https://github.com/txello/qtasks
Asynchronous Queue Tasks
https://github.com/txello/qtasks
framework kafka python python-framework python-library queue rabbitmq redis task-manager task-queue task-scheduler
Last synced: about 1 month ago
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Asynchronous Queue Tasks
- Host: GitHub
- URL: https://github.com/txello/qtasks
- Owner: txello
- License: apache-2.0
- Created: 2025-02-19T18:38:29.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-12-04T07:32:26.000Z (3 months ago)
- Last Synced: 2025-12-07T08:33:21.485Z (3 months ago)
- Topics: framework, kafka, python, python-framework, python-library, queue, rabbitmq, redis, task-manager, task-queue, task-scheduler
- Language: Python
- Homepage: https://txello.github.io/qtasks/
- Size: 3.51 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# QTasks
[](https://pepy.tech/projects/qtasks)
**QTasks** is a modern task queue framework for Python with a component-based
architecture and a focus on extensibility, transparency, and control over task execution.
The project is aimed at both small services and complex distributed systems
where standard solutions are redundant or inflexible.
---
## Key features
* **Component-based architecture**
Broker, Worker, Storage, GlobalConfig, Starter — each component is isolated and
fully replaceable.
* **Async and Sync tasks**
Support for `asyncio`, synchronous functions, and generators.
* **Plugins instead of rigid logic**
Retry, concurrency, logging, and execution strategies are implemented
through plugins.
* **Typed data flow**
Data transfer between components via schemas (`dataclasses`).
* **Transparent testing**
In-memory brokers and storages, component isolation, tests without running workers.
* **CLI-first approach**
Manage startup and environment through CLI without hidden magic.
---
## When to choose QTasks
* You need full control over the queue architecture.
* You need to write your own brokers, workers, and plugins.
* Predictable behavior and minimalism of the core are important.
* The project is growing and requires scalability without rewriting the logic.
---
## Installation
### Basic installation (Redis by default)
```bash
pip install qtasks
```
### Additional brokers
#### RabbitMQ
```bash
pip install qtasks[rabbitmq]
```
#### Kafka
```bash
pip install qtasks[kafka]
```
---
## Quick start
```python
from qtasks import QueueTasks
app = QueueTasks()
@app.task(name="echo")
def echo(text: str) -> str:
return text
@app.task(name="divide")
def divide(a: int, b: int):
return a / b
if __name__ == "__main__":
app.run_forever()
```
Calling tasks:
```python
# echo.add_task("Hello", timeout=50).returning -> "Hello"
# divide.add_task(1, 0, timeout=50).status -> "ERROR"
```
---
## Generators and streaming tasks
QTasks supports generator tasks without additional wrappers:
```python
async def gen_handler(value: int) -> int:
return value + 1
@app.task(generate_handler=gen_handler)
async def counter(n: int):
for _ in range(n):
n += 1
yield n
```
Result of execution:
```python
# await (counter.add_task(5, timeout=50)).returning -> [7, 8, 9, 10, 11]
```
---
## CLI
Starting the worker:
```bash
qtasks -A qtasks_app:app run
```
Or directly:
```bash
python -m qtasks -A qtasks_app:app run
```
In the future, the CLI will be expanded (inspect, stats, monitoring).
---
## Architecture (briefly)
```md
┌──────────┐ ┌──────────┐
│ Broker │ ───────▶ │ │
│ │ │ │
└────┬─────┘ │ │
│ │ Storage │
▼ │ │
┌──────────┐ ───────▶ │ │
│ Worker │ │ │
│ │ └──────────┘
└──────────┘
```
Additionally:
* plugins;
* routers;
* background components;
* WebView (optional).
---
## Documentation
👉 [https://docs.qtasks.tech](https://docs.qtasks.tech)
---
## Project status
* Active development
* Stable versions
* Python 3.8–3.12
* Open to contributions
---
## License
MIT License