[](https://pypi.org/project/taskiq/)
[](https://pypi.org/project/taskiq/)
[](https://pypistats.org/packages/taskiq)
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<a href="https://taskiq-python.github.io/"><img src="https://raw.githubusercontent.com/taskiq-python/taskiq/master/imgs/logo.svg" width=600></a>
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Documentation: https://taskiq-python.github.io/
## What is taskiq?
Taskiq is an asynchronous distributed task queue for python.
This project takes inspiration from big projects such as [Celery](https://docs.celeryq.dev) and [Dramatiq](https://dramatiq.io/).
But taskiq can send and run both the sync and async functions, has
integration with popular async frameworks, such as [FastAPI](https://fastapi.tiangolo.com/) and [AioHTTP](https://docs.aiohttp.org/en/stable/).
Also, we use [PEP-612](https://peps.python.org/pep-0612/) to provide the best autosuggestions possible. All code is type-hinted.
# Installation
This project can be installed using pip:
```bash
pip install taskiq
```
Or it can be installed directly from git:
```bash
pip install git+https://github.com/taskiq-python/taskiq
```
# Usage
At first you need to create a broker. Broker is an object that can communicate to workers using distributed queues.
We have differet brokers for different queue backends. For example, we have a broker for [NATS](https://github.com/taskiq-python/taskiq-nats), [Redis](https://github.com/taskiq-python/taskiq-redis), [RabbitMQ](https://github.com/taskiq-python/taskiq-aio-pika), [Kafka](https://github.com/taskiq-python/taskiq-aio-kafka) and even more. Choose the one that fits you and create an instance.
```python
from taskiq_nats import JetStreamBroker
broker = JetStreamBroker("nats://localhost:4222", queue="my_queue")
```
Declaring tasks is as easy as declaring a function. Just add a decorator to your function and you are ready to go.
```python
import asyncio
from taskiq_nats import JetStreamBroker
broker = JetStreamBroker("nats://localhost:4222", queue="my_queue2")
@broker.task
async def my_task(a: int, b: int) -> None:
print("AB", a + b)
async def main():
await broker.startup()
await my_task.kiq(1, 2)
await broker.shutdown()
if __name__ == "__main__":
asyncio.run(main())
```
The message is going to be sent to the broker and then to the worker. The worker will execute the function. To start worker processes, just run the following command:
```bash
taskiq worker path.to.the.module:broker
```
Where `path.to.the.module` is the path to the module where the broker is defined and `broker` is the name of the broker variable.
If you have tasks in different modules, you can ask taskiq to automatically import them by passing the `--fs-discover` flag:
```bash
taskiq worker path.to.the.module:broker --fs-discover
```
It will import all modules called `tasks.py` in the current directory and all subdirectories.
Also, we support hot reload for workers. To enable it, just pass the `--reload` flag. It will reload the worker when the code changes (To use it, install taskiq with reload extra. E.g `pip install taskiq[reload]`).
Also, we have cool integrations with popular async frameworks. For example, we have an integration with [FastAPI](https://taskiq-python.github.io/framework_integrations/taskiq-with-fastapi.html) or [AioHTTP](https://taskiq-python.github.io/framework_integrations/taskiq-with-aiohttp.html). You can use it to reuse dependencies from your web app in your tasks.
Read about all features in our documentation: https://taskiq-python.github.io/
# Local development
## Linting
We use pre-commit to do linting locally.
After cloning this project, please install [pre-commit](https://pre-commit.com/#install). It helps fix files before committing changes.
```bash
pre-commit install
```
## Testing
Pytest can run without any additional actions or options.
```bash
pytest
```
## Docs
To run docs locally, you need to install [yarn](https://yarnpkg.com/getting-started/install).
First, you need to install dependencies.
```
yarn install
```
After that you can set up a docs server by running:
```
yarn docs:dev
```
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