegram makes these ``.tl`` files public, which other implementations, such
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as Telethon, can also use to generate code. These files are versioned under
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what's called "layers". ``.tl`` files consist of thousands of definitions,
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and newer layers often add, change, or remove them. Each definition refers
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to either a Remote Procedure Call (RPC) function, or a type (which the
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`TL reference`_ calls "constructors", as they construct particular type
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instances).
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As such, the `TL reference`_ is a good place to go to learn about all possible
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requests, types, and what they look like. If you're curious about what's been
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changed between layers, you can refer to the `TL diff`_ site.
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Navigating the TL reference
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===========================
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Functions
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---------
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"Functions" is the term used for the Remote Procedure Calls (RPC) that can be
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sent to Telegram to ask it to perform something (e.g. "send message"). These
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requests have an associated return type. These can be invoked ("called"):
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.. code-block:: python
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client = TelegramClient(...)
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function_instance = SomeRequest(...)
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# Invoke the request
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returned_type = await client(function_instance)
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Whenever you find the type for a function in the `TL reference`_, the page
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will contain the following information:
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* What type of account can use the method. This information is regenerated
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from time to time (by attempting to invoke the function under both account
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types and finding out where it fails). Some requests can only be used by
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bot accounts, others by user accounts, and others by both.
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* The TL definition. This helps you get a feel for the what the function
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looks like. This is not Python code. It just contains the definition in
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a concise manner.
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* "Copy import" button. Does what it says: it will copy the necessary Python
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code to import the function to your system's clipboard for easy access.
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* Returns. The returned type. When you invoke the function, this is what the
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result will be. It also includes which of the constructors can be returned
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inline, to save you a click.
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* Parameters. The parameters accepted by the function, including their type,
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whether they expect a list, and whether they're optional.
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* Known RPC errors. A best-effort list of known errors the request may cause.
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This list is not complete and may be out of date, but should provide an
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overview of what could go wrong.
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* Example. Autogenerated example, showcasing how you may want to call it.
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Bear in mind that this is *autogenerated*. It may be spitting out non-sense.
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The goal of this example is not to show you everything you can do with the
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request, only to give you a feel for what it looks like to use it.
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It is very important to click through the links and navigate to get the full
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picture. A specific page will show you what the specific function returns and
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needs as input parameters. But it may reference other types, so you need to
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navigate to those to learn what those contain or need.
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Types
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-----
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"Types" as understood by TL are not actually generated in Telethon.
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They would be the "abstract base class" of the constructors, but since Python
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is duck-typed, there is hardly any need to generate mostly unnecessary code.
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The page for a type contains:
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* Constructors. Every type will have one or more constructors. These
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constructors *are* generated and can be immported and used.
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* Requests returning this type. A helpful way to find out "what requests can
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return this?". This is how you may learn what request you need to use to
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obtain a particular instance of a type.
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* Requests accepting this type as input. A helpful way to find out "what
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requests can use this type as one of their input parameters?". This is how
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you may learn where a type is used.
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* Other types containing this type. A helpful way to find out "where else
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does this type appear?". This is how you can walk back through nested
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objects.
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Constructors
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------------
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Constructors are used to create instances of a particular type, and are also
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returned when invoking requests. You will have to create instances yourself
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when invoking requests that need a particular type as input.
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The page for a constructor contains:
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* Belongs to. The parent type. This is a link back to the types page for the
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specific constructor. It also contains the sibling constructors inline, to
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save you a click.
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* Members. Both the input parameters *and* fields the constructor contains.
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Using the TL reference
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======================
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After you've found a request you want to send, a good start would be to simply
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copy and paste the autogenerated example into your script. Then you can simply
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tweak it to your needs.
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If you want to do it from scratch, first, make sure to import the request into
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your code (either using the "Copy import" button near the top, or by manually
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spelling out the package under ``telethon.tl.functions.*``).
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Then, start reading the parameters one by one. If the parameter cannot be
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omitted, you **will** need to specify it, so make sure to spell it out as
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an input parameter when constructing the request instance. Let's look at
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`PingRequest`_ for example. First, we copy the import:
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.. code-block:: python
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from telethon.tl.functions import PingRequest
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Then, we look at the parameters:
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ping_id - long
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A single parameter, and it's a long (a integer number with a large range of
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values). It doesn't say it can be omitted, so we must provide it, like so:
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.. code-block:: python
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PingRequest(
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ping_id=48641868471
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)
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(In this case, the ping ID is a random number. You often have to guess what
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the parameter needs just by looking at the name.)
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Now that we have our request, we can invoke it:
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.. code-block:: python
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response = await client(PingRequest(
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ping_id=48641868471
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))
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To find out what ``response`` looks like, we can do as the autogenerated
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example suggests and "stringify" the result as a pretty-printed string:
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.. code-block:: python
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print(result.stringify())
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This will print out the following:
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.. code-block:: python
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Pong(
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msg_id=781875678118,
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ping_id=48641868471
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)
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Which is a very easy way to get a feel for a response. You should nearly
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always print the stringified result, at least once, when trying out requests,
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to get a feel for what the response may look like.
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But of course, you don't need to do that. Without writing any code, you could
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have navigated through the "Returns" link to learn ``PingRequest`` returns a
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``Pong``, which only has one constructor, and the constructor has two members,
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``msg_id`` and ``ping_id``.
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If you wanted to create your own ``Pong``, you would use both members as input
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parameters:
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.. code-block:: python
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my_pong = Pong(
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msg_id=781875678118,
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ping_id=48641868471
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)
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(Yes, constructing object instances can use the same code that ``.stringify``
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would return!)
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And if you wanted to access the ``msg_id`` member, you would simply access it
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like any other attribute access in Python:
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.. code-block:: python
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print(response.msg_id)
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Example walkthrough
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===================
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Say `client.send_message()
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<telethon.client.messages.MessageMethods.send_message>` didn't exist,
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we could `use the search`_ to look for "message". There we would find
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:tl:`SendMessageRequest`, which we can work with.
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Every request is a Python class, and has the parameters needed for you
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to invoke it. You can also call ``help(request)`` for information on
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what input parameters it takes. Remember to "Copy import to the
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clipboard", or your script won't be aware of this class! Now we have:
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.. code-block:: python
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from telethon.tl.functions.messages import SendMessageRequest
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If you're going to use a lot of these, you may do:
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.. code-block:: python
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from telethon.tl import types, functions
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# We now have access to 'functions.messages.SendMessageRequest'
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We see that this request must take at least two parameters, a ``peer``
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of type :tl:`InputPeer`, and a ``message`` which is just a Python
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`str`\ ing.
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How can we retrieve this :tl:`InputPeer`? We have two options. We manually
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construct one, for instance:
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.. code-block:: python
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from telethon.tl.types import InputPeerUser
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peer = InputPeerUser(user_id, user_hash)
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Or we call `client.get_input_entity()
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<telethon.client.users.UserMethods.get_input_entity>`:
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.. code-block:: python
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import telethon
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async def main():
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peer = await client.get_input_entity('someone')
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client.loop.run_until_complete(main())
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.. note::
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Remember that ``await`` must occur inside an ``async def``.
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Every full API example assumes you already know and do this.
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When you're going to invoke an API method, most require you to pass an
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:tl:`InputUser`, :tl:`InputChat`, or so on, this is why using
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`client.get_input_entity() <telethon.client.users.UserMethods.get_input_entity>`
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is more straightforward (and often immediate, if you've seen the user before,
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know their ID, etc.). If you also **need** to have information about the whole
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user, use `client.get_entity() <telethon.client.users.UserMethods.get_entity>`
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instead:
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.. code-block:: python
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entity = await client.get_entity('someone')
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In the later case, when you use the entity, the library will cast it to
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its "input" version for you. If you already have the complete user and
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want to cache its input version so the library doesn't have to do this
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every time its used, simply call `telethon.utils.get_input_peer`:
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.. code-block:: python
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from telethon import utils
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peer = utils.get_input_peer(entity)
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.. note::
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Since ``v0.16.2`` this is further simplified. The ``Request`` itself
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will call `client.get_input_entity
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<telethon.client.users.UserMethods.get_input_entity>` for you when
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required, but it's good to remember what's happening.
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After this small parenthesis about `client.get_entity
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<telethon.client.users.UserMethods.get_entity>` versus
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`client.get_input_entity() <telethon.client.users.UserMethods.get_input_entity>`,
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we have everything we need. To invoke our
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request we do:
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.. code-block:: python
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result = await client(SendMessageRequest(peer, 'Hello there!'))
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Message sent! Of course, this is only an example. There are over 250
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methods available as of layer 80, and you can use every single of them
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as you wish. Remember to use the right types! To sum up:
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.. code-block:: python
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result = await client(SendMessageRequest(
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await client.get_input_entity('username'), 'Hello there!'
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))
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This can further be simplified to:
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.. code-block:: python
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result = await client(SendMessageRequest('username', 'Hello there!'))
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# Or even
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result = await client(SendMessageRequest(PeerChannel(id), 'Hello there!'))
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.. note::
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Note that some requests have a "hash" parameter. This is **not**
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your ``api_hash``! It likely isn't your self-user ``.access_hash`` either.
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It's a special hash used by Telegram to only send a difference of new data
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that you don't already have with that request, so you can leave it to 0,
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and it should work (which means no hash is known yet).
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For those requests having a "limit" parameter, you can often set it to
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zero to signify "return default amount". This won't work for all of them
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though, for instance, in "messages.search" it will actually return 0 items.
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Requests in Parallel
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====================
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The library will automatically merge outgoing requests into a single
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*container*. Telegram's API supports sending multiple requests in a
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single container, which is faster because it has less overhead and
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the server can run them without waiting for others. You can also
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force using a container manually:
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.. code-block:: python
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async def main():
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# Letting the library do it behind the scenes
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await asyncio.wait([
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client.send_message('me', 'Hello'),
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client.send_message('me', ','),
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client.send_message('me', 'World'),
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client.send_message('me', '.')
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])
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# Manually invoking many requests at once
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await client([
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SendMessageRequest('me', 'Hello'),
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SendMessageRequest('me', ', '),
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SendMessageRequest('me', 'World'),
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SendMessageRequest('me', '.')
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])
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Note that you cannot guarantee the order in which they are run.
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Try running the above code more than one time. You will see the
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order in which the messages arrive is different.
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If you use the raw API (the first option), you can use ``ordered``
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to tell the server that it should run the requests sequentially.
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This will still be faster than going one by one, since the server
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knows all requests directly:
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.. code-block:: python
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await client([
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SendMessageRequest('me', 'Hello'),
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SendMessageRequest('me', ', '),
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SendMessageRequest('me', 'World'),
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SendMessageRequest('me', '.')
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], ordered=True)
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If any of the requests fails with a Telegram error (not connection
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errors or any other unexpected events), the library will raise
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`telethon.errors.common.MultiError`. You can ``except`` this
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and still access the successful results:
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.. code-block:: python
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from telethon.errors import MultiError
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try:
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await client([
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SendMessageRequest('me', 'Hello'),
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SendMessageRequest('me', ''),
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SendMessageRequest('me', 'World')
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], ordered=True)
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except MultiError as e:
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# The first and third requests worked.
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first = e.results[0]
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third = e.results[2]
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# The second request failed.
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second = e.exceptions[1]
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.. _TL reference: https://tl.telethon.dev
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.. _TL diff: https://diff.telethon.dev
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.. _PingRequest: https://tl.telethon.dev/methods/ping.html
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.. _use the search: https://tl.telethon.dev/?q=message&redirect=no
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