A sane Discord API for Python 3 built on asyncio and good intentions
An opinionated, static typed Discord microframework for Python3 and asyncio that supports Discord's V8 REST API and Gateway.
Built on good intentions and the hope that it will be extendable and reusable, rather than an obstacle for future development.
import hikari bot = hikari.BotApp(token="...") @bot.listen() async def ping(event: hikari.GuildMessageCreateEvent) -> None: # If a non-bot user sends a message "hk.ping", respond with "Pong!" # We check there is actually content first, if no message content exists, # we would get `None' here. if event.is_bot or not event.content: return if event.content.startswith("hk.ping"): await event.message.reply("Pong!") bot.run()
This will only respond to messages created in guilds. You can use
instead to only listen on DMs, or
MessageCreateEvent to listen to both DMs and guild-based
Logging will be automatically configured for you if you do not enable it manually. This has been implemented after seeing a large number of new bot developers struggle with writing their first bot in other frameworks simply because of working blind after not understanding or knowing how to set up standard logging messages.
If you wish to customise the intents being used in order to change which events your bot
is notified about, then you can pass the
intents kwarg to the
# the default is to enable all unprivileged intents (all events that do not target the # presence or activity of a specific member). bot = hikari.BotApp(intents=hikari.Intents.ALL, token="...")
The above example would enable all intents, thus enabling events relating to member presences to be received (you'd need to whitelist your application first to be able to start the bot if you do this). Other options also exist such as customising timeouts for requests and enabling a proxy.
Also note that you could pass extra options to
bot.run during development, for example:
bot.run( asyncio_debug=True, # enable asyncio debug to detect blocking and slow code. coroutine_tracking_depth=20, # enable tracking of coroutines, makes some asyncio # errors clearer. propagate_interrupts=True, # Any OS interrupts get rethrown as errors. )
Many other helpful options exist for you to take advantage of if you wish.
Events are determined by the type annotation on the event parameter, or
alternatively as a type passed to the
@bot.listen() decorator, if you do not
want to use type hints.
@bot.listen(hikari.MessageCreateEvent) async def ping(event): ...
You may only want to integrate with the REST API, for example if writing a web dashboard.
This is relatively simple to do:
rest = hikari.RESTApp() async def print_my_user(token): # We acquire a client with a given token. This allows one REST app instance # with one internal connection pool to be reused. async with rest.acquire(token) as client: my_user = await client.fetch_my_user() print(my_user) asyncio.run(print_my_user("user token here"))
This client has been designed to be able to work in compliment with existing
OAuth2 client implementations, such as
Install hikari from PyPI with the following command:
python -m pip install hikari -U --pre # Windows users may need to run this instead... py -3 -m pip install hikari -U --pre
You may wish to use a command framework on top of Hikari so that you can start writing a bot quickly without implementing your own command handler.
Hikari does not include a command framework by default, so you will want to pick a third party library to do it.
lightbulb- a simple and easy to use command framework for Hikari.
Making your application more efficient
As your application scales, you may need to adjust some things to keep it performing nicely.
Python optimisation flags
CPython and Stackless Python provide two optimisation flags that remove internal safety checks that are useful for development, and change other internal settings in the interpreter.
python bot.py- no optimisation - this is the default.
python -O bot.py- first level optimisation - features such as internal assertions will be disabled.
python -OO bot.py- second level optimisation - more features (including all docstrings) will be removed from the loaded code at runtime.
If you have a C compiler (Microsoft VC++ Redistributable 14.0 or newer, or a
modern copy of GCC/G++, Clang, etc), you can install hikari using
pip install -U hikari[speedups]. This will install
ciso8601, which will provide you with a small performance boost.
If you use Linux, you will get additional performance benefits from using
a library called
uvloop. This replaces the default
asyncio event loop with
one that uses
libuv internally. You can run
pip install uvloop and then
amend your script to be something similar to the following example to utilise it
in your application:
import os import hikari if os.name != "nt": import uvloop uvloop.install() bot = hikari.Bot(...) ...
Eventually, we will start providing the option to use compiled components of this library over pure Python ones if it suits your use case. This should also enable further scalability of your application, should PEP 554 -- Multiple Interpreters in the Stdlib be accepted.
Currently, this functionality does not yet exist.
If you wish to contribute something, you should first start by cloning the repository.
In the repository, make a virtual environment (
python -m venv .venv) and enter
source .venv/bin/activate on Linux, or for Windows use one of
The first thing you should run is
pip install nox to install nox. This handles
running predefined tasks and pipelines.
You can install any dependencies with
pip install -r requirements.txt -r dev-requirements.txt.
Once this is complete, you can run
nox without any arguments to ensure
everything builds and is correct.
Where can I start?
Check out the issues tab on GitHub. If you are nervous, look for issues marked as "good first issue" for something easy to start with!
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